a literature review includes

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Writing a Literature Review

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A literature review is a document or section of a document that collects key sources on a topic and discusses those sources in conversation with each other (also called synthesis ). The lit review is an important genre in many disciplines, not just literature (i.e., the study of works of literature such as novels and plays). When we say “literature review” or refer to “the literature,” we are talking about the research ( scholarship ) in a given field. You will often see the terms “the research,” “the scholarship,” and “the literature” used mostly interchangeably.

Where, when, and why would I write a lit review?

There are a number of different situations where you might write a literature review, each with slightly different expectations; different disciplines, too, have field-specific expectations for what a literature review is and does. For instance, in the humanities, authors might include more overt argumentation and interpretation of source material in their literature reviews, whereas in the sciences, authors are more likely to report study designs and results in their literature reviews; these differences reflect these disciplines’ purposes and conventions in scholarship. You should always look at examples from your own discipline and talk to professors or mentors in your field to be sure you understand your discipline’s conventions, for literature reviews as well as for any other genre.

A literature review can be a part of a research paper or scholarly article, usually falling after the introduction and before the research methods sections. In these cases, the lit review just needs to cover scholarship that is important to the issue you are writing about; sometimes it will also cover key sources that informed your research methodology.

Lit reviews can also be standalone pieces, either as assignments in a class or as publications. In a class, a lit review may be assigned to help students familiarize themselves with a topic and with scholarship in their field, get an idea of the other researchers working on the topic they’re interested in, find gaps in existing research in order to propose new projects, and/or develop a theoretical framework and methodology for later research. As a publication, a lit review usually is meant to help make other scholars’ lives easier by collecting and summarizing, synthesizing, and analyzing existing research on a topic. This can be especially helpful for students or scholars getting into a new research area, or for directing an entire community of scholars toward questions that have not yet been answered.

What are the parts of a lit review?

Most lit reviews use a basic introduction-body-conclusion structure; if your lit review is part of a larger paper, the introduction and conclusion pieces may be just a few sentences while you focus most of your attention on the body. If your lit review is a standalone piece, the introduction and conclusion take up more space and give you a place to discuss your goals, research methods, and conclusions separately from where you discuss the literature itself.

Introduction:

• An introductory paragraph that explains what your working topic and thesis is
• A forecast of key topics or texts that will appear in the review
• Potentially, a description of how you found sources and how you analyzed them for inclusion and discussion in the review (more often found in published, standalone literature reviews than in lit review sections in an article or research paper)
• Summarize and synthesize: Give an overview of the main points of each source and combine them into a coherent whole
• Analyze and interpret: Don’t just paraphrase other researchers – add your own interpretations where possible, discussing the significance of findings in relation to the literature as a whole
• Critically Evaluate: Mention the strengths and weaknesses of your sources
• Write in well-structured paragraphs: Use transition words and topic sentence to draw connections, comparisons, and contrasts.

Conclusion:

• Summarize the key findings you have taken from the literature and emphasize their significance
• Connect it back to your primary research question

How should I organize my lit review?

Lit reviews can take many different organizational patterns depending on what you are trying to accomplish with the review. Here are some examples:

• Chronological : The simplest approach is to trace the development of the topic over time, which helps familiarize the audience with the topic (for instance if you are introducing something that is not commonly known in your field). If you choose this strategy, be careful to avoid simply listing and summarizing sources in order. Try to analyze the patterns, turning points, and key debates that have shaped the direction of the field. Give your interpretation of how and why certain developments occurred (as mentioned previously, this may not be appropriate in your discipline — check with a teacher or mentor if you’re unsure).
• Thematic : If you have found some recurring central themes that you will continue working with throughout your piece, you can organize your literature review into subsections that address different aspects of the topic. For example, if you are reviewing literature about women and religion, key themes can include the role of women in churches and the religious attitude towards women.
• Qualitative versus quantitative research
• Empirical versus theoretical scholarship
• Divide the research by sociological, historical, or cultural sources
• Theoretical : In many humanities articles, the literature review is the foundation for the theoretical framework. You can use it to discuss various theories, models, and definitions of key concepts. You can argue for the relevance of a specific theoretical approach or combine various theorical concepts to create a framework for your research.

What are some strategies or tips I can use while writing my lit review?

Any lit review is only as good as the research it discusses; make sure your sources are well-chosen and your research is thorough. Don’t be afraid to do more research if you discover a new thread as you’re writing. More info on the research process is available in our "Conducting Research" resources .

As you’re doing your research, create an annotated bibliography ( see our page on the this type of document ). Much of the information used in an annotated bibliography can be used also in a literature review, so you’ll be not only partially drafting your lit review as you research, but also developing your sense of the larger conversation going on among scholars, professionals, and any other stakeholders in your topic.

Usually you will need to synthesize research rather than just summarizing it. This means drawing connections between sources to create a picture of the scholarly conversation on a topic over time. Many student writers struggle to synthesize because they feel they don’t have anything to add to the scholars they are citing; here are some strategies to help you:

• It often helps to remember that the point of these kinds of syntheses is to show your readers how you understand your research, to help them read the rest of your paper.
• Writing teachers often say synthesis is like hosting a dinner party: imagine all your sources are together in a room, discussing your topic. What are they saying to each other?
• Look at the in-text citations in each paragraph. Are you citing just one source for each paragraph? This usually indicates summary only. When you have multiple sources cited in a paragraph, you are more likely to be synthesizing them (not always, but often
• Read more about synthesis here.

The most interesting literature reviews are often written as arguments (again, as mentioned at the beginning of the page, this is discipline-specific and doesn’t work for all situations). Often, the literature review is where you can establish your research as filling a particular gap or as relevant in a particular way. You have some chance to do this in your introduction in an article, but the literature review section gives a more extended opportunity to establish the conversation in the way you would like your readers to see it. You can choose the intellectual lineage you would like to be part of and whose definitions matter most to your thinking (mostly humanities-specific, but this goes for sciences as well). In addressing these points, you argue for your place in the conversation, which tends to make the lit review more compelling than a simple reporting of other sources.

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What is a Literature Review? How to Write It (with Examples)

A literature review is a critical analysis and synthesis of existing research on a particular topic. It provides an overview of the current state of knowledge, identifies gaps, and highlights key findings in the literature. 1 The purpose of a literature review is to situate your own research within the context of existing scholarship, demonstrating your understanding of the topic and showing how your work contributes to the ongoing conversation in the field. Learning how to write a literature review is a critical tool for successful research. Your ability to summarize and synthesize prior research pertaining to a certain topic demonstrates your grasp on the topic of study, and assists in the learning process. 

Table of Contents

• What is the purpose of literature review? 
• a. Habitat Loss and Species Extinction: 
• b. Range Shifts and Phenological Changes: 
• c. Ocean Acidification and Coral Reefs: 
• d. Adaptive Strategies and Conservation Efforts: 
• How to write a good literature review 
• Choose a Topic and Define the Research Question: 
• Decide on the Scope of Your Review: 
• Select Databases for Searches: 
• Conduct Searches and Keep Track: 
• Review the Literature: 
• Organize and Write Your Literature Review: 
• Frequently asked questions 

What is a literature review?

A well-conducted literature review demonstrates the researcher’s familiarity with the existing literature, establishes the context for their own research, and contributes to scholarly conversations on the topic. One of the purposes of a literature review is also to help researchers avoid duplicating previous work and ensure that their research is informed by and builds upon the existing body of knowledge.

What is the purpose of literature review?

A literature review serves several important purposes within academic and research contexts. Here are some key objectives and functions of a literature review: 2  

• Contextualizing the Research Problem: The literature review provides a background and context for the research problem under investigation. It helps to situate the study within the existing body of knowledge. 
• Identifying Gaps in Knowledge: By identifying gaps, contradictions, or areas requiring further research, the researcher can shape the research question and justify the significance of the study. This is crucial for ensuring that the new research contributes something novel to the field. 
• Understanding Theoretical and Conceptual Frameworks: Literature reviews help researchers gain an understanding of the theoretical and conceptual frameworks used in previous studies. This aids in the development of a theoretical framework for the current research. 
• Providing Methodological Insights: Another purpose of literature reviews is that it allows researchers to learn about the methodologies employed in previous studies. This can help in choosing appropriate research methods for the current study and avoiding pitfalls that others may have encountered. 
• Establishing Credibility: A well-conducted literature review demonstrates the researcher’s familiarity with existing scholarship, establishing their credibility and expertise in the field. It also helps in building a solid foundation for the new research. 
• Informing Hypotheses or Research Questions: The literature review guides the formulation of hypotheses or research questions by highlighting relevant findings and areas of uncertainty in existing literature. 

Literature review example

Let’s delve deeper with a literature review example: Let’s say your literature review is about the impact of climate change on biodiversity. You might format your literature review into sections such as the effects of climate change on habitat loss and species extinction, phenological changes, and marine biodiversity. Each section would then summarize and analyze relevant studies in those areas, highlighting key findings and identifying gaps in the research. The review would conclude by emphasizing the need for further research on specific aspects of the relationship between climate change and biodiversity. The following literature review template provides a glimpse into the recommended literature review structure and content, demonstrating how research findings are organized around specific themes within a broader topic. 

Literature Review on Climate Change Impacts on Biodiversity:

Climate change is a global phenomenon with far-reaching consequences, including significant impacts on biodiversity. This literature review synthesizes key findings from various studies: 

a. Habitat Loss and Species Extinction:

Climate change-induced alterations in temperature and precipitation patterns contribute to habitat loss, affecting numerous species (Thomas et al., 2004). The review discusses how these changes increase the risk of extinction, particularly for species with specific habitat requirements. 

b. Range Shifts and Phenological Changes:

Observations of range shifts and changes in the timing of biological events (phenology) are documented in response to changing climatic conditions (Parmesan & Yohe, 2003). These shifts affect ecosystems and may lead to mismatches between species and their resources. 

c. Ocean Acidification and Coral Reefs:

The review explores the impact of climate change on marine biodiversity, emphasizing ocean acidification’s threat to coral reefs (Hoegh-Guldberg et al., 2007). Changes in pH levels negatively affect coral calcification, disrupting the delicate balance of marine ecosystems. 

d. Adaptive Strategies and Conservation Efforts:

Recognizing the urgency of the situation, the literature review discusses various adaptive strategies adopted by species and conservation efforts aimed at mitigating the impacts of climate change on biodiversity (Hannah et al., 2007). It emphasizes the importance of interdisciplinary approaches for effective conservation planning. 

How to write a good literature review

Writing a literature review involves summarizing and synthesizing existing research on a particular topic. A good literature review format should include the following elements. 

Introduction: The introduction sets the stage for your literature review, providing context and introducing the main focus of your review. 

• Opening Statement: Begin with a general statement about the broader topic and its significance in the field. 
• Scope and Purpose: Clearly define the scope of your literature review. Explain the specific research question or objective you aim to address. 
• Organizational Framework: Briefly outline the structure of your literature review, indicating how you will categorize and discuss the existing research. 
• Significance of the Study: Highlight why your literature review is important and how it contributes to the understanding of the chosen topic. 
• Thesis Statement: Conclude the introduction with a concise thesis statement that outlines the main argument or perspective you will develop in the body of the literature review. 

Body: The body of the literature review is where you provide a comprehensive analysis of existing literature, grouping studies based on themes, methodologies, or other relevant criteria. 

• Organize by Theme or Concept: Group studies that share common themes, concepts, or methodologies. Discuss each theme or concept in detail, summarizing key findings and identifying gaps or areas of disagreement. 
• Critical Analysis: Evaluate the strengths and weaknesses of each study. Discuss the methodologies used, the quality of evidence, and the overall contribution of each work to the understanding of the topic. 
• Synthesis of Findings: Synthesize the information from different studies to highlight trends, patterns, or areas of consensus in the literature. 
• Identification of Gaps: Discuss any gaps or limitations in the existing research and explain how your review contributes to filling these gaps. 
• Transition between Sections: Provide smooth transitions between different themes or concepts to maintain the flow of your literature review. 

Conclusion: The conclusion of your literature review should summarize the main findings, highlight the contributions of the review, and suggest avenues for future research. 

• Summary of Key Findings: Recap the main findings from the literature and restate how they contribute to your research question or objective. 
• Contributions to the Field: Discuss the overall contribution of your literature review to the existing knowledge in the field. 
• Implications and Applications: Explore the practical implications of the findings and suggest how they might impact future research or practice. 
• Recommendations for Future Research: Identify areas that require further investigation and propose potential directions for future research in the field. 
• Final Thoughts: Conclude with a final reflection on the importance of your literature review and its relevance to the broader academic community. 

Conducting a literature review

Conducting a literature review is an essential step in research that involves reviewing and analyzing existing literature on a specific topic. It’s important to know how to do a literature review effectively, so here are the steps to follow: 1  

Choose a Topic and Define the Research Question:

• Select a topic that is relevant to your field of study. 
• Clearly define your research question or objective. Determine what specific aspect of the topic do you want to explore? 

Decide on the Scope of Your Review:

• Determine the timeframe for your literature review. Are you focusing on recent developments, or do you want a historical overview? 
• Consider the geographical scope. Is your review global, or are you focusing on a specific region? 
• Define the inclusion and exclusion criteria. What types of sources will you include? Are there specific types of studies or publications you will exclude? 

Select Databases for Searches:

• Identify relevant databases for your field. Examples include PubMed, IEEE Xplore, Scopus, Web of Science, and Google Scholar. 
• Consider searching in library catalogs, institutional repositories, and specialized databases related to your topic. 

Conduct Searches and Keep Track:

• Develop a systematic search strategy using keywords, Boolean operators (AND, OR, NOT), and other search techniques. 
• Record and document your search strategy for transparency and replicability. 
• Keep track of the articles, including publication details, abstracts, and links. Use citation management tools like EndNote, Zotero, or Mendeley to organize your references. 

Review the Literature:

• Evaluate the relevance and quality of each source. Consider the methodology, sample size, and results of studies. 
• Organize the literature by themes or key concepts. Identify patterns, trends, and gaps in the existing research. 
• Summarize key findings and arguments from each source. Compare and contrast different perspectives. 
• Identify areas where there is a consensus in the literature and where there are conflicting opinions. 
• Provide critical analysis and synthesis of the literature. What are the strengths and weaknesses of existing research? 

Organize and Write Your Literature Review:

• Literature review outline should be based on themes, chronological order, or methodological approaches. 
• Write a clear and coherent narrative that synthesizes the information gathered. 
• Use proper citations for each source and ensure consistency in your citation style (APA, MLA, Chicago, etc.). 
• Conclude your literature review by summarizing key findings, identifying gaps, and suggesting areas for future research. 

The literature review sample and detailed advice on writing and conducting a review will help you produce a well-structured report. But remember that a literature review is an ongoing process, and it may be necessary to revisit and update it as your research progresses. 

Frequently asked questions

A literature review is a critical and comprehensive analysis of existing literature (published and unpublished works) on a specific topic or research question and provides a synthesis of the current state of knowledge in a particular field. A well-conducted literature review is crucial for researchers to build upon existing knowledge, avoid duplication of efforts, and contribute to the advancement of their field. It also helps researchers situate their work within a broader context and facilitates the development of a sound theoretical and conceptual framework for their studies.

Literature review is a crucial component of research writing, providing a solid background for a research paper’s investigation. The aim is to keep professionals up to date by providing an understanding of ongoing developments within a specific field, including research methods, and experimental techniques used in that field, and present that knowledge in the form of a written report. Also, the depth and breadth of the literature review emphasizes the credibility of the scholar in his or her field.  

Before writing a literature review, it’s essential to undertake several preparatory steps to ensure that your review is well-researched, organized, and focused. This includes choosing a topic of general interest to you and doing exploratory research on that topic, writing an annotated bibliography, and noting major points, especially those that relate to the position you have taken on the topic. 

Literature reviews and academic research papers are essential components of scholarly work but serve different purposes within the academic realm. 3 A literature review aims to provide a foundation for understanding the current state of research on a particular topic, identify gaps or controversies, and lay the groundwork for future research. Therefore, it draws heavily from existing academic sources, including books, journal articles, and other scholarly publications. In contrast, an academic research paper aims to present new knowledge, contribute to the academic discourse, and advance the understanding of a specific research question. Therefore, it involves a mix of existing literature (in the introduction and literature review sections) and original data or findings obtained through research methods. 

Literature reviews are essential components of academic and research papers, and various strategies can be employed to conduct them effectively. If you want to know how to write a literature review for a research paper, here are four common approaches that are often used by researchers.  Chronological Review: This strategy involves organizing the literature based on the chronological order of publication. It helps to trace the development of a topic over time, showing how ideas, theories, and research have evolved.  Thematic Review: Thematic reviews focus on identifying and analyzing themes or topics that cut across different studies. Instead of organizing the literature chronologically, it is grouped by key themes or concepts, allowing for a comprehensive exploration of various aspects of the topic.  Methodological Review: This strategy involves organizing the literature based on the research methods employed in different studies. It helps to highlight the strengths and weaknesses of various methodologies and allows the reader to evaluate the reliability and validity of the research findings.  Theoretical Review: A theoretical review examines the literature based on the theoretical frameworks used in different studies. This approach helps to identify the key theories that have been applied to the topic and assess their contributions to the understanding of the subject.  It’s important to note that these strategies are not mutually exclusive, and a literature review may combine elements of more than one approach. The choice of strategy depends on the research question, the nature of the literature available, and the goals of the review. Additionally, other strategies, such as integrative reviews or systematic reviews, may be employed depending on the specific requirements of the research.

The literature review format can vary depending on the specific publication guidelines. However, there are some common elements and structures that are often followed. Here is a general guideline for the format of a literature review:  Introduction:   Provide an overview of the topic.  Define the scope and purpose of the literature review.  State the research question or objective.  Body:   Organize the literature by themes, concepts, or chronology.  Critically analyze and evaluate each source.  Discuss the strengths and weaknesses of the studies.  Highlight any methodological limitations or biases.  Identify patterns, connections, or contradictions in the existing research.  Conclusion:   Summarize the key points discussed in the literature review.  Highlight the research gap.  Address the research question or objective stated in the introduction.  Highlight the contributions of the review and suggest directions for future research.

Both annotated bibliographies and literature reviews involve the examination of scholarly sources. While annotated bibliographies focus on individual sources with brief annotations, literature reviews provide a more in-depth, integrated, and comprehensive analysis of existing literature on a specific topic. The key differences are as follows: 

References 

• Denney, A. S., & Tewksbury, R. (2013). How to write a literature review.  Journal of criminal justice education ,  24 (2), 218-234. 
• Pan, M. L. (2016).  Preparing literature reviews: Qualitative and quantitative approaches . Taylor & Francis. 
• Cantero, C. (2019). How to write a literature review.  San José State University Writing Center . 

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How To Write A Literature Review - A Complete Guide

Table of Contents

A literature review is much more than just another section in your research paper. It forms the very foundation of your research. It is a formal piece of writing where you analyze the existing theoretical framework, principles, and assumptions and use that as a base to shape your approach to the research question.

Curating and drafting a solid literature review section not only lends more credibility to your research paper but also makes your research tighter and better focused. But, writing literature reviews is a difficult task. It requires extensive reading, plus you have to consider market trends and technological and political changes, which tend to change in the blink of an eye.

Now streamline your literature review process with the help of SciSpace Copilot. With this AI research assistant, you can efficiently synthesize and analyze a vast amount of information, identify key themes and trends, and uncover gaps in the existing research. Get real-time explanations, summaries, and answers to your questions for the paper you're reviewing, making navigating and understanding the complex literature landscape easier.

In this comprehensive guide, we will explore everything from the definition of a literature review, its appropriate length, various types of literature reviews, and how to write one.

What is a literature review?

A literature review is a collation of survey, research, critical evaluation, and assessment of the existing literature in a preferred domain.

Eminent researcher and academic Arlene Fink, in her book Conducting Research Literature Reviews , defines it as the following:

“A literature review surveys 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 explored while researching a particular topic, and to demonstrate to your readers how your research fits within a larger field of study.”

Simply put, a literature review can be defined as a critical discussion of relevant pre-existing research around your research question and carving out a definitive place for your study in the existing body of knowledge. Literature reviews can be presented in multiple ways: a section of an article, the whole research paper itself, or a chapter of your thesis.

A literature review does function as a summary of sources, but it also allows you to analyze further, interpret, and examine the stated theories, methods, viewpoints, and, of course, the gaps in the existing content.

As an author, you can discuss and interpret the research question and its various aspects and debate your adopted methods to support the claim.

What is the purpose of a literature review?

A literature review is meant to help your readers understand the relevance of your research question and where it fits within the existing body of knowledge. As a researcher, you should use it to set the context, build your argument, and establish the need for your study.

What is the importance of a literature review?

The literature review is a critical part of research papers because it helps you:

• Gain an in-depth understanding of your research question and the surrounding area
• Convey that you have a thorough understanding of your research area and are up-to-date with the latest changes and advancements
• Establish how your research is connected or builds on the existing body of knowledge and how it could contribute to further research
• Elaborate on the validity and suitability of your theoretical framework and research methodology
• Identify and highlight gaps and shortcomings in the existing body of knowledge and how things need to change
• Convey to readers how your study is different or how it contributes to the research area

How long should a literature review be?

Ideally, the literature review should take up 15%-40% of the total length of your manuscript. So, if you have a 10,000-word research paper, the minimum word count could be 1500.

Your literature review format depends heavily on the kind of manuscript you are writing — an entire chapter in case of doctoral theses, a part of the introductory section in a research article, to a full-fledged review article that examines the previously published research on a topic.

Another determining factor is the type of research you are doing. The literature review section tends to be longer for secondary research projects than primary research projects.

What are the different types of literature reviews?

All literature reviews are not the same. There are a variety of possible approaches that you can take. It all depends on the type of research you are pursuing.

Here are the different types of literature reviews:

Argumentative review

It is called an argumentative review when you carefully present literature that only supports or counters a specific argument or premise to establish a viewpoint.

Integrative review

It is a type of literature review focused on building a comprehensive understanding of a topic by combining available theoretical frameworks and empirical evidence.

Methodological review

This approach delves into the ''how'' and the ''what" of the research question —  you cannot look at the outcome in isolation; you should also review the methodology used.

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 collect, report, and analyze data from the studies included in the review.

Meta-analysis review

Meta-analysis uses statistical methods to summarize the results of independent studies. By combining information from all relevant studies, meta-analysis can provide more precise estimates of the effects than those derived from the individual studies included within a review.

Historical review

Historical literature reviews focus on examining research throughout a period, often starting with the first time an issue, concept, theory, or phenomenon 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 identify future research's likely directions.

Theoretical Review

This form aims to examine the corpus of theory accumulated regarding an issue, concept, theory, and phenomenon. The theoretical literature review helps to establish what theories exist, the relationships between them, the degree the existing approaches have been investigated, and to develop new hypotheses to be tested.

Scoping Review

The Scoping Review is often used at the beginning of an article, dissertation, or research proposal. It is conducted before the research to highlight gaps in the existing body of knowledge and explains why the project should be greenlit.

State-of-the-Art Review

The State-of-the-Art review is conducted periodically, focusing on the most recent research. It describes what is currently known, understood, or agreed upon regarding the research topic and highlights where there are still disagreements.

Can you use the first person in a literature review?

When writing literature reviews, you should avoid the usage of first-person pronouns. It means that instead of "I argue that" or "we argue that," the appropriate expression would be "this research paper argues that."

Do you need an abstract for a literature review?

Ideally, yes. It is always good to have a condensed summary that is self-contained and independent of the rest of your review. As for how to draft one, you can follow the same fundamental idea when preparing an abstract for a literature review. It should also include:

• The research topic and your motivation behind selecting it
• A one-sentence thesis statement
• An explanation of the kinds of literature featured in the review
• Summary of what you've learned
• Conclusions you drew from the literature you reviewed
• Potential implications and future scope for research

Here's an example of the abstract of a literature review

Is a literature review written in the past tense?

Yes, the literature review should ideally be written in the past tense. You should not use the present or future tense when writing one. The exceptions are when you have statements describing events that happened earlier than the literature you are reviewing or events that are currently occurring; then, you can use the past perfect or present perfect tenses.

How many sources for a literature review?

There are multiple approaches to deciding how many sources to include in a literature review section. The first approach would be to look level you are at as a researcher. For instance, a doctoral thesis might need 60+ sources. In contrast, you might only need to refer to 5-15 sources at the undergraduate level.

The second approach is based on the kind of literature review you are doing — whether it is merely a chapter of your paper or if it is a self-contained paper in itself. When it is just a chapter, sources should equal the total number of pages in your article's body. In the second scenario, you need at least three times as many sources as there are pages in your work.

Quick tips on how to write a literature review

To know how to write a literature review, you must clearly understand its impact and role in establishing your work as substantive research material.

You need to follow the below-mentioned steps, to write a literature review:

• Outline the purpose behind the literature review
• Search relevant literature
• Examine and assess the relevant resources
• Discover connections by drawing deep insights from the resources
• Structure planning to write a good literature review

1. Outline and identify the purpose of  a literature review

As a first step on how to write a literature review, you must know what the research question or topic is and what shape you want your literature review to take. Ensure you understand the research topic inside out, or else seek clarifications. You must be able to the answer below questions before you start:

• How many sources do I need to include?
• What kind of sources should I analyze?
• How much should I critically evaluate each source?
• Should I summarize, synthesize or offer a critique of the sources?
• Do I need to include any background information or definitions?

Additionally, you should know that the narrower your research topic is, the swifter it will be for you to restrict the number of sources to be analyzed.

2. Search relevant literature

Dig deeper into search engines to discover what has already been published around your chosen topic. Make sure you thoroughly go through appropriate reference sources like books, reports, journal articles, government docs, and web-based resources.

You must prepare a list of keywords and their different variations. You can start your search from any library’s catalog, provided you are an active member of that institution. The exact keywords can be extended to widen your research over other databases and academic search engines like:

• Google Scholar
• Microsoft Academic
• Science.gov

Besides, it is not advisable to go through every resource word by word. Alternatively, what you can do is you can start by reading the abstract and then decide whether that source is relevant to your research or not.

Additionally, you must spend surplus time assessing the quality and relevance of resources. It would help if you tried preparing a list of citations to ensure that there lies no repetition of authors, publications, or articles in the literature review.

3. Examine and assess the sources

It is nearly impossible for you to go through every detail in the research article. So rather than trying to fetch every detail, you have to analyze and decide which research sources resemble closest and appear relevant to your chosen domain.

While analyzing the sources, you should look to find out answers to questions like:

• What question or problem has the author been describing and debating?
• What is the definition of critical aspects?
• How well the theories, approach, and methodology have been explained?
• Whether the research theory used some conventional or new innovative approach?
• How relevant are the key findings of the work?
• In what ways does it relate to other sources on the same topic?
• What challenges does this research paper pose to the existing theory
• What are the possible contributions or benefits it adds to the subject domain?

Be always mindful that you refer only to credible and authentic resources. It would be best if you always take references from different publications to validate your theory.

Always keep track of important information or data you can present in your literature review right from the beginning. It will help steer your path from any threats of plagiarism and also make it easier to curate an annotated bibliography or reference section.

4. Discover connections

At this stage, you must start deciding on the argument and structure of your literature review. To accomplish this, you must discover and identify the relations and connections between various resources while drafting your abstract.

A few aspects that you should be aware of while writing a literature review include:

• Rise to prominence: Theories and methods that have gained reputation and supporters over time.
• Constant scrutiny: Concepts or theories that repeatedly went under examination.
• Contradictions and conflicts: Theories, both the supporting and the contradictory ones, for the research topic.
• Knowledge gaps: What exactly does it fail to address, and how to bridge them with further research?
• Influential resources: Significant research projects available that have been upheld as milestones or perhaps, something that can modify the current trends

Once you join the dots between various past research works, it will be easier for you to draw a conclusion and identify your contribution to the existing knowledge base.

5. Structure planning to write a good literature review

There exist different ways towards planning and executing the structure of a literature review. The format of a literature review varies and depends upon the length of the research.

Like any other research paper, the literature review format must contain three sections: introduction, body, and conclusion. The goals and objectives of the research question determine what goes inside these three sections.

Nevertheless, a good literature review can be structured according to the chronological, thematic, methodological, or theoretical framework approach.

Literature review samples

1. Standalone

2. As a section of a research paper

How SciSpace Discover makes literature review a breeze?

SciSpace Discover is a one-stop solution to do an effective literature search and get barrier-free access to scientific knowledge. It is an excellent repository where you can find millions of only peer-reviewed articles and full-text PDF files. Here’s more on how you can use it:

Find the right information

Find what you want quickly and easily with comprehensive search filters that let you narrow down papers according to PDF availability, year of publishing, document type, and affiliated institution. Moreover, you can sort the results based on the publishing date, citation count, and relevance.

Assess credibility of papers quickly

When doing the literature review, it is critical to establish the quality of your sources. They form the foundation of your research. SciSpace Discover helps you assess the quality of a source by providing an overview of its references, citations, and performance metrics.

Get the complete picture in no time

SciSpace Discover’s personalized suggestion engine helps you stay on course and get the complete picture of the topic from one place. Every time you visit an article page, it provides you links to related papers. Besides that, it helps you understand what’s trending, who are the top authors, and who are the leading publishers on a topic.

Make referring sources super easy

To ensure you don't lose track of your sources, you must start noting down your references when doing the literature review. SciSpace Discover makes this step effortless. Click the 'cite' button on an article page, and you will receive preloaded citation text in multiple styles — all you've to do is copy-paste it into your manuscript.

Final tips on how to write a literature review

A massive chunk of time and effort is required to write a good literature review. But, if you go about it systematically, you'll be able to save a ton of time and build a solid foundation for your research.

We hope this guide has helped you answer several key questions you have about writing literature reviews.

Would you like to explore SciSpace Discover and kick off your literature search right away? You can get started here .

Frequently Asked Questions (FAQs)

1. how to start a literature review.

• What questions do you want to answer?

• What sources do you need to answer these questions?

• What information do these sources contain?

• How can you use this information to answer your questions?

2. What to include in a literature review?

• A brief background of the problem or issue

• What has previously been done to address the problem or issue

• A description of what you will do in your project

• How this study will contribute to research on the subject

3. Why literature review is important?

The literature review is an important part of any research project because it allows the writer to look at previous studies on a topic and determine existing gaps in the literature, as well as what has already been done. It will also help them to choose the most appropriate method for their own study.

4. How to cite a literature review in APA format?

To cite a literature review in APA style, you need to provide the author's name, the title of the article, and the year of publication. For example: Patel, A. B., & Stokes, G. S. (2012). The relationship between personality and intelligence: A meta-analysis of longitudinal research. Personality and Individual Differences, 53(1), 16-21

5. What are the components of a literature review?

• A brief introduction to the topic, including its background and context. The introduction should also include a rationale for why the study is being conducted and what it will accomplish.

• A description of the methodologies used in the study. This can include information about data collection methods, sample size, and statistical analyses.

• A presentation of the findings in an organized format that helps readers follow along with the author's conclusions.

6. What are common errors in writing literature review?

• Not spending enough time to critically evaluate the relevance of resources, observations and conclusions.

• Totally relying on secondary data while ignoring primary data.

• Letting your personal bias seep into your interpretation of existing literature.

• No detailed explanation of the procedure to discover and identify an appropriate literature review.

7. What are the 5 C's of writing literature review?

• Cite - the sources you utilized and referenced in your research.

• Compare - existing arguments, hypotheses, methodologies, and conclusions found in the knowledge base.

• Contrast - the arguments, topics, methodologies, approaches, and disputes that may be found in the literature.

• Critique - the literature and describe the ideas and opinions you find more convincing and why.

• Connect - the various studies you reviewed in your research.

8. How many sources should a literature review have?

When it is just a chapter, sources should equal the total number of pages in your article's body. if it is a self-contained paper in itself, you need at least three times as many sources as there are pages in your work.

9. Can literature review have diagrams?

• To represent an abstract idea or concept

• To explain the steps of a process or procedure

• To help readers understand the relationships between different concepts

10. How old should sources be in a literature review?

Sources for a literature review should be as current as possible or not older than ten years. The only exception to this rule is if you are reviewing a historical topic and need to use older sources.

11. What are the types of literature review?

• Argumentative review

• Integrative review

• Methodological review

• Systematic review

• Meta-analysis review

• Historical review

• Theoretical review

• Scoping review

• State-of-the-Art review

12. Is a literature review mandatory?

Yes. Literature review is a mandatory part of any research project. It is a critical step in the process that allows you to establish the scope of your research, and provide a background for the rest of your work.

But before you go,

• Six Online Tools for Easy Literature Review
• Evaluating literature review: systematic vs. scoping reviews
• Systematic Approaches to a Successful Literature Review
• Writing Integrative Literature Reviews: Guidelines and Examples

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• What is a Literature Review? | Guide, Template, & Examples

What is a Literature Review? | Guide, Template, & Examples

Published on 22 February 2022 by Shona McCombes . Revised on 7 June 2022.

What is a literature review? A literature review is a survey of scholarly sources on a specific topic. It provides an overview of current knowledge, allowing you to identify relevant theories, methods, and gaps in the existing research.

There are five key steps to writing a literature review:

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

A good literature review doesn’t just summarise sources – it analyses, synthesises, and critically evaluates to give a clear picture of the state of knowledge on the subject.

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Table of contents

Why write a literature review, examples of literature reviews, step 1: search for relevant literature, step 2: evaluate and select sources, step 3: identify themes, debates and gaps, step 4: outline your literature review’s structure, step 5: write your literature review, frequently asked questions about literature reviews, introduction.

• Quick Run-through
• Step 1 & 2

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

• Demonstrate your familiarity with the topic and scholarly context
• Develop a theoretical framework and methodology for your research
• Position yourself in relation to other researchers and theorists
• Show how your dissertation addresses a gap or contributes to a debate

You might also have to write a literature review as a stand-alone assignment. In this case, the purpose is to evaluate the current state of research and demonstrate your knowledge of scholarly debates around a topic.

The content will look slightly different in each case, but the process of conducting a literature review follows the same steps. We’ve written a step-by-step guide that you can follow below.

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

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

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

Download Word doc Download Google doc

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

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

If you are writing a literature review as a stand-alone assignment, you will have to choose a focus and develop a central question to direct your search. Unlike a dissertation research question, this question has to be answerable without collecting original data. You should be able to answer it based only on a review of existing publications.

Make a list of keywords

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

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

Search for relevant sources

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

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

You can use boolean operators to help narrow down your search:

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

To identify the most important publications on your topic, take note of recurring citations. If the same authors, books or articles keep appearing in your reading, make sure to seek them out.

You probably won’t be able to read absolutely everything that has been written on the topic – you’ll have to evaluate which sources are most relevant to your questions.

For each publication, ask yourself:

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

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

You can find out how many times an article has been cited on Google Scholar – a high citation count means the article has been influential in the field, and should certainly be included in your literature review.

The scope of your review will depend on your topic and discipline: in the sciences you usually only review recent literature, but in the humanities you might take a long historical perspective (for example, to trace how a concept has changed in meaning over time).

Remember that you can use our template to summarise and evaluate sources you’re thinking about using!

Take notes and cite your sources

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

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

You can use our free APA Reference Generator for quick, correct, consistent citations.

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

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

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

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

There are various approaches to organising the body of a literature review. You should have a rough idea of your strategy before you start writing.

Depending on the length of your literature review, you can combine several of these strategies (for example, your overall structure might be thematic, but each theme is discussed chronologically).

Chronological

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

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

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

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

Methodological

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

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

Theoretical

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

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

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

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

If you are writing the literature review as part of your dissertation or thesis, reiterate your central problem or research question and give a brief summary of the scholarly context. You can emphasise the timeliness of the topic (“many recent studies have focused on the problem of x”) or highlight a gap in the literature (“while there has been much research on x, few researchers have taken y into consideration”).

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

As you write, make sure to follow these tips:

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

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

If the literature review is part of your dissertation or thesis, reiterate how your research addresses gaps and contributes new knowledge, or discuss how you have drawn on existing theories and methods to build a framework for your research. This can lead directly into your methodology section.

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

It is often written as part of a dissertation , thesis, research paper , or proposal .

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

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

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

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

Cite this Scribbr article

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McCombes, S. (2022, June 07). What is a Literature Review? | Guide, Template, & Examples. Scribbr. Retrieved 6 May 2024, from https://www.scribbr.co.uk/thesis-dissertation/literature-review/

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Literature Reviews

• What is a literature review?
• Steps in the Literature Review Process
• Define your research question
• Determine inclusion and exclusion criteria
• Choose databases and search
• Review Results
• Synthesize Results
• Analyze Results
• Librarian Support

What is a Literature Review?

A literature or narrative review is a comprehensive review and analysis of the published literature on a specific topic or research question. The literature that is reviewed contains: books, articles, academic articles, conference proceedings, association papers, and dissertations. It contains the most pertinent studies and points to important past and current research and practices. It provides background and context, and shows how your research will contribute to the field. 

A literature review should: 

• Provide a comprehensive and updated review of the literature;
• Explain why this review has taken place;
• Articulate a position or hypothesis;
• Acknowledge and account for conflicting and corroborating points of view

From  S age Research Methods

Purpose of a Literature Review

A literature review can be written as an introduction to a study to:

• Demonstrate how a study fills a gap in research
• Compare a study with other research that's been done

Or it can be a separate work (a research article on its own) which:

• Organizes or describes a topic
• Describes variables within a particular issue/problem

Limitations of a Literature Review

Some of the limitations of a literature review are:

• It's a snapshot in time. Unlike other reviews, this one has beginning, a middle and an end. There may be future developments that could make your work less relevant.
• It may be too focused. Some niche studies may miss the bigger picture.
• It can be difficult to be comprehensive. There is no way to make sure all the literature on a topic was considered.
• It is easy to be biased if you stick to top tier journals. There may be other places where people are publishing exemplary research. Look to open access publications and conferences to reflect a more inclusive collection. Also, make sure to include opposing views (and not just supporting evidence).

Source: Grant, Maria J., and Andrew Booth. “A Typology of Reviews: An Analysis of 14 Review Types and Associated Methodologies.” Health Information & Libraries Journal, vol. 26, no. 2, June 2009, pp. 91–108. Wiley Online Library, doi:10.1111/j.1471-1842.2009.00848.x.

