how to explain related studies in research

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How to Write Review of Related Literature (RRL) in Research

A review of related literature (a.k.a RRL in research) is a comprehensive review of the existing literature pertaining to a specific topic or research question. An effective review provides the reader with an organized analysis and synthesis of the existing knowledge about a subject. With the increasing amount of new information being disseminated every day, conducting a review of related literature is becoming more difficult and the purpose of review of related literature is clearer than ever.  

All new knowledge is necessarily based on previously known information, and every new scientific study must be conducted and reported in the context of previous studies. This makes a review of related literature essential for research, and although it may be tedious work at times , most researchers will complete many such reviews of varying depths during their career. So, why exactly is a review of related literature important?    

Table of Contents

Why a review of related literature in research is important  

Before thinking how to do reviews of related literature , it is necessary to understand its importance. Although the purpose of a review of related literature varies depending on the discipline and how it will be used, its importance is never in question. Here are some ways in which a review can be crucial.  

• Identify gaps in the knowledge – This is the primary purpose of a review of related literature (often called RRL in research ). To create new knowledge, you must first determine what knowledge may be missing. This also helps to identify the scope of your study.  
• Avoid duplication of research efforts – Not only will a review of related literature indicate gaps in the existing research, but it will also lead you away from duplicating research that has already been done and thus save precious resources.  
• Provide an overview of disparate and interdisciplinary research areas – Researchers cannot possibly know everything related to their disciplines. Therefore, it is very helpful to have access to a review of related literature already written and published.  
• Highlight researcher’s familiarity with their topic 1  – A strong review of related literature in a study strengthens readers’ confidence in that study and that researcher.

Tips on how to write a review of related literature in research

Given that you will probably need to produce a number of these at some point, here are a few general tips on how to write an effective review of related literature 2 .

• Define your topic, audience, and purpose: You will be spending a lot of time with this review, so choose a topic that is interesting to you. While deciding what to write in a review of related literature , think about who you expect to read the review – researchers in your discipline, other scientists, the general public – and tailor the language to the audience. Also, think about the purpose of your review of related literature .  
• Conduct a comprehensive literature search: While writing your review of related literature , emphasize more recent works but don’t forget to include some older publications as well. Cast a wide net, as you may find some interesting and relevant literature in unexpected databases or library corners. Don’t forget to search for recent conference papers.
• Review the identified articles and take notes: It is a good idea to take notes in a way such that individual items in your notes can be moved around when you organize them. For example, index cards are great tools for this. Write each individual idea on a separate card along with the source. The cards can then be easily grouped and organized.  
• Determine how to organize your review: A review of related literature should not be merely a listing of descriptions. It should be organized by some criterion, such as chronologically or thematically.  
• Be critical and objective: Don’t just report the findings of other studies in your review of related literature . Challenge the methodology, find errors in the analysis, question the conclusions. Use what you find to improve your research. However, do not insert your opinions into the review of related literature. Remain objective and open-minded.  
• Structure your review logically: Guide the reader through the information. The structure will depend on the function of the review of related literature. Creating an outline prior to writing the RRL in research is a good way to ensure the presented information flows well.  

As you read more extensively in your discipline, you will notice that the review of related literature appears in various forms in different places. For example, when you read an article about an experimental study, you will typically see a literature review or a RRL in research , in the introduction that includes brief descriptions of similar studies. In longer research studies and dissertations, especially in the social sciences, the review of related literature will typically be a separate chapter and include more information on methodologies and theory building. In addition, stand-alone review articles will be published that are extremely useful to researchers.  

The review of relevant literature or often abbreviated as, RRL in research , is an important communication tool that can be used in many forms for many purposes. It is a tool that all researchers should befriend.  

• University of North Carolina at Chapel Hill Writing Center. Literature Reviews.  https://writingcenter.unc.edu/tips-and-tools/literature-reviews/  [Accessed September 8, 2022]
• Pautasso M. Ten simple rules for writing a literature review. PLoS Comput Biol. 2013, 9. doi: 10.1371/journal.pcbi.1003149.

Q:  Is research complete without a review of related literature?

A research project is usually considered incomplete without a proper review of related literature. The review of related literature is a crucial component of any research project as it provides context for the research question, identifies gaps in existing literature, and ensures novelty by avoiding duplication. It also helps inform research design and supports arguments, highlights the significance of a study, and demonstrates your knowledge an expertise.

Q: What is difference between RRL and RRS?

The key difference between an RRL and an RRS lies in their focus and scope. An RRL or review of related literature examines a broad range of literature, including theoretical frameworks, concepts, and empirical studies, to establish the context and significance of the research topic. On the other hand, an RRS or review of research studies specifically focuses on analyzing and summarizing previous research studies within a specific research domain to gain insights into methodologies, findings, and gaps in the existing body of knowledge. While there may be some overlap between the two, they serve distinct purposes and cover different aspects of the research process.

Q: Does review of related literature improve accuracy and validity of research?

Yes, a comprehensive review of related literature (RRL) plays a vital role in improving the accuracy and validity of research. It helps authors gain a deeper understanding and offers different perspectives on the research topic. RRL can help you identify research gaps, dictate the selection of appropriate research methodologies, enhance theoretical frameworks, avoid biases and errors, and even provide support for research design and interpretation. By building upon and critically engaging with existing related literature, researchers can ensure their work is rigorous, reliable, and contributes meaningfully to their field of study.

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How to refer to other studies or literature in the different sections of a research paper

By charlesworth author services.

• Charlesworth Author Services
• 07 October, 2021

There are many articles which discuss how you can include and discuss existing studies and research in the literature review section of a paper. However, in addition to the literature review , there are many other opportunities to discuss or engage with prior studies in your research. This article offers guidance on how to include other studies or literature in different sections in a research paper.

Engaging with literature in the Introduction

Prior studies are often mentioned in the Introduction , generally as high-level summaries without much detail. Although some people may choose not to use existing literature or research to motivate a study, this is not an uncommon practice. Researchers sometimes rely on prior studies to emphasise the importance of the current study – for example, in challenging a standing argument or addressing an outstanding gap . Prior studies are also often discussed to build the foundation of the arguments of the research paper in question. 

Working with previous studies in the Methodology

It is also common practice to refer to prior literature in the Methodology. You may refer to prior studies as you design the study, collect and/or select data and perform the analysis. If this is the case, it is important to explain clearly why you are using and drawing from previous studies and how these are relevant to your own research paper. 

It is also possible to refer to prior studies to highlight the different methodological choices you have taken in your research. For example, there may be a comparison of the data sources, the sample or subject selections. Or, you might offer a comparison in the decisions made for different parameters, constructs, factors, model selection preferences and so on. Highlighting these differences can help you to clearly present new perspectives and why your study provides value to the field.

If you are offering a comparison between your current and previous studies, try to avoid solely comparing and contrasting, or simply stating what you have performed. What is more important is to explain why you have made these different decisions so that readers can understand the rationale behind your methodological decisions and your project design .

Referring to the literature in the Discussion and Conclusion

It is always a good idea to refer to prior studies and existing literature in the Discussion or Conclusion sections. This is a good time to reiterate the arguments, research questions/hypotheses and objectives that you introduced in the earlier sections of the paper and to discuss your results and findings .

Integrating other relevant literature into your Discussion serves two key purposes . First, it outlines what has already been achieved in prior studies. Second, you can explain how your study builds on this existing work to advance the knowledge in the field . 

Sometimes, through this discussion, you can also demonstrate why or how your findings are the same as or different from prior studies. 

Three common mistakes to avoid

When forging connections between prior studies and your own research paper, it is important to be aware of three common mistakes that authors make.

• Some researchers sometimes focus too much on the existing literature , so that their research paper does not, ultimately, seem to provide many new insights. 
• Because of the way authors might present and discuss prior studies in the Introduction, readers may become distracted or be led to raise more questions that are not relevant to the present research paper. [ Tip : In this and the above instances, it is advisable that you ensure your discussion of the literature is relevant at all times to the specific issues that you are discussing in each section and does not overshadow the main idea(s) in the research paper.]
• Although you can critique prior studies to highlight the unique approach or key message of your study, it is a good practice to avoid subjective assessments, so as not to introduce any personal biases into your discussion of either the literature or your own research. 

In conclusion

Remember that engagement with the literature serves primarily to set the scene and contextualise your own research . It should provide enough information for your reader to understand the relevance and significance of your study, but not take over the main focus of the paper.

Read next (fifth/final) in series: Difference between a literature review and a critical review

Read previous (third) in series: Deciding what to include and exclude as you begin to write your literature review

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• USC Libraries
• Research Guides

Organizing Your Social Sciences Research Paper

• 5. The Literature Review
• 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
• Avoiding Plagiarism
• Footnotes or Endnotes?
• Further Readings
• Generative AI and Writing
• USC Libraries Tutorials and Other Guides
• Bibliography

A literature review surveys prior research published in books, scholarly articles, and any other sources relevant to a particular issue, area of research, or theory, and by so doing, provides a description, summary, and critical evaluation of these works in relation to the research problem being investigated. Literature reviews are designed to provide an overview of sources you have used in researching a particular topic and to demonstrate to your readers how your research fits within existing scholarship about the topic.

Fink, Arlene. Conducting Research Literature Reviews: From the Internet to Paper . Fourth edition. Thousand Oaks, CA: SAGE, 2014.

Importance of a Good Literature Review

A literature review may consist of simply a summary of key sources, but in the social sciences, a literature review usually has an organizational pattern and combines both summary and synthesis, often within specific conceptual categories . A summary is a recap of the important information of the source, but a synthesis is a re-organization, or a reshuffling, of that information in a way that informs how you are planning to investigate a research problem. The analytical features of a literature review might:

• Give a new interpretation of old material or combine new with old interpretations,
• Trace the intellectual progression of the field, including major debates,
• Depending on the situation, evaluate the sources and advise the reader on the most pertinent or relevant research, or
• Usually in the conclusion of a literature review, identify where gaps exist in how a problem has been researched to date.

Given this, the purpose of a literature review is to:

• Place each work in the context of its contribution to understanding the research problem being studied.
• Describe the relationship of each work to the others under consideration.
• Identify new ways to interpret prior research.
• Reveal any gaps that exist in the literature.
• Resolve conflicts amongst seemingly contradictory previous studies.
• Identify areas of prior scholarship to prevent duplication of effort.
• Point the way in fulfilling a need for additional research.
• Locate your own research within the context of existing literature [very important].

Fink, Arlene. Conducting Research Literature Reviews: From the Internet to Paper. 2nd ed. Thousand Oaks, CA: Sage, 2005; Hart, Chris. Doing a Literature Review: Releasing the Social Science Research Imagination . Thousand Oaks, CA: Sage Publications, 1998; Jesson, Jill. Doing Your Literature Review: Traditional and Systematic Techniques . Los Angeles, CA: SAGE, 2011; Knopf, Jeffrey W. "Doing a Literature Review." PS: Political Science and Politics 39 (January 2006): 127-132; Ridley, Diana. The Literature Review: A Step-by-Step Guide for Students . 2nd ed. Los Angeles, CA: SAGE, 2012.

Types of Literature Reviews

It is important to think of knowledge in a given field as consisting of three layers. First, there are the primary studies that researchers conduct and publish. Second are the reviews of those studies that summarize and offer new interpretations built from and often extending beyond the primary studies. Third, there are the perceptions, conclusions, opinion, and interpretations that are shared informally among scholars that become part of the body of epistemological traditions within the field.

In composing a literature review, it is important to note that it is often this third layer of knowledge that is cited as "true" even though it often has only a loose relationship to the primary studies and secondary literature reviews. Given this, while literature reviews are designed to provide an overview and synthesis of pertinent sources you have explored, there are a number of approaches you could adopt depending upon the type of analysis underpinning your study.

Argumentative Review This form examines literature selectively in order to support or refute an argument, deeply embedded assumption, or philosophical problem already established in the literature. The purpose is to develop a body of literature that establishes a contrarian viewpoint. Given the value-laden nature of some social science research [e.g., educational reform; immigration control], argumentative approaches to analyzing the literature can be a legitimate and important form of discourse. However, note that they can also introduce problems of bias when they are used to make summary claims of the sort found in systematic reviews [see below].

Integrative Review Considered a form of research that reviews, critiques, and synthesizes representative literature on a topic in an integrated way such that new frameworks and perspectives on the topic are generated. The body of literature includes all studies that address related or identical hypotheses or research problems. A well-done integrative review meets the same standards as primary research in regard to clarity, rigor, and replication. This is the most common form of review in the social sciences.

Historical Review Few things rest in isolation from historical precedent. Historical literature reviews focus on examining research throughout a period of time, often starting with the first time an issue, concept, theory, phenomena emerged in the literature, then tracing its evolution within the scholarship of a discipline. The purpose is to place research in a historical context to show familiarity with state-of-the-art developments and to identify the likely directions for future research.

Methodological Review A review does not always focus on what someone said [findings], but how they came about saying what they say [method of analysis]. Reviewing methods of analysis provides a framework of understanding at different levels [i.e. those of theory, substantive fields, research approaches, and data collection and analysis techniques], how researchers draw upon a wide variety of knowledge ranging from the conceptual level to practical documents for use in fieldwork in the areas of ontological and epistemological consideration, quantitative and qualitative integration, sampling, interviewing, data collection, and data analysis. This approach helps highlight ethical issues which you should be aware of and consider as you go through your own study.

Systematic Review This form consists of an overview of existing evidence pertinent to a clearly formulated research question, which uses pre-specified and standardized methods to identify and critically appraise relevant research, and to collect, report, and analyze data from the studies that are included in the review. The goal is to deliberately document, critically evaluate, and summarize scientifically all of the research about a clearly defined research problem . Typically it focuses on a very specific empirical question, often posed in a cause-and-effect form, such as "To what extent does A contribute to B?" This type of literature review is primarily applied to examining prior research studies in clinical medicine and allied health fields, but it is increasingly being used in the social sciences.

Theoretical Review The purpose of this form is to examine the corpus of theory that has accumulated in regard to an issue, concept, theory, phenomena. The theoretical literature review helps to establish what theories already exist, the relationships between them, to what degree the existing theories have been investigated, and to develop new hypotheses to be tested. Often this form is used to help establish a lack of appropriate theories or reveal that current theories are inadequate for explaining new or emerging research problems. The unit of analysis can focus on a theoretical concept or a whole theory or framework.

NOTE: Most often the literature review will incorporate some combination of types. For example, a review that examines literature supporting or refuting an argument, assumption, or philosophical problem related to the research problem will also need to include writing supported by sources that establish the history of these arguments in the literature.

Baumeister, Roy F. and Mark R. Leary. "Writing Narrative Literature Reviews."  Review of General Psychology 1 (September 1997): 311-320; Mark R. Fink, Arlene. Conducting Research Literature Reviews: From the Internet to Paper . 2nd ed. Thousand Oaks, CA: Sage, 2005; Hart, Chris. Doing a Literature Review: Releasing the Social Science Research Imagination . Thousand Oaks, CA: Sage Publications, 1998; Kennedy, Mary M. "Defining a Literature." Educational Researcher 36 (April 2007): 139-147; Petticrew, Mark and Helen Roberts. Systematic Reviews in the Social Sciences: A Practical Guide . Malden, MA: Blackwell Publishers, 2006; Torracro, Richard. "Writing Integrative Literature Reviews: Guidelines and Examples." Human Resource Development Review 4 (September 2005): 356-367; Rocco, Tonette S. and Maria S. Plakhotnik. "Literature Reviews, Conceptual Frameworks, and Theoretical Frameworks: Terms, Functions, and Distinctions." Human Ressource Development Review 8 (March 2008): 120-130; Sutton, Anthea. Systematic Approaches to a Successful Literature Review . Los Angeles, CA: Sage Publications, 2016.

Structure and Writing Style

I.  Thinking About Your Literature Review

The structure of a literature review should include the following in support of understanding the research problem :

• An overview of the subject, issue, or theory under consideration, along with the objectives of the literature review,
• Division of works under review into themes or categories [e.g. works that support a particular position, those against, and those offering alternative approaches entirely],
• An explanation of how each work is similar to and how it varies from the others,
• Conclusions as to which pieces are best considered in their argument, are most convincing of their opinions, and make the greatest contribution to the understanding and development of their area of research.

The critical evaluation of each work should consider :

• Provenance -- what are the author's credentials? Are the author's arguments supported by evidence [e.g. primary historical material, case studies, narratives, statistics, recent scientific findings]?
• Methodology -- were the techniques used to identify, gather, and analyze the data appropriate to addressing the research problem? Was the sample size appropriate? Were the results effectively interpreted and reported?
• Objectivity -- is the author's perspective even-handed or prejudicial? Is contrary data considered or is certain pertinent information ignored to prove the author's point?
• Persuasiveness -- which of the author's theses are most convincing or least convincing?
• Validity -- are the author's arguments and conclusions convincing? Does the work ultimately contribute in any significant way to an understanding of the subject?

II.  Development of the Literature Review

Four Basic Stages of Writing 1.  Problem formulation -- which topic or field is being examined and what are its component issues? 2.  Literature search -- finding materials relevant to the subject being explored. 3.  Data evaluation -- determining which literature makes a significant contribution to the understanding of the topic. 4.  Analysis and interpretation -- discussing the findings and conclusions of pertinent literature.

Consider the following issues before writing the literature review: Clarify If your assignment is not specific about what form your literature review should take, seek clarification from your professor by asking these questions: 1.  Roughly how many sources would be appropriate to include? 2.  What types of sources should I review (books, journal articles, websites; scholarly versus popular sources)? 3.  Should I summarize, synthesize, or critique sources by discussing a common theme or issue? 4.  Should I evaluate the sources in any way beyond evaluating how they relate to understanding the research problem? 5.  Should I provide subheadings and other background information, such as definitions and/or a history? Find Models Use the exercise of reviewing the literature to examine how authors in your discipline or area of interest have composed their literature review sections. Read them to get a sense of the types of themes you might want to look for in your own research or to identify ways to organize your final review. The bibliography or reference section of sources you've already read, such as required readings in the course syllabus, are also excellent entry points into your own research. Narrow the Topic The narrower your topic, the easier it will be to limit the number of sources you need to read in order to obtain a good survey of relevant resources. Your professor will probably not expect you to read everything that's available about the topic, but you'll make the act of reviewing easier if you first limit scope of the research problem. A good strategy is to begin by searching the USC Libraries Catalog for recent books about the topic and review the table of contents for chapters that focuses on specific issues. You can also review the indexes of books to find references to specific issues that can serve as the focus of your research. For example, a book surveying the history of the Israeli-Palestinian conflict may include a chapter on the role Egypt has played in mediating the conflict, or look in the index for the pages where Egypt is mentioned in the text. Consider Whether Your Sources are Current Some disciplines require that you use information that is as current as possible. This is particularly true in disciplines in medicine and the sciences where research conducted becomes obsolete very quickly as new discoveries are made. However, when writing a review in the social sciences, a survey of the history of the literature may be required. In other words, a complete understanding the research problem requires you to deliberately examine how knowledge and perspectives have changed over time. Sort through other current bibliographies or literature reviews in the field to get a sense of what your discipline expects. You can also use this method to explore what is considered by scholars to be a "hot topic" and what is not.

III.  Ways to Organize Your Literature Review

Chronology of Events If your review follows the chronological method, you could write about the materials according to when they were published. This approach should only be followed if a clear path of research building on previous research can be identified and that these trends follow a clear chronological order of development. For example, a literature review that focuses on continuing research about the emergence of German economic power after the fall of the Soviet Union. By Publication Order your sources by publication chronology, then, only if the order demonstrates a more important trend. For instance, you could order a review of literature on environmental studies of brown fields if the progression revealed, for example, a change in the soil collection practices of the researchers who wrote and/or conducted the studies. Thematic [“conceptual categories”] A thematic literature review is the most common approach to summarizing prior research in the social and behavioral sciences. Thematic reviews are organized around a topic or issue, rather than the progression of time, although the progression of time may still be incorporated into a thematic review. For example, a review of the Internet’s impact on American presidential politics could focus on the development of online political satire. While the study focuses on one topic, the Internet’s impact on American presidential politics, it would still be organized chronologically reflecting technological developments in media. The difference in this example between a "chronological" and a "thematic" approach is what is emphasized the most: themes related to the role of the Internet in presidential politics. Note that more authentic thematic reviews tend to break away from chronological order. A review organized in this manner would shift between time periods within each section according to the point being made. Methodological A methodological approach focuses on the methods utilized by the researcher. For the Internet in American presidential politics project, one methodological approach would be to look at cultural differences between the portrayal of American presidents on American, British, and French websites. Or the review might focus on the fundraising impact of the Internet on a particular political party. A methodological scope will influence either the types of documents in the review or the way in which these documents are discussed.

Other Sections of Your Literature Review Once you've decided on the organizational method for your literature review, the sections you need to include in the paper should be easy to figure out because they arise from your organizational strategy. In other words, a chronological review would have subsections for each vital time period; a thematic review would have subtopics based upon factors that relate to the theme or issue. However, sometimes you may need to add additional sections that are necessary for your study, but do not fit in the organizational strategy of the body. What other sections you include in the body is up to you. However, only include what is necessary for the reader to locate your study within the larger scholarship about the research problem.

