importance review of literature in research

• University of Texas Libraries

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

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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

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Conducting a literature review: why do a literature review, why do a literature review.

• How To Find "The Literature"
• Found it -- Now What?

Besides the obvious reason for students -- because it is assigned! -- a literature review helps you explore the research that has come before you, to see how your research question has (or has not) already been addressed.

You identify:

• core research in the field
• experts in the subject area
• methodology you may want to use (or avoid)
• gaps in knowledge -- or where your research would fit in

It Also Helps You:

• Publish and share your findings
• Justify requests for grants and other funding
• Identify best practices to inform practice
• Set wider context for a program evaluation
• Compile information to support community organizing

Great brief overview, from NCSU

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• Last Updated: Apr 25, 2024 1:10 PM
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• Writing Tips

What is the Purpose of a Literature Review?

4-minute read

• 23rd October 2023

If you’re writing a research paper or dissertation , then you’ll most likely need to include a comprehensive literature review . In this post, we’ll review the purpose of literature reviews, why they are so significant, and the specific elements to include in one. Literature reviews can:

1. Provide a foundation for current research.

2. Define key concepts and theories.

3. Demonstrate critical evaluation.

4. Show how research and methodologies have evolved.

5. Identify gaps in existing research.

6. Support your argument.

Keep reading to enter the exciting world of literature reviews!

What is a Literature Review?

A literature review is a critical summary and evaluation of the existing research (e.g., academic journal articles and books) on a specific topic. It is typically included as a separate section or chapter of a research paper or dissertation, serving as a contextual framework for a study. Literature reviews can vary in length depending on the subject and nature of the study, with most being about equal length to other sections or chapters included in the paper. Essentially, the literature review highlights previous studies in the context of your research and summarizes your insights in a structured, organized format. Next, let’s look at the overall purpose of a literature review.

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Literature reviews are considered an integral part of research across most academic subjects and fields. The primary purpose of a literature review in your study is to:

Provide a Foundation for Current Research

Since the literature review provides a comprehensive evaluation of the existing research, it serves as a solid foundation for your current study. It’s a way to contextualize your work and show how your research fits into the broader landscape of your specific area of study.  

Define Key Concepts and Theories

The literature review highlights the central theories and concepts that have arisen from previous research on your chosen topic. It gives your readers a more thorough understanding of the background of your study and why your research is particularly significant .

Demonstrate Critical Evaluation 

A comprehensive literature review shows your ability to critically analyze and evaluate a broad range of source material. And since you’re considering and acknowledging the contribution of key scholars alongside your own, it establishes your own credibility and knowledge.

Show How Research and Methodologies Have Evolved

Another purpose of literature reviews is to provide a historical perspective and demonstrate how research and methodologies have changed over time, especially as data collection methods and technology have advanced. And studying past methodologies allows you, as the researcher, to understand what did and did not work and apply that knowledge to your own research.  

Identify Gaps in Existing Research

Besides discussing current research and methodologies, the literature review should also address areas that are lacking in the existing literature. This helps further demonstrate the relevance of your own research by explaining why your study is necessary to fill the gaps.

Support Your Argument

A good literature review should provide evidence that supports your research questions and hypothesis. For example, your study may show that your research supports existing theories or builds on them in some way. Referencing previous related studies shows your work is grounded in established research and will ultimately be a contribution to the field.  

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Ensure your literature review is polished and ready for submission by having it professionally proofread and edited by our expert team. Our literature review editing services will help your research stand out and make an impact. Not convinced yet? Send in your free sample today and see for yourself! 

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

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

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

What are Literature Reviews?

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

Goals of Literature Reviews

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

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

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

What kinds of sources require a Literature Review?

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

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

Types of Literature Reviews

What kinds of literature reviews are written?

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

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

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

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

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

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

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

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

Literature Reviews in the Health Sciences

• UConn Health subject guide on systematic reviews Explanation of the different review types used in health sciences literature as well as tools to help you find the right review type
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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. 

• Sage Research Methods Core Collection This link opens in a new window SAGE Research Methods supports research at all levels by providing material to guide users through every step of the research process. SAGE Research Methods is the ultimate methods library with more than 1000 books, reference works, journal articles, and instructional videos by world-leading academics from across the social sciences, including the largest collection of qualitative methods books available online from any scholarly publisher. – Publisher

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A Guide to Literature Reviews

Importance of a good literature review.

• Conducting the Literature Review
• Structure and Writing Style
• Types of Literature Reviews
• Citation Management Software This link opens in a new window
• Acknowledgements

A literature review is not only a summary of key sources, but  has an organizational pattern which 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.

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].
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Why is it important to do a literature review in research?

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 “A substantive, thorough, sophisticated literature review is a precondition for doing substantive, thorough, sophisticated research”. Boote and Baile 2005

Authors of manuscripts treat writing a literature review as a routine work or a mere formality. But a seasoned one knows the purpose and importance of a well-written literature review.  Since it is one of the basic needs for researches at any level, they have to be done vigilantly. Only then the reader will know that the basics of research have not been neglected.

The aim of any literature review is to summarize and synthesize the arguments and ideas of existing knowledge in a particular field without adding any new contributions.   Being built on existing knowledge they help the researcher to even turn the wheels of the topic of research.  It is possible only with profound knowledge of what is wrong in the existing findings in detail to overpower them.  For other researches, the literature review gives the direction to be headed for its success. 

The common perception of literature review and reality:

As per the common belief, literature reviews are only a summary of the sources related to the research. And many authors of scientific manuscripts believe that they are only surveys of what are the researches are done on the chosen topic.  But on the contrary, it uses published information from pertinent and relevant sources like

• Scholarly books
• Scientific papers
• Latest studies in the field
• Established school of thoughts
• Relevant articles from renowned scientific journals

and many more for a field of study or theory or a particular problem to do the following:

• Summarize into a brief account of all information
• Synthesize the information by restructuring and reorganizing
• Critical evaluation of a concept or a school of thought or ideas
• Familiarize the authors to the extent of knowledge in the particular field
• Encapsulate
• Compare & contrast

By doing the above on the relevant information, it provides the reader of the scientific manuscript with the following for a better understanding of it:

• It establishes the authors’  in-depth understanding and knowledge of their field subject
• It gives the background of the research
• Portrays the scientific manuscript plan of examining the research result
• Illuminates on how the knowledge has changed within the field
• Highlights what has already been done in a particular field
• Information of the generally accepted facts, emerging and current state of the topic of research
• Identifies the research gap that is still unexplored or under-researched fields
• Demonstrates how the research fits within a larger field of study
• Provides an overview of the sources explored during the research of a particular topic

Importance of literature review in research:

The importance of literature review in scientific manuscripts can be condensed into an analytical feature to enable the multifold reach of its significance.  It adds value to the legitimacy of the research in many ways:

• Provides the interpretation of existing literature in light of updated developments in the field to help in establishing the consistency in knowledge and relevancy of existing materials
• It helps in calculating the impact of the latest information in the field by mapping their progress of knowledge.
• It brings out the dialects of contradictions between various thoughts within the field to establish facts
• The research gaps scrutinized initially are further explored to establish the latest facts of theories to add value to the field
• Indicates the current research place in the schema of a particular field
• Provides information for relevancy and coherency to check the research
• Apart from elucidating the continuance of knowledge, it also points out areas that require further investigation and thus aid as a starting point of any future research
• Justifies the research and sets up the research question
• Sets up a theoretical framework comprising the concepts and theories of the research upon which its success can be judged
• Helps to adopt a more appropriate methodology for the research by examining the strengths and weaknesses of existing research in the same field
• Increases the significance of the results by comparing it with the existing literature
• Provides a point of reference by writing the findings in the scientific manuscript
• Helps to get the due credit from the audience for having done the fact-finding and fact-checking mission in the scientific manuscripts
• The more the reference of relevant sources of it could increase more of its trustworthiness with the readers
• Helps to prevent plagiarism by tailoring and uniquely tweaking the scientific manuscript not to repeat other’s original idea
• By preventing plagiarism , it saves the scientific manuscript from rejection and thus also saves a lot of time and money
• Helps to evaluate, condense and synthesize gist in the author’s own words to sharpen the research focus
• Helps to compare and contrast to  show the originality and uniqueness of the research than that of the existing other researches
• Rationalizes the need for conducting the particular research in a specified field
• Helps to collect data accurately for allowing any new methodology of research than the existing ones
• Enables the readers of the manuscript to answer the following questions of its readers for its better chances for publication
• What do the researchers know?
• What do they not know?
• Is the scientific manuscript reliable and trustworthy?
• What are the knowledge gaps of the researcher?

22. It helps the readers to identify the following for further reading of the scientific manuscript:

• What has been already established, discredited and accepted in the particular field of research
• Areas of controversy and conflicts among different schools of thought
• Unsolved problems and issues in the connected field of research
• The emerging trends and approaches
• How the research extends, builds upon and leaves behind from the previous research

A profound literature review with many relevant sources of reference will enhance the chances of the scientific manuscript publication in renowned and reputed scientific journals .

References:

http://www.math.montana.edu/jobo/phdprep/phd6.pdf

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• Research Process

Literature Review in Research Writing

• 4 minute read
• 423.2K views

Table of Contents

Research on research? If you find this idea rather peculiar, know that nowadays, with the huge amount of information produced daily all around the world, it is becoming more and more difficult to keep up to date with all of it. In addition to the sheer amount of research, there is also its origin. We are witnessing the economic and intellectual emergence of countries like China, Brazil, Turkey, and United Arab Emirates, for example, that are producing scholarly literature in their own languages. So, apart from the effort of gathering information, there must also be translators prepared to unify all of it in a single language to be the object of the literature survey. At Elsevier, our team of translators is ready to support researchers by delivering high-quality scientific translations , in several languages, to serve their research – no matter the topic.