Meryl Brodsky : Communication and Information Studies

Hannah Chapman Tripp : Biology, Neuroscience

Carolyn Cunningham : Human Development & Family Sciences, Psychology, Sociology

Larayne Dallas : Engineering

Janelle Hedstrom : Special Education, Curriculum & Instruction, Ed Leadership & Policy ​

Susan Macicak : Linguistics

Imelda Vetter : Dell Medical School

For help in other subject areas, please see the guide to library specialists by subject .

Periodically, UT Libraries runs a workshop covering the basics and library support for literature reviews. While we try to offer these once per academic year, we find providing the recording to be helpful to community members who have missed the session. Following is the most recent recording of the workshop, Conducting a Literature Review. To view the recording, a UT login is required.

• October 26, 2022 recording
• Last Updated: Oct 26, 2022 2:49 PM
• URL: https://guides.lib.utexas.edu/literaturereviews

• 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
• << Previous: Getting Started
• Next: How to Pick a Topic >>
• Last Updated: Sep 21, 2022 2:16 PM
• URL: https://guides.lib.uconn.edu/literaturereview

Literature Reviews

What this handout is about.

This handout will explain what literature reviews are and offer insights into the form and construction of literature reviews in the humanities, social sciences, and sciences.

Introduction

OK. You’ve got to write a literature review. You dust off a novel and a book of poetry, settle down in your chair, and get ready to issue a “thumbs up” or “thumbs down” as you leaf through the pages. “Literature review” done. Right?

Wrong! The “literature” of a literature review refers to any collection of materials on a topic, not necessarily the great literary texts of the world. “Literature” could be anything from a set of government pamphlets on British colonial methods in Africa to scholarly articles on the treatment of a torn ACL. And a review does not necessarily mean that your reader wants you to give your personal opinion on whether or not you liked these sources.

What is a literature review, then?

A literature review discusses published information in a particular subject area, and sometimes information in a particular subject area within a certain time period.

A literature review can be just a simple summary of the sources, but it usually has an organizational pattern and combines both summary and synthesis. 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. It might give a new interpretation of old material or combine new with old interpretations. Or it might trace the intellectual progression of the field, including major debates. And depending on the situation, the literature review may evaluate the sources and advise the reader on the most pertinent or relevant.

But how is a literature review different from an academic research paper?

The main focus of an academic research paper is to develop a new argument, and a research paper is likely to contain a literature review as one of its parts. In a research paper, you use the literature as a foundation and as support for a new insight that you contribute. The focus of a literature review, however, is to summarize and synthesize the arguments and ideas of others without adding new contributions.

Why do we write literature reviews?

Literature reviews provide you with a handy guide to a particular topic. If you have limited time to conduct research, literature reviews can give you an overview or act as a stepping stone. For professionals, they are useful reports that keep them up to date with what is current in the field. For scholars, the depth and breadth of the literature review emphasizes the credibility of the writer in his or her field. Literature reviews also provide a solid background for a research paper’s investigation. Comprehensive knowledge of the literature of the field is essential to most research papers.

Who writes these things, anyway?

Literature reviews are written occasionally in the humanities, but mostly in the sciences and social sciences; in experiment and lab reports, they constitute a section of the paper. Sometimes a literature review is written as a paper in itself.

Let’s get to it! What should I do before writing the literature review?

If your assignment is not very specific, seek clarification from your instructor:

• Roughly how many sources should you include?
• What types of sources (books, journal articles, websites)?
• Should you summarize, synthesize, or critique your sources by discussing a common theme or issue?
• Should you evaluate your sources?
• Should you provide subheadings and other background information, such as definitions and/or a history?

Find models

Look for other literature reviews in your area of interest or in the discipline and read them to get a sense of the types of themes you might want to look for in your own research or ways to organize your final review. You can simply put the word “review” in your search engine along with your other topic terms to find articles of this type on the Internet or in an electronic database. The bibliography or reference section of sources you’ve already read are also excellent entry points into your own research.

Narrow your topic

There are hundreds or even thousands of articles and books on most areas of study. The narrower your topic, the easier it will be to limit the number of sources you need to read in order to get a good survey of the material. Your instructor will probably not expect you to read everything that’s out there on the topic, but you’ll make your job easier if you first limit your scope.

Keep in mind that UNC Libraries have research guides and to databases relevant to many fields of study. You can reach out to the subject librarian for a consultation: https://library.unc.edu/support/consultations/ .

And don’t forget to tap into your professor’s (or other professors’) knowledge in the field. Ask your professor questions such as: “If you had to read only one book from the 90’s on topic X, what would it be?” Questions such as this help you to find and determine quickly the most seminal pieces in the field.

Consider whether your sources are current

Some disciplines require that you use information that is as current as possible. In the sciences, for instance, treatments for medical problems are constantly changing according to the latest studies. Information even two years old could be obsolete. However, if you are writing a review in the humanities, history, or social sciences, a survey of the history of the literature may be what is needed, because what is important is how perspectives have changed through the years or within a certain time period. Try sorting through some 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 consider what is currently of interest to scholars in this field and what is not.

Strategies for writing the literature review

Find a focus.

A literature review, like a term paper, is usually organized around ideas, not the sources themselves as an annotated bibliography would be organized. This means that you will not just simply list your sources and go into detail about each one of them, one at a time. No. As you read widely but selectively in your topic area, consider instead what themes or issues connect your sources together. Do they present one or different solutions? Is there an aspect of the field that is missing? How well do they present the material and do they portray it according to an appropriate theory? Do they reveal a trend in the field? A raging debate? Pick one of these themes to focus the organization of your review.

Convey it to your reader

A literature review may not have a traditional thesis statement (one that makes an argument), but you do need to tell readers what to expect. Try writing a simple statement that lets the reader know what is your main organizing principle. Here are a couple of examples:

The current trend in treatment for congestive heart failure combines surgery and medicine. More and more cultural studies scholars are accepting popular media as a subject worthy of academic consideration.

Consider organization

You’ve got a focus, and you’ve stated it clearly and directly. Now what is the most effective way of presenting the information? What are the most important topics, subtopics, etc., that your review needs to include? And in what order should you present them? Develop an organization for your review at both a global and local level:

First, cover the basic categories

Just like most academic papers, literature reviews also must contain at least three basic elements: an introduction or background information section; the body of the review containing the discussion of sources; and, finally, a conclusion and/or recommendations section to end the paper. The following provides a brief description of the content of each:

• Introduction: Gives a quick idea of the topic of the literature review, such as the central theme or organizational pattern.
• Body: Contains your discussion of sources and is organized either chronologically, thematically, or methodologically (see below for more information on each).
• Conclusions/Recommendations: Discuss what you have drawn from reviewing literature so far. Where might the discussion proceed?

Organizing the body

Once you have the basic categories in place, then you must consider how you will present the sources themselves within the body of your paper. Create an organizational method to focus this section even further.

To help you come up with an overall organizational framework for your review, consider the following scenario:

You’ve decided to focus your literature review on materials dealing with sperm whales. This is because you’ve just finished reading Moby Dick, and you wonder if that whale’s portrayal is really real. You start with some articles about the physiology of sperm whales in biology journals written in the 1980’s. But these articles refer to some British biological studies performed on whales in the early 18th century. So you check those out. Then you look up a book written in 1968 with information on how sperm whales have been portrayed in other forms of art, such as in Alaskan poetry, in French painting, or on whale bone, as the whale hunters in the late 19th century used to do. This makes you wonder about American whaling methods during the time portrayed in Moby Dick, so you find some academic articles published in the last five years on how accurately Herman Melville portrayed the whaling scene in his novel.

Now consider some typical ways of organizing the sources into a review:

• Chronological: If your review follows the chronological method, you could write about the materials above according to when they were published. For instance, first you would talk about the British biological studies of the 18th century, then about Moby Dick, published in 1851, then the book on sperm whales in other art (1968), and finally the biology articles (1980s) and the recent articles on American whaling of the 19th century. But there is relatively no continuity among subjects here. And notice that even though the sources on sperm whales in other art and on American whaling are written recently, they are about other subjects/objects that were created much earlier. Thus, the review loses its chronological focus.
• 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 biological studies of sperm whales if the progression revealed a change in dissection practices of the researchers who wrote and/or conducted the studies.
• By trend: A better way to organize the above sources chronologically is to examine the sources under another trend, such as the history of whaling. Then your review would have subsections according to eras within this period. For instance, the review might examine whaling from pre-1600-1699, 1700-1799, and 1800-1899. Under this method, you would combine the recent studies on American whaling in the 19th century with Moby Dick itself in the 1800-1899 category, even though the authors wrote a century apart.
• Thematic: Thematic reviews of literature are organized around a topic or issue, rather than the progression of time. However, progression of time may still be an important factor in a thematic review. For instance, the sperm whale review could focus on the development of the harpoon for whale hunting. While the study focuses on one topic, harpoon technology, it will still be organized chronologically. The only difference here between a “chronological” and a “thematic” approach is what is emphasized the most: the development of the harpoon or the harpoon technology.But more authentic thematic reviews tend to break away from chronological order. For instance, a thematic review of material on sperm whales might examine how they are portrayed as “evil” in cultural documents. The subsections might include how they are personified, how their proportions are exaggerated, and their behaviors misunderstood. A review organized in this manner would shift between time periods within each section according to the point made.
• Methodological: A methodological approach differs from the two above in that the focusing factor usually does not have to do with the content of the material. Instead, it focuses on the “methods” of the researcher or writer. For the sperm whale project, one methodological approach would be to look at cultural differences between the portrayal of whales in American, British, and French art work. Or the review might focus on the economic impact of whaling on a community. A methodological scope will influence either the types of documents in the review or the way in which these documents are discussed. Once you’ve decided on the organizational method for the body of the review, the sections you need to include in the paper should be easy to figure out. They should arise out of 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.

Sometimes, though, you might 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. Put in only what is necessary. Here are a few other sections you might want to consider:

• Current Situation: Information necessary to understand the topic or focus of the literature review.
• History: The chronological progression of the field, the literature, or an idea that is necessary to understand the literature review, if the body of the literature review is not already a chronology.
• Methods and/or Standards: The criteria you used to select the sources in your literature review or the way in which you present your information. For instance, you might explain that your review includes only peer-reviewed articles and journals.

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?

Begin composing

Once you’ve settled on a general pattern of organization, you’re ready to write each section. There are a few guidelines you should follow during the writing stage as well. Here is a sample paragraph from a literature review about sexism and language to illuminate the following discussion:

However, other studies have shown that even gender-neutral antecedents are more likely to produce masculine images than feminine ones (Gastil, 1990). Hamilton (1988) asked students to complete sentences that required them to fill in pronouns that agreed with gender-neutral antecedents such as “writer,” “pedestrian,” and “persons.” The students were asked to describe any image they had when writing the sentence. Hamilton found that people imagined 3.3 men to each woman in the masculine “generic” condition and 1.5 men per woman in the unbiased condition. Thus, while ambient sexism accounted for some of the masculine bias, sexist language amplified the effect. (Source: Erika Falk and Jordan Mills, “Why Sexist Language Affects Persuasion: The Role of Homophily, Intended Audience, and Offense,” Women and Language19:2).

Use evidence

In the example above, the writers refer to several other sources when making their point. A literature review in this sense is just like any other academic research paper. Your interpretation of the available sources must be backed up with evidence to show 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 review’s focus, whether it is thematic, methodological, or chronological.

Use quotes sparingly

Falk and Mills do not use any direct quotes. That is because the survey nature of the literature review does not allow for in-depth discussion or detailed quotes from the text. Some short quotes here and there are okay, though, if you want to emphasize a point, or if what the author said just cannot be rewritten in your own words. Notice that Falk and Mills do quote certain terms that were coined by the author, not common knowledge, or taken directly from the study. But if you find yourself wanting to put in more quotes, check with your instructor.

Summarize and synthesize

Remember to summarize and synthesize your sources within each paragraph as well as throughout the review. The authors here recapitulate important features of Hamilton’s study, but then synthesize it by rephrasing the study’s significance and relating it to their own work.

Keep your own voice

While the literature review presents others’ ideas, your voice (the writer’s) should remain front and center. Notice that Falk and Mills weave references to other sources into their own text, but they still maintain their own voice by starting and ending the paragraph with their own ideas and their own words. The sources support what Falk and Mills are saying.

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. In the preceding example, Falk and Mills either directly refer in the text to the author of their source, such as Hamilton, or they provide ample notation in the text when the ideas they are mentioning are not their own, for example, Gastil’s. For more information, please see our handout on plagiarism .

Revise, revise, revise

Draft in hand? Now you’re ready to revise. Spending a lot of time revising is a wise idea, because your main objective is to present the material, not the argument. So check over your review again to make sure it follows the assignment and/or your outline. Then, just as you would for most other academic forms of writing, rewrite or rework the language of your review so that you’ve presented your information in the most concise manner possible. Be sure to use terminology familiar to your audience; get rid of unnecessary jargon or slang. Finally, double check that you’ve documented your sources and formatted the review appropriately for your discipline. For tips on the revising and editing process, see our handout on revising drafts .

Works consulted

We consulted these works while writing this handout. This is not a comprehensive list of resources on the handout’s topic, and we encourage you to do your own research to find additional publications. Please do not use this list as a model for the format of your own reference list, as it may not match the citation style you are using. For guidance on formatting citations, please see the UNC Libraries citation tutorial . We revise these tips periodically and welcome feedback.

Anson, Chris M., and Robert A. Schwegler. 2010. The Longman Handbook for Writers and Readers , 6th ed. New York: Longman.

Jones, Robert, Patrick Bizzaro, and Cynthia Selfe. 1997. The Harcourt Brace Guide to Writing in the Disciplines . New York: Harcourt Brace.

Lamb, Sandra E. 1998. How to Write It: A Complete Guide to Everything You’ll Ever Write . Berkeley: Ten Speed Press.

Rosen, Leonard J., and Laurence Behrens. 2003. The Allyn & Bacon Handbook , 5th ed. New York: Longman.

Troyka, Lynn Quittman, and Doug Hesse. 2016. Simon and Schuster Handbook for Writers , 11th ed. London: Pearson.

You may reproduce it for non-commercial use if you use the entire handout and attribute the source: The Writing Center, University of North Carolina at Chapel Hill

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Literature reviews, what is a literature review, learning more about how to do a literature review.

• Planning the Review
• The Research Question
• Choosing Where to Search
• Organizing the Review
• Writing the Review

A literature review is a review and synthesis of existing research on a topic or research question. A literature review is meant to analyze the scholarly literature, make connections across writings and identify strengths, weaknesses, trends, and missing conversations. A literature review should address different aspects of a topic as it relates to your research question. A literature review goes beyond a description or summary of the literature you have read. 

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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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How to Write a Literature Review

What is a literature review.

• What Is the Literature
• Writing the Review

A literature review is much more than an annotated bibliography or a list of separate reviews of articles and books. It is a critical, analytical summary and synthesis of the current knowledge of a topic. Thus it should compare and relate different theories, findings, etc, rather than just summarize them individually. In addition, it should have a particular focus or theme to organize the review. It does not have to be an exhaustive account of everything published on the topic, but it should discuss all the significant academic literature and other relevant sources important for that focus.

This is meant to be a general guide to writing a literature review: ways to structure one, what to include, how it supplements other research. For more specific help on writing a review, and especially for help on finding the literature to review, sign up for a Personal Research Session .

The specific organization of a literature review depends on the type and purpose of the review, as well as on the specific field or topic being reviewed. But in general, it is a relatively brief but thorough exploration of past and current work on a topic. Rather than a chronological listing of previous work, though, literature reviews are usually organized thematically, such as different theoretical approaches, methodologies, or specific issues or concepts involved in the topic. A thematic organization makes it much easier to examine contrasting perspectives, theoretical approaches, methodologies, findings, etc, and to analyze the strengths and weaknesses of, and point out any gaps in, previous research. And this is the heart of what a literature review is about. A literature review may offer new interpretations, theoretical approaches, or other ideas; if it is part of a research proposal or report it should demonstrate the relationship of the proposed or reported research to others' work; but whatever else it does, it must provide a critical overview of the current state of research efforts. 

Literature reviews are common and very important in the sciences and social sciences. They are less common and have a less important role in the humanities, but they do have a place, especially stand-alone reviews.

Types of Literature Reviews

There are different types of literature reviews, and different purposes for writing a review, but the most common are:

• Stand-alone literature review articles . These provide an overview and analysis of the current state of research on a topic or question. The goal is to evaluate and compare previous research on a topic to provide an analysis of what is currently known, and also to reveal controversies, weaknesses, and gaps in current work, thus pointing to directions for future research. You can find examples published in any number of academic journals, but there is a series of Annual Reviews of *Subject* which are specifically devoted to literature review articles. Writing a stand-alone review is often an effective way to get a good handle on a topic and to develop ideas for your own research program. For example, contrasting theoretical approaches or conflicting interpretations of findings can be the basis of your research project: can you find evidence supporting one interpretation against another, or can you propose an alternative interpretation that overcomes their limitations?
• Part of a research proposal . This could be a proposal for a PhD dissertation, a senior thesis, or a class project. It could also be a submission for a grant. The literature review, by pointing out the current issues and questions concerning a topic, is a crucial part of demonstrating how your proposed research will contribute to the field, and thus of convincing your thesis committee to allow you to pursue the topic of your interest or a funding agency to pay for your research efforts.
• Part of a research report . When you finish your research and write your thesis or paper to present your findings, it should include a literature review to provide the context to which your work is a contribution. Your report, in addition to detailing the methods, results, etc. of your research, should show how your work relates to others' work.

A literature review for a research report is often a revision of the review for a research proposal, which can be a revision of a stand-alone review. Each revision should be a fairly extensive revision. With the increased knowledge of and experience in the topic as you proceed, your understanding of the topic will increase. Thus, you will be in a better position to analyze and critique the literature. In addition, your focus will change as you proceed in your research. Some areas of the literature you initially reviewed will be marginal or irrelevant for your eventual research, and you will need to explore other areas more thoroughly. 

Examples of Literature Reviews

See the series of Annual Reviews of *Subject* which are specifically devoted to literature review articles to find many examples of stand-alone literature reviews in the biomedical, physical, and social sciences. 

Research report articles vary in how they are organized, but a common general structure is to have sections such as:

• Abstract - Brief summary of the contents of the article
• Introduction - A explanation of the purpose of the study, a statement of the research question(s) the study intends to address
• Literature review - A critical assessment of the work done so far on this topic, to show how the current study relates to what has already been done
• Methods - How the study was carried out (e.g. instruments or equipment, procedures, methods to gather and analyze data)
• Results - What was found in the course of the study
• Discussion - What do the results mean
• Conclusion - State the conclusions and implications of the results, and discuss how it relates to the work reviewed in the literature review; also, point to directions for further work in the area

Here are some articles that illustrate variations on this theme. There is no need to read the entire articles (unless the contents interest you); just quickly browse through to see the sections, and see how each section is introduced and what is contained in them.

The Determinants of Undergraduate Grade Point Average: The Relative Importance of Family Background, High School Resources, and Peer Group Effects , in The Journal of Human Resources , v. 34 no. 2 (Spring 1999), p. 268-293.

This article has a standard breakdown of sections:

• Introduction
• Literature Review
• Some discussion sections

First Encounters of the Bureaucratic Kind: Early Freshman Experiences with a Campus Bureaucracy , in The Journal of Higher Education , v. 67 no. 6 (Nov-Dec 1996), p. 660-691.

This one does not have a section specifically labeled as a "literature review" or "review of the literature," but the first few sections cite a long list of other sources discussing previous research in the area before the authors present their own study they are reporting.

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How To Structure Your Literature Review

3 options to help structure your chapter.

By: Amy Rommelspacher (PhD) | Reviewer: Dr Eunice Rautenbach | November 2020 (Updated May 2023)

Writing the literature review chapter can seem pretty daunting when you’re piecing together your dissertation or thesis. As  we’ve discussed before , a good literature review needs to achieve a few very important objectives – it should:

• Demonstrate your knowledge of the research topic
• Identify the gaps in the literature and show how your research links to these
• Provide the foundation for your conceptual framework (if you have one)
• Inform your own  methodology and research design

To achieve this, your literature review needs a well-thought-out structure . Get the structure of your literature review chapter wrong and you’ll struggle to achieve these objectives. Don’t worry though – in this post, we’ll look at how to structure your literature review for maximum impact (and marks!).

But wait – is this the right time?

Deciding on the structure of your literature review should come towards the end of the literature review process – after you have collected and digested the literature, but before you start writing the chapter. 

In other words, you need to first develop a rich understanding of the literature before you even attempt to map out a structure. There’s no use trying to develop a structure before you’ve fully wrapped your head around the existing research.

Equally importantly, you need to have a structure in place before you start writing , or your literature review will most likely end up a rambling, disjointed mess. 

Importantly, don’t feel that once you’ve defined a structure you can’t iterate on it. It’s perfectly natural to adjust as you engage in the writing process. As we’ve discussed before , writing is a way of developing your thinking, so it’s quite common for your thinking to change – and therefore, for your chapter structure to change – as you write. 

Need a helping hand?

Like any other chapter in your thesis or dissertation, your literature review needs to have a clear, logical structure. At a minimum, it should have three essential components – an  introduction , a  body   and a  conclusion . 

Let’s take a closer look at each of these.

1: The Introduction Section

Just like any good introduction, the introduction section of your literature review should introduce the purpose and layout (organisation) of the chapter. In other words, your introduction needs to give the reader a taste of what’s to come, and how you’re going to lay that out. Essentially, you should provide the reader with a high-level roadmap of your chapter to give them a taste of the journey that lies ahead.

Here’s an example of the layout visualised in a literature review introduction:

Your introduction should also outline your topic (including any tricky terminology or jargon) and provide an explanation of the scope of your literature review – in other words, what you  will   and  won’t   be covering (the delimitations ). This helps ringfence your review and achieve a clear focus . The clearer and narrower your focus, the deeper you can dive into the topic (which is typically where the magic lies). 

Depending on the nature of your project, you could also present your stance or point of view at this stage. In other words, after grappling with the literature you’ll have an opinion about what the trends and concerns are in the field as well as what’s lacking. The introduction section can then present these ideas so that it is clear to examiners that you’re aware of how your research connects with existing knowledge .

2: The Body Section

The body of your literature review is the centre of your work. This is where you’ll present, analyse, evaluate and synthesise the existing research. In other words, this is where you’re going to earn (or lose) the most marks. Therefore, it’s important to carefully think about how you will organise your discussion to present it in a clear way. 

The body of your literature review should do just as the description of this chapter suggests. It should “review” the literature – in other words, identify, analyse, and synthesise it. So, when thinking about structuring your literature review, you need to think about which structural approach will provide the best “review” for your specific type of research and objectives (we’ll get to this shortly).

There are (broadly speaking)  three options  for organising your literature review.

Option 1: Chronological (according to date)

Organising the literature chronologically is one of the simplest ways to structure your literature review. You start with what was published first and work your way through the literature until you reach the work published most recently. Pretty straightforward.

The benefit of this option is that it makes it easy to discuss the developments and debates in the field as they emerged over time. Organising your literature chronologically also allows you to highlight how specific articles or pieces of work might have changed the course of the field – in other words, which research has had the most impact . Therefore, this approach is very useful when your research is aimed at understanding how the topic has unfolded over time and is often used by scholars in the field of history. That said, this approach can be utilised by anyone that wants to explore change over time .

For example , if a student of politics is investigating how the understanding of democracy has evolved over time, they could use the chronological approach to provide a narrative that demonstrates how this understanding has changed through the ages.

Here are some questions you can ask yourself to help you structure your literature review chronologically.

• What is the earliest literature published relating to this topic?
• How has the field changed over time? Why?
• What are the most recent discoveries/theories?

In some ways, chronology plays a part whichever way you decide to structure your literature review, because you will always, to a certain extent, be analysing how the literature has developed. However, with the chronological approach, the emphasis is very firmly on how the discussion has evolved over time , as opposed to how all the literature links together (which we’ll discuss next ).

Option 2: Thematic (grouped by theme)

The thematic approach to structuring a literature review means organising your literature by theme or category – for example, by independent variables (i.e. factors that have an impact on a specific outcome).

As you’ve been collecting and synthesising literature , you’ll likely have started seeing some themes or patterns emerging. You can then use these themes or patterns as a structure for your body discussion. The thematic approach is the most common approach and is useful for structuring literature reviews in most fields.

For example, if you were researching which factors contributed towards people trusting an organisation, you might find themes such as consumers’ perceptions of an organisation’s competence, benevolence and integrity. Structuring your literature review thematically would mean structuring your literature review’s body section to discuss each of these themes, one section at a time.

Here are some questions to ask yourself when structuring your literature review by themes:

• Are there any patterns that have come to light in the literature?
• What are the central themes and categories used by the researchers?
• Do I have enough evidence of these themes?

PS – you can see an example of a thematically structured literature review in our literature review sample walkthrough video here.

Option 3: Methodological

The methodological option is a way of structuring your literature review by the research methodologies used . In other words, organising your discussion based on the angle from which each piece of research was approached – for example, qualitative , quantitative or mixed  methodologies.

Structuring your literature review by methodology can be useful if you are drawing research from a variety of disciplines and are critiquing different methodologies. The point of this approach is to question  how  existing research has been conducted, as opposed to  what  the conclusions and/or findings the research were.

For example, a sociologist might centre their research around critiquing specific fieldwork practices. Their literature review will then be a summary of the fieldwork methodologies used by different studies.

Here are some questions you can ask yourself when structuring your literature review according to methodology:

• Which methodologies have been utilised in this field?
• Which methodology is the most popular (and why)?
• What are the strengths and weaknesses of the various methodologies?
• How can the existing methodologies inform my own methodology?

3: The Conclusion Section

Once you’ve completed the body section of your literature review using one of the structural approaches we discussed above, you’ll need to “wrap up” your literature review and pull all the pieces together to set the direction for the rest of your dissertation or thesis.

The conclusion is where you’ll present the key findings of your literature review. In this section, you should emphasise the research that is especially important to your research questions and highlight the gaps that exist in the literature. Based on this, you need to make it clear what you will add to the literature – in other words, justify your own research by showing how it will help fill one or more of the gaps you just identified.

Last but not least, if it’s your intention to develop a conceptual framework for your dissertation or thesis, the conclusion section is a good place to present this.

Example: Thematically Structured Review

In the video below, we unpack a literature review chapter so that you can see an example of a thematically structure review in practice.

Let’s Recap

In this article, we’ve  discussed how to structure your literature review for maximum impact. Here’s a quick recap of what  you need to keep in mind when deciding on your literature review structure:

• Just like other chapters, your literature review needs a clear introduction , body and conclusion .
• The introduction section should provide an overview of what you will discuss in your literature review.
• The body section of your literature review can be organised by chronology , theme or methodology . The right structural approach depends on what you’re trying to achieve with your research.
• The conclusion section should draw together the key findings of your literature review and link them to your research questions.

If you’re ready to get started, be sure to download our free literature review template to fast-track your chapter outline.

Psst… there’s more!

This post is an extract from our bestselling short course, Literature Review Bootcamp . If you want to work smart, you don't want to miss this .

You Might Also Like:

27 Comments

Great work. This is exactly what I was looking for and helps a lot together with your previous post on literature review. One last thing is missing: a link to a great literature chapter of an journal article (maybe with comments of the different sections in this review chapter). Do you know any great literature review chapters?

I agree with you Marin… A great piece

I agree with Marin. This would be quite helpful if you annotate a nicely structured literature from previously published research articles.

Awesome article for my research.

I thank you immensely for this wonderful guide

It is indeed thought and supportive work for the futurist researcher and students

Very educative and good time to get guide. Thank you

Great work, very insightful. Thank you.

Thanks for this wonderful presentation. My question is that do I put all the variables into a single conceptual framework or each hypothesis will have it own conceptual framework?

Thank you very much, very helpful

This is very educative and precise . Thank you very much for dropping this kind of write up .

Pheeww, so damn helpful, thank you for this informative piece.

I’m doing a research project topic ; stool analysis for parasitic worm (enteric) worm, how do I structure it, thanks.

comprehensive explanation. Help us by pasting the URL of some good “literature review” for better understanding.

great piece. thanks for the awesome explanation. it is really worth sharing. I have a little question, if anyone can help me out, which of the options in the body of literature can be best fit if you are writing an architectural thesis that deals with design?

I am doing a research on nanofluids how can l structure it?

Beautifully clear.nThank you!

Lucid! Thankyou!

Brilliant work, well understood, many thanks

I like how this was so clear with simple language 😊😊 thank you so much 😊 for these information 😊

Insightful. I was struggling to come up with a sensible literature review but this has been really helpful. Thank you!

You have given thought-provoking information about the review of the literature.

Thank you. It has made my own research better and to impart your work to students I teach

I learnt a lot from this teaching. It’s a great piece.

I am doing research on EFL teacher motivation for his/her job. How Can I structure it? Is there any detailed template, additional to this?

You are so cool! I do not think I’ve read through something like this before. So nice to find somebody with some genuine thoughts on this issue. Seriously.. thank you for starting this up. This site is one thing that is required on the internet, someone with a little originality!

I’m asked to do conceptual, theoretical and empirical literature, and i just don’t know how to structure it

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What is a literature review?

A literature review is an integrated analysis -- not just a summary-- of scholarly writings and other relevant evidence related directly to your research question.  That is, it represents a synthesis of the evidence that provides background information on your topic and shows a association between the evidence and your research question.

A literature review may be a stand alone work or the introduction to a larger research paper, depending on the assignment.  Rely heavily on the guidelines your instructor has given you.

Why is it important?

A literature review is important because it:

• Explains the background of research on a topic.
• Demonstrates why a topic is significant to a subject area.
• Discovers relationships between research studies/ideas.
• Identifies major themes, concepts, and researchers on a topic.
• Identifies critical gaps and points of disagreement.
• Discusses further research questions that logically come out of the previous studies.

APA7 Style resources

APA Style Blog - for those harder to find answers

1. Choose a topic. Define your research question.

Your literature review should be guided by your central research question.  The literature represents background and research developments related to a specific research question, interpreted and analyzed by you in a synthesized way.

• Make sure your research question is not too broad or too narrow.  Is it manageable?
• Begin writing down terms that are related to your question. These will be useful for searches later.
• If you have the opportunity, discuss your topic with your professor and your class mates.

2. Decide on the scope of your review

How many studies do you need to look at? How comprehensive should it be? How many years should it cover? 

• This may depend on your assignment.  How many sources does the assignment require?

3. Select the databases you will use to conduct your searches.

Make a list of the databases you will search. 

Where to find databases:

• use the tabs on this guide
• Find other databases in the Nursing Information Resources web page
• More on the Medical Library web page
• ... and more on the Yale University Library web page

4. Conduct your searches to find the evidence. Keep track of your searches.

• Use the key words in your question, as well as synonyms for those words, as terms in your search. Use the database tutorials for help.
• Save the searches in the databases. This saves time when you want to redo, or modify, the searches. It is also helpful to use as a guide is the searches are not finding any useful results.
• Review the abstracts of research studies carefully. This will save you time.
• Use the bibliographies and references of research studies you find to locate others.
• Check with your professor, or a subject expert in the field, if you are missing any key works in the field.
• Ask your librarian for help at any time.
• Use a citation manager, such as EndNote as the repository for your citations. See the EndNote tutorials for help.

Review the literature

Some questions to help you analyze the research:

• What was the research question of the study you are reviewing? What were the authors trying to discover?
• Was the research funded by a source that could influence the findings?
• What were the research methodologies? Analyze its literature review, the samples and variables used, the results, and the conclusions.
• Does the research seem to be complete? Could it have been conducted more soundly? What further questions does it raise?
• If there are conflicting studies, why do you think that is?
• How are the authors viewed in the field? Has this study been cited? If so, how has it been analyzed?

Tips: 

• Review the abstracts carefully.  
• Keep careful notes so that you may track your thought processes during the research process.
• Create a matrix of the studies for easy analysis, and synthesis, across all of the studies.
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How to write a literature review

What is a literature review.

The literature review is a written overview of major writings and other sources on a selected topic. Sources covered in the review may include scholarly journal articles, books, government reports, Web sites, etc. The literature review provides a description, summary and evaluation of each source. It is usually presented as a distinct section of a graduate thesis or dissertation.

Purpose of the literature review

The purpose of the literature review is to provide a critical written account of the current state of research on a selected topic:

• Identifies areas of prior scholarship
• Places each source in the context of its contribution to the understanding of the specific issue, area of research, or theory under review.
• Describes the relationship of each source to the others that you have selected
• Identifies new ways to interpret, and shed light on any gaps in, previous research
• Points the way forward for further research.

Components of the literature review

The literature review should include the following:

• Objective of the literature review
• Overview of the subject under consideration.
• particular position, those opposed, and those offering completely different arguments.
• Discussion of both the distinctiveness of each source and its similarities with the others.

Steps in the literature review process

Preparation of a literature review may be divided into four steps:

• Define your subject and the scope of the review.
• Search the library catalogue, subject specific databases and other search tools to find sources that are relevant to your topic.
• Read and evaluate the sources and to determine their suitability to the understanding of topic at hand (see the Evaluating sources section).
• Analyse, interpret and discuss the findings and conclusions of the sources you selected.

Evaluating sources

In assessing each source, consideration should be given to:

• What is the author's expertise in this particular field of study (credentials)?
• Are the author's arguments supported by empirical evidence (e.g. quantitative/qualitative studies)?
• Is the author's perspective too biased in one direction or are opposing studies and viewpoints also considered?
• Does the selected source contribute to a more profound understanding of the subject?

Examples of a published literature review

Literature reviews are often published as scholarly articles, books, and reports. Here is an example of a recent literature review published as a scholarly journal article:

Ledesma, M. C., & Calderón, D. (2015). Critical race theory in education: A review of past literature and a look to the future. Qualitative Inquiry, 21(3), 206-222. Link to the article

Additional sources on writing literature reviews

Further information on the literature review process may be found below:

• Booth, A., Papaioannou, D., & Sutton, A. (2012). Systematic approaches to a successful literature review
• Fink, A. (2010). Conducting research literature reviews: From the Internet to paper
• Galvin, J. (2006). Writing literature reviews: A guide for students of the social and behavioral sciences
• Machi, L. A., & McEvoy, B. T. (2012). The literature review: Six steps to success

Adapted with permission and thanks from How to Write a Literature Review originally created by Kenneth Lyons, McHenry Library, University of California, Santa Cruz.

Want to create or adapt books like this? Learn more about how Pressbooks supports open publishing practices.

The Research Proposal

83 Components of the Literature Review

Krathwohl (2005) suggests and describes a variety of components to include in a research proposal.  The following sections present these components in a suggested template for you to follow in the preparation of your research proposal.

Introduction

The introduction sets the tone for what follows in your research proposal – treat it as the initial pitch of your idea.  After reading the introduction your reader should:

• Understand what it is you want to do;
• Have a sense of your passion for the topic;
• Be excited about the study´s possible outcomes.

As you begin writing your research proposal it is helpful to think of the introduction as a narrative of what it is you want to do, written in one to three paragraphs.  Within those one to three paragraphs, it is important to briefly answer the following questions:

• What is the central research problem?
• How is the topic of your research proposal related to the problem?
• What methods will you utilize to analyze the research problem?
• Why is it important to undertake this research? What is the significance of your proposed research?  Why are the outcomes of your proposed research important, and to whom or to what are they important?

Note : You may be asked by your instructor to include an abstract with your research proposal.  In such cases, an abstract should provide an overview of what it is you plan to study, your main research question, a brief explanation of your methods to answer the research question, and your expected findings. All of this information must be carefully crafted in 150 to 250 words.  A word of advice is to save the writing of your abstract until the very end of your research proposal preparation.  If you are asked to provide an abstract, you should include 5-7 key words that are of most relevance to your study. List these in order of relevance.

Background and significance

The purpose of this section is to explain the context of your proposal and to describe, in detail, why it is important to undertake this research. Assume that the person or people who will read your research proposal know nothing or very little about the research problem.  While you do not need to include all knowledge you have learned about your topic in this section, it is important to ensure that you include the most relevant material that will help to explain the goals of your research.

While there are no hard and fast rules, you should attempt to address some or all of the following key points:

• State the research problem and provide a more thorough explanation about the purpose of the study than what you stated in the introduction.
• Present the rationale for the proposed research study. Clearly indicate why this research is worth doing.  Answer the “so what?” question.
• Describe the major issues or problems to be addressed by your research. Do not forget to explain how and in what ways your proposed research builds upon previous related research.
• Explain how you plan to go about conducting your research.
• Clearly identify the key or most relevant sources of research you intend to use and explain how they will contribute to your analysis of the topic.
• Set the boundaries of your proposed research, in order to provide a clear focus. Where appropriate, state not only what you will study, but what will be excluded from your study.
• Provide clear definitions of key concepts and terms. As key concepts and terms often have numerous definitions, make sure you state which definition you will be utilizing in your research.

Literature Review

This is the most time-consuming aspect in the preparation of your research proposal and it is a key component of the research proposal. As described in Chapter 5 , the literature review provides the background to your study and demonstrates the significance of the proposed research. Specifically, it is a review and synthesis of prior research that is related to the problem you are setting forth to investigate.  Essentially, your goal in the literature review is to place your research study within the larger whole of what has been studied in the past, while demonstrating to your reader that your work is original, innovative, and adds to the larger whole.

As the literature review is information dense, it is essential that this section be intelligently structured to enable your reader to grasp the key arguments underpinning your study. However, this can be easier to state and harder to do, simply due to the fact there is usually a plethora of related research to sift through. Consequently, a good strategy for writing the literature review is to break the literature into conceptual categories or themes, rather than attempting to describe various groups of literature you reviewed.  Chapter V, “ The Literature Review ,” describes a variety of methods to help you organize the themes.

Here are some suggestions on how to approach the writing of your literature review:

• Think about what questions other researchers have asked, what methods they used, what they found, and what they recommended based upon their findings.
• Do not be afraid to challenge previous related research findings and/or conclusions.
• Assess what you believe to be missing from previous research and explain how your research fills in this gap and/or extends previous research

It is important to note that a significant challenge related to undertaking a literature review is knowing when to stop.  As such, it is important to know how to know when you have uncovered the key conceptual categories underlying your research topic.  Generally, when you start to see repetition in the conclusions or recommendations, you can have confidence that you have covered all of the significant conceptual categories in your literature review.  However, it is also important to acknowledge that researchers often find themselves returning to the literature as they collect and analyze their data.  For example, an unexpected finding may develop as one collects and/or analyzes the data and it is important to take the time to step back and review the literature again, to ensure that no other researchers have found a similar finding.  This may include looking to research outside your field.