Here are examples of other sections, usually in the form of a single paragraph, you may need to include depending on the type of review you write:

• Current Situation : Information necessary to understand the current topic or focus of the literature review.
• Sources Used : Describes the methods and resources [e.g., databases] you used to identify the literature you reviewed.
• History : The chronological progression of the field, the research literature, or an idea that is necessary to understand the literature review, if the body of the literature review is not already a chronology.
• Selection Methods : Criteria you used to select (and perhaps exclude) sources in your literature review. For instance, you might explain that your review includes only peer-reviewed [i.e., scholarly] sources.
• Standards : Description of the way in which you present your information.
• Questions for Further Research : What questions about the field has the review sparked? How will you further your research as a result of the review?

IV.  Writing Your Literature Review

Once you've settled on how to organize your literature review, you're ready to write each section. When writing your review, keep in mind these issues.

Use Evidence A literature review section is, in this sense, just like any other academic research paper. Your interpretation of the available sources must be backed up with evidence [citations] that demonstrates that what you are saying is valid. Be Selective Select only the most important points in each source to highlight in the review. The type of information you choose to mention should relate directly to the research problem, whether it is thematic, methodological, or chronological. Related items that provide additional information, but that are not key to understanding the research problem, can be included in a list of further readings . Use Quotes Sparingly Some short quotes are appropriate if you want to emphasize a point, or if what an author stated cannot be easily paraphrased. Sometimes you may need to quote certain terminology that was coined by the author, is not common knowledge, or taken directly from the study. Do not use extensive quotes as a substitute for using your own words in reviewing the literature. Summarize and Synthesize Remember to summarize and synthesize your sources within each thematic paragraph as well as throughout the review. Recapitulate important features of a research study, but then synthesize it by rephrasing the study's significance and relating it to your own work and the work of others. Keep Your Own Voice While the literature review presents others' ideas, your voice [the writer's] should remain front and center. For example, weave references to other sources into what you are writing but maintain your own voice by starting and ending the paragraph with your own ideas and wording. Use Caution When Paraphrasing When paraphrasing a source that is not your own, be sure to represent the author's information or opinions accurately and in your own words. Even when paraphrasing an author’s work, you still must provide a citation to that work.

V.  Common Mistakes to Avoid

These are the most common mistakes made in reviewing social science research literature.

• Sources in your literature review do not clearly relate to the research problem;
• You do not take sufficient time to define and identify the most relevant sources to use in the literature review related to the research problem;
• Relies exclusively on secondary analytical sources rather than including relevant primary research studies or data;
• Uncritically accepts another researcher's findings and interpretations as valid, rather than examining critically all aspects of the research design and analysis;
• Does not describe the search procedures that were used in identifying the literature to review;
• Reports isolated statistical results rather than synthesizing them in chi-squared or meta-analytic methods; and,
• Only includes research that validates assumptions and does not consider contrary findings and alternative interpretations found in the literature.

Cook, Kathleen E. and Elise Murowchick. “Do Literature Review Skills Transfer from One Course to Another?” Psychology Learning and Teaching 13 (March 2014): 3-11; Fink, Arlene. Conducting Research Literature Reviews: From the Internet to Paper . 2nd ed. Thousand Oaks, CA: Sage, 2005; Hart, Chris. Doing a Literature Review: Releasing the Social Science Research Imagination . Thousand Oaks, CA: Sage Publications, 1998; Jesson, Jill. Doing Your Literature Review: Traditional and Systematic Techniques . London: SAGE, 2011; Literature Review Handout. Online Writing Center. Liberty University; Literature Reviews. The Writing Center. University of North Carolina; Onwuegbuzie, Anthony J. and Rebecca Frels. Seven Steps to a Comprehensive Literature Review: A Multimodal and Cultural Approach . Los Angeles, CA: SAGE, 2016; Ridley, Diana. The Literature Review: A Step-by-Step Guide for Students . 2nd ed. Los Angeles, CA: SAGE, 2012; Randolph, Justus J. “A Guide to Writing the Dissertation Literature Review." Practical Assessment, Research, and Evaluation. vol. 14, June 2009; Sutton, Anthea. Systematic Approaches to a Successful Literature Review . Los Angeles, CA: Sage Publications, 2016; Taylor, Dena. The Literature Review: A Few Tips On Conducting It. University College Writing Centre. University of Toronto; Writing a Literature Review. Academic Skills Centre. University of Canberra.

Writing Tip

Break Out of Your Disciplinary Box!

Thinking interdisciplinarily about a research problem can be a rewarding exercise in applying new ideas, theories, or concepts to an old problem. For example, what might cultural anthropologists say about the continuing conflict in the Middle East? In what ways might geographers view the need for better distribution of social service agencies in large cities than how social workers might study the issue? You don’t want to substitute a thorough review of core research literature in your discipline for studies conducted in other fields of study. However, particularly in the social sciences, thinking about research problems from multiple vectors is a key strategy for finding new solutions to a problem or gaining a new perspective. Consult with a librarian about identifying research databases in other disciplines; almost every field of study has at least one comprehensive database devoted to indexing its research literature.

Frodeman, Robert. The Oxford Handbook of Interdisciplinarity . New York: Oxford University Press, 2010.

Another Writing Tip

Don't Just Review for Content!

While conducting a review of the literature, maximize the time you devote to writing this part of your paper by thinking broadly about what you should be looking for and evaluating. Review not just what scholars are saying, but how are they saying it. Some questions to ask:

• How are they organizing their ideas?
• What methods have they used to study the problem?
• What theories have been used to explain, predict, or understand their research problem?
• What sources have they cited to support their conclusions?
• How have they used non-textual elements [e.g., charts, graphs, figures, etc.] to illustrate key points?

When you begin to write your literature review section, you'll be glad you dug deeper into how the research was designed and constructed because it establishes a means for developing more substantial analysis and interpretation of the research problem.

Hart, Chris. Doing a Literature Review: Releasing the Social Science Research Imagination . Thousand Oaks, CA: Sage Publications, 1 998.

Yet Another Writing Tip

When Do I Know I Can Stop Looking and Move On?

Here are several strategies you can utilize to assess whether you've thoroughly reviewed the literature:

• Look for repeating patterns in the research findings . If the same thing is being said, just by different people, then this likely demonstrates that the research problem has hit a conceptual dead end. At this point consider: Does your study extend current research?  Does it forge a new path? Or, does is merely add more of the same thing being said?
• Look at sources the authors cite to in their work . If you begin to see the same researchers cited again and again, then this is often an indication that no new ideas have been generated to address the research problem.
• Search Google Scholar to identify who has subsequently cited leading scholars already identified in your literature review [see next sub-tab]. This is called citation tracking and there are a number of sources that can help you identify who has cited whom, particularly scholars from outside of your discipline. Here again, if the same authors are being cited again and again, this may indicate no new literature has been written on the topic.

Onwuegbuzie, Anthony J. and Rebecca Frels. Seven Steps to a Comprehensive Literature Review: A Multimodal and Cultural Approach . Los Angeles, CA: Sage, 2016; Sutton, Anthea. Systematic Approaches to a Successful Literature Review . Los Angeles, CA: Sage Publications, 2016.

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• UConn Library
• Literature Review: The What, Why and How-to Guide
• Introduction

Literature Review: The What, Why and How-to Guide — Introduction

• Getting Started
• How to Pick a Topic
• Strategies to Find Sources
• Evaluating Sources & Lit. Reviews
• Tips for Writing Literature Reviews
• Writing Literature Review: Useful Sites
• Citation Resources
• Other Academic Writings

What are Literature Reviews?

So, what is a literature review? "A literature review is an account of what has been published on a topic by accredited scholars and researchers. In writing the literature review, your purpose is to convey to your reader what knowledge and ideas have been established on a topic, and what their strengths and weaknesses are. As a piece of writing, the literature review must be defined by a guiding concept (e.g., your research objective, the problem or issue you are discussing, or your argumentative thesis). It is not just a descriptive list of the material available, or a set of summaries." Taylor, D.  The literature review: A few tips on conducting it . University of Toronto Health Sciences Writing Centre.

Goals of Literature Reviews

What are the goals of creating a Literature Review?  A literature could be written to accomplish different aims:

• To develop a theory or evaluate an existing theory
• To summarize the historical or existing state of a research topic
• Identify a problem in a field of research 

Baumeister, R. F., & Leary, M. R. (1997). Writing narrative literature reviews .  Review of General Psychology , 1 (3), 311-320.

What kinds of sources require a Literature Review?

• A research paper assigned in a course
• A thesis or dissertation
• A grant proposal
• An article intended for publication in a journal

All these instances require you to collect what has been written about your research topic so that you can demonstrate how your own research sheds new light on the topic.

Types of Literature Reviews

What kinds of literature reviews are written?

Narrative review: The purpose of this type of review is to describe the current state of the research on a specific topic/research and to offer a critical analysis of the literature reviewed. Studies are grouped by research/theoretical categories, and themes and trends, strengths and weakness, and gaps are identified. The review ends with a conclusion section which summarizes the findings regarding the state of the research of the specific study, the gaps identify and if applicable, explains how the author's research will address gaps identify in the review and expand the knowledge on the topic reviewed.

• Example : Predictors and Outcomes of U.S. Quality Maternity Leave: A Review and Conceptual Framework:  10.1177/08948453211037398  

Systematic review : "The authors of a systematic review use a specific procedure to search the research literature, select the studies to include in their review, and critically evaluate the studies they find." (p. 139). Nelson, L. K. (2013). Research in Communication Sciences and Disorders . Plural Publishing.

• Example : The effect of leave policies on increasing fertility: a systematic review:  10.1057/s41599-022-01270-w

Meta-analysis : "Meta-analysis is a method of reviewing research findings in a quantitative fashion by transforming the data from individual studies into what is called an effect size and then pooling and analyzing this information. The basic goal in meta-analysis is to explain why different outcomes have occurred in different studies." (p. 197). Roberts, M. C., & Ilardi, S. S. (2003). Handbook of Research Methods in Clinical Psychology . Blackwell Publishing.

• Example : Employment Instability and Fertility in Europe: A Meta-Analysis:  10.1215/00703370-9164737

Meta-synthesis : "Qualitative meta-synthesis is a type of qualitative study that uses as data the findings from other qualitative studies linked by the same or related topic." (p.312). Zimmer, L. (2006). Qualitative meta-synthesis: A question of dialoguing with texts .  Journal of Advanced Nursing , 53 (3), 311-318.

• Example : Women’s perspectives on career successes and barriers: A qualitative meta-synthesis:  10.1177/05390184221113735

Literature Reviews in the Health Sciences

• UConn Health subject guide on systematic reviews Explanation of the different review types used in health sciences literature as well as tools to help you find the right review type
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Review of Related Literature: Format, Example, & How to Make RRL

A review of related literature is a separate paper or a part of an article that collects and synthesizes discussion on a topic. Its purpose is to show the current state of research on the issue and highlight gaps in existing knowledge. A literature review can be included in a research paper or scholarly article, typically following the introduction and before the research methods section.

This article will clarify the definition, significance, and structure of a review of related literature. You’ll also learn how to organize your literature review and discover ideas for an RRL in different subjects.

🔤 What Is RRL?

• ❗ Significance of Literature Review
• 🔎 How to Search for Literature
• 🧩 Literature Review Structure
• 📋 Format of RRL — APA, MLA, & Others
• ✍️ How to Write an RRL
• 📚 Examples of RRL

🔗 References

A review of related literature (RRL) is a part of the research report that examines significant studies, theories, and concepts published in scholarly sources on a particular topic. An RRL includes 3 main components:

• A short overview and critique of the previous research.
• Similarities and differences between past studies and the current one.
• An explanation of the theoretical frameworks underpinning the research.

❗ Significance of Review of Related Literature

Although the goal of a review of related literature differs depending on the discipline and its intended use, its significance cannot be overstated. Here are some examples of how a review might be beneficial:

• It helps determine knowledge gaps .
• It saves from duplicating research that has already been conducted.
• It provides an overview of various research areas within the discipline.
• It demonstrates the researcher’s familiarity with the topic.

🔎 How to Perform a Literature Search

Including a description of your search strategy in the literature review section can significantly increase your grade. You can search sources with the following steps:

🧩 Literature Review Structure Example

The majority of literature reviews follow a standard introduction-body-conclusion structure. Let’s look at the RRL structure in detail.

Introduction of Review of Related Literature: Sample

An introduction should clarify the study topic and the depth of the information to be delivered. It should also explain the types of sources used. If your lit. review is part of a larger research proposal or project, you can combine its introductory paragraph with the introduction of your paper.

Here is a sample introduction to an RRL about cyberbullying:

Bullying has troubled people since the beginning of time. However, with modern technological advancements, especially social media, bullying has evolved into cyberbullying. As a result, nowadays, teenagers and adults cannot flee their bullies, which makes them feel lonely and helpless. This literature review will examine recent studies on cyberbullying.

Sample Review of Related Literature Thesis

A thesis statement should include the central idea of your literature review and the primary supporting elements you discovered in the literature. Thesis statements are typically put at the end of the introductory paragraph.

Look at a sample thesis of a review of related literature:

This literature review shows that scholars have recently covered the issues of bullies’ motivation, the impact of bullying on victims and aggressors, common cyberbullying techniques, and victims’ coping strategies. However, there is still no agreement on the best practices to address cyberbullying.

Literature Review Body Paragraph Example

The main body of a literature review should provide an overview of the existing research on the issue. Body paragraphs should not just summarize each source but analyze them. You can organize your paragraphs with these 3 elements:

• Claim . Start with a topic sentence linked to your literature review purpose.
• Evidence . Cite relevant information from your chosen sources.
• Discussion . Explain how the cited data supports your claim.

Here’s a literature review body paragraph example:

Scholars have examined the link between the aggressor and the victim. Beran et al. (2007) state that students bullied online often become cyberbullies themselves. Faucher et al. (2014) confirm this with their findings: they discovered that male and female students began engaging in cyberbullying after being subject to bullying. Hence, one can conclude that being a victim of bullying increases one’s likelihood of becoming a cyberbully.

Review of Related Literature: Conclusion

A conclusion presents a general consensus on the topic. Depending on your literature review purpose, it might include the following:

• Introduction to further research . If you write a literature review as part of a larger research project, you can present your research question in your conclusion .
• Overview of theories . You can summarize critical theories and concepts to help your reader understand the topic better.
• Discussion of the gap . If you identified a research gap in the reviewed literature, your conclusion could explain why that gap is significant.

Check out a conclusion example that discusses a research gap:

There is extensive research into bullies’ motivation, the consequences of bullying for victims and aggressors, strategies for bullying, and coping with it. Yet, scholars still have not reached a consensus on what to consider the best practices to combat cyberbullying. This question is of great importance because of the significant adverse effects of cyberbullying on victims and bullies.

📋 Format of RRL — APA, MLA, & Others

In this section, we will discuss how to format an RRL according to the most common citation styles: APA, Chicago, MLA, and Harvard.

Writing a literature review using the APA7 style requires the following text formatting:

• When using APA in-text citations , include the author’s last name and the year of publication in parentheses.
• For direct quotations , you must also add the page number. If you use sources without page numbers, such as websites or e-books, include a paragraph number instead.
• When referring to the author’s name in a sentence , you do not need to repeat it at the end of the sentence. Instead, include the year of publication inside the parentheses after their name.
• The reference list should be included at the end of your literature review. It is always alphabetized by the last name of the author (from A to Z), and the lines are indented one-half inch from the left margin of your paper. Do not forget to invert authors’ names (the last name should come first) and include the full titles of journals instead of their abbreviations. If you use an online source, add its URL.

The RRL format in the Chicago style is as follows:

• Author-date . You place your citations in brackets within the text, indicating the name of the author and the year of publication.
• Notes and bibliography . You place your citations in numbered footnotes or endnotes to connect the citation back to the source in the bibliography.
• The reference list, or bibliography , in Chicago style, is at the end of a literature review. The sources are arranged alphabetically and single-spaced. Each bibliography entry begins with the author’s name and the source’s title, followed by publication information, such as the city of publication, the publisher, and the year of publication.

Writing a literature review using the MLA style requires the following text formatting:

• In the MLA format, you can cite a source in the text by indicating the author’s last name and the page number in parentheses at the end of the citation. If the cited information takes several pages, you need to include all the page numbers.
• The reference list in MLA style is titled “ Works Cited .” In this section, all sources used in the paper should be listed in alphabetical order. Each entry should contain the author, title of the source, title of the journal or a larger volume, other contributors, version, number, publisher, and publication date.

The Harvard style requires you to use the following text formatting for your RRL:

• In-text citations in the Harvard style include the author’s last name and the year of publication. If you are using a direct quote in your literature review, you need to add the page number as well.
• Arrange your list of references alphabetically. Each entry should contain the author’s last name, their initials, the year of publication, the title of the source, and other publication information, like the journal title and issue number or the publisher.

✍️ How to Write Review of Related Literature – Sample

Literature reviews can be organized in many ways depending on what you want to achieve with them. In this section, we will look at 3 examples of how you can write your RRL.

Thematic Literature Review

A thematic literature review is arranged around central themes or issues discussed in the sources. If you have identified some recurring themes in the literature, you can divide your RRL into sections that address various aspects of the topic. For example, if you examine studies on e-learning, you can distinguish such themes as the cost-effectiveness of online learning, the technologies used, and its effectiveness compared to traditional education.

Chronological Literature Review

A chronological literature review is a way to track the development of the topic over time. If you use this method, avoid merely listing and summarizing sources in chronological order. Instead, try to analyze the trends, turning moments, and critical debates that have shaped the field’s path. Also, you can give your interpretation of how and why specific advances occurred.

Methodological Literature Review

A methodological literature review differs from the preceding ones in that it usually doesn’t focus on the sources’ content. Instead, it is concerned with the research methods . So, if your references come from several disciplines or fields employing various research techniques, you can compare the findings and conclusions of different methodologies, for instance:

• empirical vs. theoretical studies;
• qualitative vs. quantitative research.

📚 Examples of Review of Related Literature and Studies

We have prepared a short example of RRL on climate change for you to see how everything works in practice!

Climate change is one of the most important issues nowadays. Based on a variety of facts, it is now clearer than ever that humans are altering the Earth's climate. The atmosphere and oceans have warmed, causing sea level rise, a significant loss of Arctic ice, and other climate-related changes. This literature review provides a thorough summary of research on climate change, focusing on climate change fingerprints and evidence of human influence on the Earth's climate system.

Physical Mechanisms and Evidence of Human Influence

Scientists are convinced that climate change is directly influenced by the emission of greenhouse gases. They have carefully analyzed various climate data and evidence, concluding that the majority of the observed global warming over the past 50 years cannot be explained by natural factors alone. Instead, there is compelling evidence pointing to a significant contribution of human activities, primarily the emission of greenhouse gases (Walker, 2014). For example, based on simple physics calculations, doubled carbon dioxide concentration in the atmosphere can lead to a global temperature increase of approximately 1 degree Celsius. (Elderfield, 2022). In order to determine the human influence on climate, scientists still have to analyze a lot of natural changes that affect temperature, precipitation, and other components of climate on timeframes ranging from days to decades and beyond.

Fingerprinting Climate Change

Fingerprinting climate change is a useful tool to identify the causes of global warming because different factors leave unique marks on climate records. This is evident when scientists look beyond overall temperature changes and examine how warming is distributed geographically and over time (Watson, 2022). By investigating these climate patterns, scientists can obtain a more complex understanding of the connections between natural climate variability and climate variability caused by human activity.

Modeling Climate Change and Feedback

To accurately predict the consequences of feedback mechanisms, the rate of warming, and regional climate change, scientists can employ sophisticated mathematical models of the atmosphere, ocean, land, and ice (the cryosphere). These models are grounded in well-established physical laws and incorporate the latest scientific understanding of climate-related processes (Shuckburgh, 2013). Although different climate models produce slightly varying projections for future warming, they all will agree that feedback mechanisms play a significant role in amplifying the initial warming caused by greenhouse gas emissions. (Meehl, 2019).

In conclusion, the literature on global warming indicates that there are well-understood physical processes that link variations in greenhouse gas concentrations to climate change. In addition, it covers the scientific proof that the rates of these gases in the atmosphere have increased and continue to rise fast. According to the sources, the majority of this recent change is almost definitely caused by greenhouse gas emissions produced by human activities. Citizens and governments can alter their energy production methods and consumption patterns to reduce greenhouse gas emissions and, thus, the magnitude of climate change. By acting now, society can prevent the worst consequences of climate change and build a more resilient and sustainable future for generations to come.

Have you ever struggled with finding the topic for an RRL in different subjects? Read the following paragraphs to get some ideas!

Nursing Literature Review Example

Many topics in the nursing field require research. For example, you can write a review of literature related to dengue fever . Give a general overview of dengue virus infections, including its clinical symptoms, diagnosis, prevention, and therapy.

Another good idea is to review related literature and studies about teenage pregnancy . This review can describe the effectiveness of specific programs for adolescent mothers and their children and summarize recommendations for preventing early pregnancy.