What is a literature review?

A literature review is a study – or, more accurately, a survey – involving scholarly material, with the aim to discuss published information about a specific topic or research question. Therefore, to write a literature review, it is compulsory that you are a real expert in the object of study. The results and findings will be published and made available to the public, namely scientists working in the same area of research.

How to Write a Literature Review

First of all, don’t forget that writing a literature review is a great responsibility. It’s a document that is expected to be highly reliable, especially concerning its sources and findings. You have to feel intellectually comfortable in the area of study and highly proficient in the target language; misconceptions and errors do not have a place in a document as important as a literature review. In fact, you might want to consider text editing services, like those offered at Elsevier, to make sure your literature is following the highest standards of text quality. You want to make sure your literature review is memorable by its novelty and quality rather than language errors.

Writing a literature review requires expertise but also organization. We cannot teach you about your topic of research, but we can provide a few steps to guide you through conducting a literature review:

• Choose your topic or research question: It should not be too comprehensive or too limited. You have to complete your task within a feasible time frame.
• Set the scope: Define boundaries concerning the number of sources, time frame to be covered, geographical area, etc.
• Decide which databases you will use for your searches: In order to search the best viable sources for your literature review, use highly regarded, comprehensive databases to get a big picture of the literature related to your topic.
• Search, search, and search: Now you’ll start to investigate the research on your topic. It’s critical that you keep track of all the sources. Start by looking at research abstracts in detail to see if their respective studies relate to or are useful for your own work. Next, search for bibliographies and references that can help you broaden your list of resources. Choose the most relevant literature and remember to keep notes of their bibliographic references to be used later on.
• Review all the literature, appraising carefully it’s content: After reading the study’s abstract, pay attention to the rest of the content of the articles you deem the “most relevant.” Identify methodologies, the most important questions they address, if they are well-designed and executed, and if they are cited enough, etc.

If it’s the first time you’ve published a literature review, note that it is important to follow a special structure. Just like in a thesis, for example, it is expected that you have an introduction – giving the general idea of the central topic and organizational pattern – a body – which contains the actual discussion of the sources – and finally the conclusion or recommendations – where you bring forward whatever you have drawn from the reviewed literature. The conclusion may even suggest there are no agreeable findings and that the discussion should be continued.

Why are literature reviews important?

Literature reviews constantly feed new research, that constantly feeds literature reviews…and we could go on and on. The fact is, one acts like a force over the other and this is what makes science, as a global discipline, constantly develop and evolve. As a scientist, writing a literature review can be very beneficial to your career, and set you apart from the expert elite in your field of interest. But it also can be an overwhelming task, so don’t hesitate in contacting Elsevier for text editing services, either for profound edition or just a last revision. We guarantee the very highest standards. You can also save time by letting us suggest and make the necessary amendments to your manuscript, so that it fits the structural pattern of a literature review. Who knows how many worldwide researchers you will impact with your next perfectly written literature review.

Know more: How to Find a Gap in Research .

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What is a Research Gap

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Conducting a Literature Review

Benefits of conducting a literature review.

• Steps in Conducting a Literature Review
• Summary of the Process
• Additional Resources
• Literature Review Tutorial by American University Library
• The Literature Review: A Few Tips On Conducting It by University of Toronto
• Write a Literature Review by UC Santa Cruz University Library

While there might be many reasons for conducting a literature review, following are four key outcomes of doing the review.

Assessment of the current state of research on a topic . This is probably the most obvious value of the literature review. Once a researcher has determined an area to work with for a research project, a search of relevant information sources will help determine what is already known about the topic and how extensively the topic has already been researched.

Identification of the experts on a particular topic . One of the additional benefits derived from doing the literature review is that it will quickly reveal which researchers have written the most on a particular topic and are, therefore, probably the experts on the topic. Someone who has written twenty articles on a topic or on related topics is more than likely more knowledgeable than someone who has written a single article. This same writer will likely turn up as a reference in most of the other articles written on the same topic. From the number of articles written by the author and the number of times the writer has been cited by other authors, a researcher will be able to assume that the particular author is an expert in the area and, thus, a key resource for consultation in the current research to be undertaken.

Identification of key questions about a topic that need further research . In many cases a researcher may discover new angles that need further exploration by reviewing what has already been written on a topic. For example, research may suggest that listening to music while studying might lead to better retention of ideas, but the research might not have assessed whether a particular style of music is more beneficial than another. A researcher who is interested in pursuing this topic would then do well to follow up existing studies with a new study, based on previous research, that tries to identify which styles of music are most beneficial to retention.

Determination of methodologies used in past studies of the same or similar topics.  It is often useful to review the types of studies that previous researchers have launched as a means of determining what approaches might be of most benefit in further developing a topic. By the same token, a review of previously conducted studies might lend itself to researchers determining a new angle for approaching research.

Upon completion of the literature review, a researcher should have a solid foundation of knowledge in the area and a good feel for the direction any new research should take. Should any additional questions arise during the course of the research, the researcher will know which experts to consult in order to quickly clear up those questions.

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• Steps in Conducting a Literature Review

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

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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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Organizing Your Social Sciences Research Paper

• 5. The Literature Review
• Purpose of Guide
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• Scholarly vs. Popular Publications
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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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• Volume 19, Issue 1
• Reviewing the literature
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• Joanna Smith 1 ,
• Helen Noble 2
• 1 School of Healthcare, University of Leeds , Leeds , UK
• 2 School of Nursing and Midwifery, Queens's University Belfast , Belfast , UK
• Correspondence to Dr Joanna Smith , School of Healthcare, University of Leeds, Leeds LS2 9JT, UK; j.e.smith1{at}leeds.ac.uk

https://doi.org/10.1136/eb-2015-102252

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If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

Implementing evidence into practice requires nurses to identify, critically appraise and synthesise research. This may require a comprehensive literature review: this article aims to outline the approaches and stages required and provides a working example of a published review.

Are there different approaches to undertaking a literature review?

What stages are required to undertake a literature review.

The rationale for the review should be established; consider why the review is important and relevant to patient care/safety or service delivery. For example, Noble et al 's 4 review sought to understand and make recommendations for practice and research in relation to dialysis refusal and withdrawal in patients with end-stage renal disease, an area of care previously poorly described. If appropriate, highlight relevant policies and theoretical perspectives that might guide the review. Once the key issues related to the topic, including the challenges encountered in clinical practice, have been identified formulate a clear question, and/or develop an aim and specific objectives. The type of review undertaken is influenced by the purpose of the review and resources available. However, the stages or methods used to undertake a review are similar across approaches and include:

Formulating clear inclusion and exclusion criteria, for example, patient groups, ages, conditions/treatments, sources of evidence/research designs;

Justifying data bases and years searched, and whether strategies including hand searching of journals, conference proceedings and research not indexed in data bases (grey literature) will be undertaken;

Developing search terms, the PICU (P: patient, problem or population; I: intervention; C: comparison; O: outcome) framework is a useful guide when developing search terms;

Developing search skills (eg, understanding Boolean Operators, in particular the use of AND/OR) and knowledge of how data bases index topics (eg, MeSH headings). Working with a librarian experienced in undertaking health searches is invaluable when developing a search.

Once studies are selected, the quality of the research/evidence requires evaluation. Using a quality appraisal tool, such as the Critical Appraisal Skills Programme (CASP) tools, 5 results in a structured approach to assessing the rigour of studies being reviewed. 3 Approaches to data synthesis for quantitative studies may include a meta-analysis (statistical analysis of data from multiple studies of similar designs that have addressed the same question), or findings can be reported descriptively. 6 Methods applicable for synthesising qualitative studies include meta-ethnography (themes and concepts from different studies are explored and brought together using approaches similar to qualitative data analysis methods), narrative summary, thematic analysis and content analysis. 7 Table 1 outlines the stages undertaken for a published review that summarised research about parents’ experiences of living with a child with a long-term condition. 8

• View inline

An example of rapid evidence assessment review

In summary, the type of literature review depends on the review purpose. For the novice reviewer undertaking a review can be a daunting and complex process; by following the stages outlined and being systematic a robust review is achievable. The importance of literature reviews should not be underestimated—they help summarise and make sense of an increasingly vast body of research promoting best evidence-based practice.

• ↵ Centre for Reviews and Dissemination . Guidance for undertaking reviews in health care . 3rd edn . York : CRD, York University , 2009 .
• ↵ Canadian Best Practices Portal. http://cbpp-pcpe.phac-aspc.gc.ca/interventions/selected-systematic-review-sites / ( accessed 7.8.2015 ).
• Bridges J , et al
• ↵ Critical Appraisal Skills Programme (CASP). http://www.casp-uk.net / ( accessed 7.8.2015 ).
• Dixon-Woods M ,
• Shaw R , et al
• Agarwal S ,
• Jones D , et al
• Cheater F ,

Twitter Follow Joanna Smith at @josmith175

Competing interests None declared.