This situation occurred with one of the authors of this textbook´s research related to community resilience.  During the interviews, the researchers heard many participants discuss individual resilience factors and how they believed these individual factors helped make the community more resilient, overall.  Sheppard and Williams (2016) had not discovered these individual factors in their original literature review on community and environmental resilience. However, when they returned to the literature to search for individual resilience factors, they discovered a small body of literature in the child and youth psychology field. Consequently, Sheppard and Williams had to go back and add a new section to their literature review on individual resilience factors. Interestingly, their research appeared to be the first research to link individual resilience factors with community resilience factors.

Research design and methods

The objective of this section of the research proposal is to convince the reader that your overall research design and methods of analysis will enable you to solve the research problem you have identified and also enable you to accurately and effectively interpret the results of your research. Consequently, it is critical that the research design and methods section is well-written, clear, and logically organized.  This demonstrates to your reader that you know what you are going to do and how you are going to do it.  Overall, you want to leave your reader feeling confident that you have what it takes to get this research study completed in a timely fashion.

Essentially, this section of the research proposal should be clearly tied to the specific objectives of your study; however, it is also important to draw upon and include examples from the literature review that relate to your design and intended methods.  In other words, you must clearly demonstrate how your study utilizes and builds upon past studies, as it relates to the research design and intended methods.  For example, what methods have been used by other researchers in similar studies?

While it is important to consider the methods that other researchers have employed, it is equally important, if not more so, to consider what methods have not been employed but could be.  Remember, the methods section is not simply a list of tasks to be undertaken. It is also an argument as to why and how the tasks you have outlined will help you investigate the research problem and answer your research question(s).

Tips for writing the research design and methods section:

• Specify the methodological approaches you intend to employ to obtain information and the techniques you will use to analyze the data.
• Specify the research operations you will undertake and he way you will interpret the results of those operations in relation to the research problem.
• Go beyond stating what you hope to achieve through the methods you have chosen. State how you will actually do the methods (i.e. coding interview text, running regression analysis, etc.).
• Anticipate and acknowledge any potential barriers you may encounter when undertaking your research and describe how you will address these barriers.
• Explain where you believe you will find challenges related to data collection, including access to participants and information.

Preliminary suppositions and implications

The purpose of this section is to argue how and in what ways you anticipate that your research will refine, revise, or extend existing knowledge in the area of your study. Depending upon the aims and objectives of your study, you should also discuss how your anticipated findings may impact future research.  For example, is it possible that your research may lead to a new policy, new theoretical understanding, or a new method for analyzing data?  How might your study influence future studies?  What might your study mean for future practitioners working in the field?  Who or what may benefit from your study?  How might your study contribute to social, economic, environmental issues?  While it is important to think about and discuss possibilities such as these, it is equally important to be realistic in stating your anticipated findings.  In other words, you do not want to delve into idle speculation.  Rather, the purpose here is to reflect upon gaps in the current body of literature and to describe how and in what ways you anticipate your research will begin to fill in some or all of those gaps.

The conclusion reiterates the importance and significance of your research proposal and it provides a brief summary of the entire proposed study.  Essentially, this section should only be one or two paragraphs in length. Here is a potential outline for your conclusion:

• Discuss why the study should be done. Specifically discuss how you expect your study will advance existing knowledge and how your study is unique.
• Explain the specific purpose of the study and the research questions that the study will answer.
• Explain why the research design and methods chosen for this study are appropriate, and why other design and methods were not chosen.
• State the potential implications you expect to emerge from your proposed study,
• Provide a sense of how your study fits within the broader scholarship currently in existence related to the research problem.

As with any scholarly research paper, you must cite the sources you used in composing your research proposal.  In a research proposal, this can take two forms: a reference list or a bibliography.  A reference list does what the name suggests, it lists the literature you referenced in the body of your research proposal.  All references in the reference list, must appear in the body of the research proposal.  Remember, it is not acceptable to say “as cited in …”  As a researcher you must always go to the original source and check it for yourself.  Many errors are made in referencing, even by top researchers, and so it is important not to perpetuate an error made by someone else. While this can be time consuming, it is the proper way to undertake a literature review.

In contrast, a bibliography , is a list of everything you used or cited in your research proposal, with additional citations to any key sources relevant to understanding the research problem.  In other words, sources cited in your bibliography may not necessarily appear in the body of your research proposal.  Make sure you check with your instructor to see which of the two you are expected to produce.

Overall, your list of citations should be a testament to the fact that you have done a sufficient level of preliminary research to ensure that your project will complement, but not duplicate, previous research efforts. For social sciences, the reference list or bibliography should be prepared in American Psychological Association (APA) referencing format. Usually, the reference list (or bibliography) is not included in the word count of the research proposal. Again, make sure you check with your instructor to confirm.

An Introduction to Research Methods in Sociology Copyright © 2019 by Valerie A. Sheppard is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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How to write a literature review introduction (+ examples)

The introduction to a literature review serves as your reader’s guide through your academic work and thought process. Explore the significance of literature review introductions in review papers, academic papers, essays, theses, and dissertations. We delve into the purpose and necessity of these introductions, explore the essential components of literature review introductions, and provide step-by-step guidance on how to craft your own, along with examples.

Why you need an introduction for a literature review

When you need an introduction for a literature review, what to include in a literature review introduction, examples of literature review introductions, steps to write your own literature review introduction.

A literature review is a comprehensive examination of the international academic literature concerning a particular topic. It involves summarizing published works, theories, and concepts while also highlighting gaps and offering critical reflections.

In academic writing , the introduction for a literature review is an indispensable component. Effective academic writing requires proper paragraph structuring to guide your reader through your argumentation. This includes providing an introduction to your literature review.

It is imperative to remember that you should never start sharing your findings abruptly. Even if there isn’t a dedicated introduction section .

Instead, you should always offer some form of introduction to orient the reader and clarify what they can expect.

There are three main scenarios in which you need an introduction for a literature review:

• Academic literature review papers: When your literature review constitutes the entirety of an academic review paper, a more substantial introduction is necessary. This introduction should resemble the standard introduction found in regular academic papers.
• Literature review section in an academic paper or essay: While this section tends to be brief, it’s important to precede the detailed literature review with a few introductory sentences. This helps orient the reader before delving into the literature itself.
• Literature review chapter or section in your thesis/dissertation: Every thesis and dissertation includes a literature review component, which also requires a concise introduction to set the stage for the subsequent review.

You may also like: How to write a fantastic thesis introduction (+15 examples)

It is crucial to customize the content and depth of your literature review introduction according to the specific format of your academic work.

In practical terms, this implies, for instance, that the introduction in an academic literature review paper, especially one derived from a systematic literature review , is quite comprehensive. Particularly compared to the rather brief one or two introductory sentences that are often found at the beginning of a literature review section in a standard academic paper. The introduction to the literature review chapter in a thesis or dissertation again adheres to different standards.

Here’s a structured breakdown based on length and the necessary information:

Academic literature review paper

The introduction of an academic literature review paper, which does not rely on empirical data, often necessitates a more extensive introduction than the brief literature review introductions typically found in empirical papers. It should encompass:

• The research problem: Clearly articulate the problem or question that your literature review aims to address.
• The research gap: Highlight the existing gaps, limitations, or unresolved aspects within the current body of literature related to the research problem.
• The research relevance: Explain why the chosen research problem and its subsequent investigation through a literature review are significant and relevant in your academic field.
• The literature review method: If applicable, describe the methodology employed in your literature review, especially if it is a systematic review or follows a specific research framework.
• The main findings or insights of the literature review: Summarize the key discoveries, insights, or trends that have emerged from your comprehensive review of the literature.
• The main argument of the literature review: Conclude the introduction by outlining the primary argument or statement that your literature review will substantiate, linking it to the research problem and relevance you’ve established.
• Preview of the literature review’s structure: Offer a glimpse into the organization of the literature review paper, acting as a guide for the reader. This overview outlines the subsequent sections of the paper and provides an understanding of what to anticipate.

By addressing these elements, your introduction will provide a clear and structured overview of what readers can expect in your literature review paper.

Regular literature review section in an academic article or essay

Most academic articles or essays incorporate regular literature review sections, often placed after the introduction. These sections serve to establish a scholarly basis for the research or discussion within the paper.

In a standard 8000-word journal article, the literature review section typically spans between 750 and 1250 words. The first few sentences or the first paragraph within this section often serve as an introduction. It should encompass:

• An introduction to the topic: When delving into the academic literature on a specific topic, it’s important to provide a smooth transition that aids the reader in comprehending why certain aspects will be discussed within your literature review.
• The core argument: While literature review sections primarily synthesize the work of other scholars, they should consistently connect to your central argument. This central argument serves as the crux of your message or the key takeaway you want your readers to retain. By positioning it at the outset of the literature review section and systematically substantiating it with evidence, you not only enhance reader comprehension but also elevate overall readability. This primary argument can typically be distilled into 1-2 succinct sentences.

In some cases, you might include:

• Methodology: Details about the methodology used, but only if your literature review employed a specialized method. If your approach involved a broader overview without a systematic methodology, you can omit this section, thereby conserving word count.

By addressing these elements, your introduction will effectively integrate your literature review into the broader context of your academic paper or essay. This will, in turn, assist your reader in seamlessly following your overarching line of argumentation.

Introduction to a literature review chapter in thesis or dissertation

The literature review typically constitutes a distinct chapter within a thesis or dissertation. Often, it is Chapter 2 of a thesis or dissertation.

Some students choose to incorporate a brief introductory section at the beginning of each chapter, including the literature review chapter. Alternatively, others opt to seamlessly integrate the introduction into the initial sentences of the literature review itself. Both approaches are acceptable, provided that you incorporate the following elements:

• Purpose of the literature review and its relevance to the thesis/dissertation research: Explain the broader objectives of the literature review within the context of your research and how it contributes to your thesis or dissertation. Essentially, you’re telling the reader why this literature review is important and how it fits into the larger scope of your academic work.
• Primary argument: Succinctly communicate what you aim to prove, explain, or explore through the review of existing literature. This statement helps guide the reader’s understanding of the review’s purpose and what to expect from it.
• Preview of the literature review’s content: Provide a brief overview of the topics or themes that your literature review will cover. It’s like a roadmap for the reader, outlining the main areas of focus within the review. This preview can help the reader anticipate the structure and organization of your literature review.
• Methodology: If your literature review involved a specific research method, such as a systematic review or meta-analysis, you should briefly describe that methodology. However, this is not always necessary, especially if your literature review is more of a narrative synthesis without a distinct research method.

By addressing these elements, your introduction will empower your literature review to play a pivotal role in your thesis or dissertation research. It will accomplish this by integrating your research into the broader academic literature and providing a solid theoretical foundation for your work.

Comprehending the art of crafting your own literature review introduction becomes significantly more accessible when you have concrete examples to examine. Here, you will find several examples that meet, or in most cases, adhere to the criteria described earlier.

Example 1: An effective introduction for an academic literature review paper

To begin, let’s delve into the introduction of an academic literature review paper. We will examine the paper “How does culture influence innovation? A systematic literature review”, which was published in 2018 in the journal Management Decision.

The entire introduction spans 611 words and is divided into five paragraphs. In this introduction, the authors accomplish the following:

• In the first paragraph, the authors introduce the broader topic of the literature review, which focuses on innovation and its significance in the context of economic competition. They underscore the importance of this topic, highlighting its relevance for both researchers and policymakers.
• In the second paragraph, the authors narrow down their focus to emphasize the specific role of culture in relation to innovation.
• In the third paragraph, the authors identify research gaps, noting that existing studies are often fragmented and disconnected. They then emphasize the value of conducting a systematic literature review to enhance our understanding of the topic.
• In the fourth paragraph, the authors introduce their specific objectives and explain how their insights can benefit other researchers and business practitioners.
• In the fifth and final paragraph, the authors provide an overview of the paper’s organization and structure.

In summary, this introduction stands as a solid example. While the authors deviate from previewing their key findings (which is a common practice at least in the social sciences), they do effectively cover all the other previously mentioned points.

Example 2: An effective introduction to a literature review section in an academic paper

The second example represents a typical academic paper, encompassing not only a literature review section but also empirical data, a case study, and other elements. We will closely examine the introduction to the literature review section in the paper “The environmentalism of the subalterns: a case study of environmental activism in Eastern Kurdistan/Rojhelat”, which was published in 2021 in the journal Local Environment.

The paper begins with a general introduction and then proceeds to the literature review, designated by the authors as their conceptual framework. Of particular interest is the first paragraph of this conceptual framework, comprising 142 words across five sentences:

“ A peripheral and marginalised nationality within a multinational though-Persian dominated Iranian society, the Kurdish people of Iranian Kurdistan (a region referred by the Kurds as Rojhelat/Eastern Kurdi-stan) have since the early twentieth century been subject to multifaceted and systematic discriminatory and exclusionary state policy in Iran. This condition has left a population of 12–15 million Kurds in Iran suffering from structural inequalities, disenfranchisement and deprivation. Mismanagement of Kurdistan’s natural resources and the degradation of its natural environmental are among examples of this disenfranchisement. As asserted by Julian Agyeman (2005), structural inequalities that sustain the domination of political and economic elites often simultaneously result in environmental degradation, injustice and discrimination against subaltern communities. This study argues that the environmental struggle in Eastern Kurdistan can be asserted as a (sub)element of the Kurdish liberation movement in Iran. Conceptually this research is inspired by and has been conducted through the lens of ‘subalternity’ ” ( Hassaniyan, 2021, p. 931 ).

In this first paragraph, the author is doing the following:

• The author contextualises the research
• The author links the research focus to the international literature on structural inequalities
• The author clearly presents the argument of the research
• The author clarifies how the research is inspired by and uses the concept of ‘subalternity’.

Thus, the author successfully introduces the literature review, from which point onward it dives into the main concept (‘subalternity’) of the research, and reviews the literature on socio-economic justice and environmental degradation.

While introductions to a literature review section aren’t always required to offer the same level of study context detail as demonstrated here, this introduction serves as a commendable model for orienting the reader within the literature review. It effectively underscores the literature review’s significance within the context of the study being conducted.

Examples 3-5: Effective introductions to literature review chapters

The introduction to a literature review chapter can vary in length, depending largely on the overall length of the literature review chapter itself. For example, a master’s thesis typically features a more concise literature review, thus necessitating a shorter introduction. In contrast, a Ph.D. thesis, with its more extensive literature review, often includes a more detailed introduction.

Numerous universities offer online repositories where you can access theses and dissertations from previous years, serving as valuable sources of reference. Many of these repositories, however, may require you to log in through your university account. Nevertheless, a few open-access repositories are accessible to anyone, such as the one by the University of Manchester . It’s important to note though that copyright restrictions apply to these resources, just as they would with published papers.

Master’s thesis literature review introduction

The first example is “Benchmarking Asymmetrical Heating Models of Spider Pulsar Companions” by P. Sun, a master’s thesis completed at the University of Manchester on January 9, 2024. The author, P. Sun, introduces the literature review chapter very briefly but effectively:

PhD thesis literature review chapter introduction

The second example is Deep Learning on Semi-Structured Data and its Applications to Video-Game AI, Woof, W. (Author). 31 Dec 2020, a PhD thesis completed at the University of Manchester . In Chapter 2, the author offers a comprehensive introduction to the topic in four paragraphs, with the final paragraph serving as an overview of the chapter’s structure:

PhD thesis literature review introduction

The last example is the doctoral thesis Metacognitive strategies and beliefs: Child correlates and early experiences Chan, K. Y. M. (Author). 31 Dec 2020 . The author clearly conducted a systematic literature review, commencing the review section with a discussion of the methodology and approach employed in locating and analyzing the selected records.

Having absorbed all of this information, let’s recap the essential steps and offer a succinct guide on how to proceed with creating your literature review introduction:

• Contextualize your review : Begin by clearly identifying the academic context in which your literature review resides and determining the necessary information to include.
• Outline your structure : Develop a structured outline for your literature review, highlighting the essential information you plan to incorporate in your introduction.
• Literature review process : Conduct a rigorous literature review, reviewing and analyzing relevant sources.
• Summarize and abstract : After completing the review, synthesize the findings and abstract key insights, trends, and knowledge gaps from the literature.
• Craft the introduction : Write your literature review introduction with meticulous attention to the seamless integration of your review into the larger context of your work. Ensure that your introduction effectively elucidates your rationale for the chosen review topics and the underlying reasons guiding your selection.

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Lau F, Kuziemsky C, editors. Handbook of eHealth Evaluation: An Evidence-based Approach [Internet]. Victoria (BC): University of Victoria; 2017 Feb 27.

Handbook of eHealth Evaluation: An Evidence-based Approach [Internet].

Chapter 9 methods for literature reviews.

Guy Paré and Spyros Kitsiou .

9.1. Introduction

Literature reviews play a critical role in scholarship because science remains, first and foremost, a cumulative endeavour ( vom Brocke et al., 2009 ). As in any academic discipline, rigorous knowledge syntheses are becoming indispensable in keeping up with an exponentially growing eHealth literature, assisting practitioners, academics, and graduate students in finding, evaluating, and synthesizing the contents of many empirical and conceptual papers. Among other methods, literature reviews are essential for: (a) identifying what has been written on a subject or topic; (b) determining the extent to which a specific research area reveals any interpretable trends or patterns; (c) aggregating empirical findings related to a narrow research question to support evidence-based practice; (d) generating new frameworks and theories; and (e) identifying topics or questions requiring more investigation ( Paré, Trudel, Jaana, & Kitsiou, 2015 ).

Literature reviews can take two major forms. The most prevalent one is the “literature review” or “background” section within a journal paper or a chapter in a graduate thesis. This section synthesizes the extant literature and usually identifies the gaps in knowledge that the empirical study addresses ( Sylvester, Tate, & Johnstone, 2013 ). It may also provide a theoretical foundation for the proposed study, substantiate the presence of the research problem, justify the research as one that contributes something new to the cumulated knowledge, or validate the methods and approaches for the proposed study ( Hart, 1998 ; Levy & Ellis, 2006 ).

The second form of literature review, which is the focus of this chapter, constitutes an original and valuable work of research in and of itself ( Paré et al., 2015 ). Rather than providing a base for a researcher’s own work, it creates a solid starting point for all members of the community interested in a particular area or topic ( Mulrow, 1987 ). The so-called “review article” is a journal-length paper which has an overarching purpose to synthesize the literature in a field, without collecting or analyzing any primary data ( Green, Johnson, & Adams, 2006 ).

When appropriately conducted, review articles represent powerful information sources for practitioners looking for state-of-the art evidence to guide their decision-making and work practices ( Paré et al., 2015 ). Further, high-quality reviews become frequently cited pieces of work which researchers seek out as a first clear outline of the literature when undertaking empirical studies ( Cooper, 1988 ; Rowe, 2014 ). Scholars who track and gauge the impact of articles have found that review papers are cited and downloaded more often than any other type of published article ( Cronin, Ryan, & Coughlan, 2008 ; Montori, Wilczynski, Morgan, Haynes, & Hedges, 2003 ; Patsopoulos, Analatos, & Ioannidis, 2005 ). The reason for their popularity may be the fact that reading the review enables one to have an overview, if not a detailed knowledge of the area in question, as well as references to the most useful primary sources ( Cronin et al., 2008 ). Although they are not easy to conduct, the commitment to complete a review article provides a tremendous service to one’s academic community ( Paré et al., 2015 ; Petticrew & Roberts, 2006 ). Most, if not all, peer-reviewed journals in the fields of medical informatics publish review articles of some type.

The main objectives of this chapter are fourfold: (a) to provide an overview of the major steps and activities involved in conducting a stand-alone literature review; (b) to describe and contrast the different types of review articles that can contribute to the eHealth knowledge base; (c) to illustrate each review type with one or two examples from the eHealth literature; and (d) to provide a series of recommendations for prospective authors of review articles in this domain.

9.2. Overview of the Literature Review Process and Steps

As explained in Templier and Paré (2015) , there are six generic steps involved in conducting a review article:

• formulating the research question(s) and objective(s),
• searching the extant literature,
• screening for inclusion,
• assessing the quality of primary studies,
• extracting data, and
• analyzing data.

Although these steps are presented here in sequential order, one must keep in mind that the review process can be iterative and that many activities can be initiated during the planning stage and later refined during subsequent phases ( Finfgeld-Connett & Johnson, 2013 ; Kitchenham & Charters, 2007 ).

Formulating the research question(s) and objective(s): As a first step, members of the review team must appropriately justify the need for the review itself ( Petticrew & Roberts, 2006 ), identify the review’s main objective(s) ( Okoli & Schabram, 2010 ), and define the concepts or variables at the heart of their synthesis ( Cooper & Hedges, 2009 ; Webster & Watson, 2002 ). Importantly, they also need to articulate the research question(s) they propose to investigate ( Kitchenham & Charters, 2007 ). In this regard, we concur with Jesson, Matheson, and Lacey (2011) that clearly articulated research questions are key ingredients that guide the entire review methodology; they underscore the type of information that is needed, inform the search for and selection of relevant literature, and guide or orient the subsequent analysis. Searching the extant literature: The next step consists of searching the literature and making decisions about the suitability of material to be considered in the review ( Cooper, 1988 ). There exist three main coverage strategies. First, exhaustive coverage means an effort is made to be as comprehensive as possible in order to ensure that all relevant studies, published and unpublished, are included in the review and, thus, conclusions are based on this all-inclusive knowledge base. The second type of coverage consists of presenting materials that are representative of most other works in a given field or area. Often authors who adopt this strategy will search for relevant articles in a small number of top-tier journals in a field ( Paré et al., 2015 ). In the third strategy, the review team concentrates on prior works that have been central or pivotal to a particular topic. This may include empirical studies or conceptual papers that initiated a line of investigation, changed how problems or questions were framed, introduced new methods or concepts, or engendered important debate ( Cooper, 1988 ). Screening for inclusion: The following step consists of evaluating the applicability of the material identified in the preceding step ( Levy & Ellis, 2006 ; vom Brocke et al., 2009 ). Once a group of potential studies has been identified, members of the review team must screen them to determine their relevance ( Petticrew & Roberts, 2006 ). A set of predetermined rules provides a basis for including or excluding certain studies. This exercise requires a significant investment on the part of researchers, who must ensure enhanced objectivity and avoid biases or mistakes. As discussed later in this chapter, for certain types of reviews there must be at least two independent reviewers involved in the screening process and a procedure to resolve disagreements must also be in place ( Liberati et al., 2009 ; Shea et al., 2009 ). Assessing the quality of primary studies: In addition to screening material for inclusion, members of the review team may need to assess the scientific quality of the selected studies, that is, appraise the rigour of the research design and methods. Such formal assessment, which is usually conducted independently by at least two coders, helps members of the review team refine which studies to include in the final sample, determine whether or not the differences in quality may affect their conclusions, or guide how they analyze the data and interpret the findings ( Petticrew & Roberts, 2006 ). Ascribing quality scores to each primary study or considering through domain-based evaluations which study components have or have not been designed and executed appropriately makes it possible to reflect on the extent to which the selected study addresses possible biases and maximizes validity ( Shea et al., 2009 ). Extracting data: The following step involves gathering or extracting applicable information from each primary study included in the sample and deciding what is relevant to the problem of interest ( Cooper & Hedges, 2009 ). Indeed, the type of data that should be recorded mainly depends on the initial research questions ( Okoli & Schabram, 2010 ). However, important information may also be gathered about how, when, where and by whom the primary study was conducted, the research design and methods, or qualitative/quantitative results ( Cooper & Hedges, 2009 ). Analyzing and synthesizing data : As a final step, members of the review team must collate, summarize, aggregate, organize, and compare the evidence extracted from the included studies. The extracted data must be presented in a meaningful way that suggests a new contribution to the extant literature ( Jesson et al., 2011 ). Webster and Watson (2002) warn researchers that literature reviews should be much more than lists of papers and should provide a coherent lens to make sense of extant knowledge on a given topic. There exist several methods and techniques for synthesizing quantitative (e.g., frequency analysis, meta-analysis) and qualitative (e.g., grounded theory, narrative analysis, meta-ethnography) evidence ( Dixon-Woods, Agarwal, Jones, Young, & Sutton, 2005 ; Thomas & Harden, 2008 ).

9.3. Types of Review Articles and Brief Illustrations

EHealth researchers have at their disposal a number of approaches and methods for making sense out of existing literature, all with the purpose of casting current research findings into historical contexts or explaining contradictions that might exist among a set of primary research studies conducted on a particular topic. Our classification scheme is largely inspired from Paré and colleagues’ (2015) typology. Below we present and illustrate those review types that we feel are central to the growth and development of the eHealth domain.

9.3.1. Narrative Reviews

The narrative review is the “traditional” way of reviewing the extant literature and is skewed towards a qualitative interpretation of prior knowledge ( Sylvester et al., 2013 ). Put simply, a narrative review attempts to summarize or synthesize what has been written on a particular topic but does not seek generalization or cumulative knowledge from what is reviewed ( Davies, 2000 ; Green et al., 2006 ). Instead, the review team often undertakes the task of accumulating and synthesizing the literature to demonstrate the value of a particular point of view ( Baumeister & Leary, 1997 ). As such, reviewers may selectively ignore or limit the attention paid to certain studies in order to make a point. In this rather unsystematic approach, the selection of information from primary articles is subjective, lacks explicit criteria for inclusion and can lead to biased interpretations or inferences ( Green et al., 2006 ). There are several narrative reviews in the particular eHealth domain, as in all fields, which follow such an unstructured approach ( Silva et al., 2015 ; Paul et al., 2015 ).

Despite these criticisms, this type of review can be very useful in gathering together a volume of literature in a specific subject area and synthesizing it. As mentioned above, its primary purpose is to provide the reader with a comprehensive background for understanding current knowledge and highlighting the significance of new research ( Cronin et al., 2008 ). Faculty like to use narrative reviews in the classroom because they are often more up to date than textbooks, provide a single source for students to reference, and expose students to peer-reviewed literature ( Green et al., 2006 ). For researchers, narrative reviews can inspire research ideas by identifying gaps or inconsistencies in a body of knowledge, thus helping researchers to determine research questions or formulate hypotheses. Importantly, narrative reviews can also be used as educational articles to bring practitioners up to date with certain topics of issues ( Green et al., 2006 ).

Recently, there have been several efforts to introduce more rigour in narrative reviews that will elucidate common pitfalls and bring changes into their publication standards. Information systems researchers, among others, have contributed to advancing knowledge on how to structure a “traditional” review. For instance, Levy and Ellis (2006) proposed a generic framework for conducting such reviews. Their model follows the systematic data processing approach comprised of three steps, namely: (a) literature search and screening; (b) data extraction and analysis; and (c) writing the literature review. They provide detailed and very helpful instructions on how to conduct each step of the review process. As another methodological contribution, vom Brocke et al. (2009) offered a series of guidelines for conducting literature reviews, with a particular focus on how to search and extract the relevant body of knowledge. Last, Bandara, Miskon, and Fielt (2011) proposed a structured, predefined and tool-supported method to identify primary studies within a feasible scope, extract relevant content from identified articles, synthesize and analyze the findings, and effectively write and present the results of the literature review. We highly recommend that prospective authors of narrative reviews consult these useful sources before embarking on their work.

Darlow and Wen (2015) provide a good example of a highly structured narrative review in the eHealth field. These authors synthesized published articles that describe the development process of mobile health ( m-health ) interventions for patients’ cancer care self-management. As in most narrative reviews, the scope of the research questions being investigated is broad: (a) how development of these systems are carried out; (b) which methods are used to investigate these systems; and (c) what conclusions can be drawn as a result of the development of these systems. To provide clear answers to these questions, a literature search was conducted on six electronic databases and Google Scholar . The search was performed using several terms and free text words, combining them in an appropriate manner. Four inclusion and three exclusion criteria were utilized during the screening process. Both authors independently reviewed each of the identified articles to determine eligibility and extract study information. A flow diagram shows the number of studies identified, screened, and included or excluded at each stage of study selection. In terms of contributions, this review provides a series of practical recommendations for m-health intervention development.

9.3.2. Descriptive or Mapping Reviews

The primary goal of a descriptive review is to determine the extent to which a body of knowledge in a particular research topic reveals any interpretable pattern or trend with respect to pre-existing propositions, theories, methodologies or findings ( King & He, 2005 ; Paré et al., 2015 ). In contrast with narrative reviews, descriptive reviews follow a systematic and transparent procedure, including searching, screening and classifying studies ( Petersen, Vakkalanka, & Kuzniarz, 2015 ). Indeed, structured search methods are used to form a representative sample of a larger group of published works ( Paré et al., 2015 ). Further, authors of descriptive reviews extract from each study certain characteristics of interest, such as publication year, research methods, data collection techniques, and direction or strength of research outcomes (e.g., positive, negative, or non-significant) in the form of frequency analysis to produce quantitative results ( Sylvester et al., 2013 ). In essence, each study included in a descriptive review is treated as the unit of analysis and the published literature as a whole provides a database from which the authors attempt to identify any interpretable trends or draw overall conclusions about the merits of existing conceptualizations, propositions, methods or findings ( Paré et al., 2015 ). In doing so, a descriptive review may claim that its findings represent the state of the art in a particular domain ( King & He, 2005 ).

In the fields of health sciences and medical informatics, reviews that focus on examining the range, nature and evolution of a topic area are described by Anderson, Allen, Peckham, and Goodwin (2008) as mapping reviews . Like descriptive reviews, the research questions are generic and usually relate to publication patterns and trends. There is no preconceived plan to systematically review all of the literature although this can be done. Instead, researchers often present studies that are representative of most works published in a particular area and they consider a specific time frame to be mapped.

An example of this approach in the eHealth domain is offered by DeShazo, Lavallie, and Wolf (2009). The purpose of this descriptive or mapping review was to characterize publication trends in the medical informatics literature over a 20-year period (1987 to 2006). To achieve this ambitious objective, the authors performed a bibliometric analysis of medical informatics citations indexed in medline using publication trends, journal frequencies, impact factors, Medical Subject Headings (MeSH) term frequencies, and characteristics of citations. Findings revealed that there were over 77,000 medical informatics articles published during the covered period in numerous journals and that the average annual growth rate was 12%. The MeSH term analysis also suggested a strong interdisciplinary trend. Finally, average impact scores increased over time with two notable growth periods. Overall, patterns in research outputs that seem to characterize the historic trends and current components of the field of medical informatics suggest it may be a maturing discipline (DeShazo et al., 2009).

9.3.3. Scoping Reviews

Scoping reviews attempt to provide an initial indication of the potential size and nature of the extant literature on an emergent topic (Arksey & O’Malley, 2005; Daudt, van Mossel, & Scott, 2013 ; Levac, Colquhoun, & O’Brien, 2010). A scoping review may be conducted to examine the extent, range and nature of research activities in a particular area, determine the value of undertaking a full systematic review (discussed next), or identify research gaps in the extant literature ( Paré et al., 2015 ). In line with their main objective, scoping reviews usually conclude with the presentation of a detailed research agenda for future works along with potential implications for both practice and research.

Unlike narrative and descriptive reviews, the whole point of scoping the field is to be as comprehensive as possible, including grey literature (Arksey & O’Malley, 2005). Inclusion and exclusion criteria must be established to help researchers eliminate studies that are not aligned with the research questions. It is also recommended that at least two independent coders review abstracts yielded from the search strategy and then the full articles for study selection ( Daudt et al., 2013 ). The synthesized evidence from content or thematic analysis is relatively easy to present in tabular form (Arksey & O’Malley, 2005; Thomas & Harden, 2008 ).

One of the most highly cited scoping reviews in the eHealth domain was published by Archer, Fevrier-Thomas, Lokker, McKibbon, and Straus (2011) . These authors reviewed the existing literature on personal health record ( phr ) systems including design, functionality, implementation, applications, outcomes, and benefits. Seven databases were searched from 1985 to March 2010. Several search terms relating to phr s were used during this process. Two authors independently screened titles and abstracts to determine inclusion status. A second screen of full-text articles, again by two independent members of the research team, ensured that the studies described phr s. All in all, 130 articles met the criteria and their data were extracted manually into a database. The authors concluded that although there is a large amount of survey, observational, cohort/panel, and anecdotal evidence of phr benefits and satisfaction for patients, more research is needed to evaluate the results of phr implementations. Their in-depth analysis of the literature signalled that there is little solid evidence from randomized controlled trials or other studies through the use of phr s. Hence, they suggested that more research is needed that addresses the current lack of understanding of optimal functionality and usability of these systems, and how they can play a beneficial role in supporting patient self-management ( Archer et al., 2011 ).

9.3.4. Forms of Aggregative Reviews

Healthcare providers, practitioners, and policy-makers are nowadays overwhelmed with large volumes of information, including research-based evidence from numerous clinical trials and evaluation studies, assessing the effectiveness of health information technologies and interventions ( Ammenwerth & de Keizer, 2004 ; Deshazo et al., 2009 ). It is unrealistic to expect that all these disparate actors will have the time, skills, and necessary resources to identify the available evidence in the area of their expertise and consider it when making decisions. Systematic reviews that involve the rigorous application of scientific strategies aimed at limiting subjectivity and bias (i.e., systematic and random errors) can respond to this challenge.

Systematic reviews attempt to aggregate, appraise, and synthesize in a single source all empirical evidence that meet a set of previously specified eligibility criteria in order to answer a clearly formulated and often narrow research question on a particular topic of interest to support evidence-based practice ( Liberati et al., 2009 ). They adhere closely to explicit scientific principles ( Liberati et al., 2009 ) and rigorous methodological guidelines (Higgins & Green, 2008) aimed at reducing random and systematic errors that can lead to deviations from the truth in results or inferences. The use of explicit methods allows systematic reviews to aggregate a large body of research evidence, assess whether effects or relationships are in the same direction and of the same general magnitude, explain possible inconsistencies between study results, and determine the strength of the overall evidence for every outcome of interest based on the quality of included studies and the general consistency among them ( Cook, Mulrow, & Haynes, 1997 ). The main procedures of a systematic review involve:

• Formulating a review question and developing a search strategy based on explicit inclusion criteria for the identification of eligible studies (usually described in the context of a detailed review protocol).
• Searching for eligible studies using multiple databases and information sources, including grey literature sources, without any language restrictions.
• Selecting studies, extracting data, and assessing risk of bias in a duplicate manner using two independent reviewers to avoid random or systematic errors in the process.
• Analyzing data using quantitative or qualitative methods.
• Presenting results in summary of findings tables.
• Interpreting results and drawing conclusions.

Many systematic reviews, but not all, use statistical methods to combine the results of independent studies into a single quantitative estimate or summary effect size. Known as meta-analyses , these reviews use specific data extraction and statistical techniques (e.g., network, frequentist, or Bayesian meta-analyses) to calculate from each study by outcome of interest an effect size along with a confidence interval that reflects the degree of uncertainty behind the point estimate of effect ( Borenstein, Hedges, Higgins, & Rothstein, 2009 ; Deeks, Higgins, & Altman, 2008 ). Subsequently, they use fixed or random-effects analysis models to combine the results of the included studies, assess statistical heterogeneity, and calculate a weighted average of the effect estimates from the different studies, taking into account their sample sizes. The summary effect size is a value that reflects the average magnitude of the intervention effect for a particular outcome of interest or, more generally, the strength of a relationship between two variables across all studies included in the systematic review. By statistically combining data from multiple studies, meta-analyses can create more precise and reliable estimates of intervention effects than those derived from individual studies alone, when these are examined independently as discrete sources of information.

The review by Gurol-Urganci, de Jongh, Vodopivec-Jamsek, Atun, and Car (2013) on the effects of mobile phone messaging reminders for attendance at healthcare appointments is an illustrative example of a high-quality systematic review with meta-analysis. Missed appointments are a major cause of inefficiency in healthcare delivery with substantial monetary costs to health systems. These authors sought to assess whether mobile phone-based appointment reminders delivered through Short Message Service ( sms ) or Multimedia Messaging Service ( mms ) are effective in improving rates of patient attendance and reducing overall costs. To this end, they conducted a comprehensive search on multiple databases using highly sensitive search strategies without language or publication-type restrictions to identify all rct s that are eligible for inclusion. In order to minimize the risk of omitting eligible studies not captured by the original search, they supplemented all electronic searches with manual screening of trial registers and references contained in the included studies. Study selection, data extraction, and risk of bias assessments were performed inde­­pen­dently by two coders using standardized methods to ensure consistency and to eliminate potential errors. Findings from eight rct s involving 6,615 participants were pooled into meta-analyses to calculate the magnitude of effects that mobile text message reminders have on the rate of attendance at healthcare appointments compared to no reminders and phone call reminders.

Meta-analyses are regarded as powerful tools for deriving meaningful conclusions. However, there are situations in which it is neither reasonable nor appropriate to pool studies together using meta-analytic methods simply because there is extensive clinical heterogeneity between the included studies or variation in measurement tools, comparisons, or outcomes of interest. In these cases, systematic reviews can use qualitative synthesis methods such as vote counting, content analysis, classification schemes and tabulations, as an alternative approach to narratively synthesize the results of the independent studies included in the review. This form of review is known as qualitative systematic review.

A rigorous example of one such review in the eHealth domain is presented by Mickan, Atherton, Roberts, Heneghan, and Tilson (2014) on the use of handheld computers by healthcare professionals and their impact on access to information and clinical decision-making. In line with the methodological guide­lines for systematic reviews, these authors: (a) developed and registered with prospero ( www.crd.york.ac.uk/ prospero / ) an a priori review protocol; (b) conducted comprehensive searches for eligible studies using multiple databases and other supplementary strategies (e.g., forward searches); and (c) subsequently carried out study selection, data extraction, and risk of bias assessments in a duplicate manner to eliminate potential errors in the review process. Heterogeneity between the included studies in terms of reported outcomes and measures precluded the use of meta-analytic methods. To this end, the authors resorted to using narrative analysis and synthesis to describe the effectiveness of handheld computers on accessing information for clinical knowledge, adherence to safety and clinical quality guidelines, and diagnostic decision-making.