📝 Check out some more valuable examples below:

• Hospital Readmissions: Literature Review .
• Literature Review: Lower Sepsis Mortality Rates .
• Breast Cancer: Literature Review .
• Sexually Transmitted Diseases: Literature Review .
• PICO for Pressure Ulcers: Literature Review .
• COVID-19 Spread Prevention: Literature Review .
• Chronic Obstructive Pulmonary Disease: Literature Review .
• Hypertension Treatment Adherence: Literature Review .
• Neonatal Sepsis Prevention: Literature Review .
• Healthcare-Associated Infections: Literature Review .
• Understaffing in Nursing: Literature Review .

Psychology Literature Review Example

If you look for an RRL topic in psychology , you can write a review of related literature about stress . Summarize scientific evidence about stress stages, side effects, types, or reduction strategies. Or you can write a review of related literature about computer game addiction . In this case, you may concentrate on the neural mechanisms underlying the internet gaming disorder, compare it to other addictions, or evaluate treatment strategies.

A review of related literature about cyberbullying is another interesting option. You can highlight the impact of cyberbullying on undergraduate students’ academic, social, and emotional development.

📝 Look at the examples that we have prepared for you to come up with some more ideas:

• Mindfulness in Counseling: A Literature Review .
• Team-Building Across Cultures: Literature Review .
• Anxiety and Decision Making: Literature Review .
• Literature Review on Depression .
• Literature Review on Narcissism .
• Effects of Depression Among Adolescents .
• Causes and Effects of Anxiety in Children .

Literature Review — Sociology Example

Sociological research poses critical questions about social structures and phenomena. For example, you can write a review of related literature about child labor , exploring cultural beliefs and social norms that normalize the exploitation of children. Or you can create a review of related literature about social media . It can investigate the impact of social media on relationships between adolescents or the role of social networks on immigrants’ acculturation .

📝 You can find some more ideas below!

• Single Mothers’ Experiences of Relationships with Their Adolescent Sons .
• Teachers and Students’ Gender-Based Interactions .
• Gender Identity: Biological Perspective and Social Cognitive Theory .
• Gender: Culturally-Prescribed Role or Biological Sex .
• The Influence of Opioid Misuse on Academic Achievement of Veteran Students .
• The Importance of Ethics in Research .
• The Role of Family and Social Network Support in Mental Health .

Education Literature Review Example

For your education studies , you can write a review of related literature about academic performance to determine factors that affect student achievement and highlight research gaps. One more idea is to create a review of related literature on study habits , considering their role in the student’s life and academic outcomes.

You can also evaluate a computerized grading system in a review of related literature to single out its advantages and barriers to implementation. Or you can complete a review of related literature on instructional materials to identify their most common types and effects on student achievement.

📝 Find some inspiration in the examples below:

• Literature Review on Online Learning Challenges From COVID-19 .
• Education, Leadership, and Management: Literature Review .
• Literature Review: Standardized Testing Bias .
• Bullying of Disabled Children in School .
• Interventions and Letter & Sound Recognition: A Literature Review .
• Social-Emotional Skills Program for Preschoolers .
• Effectiveness of Educational Leadership Management Skills .

Business Research Literature Review

If you’re a business student, you can focus on customer satisfaction in your review of related literature. Discuss specific customer satisfaction features and how it is affected by service quality and prices. You can also create a theoretical literature review about consumer buying behavior to evaluate theories that have significantly contributed to understanding how consumers make purchasing decisions.

📝 Look at the examples to get more exciting ideas:

• Leadership and Communication: Literature Review .
• Human Resource Development: Literature Review .
• Project Management. Literature Review .
• Strategic HRM: A Literature Review .
• Customer Relationship Management: Literature Review .
• Literature Review on International Financial Reporting Standards .
• Cultures of Management: Literature Review .

To conclude, a review of related literature is a significant genre of scholarly works that can be applied in various disciplines and for multiple goals. The sources examined in an RRL provide theoretical frameworks for future studies and help create original research questions and hypotheses.

When you finish your outstanding literature review, don’t forget to check whether it sounds logical and coherent. Our text-to-speech tool can help you with that!

• Literature Reviews | University of North Carolina at Chapel Hill
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Home » Research Findings – Types Examples and Writing Guide

Research Findings – Types Examples and Writing Guide

Table of Contents

Research Findings

Definition:

Research findings refer to the results obtained from a study or investigation conducted through a systematic and scientific approach. These findings are the outcomes of the data analysis, interpretation, and evaluation carried out during the research process.

Types of Research Findings

There are two main types of research findings:

Qualitative Findings

Qualitative research is an exploratory research method used to understand the complexities of human behavior and experiences. Qualitative findings are non-numerical and descriptive data that describe the meaning and interpretation of the data collected. Examples of qualitative findings include quotes from participants, themes that emerge from the data, and descriptions of experiences and phenomena.

Quantitative Findings

Quantitative research is a research method that uses numerical data and statistical analysis to measure and quantify a phenomenon or behavior. Quantitative findings include numerical data such as mean, median, and mode, as well as statistical analyses such as t-tests, ANOVA, and regression analysis. These findings are often presented in tables, graphs, or charts.

Both qualitative and quantitative findings are important in research and can provide different insights into a research question or problem. Combining both types of findings can provide a more comprehensive understanding of a phenomenon and improve the validity and reliability of research results.

Parts of Research Findings

Research findings typically consist of several parts, including:

• Introduction: This section provides an overview of the research topic and the purpose of the study.
• Literature Review: This section summarizes previous research studies and findings that are relevant to the current study.
• Methodology : This section describes the research design, methods, and procedures used in the study, including details on the sample, data collection, and data analysis.
• Results : This section presents the findings of the study, including statistical analyses and data visualizations.
• Discussion : This section interprets the results and explains what they mean in relation to the research question(s) and hypotheses. It may also compare and contrast the current findings with previous research studies and explore any implications or limitations of the study.
• Conclusion : This section provides a summary of the key findings and the main conclusions of the study.
• Recommendations: This section suggests areas for further research and potential applications or implications of the study’s findings.

How to Write Research Findings

Writing research findings requires careful planning and attention to detail. Here are some general steps to follow when writing research findings:

• Organize your findings: Before you begin writing, it’s essential to organize your findings logically. Consider creating an outline or a flowchart that outlines the main points you want to make and how they relate to one another.
• Use clear and concise language : When presenting your findings, be sure to use clear and concise language that is easy to understand. Avoid using jargon or technical terms unless they are necessary to convey your meaning.
• Use visual aids : Visual aids such as tables, charts, and graphs can be helpful in presenting your findings. Be sure to label and title your visual aids clearly, and make sure they are easy to read.
• Use headings and subheadings: Using headings and subheadings can help organize your findings and make them easier to read. Make sure your headings and subheadings are clear and descriptive.
• Interpret your findings : When presenting your findings, it’s important to provide some interpretation of what the results mean. This can include discussing how your findings relate to the existing literature, identifying any limitations of your study, and suggesting areas for future research.
• Be precise and accurate : When presenting your findings, be sure to use precise and accurate language. Avoid making generalizations or overstatements and be careful not to misrepresent your data.
• Edit and revise: Once you have written your research findings, be sure to edit and revise them carefully. Check for grammar and spelling errors, make sure your formatting is consistent, and ensure that your writing is clear and concise.

Research Findings Example

Following is a Research Findings Example sample for students:

Title: The Effects of Exercise on Mental Health

Sample : 500 participants, both men and women, between the ages of 18-45.

Methodology : Participants were divided into two groups. The first group engaged in 30 minutes of moderate intensity exercise five times a week for eight weeks. The second group did not exercise during the study period. Participants in both groups completed a questionnaire that assessed their mental health before and after the study period.

Findings : The group that engaged in regular exercise reported a significant improvement in mental health compared to the control group. Specifically, they reported lower levels of anxiety and depression, improved mood, and increased self-esteem.

Conclusion : Regular exercise can have a positive impact on mental health and may be an effective intervention for individuals experiencing symptoms of anxiety or depression.

Applications of Research Findings

Research findings can be applied in various fields to improve processes, products, services, and outcomes. Here are some examples:

• Healthcare : Research findings in medicine and healthcare can be applied to improve patient outcomes, reduce morbidity and mortality rates, and develop new treatments for various diseases.
• Education : Research findings in education can be used to develop effective teaching methods, improve learning outcomes, and design new educational programs.
• Technology : Research findings in technology can be applied to develop new products, improve existing products, and enhance user experiences.
• Business : Research findings in business can be applied to develop new strategies, improve operations, and increase profitability.
• Public Policy: Research findings can be used to inform public policy decisions on issues such as environmental protection, social welfare, and economic development.
• Social Sciences: Research findings in social sciences can be used to improve understanding of human behavior and social phenomena, inform public policy decisions, and develop interventions to address social issues.
• Agriculture: Research findings in agriculture can be applied to improve crop yields, develop new farming techniques, and enhance food security.
• Sports : Research findings in sports can be applied to improve athlete performance, reduce injuries, and develop new training programs.

When to use Research Findings

Research findings can be used in a variety of situations, depending on the context and the purpose. Here are some examples of when research findings may be useful:

• Decision-making : Research findings can be used to inform decisions in various fields, such as business, education, healthcare, and public policy. For example, a business may use market research findings to make decisions about new product development or marketing strategies.
• Problem-solving : Research findings can be used to solve problems or challenges in various fields, such as healthcare, engineering, and social sciences. For example, medical researchers may use findings from clinical trials to develop new treatments for diseases.
• Policy development : Research findings can be used to inform the development of policies in various fields, such as environmental protection, social welfare, and economic development. For example, policymakers may use research findings to develop policies aimed at reducing greenhouse gas emissions.
• Program evaluation: Research findings can be used to evaluate the effectiveness of programs or interventions in various fields, such as education, healthcare, and social services. For example, educational researchers may use findings from evaluations of educational programs to improve teaching and learning outcomes.
• Innovation: Research findings can be used to inspire or guide innovation in various fields, such as technology and engineering. For example, engineers may use research findings on materials science to develop new and innovative products.

Purpose of Research Findings

The purpose of research findings is to contribute to the knowledge and understanding of a particular topic or issue. Research findings are the result of a systematic and rigorous investigation of a research question or hypothesis, using appropriate research methods and techniques.

The main purposes of research findings are:

• To generate new knowledge : Research findings contribute to the body of knowledge on a particular topic, by adding new information, insights, and understanding to the existing knowledge base.
• To test hypotheses or theories : Research findings can be used to test hypotheses or theories that have been proposed in a particular field or discipline. This helps to determine the validity and reliability of the hypotheses or theories, and to refine or develop new ones.
• To inform practice: Research findings can be used to inform practice in various fields, such as healthcare, education, and business. By identifying best practices and evidence-based interventions, research findings can help practitioners to make informed decisions and improve outcomes.
• To identify gaps in knowledge: Research findings can help to identify gaps in knowledge and understanding of a particular topic, which can then be addressed by further research.
• To contribute to policy development: Research findings can be used to inform policy development in various fields, such as environmental protection, social welfare, and economic development. By providing evidence-based recommendations, research findings can help policymakers to develop effective policies that address societal challenges.

Characteristics of Research Findings

Research findings have several key characteristics that distinguish them from other types of information or knowledge. Here are some of the main characteristics of research findings:

• Objective : Research findings are based on a systematic and rigorous investigation of a research question or hypothesis, using appropriate research methods and techniques. As such, they are generally considered to be more objective and reliable than other types of information.
• Empirical : Research findings are based on empirical evidence, which means that they are derived from observations or measurements of the real world. This gives them a high degree of credibility and validity.
• Generalizable : Research findings are often intended to be generalizable to a larger population or context beyond the specific study. This means that the findings can be applied to other situations or populations with similar characteristics.
• Transparent : Research findings are typically reported in a transparent manner, with a clear description of the research methods and data analysis techniques used. This allows others to assess the credibility and reliability of the findings.
• Peer-reviewed: Research findings are often subject to a rigorous peer-review process, in which experts in the field review the research methods, data analysis, and conclusions of the study. This helps to ensure the validity and reliability of the findings.
• Reproducible : Research findings are often designed to be reproducible, meaning that other researchers can replicate the study using the same methods and obtain similar results. This helps to ensure the validity and reliability of the findings.

Advantages of Research Findings

Research findings have many advantages, which make them valuable sources of knowledge and information. Here are some of the main advantages of research findings:

• Evidence-based: Research findings are based on empirical evidence, which means that they are grounded in data and observations from the real world. This makes them a reliable and credible source of information.
• Inform decision-making: Research findings can be used to inform decision-making in various fields, such as healthcare, education, and business. By identifying best practices and evidence-based interventions, research findings can help practitioners and policymakers to make informed decisions and improve outcomes.
• Identify gaps in knowledge: Research findings can help to identify gaps in knowledge and understanding of a particular topic, which can then be addressed by further research. This contributes to the ongoing development of knowledge in various fields.
• Improve outcomes : Research findings can be used to develop and implement evidence-based practices and interventions, which have been shown to improve outcomes in various fields, such as healthcare, education, and social services.
• Foster innovation: Research findings can inspire or guide innovation in various fields, such as technology and engineering. By providing new information and understanding of a particular topic, research findings can stimulate new ideas and approaches to problem-solving.
• Enhance credibility: Research findings are generally considered to be more credible and reliable than other types of information, as they are based on rigorous research methods and are subject to peer-review processes.

Limitations of Research Findings

While research findings have many advantages, they also have some limitations. Here are some of the main limitations of research findings:

• Limited scope: Research findings are typically based on a particular study or set of studies, which may have a limited scope or focus. This means that they may not be applicable to other contexts or populations.
• Potential for bias : Research findings can be influenced by various sources of bias, such as researcher bias, selection bias, or measurement bias. This can affect the validity and reliability of the findings.
• Ethical considerations: Research findings can raise ethical considerations, particularly in studies involving human subjects. Researchers must ensure that their studies are conducted in an ethical and responsible manner, with appropriate measures to protect the welfare and privacy of participants.
• Time and resource constraints : Research studies can be time-consuming and require significant resources, which can limit the number and scope of studies that are conducted. This can lead to gaps in knowledge or a lack of research on certain topics.
• Complexity: Some research findings can be complex and difficult to interpret, particularly in fields such as science or medicine. This can make it challenging for practitioners and policymakers to apply the findings to their work.
• Lack of generalizability : While research findings are intended to be generalizable to larger populations or contexts, there may be factors that limit their generalizability. For example, cultural or environmental factors may influence how a particular intervention or treatment works in different populations or contexts.

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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

Have a language expert improve your writing

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• Starting the research process

A Beginner's Guide to Starting the Research Process

When you have to write a thesis or dissertation , it can be hard to know where to begin, but there are some clear steps you can follow.

The research process often begins with a very broad idea for a topic you’d like to know more about. You do some preliminary research to identify a  problem . After refining your research questions , you can lay out the foundations of your research design , leading to a proposal that outlines your ideas and plans.

This article takes you through the first steps of the research process, helping you narrow down your ideas and build up a strong foundation for your research project.

Table of contents

Step 1: choose your topic, step 2: identify a problem, step 3: formulate research questions, step 4: create a research design, step 5: write a research proposal, other interesting articles.

First you have to come up with some ideas. Your thesis or dissertation topic can start out very broad. Think about the general area or field you’re interested in—maybe you already have specific research interests based on classes you’ve taken, or maybe you had to consider your topic when applying to graduate school and writing a statement of purpose .

Even if you already have a good sense of your topic, you’ll need to read widely to build background knowledge and begin narrowing down your ideas. Conduct an initial literature review to begin gathering relevant sources. As you read, take notes and try to identify problems, questions, debates, contradictions and gaps. Your aim is to narrow down from a broad area of interest to a specific niche.

Make sure to consider the practicalities: the requirements of your programme, the amount of time you have to complete the research, and how difficult it will be to access sources and data on the topic. Before moving onto the next stage, it’s a good idea to discuss the topic with your thesis supervisor.

>>Read more about narrowing down a research topic

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So you’ve settled on a topic and found a niche—but what exactly will your research investigate, and why does it matter? To give your project focus and purpose, you have to define a research problem .

The problem might be a practical issue—for example, a process or practice that isn’t working well, an area of concern in an organization’s performance, or a difficulty faced by a specific group of people in society.

Alternatively, you might choose to investigate a theoretical problem—for example, an underexplored phenomenon or relationship, a contradiction between different models or theories, or an unresolved debate among scholars.

To put the problem in context and set your objectives, you can write a problem statement . This describes who the problem affects, why research is needed, and how your research project will contribute to solving it.

>>Read more about defining a research problem

Next, based on the problem statement, you need to write one or more research questions . These target exactly what you want to find out. They might focus on describing, comparing, evaluating, or explaining the research problem.

A strong research question should be specific enough that you can answer it thoroughly using appropriate qualitative or quantitative research methods. It should also be complex enough to require in-depth investigation, analysis, and argument. Questions that can be answered with “yes/no” or with easily available facts are not complex enough for a thesis or dissertation.

In some types of research, at this stage you might also have to develop a conceptual framework and testable hypotheses .

>>See research question examples

The research design is a practical framework for answering your research questions. It involves making decisions about the type of data you need, the methods you’ll use to collect and analyze it, and the location and timescale of your research.

There are often many possible paths you can take to answering your questions. The decisions you make will partly be based on your priorities. For example, do you want to determine causes and effects, draw generalizable conclusions, or understand the details of a specific context?

You need to decide whether you will use primary or secondary data and qualitative or quantitative methods . You also need to determine the specific tools, procedures, and materials you’ll use to collect and analyze your data, as well as your criteria for selecting participants or sources.

>>Read more about creating a research design

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Finally, after completing these steps, you are ready to complete a research proposal . The proposal outlines the context, relevance, purpose, and plan of your research.

As well as outlining the background, problem statement, and research questions, the proposal should also include a literature review that shows how your project will fit into existing work on the topic. The research design section describes your approach and explains exactly what you will do.

You might have to get the proposal approved by your supervisor before you get started, and it will guide the process of writing your thesis or dissertation.

>>Read more about writing a research proposal

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.

Methodology

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

 Statistics

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

Research bias

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

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September 8, 2021

Explaining How Research Works

We’ve heard “follow the science” a lot during the pandemic. But it seems science has taken us on a long and winding road filled with twists and turns, even changing directions at times. That’s led some people to feel they can’t trust science. But when what we know changes, it often means science is working.

Explaining the scientific process may be one way that science communicators can help maintain public trust in science. Placing research in the bigger context of its field and where it fits into the scientific process can help people better understand and interpret new findings as they emerge. A single study usually uncovers only a piece of a larger puzzle.

Questions about how the world works are often investigated on many different levels. For example, scientists can look at the different atoms in a molecule, cells in a tissue, or how different tissues or systems affect each other. Researchers often must choose one or a finite number of ways to investigate a question. It can take many different studies using different approaches to start piecing the whole picture together.

Sometimes it might seem like research results contradict each other. But often, studies are just looking at different aspects of the same problem. Researchers can also investigate a question using different techniques or timeframes. That may lead them to arrive at different conclusions from the same data.

Using the data available at the time of their study, scientists develop different explanations, or models. New information may mean that a novel model needs to be developed to account for it. The models that prevail are those that can withstand the test of time and incorporate new information. Science is a constantly evolving and self-correcting process.

Scientists gain more confidence about a model through the scientific process. They replicate each other’s work. They present at conferences. And papers undergo peer review, in which experts in the field review the work before it can be published in scientific journals. This helps ensure that the study is up to current scientific standards and maintains a level of integrity. Peer reviewers may find problems with the experiments or think different experiments are needed to justify the conclusions. They might even offer new ways to interpret the data.

It’s important for science communicators to consider which stage a study is at in the scientific process when deciding whether to cover it. Some studies are posted on preprint servers for other scientists to start weighing in on and haven’t yet been fully vetted. Results that haven't yet been subjected to scientific scrutiny should be reported on with care and context to avoid confusion or frustration from readers.

We’ve developed a one-page guide, "How Research Works: Understanding the Process of Science" to help communicators put the process of science into perspective. We hope it can serve as a useful resource to help explain why science changes—and why it’s important to expect that change. Please take a look and share your thoughts with us by sending an email to  [email protected].

Below are some additional resources:

• Discoveries in Basic Science: A Perfectly Imperfect Process
• When Clinical Research Is in the News
• What is Basic Science and Why is it Important?
• ​ What is a Research Organism?
• What Are Clinical Trials and Studies?
• Basic Research – Digital Media Kit
• Decoding Science: How Does Science Know What It Knows? (NAS)
• Can Science Help People Make Decisions ? (NAS)

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• Jul 9, 2017

What are Related studies in research? How it is helpful for all Ph.D and master level students?

Updated: Jun 11, 2020

Once you all set with research field/domain/area in next step you need to know about recent trends and research going on particular domain. Before starting with your research or project work to understand feasibility of research/project related study or review of literature need to be done.

Here we will see what are related studies/ literature review for completing your project/research work.

Usually, related studies is about reviewing or studying existing works carried out in your project/research field. Especially, for Ph.D candidate’s related works is important constraint since pave path to entire research process. Related studies can be taken from journals, magazines, website links, government reports and other source.