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Dimensions of teachers’ data literacy: A systematic review of literature from 1990 to 2021

• Open access
• Published: 06 May 2024

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• Jihyun Lee   ORCID: orcid.org/0000-0001-5896-0686 1 ,
• Dennis Alonzo 1 ,
• Kim Beswick 1 ,
• Jan Michael Vincent Abril 1 ,
• Adrian W. Chew 1 &
• Cherry Zin Oo 2  

The current study presents a systematic review of teachers’ data literacy, arising from a synthesis of 83 empirical studies published between 1990 to 2021. Our review identified 95 distinct indicators across five dimensions: (a) knowledge about data, (b) skills in using data, (c) dispositions towards data use, (d) data application for various purposes, and (e) data-related behaviors. Our findings indicate that teachers' data literacy goes beyond addressing the needs of supporting student learning and includes elements such as teacher reflection, collaboration, communication, and participation in professional development. Considering these findings, future policies should acknowledge the significance of teacher dispositions and behaviors in relation to data, recognizing that they are as important as knowledge and skills acquisition. Additionally, prioritizing the provision of system-level support to foster teacher collaboration within in-school professional development programs may prove useful in enhancing teachers’ data literacy.

Avoid common mistakes on your manuscript.

1 Introduction

In recent years, there has been a growing recognition of the importance of teachers’ data literacy for educational policy, research, and practice. This trend was ignited in 2009 when Arne Duncan, the former Secretary of Education of the United States, advocated evidence-driven practices in schools to enhance student performance (Mandinach & Gummer, 2016 ). Since then, there has been an increasing expectation for teachers to engage in data-informed practices to guide teaching and decision-making in schools. Following this trend, educational researchers have also increasingly directed their attention towards offering conceptual and theoretical foundations for teachers’ data literacy.

Various organizations and researchers have provided the definitions of teachers’ data literacy. For example, drawing on the opinions of diverse stakeholder groups, Data Quality Campaign ( 2014 ) defined teachers’ data literacy as teachers’ capabilities to “continuously, effectively, and ethically access, interpret, act on, and communicate multiple types of data from state, local, classroom, and other sources to improve outcomes for students in a manner appropriate to educators' professional roles and responsibilities” (p. 1). Kippers et al. ( 2018 ) defined teachers’ data literacy as “educators’ ability to set a purpose, collect, analyze, and interpret data and take instructional action” (p. 21). Similarly, teachers’ data literacy has been defined as “one’s ability, or the broad knowledge and skills, needed to engage in data use or implement a data use inquiry process (Abrams et al., 2021 , p. 100,868).

The data literacy for teachers (DLFT) framework proposed by Mandinach and Gummer defined teachers’ data literacy as “… the ability to transform information into actionable instructional knowledge and practices by collecting, analyzing, and interpreting all types of data to help determine instructional steps” (Gummer & Mandinach, 2015 , p. 2). In recent years, much of the research efforts to provide a theoretical framework on teachers’ data literacy has been led by Mandinach and Gummer (Gummer & Mandinach, 2015 ; Mandinach & Gummer, 2012 , 2013a , 2016 ; Mandinach et al., 2015 ). As far as we can ascertain, their work presents the most comprehensive framework of teachers’ data literacy in the current literature. The primary sources of Mandinach and Gummer’s DLFT framework were their previous works, Mandinach and Gummer ( 2012 ) and Mandinach et al. ( 2015 ). Their DLFT framework was developed as the results of the analysis of the teacher licensure documents across the US states (Mandinach et al., 2015 ) and the text analysis of the perspectives and definitions provided by 55 researchers and professional development providers during a braining storming at the conference held in 2012 (cf. Mandinach & Gummer, 2012 ). There are five components in the framework: (a) identifying problems and framing questions, (b) using data, (c) transforming data into information, (d) transforming information into decisions, and (e) evaluating outcomes. Their framework aimed to identify “the specific knowledge, skills, and dispositions teachers need to use data effectively and responsibly” (Mandinach & Gummer, 2016 , p. 366). However, a potential sixth dimension, “dispositions, habits of mind, or factors that influence data use” (Mandinach & Gummer, 2016 , p. 372) was mentioned but not included in the framework.

2 The present study

In the present study, we conducted a systematic review of the empirical studies on teachers’ data literacy and data use published in academic journals between 1990 and 2021. Our primary purpose was to enhance the conceptual clarity of teachers’ data literacy by providing its updated definition, indicators, and dimensions.

We argue that there are several reasons to justify the need for this systematic review. Firstly, we update, complement, and compare our review outcomes and the DLFT framework in Mandinach and Gummer ( 2016 ). A systematic review of research studies on teachers’ data use was conducted by Mandinach and Gummer ( 2013b ), but the study selection was limited to years between 2001 and 2009. Therefore, one of the aims of the present study is to compare our systematic review outcomes against the dimensions and specific indicators identified in the DLFT framework (Mandinach & Gummer, 2016 ). The present literature search spans a period from 1990 to 2021. We have set 1990 as the lower-boundary year because “during the 1990s, a new hypothesis – that the quality of teaching would provide a high-leverage policy target – began to gain currency” (Darling-Hammond et al., 2003 , p. 5).

Secondly, it appears that much work on teachers’ data literacy, including that of Mandinach and Gummer, has tended to focus on teachers’ data use in relation to teaching (e.g., Beck et al., 2020 ; Datnow et al., 2012 ) and instructional improvement (e.g., Datnow et al., 2021 ; Kerr et al., 2006 ; Wachen et al., 2018 ) or in relation to student academic performance (e.g., Poortman & Schildkamp, 2016 ; Staman et al., 2017 ). However, we argue that classroom teachers’ tasks and responsibilities go beyond teaching itself and include many other tasks such as advising/counselling, organising excursions, and administrative work (e.g., Albiladi et al., 2020 ; Kallemeyn, 2014 ). Our review, therefore, examines how teachers’ data use practices may be manifested across a range of teacher responsibilities beyond teaching and teaching-related tasks.

Thirdly, there has been a relative lack of attention to teachers’ personal dispositions in data literacy research. Dispositions refer to a person's inherent tendencies, attitudes, approaches, and inclinations towards ways of thinking, behaving, and believing (Lee & Stankov, 2018 ; Mischel & Shoda, 1995 ). According to Katz ( 1993 ), a disposition can be defined as “a tendency to exhibit frequently, consciously, and voluntarily a pattern of behavior that is directed to a broad goal” (p. 2). In the context of education, disposition refers to the attitudes, beliefs, and values that influence a teacher’s actions, decision-making, and interactions with various stakeholders including students, colleagues, and school leaders (Darling-Hammond et al., 2003 ). While teachers’ dispositions were mentioned in Mandinach and Gummer ( 2016 ), dispositions were not included in their DLFT framework. Teacher educators have long emphasized that accomplished teachers need to possess extensive knowledge, skills, and a range of dispositions to support the learning of all students in the classroom, engage in on-going professional development, and continuously strive to enhance their own learning throughout their careers (Darling-Hammond et al., 2003 ; Sykes, 1999 ). Therefore, we aim to identify a range of teachers’ dispositions in relation to data literacy and data use in the school contexts.

Fourthly, we argue that teachers’ data literacy may be more important in the current context of the rapidly evolving data and digital landscape influenced by the technical advancements in artificial intelligence. Teachers may encounter significant challenges in comprehending and addressing a wide array of issues, both anticipated and unforeseen, as well as observed and unobserved situations, stemming from various artificial intelligence tools and automated machines. In this sense, comprehending the nature, types, and functions of data is crucial for teachers. Without such understanding, the educational community and teaching workforce may soon find themselves in an increasingly worrisome situation when it comes to evaluating data and information.

Finally, we argue that there is a need to update conceptual clarity regarding teachers’ data literacy in the current literature. Several systematic review studies have focused on features in professional development interventions (PDIs) aimed at improving teachers’ data use in schools (e.g., Ansyari et al., 2020 ; 2022 ; Espin et al., 2021 ), emphasizing the need to understand data literacy as a continuum spanning from pre-service to in-service teachers and from novice to veteran educators (Beck & Nunnaley, 2021 ). Other systematic review studies have given substantial attention to data-based decision-making (DBDM) in the schools (e.g., Espin et al., 2021 ; Filderman et al., 2018 ; Gesel et al., 2021 ; Hoogland et al., 2016 ). For example, Hoogland et al. ( 2016 ) investigated the prerequisites for data-based decision-making (DBDM) in the classroom, highlighting nine themes that influence DBDM, such as collaboration, leadership, culture, time, and resources. These systematic reviews are highly relevant to the current review, as the PDIs, understanding the continuum, or data-based decision-making would require a clear and updated understanding of what teachers’ data literacy should be. We hope that the current study’s definition, indicators, and dimensions of teachers’ data literacy may be useful in conjunction with other systematic review studies on teachers’ data use and factors influencing teachers’ data use.

3.1 Data sources and selection of the studies

Our strategies for literature search were based on the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), a framework for reporting and synthesising literature review (Moher et al., 2009 ). In accordance with PRISMA suggestions, we followed the four steps in locating and reviewing the relevant studies. First, we conducted initial searches to identify relevant studies, using three databases: Scopus, ProQuest, and Web of Science. Keywords in our search were teacher, school, data, data use, data literacy, evidence-based, and decision-making (see Table  1 for the detailed search strategy syntax). This initial search, using the combination of the identified keywords, yielded 2,414 journal articles (see Fig.  1 ). After removing duplicates, 1,976 articles remained.