In recent years, the number of systematic reviews in the field of health informatics has increased considerably. Systematic reviews with discordant findings can cause great confusion and make it difficult for decision-makers to interpret the review-level evidence ( Moher, 2013 ). Therefore, there is a growing need for appraisal and synthesis of prior systematic reviews to ensure that decision-making is constantly informed by the best available accumulated evidence. Umbrella reviews , also known as overviews of systematic reviews, are tertiary types of evidence synthesis that aim to accomplish this; that is, they aim to compare and contrast findings from multiple systematic reviews and meta-analyses ( Becker & Oxman, 2008 ). Umbrella reviews generally adhere to the same principles and rigorous methodological guidelines used in systematic reviews. However, the unit of analysis in umbrella reviews is the systematic review rather than the primary study ( Becker & Oxman, 2008 ). Unlike systematic reviews that have a narrow focus of inquiry, umbrella reviews focus on broader research topics for which there are several potential interventions ( Smith, Devane, Begley, & Clarke, 2011 ). A recent umbrella review on the effects of home telemonitoring interventions for patients with heart failure critically appraised, compared, and synthesized evidence from 15 systematic reviews to investigate which types of home telemonitoring technologies and forms of interventions are more effective in reducing mortality and hospital admissions ( Kitsiou, Paré, & Jaana, 2015 ).

9.3.5. Realist Reviews

Realist reviews are theory-driven interpretative reviews developed to inform, enhance, or supplement conventional systematic reviews by making sense of heterogeneous evidence about complex interventions applied in diverse contexts in a way that informs policy decision-making ( Greenhalgh, Wong, Westhorp, & Pawson, 2011 ). They originated from criticisms of positivist systematic reviews which centre on their “simplistic” underlying assumptions ( Oates, 2011 ). As explained above, systematic reviews seek to identify causation. Such logic is appropriate for fields like medicine and education where findings of randomized controlled trials can be aggregated to see whether a new treatment or intervention does improve outcomes. However, many argue that it is not possible to establish such direct causal links between interventions and outcomes in fields such as social policy, management, and information systems where for any intervention there is unlikely to be a regular or consistent outcome ( Oates, 2011 ; Pawson, 2006 ; Rousseau, Manning, & Denyer, 2008 ).

To circumvent these limitations, Pawson, Greenhalgh, Harvey, and Walshe (2005) have proposed a new approach for synthesizing knowledge that seeks to unpack the mechanism of how “complex interventions” work in particular contexts. The basic research question — what works? — which is usually associated with systematic reviews changes to: what is it about this intervention that works, for whom, in what circumstances, in what respects and why? Realist reviews have no particular preference for either quantitative or qualitative evidence. As a theory-building approach, a realist review usually starts by articulating likely underlying mechanisms and then scrutinizes available evidence to find out whether and where these mechanisms are applicable ( Shepperd et al., 2009 ). Primary studies found in the extant literature are viewed as case studies which can test and modify the initial theories ( Rousseau et al., 2008 ).

The main objective pursued in the realist review conducted by Otte-Trojel, de Bont, Rundall, and van de Klundert (2014) was to examine how patient portals contribute to health service delivery and patient outcomes. The specific goals were to investigate how outcomes are produced and, most importantly, how variations in outcomes can be explained. The research team started with an exploratory review of background documents and research studies to identify ways in which patient portals may contribute to health service delivery and patient outcomes. The authors identified six main ways which represent “educated guesses” to be tested against the data in the evaluation studies. These studies were identified through a formal and systematic search in four databases between 2003 and 2013. Two members of the research team selected the articles using a pre-established list of inclusion and exclusion criteria and following a two-step procedure. The authors then extracted data from the selected articles and created several tables, one for each outcome category. They organized information to bring forward those mechanisms where patient portals contribute to outcomes and the variation in outcomes across different contexts.

9.3.6. Critical Reviews

Lastly, critical reviews aim to provide a critical evaluation and interpretive analysis of existing literature on a particular topic of interest to reveal strengths, weaknesses, contradictions, controversies, inconsistencies, and/or other important issues with respect to theories, hypotheses, research methods or results ( Baumeister & Leary, 1997 ; Kirkevold, 1997 ). Unlike other review types, critical reviews attempt to take a reflective account of the research that has been done in a particular area of interest, and assess its credibility by using appraisal instruments or critical interpretive methods. In this way, critical reviews attempt to constructively inform other scholars about the weaknesses of prior research and strengthen knowledge development by giving focus and direction to studies for further improvement ( Kirkevold, 1997 ).

Kitsiou, Paré, and Jaana (2013) provide an example of a critical review that assessed the methodological quality of prior systematic reviews of home telemonitoring studies for chronic patients. The authors conducted a comprehensive search on multiple databases to identify eligible reviews and subsequently used a validated instrument to conduct an in-depth quality appraisal. Results indicate that the majority of systematic reviews in this particular area suffer from important methodological flaws and biases that impair their internal validity and limit their usefulness for clinical and decision-making purposes. To this end, they provide a number of recommendations to strengthen knowledge development towards improving the design and execution of future reviews on home telemonitoring.

9.4. Summary

Table 9.1 outlines the main types of literature reviews that were described in the previous sub-sections and summarizes the main characteristics that distinguish one review type from another. It also includes key references to methodological guidelines and useful sources that can be used by eHealth scholars and researchers for planning and developing reviews.

Typology of Literature Reviews (adapted from Paré et al., 2015).

As shown in Table 9.1 , each review type addresses different kinds of research questions or objectives, which subsequently define and dictate the methods and approaches that need to be used to achieve the overarching goal(s) of the review. For example, in the case of narrative reviews, there is greater flexibility in searching and synthesizing articles ( Green et al., 2006 ). Researchers are often relatively free to use a diversity of approaches to search, identify, and select relevant scientific articles, describe their operational characteristics, present how the individual studies fit together, and formulate conclusions. On the other hand, systematic reviews are characterized by their high level of systematicity, rigour, and use of explicit methods, based on an “a priori” review plan that aims to minimize bias in the analysis and synthesis process (Higgins & Green, 2008). Some reviews are exploratory in nature (e.g., scoping/mapping reviews), whereas others may be conducted to discover patterns (e.g., descriptive reviews) or involve a synthesis approach that may include the critical analysis of prior research ( Paré et al., 2015 ). Hence, in order to select the most appropriate type of review, it is critical to know before embarking on a review project, why the research synthesis is conducted and what type of methods are best aligned with the pursued goals.

9.5. Concluding Remarks

In light of the increased use of evidence-based practice and research generating stronger evidence ( Grady et al., 2011 ; Lyden et al., 2013 ), review articles have become essential tools for summarizing, synthesizing, integrating or critically appraising prior knowledge in the eHealth field. As mentioned earlier, when rigorously conducted review articles represent powerful information sources for eHealth scholars and practitioners looking for state-of-the-art evidence. The typology of literature reviews we used herein will allow eHealth researchers, graduate students and practitioners to gain a better understanding of the similarities and differences between review types.

We must stress that this classification scheme does not privilege any specific type of review as being of higher quality than another ( Paré et al., 2015 ). As explained above, each type of review has its own strengths and limitations. Having said that, we realize that the methodological rigour of any review — be it qualitative, quantitative or mixed — is a critical aspect that should be considered seriously by prospective authors. In the present context, the notion of rigour refers to the reliability and validity of the review process described in section 9.2. For one thing, reliability is related to the reproducibility of the review process and steps, which is facilitated by a comprehensive documentation of the literature search process, extraction, coding and analysis performed in the review. Whether the search is comprehensive or not, whether it involves a methodical approach for data extraction and synthesis or not, it is important that the review documents in an explicit and transparent manner the steps and approach that were used in the process of its development. Next, validity characterizes the degree to which the review process was conducted appropriately. It goes beyond documentation and reflects decisions related to the selection of the sources, the search terms used, the period of time covered, the articles selected in the search, and the application of backward and forward searches ( vom Brocke et al., 2009 ). In short, the rigour of any review article is reflected by the explicitness of its methods (i.e., transparency) and the soundness of the approach used. We refer those interested in the concepts of rigour and quality to the work of Templier and Paré (2015) which offers a detailed set of methodological guidelines for conducting and evaluating various types of review articles.

To conclude, our main objective in this chapter was to demystify the various types of literature reviews that are central to the continuous development of the eHealth field. It is our hope that our descriptive account will serve as a valuable source for those conducting, evaluating or using reviews in this important and growing domain.

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• Published: 29 April 2024

What is context in knowledge translation? Results of a systematic scoping review

• Tugce Schmitt   ORCID: orcid.org/0000-0001-6893-6428 1 ,
• Katarzyna Czabanowska 1 &
• Peter Schröder-Bäck 1  

Health Research Policy and Systems volume  22 , Article number:  52 ( 2024 ) Cite this article

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Knowledge Translation (KT) aims to convey novel ideas to relevant stakeholders, motivating their response or action to improve people’s health. Initially, the KT literature focused on evidence-based medicine, applying findings from laboratory and clinical research to disease diagnosis and treatment. Since the early 2000s, the scope of KT has expanded to include decision-making with health policy implications.

This systematic scoping review aims to assess the evolving knowledge-to-policy concepts, that is, macro-level KT theories, models and frameworks (KT TMFs). While significant attention has been devoted to transferring knowledge to healthcare settings (i.e. implementing health policies, programmes or measures at the meso-level), the definition of 'context' in the realm of health policymaking at the macro-level remains underexplored in the KT literature. This study aims to close the gap.

A total of 32 macro-level KT TMFs were identified, with only a limited subset of them offering detailed insights into contextual factors that matter in health policymaking. Notably, the majority of these studies prompt policy changes in low- and middle-income countries and received support from international organisations, the European Union, development agencies or philanthropic entities.

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Few concepts are used by health researchers as vaguely and yet as widely as Knowledge Translation (KT), a catch-all term that accommodates a broad spectrum of ambitions. Arguably, to truly understand the role of context in KT, we first need to clarify what KT means. The World Health Organization (WHO) defines KT as ‘the synthesis, exchange and application of knowledge by relevant stakeholders to accelerate the benefits of global and local innovation in strengthening health systems and improving people’s health’ [ 1 ]. Here, particular attention should be paid to ‘innovation’, given that without unpacking this term, the meaning of KT would still remain ambiguous. Rogers’ seminal work ‘Diffusion of Innovations’ [ 2 ] defines innovation as an idea, practice or object that is perceived as novel by individuals or groups adopting it. In this context, he argues that the objective novelty of an idea in terms of the amount of time passed after its discovery holds little significance [ 2 ]. Rather, it is the subjective perception of newness by the individual that shapes their response [ 2 ]. In other words, if an idea seems novel to individuals, and thereby relevant stakeholders according to the aforementioned WHO definition, it qualifies as an innovation. From this perspective, it can be stated that a fundamental activity of KT is to communicate ideas that could be perceived as original to the targeted stakeholders, with the aim of motivating their response to improve health outcomes. This leaves us with the question of who exactly these stakeholders might be and what kind of actions would be required from them.

The scope of stakeholders in KT has evolved over time, along with their prompted responses. Initially, during the early phases of KT, the focus primarily revolved around healthcare providers and their clinical decisions, emphasising evidence-based medicine. Nearly 50 years ago, the first scientific article on KT was published, introducing Tier 1 KT, which concentrated on applying laboratory discoveries to disease diagnosis or treatment, also known as bench-to-bedside KT [ 3 ]. The primary motivation behind this initial conceptualisation of KT was to engage healthcare providers as the end-users of specific forms of knowledge, primarily related to randomised controlled trials of pharmaceuticals and evidence-based medicine [ 4 ]. In the early 2000s, the second phase of KT (Tier 2) emerged under the term ‘campus-to-clinic KT’ [ 3 ]. This facet, also known as translational research, was concerned with using evidence from health services research in healthcare provision, both in practice and policy [ 4 ]. Consequently, by including decision-makers as relevant end-users, KT scholars expanded the realm of research-to-action from the clinical environment to policy-relevant decision-making [ 5 ]. Following this trajectory, additional KT schemes (Tier 3–Tier 5) have been introduced into academic discourse, encompassing the dissemination, implementation and broader integration of knowledge into public policies [ 6 , 7 ]. Notably, the latest scheme (Tier 5) is becoming increasingly popular and represents the broadest approach, which describes the translation of knowledge to global communities and aims to involve fundamental, universal change in attitudes, policies and social systems [ 7 ].

In other words, a noticeable shift in KT has occurred with time towards macro-level interventions, named initially as evidence- based policymaking and later corrected to evidence- informed policymaking. In parallel with these significant developments, various alternative terms to KT have emerged, including ‘implementation science’, ‘knowledge transfer’, and ‘dissemination and research use’, often with considerable overlap [ 8 ]. Arguably, among the plethora of alternative terms proposed, implementation science stands out prominently. While initially centred on evidence-based medicine at the meso-level (e.g. implementing medical guidelines), it has since broadened its focus to ‘encompass all aspects of research relevant to the scientific study of methods to promote the uptake of research findings into routine settings in clinical, community and policy contexts’ [ 9 ], closely mirroring the definition to KT. Thus, KT, along with activities under different names that share the same objective, has evolved into an umbrella term over the years, encompassing a wide range of strategies aimed at enhancing the impact of research not only on clinical practice but also on public policies [ 10 ]. Following the adoption of such a comprehensive definition of KT, some researchers have asserted that using evidence in public policies is not merely commendable but essential [ 11 ].

In alignment with the evolution of KT from (bio-)medical sciences to public policies, an increasing number of scholars have offered explanations on how health policies should be developed [ 12 ], indicating a growing focus on exploring the mechanisms of health policymaking in the KT literature. However, unlike in the earlier phases of KT, which aimed to transfer knowledge from the laboratory to healthcare provision, decisions made for public policies may be less technical and more complex than those in clinical settings [ 3 , 13 , 14 ]. Indeed, social scientists point out that scholarly works on evidence use in health policies exhibit theoretical shortcomings as they lack engagement with political science and public administration theories and concepts [ 15 , 16 , 17 , 18 ]; only a few of these works employ policy theories and political concepts to guide data collection and make sense of their findings [ 19 ]. Similarly, contemporary literature that conceptualises KT as an umbrella term for both clinical and public policy decision-making, with calls for a generic ‘research-to-action’ [ 20 ], may fail to recognise the different types of actions required to change clinical practices and influence health policies. In many respects, such calls can even lead to a misconception that evidence-informed policymaking is simply a scaled-up version of evidence-based medicine [ 21 ].

In this study, we systematically review knowledge translation theories, models and frameworks (also known as KT TMFs) that were developed for health policies. Essentially, KT TMFs can be depicted as bridges that connect findings across diverse studies, as they establish a common language and standardise the measurement and assessment of desired policy changes [ 22 ]. This makes them essential for generalising implementation efforts and research findings [ 23 ]. While distinctions between a theory, a model or a framework are not always crystal-clear [ 24 ], the following definitions shed light on how they are interpreted in the context of KT. To start with, theory can be described as a set of analytical principles or statements crafted to structure our observations, enhance our understanding and explain the world [ 24 ]. Within implementation science, theories are encapsulated as either generalised models or frameworks. In other words, they are integrated into broader concepts, allowing researchers to form assumptions that help clarify phenomena and create hypotheses for testing [ 25 ].

Whereas theories in the KT literature are explanatory as well as descriptive, KT models are only descriptive with a more narrowly defined scope of explanation [ 24 ]; hence they have a more specific focus than theories [ 25 ]. KT models are created to facilitate the formulation of specific assumptions regarding a set of parameters or variables, which can subsequently be tested against outcomes using predetermined methods [ 25 ]. By offering simplified representations of complex situations, KT models can describe programme elements expected to produce desired results, or theoretical constructs believed to influence or moderate observed outcomes. In this way, they encompass theories related to change or explanation [ 22 ].

Lastly, frameworks in the KT language define a set of variables and the relations among them in a broad sense [ 25 ]. Frameworks, without the aim of providing explanations, solely describe empirical phenomena, representing a structure, overview, outline, system or plan consisting of various descriptive categories and the relations between them that are presumed to account for a phenomenon [ 24 ]. They portray loosely-structured constellations of theoretical constructs, without necessarily specifying their relationships; they can also offer practical methods for achieving implementation objectives [ 22 ]. Some scholars suggest sub-classifications and categorise a framework as ‘actionable’ if it has the potential to facilitate macro-level policy changes [ 11 ].

Context, which encompasses the entire environment in which policy decisions are made, is not peripheral but central to policymaking, playing a crucial role in its conceptualisation [ 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 ]. In the KT literature, the term ‘context’ is frequently employed, albeit often with a lack of precision [ 35 ]. It tends to serve as a broad term including various elements within a situation that are relevant to KT in some way but have not been explicitly identified [36]. However, there is a growing interest in delving deeper into what context refers to, as evidenced by increasing research attention [ 31 , 32 , 37 , 38 , 39 , 40 , 41 ]. While the definition of context in the transfer of knowledge to healthcare settings (i.e. implementing health policies, programmes or measures at the meso-level) has been systematically studied [ 36 , 37 , 42 , 43 ], the question of how KT scholars detail context in health policymaking remains unanswered. With our systematic scoping review, we aim to close this gap.

While KT TMFs, emerged from evidence-based medicine, have historically depicted the use of evidence from laboratories or healthcare organisations as the gold standard, we aimed to assess in this study whether and to what extent the evolving face of KT, addressing health policies, succeeded in foregrounding ‘context’. Our objective was thus not to evaluate the quality of these KT TMFs but rather to explore how scholars have incorporated contextual influences into their reasoning. We conducted a systematic scoping review to explore KT TMFs that are relevant to agenda-setting, policy formulation or policy adoption, in line with the aim of this study. Therefore, publications related to policy implementation in healthcare organisations or at the provincial level, as well as those addressing policy evaluation, did not meet our inclusion criteria. Consequently, given our focus on macro-level interventions, we excluded all articles that concentrate on translating clinical research into practice (meso-level interventions) and health knowledge to patients or citizens (micro-level interventions).

Prior systematic scoping reviews in the area of KT TMFs serve as a valuable foundation upon which to build further studies [ 44 , 45 ]. Using established methodologies may ensure a validated approach, allowing for a more nuanced understanding of KT TMFs in the context of existing scholarly work. Our review methodology employed a similar approach to that followed by Strifler et al. in 2018, who conducted a systematic scoping review of KT TMFs in the field of cancer prevention and management, as well as other chronic diseases [ 44 ]. Their search strategy was preferred over others for two primary reasons. First, Strifler et al. investigated KT TMFs altogether, systematically and comprehensively. Second, unlike many other review studies on KT, they focused on macro-level KT and included all relevant keywords useful for the purpose of our study in their Ovid/MEDLINE search query [ 44 ]. For our scoping review, we adapted their search query with the assistance of a specialist librarian. This process involved eliminating terms associated with cancer and chronic diseases, removing time limitation on the published papers, and including an additional language other than English due to authors’ proficiency in German. We included articles published in peer-reviewed journals until November 2022, excluding opinion papers, conference abstracts and study protocols, without any restriction on publication date or place. Our search query is presented in Table  1 .

Following a screening methodology similar to that employed by Votruba et al. [ 11 ], the first author conducted an initial screening of the titles and abstracts of 2918 unique citations. Full texts were selected and scrutinised if they appeared relevant to the topics of agenda-setting, policy formulation or policy adoption. Among these papers, the first author also identified those that conceptualised a KT TMF. Simultaneously, the last author independently screened 2918 titles and abstracts, randomly selecting 20% of them to identify studies related to macro-level KT. Regarding papers that conceptualised a KT TMF, all those initially selected by the first author underwent a thorough examination by the last author as well. In the papers reviewed by these two authors of this study, KT TMFs were typically presented as either Tables or Figures. In cases where these visual representations did not contain sufficient information about ‘context’, the main body of the study was carefully scrutinised by both reviewers to ensure no relevant information was missed. Any unclear cases were discussed and resolved to achieve 100% inter-rater agreement between the first and second reviewers. This strategy resulted in the inclusion of 32 relevant studies. The flow chart outlining our review process is provided in Fig.  1 .

Flow chart of the review process

According to the results of our systematic scoping review (Table  2 ), the first KT TMF developed for health policies dates back to 2003, confirming the emergence of a trend that expanded the meaning of the term Knowledge Translation to include policymakers as end-users of evidence during approximately the same period. In their study, Jacobson et al. [ 46 ] present a framework derived from a literature review to enhance understanding of user groups by organising existing knowledge, identifying gaps and emphasising the importance of learning about new contexts. However, despite acknowledging the significance of the user group context, the paper lacks a thorough explanation of the authors’ understanding of this term. The second study in our scoping review provides some details. Recognising a shift from evidence-based medicine to evidence-based health policymaking in the KT literature, the article by Dobrow et al. from 2004 [ 30 ] emphasises the importance of considering contextual factors. They present a conceptual framework for evidence-based decision-making, highlighting the influence of context in KT. Illustrated through examples from colorectal cancer screening policy development, their conceptual framework emphasises the significance of context in the introduction, interpretation and application of evidence. Third, Lehoux et al. [ 47 ] examine the field of Health Technology Assessment (HTA) and its role in informing decision and policymaking in Canada. By developing a conceptual framework for HTA dissemination and use, they touch on the institutional environment and briefly describe contextual factors.

Notably, the first three publications in our scoping review are authored by scholars affiliated with Canada, which is less of a coincidence, given the role of Canadian Institutes of Health Research (CIHR), the federal funding agency for health research: The CIHR Act (Bill C-13) mandates CIHR to ensure that the translation of health knowledge permeates every aspect of its work [ 48 ]. Moreover, it was CIHR that coined the term Knowledge Translation, defining KT as ‘a dynamic and iterative process that includes the synthesis, dissemination, exchange and ethically sound application of knowledge to improve health, provide more effective health services and products, and strengthen the health care system’ [ 49 ] . This comprehensive definition has since been adapted by international organisations (IOs), including WHO. The first document published by WHO that utilised KT to influence health policies dates back to 2005, entitled ‘Bridging the “know-do” gap: Meeting on knowledge translation in global health’, an initiative that was supported by the Canadian Coalition for Global Health Research, the Canadian International Development Agency, the German Agency for Technical Cooperation and the WHO Special Programme on Research and Training in Tropical Diseases [ 1 ]. Following this official recognition by WHO, studies in our scoping review after 2005 indicate a noticeable expansion of KT, encompassing a wider geographical area than Canada.

The article of Ashford et al. from 2006 [ 50 ] discusses the challenge of policy decisions in Kenya in the health field being disconnected from scientific evidence and presents a model for translating knowledge into policy actions through agenda-setting, coalition building and policy learning. However, the framework lacks explicit incorporation of contextual factors influencing health policies. Bauman et al. [ 51 ] propose a six-step framework for successful dissemination of physical activity evidence, illustrated through four case studies from three countries (Canada, USA and Brazil) and a global perspective. They interpret contextual factors as barriers and facilitators to physical activity and public health innovations. Focusing on the USA, Gold [ 52 ] explains factors, processes and actors that shape pathways between research and its use in a summary diagram, including a reference to ‘other influences in process’ for context. Green et al. [ 4 ] examine the gap between health research and its application in public health without focusing on a specific geographical area. Their study comprehensively reviews various concepts of diffusion, dissemination and implementation in public health, proposing ways to blend diffusion theory with other theories. Their ‘utilization-focused surveillance framework’ interprets context as social determinants as structures, economics, politics and culture.

Further, the article by Dhonukshe-Rutten et al. from 2010 [ 53 ] presents a general framework that outlines the process of translating nutritional requirements into policy applications from a European perspective. The framework incorporates scientific evidence, stakeholder interests and the socio-political context. The description of this socio-political context is rather brief, encompassing political and social priorities, legal context, ethical issues and economic implications. Ir et al. [ 54 ] analyse the use of knowledge in shaping policy on health equity funds in Cambodia, with the objective of understanding how KT contributes to the development of health policies that promote equity. Yet no information on context is available in the framework that they suggest. A notable exception among these early KT TMFs until 2010 is the conceptual framework for analysing integration of targeted health interventions into health systems by Atun et al. [ 55 ], in which the authors provide details about the factors that have an influence on the process of bringing evidence to health policies. Focusing on the adoption, diffusion and assimilation of health interventions, their conceptual framework provides a systematic approach for evaluating and informing policies in this field. Compared to the previous studies discussed above, their definition of context for this framework is comprehensive (Table  2 ). Overall, most of the studies containing macro-level KT TMFs published until 2010 either do not fully acknowledge contextual factors or provide generic terms such as cultural, political and economic for brief description (9 out of 10; 90%).

Studies published after 2010 demonstrate a notable geographical shift, with a greater emphasis on low- and middle-income countries (LMICs). By taking the adoption of the directly observed treatment, short-course (DOTS) strategy for tuberculosis control in Mexico as a case study, Bissell et al. [ 56 ] examine policy transfer to Mexico and its relevance to operational research efforts and suggest a model for analysis of health policy transfer. The model interprets context as health system, including political, economic, social, cultural and technological features. Focusing on HIV/AIDS in India, Tran et al. [ 57 ] explore KT by considering various forms of evidence beyond scientific evidence, such as best practices derived from programme experience and disseminated through personal communication. Their proposed framework aims to offer an analytical tool for understanding how evidence-based influence is exerted. In their framework, no information is available on context. Next, Bertone et al. [ 58 ] report on the effectiveness of Communities of Practice (CoPs) in African countries and present a conceptual framework for analysing and assessing transnational CoPs in health policy. The framework organises the key elements of CoPs, linking available resources, knowledge management activities, policy and practice changes, and improvements in health outcomes. Context is only briefly included in this framework.

Some other studies include both European and global perspectives. The publication from Timotijevic et al. from 2013 [ 59 ] introduces an epistemological framework that examines the considerations influencing the policy-making process, with a specific focus on micronutrient requirements in Europe. They present case studies from several European countries, highlighting the relevance of the framework in understanding the policy context related to micronutrients. Context is interpreted in this framework as global trends, data, media, broader consumer beliefs, ethical considerations, and wider social, legal, political, and economic environment. Next, funded by the European Union, the study by Onwujekwe et al. [ 60 ] examines the role of different types of evidence in health policy development in Nigeria. Although they cover the factors related to policy actors in their framework for assessing the role of evidence in policy development, they provide no information on context. Moreover, Redman et al. [ 61 ] present the SPIRIT Action Framework, which aims to enhance the use of research in policymaking. Context is interpreted in this framework as policy influences, i.e. public opinion, media, economic climate, legislative/policy infrastructure, political ideology and priorities, stakeholder interests, expert advice, and resources. From a global perspective, Spicer et al. [ 62 ] explore the contextual factors that influenced the scale-up of donor-funded maternal and newborn health innovations in Ethiopia, India and Nigeria, highlighting the importance of context in assessing and adapting innovations. Their suggested contextual factors influencing government decisions to accept, adopt and finance innovations at scale are relatively comprehensive (Table  2 ).

In terms of publication frequency, the pinnacle of reviewed KT studies was in 2017. Among six studies published in 2017, four lack details about context in their KT conceptualisations and one study touches on context very briefly. Bragge et al. [ 5 ] brought for their study an international terminology working group together to develop a simplified framework of interventions to integrate evidence into health practices, systems, and policies, named as the Aims, Ingredients, Mechanism, Delivery framework, albeit without providing details on contextual factors. Second, Mulvale et al. [ 63 ] present a conceptual framework that explores the impact of policy dialogues on policy development, illustrating how these dialogues can influence different stages of the policy cycle. Similar to the previous one, this study too, lacks information on context. In a systematic review, Sarkies et al. [ 64 ] evaluate the effectiveness of research implementation strategies in promoting evidence-informed policy decisions in healthcare. The study explores the factors associated with effective strategies and their inter-relationship, yet without further information on context. Fourth, Houngbo et al. [ 65 ] focus on the development of a strategy to implement a good governance model for health technology management in the public health sector, drawing from their experience in Benin. They outline a six-phase model that includes preparatory analysis, stakeholder identification and problem analysis, shared analysis and visioning, development of policy instruments for pilot testing, policy development and validation, and policy implementation and evaluation. They provide no information about context in their model. Fifth, Mwendera et al. [ 66 ] present a framework for improving the use of malaria research in policy development in Malawi, which was developed based on case studies exploring the policymaking process, the use of local malaria research, and assessing facilitators and barriers to research utilisation. Contextual setting is considered as Ministry of Health (MoH) with political set up, leadership system within the MoH, government policies and cultural set up. In contrast to these five studies, Ellen et al. [ 67 ] present a relatively comprehensive framework to support evidence-informed policymaking in ageing and health. The framework includes thought-provoking questions to discover contextual factors (Table  2 ).

Continuing the trend, studies published after 2017 focus increasingly on LMICs. In their embedded case study, Ongolo-Zogo et al. [ 68 ] examine the influence of two Knowledge Translation Platforms (KTPs) on policy decisions to achieve the health millennium development goals in Cameroon and Uganda. It explores how these KTPs influenced policy through interactions within policy issue networks, engagement with interest groups, and the promotion of evidence-supported ideas, ultimately shaping the overall policy climate for evidence-informed health system policymaking. Contextual factors are thereby interpreted as institutions (structures, legacies, policy networks), interests, ideas (values, research evidence) and external factors (reports, commitments). Focusing on the ‘Global South’, Plamondon et al. [ 69 ] suggest blending integrated knowledge translation with global health governance as an approach for strengthening leadership for health equity action. In terms of contextual factors, they include some information such as adapting knowledge to local context, consideration of the composition of non-traditional actors, such as civil society and private sector, in governance bodies and guidance for meaningful engagement between actors, particularly in shared governance models. Further, Vincenten et al. [ 70 ] propose a conceptual model to enhance understanding of interlinking factors that influence the evidence implementation process. Their evidence implementation model for public health systems refers to ‘context setting’, albeit without providing further detail.

Similarly, the study by Motani et al. from 2019 [ 71 ] assesses the outcomes and lessons learned from the EVIDENT partnership that focused on knowledge management for evidence-informed decision-making in nutrition and health in Africa. Although they mention ‘contextualising evidence’ in their conceptual framework, information about context is lacking. Focusing on Latin America and the Caribbean, Varallyay et al. [ 72 ] introduce a conceptual framework for evaluating embedded implementation research in various contexts. The framework outlines key stages of evidence-informed decision-making and provides guidance on assessing embeddedness and critical contextual factors. Compared to others, their conceptual framework provides a relatively comprehensive elaboration on contextual factors. In addition, among all the studies reviewed, Leonard et al. [ 73 ] present an exceptionally comprehensive analysis, where they identify the facilitators and barriers to the sustainable implementation of evidence-based health innovations in LMICs. Through a systematic literature review, they scrutinise 79 studies and categorise the identified barriers and facilitators into seven groups: context, innovation, relations and networks, institutions, knowledge, actors, and resources. The first one, context, contains rich information that could be seen in Table  2 .

Continuing from LMICs, Votruba et al. [ 74 ] present in their study the EVITA (EVIdence To Agenda setting) conceptual framework for mental health research-policy interrelationships in LMICs with some information about context, detailed as external influences and political context. In a follow-up study, they offer an updated framework for understanding evidence-based mental health policy agenda-setting [ 75 ]. In their revised framework, context is interpreted as external context and policy sphere, encompassing policy agenda, window of opportunity, political will and key individuals. Lastly, to develop a comprehensive monitoring and evaluation framework for evidence-to-policy networks, Kuchenmüller et al. [ 76 ] present the EVIPNet Europe Theory of Change and interpret contextual factors for evidence-informed policymaking as political, economic, logistic and administrative. Overall, it can be concluded that studies presenting macro-level KT TMFs from 2011 until 2022 focus mainly on LMICs (15 out of 22; close to 70%) and the majority of them were funded by international (development) organisations, the European Commission and global health donor agencies. An overwhelming number of studies among them (19 out of 22; close to 90%) provide either no information on contextual details or these were included only partly with some generic terms in KT TMFs.

Our systematic scoping review suggests that the approach of KT, which has evolved from evidence-based medicine to evidence-informed policymaking, tends to remain closely tied to its clinical origins when developing TMFs. In other words, macro-level KT TMFs place greater emphasis on the (public) health issue at hand rather than considering the broader decision-making context, a viewpoint shared by other scholars as well [ 30 ]. One reason could be that in the early stages of KT TMFs, the emphasis primarily focused on implementing evidence-based practices within clinical settings. At that time, the spotlight was mostly on content, including aspects like clinical studies, checklists and guidelines serving as the evidence base. In those meso-level KT TMFs, a detailed description of context, i.e. the overall environment in which these practices should be implemented, might have been deemed less necessary, given that healthcare organisations, such as hospitals to implement medical guidelines or surgical safety checklists, show similar characteristics globally.

However, as the scope of KT TMFs continues to expand to include the influence on health policies, a deeper understanding of context-specific factors within different jurisdictions and the dynamics of the policy process is becoming increasingly crucial. This is even more important for KT scholars aiming to conceptualise large-scale changes, as described in KT Tier 5, which necessitate a thorough understanding of targeted behaviours within societies. As the complexity of interventions increases due to the growing number of stakeholders either affecting or being affected by them, the interventions are surrounded by a more intricate web of attitudes, incentives, relationships, rules of engagement and spheres of influence [ 7 ]. The persisting emphasis on content over context in the evolving field of KT may oversimplify the complex process of using evidence in policymaking and understanding the society [ 77 ]. Some scholars argue that this common observation in public health can be attributed to the dominance of experts primarily from medical sciences [ 78 , 79 , 80 ]. Our study confirms the potential limitation of not incorporating insights from political science and public policy studies, which can lead to what is often termed a ‘naïve’ conceptualisation of evidence-to-policy schemes [ 15 , 16 , 17 ]. It is therefore strongly encouraged that the emerging macro-level KT concepts draw on political science and public administration if KT scholars intend to effectively communicate new ideas to policymakers, with the aim of prompting their action or response. We summarised our findings into three points.

Firstly, KT scholars may want to identify and pinpoint exactly where a change should occur within the policy process. The main confusion that we observed in the KT literature arises from a lack of understanding of how public policies are made. Notably, the term ‘evidence-informed policymaking’ can refer to any stage of the policy cycle, spanning from agenda-setting to policy formulation, adoption, implementation and evaluation. Understanding these steps will allow researchers to refine their language when advocating for policy changes across various jurisdictions; for instance, the word ‘implementation’ is often inappropriately used in KT literature. As commonly known, at the macro-level, public policies take the form of legislation, law-making and regulation, thereby shaping the practices or policies to be implemented at the meso- and micro-levels [ 81 ]. In other words, the process of using specific knowledge to influence health policies, however evidence-based it might be, falls mostly under the responsibility and jurisdiction of sovereign states. For this reason, macro-level KT TMFs should reflect the importance of understanding the policy context and the complexities associated with policymaking, rather than suggesting flawed or unrealistic top-down ‘implementation’ strategies in countries by foregrounding the content, or the (public) health issue at hand.

Our second observation from this systematic scoping review points towards a selective perception among researchers when reporting on policy interventions. Research on KT does not solely exist due to the perceived gap between scientific evidence and policy but also because of the pressures the organisations or researchers face in being accountable to their funding sources, ensuring the continuity of financial support for their activities and claiming output legitimacy to change public policies [ 8 ]. This situation indirectly compels researchers working to influence health policies in the field to provide ‘evidence-based’ feedback on the success of their projects to donors [ 82 ]. In doing so, researchers may overly emphasise the content of the policy intervention in their reporting to secure further funding, while they underemphasis the contextual factors. These factors, often perceived as a given, might actually be the primary facilitators of their success. Such a lack of transparency regarding the definition of context is particularly visible in the field of global health, where LMICs often rely on external donors. It is important to note that this statement is not intended as a negative critique of their missions or an evaluation of health outcomes in countries following such missions. Rather, it seeks to explain the underlying reason why researchers, particularly those reliant on donors in LMICs, prioritise promoting the concept of KT from a technical standpoint, giving less attention to contextual factors in their reasoning.

Lastly, and connected to the previous point, it is our observation that the majority of macro-level KT TMFs fail to give adequate consideration to both power dynamics in countries (internal vs. external influences) and the actual role that government plays in public policies. Notably, although good policymaking entails an honest effort to use the best available evidence, the belief that this will completely negate the role of power and politics in decision-making is a technocratic illusion [ 83 ]. Among the studies reviewed, the framework put forth by Leonard et al. [ 73 ] offers the most comprehensive understanding of context and includes a broad range of factors (such as political, social, and economic) discovered also in other reviewed studies. Moreover, the framework, developed through an extensive systematic review, offers a more in-depth exploration of these contextual factors than merely listing them as a set of keywords. Indeed, within the domains of political science and public policy, such factors shaping health policies have received considerable scholarly attention for decades. To define what context entails, Walt refers in her book ‘Health Policy: An Introduction to Process and Power’ [ 84 ] to the work of Leichter from 1979 [ 85 ], who provides a scheme for analysing public policy. This includes i) situational factors, which are transient, impermanent, or idiosyncratic; ii) structural factors, which are relatively unchanging elements of the society and polity; iii) cultural factors, which are value commitments of groups; and iv) environmental factors, which are events, structures and values that exist outside the boundaries of a political system and influence decisions within it. His detailed sub-categories for context can be found in Table  3 . This flexible public policy framework may offer KT researchers a valuable approach to understanding contextual factors and provide some guidance to define the keywords to focus on. Scholars can adapt this framework to suit a wide range of KT topics, creating more context-sensitive and comprehensive KT TMFs.

Admittedly, our study has certain limitations. Despite choosing one of the most comprehensive bibliographic databases for our systematic scoping review, which includes materials from biomedicine, allied health fields, biological and physical sciences, humanities, and information science in relation to medicine and healthcare, we acknowledge that we may have missed relevant articles indexed in other databases. Hence, exclusively using Ovid/MEDLINE due to resource constraints may have narrowed the scope and diversity of scholarly literature examined in this study. Second, our review was limited to peer-reviewed publications in English and German. Future studies could extend our findings by examining the extent to which contextual factors are detailed in macro-level KT TMFs published in grey literature and in different languages. Given the abundance of KT reports, working papers or policy briefs published by IOs and development agencies, such an endeavour could enrich our findings and either support or challenge our conclusions. Nonetheless, to our knowledge, this study represents the first systematic review and critical appraisal of emerging knowledge-to-policy concepts, also known as macro-level KT TMFs. It successfully blends insights from both biomedical and public policy disciplines, and could serve as a roadmap for future research.