Here your related studies need to provide

What’s problem in existing in selected domain?

What are the methods developed or adopted?

Which technique exhibit excellent outcome and effective?

Once you find answer for all this question rest will be easy! To calculate the feasibility and methodology need to be adopted for completion of your project.

In final stage of both Ph.D and Master level you need to submit dissertation/thesis which is documentation of research work. In that related studies offers need to be included to justify your novelty of your research work. Even you can point out research gap of selected research field why you selected this domain. If you clearly mention in your documentation and presentation you complete research/project.

Related: Thesis writing help in India

#definitionforresearch #Inresearch #relatedstudies #researchfield #literaturereview #thesis #academic #dissertation #PhDcandidate

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How to Write the Rationale of the Study in Research (Examples)

What is the Rationale of the Study?

The rationale of the study is the justification for taking on a given study. It explains the reason the study was conducted or should be conducted. This means the study rationale should explain to the reader or examiner why the study is/was necessary. It is also sometimes called the “purpose” or “justification” of a study. While this is not difficult to grasp in itself, you might wonder how the rationale of the study is different from your research question or from the statement of the problem of your study, and how it fits into the rest of your thesis or research paper. 

The rationale of the study links the background of the study to your specific research question and justifies the need for the latter on the basis of the former. In brief, you first provide and discuss existing data on the topic, and then you tell the reader, based on the background evidence you just presented, where you identified gaps or issues and why you think it is important to address those. The problem statement, lastly, is the formulation of the specific research question you choose to investigate, following logically from your rationale, and the approach you are planning to use to do that.

Table of Contents:

How to write a rationale for a research paper , how do you justify the need for a research study.

• Study Rationale Example: Where Does It Go In Your Paper?

The basis for writing a research rationale is preliminary data or a clear description of an observation. If you are doing basic/theoretical research, then a literature review will help you identify gaps in current knowledge. In applied/practical research, you base your rationale on an existing issue with a certain process (e.g., vaccine proof registration) or practice (e.g., patient treatment) that is well documented and needs to be addressed. By presenting the reader with earlier evidence or observations, you can (and have to) convince them that you are not just repeating what other people have already done or said and that your ideas are not coming out of thin air. 

Once you have explained where you are coming from, you should justify the need for doing additional research–this is essentially the rationale of your study. Finally, when you have convinced the reader of the purpose of your work, you can end your introduction section with the statement of the problem of your research that contains clear aims and objectives and also briefly describes (and justifies) your methodological approach. 

When is the Rationale for Research Written?

The author can present the study rationale both before and after the research is conducted. 

• Before conducting research : The study rationale is a central component of the research proposal . It represents the plan of your work, constructed before the study is actually executed.
• Once research has been conducted : After the study is completed, the rationale is presented in a research article or  PhD dissertation  to explain why you focused on this specific research question. When writing the study rationale for this purpose, the author should link the rationale of the research to the aims and outcomes of the study.

What to Include in the Study Rationale

Although every study rationale is different and discusses different specific elements of a study’s method or approach, there are some elements that should be included to write a good rationale. Make sure to touch on the following:

• A summary of conclusions from your review of the relevant literature
• What is currently unknown (gaps in knowledge)
• Inconclusive or contested results  from previous studies on the same or similar topic
• The necessity to improve or build on previous research, such as to improve methodology or utilize newer techniques and/or technologies

There are different types of limitations that you can use to justify the need for your study. In applied/practical research, the justification for investigating something is always that an existing process/practice has a problem or is not satisfactory. Let’s say, for example, that people in a certain country/city/community commonly complain about hospital care on weekends (not enough staff, not enough attention, no decisions being made), but you looked into it and realized that nobody ever investigated whether these perceived problems are actually based on objective shortages/non-availabilities of care or whether the lower numbers of patients who are treated during weekends are commensurate with the provided services.

In this case, “lack of data” is your justification for digging deeper into the problem. Or, if it is obvious that there is a shortage of staff and provided services on weekends, you could decide to investigate which of the usual procedures are skipped during weekends as a result and what the negative consequences are. 

In basic/theoretical research, lack of knowledge is of course a common and accepted justification for additional research—but make sure that it is not your only motivation. “Nobody has ever done this” is only a convincing reason for a study if you explain to the reader why you think we should know more about this specific phenomenon. If there is earlier research but you think it has limitations, then those can usually be classified into “methodological”, “contextual”, and “conceptual” limitations. To identify such limitations, you can ask specific questions and let those questions guide you when you explain to the reader why your study was necessary:

Methodological limitations

• Did earlier studies try but failed to measure/identify a specific phenomenon?
• Was earlier research based on incorrect conceptualizations of variables?
• Were earlier studies based on questionable operationalizations of key concepts?
• Did earlier studies use questionable or inappropriate research designs?

Contextual limitations

• Have recent changes in the studied problem made previous studies irrelevant?
• Are you studying a new/particular context that previous findings do not apply to?

Conceptual limitations

• Do previous findings only make sense within a specific framework or ideology?

Study Rationale Examples

Let’s look at an example from one of our earlier articles on the statement of the problem to clarify how your rationale fits into your introduction section. This is a very short introduction for a practical research study on the challenges of online learning. Your introduction might be much longer (especially the context/background section), and this example does not contain any sources (which you will have to provide for all claims you make and all earlier studies you cite)—but please pay attention to how the background presentation , rationale, and problem statement blend into each other in a logical way so that the reader can follow and has no reason to question your motivation or the foundation of your research.

Background presentation

Since the beginning of the Covid pandemic, most educational institutions around the world have transitioned to a fully online study model, at least during peak times of infections and social distancing measures. This transition has not been easy and even two years into the pandemic, problems with online teaching and studying persist (reference needed) . 

While the increasing gap between those with access to technology and equipment and those without access has been determined to be one of the main challenges (reference needed) , others claim that online learning offers more opportunities for many students by breaking down barriers of location and distance (reference needed) .  

Rationale of the study

Since teachers and students cannot wait for circumstances to go back to normal, the measures that schools and universities have implemented during the last two years, their advantages and disadvantages, and the impact of those measures on students’ progress, satisfaction, and well-being need to be understood so that improvements can be made and demographics that have been left behind can receive the support they need as soon as possible.

Statement of the problem

To identify what changes in the learning environment were considered the most challenging and how those changes relate to a variety of student outcome measures, we conducted surveys and interviews among teachers and students at ten institutions of higher education in four different major cities, two in the US (New York and Chicago), one in South Korea (Seoul), and one in the UK (London). Responses were analyzed with a focus on different student demographics and how they might have been affected differently by the current situation.

How long is a study rationale?

In a research article bound for journal publication, your rationale should not be longer than a few sentences (no longer than one brief paragraph). A  dissertation or thesis  usually allows for a longer description; depending on the length and nature of your document, this could be up to a couple of paragraphs in length. A completely novel or unconventional approach might warrant a longer and more detailed justification than an approach that slightly deviates from well-established methods and approaches.

Consider Using Professional Academic Editing Services

Now that you know how to write the rationale of the study for a research proposal or paper, you should make use of Wordvice AI’s free AI Grammar Checker , or receive professional academic proofreading services from Wordvice, including research paper editing services and manuscript editing services to polish your submitted research documents.

You can also find many more articles, for example on writing the other parts of your research paper , on choosing a title , or on making sure you understand and adhere to the author instructions before you submit to a journal, on the Wordvice academic resources pages.

What is a related work? A typology of relationships in research literature

• Original Research
• Open access
• Published: 09 January 2023
• Volume 201 , article number  24 , ( 2023 )

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• Shayan Doroudi   ORCID: orcid.org/0000-0002-0602-1406 1  

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An important part of research is situating one’s work in a body of existing literature, thereby connecting to existing ideas. Despite this, the various kinds of relationships that might exist among academic literature do not appear to have been formally studied. Here I present a graphical representation of academic work in terms of entities and relations, drawing on structure-mapping theory (used in the study of analogies). I then use this representation to present a typology of operations that could relate two pieces of academic work. I illustrate the various types of relationships with examples from medicine, physics, psychology, history and philosophy of science, machine learning, education, and neuroscience. The resulting typology not only gives insights into the relationships that might exist between static publications, but also the rich process whereby an ongoing research project evolves through interactions with the research literature.

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Understanding Research Dynamics

The evolution of knowledge within and across fields in modern physics

Introduction

Avoid common mistakes on your manuscript.

1 Introduction

An important part of the research process is literature search: identifying prior work that is of relevance to the present idea being investigated. In many cases, this is an activity that a researcher may defer until writing up the results of the project, in which case, it is primarily an activity one does because one “has to” rather than an activity that can substantially change the course of the research. In some cases, whether due to negligence or the difficulty of finding related works, a researcher may never come across the fact that someone had previously tackled the same problem or made a similar discovery, and perhaps only years later (if ever) it may be realized (Merton, 1963 ; Ke et al., 2015 ; Sacks, 2002 ). But at its best, this is an activity that leads to new insights into the research problem, generates new ideas, and alters the course of the research. In fact, in some cases, searching for related work can become the research process itself; through connecting various pieces of research literature alone, one can discover previously undiscovered public knowledge (Swanson, 1986 ).

Despite the importance of prior literature in the research process, there has been little effort, if any, dedicated to developing a typology of related works, that is, a typology of relationships that might exist among different pieces of research literature. (Of course, it is entirely possible that such a typology has been constructed, but I have missed it due to an inadequate search of the literature!) In this paper, I propose such a typology to help us better understand the kinds of prior work that might have bearing on a research project. I first present a form of knowledge representation that can theoretically be used to represent any piece of research literature or research project. I then present a typology of relationships that can connect two pieces of research in terms of operations that can apply to the two representations, thereby resulting in a representation of the relationship. I will demonstrate the various operations and how they might be employed with a variety of examples from different fields, including medicine, physics, psychology, history and philosophy of science, machine learning, education, and neuroscience. The same form of representation applies to both published research literature and research projects or topics, whether nascent or fully-fledged. In fact, some of the relationships discussed below make more sense in the context of research projects (or broader research agendas) that can dynamically evolve as relevant literature is encountered, rather than research papers whose underlying representations are static. As such, I will use the terms publication, literature, project, and topic somewhat interchangeably.

The specific representation I use is borrowed from structure-mapping theory (Gentner, 1983 ; Falkenhainer et al., 1989 ), which was originally developed as a way to structurally represent analogies. Structure-mapping theory is particularly useful here, both because we can use it when discussing abstractions and analogies, and because the underlying representation can also handle other types of relationships among literature. I could have instead used other forms of knowledge representation, such as conceptual graphs (Sowa, 1976 ), entailment meshes (Pask et al., 1975 ; Pask, 1988 ), or category theoretic representations like ologs (Spivak & Kent, 2012 ). There may be relative advantages to each of these, but the representation used here is both simple and powerful enough to clearly demonstrate the typology. The exact choice of representation may need further consideration if one wants to perform inference on the representations or utilize them in information retrieval tools. For now, we are not concerned with how one might construct these representations or even the fidelity with which it is possible (though we revisit these questions in Sect. 6 ). The possibility that research projects could in theory be represented in the way described below is sufficient to formulate the typology.

While the form of representation and typology presented below may not be directly used in information retrieval tools, I contend that they may be useful in guiding the overall direction that research on such tools might take (e.g., what kinds of papers should a tool search for?). Moreover, the typology may provide some clarity to researchers going through the literature search process for a project. Constructing a graphical representation of one’s paper may be a useful exercise, and can possibly illuminate different searches that are needed to find related work. Seeing how the representation of one’s paper changes over time can also be a useful documentation of the research and literature search process. Beyond such potential practical uses of the typology, I believe it can simply be beneficial to understand the various ways in which one product of research may relate to another. If alongside the physical and social worlds, the world of research literature “also qualifies as an endless frontier” (Swanson, 1986 , p. 115), then our efforts to make sense of the former should be accompanied by efforts to make sense of the latter.

2 Related work on related work

Related work on related work exists in a number of different disciplines. Literature search is central to all research after all! Fittingly, the typology we develop combines research that exists in different, largely isolated, strands.

In the information sciences and medicine, work on “literature-based discovery” (LBD), dating back to Swanson ( 1986 ), is concerned with making new scientific discoveries by establishing novel connections between different pieces of literature. Swanson ( 1986 ) describes literature-based discovery as a form of scientific discovery that takes place in Karl Popper’s world 3—the “world of the products of the human mind” (Popper, 1978 , p. 144)—whereby search functions are likened to scientific theories and the “logic of undiscovered public knowledge” (p. 116) is analogous to the logic of scientific discovery. In doing so, Swanson ( 1986 ) made a contribution to the philosophy of science, though it seems to have not been recognized in the philosophy of science community. A number of different information-retrieval techniques have been proposed to aid in LBD (Smalheiser, 2017 ; Sebastian et al., 2017 ). Some authors have presented categorizations of different types of “undiscovered public knowledge” or different forms of LBD (Davies, 1989 ; Smalheiser, 2017 ). While these categorizations can be useful in aiding researchers who want to perform literature-based discovery, our typology has a somewhat broader scope in that not all related work necessarily results in LBD. LBD is one potential use case of literature search, and its various methods span across the relationships in the typology presented here, as discussed below.

More broadly, in information retrieval, the notion of “relevance” is central, and some researchers have tried to develop theories around what relevance is—typically conceived of as the relationship between an information need and a document (Saracevic, 1975 , 2016 ; Huang & Soergel, 2013 ). Green ( 1995 ) and Huang and Soergel ( 2013 ) pointed out that most discussions of relevance are around “topic matching,” but that this is only one form of relevance. Green and Bean ( 1995 ) then constructed a typology of different notions of relevance, and Huang ( 2009 ) expanded this to a typology consisting of over 200 notions of relevance. Huang ( 2009 ) considers three broad categories of relationships: (1) “What functional role a piece of information plays in the overall structure of a topic,” (2) “How information contributes to users’ reasoning about a topic,” and (3) “How information connects to a topic semantically” (p. 411). As examples of functional roles, an information source might present a solution to a problem, the cause of an effect, etc. As examples of contributing to reasoning, an information source might provide an analogy to the topic or might be used to deduce something about the topic. While this work is very relevant to the present paper, there are two key differences. First, their work is about the broader concept of relevance between information and needs, while this paper focuses on relevance in academic literature. One would expect that many of the kinds of broader relevance typologies would also hold for research publications, but given the particularities of literature search and the role it plays in the broader process of scientific research, it seems worth studying in its own right. Second, these prior typologies largely focus on the variety of semantic relationships between two topics, while the approach we present here views relevance in terms of operations that operate on knowledge representations of topics. In this sense, the typology I present here can express how to relate different research topics in terms of a small number of mathematically precise operations (that are hopefully easy to remember), rather than a plethora of different possible semantic relationships. The two approaches are complementary, but I contend that the approach taken here is more useful for conceptualizing the evolution of a research project over time.

In computer science and artificial intelligence, there has been a recent thread of work on citation recommendation, concerned with identifying relevant citations given a piece of text and possibly other meta-data (e.g., authors, etc.) (Strohman et al., 2007 ; Liang et al., 2011 ; Ren et al., 2014 ; Bhagavatula et al., 2018 ). Interestingly, this work has not really considered automated techniques for LBD, and it does not cite the vast literature on LBD or on relevance. Indeed, most of the work in this area is concerned with topic matching (finding citations that topically overlap). One notable exception is work by Chan et al. ( 2018 ) and Kang et al. ( 2022 ). Chan et al. ( 2018 ) presented a technique that combines crowdsourcing and machine learning to find analogies between different papers. They utilize a “soft” relational schema, a very coarse-grained representation of a research paper; they explicitly avoid using representations like the one described below, because they can be very difficult to construct for many publications. Kang et al. ( 2022 ) built on this work by training deep learning algorithms on the crowdsourced representations of abstracts to be able to automatically detect the “purpose” and “mechanism” of a paper. An analogy in this context is two papers that have a similar underlying purpose but achieve that purpose through a different mechanism. Kang et al. ( 2022 ) used this to prototype an analogical search engine for scientific literature. While their representation may be useful for LBD, I contend that it can only capture certain kinds of relationships between papers, and, as I discuss further below, some of their methods do not appear to actually look for analogies as per the typology we develop below. As such, our typology can potentially be useful in classifying the different kinds of relationships that various existing LBD and citation recommendation methods can uncover, and the kinds of relationships that they cannot.

3 A representation of a research project

In our representation, a research project or publication \(P \in \Pi \) is represented as a set of entities and relations, \(P = (E, \mathcal {R})\) . An entity conceptually represents any specific topic of relevance to the project, usually expressed as a noun or a noun phrase (e.g., DNA, the civil rights movement, high blood pressure, theorems). Notice that entities can come in different degrees of specificity (e.g., theorems vs. Gödel’s first incompleteness theorem); the important thing is that entities across all topics and publications are represented at the same level of granularity. We allow entities to be hierarchically defined as functions of other entities (e.g., the entity “volume of a cup” can be thought of as the “volume of” function applied to “cup”).

Relations define a relationship between some number of entities, such that the predicate \(R(e_1, e_2, \dots , e_n)\) indicates that \(e_1\) , \(e_2\) , ..., \(e_n\) are related as specified by the relation R . Binary relations are perhaps the most common. For example, in the sentence “stress causes high blood pressure”, “causes” is a relation that takes relates two entities (in this case, “stress” and “high blood pressure”). We might represent this as causes (stress, high blood pressure). As an example of a tertiary relation, consider the sentences “ribosomes translate mRNA into sequences of amino acids” and “Arab translators translated Greek texts into Arabic translations”; they could both be said to use the relation x-translates-y-into-z (though if we think the word “translates” has a very different semantic meaning in these two cases, we could suggest there are two different relations at play here). We also allow for unary relations; for example, “blood pressure is high” can be represented as is-high (blood pressure). Unary relations are called attributes in structure-mapping theory and they effectively allow assigning adjectives to entities; for example, high (blood pressure) would mean “high blood pressure.” With slight abuse of notation, I will use unary relations both as relations (e.g., is-high (blood pressure)) and as attributes (e.g., high (blood pressure)). Finally, we allow for higher-order relations, which take relations as input instead of, or in addition to, entities. causes is a higher-order relation because we can say, for example, causes ( provided ( treatment (subjects), New Curriculum), learn-more-than ( treatment (subjects), control (subjects))).

As with Gentner’s ( 1983 ) structure-mapping theory, the classification of relationships between research has more to do with the structure of the representation (i.e., the presence of certain entities and relations) rather than the semantic meaning of the nodes. However, semantics still play an important role in informing whether a particular relationship is sensible or important in a particular situation. That is, someone without a semantic understanding of a given domain can still apply the operators described below in the sense that one can execute \(4 + 7\) and \(4 \times 7\) , without regard to which operation makes more sense in the given situation. Furthermore, one aspect of semantics is necessary in the application of some of the operators. Namely, there is a general relation, “is a” (or “is an instance of”), which can capture any situation where a particular entity can be categorized as a special case or instance of another entity. Consistent with earlier work on knowledge representation, we will refer to this relation as is-a (Brachman, 1983 ). For example, is-a (Gödel’s first incompleteness theorem, theorem) and is-a (the civil rights movement, historical occurrence). A single entity can be an instance of many entities (e.g., a cat can be considered an animal, a pet, and an Internet phenomenon). The is-a operator is also reflexive (e.g., is-a (cat, cat)). Finally, with slight abuse of notation, we will also have is-a be a higher-order relation that can designate when one relation is an instance of another. For example, is-a ( holds (person, ball), possesses (person, object)), because holding something is a special case of possessing it and a ball is an object. Some of the operators below can only be applied with an understanding of what things are instances of other things; however, when the relationship is more abstract, sometimes even a domain expert will not readily see these connections.

The set of entities and relations that are used in the representation of a research publication will likely not include all entities and relations included in that publication (e.g., all nouns and verbs), but rather they should include the concepts that are focal to that publication. Of course, that is somewhat subjective, but a useful heuristic is to include all entities and relations that are involved in a system of relationships that might be worth providing citations in reference to, as well as any new entities and relations that are being introduced in the paper. For example, in a paper that runs an experiment with seven conditions, the number of seven is probably not an entity that should be included, but in Miller’s ( 1956 ) paper on working memory capacity or a paper on the religious symbolism of the number seven, it likely should be included.

As suggested above, there is no single correct way to represent a research project. In fact, there can be multiple different views of a research project, which induce different representations. Each of these views can be more or less useful depending on how they are to be used. Moreover, even simple relations can be expressed in different ways. For our purposes, there is a relationship between two research projects if there is at least some view of each that permits the relationship. Since we are not concerned with the practical side of how to best represent projects here, we do not worry about how one would go about discovering the “right” views. In practice though, seeing two related papers from the “wrong” viewpoint is one reason why researchers and information retrieval tools might not notice an important relationship.

We can represent these representations graphically using a graph-like structure as shown in Fig.  1 a. Boxes indicate entities, and the text outside of boxes indicate relations. The arrows coming out of a relation point to its arguments in order from left to right. Nested boxes (e.g., “some part of a new thing”) show hierarchically defined entities. For simplicity, we show binary relations as labeled directed edges for asymmetric relations and labeled undirected edges for symmetric relations, as shown in Fig.  1 b.