Study selection flow using PRISMA guidelines

Secondly, we set and applied the inclusion criteria to screen the studies. The inclusion criteria were: (a) topics relating to the key words, (b) school context of primary or secondary school settings (i.e., excluding studies focusing on university, vocational education, and adult learning), (c) the full text written in English (excluding studies if the full text is presented in another language or if only the abstract was presented in English), (d) peer-reviewed empirical studies (across quantitative, qualitative, and mixed-methods) published in academic journals (excluding book chapters, conference papers, thesis) to ensure the inclusion of the published work that has undergone peer-review process, and finally, (e) published studies from 1990 onwards. The titles and abstracts of the studies were reviewed to assess their eligibility based on the inclusion criteria. As a result of applying these criteria, 117 articles were selected for the next step, full-text review.

Thirdly, we evaluated the eligibility of the full-text versions of the published studies. This full-text review resulted in a further exclusion of 34 studies as they were found to not meet all the inclusion criteria. We also examined whether the studies included data literacy or data-driven decision-making. Following these assessments, we identified 83 articles that met all the inclusion criteria.

Finally, we reviewed, coded, and analyzed the final set of the selected studies. The analysis approaches are described below.

3.2 Approach to analysis

We employed a thematic synthesis methodology, following the framework outlined by Thomas & Harden ( 2008 ). The coding and analysis process consisted of three main stages: (a) conducting a line-by-line reading and coding of the text, (b) identifying specific descriptive codes, and (c) generating analytical themes by grouping conceptually inter-related descriptive codes. The final analytic process was, therefore, categorizing and naming related descriptive codes to produce analytical themes. During the development of the analytic themes, we utilized an inductive approach, organizing conceptually interconnected codes into broader themes.

The first author developed the descriptive and analytical themes, which were then reviewed by another two authors. To ensure coding rigor and consistency, three authors independently coded the same two articles, and then compared the coding to address any inconsistencies and reach a consensus. This process was repeated in four iterations. Once the three authors who were involved in the initial coding reached the consensus, the remaining authors double-checked the final outputs of the thematic analysis (i.e., codes, and themes). We have labelled descriptive codes as ‘indicators’ of teachers' data literacy, while the broader groups of descriptive codes, referred to as analytic themes, represent ‘dimensions’ of teachers’ data literacy.

4.1 Characteristics of the reviewed studies

The main purpose of the present study was to examine the conceptualization of teachers’ data literacy from 83 peer-reviewed empirical studies. Table 2 presents the studies included in our systematic review, along with the summary of the study characteristics such as country, school-level, study focus (i.e., main constructs), study purposes/objectives, research method, data collection tools, and sample size. Figure  2 presents the number of the reviewed studies by publication year. We found that since 2015, there has been an increase in the number of published empirical studies on teachers' data literacy.

Number of the reviewed studies by publication year

Out of 83 studies, 50 were conducted in the United States. Thirteen studies were from Netherlands, four from Belgium, three from Australia, two from each of Canada and the United Kingdom, and one study for each of the following ten countries: China, Denmark, Germany, Indonesia, Ireland, Kenya, Korea, Norway, South Africa, and Sweden. Therefore, more than half of the studies (i.e., 58 studies, 70%) were conducted in the English-speaking countries. In terms of school-settings, studies were mostly conducted in primary school settings or in combination with high school: 36 studies in primary school settings, 16 in secondary school settings, and 30 studies were in both primary and secondary school settings. The most common design was qualitative ( n  = 35 studies), followed by mixed methods ( n  = 30) and quantitative ( n  = 18). Multiple sources of data collection (e.g., interview and survey) were used in 22 studies. The most commonly used data collection tool was interview ( n  = 55), which was followed by surveys ( n  = 37) and observation ( n  = 25). A smaller set of studies used focus group discussion ( n  = 18) and document analysis ( n  = 19). A few studies used students’ standardised assessment data ( n  = 4), field notes ( n  = 4), and teacher performance on data literacy test ( n  = 4).

We also reviewed the study topics and found that there are seven foci among the reviewed studies: (a) factors influencing teachers’ data use ( n  = 29), (b) specific practices in teachers’ data use ( n  = 27), (c) teachers’ data use to enhance teaching practices ( n  = 25), (d) teachers’ data use for various purposes ( n  = 24), (e) approaches to improve teachers’ data literacy ( n  = 22), (f) approaches to improve teachers’ assessment literacy ( n  = 19), and (g) teachers’ data use to improve student learning outcomes ( n  = 19).

4.2 Dimensions and indicators of teaches’ data literacy

Our thematic analysis identified 95 descriptive codes (see Table  3 ). Careful review of the identified descriptive codes suggested that they can be viewed as indicators of teachers’ knowledge, attitudes, behaviors, and dispositions in data use. These indicators were further organized into inter-related concepts, which formed analytic themes; we refer to these as ‘dimensions’ (see Table  3 ). There were five broad dimensions that emerged from the indicators: knowledge about data (Dimension 1), skills in using data (Dimension 2), dispositions towards data use (Dimension 3), data application for various purposes (Dimension 4), and data-related behaviors (Dimension 5).

It is necessary to point out that Dimension 1 pertains to understanding the nature of data itself, focusing on knowledge about data. On the other hand, Dimension 2 revolves around data-related skills in the actual use of data , encompassing a spectrum of sequences including data generation, processing, and production. These two dimensions, i.e., knowledge and skills, are highly interconnected and complement each other. Proficiency in data-use skills (Dimension 2) may not be developed without a solid understanding of how data can be utilised, for instance, in teaching practices or school improvement in data use (Dimension 1). Conversely, teachers' understanding of how data can enhance teaching practices (Dimension 1) can guide them in determining specific approaches to analysing particular datasets (Dimension 2). While we acknowledge the complementary nature of knowledge and skills, it is important to note that certain aspects of knowledge and skills may not completely overlap. For instance, a teacher who understands the process of creating state-level assessment data may not necessarily possess the technical expertise required to analyze state-level data, taking into account measurement errors. Therefore, we maintain knowledge and skills as two distinct dimensions to highlight both as the core components of teachers’ data literacy.

Within each of the five broad dimensions, we also uncovered sub-themes to illuminate the constituent elements of those dimensions. Under Dimension 1, four sub-themes emerged: “knowledge about data”, knowledge about data for “teaching practices”, understanding “data culture in the school”, and understanding the use of “external assessment”. Dimension 2 featured sub-themes highlighting the sequential stages of data utilization: “data generation & collection”, “data analysis”, “data interpretation”, “data integration”, “evaluation”, and “reporting”. Within Dimension 3, we identified dispositions towards data use, encompassing sub-themes such as confidence, values/beliefs, trust/respect, and anxiety. Dimension 4 revealed various purposes of data applications, categorized into three sub-themes: “teaching,” “student learning,” and “school improvement.” Lastly, Dimension 5 delineated teachers’ behaviors related to data into two sub-themes: “communication & discussion” and “participation & engagement.”

In the following passages we provide detailed descriptions of the indicators and their associated dimensions. Figure  3 presents a visual a summary of these indicators and dimensions.

A summary of the dimensions and indicators of teachers’ data literacy

4.2.1 Dimension 1. Knowledge about data

The first dimension of teachers’ data literacy pertains to teachers’ knowledge about data . Many studies recognized the importance of data-related knowledge to be utilized in the schools (e.g., Jacobs et al., 2009 ; Omoso et al., 2019 ; Schildkamp et al., 2017 ). Our review revealed four major ways that teachers' data-related knowledge can be manifested. Firstly, teachers’ knowledge about data involves their understanding of the necessary steps in data analysis procedures (Ebbeler et al., 2016 ; Snodgrass Rangel et al., 2016 ; Vanlommel et al., 2021 ; Wardrip & Herman, 2018 ) and understanding of different data types to be used for varying purposes (Abdusyakur & Poortman, 2019 ; Beck et al., 2020 ; Howley et al., 2013 ; Reeves et al., 2016 ).

Secondly, teachers’ knowledge about data involves their capability to relate the insights gleaned from data to inform their teaching practices (Abrams et al., 2016 ; Jimerson et al., 2016 ). Specifically, data-literate teachers leverage student assessment data to evaluate learning progress (Abrams et al., 2016 ; Jimerson, 2014 ; Jimerson & Wayman, 2015 ; Jimerson et al., 2016 ; Snodgrass Rangel et al., 2016 ), to tailor classroom instruction based on data insights (Mokhtari et al., 2009 ; Poortman & Schildkamp, 2016 ; Staman et al., 2017 ; van der Scheer & Visscher, 2018 ), and to ensure alignment between instructional approaches and appropriate assessment methods (Howley et al., 2013 ; Marsh & Farrell, 2015 ; van der Scheer & Visscher, 2018 ).

Thirdly, teachers’ data literacy extends to understanding of the school culture surrounding data utilization (e.g., Andersen, 2020 ; Schildkamp, 2019 ; Wachen et al., 2018 ). This encompasses recognizing the conditions that may facilitate or hinder teachers’ data use (Abdusyakur & Poortman, 2019 ; Anderson et al., 2010 ; Keuning et al., 2017 ) and navigating various challenges associated with using assessment data in the school (Datnow et al., 2012 ; Ford, 2018 ; Kanjee & Moloi, 2014 ; Thomas & Huffman, 2011 ).