The translation of knowledge to policymakers involves more than technical skills commonly associated with (bio-)medical sciences, such as creating evidence-based guidelines or clinical checklists. Instead, evidence-informed policymaking reflects an ambition to engage in the political dimensions of states. Therefore, the evolving KT concepts addressing health policies should be seen as a political decision-making process, rather than a purely analytical one, as is the case with evidence-based medicine. To better understand the influence of power dynamics and governance structures in policymaking, we suggest that future macro-level KT TMFs draw on insights from political science and public administration. Collaborative, interdisciplinary research initiatives could be undertaken to bridge the gap between these fields. Technocratic KT TMFs that overlook contextual factors risk propagating misconceptions in academic circles about how health policies are made, as they become increasingly influential over time. Research, the systematic pursuit of knowledge, is neither inherently good nor bad; it can be sought after, used or misused, like any other tool in policymaking. What is needed in the KT discourse is not another generic call for ‘research-to-action’ but rather an understanding of the dividing line between research-to- clinical -action and research-to- political -action.

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Schmitt, T., Czabanowska, K. & Schröder-Bäck, P. What is context in knowledge translation? Results of a systematic scoping review. Health Res Policy Sys 22 , 52 (2024). https://doi.org/10.1186/s12961-024-01143-5

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A review of machine learning methods used for educational data

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• Zara Ersozlu   ORCID: orcid.org/0000-0002-9120-2921 1 ,
• Sona Taheri   ORCID: orcid.org/0000-0003-1779-4567 2 &
• Inge Koch   ORCID: orcid.org/0000-0001-8259-6204 2  

Integrating machine learning (ML) methods in educational research has the potential to greatly impact upon research, teaching, learning and assessment by enabling personalised learning, adaptive assessment and providing insights into student performance, progress and learning patterns. To reveal more about this notion, we investigated ML approaches used for educational data analysis in the last decade and provided recommendations for further research. Using a systematic literature review (SLR), we examined 77 publications from two large and high-impact databases for educational research using bibliometric mapping and evaluative review analysis. Our results suggest that the top five most frequently used keywords were similar in both databases. The majority of the publications (88%) utilised supervised ML approaches for predicting students’ performances and finding learning patterns. These methods include decision trees, support vector machines, random forests, and logistic regression. Semi-supervised learning methods were less frequently used, but also demonstrated promising results in predicting students’ performance. Finally, we discuss the implications of these results for statisticians, researchers, and policymakers in education.

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1 Introduction

Machine Learning (ML) methods have transformed the way we interact with data and have increased the potential of recognising patterns and making sense of large volumes of data. The application of ML in education is growing and has the potential to revolutionize both teaching and learning. ML methods mostly used by researchers with the purpose of predicting student’s performance, analysing learning preferences and teaching effectiveness. These will not only help educators to create more effective and individualised learning opportunities for their students but also will enable educational statisticians and researchers to draw highly accurate results from educational data using ML (Hilbert et al., 2021 ).

ML techniques have the capacity to evaluate and learn from large volumes of data, which makes it a desirable tool for educational data. Because ML can be used to tailor instruction, evaluate learning practices, and detect patterns and trends in student learning and performance (Baker & Siemens, 2014 ; Kovanovic et al., 2015 ). The capacity of ML methods to learn from deep, non-linear correlations in data gives it advantage over traditional statistical methods (Hilbert et al., 2021 ). In the prediction of student performance, ML can provide better accuracy when comparing the methods of traditional statistical methods. This is because ML methods have consistently outperformed traditional methods on training data, achieving higher levels of accuracy, and generalising better across diverse datasets (Japkowicz & Shah, 2011 ; Kotsiantis et al., 2004 ).

The literature on using ML for educational data is spread across different aspects of education (e.g., students, teachers Levy et al., 2020 ); all schooling levels (e.g., K-12 Tedre et al., 2021 ); higher education (Vartiainen et al., 2022 ; Križanić, 2020 ); predicting student outcomes/performance (Khan & Ghosh, 2021 ; Hashim et al., 2020 ); learning analytics (e.g., both learning and dispositional learning analytics Buckingham Shum, & Ferguson, 2012 ; Gasevic et al., 2016 ; Tempelaar et al., 2021 ); early warning systems (e.g., at risk students, dropouts Pecuchová & Drlik, 2021 ); marking automatisation (Shermis & Burstein, 2013 ); language proficiency (Crossley et al., 2011 ) and social network analysis (Romero & Ventura, 2013 ).

There are also several review studies that indirectly focus on limited aspects of ML for educational data in a given timeline. Alonso-Fernández et al. ( 2019 ) have investigated game learning analytics using literature review; Bachhal et al. ( 2021 ) have discussed the most important studies conducted until 2021 in educational data mining in general; Yunita et al. ( 2021 ) has reviewed the relevant literature on big data in education; Khan and Ghosh ( 2021 ) have examined the educational data mining publications from the perspective of student performance analysis and prediction in classroom learning; Salloum et al. ( 2020 ) have analysed the literature to find out how data mining was handled by researchers in the past and the most recent trends on data mining in educational research between 2016 and 2019; Albreiki et al. ( 2021 ) have reviewed the literature on student’ performance prediction using ML techniques where they focused identifying student dropouts and students at risk in literature between 2009 and 2021; Du et al. ( 2020 ) have examined 33 publications between 2007 and the first quarter of 2019 to analyse educational data mining research trends where they analysed research topics, methods and sample; Khalaf et al. ( 2021 ) have anlaysed the literature on using only supervised ML in the period of 2010–2020; Peña-Ayala ( 2014 ) has reviewed the literature on educational data mining between 2010 and first quarter of 2013.

While the existing body of research on ML applications in educational data offers valuable insights, a closer examination reveals notable research gaps and areas where a comprehensive understanding is still elusive. In terms of the fragmentation, the majority of review studies in this area adopt a temporal scope, focusing on specific timeframes. For instance, Alonso-Fernández et al. ( 2019 ) explored game learning analytics, Bachhal et al. ( 2021 ) covered studies up to 2021, and Salloum et al. ( 2020 ) analyzed trends between 2016 and 2019. These fragmented timelines create a gap in understanding the evolution and continuity of ML applications in educational data over an extended period. From the aspect of dimensional specificity, many reviews concentrate on singular dimensions of ML applications. Yunita et al. ( 2021 ) delved into big data in education, Khan and Ghosh ( 2021 ) focused on student performance analysis, and Albreiki et al. ( 2021 ) focused on student dropouts and at-risk students. This classified approach leads to a lack of synthesis across various dimensions, leaving unexplored intersections and potential synergies. In terms of methodological variety, some reviews show limited diversity in their methodologies. While some, like Du et al. ( 2020 ), delve into specific publications, others, such as Khalaf et al. ( 2021 ), narrow their focus to supervised ML. This highlights a need for a borader approach that comprehensively synthesises the methodologies employed in existing research. Lastly, existing reviews often fall short in providing a holistic integration of ML methods tailored for educational data. While Peña-Ayala ( 2014 ) reviewed educational data mining up to the first quarter of 2013, there’s a gap in synthesizing these methods comprehensively, considering advancements and changes in the landscape since then.

Addressing these research gaps is important for advancing and establishing a robust foundation for future studies in the nuanced intersection of ML applications and educational data. Our research endeavours to bridge these gaps by offering a unified, comprehensive, and contemporary analysis, thus contributing to a more holistic understanding of the subject.

Therefore, our research aims to address this limitation by conducting a thorough and comprehensive review that covers all relevant dimensions of ML methods specifically for educational data. Thus, it is imperative to provide a more comprehensive analysis of literature resources across two main databases for (Web of Science and EBSCOhost) education research using existing publications over the last decade. In this paper, we aim to investigate the existing research literature to reveal the type and range of ML approaches that have been used to analyse educational data sets. In this sense, this research is unique in terms of the aim and the practical interpretation of our findings for all educators from all schooling years and education researchers and statisticians from all backgrounds. More specifically, we aim to cover and respond to the following research questions:

What are the frequently used keywords and publication trends in research publications using ML to analyse educational data?

How can we categorise the machine learning methods utilised in research publications over the last decade, focusing on their application domains and algorithmic techniques?

2 Machine learning

ML is a branch of statistics and artificial intelligence (AI) that focuses on statistical methods to learn from data and build new statistical models and algorithms to understand, make sense of and analyse data in detail without the need for explicit programming. ML encompasses a diverse range of perspectives based on its primary applications. It can be defined as “the field of study that gives computers the ability to learn without being explicitly programmed” (Mitchell, 1997 ), “the process by which computers can identify patterns in data and improve their ability to recognize and predict these patterns over time” (Baker & Siemens, 2014 ), “a branch of artificial intelligence that systematically applies algorithms to synthesize the underlying relationships among data and information” (Awad & Khanna, 2015 ), and “programming computers to optimize a performance criterion using example data or past experience” (Alpaydin, 2010 , p.3). Additionally, it is worth noting that ML, which was once synonymous with statistical learning until about 2015, is primarily focused on the prediction of outputs from given inputs (Hastie et al., Ch. 9, 2009 ; Koch, Ch. 4, 2013 ).

There are many other definitions of ML proposed by various researchers from different discipline backgrounds. Based on these definitions, we can infer that ML, is a branch of artificial intelligence, that employs statistical algorithms to enable computers to learn from data and iteratively improve their performance in recognising patterns and making predictions without the need for explicit programming.

It involves the systematic study and application of statistical models to analyse and synthesise the underlying patterns and connections present in data, empowering machines to make data-driven decisions and adapt to new information over time. ML utilises a range of algorithms to reveal and analyse data sets. There is no perfect algorithm that can solve every problem, each problem’s complexity and nature dictate the most suitable approach for its solution. The selection of appropriate methods depends on several factors, including the problem’s specific characteristics, the number of variables involved, the optimal model form and other relevant considerations (Mahesh, 2021 ). ML methods typically are divided into three categories:

Supervised learning

In supervised learning, the algorithm is trained on labelled data in which the input characteristics are accompanied by matching output labels. The main goal is to learn a function that converts input to output (Alpaydin, 2010 , Ch. 2; Hastie et al., 2009 , Ch. 9). Classification (K-Nearest Neighbour (KNN), Naïve Bayes Classifier, Support Vector Machine (SVM), Logistic Regression, Linear Regression, Decision Trees, Random Forests (they are both classification and regression), Sentiment analysis etc. are mostly used in supervised learning algorithms.

Unsupervised learning

In unsupervised learning, the algorithm is provided with unlabelled data, where the input features do not have matching labels on the output. Without any prior knowledge about the output, the goal is to discover patterns and structure in the data (Bishop, 2006 ; Goodfellow et al., 2016 ). Autoencoders, principal component analysis (PCA), dimension reduction and clustering (K-means), are a few examples of unsupervised learning techniques.

Semi-supervised learning

Semi-supervised learning is a combination of supervised and unsupervised learning -labelled and unlabelled data (Zhu, 2008 ). Semi-supervised learning techniques are especially useful in situations with a shortage of labelled data to improve the reliability of results (van Engelen, & Hoos, 2020 ).

Reinforcement learning

In reinforcement learning, an algorithm learns decision-making skills by interacting with its environment. The goal is to learn a principle that optimises a reward signal. Reinforcement learning is widely used in robotics, gaming, and control systems such as an artificial neural network (Sutton & Barto, 2018 ; Kaelbling et al., 1996 ).

ML algorithms can be further classified into several categories or variants, including deep learning. ML employs thoroughly researched and developed statistical models and algorithms to enable computer systems to iteratively refine their performance on specific tasks over time. In educational settings, these statistical approaches find application in analysing extensive and complicated data sets, revealing essential insights into students’ learning patterns and preferences. As a result, ML facilitates the tailoring the learning experiences, offering personalised learning paths that align with individual requirements and consequently, optimising the educational journey for each student.

2.1 Use of ML in educational research

Studies exploring the potential uses of ML in areas such as predicting student outcomes, identifying students at risk, and customising learning experiences have all grown in recent years, with increasing interest in the use of ML in the analysis of educational data. Based on our review study, we classified the use of ML algorithms in educational research as follows:

Predicting student outcomes is one of the most exciting uses of ML methods in the examination of educational data. Researchers have employed ML methods to predict student dropout rates (Romero et al, 2008 : Latham et al., 2014 ). Particularly, ML algorithms have demonstrated higher predictive accuracy compared to traditional approaches, highlighting the potential of ML in enhancing student performance (Hilbert et al., 2021 ).

Identifying at-risk students represents another area where ML has shown promise in analysing training data. As demonstrated in a study conducted by Hsu & Yeh, 2020 , Rawat et al, 2021 , Zhang et al, 2021 and Xing & Du 2018 ), ML algorithms can be used to find non-linear connections between student performance and social, as well as academic variables. The study further highlights that utilising these insights can lead to the development of more effective interventions and activities tailored to support at-risk students’ success.

Learning analytics can assists teachers to understand students’ learning patterns and identify areas requiring additional support. By employing ML algorithms, trends and patterns emerge, thus enhancing teaching and learning methods and ultimately improving student learning outcomes. Within learning analytics, student behaviour and performance can be analysed to detail student’s learning needs and gaps to inform teaching and assessment practices. Moreover, learning analytics encompasses dispositional learning analytics, which aims to reveal students’ self-regulated learning strategies as well as their perceptions and preferences regarding specific aspects of their learning process (Buckingham Shum, & Ferguson, 2012 ; Gasevic et al., 2016 ). This comprehensive approach allows educators to gain a deeper understanding of student’s individual learning journeys, leading to more effective and personalised support to foster improved learning experiences.

Natural Language Processing (NLP) , as a component of ML, offers a powerful tool to analyse students’ writing and extract insights about their cognitive processes, learning methods and language proficiency. Using NLP, educators can assess students’ writing and provide personalised feedback to enhance their writing skills and academic achievement (Crossley et al., 2011 ). With the capacity to evaluate students’ essays without human involvement, automated essay scoring through NLP yields trustworthy and consistent results, enabling teachers to offer targeted feedback and effectively boost students’ writing abilities (Shermis & Burstein, 2013 ).

Adaptive learning systems are ML-based learning technologies customised to meet the specific requirements of each individual learner. By assessing student performance and dynamically adjusting the difficulty level and content of learning materials, these systems have the potential to enhance student engagement and improve learning outcomes significantly. Studies have shown that the implementation of adaptive learning systems can significantly improve students’ learning outcomes (Wang et al., 2017 ).

Social network analysis , as an ML approach, examines the connections between individuals within a social network, offering insights into their interactions and learning patterns in the context of education. With the identification of social connections and patterns among students, this method enables educators to pinpoint student groups that may require further assistance and targeted interventions (Romero & Ventura, 2013 ). This powerful method provides a comprehensive understanding of the dynamics of social interactions, facilitating more effective support and guidance within educational settings.

Furthermore, ML can be effectively utilised to visualise educational data, providing insights into student performance, and learning outcomes. Statisticians can employ data visualisation techniques such as heatmaps, scatterplots, and network graphs to detect patterns and trends in student data that might not be apparent through traditional statistical analysis methods. These data visualisation tools offer researchers and statisticians the capability to uncover student activities and interactions that could significantly influence learning outcomes. By employing ML-powered visualisations, researchers and statisticians can provide educators with a deeper understanding of their student progress and interactions, facilitating informed decisions to enhance the overall learning experiences of students.

3 Methodology and analysis

We utilised a systematic review of research literature using both evaluative review and research mapping analysis (McBurney & Novak, 2002 ). An evaluative systematic review analysis was conducted using the Voytant tool, the term co-occurrence map on text data and descriptive visualisations using Excel. Web of Science and EBSCOhost (by limiting to “ERIC, Education Source, Academic Research Complete”) databases were analysed for research publications (only articles) published between 2014 and 2022. We aimed to gain empirical insights by emphasizing original research findings and data-driven studies. Excluding 2023 publications is a strategic decision to ensure a focus on empirical papers where we present first-hand research results rather than synthesizing existing knowledge as seen in review articles. It was also due to the early start of our paper writing process in 2023, we have decided not to include papers published in 2023 due to their minimal presence and limited relevance to our research. This decision was made collectively in view of the need to set a cut-off point due to the timing constraints of our paper preparation.

Web of Science is recognised for its broad interdisciplinary scope, covering a wide range of academic fields. Web of Science was chosen because it is more beneficial for our research because it is more comprehensive and diverse academic publications, making it suitable for interdisciplinary studies and research that draws insights from multiple fields. Besides, citation analysis tools provided by Web of Science enable researchers a comprehensive understanding of the scientific impact of research papers. EBSCOhost encompasses various databases and indicates a strategic focus beyond education-specific literature. This decision is driven by the need for a broader exploration of topics, potentially incorporating insights from related disciplines into education.

The keywords: “machine learning”, “education”, “educational”, “educational data”, and “machine learning algorithms” were used. Using the keywords “machine learning” together or separately as “machine” and “learning” did not make a difference in terms of publication results. The same publication results were obtained in both ways.

The language of the publications was limited to only English. We included the term “machine learning” because it enabled us a broad search of publications directly related to the overarching theme of machine learning techniques in educational data. Then, we used the derivatives such as “education” and “educational” allowed for a comprehensive review of research in the field of education, ensuring that the search was not narrowly restricted to a specific aspect of education. We added the keyword “machine learning algorithms”, which allowed us to go beyond general discussions to look for publications that specifically find technical aspects of machine learning in education. Once all authors had agreed on keywords and article types, the first author conducted the searches on the timeline and created the datasets.

We conducted searches on two major databases Web of Science and EBSCOhost which have high impact factors and widely read journals. After initial search we applied inclusion and exclusion criteria for each database search (as detailed in Fig.  1 ). The PRISMA flowchart following the suggestion of systematic review guideline by Page et al. ( 2021 ) to provide more insights into our methodological framework for this research.

PRISMA flowchart for this study’s methodology

On EBSCOhost, our search resulted in 320 papers initially, then we used the keyword “ML algorithms” to narrow the papers to the ones only using ML techniques specifically and this search resulted in 62 publications (48 articles, 2 conference materials and 12 reports) in total. After removing duplicates and unrelated and no empirical research articles, we only focused on the scientific articles in this study, therefore 27 research articles in total were included in the analysis from EBSCOhost databases in total.

On Web of Science, the first search yielded 560 research articles initially. We limited the articles to the area of education and education research 77 articles were found. After using the keyword “ML algorithms” our search resulted in 62 articles, we checked if all papers were related to education, and if they used empirical research articles. We removed the irrelevant papers, non-empirical research and the duplicates removed those from the file which reduced the number of articles to 50. Consequently, we ended up 77 as a collective result from both databases. We used the Voyant tool for mapping the keywords whereas we utilised excel for evaluative review analysis. We classified and coded the papers based on their application domains, methodologies and statistical techniques used.

In this part, each research question is responded to by using evaluative analysis of the literature review of ML in the education field. The results below are specified based on the research questions.

4.1 What are the frequently used keywords and publication trends in research publications using ML to analyse educational data?

To address the first question, we mapped the keywords analysis using Voyant tool and descriptive visualisations using Excel to summarise the range of the articles based on their year of publication and publication databases to reveal publication trends. The word “learning” was the most frequent word in both corpuses, indicating that the word learning is quite commonly used for ML analytics in both databases (Fig.  2 ). Similarly, the word “machine” was among the top five most frequently used words in both databases, indicating that ML is popular for educational data mining in both databases.

Most frequent words in the corpus combined from two databases

The words “students”, “predicting” and “performance” followed the words “learning” and “machine” in the top five most frequent words. This could suggest that research publications in both databases have focused on predicting student performance of students.

[Most frequent words were in the corpus for Web of Science database: learning (67); machine (37); students (27); predicting (25); performance (22).

Based on Fig.  3 , between the year range from 2014 to 2022, majority of the papers were published between 2021 and 2022 in both databases. The increase in publications starting from 2019 can suggest a growing interest to using ML algorithms in education research. In both databases, the concentration of publications between 2018 and 2022 is noteworthy and indicates that the number of publications using ML analytics is developing rapidly (Fig.  3 ). Furthermore, the years 2020 and 2021 seem to be particularly popular for publications, with a high number of publications are in these years.

Combined publication trends from both databases

The earliest publication date was 2014. This suggests that the interest in using ML for educational data may be relatively new. It can also indicate that both databases may only have started collecting publications on this topic in 2014.

4.2 How can we categorise the machine learning methods utilised in research publications over the last decade, focusing on their application domains and algorithmic techniques?

Based on our analysis of papers, we created two associated themes based on used ML algorithms and the application domains using these algorithms. Excel was used to analyse and visualise the data and results. As we analysed articles around the themes we determined, we used triangulation technique to compare ML algorithms to interpret most common themes for both application domains and specific ML algorithms used for educational data analytics. To ensure the coding reliability, another data scientist independently coded 77 articles based on the application domains of ML analysis and the actual ML analysis used. 94.9% agreement established after comparing two coding schemes which exceeds the suggested 80% reliability criteria by Miles et al. ( 2014 ). Based on the agreed description for codes below, we analysed the data further using excel visualisation techniques such as charts, graphs, and pivot tables (Tables 1 and 2 ).

We used a coding style that described type of the ML methods. For example: SMLA (Supervised ML algorithm), SSMLA (semi-supervised ML algorithm), RMLA (Reinforcement ML algorithm) and USMLA (Unsupervised ML algorithm). We combined our analysis from both databases to see the most frequently used ML algorithms and their application domain for educational data. Below pie charts visualise these results. 25% of the combined publications were aiming to predict student performance (PT1), 17.6% of them were aiming to predict student dropouts while 23.56% of the publications was focusing on learning analytics and finally 1.52% of them were targeted to measure teaching quality (Fig.  4 ).

Application domains used in ML research in education

In terms of the type of ML used in publications (Fig.  5 ), large proportionate of publications (88% in total) used supervised learning algorithms (linear regression: 3.1%; gradient boosting: 2.7%; random forest: 16.7%; Sentiment mining and language processing: 1.8%; Support vector machine: 14.2%; Decision tree: 19.6%; Logistic regression: 11.6%; K-nearest neighbours: 3.1%; Naïve Bayes: 4%; NNge classification: 2.2.%; quadratic discriminant analysis: 0.9%; multikernel learning: 0.4%; feature selection: 7.6%).

Type of ML Methods used in ML research in education

Reinforcement learning was employed in 9.8% of the remaining 12% of the papers through neural network analytic approaches. Only 2.2% of the publications used unsupervised or semi-supervised learning algorithms through principal component analysis and some combinations of supervised unsupervised learning algorithms. The pivot tables we created that mapped out the ML methods per publications across years of publications (see the supplementary document for more detail).

We presented the results of both databases on these tables to provide clearer picture of dispersal of publications across ML methods and their main domain of use.

Tables  3 and 4 show the results of our review of research studies investigating the use of ML methods to predict various aspects of student academic performance and learning behaviours, including academic grades and performance level, student dropout, teaching quality assessment and learning analytics. The studies were conducted between 2014 and 2022 and represent a range of educational levels, from secondary education to higher education.

These tables indicated that the number of studies using ML methods has increased steadily over the past few years, with 1 study published in 2014, and a total of 76 studies published between 2017 and 2022. The results of the studies suggested that ML methods can be effective tools for predicting student academic performance, with 32 studies reporting success in predicting academic grades, and 30 studies explored their use in learning analytics. In addition, the studies highlighted the potential of these methods for use in teaching quality assessment and predicting student drop out. However, there is still much work to be done in this area, as only one study in the table explored the use of these methods for teaching quality assessment (2 studies), and only 10 studies reporting predicting student drop out.

From Tables  3 and 4 , it can be observed that several ML methods have been employed in educational data mining studies. The most used methods were random forest (37 studies), decision tree (34 studies), logistic regression (26 studies) and support vector machine classifier (32 studies). These methods have been used in several studies, indicating their effectiveness in predicting academic performance, and student drop out. SVM, decision tree and random forest were heavily used for predicting student performance while logistic regression is mostly used for learning analytics. Neural networks and deep learning (17 studies) were largely used for learning analytics and predicting student performance. Feature selection (16 Studies) was mostly used for learning analytics following predicting student performance. KNN (10 studies) was mostly used to predict student performance and Naïve Bayes (8 studies) was used in balance across predicting students’ performance, learning analytics and student drop out. Additionally, the use of sentiment mining (SM) language processing in educational data mining was also notable. It was heavily used for learning analytics based on our results. The approach has been employed in several studies, and its effectiveness in learning analytics was impressive.

Table  4 shows that several studies employed multiple methods, indicating that combining methods can improve the accuracy of predictions. It was further evident that unsupervised learning approaches were not popular in educational data mining, as the table shows that only two studies used this approach. The findings indicated that there was a growing interest in using ML techniques to predict students’ academic success and analytics or learning. The most used methods in these studies were random forest, support vector machine, decision tree, and neural networks. These methods were found to perform well in predicting student performance and finding patterns in learning in most of the studies.

Semi-supervised learning and unsupervised learning were used less frequently but still showed promise in predicting student performance in some studies. Additionally, sentiment mining was found to be a useful approach for analysing students’ attitudes and behaviours in collaborative learning environments. It is worth noting that some studies utilised multiple methods in their analyses, which highlights the importance of selecting the appropriate methods for specific educational contexts and research questions. The use of ML methods and data mining techniques in educational research can enable educators to gain insights into student learning patterns and develop personalised interventions that can improve student outcomes.

5 Discussion

Interest in using ML for educational data has grown significantly over the last decade. According to our research, ML methods have been more frequently used with the purpose of learning analytics and prediction of student performance more frequently in education research to guide educators’ decision-making, which has an impact on all stakeholders. According to Long and Siemens ( 2011 ), there is a growing trend towards the use of data analytics and predictive modelling in education to promote student performance and improve educational outcomes.

Although the word “learning” is the most frequent word in both databases, publications in both databases emphasise on learning analytics and predicting student performance because the word “students”, “predicting”, “performance” are used more frequently in both databases. On the other hand, “machine” and “learning” are among the top five most frequently used words in both databases, which may indicate a focus on data mining and a broader range of scientific research topics.

A large proportion of papers in both databases were published between 2019 and 2022, demonstrating an ongoing interest in employing ML methods in educational research. The number of publications employing ML methods is growing quickly in the EBSCOhost database, with a focus on articles published between 2019 and 2022. There is a growing interest from researchers to utilise ML methods for educational data since 2019.

The results of our research show that ML methods are more frequently used in educational data mining to predict various elements of students’ academic performance and learning habits. Most of the articles (88%) used supervised learning methods, which are the most frequently used methods. Decision tree, support vector machine classifier, random forest and logistic regression were the most commonly used supervised learning methods. This result was comparable to that of Luan and Tsai ( 2021 ), whose research revealed that the top 50 studies on AI in higher education. They found that these studies mainly employed traditional ML techniques such as linear regression, support vector machines, classification and clustering, data mining. Similarly, Issah et al. ( 2023 ) found that classification and decision trees are the most widely used methods in predicting student performance.

The supervised learning methods we explored are found to be successful in predicting student academic grades and student dropout which parallels a research study result found by Khalaf et al. ( 2021 ). Some other research furthermore suggests that these methods have been found to be more effective in predicting student outcomes in a range of contexts than traditional classroom settings (Qiu et al., 2021 ).

There is also evidence to suggest that semi-supervised learning methods, which combine labelled and unlabelled data, can be particularly effective in predicting student outcomes when labelled data is limited (Livieris et al., 2019 ). Additionally, some studies have found that feature selection techniques can improve the performance of ML models in predicting student outcomes (Xiao et al., 2021 ). However, it is worth noting that the effectiveness of ML methods in predicting student outcomes can be influenced by several factors, including the quality and quantity of data available, the context of the study, and the specific method and model used (Zaffar et al., 2018 ).

Only 9.8% of the publications employed reinforcement learning via neural network analysis algorithm. With this algorithm, models are trained to make choices based on incentives or punishments. To create personalised adaptive learning systems that cater to the needs of specific learners, reinforcement learning algorithm can be very helpful.

Romero and Ventura ( 2010 ) have suggested that there is a need for traditional mining algorithms to be adjusted to accommodate for the context of education. Because data mining algorithms must take semantic information into account when analysing educational data. They have suggested that this highlights the need for more efficient mining tools that include educational field expertise into data mining algorithms. Based on our results, 1.8% of publications utilised sentiment mining and language processing. Particularly analysing verbal or written language to find and interpret attitudes, opinions, and feelings of students. This method was widely utilised for learning analytics and investigating the attitudes and behaviours of students in group learning settings (Chen et al., 2020 ).

A study by Japkowicz & Shah ( 2011 ) has compared the effectiveness of traditional statistical methods with ML methods for predicting student performance. The results of the study showed that ML methods continuously outperformed conventional methods, reaching greater levels of accuracy and better generalisation across various datasets. One advantage of ML methods over classical statistical techniques is their ability to learn from complex, non-linear relationships in data. Another study by Kotsiantis et al. ( 2004 ) have compared the performance of six ML methods including SVM, logistic regression, 3NN, SMO, Naïve Bayes etc. in predicting student performance. The study found that the Naive Bayes method exhibits highly satisfactory accuracy when compared to other algorithms, it stands out as the simplest one to implement. However, it is essential to exercise caution while using the Naive Bayes algorithm since its appropriateness may vary depending on the specific characteristics of the data and the nature of the problem. Proper consideration and understanding of the data and problem context are crucial when deciding whether to employ the Naive Bayes algorithm in specific applications.

Based on our findings, we determined that predictive modelling is largely used with educational data. Predictive models are not a new statistical technique to education statisticians and researchers. Even though the challenge of learning prediction models from data is the same for both supervised ML and inference statistics, and they are both based on the same mathematical ideas, supervised ML focuses on predictive modelling via non-parametric models (Hilbert et al., 2021 ). The main question is why ML should be used for analysing educational data analytics? Among many other contributions, all research studies we examined supported and suggested the notion of using ML methods over classical test theory techniques because of their power of accuracy and detecting stronger predictors to generalise beyond the sample and the fairness it brings to statistical analysis versus classical test theory which mainly focuses on finding correlations among variables that most of the time remain short in terms of accuracy of predictions. There are of course challenges using ML methods for educational data mostly raised by interpretability of ML methods for educational results. There are ethical and algorithmic challenges when balancing human- and machine-assisted learning (Luan et al., 2020 ). One notable challenge is the need for comprehensive and high-quality data to effectively train models (Mitchell, 1997 ). Training datasets can be complex, heterogeneous and lack standardization, making it difficult to derive meaningful insights (Lindl et al., 2020 ; Rudin et al., 2022 ). Furthermore, interpretability of machine learning models in the educational context is crucial, as stakeholders, including educators, managers and researchers need to understand the decision-making processes of these algorithms (Hilbert et al., 2021 ). Ensuring algorithmic fairness and reducing bias is another major hurdle, as models may unintentionally perpetuate or even exacerbate existing inequalities in the education system. Hence ethical concerns about the privacy and security of student data require careful consideration and robust safeguards. Integrating machine learning into educational practice requires collaboration between data researchers, educators, managers and policy makers to overcome these challenges and harness the full potential of machine learning while ensuring responsible and equitable use for educational data.

Furthermore, based on research studies we examined, ML methods play an important role in predicting student performance, detecting patterns in student’s learning, attitudes and dispositions as well as predicting students at risk and dropout rates (Albreiki et al., 2021 ). ML methods can enhance the overall quality of data analysis in educational research and demonstrate how ML can play a significant role in the validation of empirical models (Hilbert et al., 2021 ).

6 Conclusion, implications and limitations

Our comprehensive analysis has provided a snapshot of the current state of ML methods in the field of educational data. The databases that we selected contain widely read and cited journals covering ML methods in educational data to provide a comprehensive view of the mainstream research perspective on the application of ML methods in educational contexts. By including previous review studies in our analysis, we aimed to deepen our understanding and provide a more nuanced interpretation of our findings.

The collective findings from the analysed research publications strongly suggest that machine learning methods have demonstrated remarkable effectiveness in predicting student performance, identifying patterns and learning needs, and identifying at-risk students. The implications of these findings for educators are profound, as the availability of such knowledge can significantly transform teaching, learning and assessment practices. Personalised and adaptive approaches to education are emerging and moving away from the traditional one-size-fits-all paradigm. One way to do this is to increase educational statisticians and researchers’ awareness and knowledge of ML methods to further their data analysis, as these results influence the decision-making process for all stakeholders.

However, it is important to acknowledge some limitations in our study. While our analysis sheds light on the current landscape, it is not comprehensive and may not capture new trends or the latest developments in the rapidly evolving field of machine learning in education. Not including 2023 publications in our study may create a temporal bias and future research should consider including more recent publications to provide a comprehensive understanding. Furthermore, the successful application of machine learning methods in education depends on the awareness and expertise of educational statisticians and researchers. There is a need to bridge the gap between traditional educational research and advanced data analysis techniques. Future research efforts should explore strategies that will enhance the knowledge and skills of educational stakeholders and empower them to use machine learning methods effectively. This interdisciplinary collaboration between educators and data scientists has the potential to optimise decision-making processes for all stakeholders involved in the education ecosystem.

The accuracy of predictions based on educational data is crucial, as the results of such analyses can drive education policies worldwide, especially for international exams. In analysing well-known international tests such as PISA, PIRLS, TIMMS and TALIS, ML methods can be used to improve the accuracy of predictions and reduce biases that naturally arise from the data. These publications we analysed in this current research help to improve the interpretability of ML methods in educational research. We recommend that statisticians, researchers, educators, and policymakers collaborate to develop guidelines and policies for ethical and responsible use of ML methods in education.

In conclusion, our study highlights the transformative potential of machine learning methods in reshaping education and calls for a concerted effort to bridge the gap between classical statistical test theory techniques for educational data and the latest data analysis techniques such as ML techniques. As we navigate the evolving landscape of machine learning in education, continued research and collaboration will be instrumental in realising the full potential of using ML techniques for educational data.

Data availability

Please note that all data generated or analysed during this study are included in this article as an appendix [and its supplementary information files].

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Application of exercise therapy in patients with chronic kidney disease-induced muscle atrophy: a scoping review

• Jiawei Yin 1 ,
• Xiaotu Zhang 1 ,
• Zilin Wang 1 ,
• Zihan Qu 1 ,
• Xuefeng Sun 1 ,
• Yuqing Song 1 &
• Hongshi Zhang 1  

BMC Sports Science, Medicine and Rehabilitation volume  16 , Article number:  100 ( 2024 ) Cite this article

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The prevalence of muscle atrophy in patients suffering from chronic kidney disease (CKD) presents a significant challenge to healthcare providers, necessitating innovative approaches to management and care. Against this backdrop, this study embarks on a comprehensive review of literature concerning the application of exercise interventions in the nursing care of these patients. Such interventions are critical in addressing the debilitating effects of the condition, which include progressive loss of muscle mass and strength, adversely affecting patient mobility, quality of life, and overall survival. This review aims to identify the specific exercise modalities, contents, outcome indicators, and application effects associated with this intervention, in the context of the complex interplay of metabolic, inflammatory, and hormonal factors contributing to muscle wasting in CKD patients. By examining the efficacy of various exercise interventions, this study seeks to elucidate optimal strategies for mitigating the impact of CKD-induced muscle atrophy, thereby informing clinical practices and improving patient outcomes.

According to the method of a scoping review, nine databases (Cochrane, PubMed, EMBASE, Web of Science, ProQuest, Ovid, CNKI, Wanfang Data, and VIP) were searched until September 28, 2023. The included literature was screened, summarized, and analyzed.

A total of 20 pieces of literature were included. Some types include aerobic exercise, resistance exercise, and aerobic combined resistance exercise. The exercise intensity primarily falls within the mild to moderate range, with a recommended frequency of 2 − 3 times a week, lasting 30 − 60 min each time. The types of outcomes encompassed in this study include body composition, functional testing, strength measurements, laboratory examinations, cardiopulmonary function assessments, and patient-reported outcomes. To varying degrees, exercise intervention positively impacts the subjects' physical activity ability, body composition, and skeletal muscle status. Currently, resistance training is the primary type of intervention used for preventing and treating CKD patients induced by muscle atrophy.

Exercise intervention can improve muscle strength, physical function, and quality of life in patients with CKD muscle atrophy. Therefore, patients should be fully informed of the effect of exercise intervention in the treatment of chronic kidney disease-induced muscle atrophy in future, so as to promote the standardized implementation of exercise intervention.

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Introduction

Chronic kidney disease (CKD) significantly impacts global health, with its management complicated by the high prevalence of sarcopenia, identified as a loss of skeletal muscle mass and strength. Duarte et al. [ 1 ] report a notable prevalence of sarcopenia in CKD patients at 24.5%, with a higher incidence observed in those undergoing dialysis. This condition, especially severe in 26.2% of dialysis patients compared to 3.0% in non-dialysis patients, underscores the critical need for early identification and intervention.Chronic Kidney Disease (CKD) is associated with various pathophysiological processes, including mitochondrial dysfunction. Studies reported that muscle atrophy in CKD patients is related to mitochondrial dysfunction [ 2 ]. Exercise intervention can reduce oxidative stress, increase mitochondrial capacity, and enhance mitochondrial function [ 3 ]. Furthermore, it is particularly noteworthy that research has identified the combination of moderate-intensity continuous exercise (MICE) with blood flow restriction (BFR) as effective in suppressing the appetite of obese adults through the promotion of Lac-Phe and ghrelin secretion [ 4 ]. This finding underscores the significant implications of exercise not only for CKD but also for diabetes management, highlighting its potential as a pivotal intervention in the treatment and prevention strategies for these conditions. Mitochondrial DNA copy number (mtDNA-CN) is considered a novel biomarker for CKD risk, as higher levels of mtDNA-CN are associated with a lower risk of CKD. This relationship is independent of traditional CKD risk factors, suggesting that mtDNA-CN could serve as an important indicator for identifying CKD progression and severity [ 5 ]. Furthermore, the onset of diabetes in patients with CKD is significant, as mitochondrial dysfunction can exacerbate metabolic dysregulation. The relationship between mitochondrial function and CKD highlights the potential for targeted interventions to improve mitochondrial health and manage CKD, particularly in the context of comorbid conditions like diabetes [ 6 ].