Examples of how to graphically represent research projects/publications. a An example of a tertiary relation with three entities that would be read as “An old thing can become some part of a new thing through some process.” There are also two unary relations: is-old and is-new . b Two examples of binary relations. The causes relation is asymmetric while the correlated relation is symmetric

This representation could be couched in the language of model-theoretic philosophy of science (Suppes, 1957 , 1960 ), in particular using the partial structures formalism (French, 2000 ; Da Costa & French, 1990 ), which is also often expressed in terms of entities and (partial) relations. Doing so may be appealing since it would connect literature search to an existing framework for discussing scientific theories. The partial structures formalism has also been used in describing analogies and abstractions in science and provides a way to formalize research undergoing change. However, the ideas presented here not only apply to formal scientific theories, but also to non-scientific literature and more nascent representations of scientific topics, and I do not want to associate the typology presented here with a particular interpretation of scientific theories.

4 A typology of related works

We can now describe the different kinds of relationships that can exist between a research project and prior work. Suppose we have a research project \(P = (E_P, \mathcal {R}_P)\) and a piece of literature \(L = (E_L, \mathcal {R}_L)\) . We assume that P is an ongoing project that can potentially change, while L is already published literature and hence static. Below we describe a set of operations that can be used to describe the relationship between P and L . These operations are functions that take the representations of P and L as inputs and output a representation \(\rho \) of the relationship between P and L (as defined by the operation). Since we allow for composing these operations in sequence, some of the operations will actually take as input P , L , and our current representation of the relationship between the two ( \(\rho _i\) ), and will output a modified representation of the relationship ( \(\rho _{i+1}\) ). Moreover, when applying multiple operations in sequence, we may want to keep track of the ongoing relationship, which we can do by merging multiple relationships (i.e., taking the union of entities and the union of relations in the sequence of relationships). After each operation is applied, we can also potentially modify P Footnote 1 , thereby modifying the relationship between P and L as well. The series of operations and modifications reflects the iterative and influential nature of literature search in the research process. The operations, described below, are called intersection, interpretation, expansion, abstraction, reification, analogy, and substitution. Table  1 lists some basic information about the operations, which may be useful when reading the sections below. I do not make any claims that the typology presented here is complete. There might be other operations, or perhaps more useful categorizations of the operations presented here, which can be elucidated upon in future work. In what follows, I will describe each of the operators in words as well as mathematical formalism when needed; readers can safely skip the mathematical formalism and still grasp the key ideas.

4.1 Intersection

The first and probably most prevalent operation is intersection , which outputs a subset of entities that are shared by P and L and a subset of relations shared by the two. Specifically, intersection outputs a representation \(\rho = (E_{PL}, \mathcal {R}_{PL})\) , where \(E_{PL} \subseteq E_P \cap E_L\) and \(\mathcal {R}_{PL} \subseteq \mathcal {R}_P \cap \mathcal {R}_L\) . The exact subset depends on what is determined to be relevant between the two representations. A simple special case of this would be when P and L share just a single entity. For example, suppose P and L both have to do with DNA, but one is about DNA to solve computational problems (Adleman, 1994 ) and the other is about DNA vaccines for coronavirus (Callaway, 2020 ). It is unlikely that these publications have other entities in common. In many such cases, publications are not worth citing, and such an intersection would actually not be relevant. A relationship is worth noting when the degree of overlap is large enough; this can be measured by associating some degree of importance to each entity in P and taking the sum (or some non-linear function) of importances across all the entities in \(\rho \) .

In some cases, overlap in a single entity may be enough to warrant citation or even to alter the course of a research project. For example, one of the examples that Swanson ( 1986 ) gives for undiscovered public knowledge has to do with a potential research publication on the “all swans are white hypothesis,” a hypothesis that states that all swans are white. This hypothesis could be supported inductively if there was a lack of any documented evidence of black swans. As Swanson ( 1986 ) says:

Suppose for the sake of argument that scientists living in a remote part of the world were to publish, in a local wildlife journal, some observations about a family of black swans living on a nearby lake. We suppose further that the report comes from a half-dozen people who are reliable observers, and that they are unaware that other people in the world think that all swans are white. (p. 109)

As shown in Fig.  2 , the potential all-swans-are-white hypothesis publication ( P ) is represented using three entities and two relations, although it can be interpreted as two entities and the relationship between them (“the all-swans-are-white hypothesis is proved by the fact that there is no evidence of black swans”); on the other hand, the article in the wildlife journal ( L ) only concerns itself with black swans and possibly other topics of local interest. As such, the two articles overlap in only one entity: black swans. It just so happens that the existence of black swans is a critical refutation of the theory (i.e., “evidence of black swans” is a very important entity in P ), and so this single article can change the course of the research project (e.g., the authors publish a refutation of the all-swans-are-white hypothesis rather than a proclamation of it).

Notice that the intersection of the two articles was “black swans” not “evidence of black swans.” (The wildlife journal is not trying to present evidence of black swans; it is discussing a piece of wildlife whose existence they never called into question.) The intersection of “black swans” by itself is not necessarily meaningful. Another paper that discusses black swans but provides no evidence for them is of less value to P . How then can we capture the obvious fact that L presents evidence of black swans, even though it is not captured in its representation? The answer lies in the interpretation operation.

Swanson’s ( 1986 ) black swans example as an example of intersection

4.2 Interpretation

An interpretation takes an existing relationship between P and L and adds additional entities and/or relations from P (not included in L ) that can help interpret the current relationship. Namely, if \(\rho _{i} = (E_{\rho _{i}}, \mathcal {R}_{\rho _{i}})\) is the output of a previous operation, then \(\rho _{i+1} = (E_{\rho _{i}} \cup E_{PS}, \mathcal {R}_{\rho _{i}} \cup \mathcal {R}_{PS})\) , where \(E_{PS} \subseteq E_P \setminus E_L\) and \(\mathcal {R}_{PS} \subseteq \mathcal {R}_P \setminus \mathcal {R}_L\) . (I use PS and LS as subscripts to denote subsets of P and L .) A natural use of interpretation is to apply it after an intersection. For example, in the black swans example above, we can interpret the intersection of P and L as being “evidence of black swans.” Clearly, L does present evidence of black swans, but it was not interpreted that way until it was interpreted in light of P . Notice that if a researcher conducting project P were to construct the representation of L , they might do so according to their interpretation, whereby “evidence of black swans” would appear in L . Therefore, interpretation steps may often be implicit or hidden in the particular view of L that a researcher adopts. In this paper, I try to represent prior work in a way that is faithful to the original authors’ meaning, though we must recognize that views of prior work will always be informed by our worldview.

4.3 Expansion

An expansion takes an existing relationship between P and L and adds additional entities and/or relations from L (not included in P ) to potentially expand the content of P or to bring new insights into the picture. Notice that structurally, the expansion operation is equivalent to the interpretation operation with P and L swapped; however, semantically, the two are often quite different. An expansion will often result in a change in P . As a result, it makes the most sense when P is an ongoing research topic (or a follow-up investigation to published work), rather than a final publication. Once P has changed to \(P'\) to incorporate the new entities and relations, what was once an expansion between P and L may be viewed as an intersection between \(P'\) and L . Therefore expansions play developmental roles in the research process, which are often not captured in publications. That is, many research projects may have changed course as a result of particular publications, but the final publication may only refer to the relationship to prior work at the time of publication, rather than the developmental influence of that prior work.

For example, in the related works section above, I acknowledged connections to Chan et al. ( 2018 ); these connections would be viewed as intersections (e.g., both papers have to do with academic literature, analogies, knowledge representation, etc.). However, what I did not state was that reading Chan et al. ( 2018 ) led me to read about structure-mapping theory (Gentner, 1983 ), and the two publications combined (and considered in relation to Swanson ( 1986 )) resulted in the beginnings of this paper. That is, before this paper was even conceived of, the aforementioned prior works resulted in a series of expansions, which turned into the present piece only after many iterations, which involved a series of other operations applied to various publications (some of which are cited, and some of which may not be). This reflects the role of literature search in the messy process that is research. I suspect that researchers rarely document the series of expansions (and other steps) that lead to the final state of a publication.

In fact, at times, some prior work may only play the role of a stepping stone to discovering other, more relevant, prior works. That is, an expansion of P by \(L_1\) may result in an exploration of the new entities in the expansion, which results in discovering \(L_2\) , which intersects with P . At that point, \(L_1\) may no longer really be relevant; that is, the extent of \(L_1\) ’s relevance may be better captured by \(L_2\) .

One broad category of expansions falls under Swanson’s ( 1986 ) second example—“A Missing Link in the Logic of Discovery” or what is often referred to as the ABC model. As Swanson ( 1986 ) originally expressed it:

Suppose the following two reports are published separately and independently, the authors of each report being unaware of the other report: (i) a report that process A causes the result B, and (ii) a separate report that B causes the result C. It follows of course that A leads to, causes, or implies C. That is, the proposition that A causes C objectively exists, at least as a hypothesis. (p. 110)

Swanson gave a specific example of a discovery he made (the first of his several literature-based discoveries in medicine): connecting (a) literature on how fish oil causes a reduction of blood viscosity with (b) literature on how reducing blood viscosity leads to an improvement in symptoms of Raynaud’s syndrome. The intersection of these two literatures is the entity “reduction of blood viscosity.” An expansion adds the causal link to “relief from Raynaud’s syndrome” and that link is then interpreted in light of the connection to “dietary fish oil.” Connecting these two literatures via these steps can result in a change in P as shown in Fig.  3 . Notice that the addition of a new causal relation between dietary fish oil and relief from Raynaud’s syndrome was inferred from this expansion, but had never been experimentally shown or even published about. Two years later, a clinical trial independently confirmed this hypothesis (Swanson & Smalheiser, 1996 ).

Swanson’s ( 1986 ) example of the ABC model as an example of expansion

Literature-based discovery often involves this kind of linking between two “non-interactive literatures,” literatures that are rarely, if ever, cited in the same publications (Swanson & Smalheiser, 1996 ). However, expansion need not always be between two non-interactive literatures. Indeed, researchers may often be unaware of highly relevant work within their own research community (or other interactive literatures) that build upon the concepts they are investigating. Such cases can often be caught by the researchers themselves when conducting a more expansive literature review, or by reviewers during the peer review process, but likely often go undetected.

4.4 Abstraction

An abstraction applies if P contains a subset of entities and relations that are instances of entities and relations in L . In other words, we have an abstraction when L contains a more abstract or generalized representation of part of P . An abstraction can still consist of concrete entities and relations as long as they are more general or more abstract than the entities and relations in P (e.g., as suggested above is-a (cat, animal), is-a (cat, Internet phenomenon), and is-a (the civil rights movement, historical occurrence) can all be single entity abstractions).

Describing an abstraction mathematically requires a bit more care than for previous operations since abstractions must be semantically “consistent” across the entities and relations involved. Formally, an abstraction applies if there is a subset of entities and relations in P —say \(E_{PS} \subseteq E_P\) and \(\mathcal {R}_{PS} \subseteq \mathcal {R}_P\) —and a subset of entities and relations in L —say \(E_{LS} \subseteq E_L\) and \(\mathcal {R}_{LS} \subseteq \mathcal {R}_L\) —such that the following four conditions hold:

For all \(e \in E_{PS}\) , there exists a \(\tilde{e} \in E_{LS}\) such that e is an instance of \(\tilde{e}\) .

For all \(R \in \mathcal {R}_{PS}\) , there exists a \(\tilde{R} \in \mathcal {R}_{LS}\) such that R is an instance of \(\tilde{R}\) .

For all \(R \in \mathcal {R}_{PS}\) , if \(R(e_1, e_2, \dots , e_n)\) , then \(\tilde{R}(\tilde{e}_1, \tilde{e}_2, \dots , \tilde{e}_n)\) , where \(R, e_1, \dots , e_n\) are instances of \(\tilde{R}, \tilde{e},_1 \dots , \tilde{e}_n\) respectively.

At least some \(e \not = \tilde{e}\) or some \(R \not = \tilde{R}\) .

The last condition is required to make sure the abstraction is not simply mapping identical representations (in which case it would just be an intersection). The resulting representation is \(\rho = (E_{PS} \cup E_{LS}, \mathcal {R}_{PS} \cup \mathcal {R}_{LS} \cup \textsc {is-a})\) , where \(\textsc {is-a}(e, \tilde{e})\) and \(\textsc {is-a}(R(e_1, e_2, \dots , e_n), \tilde{R}(\tilde{e}_1, \tilde{e}_2, \dots , \tilde{e}_n))\) , for all e , \(\tilde{e}\) , R , and \(\tilde{R}\) as defined in the conditions above.

Abstractions need not be profound. Consider the black swans example again. The way I presented it above was actually a bit disingenuous: black swans are not the only evidence that disproves the all-swans-are-white hypothesis; any non-white swans would. Thus it might be more accurate to replace the “black swans” entity with “non-white swans” in Fig.  2 a. The relationship between P and L then first involves an abstraction (instead of an intersection)—namely is-a (black swans, non-white swans)—followed by an interpretation, as shown in Fig.  4 . This is a rather trivial kind of abstraction, which likely happens all the time when interpreting prior work in the context of current work.

The black swans example revisited. The relationship between P and L is now an interpretation of an abstraction of L . Notice that we used “are” instead of “is a” simply because the entities are expressed in plural

A more substantial form of abstraction is whenever P reports on empirical findings that can be subsumed into an existing theory described by L . For example, if researchers find that students in a collaborative problem-solving activity learned more than students who were working on the activity on their own, then they might see the ICAP hypothesis (Chi & Wylie, 2014 ), which posits that interactive learning is better than constructive learning, as an abstraction.

Finally, perhaps the most interesting (but also rarest) form of abstraction is when a body of research is interpreted or a problem is solved using some abstract formalism or framework that exists in the literature (often in a different field). For example, a notable example in the history of science is the introduction of group theory to quantum mechanics to solve certain problems related to symmetry (French, 2000 ; Scholz, 2006 ). According to French ( 2000 ):

the relationship between mathematics and physics is represented in terms of an embedding of a scientific theory into a mathematical structure. This effectively gives the theory access to ‘surplus’ mathematical structure which can play an essential role in the further development of theory. (p. 104)

This “surplus structure”—a term originally from Redhead ( 1975 )—is represented in our typology by expansion steps that can follow the abstraction. Namely, once a connection is made between L (say group theory) and P (a particular problem in physics), an expansion can be applied to bring new mathematical machinery from L to bear on P . Furthermore, an interpretation of the abstraction of L in light of P might result in new insights that could lead to further developments in L (if we do not consider L to be static literature). As French ( 2000 ) states, “it is important to acknowledge that both group theory and quantum mechanics were in a state of flux at the time they were brought into contact and both subsequently underwent further development” (p. 110).

4.5 Reification

A reification is the inverse of an abstraction. That is, a reification has the same definition of an abstraction, except that P and L are exchanged. We can say P is reified by L if L is abstracted by P . A reification can occur when prior work might contain a concrete example of a phenomenon, which one’s present work presents in more abstract or general terms. Reifications will often be used when interpreting prior empirical findings in light of a new theoretical framework. For example, when articulating his theory of the structure of scientific revolutions, Kuhn ( 2012 ) drew on myriad concrete historical examples from the history of physics, astronomy, chemistry, and other fields. These findings are reifications of particular components of Kuhn’s theory (e.g., paradigms, anomalies, paradigm shifts, etc.).

A reification can also make sense when one is in a formative stage of a project where some of the specifics have not yet been determined. For example, consider Tu Youyou’s work on finding a cure for malaria in the 1970s for which she won the Nobel Prize in 2015. The problem that Tu and her team were working on is represented in Fig.  5 a. According to Tu ( 2015 ):

After thoroughly reviewing the traditional Chinese medical literature and folk recipes and interviewing experienced Chinese medical practitioners, I collected over two thousand herbal, animal and mineral prescriptions within three months after initiation of the project.

One of the substances that showed some initial promise was sweet wormwood ( qinghao ), which was shown in the literature to cure intermittent fevers, as shown in Fig.  5 b. Therefore sweet wormwood is a reification of a potential cure for malaria, as shown in Fig.  5 c, and this can be interpreted in the broader research of finding a cure for malaria, as shown in Fig.  5 d. Yu went on to identify artemisinin as an actual cure for malaria, but there was an additional step of literature-based discovery needed first, which we will return to later.

The discovery of sweet wormwood as a cure for malaria as an example of reification

4.6 Analogy

An analogy applies when P and L both have a subset of entities and relations that have a shared abstraction. More formally, using the same notation as above, an analogy applies if there exists some other representation \(A = (E_A, \mathcal {R}_A)\) (representing an abstraction) and the following four conditions hold Footnote 2 :

For all \(\tilde{e} \in E_A\) , there exists an \(e \in E_{PS}\) and an \(e' \in E_{LS}\) such that e and \(e'\) are both instances of \(\tilde{e}\) .

For all \(\tilde{R} \in \mathcal {R}_A\) , there exists an \(R \in \mathcal {R}_{PS}\) and an \(R' \in \mathcal {R}_{LS}\) such that R and \(R'\) are both instances of \(\tilde{R}\) .

For all \(\tilde{R} \in \mathcal {R}_{A}\) and for every pair \(R \in \mathcal {R}_{PS}\) and \(R' \in \mathcal {R}_{LS}\) such that R and \(R'\) are both instances of \(\tilde{R}\) , if \(\tilde{R}(\tilde{e}_1, \tilde{e}_2, \dots , \tilde{e}_n)\) then \(R(e_1, e_2, \dots , e_n)\) and \(R'(e'_1, e'_2, \dots , e'_n)\) , where \(e_i\) and \(e'_i\) are instances of \(\tilde{e}_i\) for all i and R and \(R'\) are instances of \(\tilde{R}\) .

At least some \(e \not = e'\) or some \(R \not = R'\) .

We say that \(\textsc {analogous}(e,e')\) if and only if condition 1 holds for e and \(e'\) and similarly we say that \(\textsc {analogous}(R(e_1, e_2, \dots , e_n), R'(e'_1, e'_2, \dots , e'_n))\) if and only if the conditions 2 and 3 above hold for those entities and relations. The representation that results from an analogy operation is \(\rho = (E_{PS} \cup E_{LS}, \mathcal {R}_{PS} \cup \mathcal {R}_{LS} \cup \textsc {analogous})\) .

Analogies can span from shallow analogies between two instances of a similar phenomenon in the same field to deep analogies across scientific fields that share little apparent relation to one another on the surface. The further removed that P and L are from the abstraction A , the deeper the analogy becomes (and typically, the harder to notice). Concretely identifying the abstraction implicit in an analogy is not necessary, and in some cases, it can actually be difficult to do, but I suggest that doing so may be a useful exercise (and could lead to refining the analogy).

Like expansions, analogies can sometimes result in modifying P by looking at the research project in a whole new light. Like expansions, this also means the way in which an analogy might have helped develop P over time may not always be apparent from the final product. Even if a publication discusses an analogy, it may not always be clear if that analogy was instrumental in developing the idea in the first place or if it was an afterthought that the two ideas were related.

An example of an analogy where the impact of prior work on a research project is actually made explicit is the analogy between Thomas Kuhn’s historical philosophy of science and Jean Piaget’s psychological and epistemological theory of how a child develops knowledge. In The Structure of Scientific Revolutions , Kuhn ( 2012 ) gives us a brief sense of his indebtedness to Piaget:

A footnote encountered by chance led me to the experiments by which Jean Piaget has illuminated both the various worlds of the growing child and the process of transition from one to the next. (p. xi)

The extent of this has recently been clarified by historians examining Kuhn’s other works and archival materials (Galison, 2016 ; Burman, 2020 ). For example, Kuhn ( 1977 , as cited in Burman, 2020) states:

Almost twenty years ago I first discovered, very nearly at the same time, both the intellectual interest of the history of science and the psychological studies of Jean Piaget. Ever since that time the two have interacted closely in my mind and in my work. (p. 21)

So what was the nature of this close interaction? One can draw a clear analogy between the two. At risk of oversimplification, a representation of the analogy between Kuhn’s theory and Piaget’s is shown in Fig.  6 , adapted from a mapping given by MacIsaac ( 1991 ). This is not at all to say that this is the precise analogy that Kuhn drew which led to a refinement of his theory as presented in The Structure of Scientific Revolutions . However, he probably made similar mappings that changed over time as he developed his theory. Similar analogies can also be drawn from Kuhn’s theory to gestalt theory and Bruner and Postman’s ( 1949 ) psychological theory of how people perceive incongruities, both of which Kuhn ( 2012 ) explicitly builds off of. Interestingly enough, the Piagetian analogy, while very influential on the development of Kuhn’s theory, was not retained in the final representation of his book, while the analogies to gestalt theory and Bruner and Postman ( 1949 ) were explicitly an important part of his narrative. Note that the relations in P and L are identical in this case, but this need not be the case in general; in fact, they may only be identical because I constructed them that way, but perhaps if the representations were to be derived independently, the relations would be non-identical, but share a common abstraction.