Lastly, teachers’ knowledge about data includes understanding of externally administered assessment data and data system, such as state-level assessment policies related to data use (Copp, 2017 ; Hardy, 2019 ; Reed, 2015 ) and understanding the broader state-level contexts that impact data utilization within the school (Datnow et al., 2013 ; Dunn et al., 2013a ; Ford, 2018 ; Omoso et al., 2019 ; Powell et al., 2021 ). Teachers may need to have thorough knowledge of educational government policies to ensure alignment between state-level curriculum initiatives and school-level assessment policies (Anderson et al., 2010 ; Copp, 2017 ; Gelderblom et al., 2016 ; Hardy, 2015 ).

In summary, existing literature highlights that data-literate teachers would have a comprehensive understanding of a diverse range of data sources and purposes, regularly reviewing and evaluating student outcomes from various channels. Consequently, if teachers face excessive pressure to meet accountability measures and improve standardized testing results, it could potentially hinder their overall development and growth in a broad spectrum of data-related knowledge.

4.2.2 Dimension 2. Skills in using data

Skills in using data is the second key dimension in teachers’ data literacy. There were a wide range of specific data-skills mentioned in the literature, spanning from data generation and collection (Farley-Ripple et al., 2019 ; Jimerson & Wayman, 2015 ) to data analysis (Farley-Ripple et al., 2019 ; Jimerson & Wayman, 2015 ; Marsh et al., 2010 ), data interpretation and integration (Jimerson & Wayman, 2015 ; Marsh et al., 2010 ), evaluation (Andersen, 2020 ; Dunn et al., 2013b ; Thomas & Huffman, 2011 ), and report writing (Farley-Ripple et al., 2019 ; Jimerson & Wayman, 2015 ). These indicators (see Table  3 ) emphasize that teachers’ data literacy requires proficiency across the entire sequence, across different stages of data generation, processing, and production.

Teachers’ skills in data use also involve selecting specific data types appropriate for different purposes (Anderson et al., 2010 ; Jimerson et al., 2016 ; Kanjee & Moloi, 2014 ), analysing multiple sources of data on student learning outcomes (Datnow et al., 2012 ; Vanlommel et al., 2021 ; von der Embse et al., 2021 ), and integrating multiple data sources to arrive at a holistic assessment of student progress (Brunner et al., 2005 ; Farley-Ripple et al., 2019 ; Ford, 2018 ; Jacobs et al., 2009 ; Mausethagen et al., 2018 ). For example, teachers may need to apply different data analytic approaches when evaluating student outcomes based on school-based versus externally administered standardized assessments (Copp, 2017 ; Curry et al., 2016 ; Omoso et al., 2019 ; Wardrip & Herman, 2018 ; Zeuch et al., 2017 ). Data-literate teachers may also plan data analysis for targeted purposes, such as analyzing students’ social-emotional outcomes (Abrams et al., 2021 ; Jimerson et al., 2021 ; von der Embse et al., 2021 ; Wardrip & Herman, 2018 ), identifying individual students’ learning needs, making recommendations for curriculum revisions, or evaluating pedagogical approaches (Dunn et al., 2013a ; Snodgrass Rangel et al., 2016 ; Wolff et al., 2019 ; Young, 2006 ).

In summary, this “skills” dimension highlights the importance of teachers possessing a diverse array of competencies to leverage data effectively. The literature reviewed identified various aspects of teachers’ data use, spanning the spectrum from data collection and generation to analysis, interpretation, integration across multiple sources, evaluation, and reporting.

4.2.3 Dimension 3. Dispositions towards data use

While somewhat overlooked in data literacy literature, teachers’ disposition is a crucial component of their data literacy. Our review identified four major types of such dispositions in the context of teachers’ data literacy (see Table  3 ). Firstly, studies have underscored that teachers’ confidence in using data may be necessary when making data-driven school-level decisions, for example, to design intervention programs (Andersen, 2020 ; Keuning et al., 2017 ; Staman et al., 2017 ; Thompson, 2012 ), or to develop strategic plans for school improvement (Dunn et al., 2013b ; Poortman & Schildkamp, 2016 ). Researchers also claimed that teachers may need to feel confident in many steps of data processes, across accessing, analyzing, interpreting, evaluating, and discussing data within the school environment (Abrams et al., 2021 ; Dunn et al., 2013a ; von der Embse et al., 2021 ).

The second disposition pertains to teachers valuing and believing in the importance of data use in schools. Data-literate teachers would recognize the usefulness of data in informing school improvement and enhancing student performance (Howley et al., 2013 ; Poortman & Schildkamp, 2016 ; Prenger & Schildkamp, 2018 ). They would also place value on collaboration among colleagues and actively seek institutional support for effective data use (Kallemeyn, 2014 ; Marsh & Farrell, 2015 ; Nicholson et al., 2017 ; Poortman & Schildkamp, 2016 ). Furthermore, they would appreciate the pivotal role of school leaders in supporting and promoting teachers’ data use within the school (Albiladi et al., 2020 ; Curry et al., 2016 ; Joo, 2020 ; Young, 2006 ).

A third type of teacher disposition that our review identified is trust in and respect towards colleagues and school leaders . Teachers often work collaboratively in the school environment when they learn about and utilise school-level data. In this sense, teacher collaboration and sustaining trusting relationships are fundamental in fostering a school culture that appreciates data-driven decision-making, as well as for encouraging teachers to further develop their own data knowledge and skills (Abrams et al., 2021 ; Andersen, 2020 ; Keuning et al., 2017 ). Mutual trust and respect among teachers can allow them to have open and honest conversations about their experiences and share any concerns arising from data use in the school context (Andersen, 2020 ; Datnow et al., 2013 ; Ford, 2018 ; Wachen et al., 2018 ).

Lastly, data anxiety may play a role when teachers use or are expected to use data in the school (Abrams et al., 2021 ; Dunn et al., 2013b ; Reeves et al., 2016 ). Teachers may experience data anxiety when they are expected to effectively analyze student assessment outcomes (Dunn et al., 2013b ; Powell et al., 2021 ), when they are introduced to new data management systems in the school, when they feel pressured to quickly grasp the school’s data management system (Andersen, 2020 ; Dunn et al., 2013a ), or when they are tasked with developing specific strategies to assess and enhance student learning outcomes (Dunn et al., 2013a , b ; Jimerson et al., 2019 ). These types of teacher responsibilities demand proficient data skills and knowledge, which not all teachers may possess, and thus, anxiety may hinder their ability to further develop their data literacy.

In summary, teacher dispositions towards data use can impact their effective utilization of data or impede the capacity to further develop their own data literacy. Our review also illuminated that it is not just individual teachers’ confidence or anxiety towards data use, but also the social dynamics within the school environment, including teacher collaboration, trust and respect, and relationships with the school management team, that can influence teachers’ data literacy. Therefore, fostering a collaborative climate within the school community and creating more opportunities for data use may strengthen a data-driven culture within the school.

4.2.4 Dimension 4. Data applications for various purposes

Our review suggests that teachers' data literacy can be manifested in their use of data for multiple purposes, primarily in three areas: (a) to enhance teaching practices (e.g., Datnow et al., 2012 , 2021 ; Farrell, 2015 ; Gelderblom et al., 2016 ; Wachen et al., 2018 ), (b) to support student learning (e.g., Joo, 2020 ; Lockton et al., 2020 ; Staman et al., 2017 ; Vanlommel et al., 2021 ; van der Scheer & Visscher,  2018 ), and (c) to make plans and strategies for school improvement (e.g., Abdusyakur & Poortman, 2019 ; Jimerson et al., 2021 ; Kallemeyn, 2014 ).

With respect to teaching enhancement purposes, teachers use data to inform their lesson plans (Ford, 2018 ; Gelderblom et al., 2016 ; Snodgrass Rangel et al., 2016 ; Reeves et al., 2016 ), set lesson objectives (Kallemeyn, 2014 ; Snodgrass Rangel et al., 2016 ; Reeves et al., 2016 ), develop differentiated instructions (Beck et al., 2020 ; Datnow et al., 2012 ; Farley-Ripple et al., 2019 ), and provide feedback to students (Gelderblom et al., 2016 ; Andersen, 2020 ; Jimerson et al., 2019 ; Marsh & Farrell, 2015 ). Furthermore, teachers use data to reflect on their own teaching practices (Datnow et al., 2021 ; Ford, 2018 ; Jimerson et al., 2019 ; Snodgrass Rangel et al., 2016 ) and evaluate the impact of using data on teaching and learning outcomes (Gelderblom et al., 2016 ; Marsh & Farrell, 2015 ).

In relation to supporting student learning, teachers use data to recognize individual students’ learning needs (Curry et al., 2016 ; Gelderblom et al., 2016 ), guide students to learning new or challenging concepts (Abrams et al., 2021 ; Keuning et al., 2017 ; Marsh et al., 2010 ; Reeves et al., 2016 ), set learning goals (Abdusyakur & Poortman, 2019 ; Curry et al., 2016 ), and monitor learning progress (Curry et al., 2016 ; Gelderblom et al., 2016 ; Marsh et al., 2010 ).

In terms of guiding school improvement strategies, teachers use data to develop school-based intervention programs (Abdusyakur & Poortman, 2019 ; Jimerson et al., 2021 ; Kallemeyn, 2014 ; Thompson, 2012 ), make decisions about school directions (Huffman & Kalnin, 2003 ; Prenger & Schildkamp, 2018 ; Schildkamp, 2019 ), and evaluate school performance for meeting the accountability requirements (Hardy, 2015 ; Jacobs et al., 2009 ; Jimerson & Wayman, 2015 ; Marsh et al., 2010 ; Omoso et al., 2019 ; Snodgrass Rangel et al., 2019 ).