Recent meta-analyses showed that exercise training can increase cardiorespiratory endurance, improve muscle strength and muscle volume, reduce the risk of cardiovascular disease, delay the progression of CKD, and improve the quality of life of CKD patients [ 7 ]. Therefore, we should identify muscle atrophy in CKD patients as early as possible and implement the intervention. While patients diagnosed with CKD may participate in resistance training, flexibility exercises, and aerobic exercise [ 8 ], it is crucial to consider the diverse physical capacities and tolerances of subjects at various phases of CKD. Furthermore, the lack of clear evaluation criteria for the type, specific content, and outcomes of exercise interventions for CKD patients leads to significant heterogeneity in the type, frequency, and intensity of exercise interventions [ 7 ].

A scoping review assists researchers in elucidating their research inquiries, presenting the scope and extent of research involved, summarizing research results, identifying the limitations of existing research, and finding research progress in a particular knowledge field [ 9 ]. This study used a scoping review methodology to analyze and synthesize the application research on exercise intervention in chronic nephritis muscle atrophy. Our objective is to furnish medical and nursing professionals with a comprehensive summary of exercise intervention types, content elements, evaluation indices, and efficacy, serving as a valuable resource.

Research question

① What are the methods, intensity, frequency, and time of exercise intervention for chronic kidney disease-related muscle atrophy? ② How does the application affect the exercise intervention program?

Identifying relevant studies

Search strategy.

Using a computer, a search was conducted in the Cochrane Library, PubMed, EMBASE, Ovid, ProQuest, Web of Science, CNKI, Wanfang, and VIP. The search time was covered from the establishment of the database until September 2023. The search words were combined with the MeSH words and entry terms in the PubMed database, including the search terms "Sarcopenias," "Muscle wasting," "Muscle atrophy," "Diabetes Mellitus," "Diabetes Insipidus" "Diet, Diabetic," "Prediabetic State" "Exercise Therapy" "Remedial Exercise," "Rehabilitation Exercises," "Physical Activities," "Aerobic Exercise," "Acute Exercise," "Isometric Exercise," "Exercise Training." The relevant references were tracked and noted.

Inclusion criteria and Exclusion criteria

Inclusion criteria: (1) Population: The study subjects included CKD patients with muscle atrophy or sarcopenia. (2) Intervention:Articles that employ exercise therapy as an intervention strategy are included, covering a range of modalities such as aerobic training, resistance training, and stretching exercises. Studies focusing on traditional physical therapy interventions, such as electrostimulation, and pharmacological treatments are excluded from this review. (3) Comparison: The control arm was subjected to conventional care, incorporating stretching routines or engaging in physical activities quantitatively inferior to the normative daily exertion levels. (4) Outcomes: Muscle Mass, Muscle Strength, Physical Performance, Biochemical Markers, Functional Status were measured at baseline and post-exercise. (5) Study: The literature categories comprised a variety of original research encompassing randomized controlled trials, quantitative studies, qualitative studies, and mixed studies.

Exclusion criteria: Reviews, conference abstracts, thematic summaries, protocols, duplicate publications, and full-text articles that were not accessible were excluded from the analysis. Literature that missed any discussion of the specific details regarding the execution, substance, or impact of exercise intervention in individuals afflicted with muscular atrophy due to chronic renal illness was likewise disregarded.

Study selection

Two proficient researchers conducted an exhaustive review of titles and abstracts based on the inclusion and exclusion criteria, completing preliminary literature screening. Subsequently, they reviewed the complete text to make a final selection. The screening was conducted independently, and then the results were compared. The issue was referred to the research team for discussion in a dispute.Through open dialogue and a rigorous examination of the inclusion and exclusion criteria, we reconciled differing viewpoints and reached a mutually agreed-upon selection of literature. This process highlights the critical role of collaborative discussion and meticulous scrutiny in achieving a consensus on literature screening outcomes, ensuring the integrity and quality of our research methodology.

Data extraction and synthesis

Two researchers independently extracted all the information from the included literature as follows: (1) authors, research type, country and year of publication, and sample size; (2) intervention method, intervention content and type, intervention duration of the experimental group and the control group; (3) outcome indicators, and measurement content of outcome indicators.

Study characteristics

Following the initial retrieval of 875 articles, a final selection of 20 articles was made [ 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 ]. Figure 1 depicts the specific screening process. These included studies were conducted in China ( n  = 9), United Kingdom( n  = 3), Brazil ( n  = 2), Australia ( n  = 1), Germany ( n  = 1), Italy ( n  = 1), South Korea (= 1), Sweden ( n  = 1), and the USA ( n  = 1). Regarding the publication years of the studies included in this article, the distribution is as follows: 2023 ( n  = 3), 2022 ( n  = 4), 2021 ( n  = 4), 2019 ( n  = 3), 2018 ( n  = 1), 2016 ( n  = 1), 2015 ( n  = 1), 2014 ( n  = 2), and 2007 ( n  = 1). The distribution of the studies by year and geographic location is presented in the supplementary figure. Among the 20 pieces of literature included in this study, 14 literatures described RCTs [ 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 ] and six literatures are quantitative non-random studies [ 10 , 11 , 13 , 19 , 22 , 29 ]. Table 1 lists the characteristics of the included literature and is discussed below.

Types of Exercise Intervention Programs

The exercise intervention scheme mainly includes resistance exercise [ 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 ], aerobic exercise [ 23 , 29 ], and aerobic exercise combined with resistance exercise [ 13 , 15 , 22 , 24 ]. (1) Currently, resistance training is the most prevalent form of exercise intervention. The common resistance exercise intervention scheme involves strength training of the upper and lower limbs. Upper limb strength training includes biceps curl with dumbbells, elastic ball movement on the non-internal fistula side, pull-ups, and chest and shoulder compression. However, lower limb strength training focuses on the muscle groups around the knee joint, including lunge, squat, sitting leg raising, knee flexion and extension, and quadriceps strength training with elastic belts. Furthermore, there are resistance exercises for the hip joint, such as leg compression and hip flexion. (2) The aerobic exercise intervention scheme primarily consists of several modalities, such as bicycle modalities [ 11 , 16 ], treadmill exercise [ 13 ], Baduanjin [ 29 ], and steady-state walking [ 23 ]. In this context, Luca et al. [ 23 ] used steady-state walking as an intervention plan for aerobic exercise and examined the impact of this simple aerobic exercise on the subjects. (3) The intervention program mostly incorporates resistance exercise with low-to-moderate intensity aerobic exercise. The three most prevalent forms of aerobic exercise are cycling, treadmill, and rowing. Liming et al. [ 19 ] used psychological theory to guide patients in resistance exercise, helping patients develop healthy behaviors through the healthy action process orientation model.

Intensity, frequency, and duration of exercise intervention

The intervention intensity and frequency varied among the studies. (1) Exercise intensity: Eight studies [ 10 , 11 , 12 , 18 , 19 , 22 , 24 , 26 ] set the exercise intensity according to the scores of the subjects' perceived exertion (RPE). The intensity target of exercise training was established in two studies [ 14 , 26 ] based on the patient's capacity to tolerate the quantity of exercise. The training intensity progressively escalated until the patients reached the optimal tolerance level. Two studies [ 21 , 27 ] assessed the exercise intensity of the subjects based on maximum repetitions (RM) and the percentage of maximum loading (1RM) of the exercise load. Four studies [ 13 , 15 , 16 , 19 ] set the exercise intensity based on the subjects' cardiopulmonary function indexes. This was achieved by measuring the heart rate of the patients during exercise as a reference, setting the appropriate exercise intensity after evaluating the heart rate at the maximum exercise intensity they could tolerate. Zhang Bo et al. [ 13 ] divided the exercise training into low intensity (25% ~ 44% VO 2 max ) and moderate intensity (45% ~ 59% VO 2 max ) based on the subjects' peak oxygen uptake (VO 2 max ). There was a gradual transition from low to moderate intensity during the intervention. This. (2) Exercise frequency: The intervention frequency of each study varied from 2 to 3 times per week, while the duration of intervention was typically set based on the subjects' tolerance level and training objectives. (3) Duration of exercise intervention: There are a total of 13 studies in which the intervention period spans 12 weeks [ 11 , 12 , 13 , 15 , 16 , 17 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 29 ], two studies have an intervention duration of 24 weeks [ 14 , 19 ], three studies have an intervention duration of 12 months [ 10 , 18 , 28 ], and two studies have an intervention duration of 6 months [ 19 , 23 ].

Outcome indicators and measurement tools

Outcome indicators included functional tests, body composition, strength, laboratory examination, cardiopulmonary function, and strength, and functional evaluations. The principal physical activity assessments comprised a walk test, sit-to-stand test, functional reach, balance test, SPPB score, and physical activity recall. The measurement of body composition included weight, body mass index, body fat, and lean body mass. Skeletal muscle mass was assessed using dual-energy X-ray absorptiometry, anthropometry, and muscle ultrasound. Laboratory examination indicators included inflammatory markers, renal profile, and body fat. Cardiopulmonary function indicators examined forced expiratory volume in one second (FEV-1), vital capacity, forced vital capacity (FVC), maximum inspiratory pressure (MIP), and peak oxygen uptake (VO 2 max ). In terms of patient-reported outcomes, the primary measurement tools encompassed the Quality-of-Life Questionnaire, Pain Scale, Leicester Uremic Symptom Score, Sarcopenia Quality of Life Scale, Activities of Daily Living Scale, Barthel Index, Kidney Disease Quality of Life Scale, Dialysis Patient Quality of Life Scale, and Revised Piper Fatigue Scale.

Effects of Exercise Intervention

(1) Effects of resistance exercise intervention: The exercise intervention schemes for muscle atrophy in CKD patients in the literature included different levels of resistance exercise. A total of ten studies have documented that resistance training protocols yielded a positive impact on several aspects of the subjects' physical function [ 10 , 11 , 13 , 16 , 29 ], muscle strength [ 10 , 13 , 16 , 22 , 26 , 27 , 28 , 29 ], daily living ability [ 10 , 13 , 27 ] and renal function [ 19 , 22 ]. Danielle and colleagues [ 12 ] found that a 12-week program of high-intensity progressive resistance exercise training (PRET) for hemodialysis patients led to a statistically and clinically significant increase in thigh muscle volume, with a mean difference of 193 cm 3 (95% CI: 63 to 324 cm 3 ; P  = 0.007) compared to the control group. However, it did not significantly enhance the subjects' physical activity capacity or overall quality of life. (2) Aerobic exercise intervention effect: Eleven studies [ 11 , 13 , 15 , 16 , 22 , 23 , 24 , 25 , 26 , 27 , 28 ] reported the effects of different levels of aerobic exercise on subjects. Since low-intensity aerobic exercise was difficult to improve muscle strength [ 30 ] significantly, it was mostly used as an exercise intervention program for the control group [ 11 , 13 , 16 , 22 , 23 , 26 , 27 , 28 ]. Furthermore, other studies showed positive impacts of aerobic exercise training interventions on the subjects. For example, Wu Qian et al. [ 29 ] found significant improvements in the intervention group's handgrip strength, daily walking speed, and physical activity level compared to the control group, with the revised Piper fatigue scale (RPFS) scores also being significantly lower (indicating less fatigue) in the intervention group. These differences were statistically significant ( P  < 0.05). (3) Effects of aerobic exercise combined with resistance exercise intervention: Four literatures [ 13 , 15 , 22 , 24 ] incorporated a combination of aerobic exercise and resistance training in their physical exercise intervention program. Emma et al. [ 24 ] showed that combined resistance and aerobic training were more beneficial than aerobic training alone. Zhang Bo et al. [ 13 ] demonstrated that after 12 weeks of low and medium intensity aerobic combined with resistance exercise, elderly patients with chronic kidney disease complicated with sarcopenia showed significant improvements in appendicular skeletal muscle mass index (ASMI), grip strength index, 6-m walking speed, peak oxygen uptake (VO 2 max ), one-leg standing time, and reach in seat distance, with p-values indicating statistical significance ( P  < 0.05) for these improvements. This indicates that the exercise intervention was effective in enhancing muscle mass, muscle strength, and motor function without adversely affecting renal function.

This study demonstrates that exercise intervention for muscle atrophy in individuals with CKD includes different modalities, mostly resistance training and a combination of aerobic exercise. Guiding patients regarding resistance training can facilitate the anabolism and metabolism of skeletal muscle, enhancing muscle quality, improving muscle strength, and effectively enhancing patients' overall quality of life [ 31 ]. Exercise intervention schemes for CKD patients are often carried out in various forms of exercise combinations. Researchers often use aerobic exercise as an important auxiliary intervention method that benefits cardiovascular health. It improves the heart and lung function of the subjects, enhances their endurance, and facilitates the development of resistance training.

There are significant differences among CKD patients at different stages, so we should comprehensively evaluate the physiological function and tolerance of CKD patients and develop individualized exercise intervention programs for patients [ 7 ]. This study showed that the exercise intervention program includes detailed pre-exercise examinations, such as preliminarily assessing the subjects’ muscle strength and cardiopulmonary function status, determining whether they can tolerate exercise intervention, and developing personalized exercise prescriptions. Jonathan [ 15 ] and colleagues completed detailed medical examinations before the intervention, measuring the subjects' cardiopulmonary function and upper and lower limb strength. Results indicated that the design of the exercise intervention program was personalized. This study showed that the exercise form of CKD patients is not a single repeat of a certain type of exercise but a combination of various exercise methods that can achieve the best effect. Despite numerous RCTs reported that resistance exercise could significantly improve muscle strength in patients with CKD [ 32 ], a meta-analysis [ 33 ] has revealed that the use of progressive resistance exercise as the sole intervention did not result in a significant improvement in the 6-min walk test, which serves as a proxy indicator of cardiopulmonary function. It indicates that resistance training alone makes it difficult to improve the cardiopulmonary function of subjects significantly. As resistance exercise training necessitates a minimum level of cardiopulmonary function as a foundation, it also imposes specific cardiopulmonary function requirements on the subjects. Low-intensity, long-duration aerobic exercise has been shown to enhance the cardiopulmonary function and exercise capacity of patients with chronic kidney disease [ 34 ]. Therefore, clinical researchers frequently combine two forms of exercise to enhance patients' quality of life by enhancing their cardiopulmonary function and muscle strength. It demonstrates the comprehensive nature of exercise intervention program design. Universality: For patients with non-maintenance dialysis CKD, regular visits to the hospital for dialysis treatment means that they cannot receive the supervision of clinical researchers throughout the process. They also face problems such as a lack of exercise equipment and professional guidance. Emma et al. [ 24 ] found that patients considered frequent visits to the hospital as a major obstacle to participating in the study. So, future research needs to design simple and feasible home training programs for different patient situations and provide feedback when patients come to the hospital for dialysis. Luca’s [ 23 ] exercise training program was designed and organized by the hospital and ultimately completed by patients at home. It improved patients' physical function significantly after six months of intervention with low-intensity exercise.

The results of this study show that exercise intervention can improve physical function, activity ability, muscle atrophy, and quality of life in patients with CKD. This viewpoint is also supported by Vanden et al.'s systematic review of exercise intervention in CKD patients [ 35 ]. Furthermore, a cross-sectional study [ 36 ] also suggested that clinical medical staff should actively implement exercise interventions for CKD patients to address adverse outcomes such as muscle atrophy and decreased quality of life caused by long-term catabolism and dialysis treatment. Although exercise intervention positively impacts CKD patients, the current studies are mainly small-sample randomized controlled trials with low quality. Therefore, larger-sample randomized controlled trials are needed to evaluate the impact of exercise intervention on muscle atrophy in CKD patients more accurately. Notably, the frequency and duration of exercise intervention are not positively correlated with the intervention effect. Excessive exercise intensity may lead to lactic acidosis in patients, and severe cases may cause acute renal failure secondary to rhabdomyolysis [ 37 ]. Therefore, exercise frequency must be determined by the patient's condition; high-intensity training should not be pursued indiscriminately. Furthermore, cardiac function in CKD patients must be matched with the intensity of exercise. A systematic review have shown that high-intensity interval exercise with passive recovery leads to a greater increase in cardiac troponin T levels compared to moderate-intensity continuous exercise [ 38 ]. To minimize cardiovascular risk during exercise, exercise prescriptions should be tailored based on individual circumstances.A unified standard regarding the exercise frequency and intervention cycle of CKD patients does not exist. The guidelines indicate that the optimal resistance exercise frequency is 2 − 3 times per week, with an interval of 24 − 48 h each time, which is consistent with the results shown in this study [ 39 ]. In the literature included in this study, only seven articles [ 12 , 16 , 17 , 19 , 25 , 26 , 29 ] mentioned the safety of exercise intervention, and 3 of them [ 12 , 17 , 19 ] reported adverse events. Danielle et al. [ 12 ] reported muscle soreness and laceration of the back wound, indicating that there is a lack of comprehensive reports regarding the safety of exercise intervention trials in CKD patients. Some researchers failed to fully consider the safety of exercise intervention based on individual differences among subjects.

Integrating insights from the studies on exercise's impact on CKD, sarcopenia in hemodialysis patients, and diabetes management through physical activity, the future perspective emphasizes a holistic approach to CKD treatment. This approach advocates for the incorporation of tailored exercise programs to address the multifaceted challenges of CKD. A study elucidates how diverse exercise modalities can significantly impact blood glucose levels, emphasizing the importance of exercise in the management of diabetes, particularly in patients with CKD. It underscores the role of physical activity in enhancing insulin sensitivity and glycemic control, offering a non-pharmacological strategy to mitigate diabetes-related complications in CKD patients [ 40 ]. Additionally, exercise has beneficial effects on mitochondrial function and diabetes management. The research emphasizes that various exercise modalities, such as resistance and endurance training, can enhance mitochondrial density, dynamics, and oxidative capacity in muscle tissues. These improvements aid in boosting glucose metabolism and insulin sensitivity, which are crucial for diabetes control. The findings indicate that structured exercise programs are an indispensable component in addressing mitochondrial dysfunction and managing diabetes, especially in populations with chronic conditions like CKD [ 41 ]. Moreover, research has identified the efficacy of exercise in alleviating fatigue among hemodialysis patients, highlighting the potential of structured exercise programs to enhance energy levels and overall health in this demographic, regular physical activity could be an essential component of comprehensive care for hemodialysis patients, thus improving their quality of life and physical function [ 42 ]. The envisioned future includes rigorous clinical trials to further validate exercise as a key adjunct therapy, potentially leading to standardized exercise recommendations that enhance patient outcomes and quality of life in CKD management.

Strengths and limitations

The strengths of this scoping review include an extensive and repeated search of the literature to capture all relevant articles and limit emissions while strictly adhering to the PRISMA reporting guidelines. Unpublished dissertations are more likely to report uncertain or negative results, which may produce a reverse publication bias and be excluded from this study. The literature included in this study lacks large-sample, multi-center, randomized controlled studies, and the methodological rigor and data quality of the included studies have not been systematically evaluated.

Patients with CKD face many complex issues that seriously affect their quality of life. For them, long-term dialysis treatment has produced negligible side effects, and exercise therapy is needed to improve their quality of life. Exercise intervention can improve the muscle strength, physical function, and quality of life of patients with chronic nephritis muscle atrophy, which is an effective intervention method. We are still waiting to find its potential positive effects on CKD patients. In future nursing work, we should evaluate the physiological function status of CKD patients, formulate safe and effective exercise intervention plans, and intervene early in their muscle atrophy symptoms to promote their rehabilitation and improve their clinical outcomes.

Availability of data and materials

All data generated or analysed during this study are included in supplementary information files.

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The literature review and inclusion criteria were collaboratively developed by all authors, while Jiawei Yin and Xiaotu Zhang conducted the systematic literature search and screening. Data extraction from relevant literature was performed solely by Jiawei Yin. Following data extraction, Jiawei Yin composed the manuscript. Zilin Wang managed the data. Yuqing Song, Zihan Qu, and Xuefeng Sun undertook data collection and analysis, as well as provided suggestions. The final draft was reviewed and approved by Hongshi Zhang.

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Yin, J., Zhang, X., Wang, Z. et al. Application of exercise therapy in patients with chronic kidney disease-induced muscle atrophy: a scoping review. BMC Sports Sci Med Rehabil 16 , 100 (2024). https://doi.org/10.1186/s13102-024-00876-8

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Mycophenolate-induced colitis in a patient with lupus nephritis: a case report and review of the literature

• Ziyad Alakkas 1 ,
• Abdulaziz M. Gari 2 ,
• Sara Makhdoum 3 &
• Eman A. AlSindi 2  

Journal of Medical Case Reports volume  18 , Article number:  229 ( 2024 ) Cite this article

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Mycophenolate mofetil (MMF) is an immunosuppressive drug that is frequently prescribed to patients with rheumatological diseases. MMF’s side effects include abdominal discomfort, nausea, vomiting, and other gastro-intestinal side effects, which typically appear in the first few months of treatment. However, late-onset diarrhea does not rule out the presence of MMF-induced colitis, which can be misdiagnosed since it is linked to a broad range of histopathological characteristics, including alterations that resemble inflammatory bowel disease, graft-versus-host disease, and ischemia. The differences in treatment response may be explained by the complexity of the histopathologic characteristics.

Case presentation

Here we present a case of a 29-year-old Arabian female with lupus nephritis who started on MMF as induction therapy. In two months, the patient was presented to the Emergency Department with diarrhea and manifestations of severe dehydration. Infectious diseases and adverse drug events were suspected, so the patient was admitted for further workup, and MMF was stopped. The patient was diagnosed with MMF-induced colitis based on colonoscopy and histological findings. Fourteen days after stopping MMF, she was within her baseline.

The purpose of this paper is to report a case of early-onset MMF-induced colitis in a patient with lupus nephritis who had started MMF as induction therapy. A review of the available literature on this uncommon immunosuppressive effect is also presented.

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Introduction

Mycophenolate mofetil (MMF) is widely used as an immunosuppressive agent for various inflammatory and/rheumatic conditions, including lupus nephritis and organ transplantation. Mycophenolic acid is an active metabolite of MMF that reversibly inhibits inosine monophosphate (IMP) dehydrogenase, preventing purine synthesis in T and B cells [ 1 , 2 ]. Dose modification or even discontinuation of MMF is quite common due to adverse effects, especially gastro-intestinal side effects, which occur in nearly 45% of cases [ 2 ]. Enterocytes are particularly susceptible to the antimetabolic effects of MMF due to their reliance on the de novo process of purine synthesis. This prevents the growth and reproduction of small bowel epithelial cells, which disrupts fluid absorption and causes diarrhea [ 3 , 4 ]. However, MMF is a well-tolerated therapy in general.

One of the major adverse effects of MMF is colitis, which can lead to serious complications that include perforation, bleeding, and hospitalization. In recent years, several studies have investigated the factors associated with MMF-induced colitis. One study evaluated the incidence of gastro-intestinal complications following kidney transplant and showed that MMF-induced colitis was the most common type of colitis, occurring in 6–9% of patients, and the most common symptom was diarrhea [ 5 , 6 ]. MMF is one of the common immunosuppression medications for rheumatological disease and has been used for the last two decades with very good outcomes in terms of different aspects and system involvement.

There are only a few reports of patients who developed MMF-related colitis (Table  1 ). A small retrospective study evaluated 11 patients with rheumatologic disease who had been treated with MMF and found that only one patient had medication-related colitis [ 7 ]. We report a case of a young female who had systemic lupus erythematosus and lupus nephritis and presented with abdominal pain and diarrhea. We also discuss the challenges in the diagnosis of MMF-induced colitis.

Written consent was obtained from the patient, and ethical approval was provided by the Institutional Review Board (IRB) of the Study and Research Department of King Fahad Hospital, Jeddah.

The patient was a 29-year-old Arabian woman with a known case of systemic lupus erythematosus, which had been diagnosed 5 years prior based on the criteria of the European League Against Rheumatism (EULAR)/American College of Rheumatology (ACR). She was started on hydroxychloroquine at 200 mg orally once per day, and she had no comorbidities except for hypothyroidism.

The patient had not been followed up due to the COVID-19 pandemic, but in January 2023, she presented to the clinic with an incidental lab result showing a creatinine level of 4.3 mg/dL. Thus, a renal biopsy was planned, and she was diagnosed with class IV lupus nephritis. She received pulse methylprednisolone therapy at 500 mg intravenously for 3 days, which was then switched to a tapering dose of prednisolone. Induction therapy using MMF was initiated at 500 mg orally twice daily then titrated up weekly until she was discharged to home on 1.5 g orally twice per day, which is the maximum recommended dose of induction phase for lupus nephritis.

After 2 months, the patient presented to the emergency department with complaints of nausea, vomiting, and left-sided abdominal pain associated with diarrhea 5–6 times per day, which was watery but contained no blood or mucus. Her symptoms started at just 2 weeks after starting MMF therapy and had progressed over the last month. She denied having fever, weight loss, or night sweats. Upon physical examination, she was alert and oriented but in pain. The abdomen was tender, but there were no signs of peritonitis. The rest of the physical examination was unremarkable apart from Cushingoid face. She was afebrile, and her blood pressure, heart rate, respiratory rate, and oxygen saturation were within normal ranges. Her weight was 90 kg.

Upon admission, MMF was promptly discontinued due to the possibility that it might have led to an infection. The immediate care involved the delivery of intravenous fluids, a low-residue diet, analgesic medications like intravenous acetaminophen, and antispastic treatments. Routine blood tests performed at admission indicated leukopenia 3.800 × 10 6 /L normal range (4–11 × 10 6 /L), elevated creatinine 6.3 mg/dL normal range (07–1.3 mg/dL) while her baseline of creatinine was 2 mg/dL and GFR 60 ml/min, and noticeably increased inflammatory markers (C-reactive protein 32 mg/dL normal range < 5 mg/dL, erythrocyte sedimentation rate 40 mm/hour normal range < 20 mm/hour). The C3 and C4 complement levels were 0.6 g/L (0.8–1.6 g/L) and C4 0.18 g/L (0.20–0.65 g/L), respectively. Stool analysis indicated + 2 pus cells and a negative culture. Urine analysis indicated a protein level of + 1 with no red blood cell crystals or casts. An abdominal ultrasound was performed, but the result was unremarkable.

Later, computed tomography scan was performed, which did not reveal any other abnormalities and confirmed the ultrasound results. A colonoscopy showed erythematous patches with few erosions and rectal-sparing colitis. Multiple biopsies been taken (Fig.  1 ). Infectious colitis, drug-induced colitis, newly diagnosed inflammatory bowel disease (IBD), gastro-intestinal involvement associated with systemic lupus erythematosus, and mesenteric ischemia were all considered in the differential diagnosis. Cytomegalovirus (CMV) infection is the main concern among infectious causes of colitis in patients with impaired immune systems, and its possible endoscopic findings include diffuse erythema, ischemia, erosions, and ulcers.

Colonoscopy shows hyperemic mucosa with some superficial ulcers from sigmoid up to the cecum, while the terminal ileum shows superficial ulceration with some area of inflammatory patches

The endoscopic appearance of drug-induced colitis can resemble that of ulcerative colitis, infectious colitis, and ischemic colitis. Non-steroidal anti-inflammatory drugs (NSAIDs) are the most common cause of drug-induced colitis, but MMF was probably involved in the present case. Rectal sparing almost always occurs in MMF-induced colitis. Microscopically, the colonic mucosa displayed a mild architectural distortion, with ruptures of few dilated glands. Mild cryptitis is observed. However, no obvious apoptosis seen as been previously described in few cases of MMF induced colitis. There were no evidence of viral cytopathic changes, granuloma, dysplasia or malignancy (Fig.  2 A–D),

Mycophenolate Mofetil induced colitis. A Colonic biopsy with mild architectural distortion, crypt hyperplasia and lamina propria inflammation (HEx 4 ×). B Higher magnification (HE 20 ×) show dilated colonic glands. C Destructed ruptured colonic glands with mucin spillage (HE × 20 ×). D Acute inflammation within the glands (cryptitis), at high power magnification (HE x 40 ×)

Following the cessation of MMF, the gastro-intestinal symptoms and the biomarkers for systemic inflammation gradually subsided and returned to base line levels after 14 days without further therapy, thus supporting the suspicion of drug-induced colitis. The patient was discharged 24 days after admission, MMF was discontinued, and the Euro-Lupus protocol was started with cyclophosphamide as induction therapy for lupus nephritis. The patient has been followed up closely and has shown improvement of active and chronic issues with 6 doses of cyclophosphamide completed. Azathioprine with a low dose of steroid was initiated. There have been no other gastro-intestinal manifestations.

MMF is an immunosuppressive medication that was first used to decrease the risk of organ rejection after transplantation, but now, it is also being used to treat patients with autoimmune systemic disorders, including systemic lupus erythematosus. The target dose of MMF for the treatment of Lupus Nephritis is 2–3 g per day in combination with glucocorticoids especially for those high-risk patients for kidney failure including reduced GFR. Dosage may need to be adjusted according to adverse events, toxicity, efficacy and MPA blood level [according to 2019 European Leage Against Rheumatism and European Dialysis and Transplant Association (EULAR/ERA-EDTA) recommendation for the management of Lupus Nephritis]. General recommendation to not exceed 2 g in patients with chronic renal failure with GFR less than 25 mL/min.

As far as we are aware, there have been only a few documented cases of colitis caused by MMF in a patient with a rheumatological condition. The onset of MMF-induced colitis in a patient with lupus nephritis, sclerosis, mixed connective tissue disease (MCTD), and polymyositis has previously been documented by other authors (Table  1 ). In transplant recipients, however, MMF is a well-known trigger of drug-induced colitis [ 6 ].

Mycophenolate targets tissues with fast cell division and reliance on purine synthesis. Lymphocytes and gut cells are the two main organs in which regeneration is dependent on this system. Immunosuppression results from lymphocytes (B and T cells) being more dependent on this route (by 90%) [ 8 ]. The blood level of mycophenolic acid is directly inversely correlated with mycophenolate’s adverse effects [ 9 ]. Since 50% of enterocytes rely on the mycophenolate-targeting mechanisms, it is believed to explain why 45% of patients experience gastro-intestinal side effects, including simple diarrhea, esophagitis, gastroesophageal reflux disease, enteritis, and colitis, as in our patient [ 2 ]. The most typical gastro-intestinal mucosal pattern associated with MMF is mucosa that seems normal [ 10 ]. The histological changes in patients receiving MMF have mostly been classified in many studies as normal or near normal in around one-third of cases, followed by changes resembling IBD, graft-versus-host disease (GVHD), self-limited colitis, and ischemia [ 11 , 12 , 13 ]. Another study reported histological results that were in line with an acute colitis-like pattern in half of cases as being the most common, followed by IBD-like pathologic findings in 36% of cases, ischemia-like characteristics in 5.6% of cases, and GVHD-like abnormalities in 8.3% of cases [ 6 ]. Examples of specific histological characteristics of MMF-related colitis include crypt architectural disarray, increased lamina propria inflammation, dilated damaged crypts, increased crypt epithelial apoptosis, and GVHD-like alterations [ 14 ].

The wide morphological spectrum documented in MMF-induced colitis includes features that can lead to misdiagnosis and delayed intervention. Therefore, it is essential to discuss the clinical history of MMF therapy with pathologists and to take this diagnosis into consideration, regardless of the length of therapy, given the variations in the therapeutic management and prognosis of these disorders. The most frequent indication for a colonoscopy referral for patients on MMF medication is diarrhea. Nearly half of such patients have normal colonoscopy results. Other endoscopic findings include erythema (33%) and erosions/ulcers (19%), which indicate a need for routine biopsies to help with confirmation of the diagnosis [ 6 ].

Treatment options range from stopping MMF use to using specialized immunosuppressive medications to correct the histological pattern replicated by MMF-induced colitis. There are no recommendations available to help clinicians treat colitis induced by MMF. Case reports have frequently shown that after stopping MMF, diarrhea symptoms improve within a week. In another study, after unsuccessful attempts with MMF cessation, a patient was given 50 mg of intravenous steroids daily for two weeks and a single infusion of 5 mg/kg of infliximab, which led to decreased stool frequency within three days after infusion [ 28 ].

It is well known that MMF causes drug induced colitis with a variety of patterns and clinical manifestations. When caring for people with autoimmune systemic disorders, colitis should be recognized as a rare side effect of MMF therapy. It is necessary for physicians to be aware that discontinuing the medicine is typically effective without the need for extra treatments.

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Abbreviations

• Mycophenolate mofetil

Mycophenolate sodium

Inosine monophosphate

Gastro-intestinal

Inflammatory bowel disease

Cytomegalovirus

Polyendocrinopathy-candidiasis-ectodermal dystrophy

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Alakkas, Z., Gari, A.M., Makhdoum, S. et al. Mycophenolate-induced colitis in a patient with lupus nephritis: a case report and review of the literature. J Med Case Reports 18 , 229 (2024). https://doi.org/10.1186/s13256-024-04539-7

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Inclusion of the severe and enduring anorexia nervosa phenotype in genetics research: a scoping review

• Sarah Ramsay 1 ,
• Kendra Allison 2 ,
• Heide S. Temples 2 ,
• Luigi Boccuto 1 &
• Sara M. Sarasua 1  

Journal of Eating Disorders volume  12 , Article number:  53 ( 2024 ) Cite this article

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Anorexia nervosa has one of the highest mortality rates of all mental illnesses. For those who survive, less than 70% fully recover, with many going on to develop a more severe and enduring phenotype. Research now suggests that genetics plays a role in the development and persistence of anorexia nervosa. Inclusion of participants with more severe and enduring illness in genetics studies of anorexia nervosa is critical.

The primary goal of this review was to assess the inclusion of participants meeting the criteria for the severe enduring anorexia nervosa phenotype in genetics research by (1) identifying the most widely used defining criteria for severe enduring anorexia nervosa and (2) performing a review of the genetics literature to assess the inclusion of participants meeting the identified criteria.

Searches of the genetics literature from 2012 to 2023 were performed in the PubMed, PsycINFO, and Web of Science databases. Publications were selected per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). The criteria used to define the severe and enduring anorexia nervosa phenotype were derived by how often they were used in the literature since 2017. The publications identified through the literature search were then assessed for inclusion of participants meeting these criteria.

most prevalent criteria used to define severe enduring anorexia nervosa in the literature were an illness duration of ≥ 7 years, lack of positive response to at least two previous evidence-based treatments, a body mass index meeting the Diagnostic and Statistical Manual of Mental Disorders-5 for extreme anorexia nervosa, and an assessment of psychological and/or behavioral severity indicating a significant impact on quality of life. There was a lack of consistent identification and inclusion of those meeting the criteria for severe enduring anorexia nervosa in the genetics literature.

This lack of consistent identification and inclusion of patients with severe enduring anorexia nervosa in genetics research has the potential to hamper the isolation of risk loci and the development of new, more effective treatment options for patients with anorexia nervosa.

Plain English Summary

Anorexia nervosa (AN) is a serious illness with a high death rate. Many of those with AN do not recover and have continuing severe psychological and physical symptoms that greatly impact their quality of life. Research has shown that genetics plays an important role, along with environment, in the development and persistence of AN. This review highlights the continued lack of consensus on defining criteria for severe and enduring AN in the literature and the continued focus on younger females with shorter illness durations in AN genetics research. Greater efforts are needed to include older participants with severe AN of longer duration in genetics research in hopes of developing more effective treatments for this underrepresented group.

Anorexia nervosa (AN) is a devastating illness with a high mortality rate. The standardized mortality ratio (SMR) calculates whether those in a given study population are equally, more or less likely to die compared to a reference population [ 1 ]. With an estimated SMR between 5.9 and 15.9 (i.e., 6–16 times excess mortality), AN is considered one of the deadliest mental disorders [ 2 , 3 ].

Studies indicate that the overall incidence rate for AN has remained relatively stable (4% female lifetime-0.3% male lifetime) since the 1970s [ 2 , 4 ]. The symptomology and presentation of AN have evolved along cultural lines; however, it is not simply a manifestation of modern cultural and social pressures. Accounts of deliberate self-starvation date back to the beginning of written history [ 5 ].

Although the exact etiology of AN is still unclear, a substantial body of evidence indicates that genetics plays a considerable role [ 6 , 7 ]. Genetic studies dating from the late 20th century have shown that AN is highly familial. The lifetime risk of developing AN for female relatives of individuals with AN is 11 times greater than that for female relatives of individuals without AN [ 8 ]. Heritability (h 2 twin ) estimates from twin studies range from ∼ 48–74% [ 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 ]. The large range in estimates may be due to the use of broader participant inclusion criteria in AN studies to increase study group size. Broadening the inclusion criteria results in a more heterogeneous sample and decreased heritability estimates, while narrowing the definition of AN yields higher and more consistent estimates [ 17 ].

Although recovery from AN is possible, for approximately 20% of affected individuals the condition takes on a more intractable phenotype [ 18 , 19 ]. While AN symptoms vary from person to person, it has been suggested that a unique severe and enduring anorexia nervosa (SE-AN) subtype exists; however, aligning on clear defining criteria has proved challenging [ 20 ].

Since the 1980s, a small number of literature reviews of varying breadth and depth have been conducted in attempts to better define SE-AN. The most comprehensive to date, a 2017 review by Broomfield and colleagues identified illness duration and previous unsuccessful treatment as the criteria most often used in the literature to define AN severity [ 21 ]. A 2018 editorial by Hay and Touz, which referenced the Broomfield review, expanded the suggested criterion to include significantly diminished quality of life and narrowed the duration criterion to a minimum of three years and the therapeutic intervention exposure criterion to at least two previous evidence-based treatments [ 22 ]. In a 2021 follow-up review, with the aim of defining a neuropsychological profile for SE-AN, Bloomfield et al. identified intelligence, set-shifting and decision-making as features warranting further attention and noted that additional data are needed to align on defining severity criteria [ 23 ]. In short, there continues to be a lack of consensus on how to best define SE-AN.

Psychiatric illness is often diagnosed in a binary manner; an individual is assessed as either having the illness or not. In reality, due to their complex nature, psychiatric illnesses are better defined on a continuum [ 24 , 25 ]. Genome-wide association studies (GWAS) often use a binary case-control design. However, as Yang et al. [ 26 ] noted, with an equal population sample size, a quantitative trait (for example, symptom severity) association study will have greater power than a case-control association study. The difference is because in a case-control study, an individual with mild symptoms is not differentiated from one with severe symptoms. Relating this to AN, there would be no differentiation between an individual who met the DSM-5 criteria for mild illness, of short duration and who was responsive to first-line treatment, and an individual who met the extreme illness criteria, with a duration of over a decade and lack of positive response to multiple treatment modalities. Delineating participants based on illness severity when performing genetic data analysis of those with AN may improve the chances of identifying significant variants.