The representation of the analogy between Kuhn’s The Structure of Scientific Revolutions and Piagetian theory. The analogous relations are shown as dotted lines without labels for ease of reading

To provide a more recent example of analogy, we can consider the relationship between the recent machine learning literature on fairness ( P ) in relation to older literature from the 1960s-1970s on fairness in educational and employment testing ( L ). As Hutchinson and Mitchell ( 2019 ) point out, the two literatures share much in common including many mathematical definitions of fairness. To formalize this, Hutchinson and Mitchell ( 2019 ) explicitly construct an analogy between the two literatures:

Test items (questions) are analogous to model features, and item responses analogous to specific activations of those features. Scoring a test is typically a simple linear model which produces a (possibly weighted) sum of the item scores....Because of this correspondence, much of the math is directly comparable; and many of the underlying ideas in earlier fairness work trivially map on to modern day ML fairness. “History doesn’t repeat itself, but it often rhymes”; and by hearing this rhyme, we hope to gain insight into the future of ML fairness. (p. 49)

Their last sentence suggests that the goal of pointing out the relationship between these two literatures are further steps of expansion and interpretation, or in other words, exploiting the “surplus of structure.” Indeed, the authors surface several definitions from test fairness that had not been proposed in machine learning (i.e., an expansion). Notice that in this case, the underlying abstraction may not be immediately obvious (e.g., what is the abstraction underlying both a test item and a feature?); in fact, in some cases, there may not be a simple word or phrase to describe the abstraction, but the fact that a clear analogy can be drawn indicates that there must be some more abstract underlying representation.

Finally, in my own research, I have found that there is an analogy between debates in education research and the bias-variance tradeoff in machine learning (Doroudi, 2020 ). Here an analogy was determined by directly formulating the abstraction (a generalized version of the bias-variance decomposition theorem). This abstraction has four components that any instance must specify: a target, an approximator, a random mechanism, and a source of randomness; once these components are specified, one can derive other phenomena (e.g., the meaning of bias, variance, etc.). This naturally sounds very abstract, but it is more concrete once instantiated in specific contexts. Table  2 gives an example of the analogy between these concepts in machine learning and debates around pedagogy. Once this analogy is drawn, it may be possible to expand techniques that are developed in machine learning to bear on educational debates (Doroudi, 2020 ). One benefit of making the abstraction concrete is that the same abstraction can be used to draw analogies to other fields as well.

4.7 Substitution

The analogy operator as described above can be applied in cases that do not semantically appear to be analogies. For example, consider two papers that use different methods to achieve the same outcome; many of the entities and relations may be the same across the two representations, but the entity (or entities) representing the methods would be different. Colloquially we would probably not say there is an analogy between the two approaches. For this reason, we make a distinction between substitutions and analogies. A substitution operates exactly in the same way as an analogy, but it should be applied when it is more sensible. The analogous relation can be replaced with the substitutes relation for semantic clarity. Therefore, unlike the other operators, the distinction between the analogy and substitution operators is semantic. However, there are typically clear structural differences between the two. In a substitution, typically only one or a few entities and relations will change, and the rest will be identical across P and L . Moreover, a substitution is similar to what Gentner ( 1983 ) terms a literal similarity. Namely, Gentner ( 1983 ) suggests that the difference between a literal similarity and an analogy is typically that a literal similarity will involve a greater number of identical attributes (or unary relations).

Consider the following four scenarios that loosely describe different papers:

Convolutional neural networks are trained to classify histopathological images of breast tissue as benign or malignant (Spanhol et al., 2016 ).

Support vector machines are trained to classify histopathological images of breast tissue as benign or malignant (Aswathy & Jagannath, 2021 ).

Human crowdworkers are trained to classify histopathological images of breast tissue as benign or malignant (Eickhoff, 2014 ).

Pigeons are trained to classify histopathological images of breast tissue as benign or malignant (Levenson et al., 2015 ).

In cases 1 and 2, it would be a stretch to say that there is an analogy between “convolutional neural networks” and “support vector machines,” which are both machine learning algorithms that can be applied to the same classification tasks. Thus, here is a clear case of substitution. However, with case 4, even though one could argue a pigeon is being substituted for a machine learning algorithm, the idea of training pigeons and the idea of training machine learning algorithms both have long histories and are often used for different purposes. Thus, it seems more natural to say pigeons are analogical to neural networks or support vector machines in these scenarios (with the underlying abstraction being a learning agent). Pigeons and support vector machines have a lot fewer attributes in common than convolutional neural networks and support vector machines. Unlike pigeons, the latter two are both algorithms implemented in computer code that were designed specifically for classification tasks. Pigeons, on the other hand, are animals, fly, eat, and make sounds. Some attributes of pigeons are actually important for the training process but not shared by any standard machine learning algorithms, such as their hunger. While we might say getting hungry is analogous to the “reward seeking” or “loss minimizing” property of machine learning algorithms, there is no literal hunger in those algorithms.

Case 3 is less clear-cut. While human crowdworkers are also significantly different from machine learning algorithms, crowdsourcing is often used for tasks where state-of-the-art machine learning is not good enough or a machine learning engineer might want to compare the performance of their algorithm against crowdworkers. On the other hand, human crowdworkers and pigeons share a lot of similar attributes that are lacking in machine learning algorithms. These ambiguities point out that ultimately the decision of whether an analogy or a substitution applies is in the eyes of the beholder. In other words, the degree of overlap in attributes depends on what attributes are most salient to the researcher. If a crowdworker is seen as an alternative to artificial intelligence and its humanity is not at the forefront, then perhaps a substitution would apply. On the other hand, researchers interested in using pigeons’ visual properties as a substitute for human labelers (Levenson et al., 2015 ) could also see a substitution between crowdworkers and pigeons.

As mentioned earlier, Kang et al.’s ( 2022 ) analogical search engine looks for papers that overlap in terms of purpose with a researchers’ study (as represented in the form of a search query). However, if the purpose is virtually identical, then replacing one mechanism for another may often be a substitution, not an analogy, as seen in cases 1 and 2 above. In some cases, such as using pigeons vs. neural networks to classify images, swapping mechanisms may result in an analogy. On the other hand, when the purpose is only similar (but not identical), there is no guarantee that the purpose-mechanism relationship will be analogical across different papers. Footnote 3 Thus, while Kang et al. ( 2022 ) find that their search engine is more likely to identify papers that trigger creative adaptations of the original idea (when compared to a standard keyword-based search engine), it is important to distinguish related work that might result in generating novel ideas and related work that actually has an analogical relationship with the present work.

Returning to Tu’s work on discovering a cure for malaria, she found that wormwood “showed some effects in inhibiting malaria parasites during initial screening, but the result was inconsistent and not reproducible.” Scouring over the relevant literature, she then identified a relevant sentence in Ge Hong’s fifth century A Handbook of Prescriptions for Emergencies : “A handful of Qinghao immersed in two liters of water, wring out the juice and drink it all” (Tu, 2015 ). Tu realized that while herbs are typically boiled, Ge’s recipe did not advocate for boiling it so perhaps the heat killed the active components in the wormwood. This led to a new method for extracting artemisinin from wormwood. To model this we would have to add entities to Fig.  5 that account for the method by which the drug is extracted. In that case, Ge’s method can be seen as a substitution for Tu’s original method. This substitution led to a drastic change in the research direction, eventually resulting in a cure for malaria.

Example of literature search as a sequence of operators applied to a research question on how memory is stored in synapses

5 Putting the pieces together

Now that we have seen the various operations that can relate two pieces of research to one another, it is worth discussing how these operations might be used in sequence over the scope of a research project. To do so, I provide a hypothetical example. As a disclaimer, the example is not from an area I have any expertise in; in fact, I encountered the relationships described below in the process of writing this paper (although not in the exact sequence described below). On the one hand, this suggests that the example may be oversimplified; on the other hand, perhaps it gives a somewhat authentic account of a non-expert navigating a new research field.

Suppose we are interested in conducting a literature review related to the question “how are memories stored in synapses?” This research question can be represented as “memories are stored in synapses through some mechanism” as shown at the top of Fig.  7 . Some of the steps described below are also represented in Fig.  7 ; in those cases, I will mention the number of the step in parentheses. Operator names are italicized below. If the reader wants to assess their understanding of the operators (or perhaps assess the degree to which there could be subjectivity in which operators apply), the reader can guess which operator applies for each step of the figure before reading the rest of this section.

When embarking on this literature search process, we are likely already aware of some answers to the question. For example, “some mechanism” could be reified by “synaptic plasticity” (Step 1). But synaptic plasticity is quite broad and could be reified further by several more specific forms of plasticity, such as “long-term potentiation” (Step 2) and “long-term depression.” Further literature search might reveal a plethora of other mechanisms such as “protein synthesis,” “epigenetic mechanisms,” or “the standard model of synaptic consolidation.” However, these mechanisms are not necessarily mutually exclusive, perhaps leading to a revision of the question formulation to “memories are stored in synapses through a combination of X, Y, ...” (or some more hierarchical representation). On the other hand, some proposed mechanisms may be competing, like “the standard model of synaptic consolidation” and “multiple trace theory” (i.e., one can be substituted for the other). Moreover, we might realize that the “memory” entity can also be reified into particular kinds of memory, like “episodic memory” or “semantic memory.”

Searching the literature further may reveal that there are recent suggestions that memory is not (only) stored in synapses, but could be stored in sub-cellular materials. This might result in a substitution of certain molecules (e.g., “RNA”) for synapse (Step 3 \('\) ). Alternatively, to keep our options open we may apply an abstraction of “synapse,” such as “parts of the brain” (Step 3). “Parts of the brain” can then be reified with many different entities, like “RNA” (Step 4). But it can also be substituted for regions of the brain where memories are stored, like the hippocampus. This may subsequently lead to the realization that rather than just asking how memories are stored, we should also be asking where memories are stored, leading to an expansion of the initial representation.

So far we have primarily considered literature that directly bears on the initial question. But sometimes surprising related works can also be discovered through intersections . For example, once we have established that RNA may be involved in memory, a colleague who is a molecular biologist might point out that there is an intersection with the literature on RNA interference (Step 5). Indeed, Smalheiser et al. ( 2001 ) noticed connections between a series of controversial 1960s studies on RNA-mediated memory transfer and RNAi; Smalheiser was a pioneer of literature-based discovery. We might then posit a relation that was neither present in our initial representation nor in related work: RNAi is potentially involved in the memory storage mechanism (i.e., “some mechanism” in our representation). Although it took over a decade, Smalheiser eventually found evidence to suggest that RNAi could indeed be involved in memory transfer (Smalheiser, 2017 ).

Finally, upon contemplating the initial representation further, the researcher may recognize an analogy to “how is memory stored in computer hardware?” (Step 6) or “how is memory stored in artificial neural networks?” Studying the literature in either of these areas may lead to the addition of new hypothesized mechanisms through an interpretation in light of the analogies. Notice that while in some cases a researcher notices an analogy when examining related literature, in other cases a researcher might think of an analogy, and then search for related literature. The related literature could either be about the analog (e.g., how memory is encoded in artificial neural networks) or about the analogy itself (Langille & Gallistel, 2020 ,e.g., how do theories of memory storage in the human brain relate to theories of memory storage in computer science). In the latter case, we have an intersection applied to the entire analogy .

6 The typology in practice

In this section, we discuss some important considerations for how the representation and typology could be used in practice. In theory, an understanding of the various ways in which one piece of literature may relate to a research topic can inform directions in information retrieval and citation recommendation. Such systems could potentially represent papers in terms of entities and relations by using named entity recognition (Nadeau & Sekine, 2007 ) and relation extraction (Bach & Badaskar, 2007 ); they can also leverage a growing body of work on using knowledge graphs for information retrieval (Reinanda et al., 2020 ). The typology can then inform the kinds of relationships that such systems can explore and possibly recommend to users. However, we reiterate that there is no single way to represent a paper or single way of applying the operators to identify relationships to prior work. As noted above, the choice of what operators apply and hence which relationships to related works will be noticed depends on the view one takes of one’s work and related work. One way to potentially mitigate this challenge is by having users specify their current view of their work in terms of its representation, or perhaps by allowing them to simultaneously represent their work in multiple ways. Furthermore, recognizing that different researchers and papers will use slightly different terms to refer to identical or very similar entities and relations, search engines could try to treat semantically similar phrases as being identical or provide a pre-selected set of entities and relations that they recommend users use.

However, even if the representations of papers are completely aligned, the task of retrieving good analogies and abstractions may be computationally intractable in the worst case (Wareham et al., 2011 ). Indeed, in automated analogical search, simplifications are made to make finding potential analogies more tractable. For example, the MAC/FAC algorithm—which is rooted in structure-mapping theory—first finds several examples that have the most surface-level overlap in terms of relations and then identifies the analogy Footnote 4 that is structurally strongest (Forbus et al., 1995 ). In Kang et al.’s ( 2022 ) analogical search engine, they look for papers that have a similar purpose, where similarity is measured by neural network embeddings rather than looking for a formally analogical structure. Although such algorithms may not be perfect, they could still potentially surface candidate analogies that would be given to a researcher who would ultimately identify when an analogy operator is applicable and useful.

Given the ongoing challenges in automated search, perhaps the typology would be more useful as a conceptual tool for researchers. Huang and Soergel ( 2013 ) found that “teaching users about the different kinds of topical relevance relationships may open their minds and make them better searchers and users of information.” Similarly, perhaps the typology presented here could be used as a tool to familiarize researchers with the different ways in which their research may relate to prior work, and how to use search tools to find such works. As mentioned before, simply representing one’s paper as a network of entities and relations may be a useful exercise to help researchers realize new insights about their research; future experimental studies could confirm whether this is true. Moreover, in discussing the potential value of their analogical search engine, Kang et al. ( 2022 ) mention the importance of “how deeply the human users can reflect on the retrieved analogs...and recognize how different notions of relevance may exist for their own problem context, despite potential dissimilarity on the surface” (p. 125). They suggest that “one approach to explaining relevance might be to surface a small number of core common features between an analog and a problem query” (p. 126). The representation presented here provides a natural way of showing users the potential relevance of related work. For example, when one searches for literature (even using a traditional search engine), representations could be generated on demand for the resulting papers such that they maximally align with the user’s query (at least in terms of number of entities and relations, if not in terms of higher-order relationships). Moreover, if the user specifies multiple research projects, a search engine could potentially represent each paper in terms of the representation that best aligns with each project.

7 Conclusion

I have tried to make the case that literature search is a complex process that can influence and be influenced by research in a variety of ways. By describing research papers and projects in terms of concrete representations, we can formally articulate how different pieces of research might relate to one another. As discussed in the last section, this could have practical ramifications in terms of how search engines could better support the literature search process or how to design training for researchers to improve the way they approach literature search.

Beyond practical applications, the typology presented here could give us insight into the ways in which literature search might iteratively change the course of a research project as a sequence of operations. Although it goes beyond the scope of this paper, it might be worth briefly considering some of the ways in which a research project might be modified as a result of these operations. One form of modification is simply adding new entities and relations to P as a result of an expansion; we can view this as a natural extension of the expansion operator. Several other forms of modifications can fall under the category of logical inference (i.e., deduction , induction , and abduction ). For example, in the black swans example, evidence of black swans triggers a modus ponens argument that proves the “all-swans-are-white” hypothesis is false, thereby changing P . Similarly, in Swanson’s ABC model, we can discern the presence of a new relation through the transitivity of the causal relation. If the representations are well-specified, one can imagine creating an inference engine that can automatically detect such changes in P after coming into contact with related work.

However, literature search cannot be considered in isolation from the other aspects of scientific discovery. Another form of modification to P might be the result of an experimentation operation, whereby a deduced relation is tested. We saw this both in the case of medical research that confirmed the causal link deduced by Swanson, and Tu’s experimental confirmation that wormwood can cure malaria. Finally, there is the construction operation, whereby a new entity or relation is created. Construction can result from either literature search (e.g., where an interpretation of some finding results in the discovery of a new finding, or where the expansion of an analogy results in an analogous entity that was not previously conceived of) or from research itself (e.g., the discovery of a new molecule or a new experimental finding). A thorough understanding of the processes of inference, experimentation, and construction is beyond the scope of this paper, but they begin to give us a hint as to how literature search is an iterative process that interacts with other aspects of the research process.

As pointed out by Swanson ( 1986 ), world 3 is also a world where scientific discovery takes place, by interacting with world 1 (the physical world) and world 2 (the subjective world of mental states). Philosophy of science should try to understand how these worlds interact in the process of scientific discovery; this paper is a step in that direction.

Availability of data and material:

This can be formalized using the partial structures formalism mentioned above (Da Costa & French, 1990 ).

Gentner ( 1983 ) did not explicitly define an analogy in terms of an abstraction, but I believe it is useful to recognize that there is always implicitly an abstraction present, and in many cases, it might be useful to reason about what that abstraction is. Gentner ( 1983 ) further differentiates between abstractions, analogies, and literal similarities. These are differentiated by how many attributes and relations are shared between the two and the degree of abstractness of the entities (i.e., in an abstraction, entities are more abstract). While this is sensible, we allow for abstractions that are more concrete, so long as the entities in one representation are still instances of the entities in the other.

For example, one participant’s research question was how to “Grow plants better by optimizing entry of nanoparticle fertilizers into the plant” (p. 14). One paper identified by analogical search was about identifying plants by applying image analysis techniques to their leaves. It is not clear what the similar purpose is in this case, but regardless, the paper does not obviously share an analogical relationship with the research question. While this paper inspired a novel idea that the researcher thought would be relevant to her project, the relationship is captured by an intersection (through the “plant” entity) and possibly the application of interpretation and expansion operators.

Technically it looks for matches in terms of literal similarity to mimic people’s tendencies to find literally similar matches, but the algorithm could be easily modified to search for analogies.

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The Craft of Writing a Strong Hypothesis

Table of Contents

Writing a hypothesis is one of the essential elements of a scientific research paper. It needs to be to the point, clearly communicating what your research is trying to accomplish. A blurry, drawn-out, or complexly-structured hypothesis can confuse your readers. Or worse, the editor and peer reviewers.

A captivating hypothesis is not too intricate. This blog will take you through the process so that, by the end of it, you have a better idea of how to convey your research paper's intent in just one sentence.

What is a Hypothesis?

The first step in your scientific endeavor, a hypothesis, is a strong, concise statement that forms the basis of your research. It is not the same as a thesis statement , which is a brief summary of your research paper .

The sole purpose of a hypothesis is to predict your paper's findings, data, and conclusion. It comes from a place of curiosity and intuition . When you write a hypothesis, you're essentially making an educated guess based on scientific prejudices and evidence, which is further proven or disproven through the scientific method.

The reason for undertaking research is to observe a specific phenomenon. A hypothesis, therefore, lays out what the said phenomenon is. And it does so through two variables, an independent and dependent variable.

The independent variable is the cause behind the observation, while the dependent variable is the effect of the cause. A good example of this is “mixing red and blue forms purple.” In this hypothesis, mixing red and blue is the independent variable as you're combining the two colors at your own will. The formation of purple is the dependent variable as, in this case, it is conditional to the independent variable.

Different Types of Hypotheses‌

Types of hypotheses

Some would stand by the notion that there are only two types of hypotheses: a Null hypothesis and an Alternative hypothesis. While that may have some truth to it, it would be better to fully distinguish the most common forms as these terms come up so often, which might leave you out of context.

Apart from Null and Alternative, there are Complex, Simple, Directional, Non-Directional, Statistical, and Associative and casual hypotheses. They don't necessarily have to be exclusive, as one hypothesis can tick many boxes, but knowing the distinctions between them will make it easier for you to construct your own.

1. Null hypothesis

A null hypothesis proposes no relationship between two variables. Denoted by H 0 , it is a negative statement like “Attending physiotherapy sessions does not affect athletes' on-field performance.” Here, the author claims physiotherapy sessions have no effect on on-field performances. Even if there is, it's only a coincidence.

2. Alternative hypothesis

Considered to be the opposite of a null hypothesis, an alternative hypothesis is donated as H1 or Ha. It explicitly states that the dependent variable affects the independent variable. A good  alternative hypothesis example is “Attending physiotherapy sessions improves athletes' on-field performance.” or “Water evaporates at 100 °C. ” The alternative hypothesis further branches into directional and non-directional.

• Directional hypothesis: A hypothesis that states the result would be either positive or negative is called directional hypothesis. It accompanies H1 with either the ‘<' or ‘>' sign.
• Non-directional hypothesis: A non-directional hypothesis only claims an effect on the dependent variable. It does not clarify whether the result would be positive or negative. The sign for a non-directional hypothesis is ‘≠.'

3. Simple hypothesis

A simple hypothesis is a statement made to reflect the relation between exactly two variables. One independent and one dependent. Consider the example, “Smoking is a prominent cause of lung cancer." The dependent variable, lung cancer, is dependent on the independent variable, smoking.

4. Complex hypothesis

In contrast to a simple hypothesis, a complex hypothesis implies the relationship between multiple independent and dependent variables. For instance, “Individuals who eat more fruits tend to have higher immunity, lesser cholesterol, and high metabolism.” The independent variable is eating more fruits, while the dependent variables are higher immunity, lesser cholesterol, and high metabolism.