In summary, the literature indicates that data-literate teachers use data for multiple purposes and consider it essential in fulfilling their various roles and responsibilities within the school. Teachers’ data use for supporting student learning tends to focus primarily on helping students achieve better learning outcomes; in contrast, teachers’ data use for teaching enhancement includes a broader range of data processes and practices.

4.2.5 Dimension 5. Data-related behavior

The fifth and final dimension we identified pertains to teachers' data-related behaviors within and outside the school context. Within this dimension, there appear to be two distinctive sets of teacher behaviors: (a) teachers’ data use to enhance communication and discussion with various stakeholders such as colleagues (Datnow et al., 2013 ; Van Gasse et al., 2017 ), school leaders (Jimerson, 2014 ; Marsh & Farrell, 2015 ; Nicholson et al., 2017 ), and parents (Jimerson & Wayman, 2015 ; Jimerson et al., 2019 ); and (b) teachers’ participation in and engagement with learning about data use (Schildkamp et al., 2019 ; Wardrip & Herman, 2018 ) and data culture in schools (Datnow et al., 2021 ; Keuning et al., 2016 ). These behaviors were found to be integral aspects of teachers' data literacy. Teacher engagement with data is manifested in multiple ways, such as involvement in team-based approaches to data utilization (Michaud, 2016 ; Schildkamp et al., 2017 ; Wardrip & Herman, 2018 ; Young, 2006 ), active participation in creating a school culture of data use (Abrams et al., 2021 ; Albiladi et al., 2020 ), evaluation of the organizational culture and conditions pertaining to data use (Andersen, 2020 ; Datnow et al., 2021 ; Lockton et al., 2020 ), and participation in professional development opportunities focused on data literacy (Ebbeler et al., 2016 ; O’Brien et al., 2022 ; Schildkamp et al., 2017 ).

In summary, this dimension highlights that teachers’ data literacy includes various forms of their active engagement and behavior to enhance the effective use and understanding of data. Our findings also indicate that teacher communication and discussions regarding data primarily focus on student assessment data with various stakeholder groups including colleagues, school leaders, and parents.

5 Discussion

The present study reviews 83 empirical studies on teachers' data literacy published in peer-reviewed journals from 1990 to 2021, and we identified 95 specific indicators categorized across five dimensions: (a) knowledge about data , (b) skills in using data , (c) dispositions towards data use , (d) data applications for various purposes , and (e) data-related behaviors in the school . Our review of the identified indicators of this study has led to the following definition of teachers’ data literacy:

A set of knowledge, skills, and dispositions that empower teachers to utilize data for various purposes, including generating, collecting, analyzing, interpreting, integrating, evaluating, reporting, and communicating, aimed at enhancing teaching, supporting student learning, engaging in school improvement, and fostering self-reflection. Teachers’ data literacy also involves the appreciation for working together with colleagues and school leaders to (a) assess organizational conditions for data use, (b) foster a supportive school culture, and (c) engage in ongoing learning to optimize the effective utilization of data.

Our analysis also revealed several noteworthy findings that are presented in the following sections.

5.1 Teachers’ data literacy and assessment literacy

There have been concerns expressed by scholars about conceptual fuzziness in teachers’ data literacy and assessment literacy (cf. Brookhart, 2011 ; Ebbeler et al., 2016 ; Mandinach, 2014 ; Mandinach & Gummer, 2016 ). Indeed, student assessment data are the most salient form of data in the school (Mandinach & Schildkamp, 2021 ). The research trend of recognising the importance of teachers’ data literacy is often based on the premise that teachers’ data literacy would enhance teaching and ultimately improve student outcomes (cf. Ebbeler et al., 2016 ; Mandinach & Gummer, 2016 ; Poortman & Schildkamp, 2016 ; Thompson, 2012 ; Van Gasse et al., 2018 ; Zhao et al., 2016 ). Furthermore, the systemic pressure on schools to meet accountability requirements has also impacted their endeavors to utilize, assess, and demonstrate school performance based on student assessment data in recent years (Abdusyakur & Poortman, 2019 ; Farrell, 2015 ; Schildkamp et al., 2017 ; Weiss, 2012 ). In these contexts, it is not surprising that educational practitioners would think about student assessment data when they are expected to improve their data skills.

In this light, we have tallied the teacher data literacy indicators that directly relate to student assessment or about students’ learning outcomes . In Table  3 , the symbol “⁑” is used for the indicators related to student assessment, and “ξ” is used for the indicators related to students’ learning outcomes. We found that there were only 19 out of 95 indicators that directly related to student assessment (e.g., knowledge about different purposes of assessment, understanding the alignment between instruction and assessment, understanding state-level assessment policies on data use). Similarly, there were only 13 out of 95 indicators that directly related to students’ learning outcomes (e.g., identifying evidence of student learning outcomes, understanding student learning outcomes using multiple sources).

Our review demonstrates that teachers regularly interact with a diverse array of data and undertake various tasks closely associated with its utilization. Therefore, teachers' data literacy encompasses more than just its use in student assessment and learning outcomes; it extends to understanding students’ social-emotional learning and higher-order thinking skills, assessing school conditions for data use, reflecting on teaching practices, and communicating with colleagues. Consequently, limiting the perspective of teachers’ data literacy solely to assessment literacy may impede their full utilization and appreciation of data applications essential to their multifaceted work in supporting and enhancing student and school outcomes.

5.2 Teachers’ data literacy and data-related dispositions

We found that one of the key aspects of teachers’ data literacy is teachers’ dispositions towards data use. As noted by Mandinach and Gummer ( 2012 , 2016 ), this aspect of teacher characteristics has not received as much research attention as data knowledge or data skills. It is perhaps due to ‘literacy’ being traditionally linked to knowledge and skills (Shavelson et al., 2005 ; also see Mandinach & Gummer, 2012 ) or due to the research trend of unpacking teachers’ needs and pedagogical approaches in specific subject/learning domains (Sykes,  1999 ; see Mandinach & Gummer, 2016 ). However, our review suggests that teacher dispositions towards data use are required in virtually all aspects of data use and data analyses processes. We also found that the most important data-related teacher disposition was confidence . The data literacy literature recognized the importance of teacher confidence, with respect to accessing, collecting, analysing, integrating, evaluating, discussing, and making decisions, suggesting that for teachers to be data literate, confidence may be required in every step of data use. There has been extensive research that has demonstrated a strong link between confidence and learning motivation, indicating that individuals tend to gravitate towards domains in which they feel comfortable and confident (e.g., Lee & Durksen, 2018 ; Lee & Stankov, 2018 ; Stankov & Lee, 2008 ). Our review findings contribute to this existing body of research, emphasizing the importance of confidence in teachers’ data utilization. This underscores the necessity for policies and professional development initiatives aimed at enhancing teachers’ data use to also prioritize strategies for building teachers’ confidence in this area.

Our findings also indicate that teachers’ data literacy is associated with their trust in colleagues and school leaders, as well as their respect for the leadership team's role in leading data use and school improvement (Andersen, 2020 ; Ford, 2018 ; Wachen et al., 2018 ). This suggests that for teachers to be effective data users, they need to feel empowered to voice concerns and express frustrations with colleagues (Andersen, 2020 ; Ford, 2018 ; Wachen et al., 2018 ), seek help when necessary (Wardrip & Herman, 2018 ; Young, 2006 ), and collaboratively develop strategies for effective collaboration within the school (Datnow et al., 2013 ; Huffman & Kalnin, 2003 ; Michaud, 2016 ; Van Gasse et al., 2021 ).

Many teacher tasks are deeply intertwined with human relationships (Lee, 2021 ) and often completed through collaborative efforts (Li et al., 2022 ). Therefore, school leaders and policymakers may recognize that fostering teachers’ data literacy may necessitate cultivating open, honest, and trusting school environments conducive to collaboration. Notably, the social aspect of data literacy was not prominently evident in dimensions related to teachers' knowledge and skills, which suggests that teachers may enhance their knowledge and skills independently from others in the school environment. However, fostering teacher dispositions, such as active engagement in effective data use within the school, appears to be influenced by collaborative relationships with colleagues, as well as the supportive roles of school leaders.

5.3 Teachers’ data literacy and data-related behaviors

Our review showed that teachers’ data literacy goes beyond the knowledge, skills, and dispositions that are required to effectively use data; it also involves a range of behaviors that enhance their ways of using and learning about data. Within this dimension, we noted two sub-categories, communication/discussion and participation/engagement. Therefore, one core aspect of teacher behaviors related to data was found to be communicating with various stakeholders such as colleagues, parents, and school leaders to discuss instructional approaches (e.g., Datnow et al., 2013 ; Militello et al., 2013 ; van der Scheer & Visscher, 2018 ) and assessment results (e.g., Curry et al., 2016 ; Howley et al., 2013 ). The other aspect—participation and engagement—underscores the importance of teacher involvement in team-based learning regarding data use (e.g., Andersen, 2020 ; Young, 2006 ), active engagement in establishing conducive school conditions and fostering a culture of data use within the school community (e.g., Datnow et al., 2021 ; Keuning et al., 2016 ), and proactive participation in professional development to enhance knowledge and skills (e.g., Ebbeler et al., 2016 ; van der Scheer & Visscher, 2018 ). Existing studies on data literacy have not given substantial attention to the importance of teachers' behaviors related to data. However, we argue that teachers’ behaviors related to data deserve recognition as a distinct category within the concept of teachers’ data literacy.