The potential value of defining more phenotypically similar groups based on quantitative phenotypes and comorbidities in genetic studies of psychiatric illness has been demonstrated in major depressive disorder (MDD), schizophrenia, autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD) [ 27 , 28 , 29 , 30 ]. Individuals with more severe MDD symptoms have been found to have increased genetic risk for other psychiatric disorders [ 29 ], and polygenic risk scores (PRS) for schizophrenia correlate with symptom severity [ 28 ]. Genetic risk score (GRS), PRS and polygenic score (PGS) are the terms most often used in the literature when referring to values estimating an individual’s lifetime risk of developing a phenotype (disorder) based only on their genetics [ 31 ]. The scores are generated by combining the number of risk alleles at all the risk variants in an individual’s genome. Disease-associated risk variants are based on the latest and most comprehensive GWAS for the disorder at the time of the analysis.

Studies delineating and comparing subgroups of individuals with AN based on defined quantitative criteria may result in the discovery of rare variants associated with symptom severity, and individuals manifesting a more severe phenotype may be more likely to show higher heritability estimates and thus represent a subgroup of patients for which genetics findings may be beneficial. However, this hypothesis cannot be adequately tested to the rigorous standards required without a more precise definition of what constitutes a severe and enduring phenotype, and greater attention given to specifically identifying and including this group in genetic studies [ 32 ].

The aim of this review is to first, as an extension of the Broomfield et al. review [ 21 ], identify the criteria most widely used to describe the phenotypic severity of AN by including articles published since 2017 and, second, evaluate the genetics literature for inclusion of individuals meeting these criteria.

Delineating criteria for the severe and enduring anorexia nervosa phenotype

To better identify and delineate research participants manifesting a severe and enduring phenotype in the genetics literature, it was necessary to discern the most often used defining criteria for this subgroup of AN. The terms Anorexia Nervosa AND severe AND (Enduring OR Chronic) were used, with no year limit, to search titles and abstracts in PubMed, PsycINFO, and Web of Science. Articles were also limited to human subjects.

One of the articles identified was an extensive review by Broomfield et al. of how the literature labeled and defined AN severity up to 2017 [ 21 ]. The current search was limited to articles published after the Broomfield 2017 review to focus on the most recent literature. The references were not required to be attempting to empirically define a severe or enduring anorexia nervosa phenotype. The goal was to determine how those with a longer lasting and more severe clinical presentation are currently referred to in the literature. After removing commentaries on other references, clarifications, and updates from previous studies with the same authors and criteria, redundant references, and those not referring to a severe or enduring anorexia nervosa phenotype, 37 publications remained. Of these 37 publications, there were 22 research papers (6 clinical trials, 16 studies), 4 case reports, 6 expert panel/position papers/or opinion/editorial papers, 2 literature reviews and 3 general reviews. These references are listed in Table  1 , along with a book chapter [ 33 ] identified through reviewing the references of the selected papers, that was not included in the Broomfield 2017 review, bringing the total publications included to 38. The mean age, mean BMI, duration of illness in years, and history of previous treatment, as well as any other measures of illness severity, were extracted from the articles and are shown in Table  1 . A second reviewer, using the RANBETWEEN function in Microsoft Excel, selected 10% of the articles at random from Table  1 . to review for meeting inclusion criteria and accuracy of the data extracted.

Articles were reviewed to determine which criteria are used most often in the literature in regard to the severe enduring phenotype. Specifically, articles with a central purpose of better defining a severe and or enduring/chronic AN phenotype or the need for better treatment options (for example [ 34 , 35 ]), and articles including case studies or participants in one or more study groups defined as having a severe and or enduring/chronic AN phenotype (for example [ 36 , 37 ]) were included. The tabulation from the Broomfield review was combined with the current total. Given that the four Dalton articles referenced the same data, they were counted as only one reference. The results are outlined in Fig.  1 .

Number of references from Table  1 representing the specific duration of illness, number of previous unsuccessful treatments and body mass index (BMI) subgroups indicated either in defining severe and enduring anorexia nervosa or as inclusion criteria for participants. The totals indicated include both the references from the 2017 Broomfield review [ 21 ] and the current work

Literature review: inclusion of participants meeting the severe and enduring AN phenotype in genetics research

The search outlined in this section followed the process depicted in the PRISMA flow diagram [ 38 ] in Fig.  2 , which captures the literature selection flow. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) Checklist was utilized [ 39 ]. The goal was to assess whether participants meeting the criteria identified as the most widely used to define a severe and enduring phenotype are being included in genetics research, and, if included, whether these participants were assessed as an independent group.

PRISMA flow diagram for the literature search

The terms Anorexia Nervosa AND (genetic OR gene OR hereditary) in titles and abstracts were used for the following searches. Articles were limited to human subjects, and review articles were excluded. The goal was to be as inclusive as possible in the initial searches of each database. The search was limited to the last decade of published literature to assess current practices in genetics research. This span of time encompasses the five years leading up to and following the identification of the first genome wide significant locus for AN [ 40 ] and the publication of Broomfield et al., both of which were published in 2017. The inclusion dates were as follows: PubMed, 1-Jan-2012 to 6-Oct-2023 (date of search); PsycINFO, 1-Jan-2012 to 10-Oct-2023 (date of search); and Web of Science, 1-Jan-2012 to 12-Oct-2023 (date of search).

Searches of PubMed, PsycINFO and Web of Science conducted with the search criteria resulted in 240, 206 and 235 hits, respectively. Titles and keywords were reviewed, and 277 articles were eliminated for redundancy (see “identification” in Fig.  2 ). During the first screening, the abstracts for the remaining 404 were reviewed, and 211 were eliminated for the reasons depicted in the PRISMA diagram (“Records selected for Review 1”). The remaining 193 publications progressed to the second screening.

In the second screening, noted as “Records selected for Review 2” in the PRISMA diagram, the methods sections of the remaining 193 articles were reviewed for details on age, psychological assessments, anorexia subtype, duration of illness, prior treatment history, and other indications of disease severity. Studies did not need to specifically call out a subgroup of participants as being severe and or enduring; however, those not including participant data for at least three of the following four criteria were eliminated because they did not provide adequate information for the assessment of participant phenotype severity and intractability: (1) duration of illness; (2) body mass index (BMI); (3) prior treatment history; and (4) severity as measured by one or more clinical, social, or psychological scales. This resulted in the elimination of an additional 115 articles. A total of 78 articles were ultimately included in the information extraction process; the results are presented in Table  2 .

The data were extracted by reviewing both the methods and results sections of each paper for the following participant data: (1) mean duration of illness in years; (2) mean BMI in kg/m 2 ; (3) prior treatment history; (4) and severity as measured by one or more clinical, social, or psychological scales. Participant gender, mean age, and groups of eating disorders included in the studies (i.e., AN-restricting, AN-binge purge, bulimia, binge eating) were also extracted. A second reviewer, using the RANBETWEEN function in Microsoft Excel, selected 10% of the articles at random from Table  2 to review for meeting inclusion criteria and accuracy of the data extracted.

Defining severe enduring anorexia nervosa in the research literature

A review of the literature revealed that the terms severe, chronic, and enduring identified by Broomfield et al., in 2017 [ 21 ] continue to be widely used to label the more intractable AN phenotype. How these labels are defined in the literature, when they are defined, continues to vary greatly. The age of study participants, BMI, duration of illness, and previous treatment history were extracted from each reference and are recorded in Table  1 .

The primary inclusion criteria presented in the articles reviewed were as follows:

The Broomfield review [ 21 ] identified duration as the primary criterion used to define the severe and enduring AN phenotype, and this continues to be true. Several articles reviewed included duration of illness as a criterion for inclusion in their study or clearly delineated a subgroup using duration as one criterion. The stringency of how duration was measured varied.

In their audit of care received by patients with “early stage” versus “severe and enduring” AN, Ambwani et al. [ 36 ] defined a duration of < 3 years for early stage and ≥7 years for severe and enduring AN, as recommended by Robinson et al. and Touyz et al. [ 41 , 42 ]. This was also the case for Calugi et al. [ 43 ], who used ≥7 years in their study of cognitive behavioral therapy effectiveness. The patient described in the case study by Voderholzer et al. [ 44 ] had AN for seven years. In the four papers by Dalton et al. studying the impact of transcranial magnetic stimulation on severe and enduring AN, the duration inclusion criterion for study participation was ≥3 years of AN symptoms [ 45 , 46 , 47 , 48 ]. Whereas Knyahnytska et al. [ 49 ] included a duration of > 5 years as a criterion for treatment resistance in their insula H-coil transcranial stimulation therapy study. In the selection of a subset of participants from the Anorexia Nervosa Genetics Initiative (ANGI) to include in their assessment of the polygenic association of severity and long-term outcome in AN, Johansson et al. [ 50 ] included in their criteria for the severe enduring subtype a ≥ 5 year follow-up time, defined by the authors as years between initial registration and ANGI recruitment. Finally, in two of the three studies evaluating the effectiveness of deep brain stimulation, an illness duration of ≥ 10 years was required for participant inclusion [ 51 , 52 ], with the third requiring > 7 years [ 53 ]. Case study, clinical trial and study participants included in groups indicated as manifesting a severe and enduring phenotype tended to have illness of longer duration. For example, participants in the Calugi et al. [ 43 ] study had a mean duration of 12.3(4.7 SD) years, and the three case study subjects had illness durations of 7 [ 44 ], 11 [ 54 ], 25 [ 55 ], and 26 [ 37 ] years.

Position papers, commentaries, and reviews also varied greatly in defining duration requirements. For example, in their German language case study on palliative care for severe AN, Westermair et al. [ 56 ] proposed a long duration of illness, e.g., 10 years, as a criterion, whereas Hay and Touyz [ 22 ] and Herpetz-Dahlmann [ 57 ] used a duration of > 3 years. Other authors fell between the two extremes; Bianchi et al. [ 58 ] defined severe and enduring AN participants as those who had the disorder for six years or more, and Marzola et al. [ 59 ] used a seven-year demarcation. However, these two papers also proposed that duration should not be used alone when defining AN severity. The usefulness of duration as a criterion was also questioned by Wildes et al. [ 60 ]. In an attempt to define the severe and enduring phenotype empirically, Wildes found no evidence for a chronic subgroup of AN, instead proposing that this group may be better classified on the basis of impact on quality of life and severity of injurious behaviors. As indicated in Fig.  1 , a duration of 7 or more years was used most frequently, followed by 10 years.

Body mass index (BMI):

The DSM-5 defines four levels of AN severity: mild, BMI greater than 17 kg/m 2 ; moderate, BMI of 16–16.99 kg/m 2 ; severe, BMI of 15–15.99 kg/m 2 ; and extreme, BMI of less than 15 kg/m 2 [ 61 ]. Once again, the literature indicates a wide range of BMIs in articles attempting to define severe and enduring AN and/or for participation in studies targeting this group of individuals. The two studies of deep brain stimulation with duration criteria of ≥ 10 years for participation also had BMI requirements falling into the DSM extreme category [ 51 , 52 ]. Deep brain stimulation involves a high degree of risk, and the authors delineated that only individuals with the most severe cases should be included. Similar to duration of illness, participants included in groups indicated as manifesting a severe and enduring phenotype in case studies, clinical trials and studies, tended to have substantially lower BMIs than required per the inclusion criteria. For example, participants in the Bemer et al. bone mineral density (BMD) study had a mean BMI of 12.60 ± 1.60 kg/m 2 , which was well below the < 16 kg/m 2 criteria [ 62 ].

Notably, several studies included a low weight cutoff for participation. For example, in their transcranial magnetic stimulation studies, Dalton et al. [ 45 , 46 , 47 , 48 ] required a BMI > 14 kg/m 2 for participation. The reason provided in the study protocol for the low weight cutoff was “safety precaution” [ 63 ]. The deep brain stimulation studies conducted by Park et al. [ 64 ] required that participants be severely underweight but with a low-weight BMI criterion of > 13 kg/m 2 . Although reasons were not given for the low weight cutoff, they stated that participants needed to have a BMI > 13 kg/m 2 for surgery, which is understandable given its invasive nature.

Again, as with duration of illness, the literature suggests that BMI should not be used as the sole determinant of severity in AN. In their editorial on the challenges of defining severe and enduring AN, Hay and Touyz [ 22 ] recognized the utility of the DSM-5 BMI severity categories but also noted that for those with unremitting AN for a decade or more, having a BMI above the DSM severe range is still associated with marked morbidity.

Psychological assessment:

All the studies reviewed included an assessment of symptoms such as psychological stress, disordered eating, depression, anxiety, obsessiveness, and quality of life. For example, Wildes et al. [ 60 ], used the Research and Development Corporation (RAND) 36-Item Health Survey 1.0 (SF-36) to measure health-related quality of life, and found that these scores better classified AN subgroups than BMI and duration of illness. A score of ≤45 on the Global Assessment of Functioning (GAF) found in the DSM-4, which assesses the severity of mental illness [ 65 ], was used by Oudijn et al. [ 51 ] for inclusion in their deep brain stimulation studies. A plethora of tools was used in assessing eating disorder pathology, with the Eating Disorder Examination Questionnaire (EDE-Q) [ 66 ] and/or various iterations of the EDE-Q being the most prevalent.

Treatment response:

Lack of positive response to prior treatment, variously described as treatment resistance, treatment refractoriness, and failure to respond, was also included in assessing AN severity in several of the articles. The number and type of previous treatments required for inclusion in studies varied. For inclusion in deep brain stimulation studies, Park et al. [ 67 ] required a lack of positive response to ≥2 “typical modes” of treatment, as did Oudijn et al. [ 51 ]. The participant inclusion criteria used by Dalton et al. [ 48 ] for transcranial stimulation studies included the need to have completed at least one “previous course of National Institute for Health and Care Excellence” recommended “specialist psychotherapy or specialist day-patient or inpatient treatment”. The clearest classification criterion for treatment resistance was proposed by Hay and Touyz et al. [ 68 ]: “exposure to at least two evidence-based treatments delivered by an appropriate clinician or treatment facility together with a diagnostic assessment and formulation that incorporates an assessment of the person’s eating disorder health literacy with an assessment of the person’s stage of change”, which was referenced in the reviews of treatment options for those with severe enduring AN by Zhu et al. and Wonderlich et al. [ 20 , 69 ]. In contrast, Smith and Woodside [ 70 ] defined treatment resistance as “patients with two or more incomplete inpatient admissions and no complete admissions”. Emphasis was placed on patients failing to complete treatment rather than the treatment failing to help patients, although the authors did note that approximately 10% of patients treated at their inpatient facility were “unable to benefit”. As indicated in Fig.  1 , the criterion of two or more treatment attempts was most frequently used.

In summary, the literature indicates that a combination of assessments and criteria, including an illness duration of ≥ 7 years, lack of positive response to at least two previous evidence-based treatments, a BMI meeting the DSM-5 for extreme AN, and an assessment of psychological and/or behavioral severity indicating a significant impact on quality of life, were the most prevalent means of defining the severe and enduring AN phenotype. As the DSM-5 includes clear definitions of severe and extreme BMI (15–15.99 kg/m 2 and < 15 kg/m 2 , respectively), the criteria for severe BMI were also used in assessing the genetics literature in the following section.

Inclusion of participants meeting severe enduring anorexia nervosa-defining criteria in studies of anorexia nervosa genetics

The 78 articles identified as meeting the search criteria defined in the methods section were assessed for whether the following inclusion criteria were used and how they were defined:

Duration of illness,

Prior treatment history,

Severity as measured by one or more clinical, social, or psychological scales.

As mentioned previously, neither the statistical strength of the studies nor the study outcomes were assessed, as the purpose was to determine whether genetic studies included those meeting the severe and enduring phenotype criteria defined in the first aim through assessing prevalence of use in the literature. The studies consisted of Genome-Wide Association Studies (GWAS) as well as analyses of polymorphisms, expression, and gene methylation, including but not limited to the leptin ( LEP ) and the leptin receptor ( LEPR ) genes, the fat mass and obesity-associated gene ( FTO ), and the oxytocin receptor ( OXTR ) gene [ 16 , 71 , 72 , 73 ]. The gender of the study participants was also recorded where reported (Table  2 ).

Most of the 78 articles, including those specifically stating that the study was of severe AN, did not include criteria defined in the first aim. Most notably, only one article specifically stated that participants included had at least one prior treatment attempt [ 50 ].

Of the 71 studies reporting mean BMI, the mean BMI for all groups was 15.73 kg/m 2 (SD 1.48). For 15 studies (21%), the mean BMI was > 17 kg/m 2 (mild DSM-5). Sixteen studies (22%) had a mean BMI of 16–16.99 kg/m 2 (moderate DSM-5). Twenty-three studies (32%) had a mean BMI of ≤15.99 kg/m 2 (severe DSM-5), and 17 studies (21.8%) included at least one group with a mean BMI of ≤15 kg/m 2 , required to meet the DSM-5 definition of extreme AN. Only one study included a lifetime minimum BMI of ≤15 kg/m 2 as an inclusion criterion [ 74 ].

The duration of illness and or minimum duration required for inclusion in studies were reported for 23 (29%) of the 78 articles. Of those 23 studies, 3 (13%) had participants with a mean duration of illness ≤ 3 years, 12 (52%) had a mean of 3.1–6.99 years, and 6 (26%) had a mean of ≥ 7 years. Five of the 23 studies required a duration of illness ≥3 years as a participant inclusion criterion. None of the articles identified required duration of illness ≥7 years as an inclusion criterion.

Assessment of psychological stress, disordered eating, depression, anxiety, obsessiveness, and quality of life was another facet of defining the severity of AN in the studies evaluated. Across the 54 studies identifying defined assessment modalities, 38 different tools, checklists and guidelines were used in various combinations, including the following: Hamilton Anxiety Rating Scale (HARS), Clinical Global Impression anxiety scale (CGI), State-Trait Anxiety Inventory form (STAI); depression: Beck Depression Inventory (BDI), Children’s Depression Inventory (CDI), Montgomery-Asberg Depression Rating Scale (MADRS); alexithymia: Toronto Alexithymia Score (TAS); obsessive-compulsive and impulsive symptoms: Young-Brown Obsessive-Compulsive Symptoms (YBC-EDS), Leyton Obsessional Inventory-Child Version (LOI-CV); Barratt Impulsiveness Scale (BIS); and perfectionism: Child and Adolescent Perfectionism Scale (CAPS). Numerous eating disorder assessment tools, including the Eating Disorders Inventory (EDI), Eating Disorder Examination Questionnaire (EDE-Q), Eating Attitudes Test (EAT), and the Structured Interview for Anorexia and Bulimia Nervosa (SIAB) were also used. Table  3 shows a list of tools and how often they were used.

Historically, the focus of AN research has been on teens and young adults. The current assessment found that, of the 71 studies in which the mean age was reported or could be calculated, the mean of the mean ages reported for study participants was 20.9 (4.26 SD) years. Furthermore, the reported mean age of study participants in 36 (51%) of the 71 studies was ≤19.9 years, 21 (30%) had a mean age of 20-24.9 years, 14 (20%) had a mean age of 25-29.9 years, and only one study had an overall group mean age of ≥ 30 years, although eight studies included individual groups with means ≥ 30 years. Figure  3 provides a summary of the BMI, age and duration findings discussed above.

Number of articles in Table  1 representing the body mass index (BMI), age and duration subgroups indicated. NR = Not reported. A. BMI: 71 of the 78 articles reported BMI (kg/m 2 ), 17 of those 71 had participant mean BMI ≤ 15; Age: 72 of the 78 articles reported age, of those 72, one had a mean participant age over 30 years; Duration: 23 of the 78 articles included duration, of those 23, 6 had participant mean illness duration of ≥ 7 years

Incidence rates for AN are reported to be ten times lower in males, although this is considered an underestimation due to underreporting and underdetection [ 2 ]. Only 16 (20%) of the 78 studies included male participants.

Based on the min/max and standard deviations of the mean provided for duration of illness and BMI, it was clear that many of the articles included subsets of individuals meeting the criteria noted herein for severe and enduring AN. However, as data for those specific individuals were often not delineated, it was not possible to determine how the study conclusions may have differed for said subgroups. For example, the mean duration of illness reported by Hernández et al. [ 75 ] for the AN restricting type (AN-R) subgroup was 4.03 (4.44 SD) years, indicating that at least some of the participants met the duration criteria.

Nevertheless, there were examples of results being assessed against some measures of severity, including duration. The Booij et al. study [ 76 ] AN-R group participant duration of illness was 54.9 (30 SD) months; range: 12–84. They specifically assessed methylation against the cumulative duration of illness and observed associations between duration and methylation levels at 142 probes. The mean duration of illness in the AN-R group in the Steiger et al. study [ 77 ] was 96.00 ± 98.91 (12–456) months. They also assessed duration and found an association between chronicity of illness and methylation status at 64 probes mapping to 55 genes.

Other authors evaluated genetic correlation with the severity of various psychological assessments including quality of life, depression, food behaviors, anxiety, and obsessiveness [ 75 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 ]. For example, Acevedo and colleagues found a correlation between specific single nucleotide polymorphisms (SNPs) of the oxytocin receptor gene ( OXTR ), and increased severity of eating disorder symptoms in those with AN [ 78 ]. A polymorphism in the promotor region of the serotonin transporter gene ( 5-HTTLPR ), previously associated with stress and depression [ 91 ], may impact depression and long-term outcomes in those with AN [ 79 ]. Research also suggests a possible correlation between specific haplotypes of the DHEA-producing enzyme cytochrome P450 CYP17A [ 81 ] and the C861 allele of the serotonin receptor 1Dβ gene ( HTR1B ) and severity of anxiety in those with AN.

An example of potential utility in assessing the severe and enduring AN phenotype and the need for larger studies and more funding is the 2022 study by Johansson et al. [ 50 ] evaluating polygenic association with AN severity and long-term outcomes. Here, the authors delineated severe and enduring AN criteria, including duration of illness, clinical impairment, BMI, and having undergone at least one previous treatment attempt. They also specified requirements for the AN subtype, thereby narrowing the population. The study, which included 2843 participants followed for up to 16 years (mean: 5.3 years), provided evidence supporting the possible clinical utility of PGSs for assessing eating disorder risk but also noted the need for larger studies and sample sizes to increase statistical power.

In summary, based on the literature reviewed, genetic studies of AN continue to focus largely, but not exclusively, on younger female participants with shorter durations of illness. These findings are not surprising given that the majority of those diagnosed with AN are female, the lack of clearly defined criteria for severe and enduring AN and the need for large numbers of participants to assess significance in genetics research.

Attempts to provide criteria for labeling those with severe mental illness as chronic or treatment-resistant need to be executed with care, as has been critically reviewed for illnesses such as schizophrenia and depression [ 92 , 93 ]. Care should also be taken when defining criteria for severity of AN, which has a higher mortality rate than depression or schizophrenia [ 94 ]. However, not defining AN severity more clearly and not focusing on a more severe and enduring phenotype in research may decrease the likelihood of identifying the possible underlying biological etiology of AN. As noted by Wonderlich et al. [ 20 ] and responding commentaries by Dalle Grave [ 95 ], Wildes [ 96 ], and McIntosh [ 97 ], a lack of consensus and studies specifically targeting those with severe and enduring AN has resulted in patients being subjected to repetitive employment of largely ineffective treatment strategies resulting in a sense of hopelessness and shame and increasing the risk of suicide [ 98 ]. This review of the literature found that a duration of illness ≥7 years and an unsuccessful response to previous evidence-based treatment were the most common inclusion criteria employed, as were various measures of psychological and physical severity.

AN was once thought to be primarily caused by dysfunctional family dynamics and social and cultural pressures [ 99 ]. We now have evidence that genetics plays a significant role in its etiology. In recent years, there has been an evidence-based push to reconceptualize AN as a metabopsychiatric disorder [ 7 ]. Functional magnetic resonance imaging (fMRI) continues to provide data on the functioning of the brains of those with AN [ 100 ]. The use of large-scale GWAS and genome-wide methylation studies has been gradually revealing the interplay between genetics and environment in AN etiology and persistence, and genetic correlations with other psychiatric disorders [ 16 , 101 , 102 ]. These are all positive advances; however, as evidenced by the individuals included in these studies, female teens and young adults with shorter durations of illness appear to be the primary participants.

Historically, males have been underrepresented in AN research [ 103 ]. Until 2013, the DSM listed amenorrhea as a criterion for AN, thereby reinforcing the notion that AN affects only females [ 61 ]. According to the literature reviewed, males continue to be underrepresented in AN research.

The challenge of recruiting participants for inclusion in large-scale genetic studies of AN is significant. Of the indicated criteria, the most challenging for researchers to assess is the lack of response to prior evidence-based treatment. Most of the treatments described as evidence-based are not administered according to a defined protocol, making retrospective assessment nearly impossible. Furthermore, those with more severe symptoms of longer duration are often treated in a plethora of settings over many years.

For many of the publications, the data indicate that there were participants meeting the criteria defined in the first aim. However, as these individuals were not assessed as a group, it was not possible to determine whether outcomes for this subset may have differed from those with a less severe presentation. The purpose of the publications that either did not perform these assessments or did not report them in their studies was not to delineate this level of detail, so their absence is understandable. One of the reasons for this may be the small number of individuals meeting the criteria for severe and enduring AN, coupled with the need for a large enough “n” to provide any meaningful statistical assessment, which in turn points back to the need for larger studies and additional funding.

Nevertheless, several studies made concerted efforts to focus on a defined severe and enduring phenotype. For example, Kushima et al. [ 74 ] limited their study cohort to those reporting a lifetime lowest BMI < 15 kg/m 2 , with the median for included participants reported as 11.3 kg/m 2 , and a mean age of 37.9 years. The authors specifically stated that they focused on the “severe subgroup of patients because patients with severe symptoms or treatment-resistance are more likely to carry rare deleterious variants of large effect”, citing a schizophrenia study [ 104 ] as support.

The ultimate goal of AN research is to identify contributing factors to the manifestation and intractability of the disease and, in turn, develop superior evidence-based treatments tailored to the patient. Will next generation sequencing gene panels help in the diagnosis of AN [ 105 ]? Kushima et al. [ 74 ] suggested that rare copy number variants associated with neurodevelopmental disorders may correlate with more severe eating disorder subtypes. Is it possible to identify those at higher risk of developing severe and enduring illness earlier and in turn treat those patients based on their specific genetic and environmental circumstances instead of employing generic therapy that may work for most patients with eating disorders but is less effective for those in this cohort? Can artificial intelligence be employed to better identify risk in individuals with AN [ 106 ]? Will we one day regularly employ genetic testing and pharmacogenetics in treating mental illness, including AN [ 107 , 108 ]? Several international projects, including ANGI and the Comprehensive Risk Evaluation for Anorexia Nervosa in Twins (CREAT) are attempting to answer these questions and many more [ 109 , 110 ]. Although these projects do not focus specifically on the severe and enduring phenotype, the availability of in-depth participant health and demographic information paired with genetic analysis should allow for studies of these subsets.

The criteria for evaluating the severity and intractability of AN are evolving, as is the understanding of the disorder. The purpose of a scoping review is to map the literature on an evolving topic and to identify gaps. As such, unlike a systematic review, this review does not attempt to assess the quality of the research conducted, but rather the inclusiveness of study participants. The authors do not attempt to define the severe and enduring phenotype or suggest how the research community should create consensus on the definition. However, by assessing the current literature, we highlight the gaps between the intent to focus on those with severe and enduring AN and the inclusion of this group in published research.

Conclusion and future directions

In conclusion, this review provides an overview of the currently used criteria employed by the research community to define the severity of AN and assesses the last decade of genetics research for the inclusion of study participants meeting these criteria. We found that the following combination of assessments and criteria was used most often in the literature to define AN severity and intractability:

Illness duration of ≥ 7 years.

lack of positive response to at least two previous evidence-based treatments.

A BMI meeting the DSM-5 criteria for extreme AN.

An assessment of psychological and/or behavioral severity indicating a significant impact on quality of life.

We also found, especially in recent years, that there has been an attempt to better define severe and enduring AN in hopes of identifying patients, tailoring treatment, and improving outcomes. However, although a small subset of genetic studies reviewed specifically attempted to focus on a severe and enduring phenotype, there was a lack of aligned defining criteria. Furthermore, there is a continued focus on younger females with shorter disease durations.

Those with AN are often stigmatized, and their shame is amplified by the perception that AN is voluntary or even a lifestyle choice [ 111 , 112 , 113 ]. Those with severe and long-lasting illness are less likely to respond to currently available treatment modalities and have higher levels of mortality [ 20 ]. However, they also represent a subgroup of individuals for which genetic findings may be especially helpful [ 74 ]. Therefore, it is suggested that future genetics studies make a concerted effort to include older participants, those with longer illness durations, and those whose quality of life is most significantly impacted. It is also critically important that more objective, empirically based techniques, such as biomarker and brain structure and function analysis, be developed to more definitively classify the severe and enduring phenotype, which to this point has primarily been categorized through subjective means [ 32 , 60 , 96 , 114 ]. There has been considerable effort in recent years to expand the definition of AN in hopes of being more inclusive and identifying those who may benefit from treatment. However, although expansion has increased the sample size for genetic studies, it could be that focusing on those with longer-lasting and more severe symptomology, even though this is a much smaller group of those with AN, would provide a better chance of identifying the genetic etiology of the disorder. Recent advances have left us far better equipped to make significant progress in developing evidence-based treatments for those with severe and enduring AN. However, these advances require the inclusion of this subgroup in both research and practice.

Limitations

One limitation of the current review is that due to the wide range of similar terminology used to refer to a severe and enduring AN phenotype in the published literature, the searches performed may have left out pertinent articles and viewpoints. Furthermore, although comprehensive for the three electronic databases, the literature search did not include gray literature; thus, information from sources such as dissertations may have been missed.

Data availability

No datasets were generated or analysed during the current study.

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The authors would like to thank Dr. Michael Lutter for his valuable insight and review of the paper.

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Ramsay, S., Allison, K., Temples, H.S. et al. Inclusion of the severe and enduring anorexia nervosa phenotype in genetics research: a scoping review. J Eat Disord 12 , 53 (2024). https://doi.org/10.1186/s40337-024-01009-9

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SYSTEMATIC REVIEW article

Acupuncture therapy on myofascial pain syndrome: a systematic review and meta-analysis.

• 1 Department of Sports Rehabilitation, Southwest Medical University, Luzhou, China
• 2 Department of Psychiatry, Southwest Medical University, Luzhou, China
• 3 Department of Geriatric, Dazhou Central Hospital, Dazhou, China
• 4 School of Clinical Medicine, Southwest Medical University, Luzhou, China
• 5 College of Acupuncture and Tuina and Rehabilitation, Hunan University of Chinese Medicine, Changsha, China
• 6 Department of General Surgery, Dazhou Central Hospital, Dazhou, China
• 7 Department of General Surgery (Hepatopancreatobiliary Surgery), The Affiliated Hospital of Southwest Medical University, Luzhou, China
• 8 Academician (Expert) Workstation of Sichuan Province, Metabolic Hepatobiliary and Pancreatic Diseases Key Laboratory of Luzhou City, The Affiliated Hospital of Southwest Medical University, Luzhou, China

Purpose: Traditional Chinese medicine (TCM) therapies, especially acupuncture, have received increasing attention in the field of pain management. This meta-analysis evaluated the effectiveness of acupuncture in the treatment of myofascial pain syndrome.

Methods: A comprehensive search was conducted across a number of databases, including PubMed, Cochrane Library, WOS, CNKI, WANFANG, Sinomed, and VIP. Furthermore, articles of studies published from the inception of these databases until November 22, 2023, were examined. This systematic review and meta-analysis encompassed all randomized controlled trials (RCTs) on acupuncture for myofascial pain syndromes, without language or date restrictions. Based on the mean difference (MD) of symptom change, we critically assessed the outcomes reported in these trials. The quality of evidence was assessed using the Cochrane Risk of Bias Tool. The study is registered with PROSPERO under registration number CRD42023484933.

Results: Our analysis included 10 RCTs in which 852 patients were divided into two groups: an acupuncture group (427) and a control group (425). The results of the study showed that acupuncture was significantly more effective than the control group in treating myofascial pain syndromes, which was reflected in a greater decrease in VAS scores (MD = −1.29, 95% [−1.65, −0.94], p  < 0.00001). In addition, the improvement in PRI and PPI was more pronounced in the acupuncture group (PRI: MD = −2.04, 95% [−3.76, −0.32], p  = 0.02) (PPI: MD = −1.03, 95% [−1.26, −0.79], p  < 0.00001) compared to the control group. These results suggest that acupuncture is effective in reducing myofascial pain. It is necessary to further study the optimal acupoints and treatment time to achieve the best therapeutic effect.

Systematic review registration: https://www.crd.york.ac.uk/prospero/ , identifier CRD42023484933.

The traditional definition of myofascial pain syndrome (MPS) suggests that regional pain originates from hyperirritable spots located within the taut band of skeletal muscle, referred to as myofascial trigger points (MTrPs) ( 1 ). Myofascial pain syndrome (MPS) is regarded as one of the most prevalent chronic musculoskeletal pain syndromes. The prevalence of MPS may be as high as 85% in pain clinics ( 2 ). Common causes of MPS and dysfunction may include direct or indirect trauma, spinal pathology, exposure to cumulative and repetitive strain, postural dysfunction, and physical disorders ( 3 , 4 ). The pharmacological management of myofascial pain predominantly involves analgesics and muscle relaxants, with nonsteroidal anti-inflammatory drugs (NSAIDs) being the most frequently prescribed medications. Despite the widespread use of oral NSAIDs, there is a dearth of randomized controlled trials (RCTs) specifically assessing their efficacy for myofascial pain syndrome (MPS). Consequently, there exists a paucity of robust evidence regarding the effectiveness of anti-inflammatory drugs in treating MPS. Moreover, caution should be exercised regarding the prolonged use of oral NSAIDs due to potential gastrointestinal, renal, and antiplatelet adverse effects ( 5 ).

Over the past few decades, there has been a notable rise in clinical and scientific attention toward using acupuncture to treat myofascial pain syndrome (MPS). Many clinical studies, especially randomized controlled trials (RCTs), have explored acupuncture’s potential as an intervention for MPS. These studies have consistently demonstrated positive effects of acupuncture in alleviating pain. Several clinical trials and systematic evaluations have indicated that acupuncture can effectively reduce both pain and irritability associated with MPS ( 6 , 7 ). While the precise mechanism of acupuncture for myofascial pain syndrome (MPS) remains to be fully elucidated, mechanistic studies have concentrated on both peripheral and central aspects. Nevertheless, research indicates that acupuncture can suppress pain transmission by reducing substance P (SP) levels and enhancing the release of endogenous opioids ( 8 , 9 ). A recent study revealed that acupuncture enhances strength, function, and locomotor activity in a rat model of muscle pain syndrome through its antioxidant effects ( 10 ). Additionally, another study demonstrated that acupuncture at trigger points modulated gene expression in muscle tissue, consequently promoting muscle regeneration. Regarding the central aspect, some scholars advocate the notion that acupuncture can activate supraspinal and higher centers engaged in pain processing ( 11 ).

Despite the increasing wealth of clinical evidence on the management of myofascial pain in recent years, there is a noticeable absence of more recent meta-analyses focusing on the overall efficacy of acupuncture for this condition. This gap highlights the need for more focused meta-analyses, especially as clinical trials advance. Our proposed meta-analysis aims to fill this void by assessing acupuncture’s effectiveness for myofascial pain using clearly defined outcome measures. The goal of our meta-analysis is to provide valuable insights and information for future clinical treatment strategies, which will be especially helpful for physicians seeking effective approaches to manage myofascial pain.

Search strategy and data mining

For our systematic review and meta-analysis, we searched various literature databases, including PubMed, Cochrane Library, WOS, CNKI, WANFANG, Sinomed, and VIP. The search aimed to identify randomized controlled trials (RCTs) on the effects of acupuncture for myofascial pain syndromes from the inception of each database to November 22, 2023. For the searches, we performed separate searches for acupuncture and myofascial pain, and then combined the results of both searches. We independently conducted a comprehensive review of all relevant published meta-analyses and their reference lists, without imposing any specific limitations on article types. Based on our knowledge, there have been no recent updates on this topic, which supports our claim. The search strategies used in this study are extensively detailed in Supplementary File 1 .

Literature selection

Our inclusion criteria for the retrieved studies were as follows: (1) Diagnosis of “myofascial pain syndrome” based on clear diagnostic (inclusion) criteria ( 12 – 14 ). The patient’s diagnosis was not influenced by other co-morbidities. (2) In these trials, the treatment modality in the experimental group was acupuncture added to the control group. The manipulation and specific acupuncture points used in research are not limited. (3) Any type of control group can be considered as a control group, including traditional western medicine control group, routine care control group and blank control group. (4) Outcomes: Evaluation of the quality of pain management should include at least one of the following scales: 1. Pain Rating Index (PRI). 2. Present Pain Intensity (PPI). 3. Visual Analog Scale (VAS) scores. 4. Efficacy of diagnostic and therapeutic criteria for TCM syndromes. 5. Efficacy of clinical research guidelines for TCM (new medicines) or other meta-analyses referring to extrapolable data on myofascial pain syndromes. 6. The validity of the analysis. Exclusion criteria: patients with one or more other types of pain in addition to myofascial pain syndrome; other interventions such as moxibustion, transcutaneous electrical nerve stimulation, acupoint injections, etc. were used in the study; the paper was only an abstract or review; the study did not have outcome indicators; or the complete literature was not available.

Data collection

All exclusion and inclusion criteria will be discussed and determined by all researchers prior to the start of the study. At the formal start of the screening phase, each of the two researchers will independently review all study titles and abstracts according to the criteria discussed beforehand, exclude obviously irrelevant literature, and then read the full text of the screened articles. After further screening, the final literature for inclusion was identified, and then the basic information of the articles was extracted along with the data for the set endpoints without knowledge of each other’s review. Finally, the results were cross-checked. When the results of two researchers conflicted, a third researcher stepped in to resolve the disagreement. In the extraction of basic information and data, we mainly recorded the authors of the article and the time of the study, the age of the samples included in the study, the duration of myofascial pain, the number of samples, the measures of the intervention and the control group, the site of pain and the time of application of acupuncture. For the outcome indicators, the values of the primary and secondary outcome indicators were extracted and recorded.