5. Associative and casual hypothesis

Associative and casual hypotheses don't exhibit how many variables there will be. They define the relationship between the variables. In an associative hypothesis, changing any one variable, dependent or independent, affects others. In a casual hypothesis, the independent variable directly affects the dependent.

6. Empirical hypothesis

Also referred to as the working hypothesis, an empirical hypothesis claims a theory's validation via experiments and observation. This way, the statement appears justifiable and different from a wild guess.

Say, the hypothesis is “Women who take iron tablets face a lesser risk of anemia than those who take vitamin B12.” This is an example of an empirical hypothesis where the researcher  the statement after assessing a group of women who take iron tablets and charting the findings.

7. Statistical hypothesis

The point of a statistical hypothesis is to test an already existing hypothesis by studying a population sample. Hypothesis like “44% of the Indian population belong in the age group of 22-27.” leverage evidence to prove or disprove a particular statement.

Characteristics of a Good Hypothesis

Writing a hypothesis is essential as it can make or break your research for you. That includes your chances of getting published in a journal. So when you're designing one, keep an eye out for these pointers:

• A research hypothesis has to be simple yet clear to look justifiable enough.
• It has to be testable — your research would be rendered pointless if too far-fetched into reality or limited by technology.
• It has to be precise about the results —what you are trying to do and achieve through it should come out in your hypothesis.
• A research hypothesis should be self-explanatory, leaving no doubt in the reader's mind.
• If you are developing a relational hypothesis, you need to include the variables and establish an appropriate relationship among them.
• A hypothesis must keep and reflect the scope for further investigations and experiments.

Separating a Hypothesis from a Prediction

Outside of academia, hypothesis and prediction are often used interchangeably. In research writing, this is not only confusing but also incorrect. And although a hypothesis and prediction are guesses at their core, there are many differences between them.

A hypothesis is an educated guess or even a testable prediction validated through research. It aims to analyze the gathered evidence and facts to define a relationship between variables and put forth a logical explanation behind the nature of events.

Predictions are assumptions or expected outcomes made without any backing evidence. They are more fictionally inclined regardless of where they originate from.

For this reason, a hypothesis holds much more weight than a prediction. It sticks to the scientific method rather than pure guesswork. "Planets revolve around the Sun." is an example of a hypothesis as it is previous knowledge and observed trends. Additionally, we can test it through the scientific method.

Whereas "COVID-19 will be eradicated by 2030." is a prediction. Even though it results from past trends, we can't prove or disprove it. So, the only way this gets validated is to wait and watch if COVID-19 cases end by 2030.

Finally, How to Write a Hypothesis

Quick tips on writing a hypothesis

1.  Be clear about your research question

A hypothesis should instantly address the research question or the problem statement. To do so, you need to ask a question. Understand the constraints of your undertaken research topic and then formulate a simple and topic-centric problem. Only after that can you develop a hypothesis and further test for evidence.

2. Carry out a recce

Once you have your research's foundation laid out, it would be best to conduct preliminary research. Go through previous theories, academic papers, data, and experiments before you start curating your research hypothesis. It will give you an idea of your hypothesis's viability or originality.

Making use of references from relevant research papers helps draft a good research hypothesis. SciSpace Discover offers a repository of over 270 million research papers to browse through and gain a deeper understanding of related studies on a particular topic. Additionally, you can use SciSpace Copilot , your AI research assistant, for reading any lengthy research paper and getting a more summarized context of it. A hypothesis can be formed after evaluating many such summarized research papers. Copilot also offers explanations for theories and equations, explains paper in simplified version, allows you to highlight any text in the paper or clip math equations and tables and provides a deeper, clear understanding of what is being said. This can improve the hypothesis by helping you identify potential research gaps.

3. Create a 3-dimensional hypothesis

Variables are an essential part of any reasonable hypothesis. So, identify your independent and dependent variable(s) and form a correlation between them. The ideal way to do this is to write the hypothetical assumption in the ‘if-then' form. If you use this form, make sure that you state the predefined relationship between the variables.

In another way, you can choose to present your hypothesis as a comparison between two variables. Here, you must specify the difference you expect to observe in the results.

4. Write the first draft

Now that everything is in place, it's time to write your hypothesis. For starters, create the first draft. In this version, write what you expect to find from your research.

Clearly separate your independent and dependent variables and the link between them. Don't fixate on syntax at this stage. The goal is to ensure your hypothesis addresses the issue.

5. Proof your hypothesis

After preparing the first draft of your hypothesis, you need to inspect it thoroughly. It should tick all the boxes, like being concise, straightforward, relevant, and accurate. Your final hypothesis has to be well-structured as well.

Research projects are an exciting and crucial part of being a scholar. And once you have your research question, you need a great hypothesis to begin conducting research. Thus, knowing how to write a hypothesis is very important.

Now that you have a firmer grasp on what a good hypothesis constitutes, the different kinds there are, and what process to follow, you will find it much easier to write your hypothesis, which ultimately helps your research.

Now it's easier than ever to streamline your research workflow with SciSpace Discover . Its integrated, comprehensive end-to-end platform for research allows scholars to easily discover, write and publish their research and fosters collaboration.

It includes everything you need, including a repository of over 270 million research papers across disciplines, SEO-optimized summaries and public profiles to show your expertise and experience.

If you found these tips on writing a research hypothesis useful, head over to our blog on Statistical Hypothesis Testing to learn about the top researchers, papers, and institutions in this domain.

Frequently Asked Questions (FAQs)

1. what is the definition of hypothesis.

According to the Oxford dictionary, a hypothesis is defined as “An idea or explanation of something that is based on a few known facts, but that has not yet been proved to be true or correct”.

2. What is an example of hypothesis?

The hypothesis is a statement that proposes a relationship between two or more variables. An example: "If we increase the number of new users who join our platform by 25%, then we will see an increase in revenue."

3. What is an example of null hypothesis?

A null hypothesis is a statement that there is no relationship between two variables. The null hypothesis is written as H0. The null hypothesis states that there is no effect. For example, if you're studying whether or not a particular type of exercise increases strength, your null hypothesis will be "there is no difference in strength between people who exercise and people who don't."

4. What are the types of research?

• Fundamental research

• Applied research

• Qualitative research

• Quantitative research

• Mixed research

• Exploratory research

• Longitudinal research

• Cross-sectional research

• Field research

• Laboratory research

• Fixed research

• Flexible research

• Action research

• Policy research

• Classification research

• Comparative research

• Causal research

• Inductive research

• Deductive research

5. How to write a hypothesis?

• Your hypothesis should be able to predict the relationship and outcome.

• Avoid wordiness by keeping it simple and brief.

• Your hypothesis should contain observable and testable outcomes.

• Your hypothesis should be relevant to the research question.

6. What are the 2 types of hypothesis?

• Null hypotheses are used to test the claim that "there is no difference between two groups of data".

• Alternative hypotheses test the claim that "there is a difference between two data groups".

7. Difference between research question and research hypothesis?

A research question is a broad, open-ended question you will try to answer through your research. A hypothesis is a statement based on prior research or theory that you expect to be true due to your study. Example - Research question: What are the factors that influence the adoption of the new technology? Research hypothesis: There is a positive relationship between age, education and income level with the adoption of the new technology.

8. What is plural for hypothesis?

The plural of hypothesis is hypotheses. Here's an example of how it would be used in a statement, "Numerous well-considered hypotheses are presented in this part, and they are supported by tables and figures that are well-illustrated."

9. What is the red queen hypothesis?

The red queen hypothesis in evolutionary biology states that species must constantly evolve to avoid extinction because if they don't, they will be outcompeted by other species that are evolving. Leigh Van Valen first proposed it in 1973; since then, it has been tested and substantiated many times.

10. Who is known as the father of null hypothesis?

The father of the null hypothesis is Sir Ronald Fisher. He published a paper in 1925 that introduced the concept of null hypothesis testing, and he was also the first to use the term itself.

11. When to reject null hypothesis?

You need to find a significant difference between your two populations to reject the null hypothesis. You can determine that by running statistical tests such as an independent sample t-test or a dependent sample t-test. You should reject the null hypothesis if the p-value is less than 0.05.

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Sharing research data

As a researcher, you are increasingly encouraged, or even mandated, to make your research data available, accessible, discoverable and usable.

Sharing research data is something we are passionate about too, so we’ve created this short video and written guide to help you get started.

Research Data

What is research data.

While the definition often differs per field, generally, research data refers to the results of observations or experiments that validate your research findings. These span a range of useful materials associated with your research project, including:

Raw or processed data files

Research data  does not  include text in manuscript or final published article form, or data or other materials submitted and published as part of a journal article.

Why should I share my research data?

There are so many good reasons. We’ve listed just a few:

How you benefit

You get credit for the work you've done

Leads to more citations! 1

Can boost your number of publications

Increases your exposure and may lead to new collaborations

What it means for the research community

It's easy to reuse and reinterpret your data

Duplication of experiments can be avoided

New insights can be gained, sparking new lines of inquiry

Empowers replication

And society at large…

Greater transparency boosts public faith in research

Can play a role in guiding government policy

Improves access to research for those outside health and academia

Benefits the public purse as funding of repeat work is reduced

How do I share my research data?

The good news is it’s easy.

Yet to submit your research article?  There are a number of options available. These may vary depending on the journal you have chosen, so be sure to read the  Research Data  section in its  Guide for Authors  before you begin.

Already published your research article?  No problem – it’s never too late to share the research data associated with it.

Two of the most popular data sharing routes are:

Publishing a research elements article

These brief, peer-reviewed articles complement full research papers and are an easy way to receive proper credit and recognition for the work you have done. Research elements are research outputs that have come about as a result of following the research cycle – this includes things like data, methods and protocols, software, hardware and more.

You can publish research elements articles in several different Elsevier journals, including  our suite of dedicated Research Elements journals . They are easy to submit, are subject to a peer review process, receive a DOI and are fully citable. They also make your work more sharable, discoverable, comprehensible, reusable and reproducible.

The accompanying raw data can still be placed in a repository of your choice (see below).

Uploading your data to a repository like Mendeley Data

Mendeley Data is a certified, free-to-use repository that hosts open data from all disciplines, whatever its format (e.g. raw and processed data, tables, codes and software). With many Elsevier journals, it’s possible to upload and store your data to Mendeley Data during the manuscript submission process. You can also upload your data directly to the repository. In each case, your data will receive a DOI, making it independently citable and it can be linked to any associated article on ScienceDirect, making it easy for readers to find and reuse.

View an article featuring Mendeley data opens in new tab/window  (just select the  Research Data  link in the left-hand bar or scroll down the page).

What if I can’t submit my research data?

Data statements offer transparency.

We understand that there are times when the data is simply not available to post or there are good reasons why it shouldn’t be shared.  A number of Elsevier journals encourage authors to submit a data statement alongside their manuscript. This statement allows you to clearly explain the data you’ve used in the article and the reasons why it might not be available.  The statement will appear with the article on ScienceDirect. 

View a sample data statement opens in new tab/window  (just select the  Research Data  link in the left-hand bar or scroll down the page).

Showcasing your research data on ScienceDirect

We have 3 top tips to help you maximize the impact of your data in your article on ScienceDirect.

Link with data repositories

You can create bidirectional links between any data repositories you’ve used to store your data and your online article. If you’ve published a data article, you can link to that too.

Enrich with interactive data visualizations

The days of being confined to static visuals are over. Our in-article interactive viewers let readers delve into the data with helpful functions such as zoom, configurable display options and full screen mode.

Cite your research data

Get credit for your work by citing your research data in your article and adding a data reference to the reference list. This ensures you are recognized for the data you shared and/or used in your research. Read the  References  section in your chosen journal’s  Guide for Authors  for more information.

Ready to get started?

If you have yet to publish your research paper, the first step is to find the right journal for your submission and read the  Guide for Authors .

Find a journal by matching paper title and abstract of your manuscript in Elsevier's  JournalFinder opens in new tab/window

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Already published? Just view the options for sharing your research data above.

1 Several studies have now shown that making data available for an article increases article citations.

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Clinical trials can study:

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• New therapies or behavioral interventions, which help people change their behaviors, thoughts, and feelings to improve their mental health
• New ways to prevent health conditions or find a disease early, sometimes even before symptoms occur.

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The results of clinical trials help inform medical decision-making and provide evidence-based information about the benefits and risks of different treatments or interventions. Researchers and doctors use this information to decide which treatments should be recommended and which require more study.

Why should I participate in a clinical trial?

People volunteer for clinical trials for many reasons. Some people join clinical trials to help doctors and researchers learn more about a disease and improve health care. Other people, such as those with health conditions, join to try treatments that aren’t widely available.

Researchers usually study people who have a specific health condition. Researchers sometimes need to compare data from volunteers with no health conditions to data from people with specific health conditions so they can use that information to learn more about the disease.

Participating in a clinical trial is entirely up to you. If you volunteer for a clinical trial and later decide it’s not right for you, you can withdraw anytime.

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What is it like to participate in a clinical trial?

During a clinical trial, you will see a team of researchers, sometimes called a study team, clinical trial team, or clinical research team, who will monitor your health closely.

You may have more tests and medical exams than you would if you were getting mental health care but not participating in a clinical trial. The study team may also ask you to do other tasks, such as keeping a log about your health or filling out forms about how you feel.

Clinical trials occur in medical centers, doctors’ offices, and community-based organizations nationwide. You may need to travel or stay in a hospital to participate in a clinical trial.

Are clinical trials safe?

Clinical trials are generally safe. Though there are risks to participating in clinical research, clinical trials are designed to minimize risks and keep you safe.

Before a clinical trial can start, it must be reviewed and approved by an institutional review board (IRB) for U.S.-based studies or an independent ethics committee outside the U.S. This review ensures that it is safe and that the potential benefits of the trial are worth the potential risks. The study team will also make sure you meet certain requirements and that it is safe for you to participate.

Clinical studies might make you feel a little uncomfortable for a short time, but how much risk you face depends on the type of study you join. For instance, if you are participating in a study testing a new drug, the medication might make you feel sick or tired when you first start taking it. In some studies, instead of trying a new medicine, you might take computer-based tests or have a non-invasive magnetic resonance imaging (MRI) done, which carries different risks. The research team and the IRB continuously monitor studies to ensure ongoing safety.

Speak with the study team to understand the risks involved in a particular study. Potential risks are included in the informed consent process, and the research team will be able to explain anything you don’t understand.

Are clinical trials paid?

Some clinical trials pay participants, including some trials that take place at the National Institutes of Health (NIH) Clinical Center in Bethesda, MD.

The amount of money you get paid depends on things like how long the trial takes, how much time you need to give, and what kind of trial it is. Sometimes, the trial may also cover your travel, lodging, and food costs. Not all clinical trials are paid, and you should consider all aspects of the study, including risks and benefits, before making a final decision.

How do I find a clinical trial?

The National Institute of Mental Health (NIMH) is the lead federal agency for research on mental disorders. NIMH supports clinical trials at the NIH campus in Bethesda, MD and across the United States.

Find a study at the NIH campus

NIMH researchers conduct many clinical trials at the NIH Clinical Center  . Located on the NIH campus in Bethesda, Maryland, the Clinical Center is the largest research hospital in the world.

Learn more about how to join an NIMH clinical trial at the NIH Clinical Center. These studies enroll volunteers from the local area and across the nation.

Find NIMH clinical trials for adults and children that are currently accepting volunteers:

• Join a Research Study: Adults
• Join a Research Study: Children
• Frequently Asked Questions About Participating in NIMH Research Studies for Adults & Children

You can also subscribe to receive  email updates   about clinical trials conducted at NIH.

Find other studies around the United States

NIMH also funds many studies that are currently recruiting people around the country on different mental health disorders, including:

• Anxiety Disorders
• Attention-Deficit/Hyperactivity Disorder (ADHD)
• Autism Spectrum Disorder (ASD)
• Bipolar Disorder
• Borderline Personality Disorder
• Eating Disorders
• Generalized Anxiety Disorder
• Obsessive-Compulsive Disorder (OCD)
• Panic Disorder
• Post-Traumatic Stress Disorder (PTSD)
• Schizophrenia
• Social Anxiety Disorder
• Studies Recruiting Only Men
• Studies Recruiting Only Women
• Conditions Related to Mental Disorders

Other ways to find a clinical trial

• Search  clinicaltrials.gov   , a database of privately and publicly funded clinical studies conducted worldwide.
• Talk to your health care provider  about studies that may be right for you. You can also learn about studies in newspapers, TV, or online.
• Join a national registry of research volunteers , such as  ResearchMatch   . ResearchMatch is a nonprofit program funded by NIH that helps connect people interested in research studies with researchers from medical centers across the United States.
• Join the  NIH  All of Us  Research Program   ,  which is enrolling a large group of people that reflects the diversity of the United States. The program aims to build a diverse database that can inform thousands of studies on various health conditions.

How do I sign up to participate in a clinical trial?

After you find a clinical trial you're interested in, contact the study team to learn more about it. You can usually find the study teams’ contact information in the trial’s description. The staff can give you information that will help you decide whether to participate.

Check out this resource from the U.S. Department of Health and Human Services (HHS) for a list of specific questions to ask about volunteering for a research study  .

Let your health care provider know if you decide to join a clinical trial. They may want to talk to the study team to help coordinate your care and ensure the trial is safe for you.

How can I learn more about participating in a clinical trial?

Federal resources

• Clinical Trials  : The National Institute on Aging offers articles about how clinical trials work and how to participate about clinical trials.
• NIH Clinical Research Trials and You  : Answers from the NIH to many common questions about participating in a clinical trial
• Clinical Trials  (MedlinePlus - also en español)  : Information about clinical trial protocols and institutional review boards
• Federal Government Health Insurance Programs  : Information about federal programs that help pay the costs of care in clinical trials
• NIH Clinical Research Trials and You: Personal Stories  : Stories about volunteers and researchers
• Videos sobre la investigación clínica  : Spanish-language videos about participating in research
• What is a clinical trial?   
• Should I participate in a clinical trial? What’s in it for me? 
• What should I know to participate in a clinical trial? 
• HHS: Human Research Volunteer Informational videos  : Basic information about research, including questions to ask and what to think about when deciding whether to participate in a study

Last reviewed : April 2024

Unless otherwise specified, the information on our website and in our publications is in the public domain and may be reused or copied without permission. However, you may not reuse or copy images. Please cite the National Institute of Mental Health as the source. Read our copyright policy to learn more about our guidelines for reusing NIMH content.

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Decades of Polar Motion

Longer days, news media contacts.

Researchers used more than 120 years of data to decipher how melting ice, dwindling groundwater, and rising seas are nudging the planet’s spin axis and lengthening days.

Days on Earth are growing slightly longer, and that change is accelerating. The reason is connected to the same mechanisms that also have caused the planet’s axis to meander by about 30 feet (10 meters) in the past 120 years. The findings come from two recent NASA-funded studies focused on how the climate-related redistribution of ice and water has affected Earth’s rotation.

This redistribution occurs when ice sheets and glaciers melt more than they grow from snowfall and when aquifers lose more groundwater than precipitation replenishes. These resulting shifts in mass cause the planet to wobble as it spins and its axis to shift location — a phenomenon called polar motion. They also cause Earth’s rotation to slow, measured by the lengthening of the day. Both have been recorded since 1900.

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Analyzing polar motion across 12 decades, scientists attributed nearly all of the periodic oscillations in the axis’ position to changes in groundwater, ice sheets, glaciers, and sea levels. According to a paper published recently in Nature Geoscience , the mass variations during the 20th century mostly resulted from natural climate cycles.

The same researchers teamed on a subsequent study that focused on day length. They found that, since 2000, days have been getting longer by about 1.33 milliseconds per 100 years, a faster pace than at any point in the prior century. The cause: the accelerated melting of glaciers and the Antarctic and Greenland ice sheets due to human-caused greenhouse emissions. Their results were published July 15 in Proceedings of the National Academy of Sciences .

“The common thread between the two papers is that climate-related changes on Earth’s surface, whether human-caused or not, are strong drivers of the changes we’re seeing in the planet’s rotation,” said Surendra Adhikari, a co-author of both papers and a geophysicist at NASA’s Jet Propulsion Laboratory in Southern California.

In the earliest days, scientists tracked polar motion by measuring the apparent movement of stars. They later switched to very long baseline interferometry , which analyzes radio signals from quasars, or satellite laser ranging , which points lasers at satellites.

Researchers have long surmised that polar motion results from a combination of processes in Earth’s interior and at the surface. Less clear was how much each process shifts the axis and what kind of effect each exerts — whether cyclical movements that repeat in periods from weeks to decades, or sustained drift over the course of centuries or millennia.

For their paper, researchers used machine-learning algorithms to dissect the 120-year record. They found that 90% of recurring fluctuations between 1900 and 2018 could be explained by changes in groundwater, ice sheets, glaciers, and sea level. The remainder mostly resulted from Earth’s interior dynamics, like the wobble from the tilt of the inner core with respect to the bulk of the planet.