Dimension 4 (about teachers’ disposition) and Dimension 5 (about teachers’ behaviors) would be correlated. For example, teachers who are confident in data use may be more inclined to lead the discussions with other colleagues about data use in the school, and they may pursue additional learning opportunities to become an effective leader in school data use. Trust and respect within the school communities mentioned above would also influence how teachers behave in order to collectively enhance data literacy within the school. Studies (e.g., Ebbeler et al., 2016 ; van der Scheer & Visscher, 2018 ) have highlighted teacher participation in professional development, but there has been a relative lack of research attention to examine the collaborative nature of teacher engagement and learning within the professional settings. With the rapid evolution of educational tools and applications driven by learning analytics and artificial intelligence, the influx of data generated in this new era poses a significant challenge for teachers and school leaders. Accordingly, teacher collaboration in learning and addressing data-related challenges in schools will increasingly become a paramount concern, more so than ever before. In this regard, future policies concerning data use may prioritize the expansion of teacher collaboration and mutual learning as essential components of in-school professional development activities.

5.4 Reflections on Mandinach and Gummer’s ( 2016 ) DLFT framework

We have compared the indicators and dimensions arising from the present study and those in Mandinach and Gummer's ( 2016 ) “data literacy for teachers” (DLFT) framework. For this purpose, the conceptually similar indicators of Mandinach and Gummer ( 2016 ) are included in Table  3 alongside the corresponding indicators identified in this study. As can be seen in Table  3 , some indicators were identified in both studies, but there were also notable differences between the two sets of indicators.

Firstly, it appears that there were more fine-grained indicators across the five dimensions arising from the present study, compared to those included in Mandinach and Gummer’s ( 2016 ) DLFT framework. For instance, our study identified the importance of teacher knowledge about externally administered assessments and associated policies to guide teacher use of data, which were not a part of Mandinach and Gummer’s ( 2016 ) DLFT framework. Overall, 95 indicators of the present study, compared to 59 indicators within Mandinach and Gummer’s ( 2016 ) DLFT framework, indicates the level of details incorporated in our framework.

Secondly, perhaps the most important discrepancy is articulated in our Dimension 3 “Dispositions towards Data Use”. We have identified 25 specific indicators under this dimension, which were clustered into confidence, values/belief, trust/respect, and anxiety. These four constructs were identified as the most prominently featured psychological dispositions when teachers deal with data in the school. In Mandinach and Gummer ( 2016 ), “Dispositions, habits of mind, or factors that include data use” is mentioned, but they “chose not to include them in the conceptual framework… [due to the nature of] these positions as general to effective teaching, rather than specific to data use. They are likely to influence data literacy but are seen as more general habits of mind of good teaching” (p. 372). As such, their framework did not include dispositions as integral part of teachers’ data literacy. We argue that teacher dispositions are an essential component of teachers’ data literacy. Perhaps this discrepancy may have arisen from the views that the teacher dispositions identified in Mandinach and Gummer ( 2016 ) are general teacher qualities – such as “belief that all students can learn”, “belief in data/think critically” and “belief that improvement in education requires a continuous inquiry cycle” (p. 372). On the other hand, teachers’ dispositions in our framework were all specific to data use – such as “confidence in integrating data from multiple sources”, “confidence in discussing data with colleagues”, “trust in principals’ leadership in data use”, “trust in open and honest discussions about data use with colleagues”, and “anxiety in using data to make decision”.

On a related point, and thirdly, our framework has two separate dimensions, one focusing on individuals’ psychological dispositions under “Dimension 3: Dispositions towards Data Use”, and the other centered on behaviors “Dimension 5: Data-Related Behavior”. Most of the indicators under the behavioral dimensions were found to be social interactions, communication, discussion, participation, and engagement, as mentioned above. In Mandinach and Gummer ( 2016 ), psychological dispositions (such as belief) and behavioral tendencies (such as ethical use of data, collaboration, and communication skills) were grouped into one dimension of “Dispositions, habits of mind, or factors that include data use”. Considering these, it appears that there was less emphasis on the dispositions and behavioral tendencies in Mandinach and Gummer ( 2016 ).

On the other hand, Mandinach and Gummer ( 2016 ) offered a fine-grained description of skill-related indicators within their DLFT framework. For example, our indicator of “selecting data appropriate for different purposes” was described with more granularity in the DLFT framework: “understand what data are appropriate”, “use qualitative and quantitative data”, “prioritize data”, and “understand specificity of data to question/problem”. Likewise, our indicator of “describing data patterns” was further divided into “understand data properties”, “access patterns and trends”, “drill down into data” and “examine data” in the DLFT framework. Additionally, two indicators within the Mandinach and Gummer’ ( 2016 ) framework—“understand student privacy” and “ethics use of data, including the protection of privacy and confidentiality of data”—did not fit into any of the indicators or dimensions of the present study. This is because we were unable to locate empirical studies that directly examined ethical data management and data use among teachers. Therefore, data ethics issues, which we believe to be an important aspect of teachers’ data literacy, were omitted from our framework.

Finally, we also note the differences between the broad dimensions proposed by Mandinach and Gummer's ( 2016 ) DLFT framework and our framework. The DLFT framework consisted of: (a) identifying problems and framing questions, (b) using data, (c) transforming data into information, (d) transforming information into decisions, and (e) evaluating outcomes. These five dimensions are primarily about data skills, which was just one dimension of our framework. Furthermore, their indicator descriptions suggest heavy emphasis on data use to inform teaching and learning. In contrast, our dimensions and indicators illustrate the broader purposes and contexts of teachers' data use, highlighting the significance of fostering teacher dispositions and data-related behaviors through effective leadership and a collaborative school environment. In particular, the detailed descriptors for each of the indicators under Dimensions 3, 4, and 5 of the present study are the strengths of our framework, as they illustrate a wide range of varied and specific purposes and data-related dispositions and behaviors related to teachers’ data literacy; these descriptions are relatively sparse in Mandinach and Gummer ( 2016 ).

5.5 Limitations of the present study and future research directions

We acknowledge several limitations of the present study. First, our review focused on empirical studies published in journal articles, and omitted government documents, books, and book chapters and publications by professional organizations. Second, we did not differentiate the studies based on in-service teachers vs. pre-service teachers. Future studies may look into potential differences between these two groups and suggest policy directions and strategies for teacher preparation. Third, teachers may possess discipline-unique capabilities and inclinations, and thus it may be worthwhile to identify teacher characteristics across different disciplines (e.g., Science vs. English) and examine the influences of discipline contexts on teachers’ data use and data literacy. Fourth, exploring teachers’ data literacy required for students at different levels of schooling (e.g., early childhood, primary, and secondary) and for students with diverse needs (e.g., learning difficulties, dyslexia) may provide further insights into the specific expectations within the daily tasks and responsibilities of teachers. Fifth, most of the reviewed studies were conducted in Western or English-speaking countries, and thus our findings may have limited relevance to teacher data literacy in different world regions. Future studies may investigate cross-country characteristics in teachers’ data literacy. Sixth, our research also reveals that current studies of teachers’ data literacy have not explored the possible connections between technological advancements, particularly in AI-based systems, and teachers’ data literacy. This suggests a need to investigate the link between teachers’ data literacy and their proficiency in understanding emerging technologies such as AI-based systems. It is anticipated that discussions on data ethics will emerge as a crucial aspect of teachers’ data literacy in the era of artificial intelligence (AI). Finally, our review did not include, and thus future reviews may examine, system-level contextual factors (e.g., digital technology infrastructure, schools’ socio-economic standing) and their influences on teacher practices in data use.

6 Conclusion

Our review of 83 empirical studies published between 1990 and 2021 produced 95 specific indicators of teachers’ data literacy. The indicators were further categorised into five dimensions: (a) knowledge about data , (b) skills in using data , (c) dispositions towards data use , (d) data applications for various purposes , and (e) data-related behaviors . Our findings suggest that teachers' data literacy encompasses more than just knowledge and skills; it also includes a wide range of dispositions and behaviors. Additionally, teacher data literacy extends beyond assessing student learning outcomes and meeting accountability requirements and includes teachers’ reflection and engagement in professional development.

Data availability

Data sharing not applicable to this article as no datasets were generated or analysed during the current study.

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Literacy development in the early childhood and elementary school years is critical for learning and the acquisition of other skills essential for educational achievement. Although schools typically assume the primary responsibility in developing children’s literacy and reading skills, a holistic approach to overall literacy development requires the involvement of other important actors, including parents, caregivers, community members, and libraries. Public libraries play a key role in the literacy landscape, especially by providing access to books and a variety of free literacy programs for families. The public library as a space and place that motivates kids to enjoy reading can lead to a lifelong love of learning. In summer 2023, IMLS commissioned a review of research literature that examines the effects of motivation to read and within reading programs in communities and, particularly, public libraries.

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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.

No funding resources were used in the creation of this review. This work was performed in support of S. Ramsay’s Healthcare Genetics and Genomics doctoral dissertation.