Quality assessment

We assessed bias in the randomized controlled trials included in the review by means of the Revised Cochrane Risk of Bias Tool (RoB-2) ( 15 ). We scored high, medium and low risk based on the risk entries after reading the full text of the included studies, and the specific criteria for each score will refer to Cochrane’s meta-analysis criteria, and then presented the results of our comprehensive bias assessment through the use of Revman 5.4 software, which graphically and clearly depicts the possible bias in these trials, helping us to clearly understand the specific quality and potential risk of the included articles.

Statistical analysis

Revman software for meta-analysis. Visualization was achieved through forest plots. Statistical analyses were performed using mean difference (MD), and heterogeneity was assessed using the I 2 index. When the effects showed heterogeneity (I 2 > 50%), the analysis was performed using a random-effects model; when the data showed homogeneity, the analysis was performed using a fixed-effects model ( 16 ).

Search results

Initially, a total of 6,234 potential research articles were identified through our search using the designated terms. We then excluded 2,876 duplicate studies using EndNote 20 software. After reviewing titles and abstracts, we identified 2,690 articles that were not relevant to the study and excluded them. In addition, we excluded 300 articles because they were reviews or conference materials. We then thoroughly examined the full text of the remaining 367 articles. Of these, 357 articles were excluded for reasons such as being retrospective studies or not related to acupuncture for myofascial pain symptoms. Ultimately, after careful review, a total of 10 clinical studies met the criteria and were deemed suitable for inclusion in the meta-analysis ( 17 – 26 ) ( Figure 1 ).

Figure 1 . Flow diagram showing the screening and selection process of reports to be included in the meta-analysis.

Characteristics of the included studies

A total of 852 patients were included in the 10 trials, including 427 in the acupuncture group and 425 in the control group ( 17 – 26 ). Of the 10 studies, seven groups were treated with direct acupuncture ( 17 , 19 , 21 – 25 ), and three studies used acupuncture and massage ( 18 , 20 , 26 ). In five studies, the control group used medication for oral treatment ( 18 – 21 , 26 ). Several other studies one used rehabilitation ( 17 ), one used lidocaine injections ( 22 ), one used McKenzie therapy. The remaining two studies control group was treated with herbal medicine ( 23 , 24 ). For the diagnosis of myofascial pain syndrome, 3 studies used the Pain Science ( 19 , 21 , 22 ). The diagnostic criteria were: the diagnostic criteria were categorized into major and minor criteria, and five major criteria and at least one minor criterion were met to diagnose MPS. Primary criteria: (1) complaints of regional pain; (2) sensory abnormalities in the area of expected distribution of the complaints of pain or trigger point tenderness; (3) palpable tension zone in the affected muscle; (4) intense point tenderness at a point within the tension zone; (5) some degree of restriction of movement during measurement. Secondary criteria: (1) repetition of the complained clinical pain or sensory abnormality at the pressure point; (2) localized twitch response induced by lateral grasping or needle insertion into the trigger point of the band; (3) relief of pain by stretching the muscle or injecting the trigger point. Three studies used the Criteria for Diagnosis and Efficacy of Diseases in Traditional Chinese Medicine ( 19 , 22 , 25 ), and four studies used other criteria such as the Guiding Principles for Clinical Research of New Traditional Chinese Medicines, and Surgical Treatment of Cervical Spine Disease ( 17 , 23 , 24 , 26 ). Six of the 10 studies treated neck and shoulder myofascial pain ( 17 – 20 , 25 , 26 ) and four studies were on low back myofascial pain ( 21 – 24 ). Table 1 shows the main characteristics of the included studies: including the sample sizes of the two groups, the ages of the included patients, the treatments used in the treatment group, the treatments used in the control group, and the duration of myofascial pain syndrome. Regarding the efficacy criteria of the included studies, eight studies assessed the VAS ( 17 – 23 , 26 ), four studies assessed the PPI and PRI scores ( 19 , 20 , 22 , 23 ), and nine studies assessed the efficacy of the treatments using the treatment criteria of TCM evidence ( 17 – 25 ). Table 2 shows the outcome indicators of the included studies.

Table 1 . Characteristics of included studies.

Table 2 . Data on outcome indicators included in the study.

The methodological assessment results are depicted in Figure 2 . Out of the 10 studies employing random allocation methods, 9 were appraised as low risk due to the utilization of a randomized table of numbers ( 17 , 19 – 26 ), while 1 study was deemed to have an unclear risk of bias due to inadequate information ( 18 ). None of these studies provided sufficient detail about the allocation concealment process to warrant a clear risk of bias judgment. Similarly, none of them involved blinding of subjects or administrators due to notable discrepancies in acupuncture treatment utilization between the treatment and control groups. All studies were found to have complete outcome data with a low risk of bias ( 17 – 26 ). Six studies were classified as having a low risk of bias for selective reporting ( 17 – 19 , 21 – 23 ), as they reported all prespecified endpoints. Conversely, four studies were identified as having a high risk of bias for selective reporting due to poor endpoint reporting ( 20 , 24 – 26 ). Additionally, insufficient data were available in the 10 studies to assess other risks of bias.

Figure 2 . The figure represents the risk of bias assessment for the studies selected in the meta-analysis.

Results of individual studies

Main outcome indicators, visual analog scale (vas).

The Visual Analog Scale (VAS) is a commonly used tool for assessing pain intensity. It consists of a horizontal or vertical line, usually 10 centimeters in length, with anchor points at each end representing the extremes of pain intensity (e.g., “no pain” to “worst pain imaginable”). Patients are asked to mark on the line the point that best represents their current level of pain. The distance from the “no pain” end of the line to the patient’s mark is measured and recorded, providing a numerical value that represents the intensity of the pain experienced by the patient. The VAS score can range from 0 to 10 or from 0 to 100, with higher scores indicating greater pain intensity. A total of 8 articles assessed VAS scores in 694 patients, 348 in the acupuncture group and 346 patients in the control group ( 17 – 23 , 26 ). Notably, VAS values were significantly lower in patients who underwent acupuncture treatment than in the control group. Due to substantial heterogeneity among these studies (I 2  = 98%, p  < 0.00001), we employed a random-effects model. The combined results, as depicted in Figure 3 , revealed a statistically significant difference in VAS scores (MD = −1.29, 95% CI [−1.65, −0.94], p < 0.00001). These findings indicate that the acupuncture treatment group exhibited greater improvement in myofascial pain compared to the control group To ensure the stability of our findings, we excluded each study and observed the changes in the combined results after exclusion. We found that the results showed consistency after the exclusion of each study, which demonstrated the stability of our conclusion that the acupuncture group had a significantly lower VAS than the control group after treatment. Therefore, we can state that for myofascial pain, acupuncture treatment is effective in reducing the pain level of patients compared to the control group.

Figure 3 . The figure represents a forest plot of the meta-analysis for Visual analog scale (VAS). Each row represents a study and lists the name of the study, the mean systolic blood pressure and standard deviation for the acupuncture and control groups, the sample size, and the mean difference and its 95% confidence interval.

To ensure the accuracy of the results, we performed subgroup analyses for the different acupuncture interventions in the treatment groups (acupuncture, acupuncture combined with massage) ( Figure 4 ). Acupuncture combined with massage treatments were mainly based on rubbing and pressing on the affected acupoints on the basis of acupuncture, and crossing the hands to squeeze and knead the patient’s painful areas of the tendons in front of and behind the muscles. The results showed that there was a statistical effect of both acupuncture and acupuncture combined with massage on the outcome of myofascial pain ( p  < 0.00001) and there was no heterogeneity between the two groups (I 2  = 0%). To further investigate the treatment of myofascial pain with acupuncture, we performed a subgroup analysis of patient age and pain site, which showed that differences in patient age and pain site did not affect the results, and there was no heterogeneity between the different subgroups. The results of the subgroup analysis showed the robustness of the results of acupuncture for myofascial pain.

Figure 4 . Figure shows a forest plot of subgroup analyses of the visual analog scale (VAS). (A) Subgroup analyses regarding different interventions. (B) Subgroup analyses of patient age. (C) Subgroup analyses of different pain sites.

Secondary outcome indicators

Pain rating index (pri).

The Pain Rating Index (PRI) is a component of the McGill Pain Questionnaire, a widely used tool for assessing the quality and intensity of pain. The PRI consists of 78 pain descriptors divided into 20 groups, each representing a different quality of pain (such as throbbing, shooting, stabbing, etc.). Patients are asked to indicate which words best describe their pain, and each selected word is assigned a numerical value based on its rank in the group (e.g., the first word selected is assigned a value of 1, the second word a value of 2, and so on). The PRI score is calculated by summing the numerical values of all selected words, providing a measure of the overall intensity of pain descriptors chosen by the patient. A total of 4 articles evaluated PRI scores in 330 patients, 166 in the acupuncture group and 164 patients in the control group ( 19 , 20 , 22 , 23 ). Notably, PRI values were significantly lower in patients who underwent acupuncture treatment than in the control group. Due to the significant heterogeneity between these studies (I 2  = 99%, p  < 0.00001), we used a random effects model for the analysis. The results of the combined analysis showed ( Figure 5 ) that there was a significant difference in PRI between the acupuncture group and the control group (MD = −2.04, 95% CI [−3.76, −0.32], p  = 0.02), suggesting that acupuncture treatment was more effective in improving myofascial pain. To ensure the stability of our findings, we excluded each study and observed the changes in the combined results after exclusion. We found that the results showed consistency after the exclusion of each study, which demonstrated the stability of our conclusion that the acupuncture group had a significantly lower PRI than the control group after treatment. Therefore, we can state that for myofascial pain, acupuncture treatment is effective in reducing the pain level of patients compared to the control group.

Figure 5 . The figure represents a forest plot of the meta-analysis for Pain rating index (PRI).

Present pain intensity (PPI)

Present Pain Intensity (PPI) is a scale used to assess the current level of pain experienced by an individual. It is commonly used in clinical settings and research studies to quantify pain intensity at a specific point in time. The PPI scale typically ranges from 0 to 10, with 0 indicating no pain and 10 indicating the worst possible pain. Patients are asked to rate their current pain level on the PPI scale, providing a subjective measure of their pain intensity. This rating can be used to monitor changes in pain over time, assess the effectiveness of pain management interventions, and guide treatment decisions. A total of 4 articles evaluated PPI scores in 330 patients, 166 in the acupuncture group and 164 patients in the control group ( 19 , 22 , 23 ). Notably, PPI values were significantly lower in patients who underwent acupuncture treatment than in the control group. Due to the significant heterogeneity between these studies (I 2  = 95%, p  < 0.00001), we used a random effects model for the analysis. The results of the combined analysis showed ( Figure 6 ) that there was a significant difference in PPI between the acupuncture group and the control group (MD = −1.03, 95% CI [−1.26, −0.79], p < 0.00001), suggesting that acupuncture treatment is more effective in improving myofascial pain. To ensure the stability of our findings, we excluded each study and observed the changes in the combined results after exclusion. We found that the results showed consistency after the exclusion of each study, which demonstrated the stability of our conclusion that the acupuncture group had a significantly lower PPI than the control group after treatment. Therefore, we can state that for myofascial pain, acupuncture treatment is effective in reducing the pain level of patients compared to the control group.

Figure 6 . The figure represents a forest plot of the meta-analysis for Present pain intensity (PPI).

Diagnostic efficacy criteria for Chinese medicine diseases

Nine studies evaluated the efficacy of acupuncture treatment involving 752 patients ( 17 – 25 ), and the efficacy was assessed according to the Criteria for Diagnosis and Efficacy of Traditional Chinese Medicine (TCM) Conditions for Myofascial Pain Syndrome. Cure: Symptoms and signs disappear and the patient is able to return to normal work. Significant effect: disappearance of signs and symptoms, no limitation of activity, only pain and discomfort. Effective: improvement of symptoms, reduction of pain, mild limitation of activity; Ineffective: no improvement of symptoms and signs. We combined the cure rate and the significant efficiency rate into the significant efficiency rate. In terms of significant efficacy, we used a fixed-effects model given the low heterogeneity that existed between these studies (I 2  = 14%, p  = 0.32). The results indicate ( Figure 7A ) that the combined treatment shows a significant statistical difference compared to the control group (RR = 1.35, 95% CI [1.21, 1.51], p  < 0.0001). There was no significant heterogeneity among the studies in terms of overall efficacy (I 2  = 0%, p  = 0.52), and we employed a fixed-effect model for analysis. The results show ( Figure 7B ) that the combined results also exhibit significant statistical significance compared to the control group (RR = 1.12, 95% CI [1.06, 1.18], p < 0.0001). The efficacy rates and overall effectiveness indicate that the acupuncture treatment group is more effective in treating myofascial pain compared to the control group.

Figure 7 . (A) The graph shows a forest plot of significant efficacy rates. (B) The graph shows a forest plot of total efficacy rates for the treatment of myofascial pain syndromes.

Acupuncture stands as one of the commonly utilized alternative therapies. Despite its unclear mechanism of action, the prevailing consensus suggests that acupuncture elicits systemic responses, particularly within the nervous system, through physical stimulation of specific points on the body’s surface. This stimulation regulates bodily functions, ultimately yielding therapeutic effects ( 27 , 28 ). The publication of various controlled trials has demonstrated acupuncture’s significant efficacy in managing pain syndromes, including acute and chronic low back pain, osteoarthritis of the knee, headaches, myofascial pain, neck pain, and fibromyalgia. Numerous studies have indicated that acupuncture analgesia can be initiated through the stimulation of high-threshold, small-diameter nerves in the muscles ( 29 ). These nerves are able to send messages to the spinal cord, which then activates neurons in the spinal cord, brainstem (the gray area around the aqueduct), and hypothalamus (arcuate), which in turn triggers the endogenous opioid mechanism ( 30 – 32 ). A study has shown that pressure-point acupuncture has an analgesic effect and that the intensity of the stimulus may depend on various parameters, such as the procedure, needle size and insertion site. Pressure-point insertion of needles affects sensitized injury receptors, whereas non-pressure-point insertion does not. Pressure pain points are sites where injury receptors (e.g., multimodal receptors) are sensitized by various factors. Moxibustion stimulation of pressure points activates the sensitized multimodal receptors, thereby relieving pain ( 33 ). It is also because of its role in myofascial pain that acupuncture is recommended as a treatment option for myofascial pain ( 34 ). The results of our meta-analysis showed that acupuncture significantly outperformed the treatment regimen in the control group. This superiority was reflected in lower VAS scores, lower PRI and PPI scores, and higher treatment efficacy in the acupuncture group, and these differences were statistically significant. In order to compare acupuncture therapy and drug efficacy in more depth, we performed a subgroup analysis based on the differences between the treatment protocols of the control group and the acupuncture group, a step taken to explore whether the differences in the treatment groups would affect the reliability of the results, which showed that the different interventions demonstrated good therapeutic effects. Subsequently, subgroup analyses were performed according to the age and pain site of the patients in the different studies. In terms of safety, it is noteworthy that no serious adverse effects were reported in any of the studies, which highlights the fact that acupuncture treatment has a good safety record ( 35 ).

While our research findings suggest that the combination of acupuncture and medication is more effective than medication alone for myofascial pain, it is important to acknowledge the limitations of our study. There is significant heterogeneity among the included studies, likely due to differences in the implementation of clinical trials, such as variations in acupuncture point selection, treatment duration and techniques, as well as differences in the types and dosages of medication used in control groups. To comprehensively assess the clinical efficacy of acupuncture in alleviating myofascial pain, future studies should prioritize large-sample, multicenter randomized controlled trials using recognized reliable study designs. We also observed that adverse effects were not systematically studied and documented in the included studies, highlighting the need for future research to verify efficacy. Furthermore, these studies should standardize acupoint selection and treatment methods based on evidence-based principles of traditional Chinese medicine to enhance comparability between treatment studies and facilitate more effective treatments. Additionally, efforts are needed to develop clinical acupuncture treatment protocols that are both efficacious and feasible. This will contribute to the development of evidence-based clinical practice guidelines. Finally, it is important to note that due to the many limitations present in this paper, an updated meta-analysis will be necessary in the future as more clinical trials are conducted. Incorporating higher-quality original studies can provide results with a higher degree of confidence.

Our study revealed an important finding: the acupuncture group showed significant improvements in VAS scores, PPI and PRI scores, and treatment efficiency compared to treatment with medication alone. This finding provides a solid theoretical basis for the treatment of myofascial pain syndrome with acupuncture. Nevertheless, given the limitations of the existing literature, there is an urgent need for more rigorous and reliable clinical trials to further validate this finding. It may be necessary to conduct an in-depth analysis of different acupoints and intervention times to better explore the factors affecting efficacy.

Data availability statement

The original contributions presented in the study are included in the article/ Supplementary material , further inquiries can be directed to the corresponding authors.

Author contributions

JX: Writing – original draft, Validation, Formal analysis, Data curation, Conceptualization. XZ: Writing – original draft, Methodology, Formal analysis, Data curation. XL: Writing – original draft, Validation, Project administration, Methodology, Data curation. XG: Writing – original draft, Investigation, Data curation. LJ: Writing – original draft, Investigation, Conceptualization. QL: Writing – original draft, Methodology, Investigation. SZ: Writing – original draft, Project administration, Conceptualization. CJ: Writing – original draft, Project administration, Data curation, Conceptualization. TP: Writing – original draft, Validation, Data curation, Conceptualization. JL: Writing – original draft, Methodology, Funding acquisition, Conceptualization. JZ: Writing – review & editing, Writing – original draft, Methodology, Funding acquisition, Conceptualization. BL: Writing – review & editing, Writing – original draft, Software, Project administration, Methodology, Funding acquisition. HC: Writing – review & editing, Writing – original draft, Visualization, Validation, Software, Conceptualization.

The authors declare financial support was received for the research, authorship, and/or publication of this article. The study was funded by Sichuan Medical Association Project (S21048), Science and Technology Department of Sichuan Province project (2022YFS0256), Bethune Medical Science Research Fund (19007), and Sichuan Provincial Administration of Traditional Chinese Medicine project (2020LC0107).

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fneur.2024.1374542/full#supplementary-material

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Keywords: acupuncture, myofascial pain syndrome, complementary and alternative therapies, pain, traditional Chinese medicine

Citation: Xiong J, Zhou X, Luo X, Gong X, Jiang L, Luo Q, Zhang S, Jiang C, Pu T, Liu J, Zhang J, Li B and Chi H (2024) Acupuncture therapy on myofascial pain syndrome: a systematic review and meta-analysis. Front. Neurol . 15:1374542. doi: 10.3389/fneur.2024.1374542

Received: 22 January 2024; Accepted: 22 April 2024; Published: 03 May 2024.

Reviewed by:

Copyright © 2024 Xiong, Zhou, Luo, Gong, Jiang, Luo, Zhang, Jiang, Pu, Liu, Zhang, Li and Chi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Jun Zhang, [email protected] ; Bo Li, [email protected] ; Hao Chi, [email protected]

† These authors have contributed equally to this work

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

• Open access
• Published: 01 May 2024

Low-cost otolaryngology simulation models for early-stage trainees: a scoping review

• Joselyne Nzisabira 1 , 2   na1 ,
• Sarah Nuss 1 , 3   na1 ,
• Estephanía Candelo 1 , 4 , 5 ,
• Ernest Aben Oumo 1 , 2 ,
• Keshav V. Shah 1 , 6 ,
• Eric K. Kim 1 , 7 ,
• Joshua Wiedermann 1 , 8 ,
• Ornella Masimbi 2 ,
• Natnael Shimelash 2 &
• Mary Jue Xu 1 , 7 , 9  

BMC Medical Education volume  24 , Article number:  483 ( 2024 ) Cite this article

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Medical simulation is essential for surgical training yet is often too expensive and inaccessible in low- and middle-income countries (LMICs). Furthermore, in otolaryngology-head and neck surgery (OHNS), while simulation training is often focused on senior residents and specialists, there is a critical need to target general practitioners who carry a significant load of OHNS care in countries with limited OHNS providers. This scoping review aims to describe affordable, effective OHNS simulation models for early-stage trainees and non-OHNS specialists in resource-limited settings and discuss gaps in the literature.

This scoping review followed the five stages of Arksey and O’Malley’s Scoping Review Methodology. Seven databases were used to search for articles. Included articles discussed physical models of the ear, nose, or throat described as “low-cost,” “cost-effective,” or defined as <$150 if explicitly stated; related to the management of common and emergent OHNS conditions; and geared towards undergraduate students, medical, dental, or nursing students, and/or early-level residents.

Of the 1706 studies screened, 17 met inclusion criteria. Most studies were conducted in HICs. Most models were low-fidelity (less anatomically realistic) models. The most common simulated skills were peritonsillar abscess aspiration and cricothyrotomy. Information on cost was limited, and locally sourced materials were infrequently mentioned. Simulations were evaluated using questionnaires and direct observation.

Low-cost simulation models can be beneficial for early medical trainees and students in LMICs, addressing resource constraints and improving skill acquisition. However, there is a notable lack of contextually relevant, locally developed, and cost-effective models. This study summarizes existing low-cost OHNS simulation models for early-stage trainees and highlights the need for additional locally sourced models. Further research is needed to assess the effectiveness and sustainability of these models.

Question: What is the current landscape of low-cost otolaryngology-head and neck surgery simulation for early medical trainees and students?

Finding: In this scoping review we identified 17 studies that met inclusion criteria. Most studies were developed in high-income countries, and most models were not locally sourced.

Meaning: There is a notable lack of low-cost OHNS simulation models that are relevant for early medical trainees and students.

Peer Review reports

Introduction

Medical simulation is a valuable component of training [ 1 ]. Historically, simulation usage has been predominantly centered in high-income countries (HICs). Consequently, there exists an opportunity to expand access to simulation education in low- and middle-income countries (LMICs) [ 2 , 3 ]. While low-cost simulation models have been explored in HICs, the specific models used in these settings may not be applicable to LMICs due to lacking the same resources. Studies have demonstrated that using locally sourced materials and readily available devices is cost-effective [ 4 ]. Furthermore, low-fidelity, or less anatomically realistic, simulation may confer similar benefits compared to high-fidelity, or highly anatomically realistic, simulation though with lower costs [ 5 , 6 ]. Despite the potential benefits of simulation in LMICs, there is limited literature, particularly for surgical specialties where workforce shortages, ethical considerations, and financial constraints limit opportunities for practice [ 7 ].

In otolaryngology-head and neck surgery (OHNS), simulation training has an opportunity to address the burden of disease centered in LMICs through training of general practitioners (GPs) and primary care providers in regions where subspecialists are limited. The burden of OHNS disease is high, with 1.5 billion people worldwide experiencing hearing loss, primarily in LMICs [ 8 ]. Paradoxically, low-income countries have 50 times fewer OHNS providers than high income countries [ 9 ]. Given the burden of OHNS disease far outweighs the current number of providers, it is imperative to train primary healthcare provider to help increase access to essential OHNS care. Simulation is a central component of many HIC OHNS training programs [ 10 , 11 , 12 , 13 ], [ 14 ], ; however, many models are largely directed at the skill set of senior residents and physicians. Given that primary care providers such as GPs in LMICs may be the first or only providers available in rural or first-level hospitals, the opportunity to develop skills that are critical for managing OHNS emergencies and common conditions is essential to developing confidence and preventing morbidity and mortality.

To address the gap in simulation models for primary care practitioners in common and emergent OHNS conditions, this scoping review aims to describe and evaluate available low-cost OHNS simulation models geared toward early-stage medical trainees or GPs.

Study design

Given limited and heterogenous literature, a scoping review was selected and conducted in February 2023 in accordance with Arksey and O’Malley’s Scoping Review Methodology and following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) Extension for Scoping Reviews Guidelines [ 15 , 16 ]. The search strategy aimed to address the research question regarding the outcomes of using low-cost OHNS simulation models for early-stage trainees in education.

Literature search

A search strategy was developed to capture the maximal results, which included the main search concepts of “simulation,” “otolaryngology,” “education,” and “low cost.” These terms were combined using Boolean operators OR (within critical constructed concepts) and AND (between key concepts). The specific search strategy was adapted to each data base. The search was conducted in the following databases: PubMed, MEDLINE, EBSCO, Scopus, Science Direct, CINAHL, EMBASE, and Web of Science (Supplemental Table 1 ).

Inclusion criteria included studies of any language that discussed the development or implementation of a physical model of the ear, nose, or throat that were explicitly described as “low-cost,” “cost-effective,” or defined as <$150 if explicitly stated related to the care or management of OHNS conditions (operative or non-operative). Models were only considered if they were applicable for training of undergraduate students, medical, dental, or nursing students, and/or early-level residents, and we excluded simulations that would not be applicable to a GP (i.e., advanced OHNS resident level skills). Original research of any study type was included. Letters to the editor, abstracts, systematic reviews, virtual reality simulations, electronic simulations, and studies that utilized mannequin models were not included.

The study team completed a primary title and abstract screening using a Covidence database (Veritas Health Innovation Ltd, Melbourne) based on the search criteria. Two reviewers each independently screened the titles and abstracts of all identified articles for relevance to the research question. A third independent reviewer resolved disagreements over article eligibility. In the full-text review, data was extracted and recorded following the Arksey and O’Malley’s “descriptive-analytical” approach for data extraction, and the information was summarized from selected articles on an Excel spreadsheet [ 15 ]. At least two authors reviewed extracted data from the included articles. A third reviewer resoled any remaining conflicts. Snowball sampling was used to identify gray literature from study reference lists.

Statistical analysis

Outcomes included study characteristics (authors, year, language, journal of publication, study design), context (study country, target population) simulation details (specialty of simulation model, cost, fidelity of model, materials used, local sourcing of materials, condition being simulated), and model evaluation (evaluation of surgical skill and efficacy of model). Summary statistics were performed using Microsoft Excel. Categorical variables were presented as counts and percentages n(%). There were no continuous data.

The initial search returned 3355 studies. After 1649 duplicates were removed, 1706 studies underwent title and abstract screening. Of these, 1607 were excluded. Ninety studies were screened for full text review based on inclusion and exclusion criteria. Seventy-four studies met inclusion criteria (Fig.  1 ). Table  1 provides an overview of the included low-cost simulation models for essential OHNS conditions.

PRISMA Flow diagram of data analysis procedure

Characteristics of studies

Of the studies examined, 82% ( n  = 14) of studies were conducted in HICs, and the majority were conducted in the United States or in the United Kingdom (Fig.  2 ). 94% ( n  = 16) of the studies utilized a cross-sectional study design. Most articles targeted general OHNS care ( n  = 8, 47%). 35% ( n  = 6) of the models were low-fidelity models (less anatomically realistic). The characteristics of the studies are summarized in Table  2 . Simulation fidelity was assessed using the Simulation Fidelity (SiFi) scale, a validated 6-point scale to describe simulation fidelity across five domains, with scores of 0–1 meaning low-fidelity, 2–3 meaning medium fidelity, and 4–5 meaning high fidelity (Table  3 ) [ 17 ].

Global distribution of Low-Cost ENT Simulation Model Studies

Reflexivity Statement

This scoping review emerged from collaborative work within the Global OHNS Initiative involving LMIC and HIC researchers. This piece was written to promote more accessible and equitable avenues to education and training for LMIC researchers. Our authorship group consists of five LMIC authors and five HIC authors. Five of the ten authors are women. All authors contributed substantially to the conception, drafting, and revision of this piece. All authors approved the final version. Everyone has agreed to be accountable for all aspects of the work, aligning with ICJME Authorship Criteria

The most common simulated skills were peritonsillar abscess aspiration ( n  = 6, 35%), cricothyrotomy ( n  = 4, 24%), myringotomy with tube placement ( n  = 2, 12%), and other ear models (2, 12%). Nasal packing ( n  = 1, 6%), auricular hematoma ( n  = 1, 6%), and tracheostomy care ( n  = 1, 6%) were also included.

One (6%) study was geared towards medical students, eight (47%) towards residents, two (12%) towards both medical students and residents, one (6%) towards nurses, one towards anesthesia students, and one (6%) towards paramedics. Out of the eight resident-focused models, three were geared towards emergency medicine residents. Two (12%) models were geared towards attendings or consultants, and both models were included given the models’ transferability to simulate other more basic skills.

Eleven (65%) models reported a dollar value associated with their model. The average price per model was $52.00 USD (range: $10 - $150). Prices were all converted directly to USD and were standardized to a 2024 estimated cost. The remaining models were described as “low-cost” by authors without specific information about the cost of the materials. Fifteen (88%) studies reported using locally sourced materials. Model reusability is reported in Table  1 .

Simulation evaluation

Sixteen (94%) studies assessed model efficacy. Models were evaluated using both questionnaires ( n  = 8, 47%), direct observation of skills ( n  = 4, 24%), or both ( n  = 4, 24%). Three of the eight studies that included direct observation (38%) used video monitoring to evaluate clinical skill. Participant questionnaires included a variety of themes such as participants’ comfort with the skill, model realism, ease of use, and participant confidence performing the skill.

Given the substantial burden of OHNS disease worldwide and current limited OHNS workforce, simulation training tools tailored for primary care providers are critical in developing OHNS knowledge and skills to increase access to OHNS care globally [ 8 , 9 ]. Existing low-cost OHNS simulations primarily target residents and consultants and can often overlook the essential skill set required by GPs [ 18 , 19 ]. These skills encompass emergent and common OHNS conditions such as epistaxis, emergent surgical airway, and ear and nose foreign body removal. Equipping medical students and early-trainees with basic OHNS care skills is vital. This type of task shifting can alleviate delays in care, transportation challenges, and alleviate the burden on tertiary centers.

This is the first study to evaluate low-cost OHNS simulations tailored to GPs and early-trainee education, emphasizing locally sourced models. The low number of studies identified in this review highlights that simulations addressing the skill set of early trainees and primary care providers is an area for future educational research depending on regional needs and resource availability. Our findings describe the available low-cost simulations in OHNS and highlights insufficient availability of such models. Future work should focus on developing additional low-cost, contextually appropriate models to bridge gaps in healthcare training and delivery in resource-constrained settings.

A variety of approaches have been employed to develop low-cost OHNS simulation models. For instance, studies such as those by Chudek et al. (2021, UK) and Taylor et al. (2014, USA) utilized inexpensive materials like latex gloves, custard, and latex moulage for simulating peritonsillar abscess aspiration [ 1 , 2 ]. These models offer a cost-effective solution for training primary care providers in essential procedures.

Conversely, studies such as Bright et al. (2021, India) and Bhalla et al. (2021, UK) employed thermoplastic ray cast and cork as materials for nasopharyngeal swabbing and peritonsillar abscess aspiration simulations, respectively [ 3 , 4 ]. While these models may have slightly higher initial costs, their reusable components contribute to long-term cost-effectiveness and sustainability.

Moreover, innovative approaches were seen in studies like Botto et al. (2019, Italy) and Ozkaya Senuren et al. (2020, Turkey), where wooden tablets and sheep trachea were utilized for cricothyrotomy simulations [ 5 , 6 ]. These models demonstrate adaptability to local resources and highlight the potential for contextually appropriate simulation solutions.

In terms of dissemination and implementation, workshops, online resources, and collaborative initiatives with local healthcare organizations could facilitate the adoption of these low-cost simulation models. By sharing detailed instructions and training materials, such as those provided by Molin et al. (2020, USA), the reach and impact of these models can be expanded to benefit primary care providers in diverse settings [ 7 ].

Simulated medical models have proven highly effective in imparting essential OHNS procedure skills and can provide an important avenue to improve surgical training in resource constrained environments. However, our data show that most low-cost simulation models ( n  = 14, 82%) are developed and utilized in HIC, which aligns with prior studies that report a lack of locally developed low-cost simulations in LMIC contexts [ 7 ]. Furthermore, many “low-cost” simulation models rely on high-cost materials such as 3D printers or specialized mannequins, which may not be available in LMICs. When considering model sustainability and applicability of these models in LMICs, it is important to recognize the limitations of certain high-fidelity models in such resource-constrained environments. Prior studies demonstrate that low fidelity simulation models do not necessarily lead to worse skill outcomes, which emphasizes the potential of low-cost, less intricate models as valuable tools for skill acquisition [ 5 , 20 ].

A previous systematic review of low-cost simulations in OHNS identified 18 studies on low-cost ENT simulations [ 14 ]. However, only five of these simulations were relevant to GPs as shown in Table  4 . In contrast, our study included 17 simulations directly applicable to GPs. There is potential for expanding the range, reach, and applications of existing models. Most of the models in our study focused on peritonsillar abscess simulations, which may not always fall within a GP’s scope of practice. Future efforts should focus on exploring simulation models that use locally sourced materials and align with the skill requirements of primary care providers in LMICs. Specifically, investigations into simple yet effective simulation approaches, such as task trainers or hybrid models incorporating both physical and virtual elements, could be prioritized to address the diverse educational needs and resource constraints in these settings. Specifically, more models focusing on skills like epistaxis management and nasal/ear foreign body removal are essential to address common conditions encountered by primary care providers in LMICs.

Additionally, several of the existing models could be adapted for a broader set of GP-level skills, such as using ear models for foreign body removal and cerumen management, in addition to myringotomy. There is also a clear need for alternatives to animal models, which can be harder to procure or reuse, leading to higher operation and maintenance costs. Additionally, most models in this study did not explore the use of locally sourced materials. Collaborating with LMICs to adapt models to utilize locally available materials is an essential next step to enhance accessibility and effectiveness. Finally, our study identified heterogeneity in evaluations of the efficacy of these simulations in augmenting the knowledge, skills, and confidence of GPs. This suggests that future research should incorporate standardized metrics that evaluate educational utility of low-cost OHNS simulations.

Our study has several limitations. Not all the studies we included provided exact cost information for the simulations, which, if available, could have contributed to our understanding of the cost-effectiveness of these models. Reusability of the models was reported, however not incorporated into the cost calculation. We also did not independently evaluate fidelity and instead relied on fidelity assessments as reported by the authors for the scope of this study. Furthermore, excluding studies involving 3D printing or mannequins might have resulted in overlooking potentially useful insights regarding the development and components of these models. As 3D printing technology becomes more affordable, cost and access may not be a barrier in the future, opening exciting possibilities for its integration into future research studies and innovations across various fields. Additionally, a notable portion of the studies reviewed did not compare efficacy directly to high-fidelity models, highlighting the need for further research regarding the effectiveness of these simulations.

Low-cost, locally sourced OHNS simulations for GPs, early trainees, and students hold immense promise in LMICs. This tailored simulation-based training not only addresses the financial constraints faced by educational institutions but also considers local factors, including the local burden of OHNS diseases, available resources, hospital infrastructure, and the distinct roles and responsibilities of GPs in these settings. By conducting country-specific studies, these simulations could offer a practical and sustainable solution to enhance OHNS knowledge and skills among primary care providers, ultimately improving healthcare delivery and patient outcomes. Our scoping identified a range of potential simulation models that hold promise for replication in LMICs, along with crucial gaps that warrant exploration for the development of contextually relevant, low-cost models.

Data availability

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Acknowledgements

The authors would like to thank the Global Otolaryngology-Head and Neck Initiative for facilitating this collaboration. We would like to thank Chris Wen, John Bukuru, Patrick Balungwe, Nabin Lageju, and Tianzeng Chen for their contributions to reviewing the manuscript.

SRN is supported by the Fogarty International Center and National Institute of Mental Health, of the National Institutes of Health under Award Number D43 TW010543. This study is a part the study funded by NIH grant number NIH/FIC- 5R21HD103052-02. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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Joselyne Nzisabira and Sarah Nuss contributed equally to this work.

Authors and Affiliations

Global Otolaryngology-Head and Neck Surgery (OHNS) Initiative, Durham, NC, USA

Joselyne Nzisabira, Sarah Nuss, Estephanía Candelo, Ernest Aben Oumo, Keshav V. Shah, Eric K. Kim, Joshua Wiedermann & Mary Jue Xu

School of Medicine, University of Global Health Equity, Butaro, Rwanda

Joselyne Nzisabira, Ernest Aben Oumo, Ornella Masimbi & Natnael Shimelash

Brown University Warren Alpert Medical School, Providence, RI, USA

Fundación Valle del Lili, Cali, Colombia

Estephanía Candelo

Department of Otolaryngology-Head and Neck Surgery, Mayo Clinic Florida, Jacksonville, FL, USA

Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

Keshav V. Shah

Department of Otolaryngology-Head and Neck Surgery, University of California, San Francisco, USA

Eric K. Kim & Mary Jue Xu

Department of Otolaryngology-Head and Neck Surgery, Mayo Clinic , Rochester, USA

Joshua Wiedermann

National Clinician Scholars Program, University of California, San Francisco, USA

Mary Jue Xu

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JN contributed to the study design, team management, data extraction, data analysis, manuscript writing, and final manuscript review SN contributed to the study design, team management, data extraction, data analysis, manuscript writing, and final manuscript review EC contributed to the data extraction, data analysis, manuscript revisions, and final manuscript review EAO contributed to the data extraction, data analysis, manuscript revisions, and final manuscript reviewKVS contributed to the data extraction, data analysis, manuscript revisions, and final manuscript reviewEKK contributed to the data extraction, data analysis, manuscript revisions, and final manuscript reviewJW contributed to the project oversight, data interpretation, manuscript revisions, and final manuscript reviewOM contributed to the study conception, study design, project oversight, data interpretation, manuscript revisions, and final manuscript review NS contributed to the study conception, study design, project oversight, data extraction, data interpretation, manuscript revisions, and final manuscript reviewMJX contributed to the study conception, study design, project oversight, data interpretation, manuscript revisions, and final manuscript review.

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Nzisabira, J., Nuss, S., Candelo, E. et al. Low-cost otolaryngology simulation models for early-stage trainees: a scoping review. BMC Med Educ 24 , 483 (2024). https://doi.org/10.1186/s12909-024-05466-3

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Received : 27 November 2023

Accepted : 24 April 2024

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DOI : https://doi.org/10.1186/s12909-024-05466-3

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