The patterns of polar motion linked to surface mass shifts repeated a few times about every 25 years during the 20th century, suggesting to the researchers that they were largely due to natural climate variations. Past papers have drawn connections between more recent polar motion and human activities, including one authored by Adhikari that attributed a sudden eastward drift of the axis (starting around 2000) to faster melting of the Greenland and Antarctic ice sheets and groundwater depletion in Eurasia.

That research focused on the past two decades, during which groundwater and ice mass loss as well as sea level rise — all measured via satellites — have had strong connections to human-caused climate change.

“It’s true to a certain degree” that human activities factor into polar motion, said Mostafa Kiani Shahvandi, lead author of both papers and a doctoral student at the Swiss university ETH Zurich. “But there are natural modes in the climate system that have the main effect on polar motion oscillations.”

For the second paper, the authors used satellite observations of mass change from the GRACE mission (short for Gravity Recovery and Climate Experiment) and its follow-on GRACE-FO , as well as previous mass-balance studies that analyzed the contributions of changes in groundwater, ice sheets, and glaciers to sea level rise in the 20th century to reconstruct changes in the length of days due to those factors from 1900 to 2018.

Scientists have known through historical eclipse records that length of day has been growing for millennia. While almost imperceptible to humans, the lag must be accounted for because many modern technologies, including GPS, rely on precise timekeeping.

In recent decades, the faster melting of ice sheets has shifted mass from the poles toward the equatorial ocean. This flattening causes Earth to decelerate and the day to lengthen, similar to when an ice skater lowers and spreads their arms to slow a spin.

The authors noticed an uptick just after 2000 in how fast the day was lengthening, a change closely correlated with independent observations of the flattening. For the period from 2000 to 2018, the rate of length-of-day increase due to movement of ice and groundwater was 1.33 milliseconds per century — faster than at any period in the prior 100 years, when it varied from 0.3 to 1.0 milliseconds per century.

The lengthening due to ice and groundwater changes could decelerate by 2100 under a climate scenario of severely reduced emissions, the researchers note. (Even if emissions were to stop today, previously released gases — particularly carbon dioxide — would linger for decades longer.)

If emissions continue to rise, lengthening of day from climate change could reach as high as 2.62 milliseconds per century, overtaking the effect of the Moon’s pull on tides, which has been increasing Earth’s length of day by 2.4 milliseconds per century, on average. Called lunar tidal friction, the effect has been the primary cause of Earth’s day-length increase for billions for years.

“In barely 100 years, human beings have altered the climate system to such a degree that we’re seeing the impact on the very way the planet spins,” Adhikari said.

Andrew Wang / Jane J. Lee Jet Propulsion Laboratory, Pasadena, Calif. 626-379-6874 / 818-354-0307 [email protected] / [email protected]

Related Terms

• Earth Science Division
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• GRACE (Gravity Recovery And Climate Experiment)
• GRACE-FO (Gravity Recovery and Climate Experiment Follow-on)

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Sharks in Brazil test positive for cocaine, scientists say

Cocaine consumption has risen massively around the world in recent decades, according to the study.

Sharks living off the coast of Brazil have tested positive for cocaine, according to new research, the first time that the drug has been detected in free-ranging sharks.

Scientists tested 13 Brazilian sharpnose sharks in the waters off the city of Rio de Janeiro and found cocaine present in both the liver and muscle tissue of all 13 specimens, according to a paper by researchers at the Oswaldo Cruz Foundation in Brazil sent to CNN on Tuesday.

The species was chosen due to its small size and the fact that it lives in a small area of coastal waters, where it is exposed to significant contaminant discharges for its entire life cycle, according to the study.

Cocaine levels were around three times higher in muscle tissue than liver tissue, according to the study, while female sharks had higher cocaine concentrations in muscle tissue compared to males.

Cocaine pollutes the sea due to sewage discharges from humans who use the drug, as well as the illegal laboratories that produce it, study co-author Enrico Mendes Saggioro, an ecotoxicologist at the foundation, told CNN on Tuesday.

Around 22% of users live in South America, the paper added, with Brazil the second largest consumer market in the region. Increased consumption and poor sewage treatment infrastructure has made for increased cocaine levels in the sea, say researchers.

Previous research suggested that cocaine dumped at sea by traffickers could be responsible for contamination, but that is not the case here, said Mendes Saggioro.

"We don't usually see many bales of coke dumped or lost at sea here, unlike what is reported in Mexico and Florida," he said.

Studies have not been conducted to determine whether cocaine damages the sharks' health, explained Mendes Saggioro and study co-author Rachel Ann Hauser Davis, a biologist at the foundation, but previous research has shown that the drug harms other animals such as fish and mussels.

"It is probable, although not yet proven that exposure would have deleterious physiological effects on the sharks," they said in a joint statement.

In addition, it is not possible to prove any effects on the sharks' behavior due to a lack of research, but "cocaine targets the brain and hyperactive and erratic behaviour has been noted in other animals," the pair explained.

Hauser Davis said that it is "very likely" that crustaceans, fish and other animals that the sharks prey on are also contaminated with cocaine.

The potential effects on human health are also difficult to establish, the pair explained, although "cocaine has already entered the food chain, as sharks are routinely eaten by humans in Brazil and in many other countries."

Next, the team plans to analyze other species of shark, as well as rays that live in river estuaries, said Mendes Saggioro.

"We also plan on assessing migratory fish, such as mullet, to verify if migratory behavior affects cocaine accumulation," he added.

The study appears in the journal Science of the Total Environment.

In 2021, researchers found that brown trout can become addicted to the illegal drug methamphetamine when it accumulates in waterways.

"Fish are sensitive to adverse effects of many neurologically active drugs from alcohol to cocaine and can develop drug addiction related to the dopamine reward pathway in a similar manner as humans," lead study author Pavel Horky, a behavioral ecologist from the Czech University of Life Sciences in Prague, told CNN via email at the time.

In 2019, researchers in the United Kingdom announced they had found traces of illicit drugs, pharmaceuticals and pesticides in samples of freshwater shrimp.

And the previous year, scientists working in Puget Sound, an inlet of the Pacific Ocean along the northwest coast of Washington state in the US, said that mussels in the area had tested positive for the prescription opioid oxycodone.

The-CNN-Wire & 2024 Cable News Network, Inc., a Warner Bros. Discovery Company. All rights reserved.

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What the data says about immigrants in the U.S.

The United States has long had more immigrants than any other country. In fact, the U.S. is home to one-fifth of the world’s international migrants . These immigrants have come from just about every country in the world.

Pew Research Center regularly publishes research on U.S. immigrants . Based on this research, here are answers to some key questions about the U.S. immigrant population.

Pew Research Center conducted this analysis to answer common questions about immigration to the United States and the U.S. immigrant population.

The data in this analysis comes mainly from Center tabulations of Census Bureau microdata from decennial censuses and American Community Survey (IPUMS USA). This analysis also features estimates of the U.S. unauthorized immigrant population . The estimates presented in this research for 2022 are the Center’s latest.

How many people in the U.S. are immigrants?

The U.S. foreign-born population reached a record 46.1 million in 2022. Growth accelerated after Congress made U.S. immigration laws more permissive in 1965. In 1970, the number of immigrants living in the U.S. was less than a quarter of what it is today.

Immigrants today account for 13.8% of the U.S. population. This is a roughly threefold increase from 4.7% in 1970. However, the immigrant share of the population today remains below the record 14.8% in 1890 .

Where are U.S. immigrants from?

Mexico is the top country of birth for U.S. immigrants. In 2022, roughly 10.6 million immigrants living in the U.S. were born there, making up 23% of all U.S. immigrants. The next largest origin groups were those from India (6%), China (5%), the Philippines (4%) and El Salvador (3%).

By region of birth, immigrants from Asia accounted for 28% of all immigrants. Other regions make up smaller shares:

• Latin America (27%), excluding Mexico but including the Caribbean (10%), Central America (9%) and South America (9%)
• Europe, Canada and other North America (12%)
• Sub-Saharan Africa (5%)
• Middle East and North Africa (4%)

How have immigrants’ origin countries changed in recent decades?

Before 1965, U.S. immigration law favored immigrants from Northern and Western Europe and mostly barred immigration from Asia. The 1965 Immigration and Nationality Act opened up immigration from Asia and Latin America. The Immigration Act of 1990 further increased legal immigration and allowed immigrants from more countries to enter the U.S. legally.

Since 1965, about 72 million immigrants have come to the United States from different and more countries than their predecessors:

• From 1840 to 1889, about 90% of U.S. immigrants came from Europe, including about 70% from Germany, Ireland and the United Kingdom.
• Almost 90% of the immigrants who arrived from 1890 to 1919 came from Europe. Nearly 60% came from Italy, Austria-Hungary and Russia-Poland.
• Since 1965, about half of U.S. immigrants have come from Latin America, with about a quarter from Mexico alone. About another quarter have come from Asia. Large numbers have come from China, India, the Philippines, Central America and the Caribbean.

The newest wave of immigrants has dramatically changed states’ immigrant populations . In 1980, German immigrants were the largest group in 19 states, Canadian immigrants were the largest in 11 states and Mexicans were the largest in 10 states. By 2000, Mexicans were the largest group in 31 states.

Today, Mexico remains the largest origin country for U.S. immigrants. However, immigration from Mexico has slowed since 2007 and the Mexican-born population in the U.S. has dropped. The Mexican share of the U.S. immigrant population dropped from 29% in 2010 to 23% in 2022.

Where are recent immigrants coming from?

In 2022, Mexico was the top country of birth for immigrants who arrived in the last year, with about 150,000 people. India (about 145,000) and China (about 90,000) were the next largest sources of immigrants. Venezuela, Cuba, Brazil and Canada each had about 50,000 to 60,000 new immigrant arrivals.

The main sources of immigrants have shifted twice in the 21st century. The first was caused by the Great Recession (2007-2009). Until 2007, more Hispanics than Asians arrived in the U.S. each year. From 2009 to 2018, the opposite was true.

Since 2019, immigration from Latin America – much of it unauthorized – has reversed the pattern again. More Hispanics than Asians have come each year.

What is the legal status of immigrants in the U.S.?

Most immigrants (77%) are in the country legally. As of 2022:

• 49% were naturalized U.S. citizens.
• 24% were lawful permanent residents.
• 4% were legal temporary residents.
• 23% were unauthorized immigrants .

From 1990 to 2007, the unauthorized immigrant population more than tripled in size, from 3.5 million to a record high of 12.2 million. From there, the number slowly declined to about 10.2 million in 2019.

In 2022, the number of unauthorized immigrants in the U.S. showed sustained growth for the first time since 2007, to 11.o million.

As of 2022, about 4 million unauthorized immigrants in the U.S. are Mexican. This is the largest number of any origin country, representing more than one-third of all unauthorized immigrants. However, the Mexican unauthorized immigrant population is down from a peak of almost 7 million in 2007, when Mexicans accounted for 57% of all unauthorized immigrants.

The drop in the number of unauthorized immigrants from Mexico has been partly offset by growth from other parts of the world, especially Asia and other parts of Latin America.

The 2022 estimates of the unauthorized immigrant population are our latest comprehensive estimates. Other partial data sources suggest continued growth in 2023 and 2024 .

Who are unauthorized immigrants?

Virtually all unauthorized immigrants living in the U.S. entered the country without legal permission or arrived on a nonpermanent visa and stayed after it expired.

A growing number of unauthorized immigrants have permission to live and work in the U.S. and are temporarily protected from deportation. In 2022, about 3 million unauthorized immigrants had these temporary legal protections. These immigrants fall into several groups:

• Temporary Protected Status (TPS): About 650,000 immigrants have TPS as of July 2022. TPS is offered to individuals who cannot safely return to their home country because of civil unrest, violence, natural disaster or other extraordinary and temporary conditions.
• Deferred Action for Childhood Arrivals program (DACA): Almost 600,000 immigrants are beneficiaries of DACA. This program allows individuals brought to the U.S. as children before 2007 to remain in the U.S.
• Asylum applicants: About 1.6 million immigrants have pending applications for asylum in the U.S. as of mid-2022 because of dangers faced in their home country. These immigrants can stay in the U.S. legally while they wait for a decision on their case.
• Other protections: Several hundred thousand individuals have applied for special visas to become lawful immigrants. These types of visas are offered to victims of trafficking and certain other criminal activities.

In addition, about 500,000 immigrants arrived in the U.S. by the end of 2023 under programs created for Ukrainians (U4U or Uniting for Ukraine ) and people from Cuba, Haiti, Nicaragua and Venezuela ( CHNV parole ). These immigrants mainly arrived too late to be counted in the 2022 estimates but may be included in future estimates.

Do all lawful immigrants choose to become U.S. citizens?

Immigrants who are lawful permanent residents can apply to become U.S. citizens if they meet certain requirements. In fiscal year 2022, almost 1 million lawful immigrants became U.S. citizens through naturalization . This is only slightly below record highs in 1996 and 2008.

Most immigrants eligible for naturalization apply for citizenship, but not all do. Top reasons for not applying include language and personal barriers, lack of interest and not being able to afford it, according to a 2015 Pew Research Center survey .

Where do most U.S. immigrants live?

In 2022, most of the nation’s 46.1 million immigrants lived in four states: California (10.4 million or 23% of the national total), Texas (5.2 million or 11%), Florida (4.8 million or 10%) and New York (4.5 million or 10%).

Most immigrants lived in the South (35%) and West (33%). Another 21% lived in the Northeast and 11% were in the Midwest.

In 2022, more than 29 million immigrants – 63% of the nation’s foreign-born population – lived in just 20 major metropolitan areas. The largest populations were in the New York, Los Angeles and Miami metro areas. Most of the nation’s unauthorized immigrant population (60%) lived in these metro areas as well.

How many immigrants are working in the U.S.?

In 2022, over 30 million immigrants were in the U.S. workforce. Lawful immigrants made up the majority of the immigrant workforce, at 22.2 million. An additional 8.3 million immigrant workers are unauthorized. This is a notable increase over 2019 but about the same as in 2007 .

The share of workers who are immigrants increased slightly from 17% in 2007 to 18% in 2022. By contrast, the share of immigrant workers who are unauthorized declined from a peak of 5.4% in 2007 to 4.8% in 2022. Immigrants and their children are projected to add about 18 million people of working age between 2015 and 2035. This would offset an expected decline in the working-age population from retiring Baby Boomers.

How educated are immigrants compared with the U.S. population overall?

On average, U.S. immigrants have lower levels of education than the U.S.-born population. In 2022, immigrants ages 25 and older were about three times as likely as the U.S. born to have not completed high school (25% vs. 7%). However, immigrants were as likely as the U.S. born to have a bachelor’s degree or more (35% vs. 36%).

Immigrant educational attainment varies by origin. About half of immigrants from Mexico (51%) had not completed high school, and the same was true for 46% of those from Central America and 21% from the Caribbean. Immigrants from these three regions were also less likely than the U.S. born to have a bachelor’s degree or more.

On the other hand, immigrants from all other regions were about as likely as or more likely than the U.S. born to have at least a bachelor’s degree. Immigrants from South Asia (72%) were the most likely to have a bachelor’s degree or more.

How well do immigrants speak English?

About half of immigrants ages 5 and older (54%) are proficient English speakers – they either speak English very well (37%) or speak only English at home (17%).

Immigrants from Canada (97%), Oceania (82%), sub-Saharan Africa (76%), Europe (75%) and South Asia (73%) have the highest rates of English proficiency.

Immigrants from Mexico (36%) and Central America (35%) have the lowest proficiency rates.

Immigrants who have lived in the U.S. longer are somewhat more likely to be English proficient. Some 45% of immigrants who have lived in the U.S. for five years or less are proficient, compared with 56% of immigrants who have lived in the U.S. for 20 years or more.

Spanish is the most commonly spoken language among U.S. immigrants. About four-in-ten immigrants (41%) speak Spanish at home. Besides Spanish, the top languages immigrants speak at home are English only (17%), Chinese (6%), Filipino/Tagalog (4%), French or Haitian Creole (3%), and Vietnamese (2%).

Note: This is an update of a post originally published May 3, 2017.

• Immigrant Populations
• Immigration & Migration
• Unauthorized Immigration

Mohamad Moslimani is a research analyst focusing on race and ethnicity at Pew Research Center .

Jeffrey S. Passel is a senior demographer at Pew Research Center .

What we know about unauthorized immigrants living in the U.S.

How the origins of america’s immigrants have changed since 1850, in some countries, immigration accounted for all population growth between 2000 and 2020, cultural issues and the 2024 election, how temporary protected status has expanded under the biden administration, most popular.

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Moderate drinking won't prolong your life, new research indicates

NEW YORK, July 25 (UPI) -- Moderate drinking won't lengthen your life, a new report suggests, challenging earlier findings that a glass of wine a day is healthy.

That report, generated by the Canadian Institute for Substance Use Research at the University of Victoria in British Columbia, Canada, appeared Thursday in the Journal of Studies on Alcohol and Drugs -- from the Center of Alcohol & Substance Use Studies at Rutgers University in New Jersey. Advertisement

Researchers said previous recommendation touting the life-extending benefit of wine relied on flawed scientific research.

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But not all studies have portrayed alcohol in such a positive light -- and this new analysis explains why. Advertisement

The public should "be skeptical of claims that alcohol use in moderation may prolong life and reduce the risk of serious health conditions and premature death," the study's lead author, Tim Stockwell, a scientist at the Canadian Institute for Substance Use Research, told UPI via email.

"Drinking less or not at all is more consistent with improving health and well-being," added Stockwell, who also is a professor emeritus and adjunct professor in the Department of Psychology at the University of Victoria.

The studies that show a favorable impact from alcohol use typically focused on older adults and failed to consider people's lifetime drinking habits, Stockwell said.

They compared moderate drinkers with "abstainer" and "occasional drinker" groups that included some older adults who had quit or lowered their alcohol consumption because they had developed health conditions, he added.

"This makes people who are able to keep on drinking look very healthy by comparison," Stockwell said, noting that looks can be deceptive.

For this analysis, researchers identified 107 published studies that followed people over time and examined the relationship between drinking habits and longevity.

When they amassed all the data, it appeared that light-to-moderate drinkers -- those who imbibed between one drink per week and two per day -- had a 14% lower risk of dying during the study period compared with abstainers. Advertisement

That changed, however, when researchers probed more deeply. Moderate drinking was not associated with a longer life in a handful of "higher quality" studies, researchers said.

These studies included people who were relatively young at the outset (younger than 55, on average) and had ensured former and occasional drinkers were not considered "abstainers."

Instead, it was the weakest studies -- involving older participants with no differentiation between former drinkers and lifelong abstainers -- that linked moderate drinking to greater longevity.

"Well-designed, high-quality studies did not find health benefits," Stockwell said. "Poorly designed, low-quality studies found large benefits."

The concept that moderate drinking leads to a longer, healthier life can be traced back decades.

For instance, researchers alluded to the "French paradox" -- an idea popularized in the 1990s that promoted red wine as helpful in explaining why French people experience relatively low rates of heart disease, despite a rich, fatty diet.

In reality, moderate drinking likely does not lengthen people's lives -- rather, it comes with some potential health hazards, including heighted risks of certain cancers. That's why no significant health organization has ever set a risk-free level of alcohol intake, the researchers noted.

However, this study shouldn't be the basis for establishing drinking guidelines, said Stockwell, who has studied alcohol consumption and its hypothetical health benefits for about 25 years. Advertisement

"The great majority of deaths are not due to alcohol, so the results are likely confounded by lifestyle and other uncontrolled factors," he said.

"Our study was really about how misleading the majority of such studies are -- and how the appearance of health benefits vanishes when studies use more rigorous methods."

He added that "our research casts further doubt on the comforting idea that moderate drinking has health benefits."

Dr. Tyler Saunders, an internal medicine physician at Endeavor Health in Chicago, said alcohol consumption has a negative impact on patients' lives. He was not involved in the study.

For instance, drinking lowers metabolism, interfering with weight loss. Alcohol also causes specific changes in body composition, increasing belly fat, which is directly related to cardiovascular risk and inflammation, Saunders said.

In addition, he noted that alcohol decreases rapid eye movement sleep, a stage in which most dreams occur. REM sleep also may affect learning, memory and mood.

"I don't think we can conclude that no one should drink from this study alone. More research is needed before making such a statement," Saunders said.

"However, for those trying to improve their health -- diet, sleep and energy -- studies like this may prompt us to reconsider regular, consistent alcohol consumption," he said. Advertisement

Based on the most recent and more rigorously designed studies, there are no levels of alcohol use that provide overall health benefit, said Dr. Brian P. Lee, who specializes in liver disease at the Keck School of Medicine of the University of Southern California in Los Angeles.

"This current study shows how and why prior studies that did show benefit were flawed," Lee said, adding that it's important for health care providers "to be consistent with our messaging to the public -- you may like alcohol and it may be enjoyable, but it doesn't prolong your life."

For those who consume alcohol, the study suggests that "it is safest, both in the near-term and over prolonged periods of time, to drink in moderation," said Dr. Martin Plawecki, an investigator in the Indiana Alcohol Research Center at Indiana University School of Medicine in Indianapolis.

Plawecki, who also is an associate professor of psychiatry, cited the National Institute on Alcohol Abuse and Alcoholism's recommendation that "drinking less is better for health than drinking more."

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