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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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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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• Cite this Page Paré G, Kitsiou S. Chapter 9 Methods for Literature Reviews. In: Lau F, Kuziemsky C, editors. Handbook of eHealth Evaluation: An Evidence-based Approach [Internet]. Victoria (BC): University of Victoria; 2017 Feb 27.
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• Published: 06 May 2024

Chronic atrophic gastritis and risk of incident upper gastrointestinal cancers: a systematic review and meta-analysis

• Junqiu Li   ORCID: orcid.org/0000-0003-3563-4831 1   na1 ,
• Jielu Pan 1   na1 ,
• Dinghong Xiao 1 ,
• Nan Shen 1 ,
• Ruiqing Wang 1 ,
• Hongyv Miao 1 ,
• Peimin Pu 1 ,
• Haiyan Zhang 1 ,
• Xiao Yv 1 &
• Lianjun Xing 1  

Journal of Translational Medicine volume  22 , Article number:  429 ( 2024 ) Cite this article

Metrics details

Previous literature has explored the relationship between chronic atrophic gastritis (CAG) and isolated cancers within the upper gastrointestinal cancers; However, an integrative synthesis across the totality of upper gastrointestinal cancers was conspicuously absent. The research objective was to assess the relationship between CAG and the risk of incident upper gastrointestinal cancers, specifically including gastric cancer, oesophageal cancer, and oesophagogastric junction cancer.

Rigorous systematic searches were conducted across three major databases, namely PubMed, Embase and Web of Science, encompassing the timeline from database inception until August 10, 2023. We extracted the necessary odds ratio (OR) and their corresponding 95% confidence interval (CI) for subsequent meta-analysis. Statistical analyses were conducted using Stata 17.0 software.

This meta-analysis included a total of 23 articles encompassing 5858 patients diagnosed with upper gastrointestinal cancers. CAG resulted in a statistically significant 4.12-fold elevated risk of incident gastric cancer (OR = 4.12, 95% CI 3.20–5.30). Likewise, CAG was linked to a 2.08-fold increased risk of incident oesophageal cancer (OR = 2.08, 95%CI 1.60–2.72). Intriguingly, a specific correlation was found between CAG and the risk of incident oesophageal squamous cell carcinoma (OR = 2.29, 95%CI 1.77–2.95), while no significant association was detected for oesophageal adenocarcinoma (OR = 0.62, 95%CI 0.17–2.26). Moreover, CAG was correlated with a 2.77-fold heightened risk of oesophagogastric junction cancer (OR = 2.77, 95%CI 2.21–3.46). Notably, for the same type of upper gastrointestinal cancer, it was observed that diagnosing CAG through histological methods was linked to a 33–77% higher risk of developing cancer compared to diagnosing CAG through serological methods.

This meta-analysis indicated a two- to fourfold increased risk of gastric cancer, oesophageal cancer, and oesophagogastric junction cancer in patients with CAG. Importantly, for the same upper gastrointestinal cancer, the risk of incident cancer was higher when CAG was diagnosed histologically compared to serological diagnosis. Further rigorous study designs are required to explore the impact of CAG diagnosed through both diagnostic methods on the risk of upper gastrointestinal cancers.

Introduction

Within the global healthcare arena, cancer plays a dual role, being both a disease of significant global interest and a principal factor in clinical mortality. It is characterized by a protracted disease course, a predisposition for deterioration, low survival rates, and a significant economic burden. With the ageing of the population and an increase in cancer risk factors, the incidence and mortality of cancer have also risen.

Upper gastrointestinal cancers, comprising gastric cancer (GC), oesophagogastric junction cancer (OJC), and oesophageal cancer (OC); Oesophageal cancer is mainly classified into two subtypes: oesophageal adenocarcinoma (OAC) and oesophageal squamous cell carcinoma (OSCC). In 2019, there were approximately 23.6 million new cancer cases reported worldwide, with upper gastrointestinal cancers representing about 7.6% of these cases; Meanwhile, the worldwide cancer-related mortality rate reached an estimated 10.0 million, and upper gastrointestinal cancers were responsible for roughly 14.6% of these deaths [ 1 ]. The etiopathogenesis and progression of upper gastrointestinal cancers are closely linked to numerous factors, including diet, lifestyle, and others [ 2 , 3 ]. Notably, Chronic atrophic gastritis (CAG) has captured the attention of researchers as a potential risk factor. This association is consistent with the involvement of chronic inflammation in cancer development [ 4 , 5 ].

CAG is a chronic inflammatory disease characterized by the reduction or loss of gastric mucosal glands, with or without metaplasia of the intestinal epithelium or pyloric glands. A primary etiological factor in the development of this disease is the infection of H. pylori [ 6 , 7 , 8 ]. Upon infection, the gastric mucosa undergoes an intense inflammatory response, resulting in tissue damage and an increased risk of cancer [ 9 ]. Subsequently, some researchers initiated studies of the associations between CAG and upper gastrointestinal cancers. Over the last 15 years, the majority of studies have primarily centred around meta-analyses examining the relationship between CAG and GC [ 10 , 11 ]. However, there has been relatively limited research concerning the relationship between CAG and OC or OJC. Notably, it was not until 2010 that a meta-analysis was published, reporting on the risk of gastric atrophy in the development of OAC and OSCC [ 12 ]. At present, no exhaustive meta-analysis offers a comprehensive assessment of the risk of upper gastrointestinal cancers in relation to CAG. Meanwhile, with advances in medical science and technology, the primary diagnostic modality for CAG has shifted towards histological methods, whereas previous studies mainly used serologic diagnostic modalities. However, Whether the risk relationship between CAG diagnosed using these two diagnostic methods and upper gastrointestinal cancers is consistent remains unclear and has not been clearly reported.

Consequently, we conducted this systematic review and meta-analysis to comprehensively and accurately assess the magnitude and nature of the relationship between CAG and the incidence risk of upper gastrointestinal cancers. Furthermore, we aimed to report the extent of risk associated with the diagnosis of CAG through histological and serological methods for the development of upper gastrointestinal cancers.

Materials and methods

This study was conducted in accordance with the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) [ 13 ] and was registered with the PROSPERO (CRD42023455940).

Search strategy

We systematically searched databases (PubMed, Embase, Web of Science) using a combination of search terms and free phrases to assess the risk association between CAG and upper gastrointestinal cancers. The search included articles published from the creation of the database through August 10, 2023. The search strategies used for each database are displayed in Additional file 1 : File 1 Search strategy.

Inclusion and exclusion criteria

The inclusion criteria were as follows: (1) Case–control studies, nested case–control studies, or cohort studies; (2) To investigate the risk relationship between CAG and upper gastrointestinal cancers; (3) The diagnosis of CAG is based on endoscopic histology or serological methods. (4) The study involved human participants, with no restrictions on race or gender, and all individuals were aged 18 years or older. (5) The main outcome was the incidence risk of upper gastrointestinal cancers, which was measured using odds ratio (OR).

The exclusion criteria were as follows: (1) Case reports, reviews, commentaries, animal and cell studies, as well as cross-sectional research; (2) Duplicate publications; (3) Literature with missing research data and inability to extract the required data; (4) Non-English literature; (5) Newcastle–Ottawa Scale score (NOS) < 7.

Data extraction and quality assessment

According to the inclusion and exclusion criteria, two researchers (JQL and XY) independently screened titles and abstracts that met the requirements. Subsequently, they obtained and read the full texts, selecting articles that met the specified criteria. According to the data extraction guidelines for systematic reviews and meta-analyses [ 14 ], two researchers independently extracted the following information: study design, study’s author and year of publication, country, sample size, outcomes, study period, sex, diagnosis of CAG, assessment of cancer, adjustment for covariates, participant source and NOS score.

If a study did not clearly give a standard definition of gastric atrophy, we defined it as atrophic gastritis based on histological evidence of gastric mucosal atrophy and intestinal metaplasia. This was based on an expert review of atrophic gastritis updated by the American Gastrointestinal Association [ 15 ]. Hence, when independently assessing the risks associated with gastric mucosal atrophy and intestinal metaplasia in the literature, we regarded them as separate studies. Similarly, when conducting separate risk assessments for histology and serology, we also treated them as separate studies. If the literature independently assessed the risks of non-cardia cancer and cardia cancer, we extracted relevant data on non-cardia cancer for the study of gastric cancer incidence risk. In accordance with the classification of oesophagogastric junction adenocarcinoma [ 16 ], we included cardia cancer-related data in the study of oesophagogastric junction cancer incidence risk.

We undertook a qualitative evaluation of the included literature utilizing the Newcastle–Ottawa Scale (NOS). This assessment was carried out independently by two researchers (JQL and JLP). The NOS scale comprises three aspects of evaluation, with scores ranging from 0 to 9. In this study, the quality assessment scores for all screened literature were 7 or higher. Therefore, the literature screened in this study was considered to be of high quality [ 17 ].

Any disagreements encountered during the processes of data extraction and quality assessment were addressed through discussions with the senior author (LJX).

Statistical methods

The meta-analysis was conducted by comparing the risk of upper gastrointestinal cancers between patients with and without CAG. We extracted OR, hazard ratio (HR), and relative risk (RR) from the eligible literature. Given the relatively low risk of upper gastrointestinal cancers, during the data analysis, the extracted HR and RR were approximated to be equal to the OR [ 18 ]. We used the OR and its corresponding 95% confidence interval (CI) for statistical analysis.

The statistical analyses were performed using Stata 17.0 software. To assess heterogeneity, we used the Q-test and the I 2 value. When I 2  > 50% or P < 0.1, we considered significant heterogeneity among the studies, allowing for the adoption of a random-effects model. Otherwise, a fixed-effects model was used; Additionally, in order to explore the sources of heterogeneity, we conducted subgroup analyses based on the diagnosis of CAG, study type, participant source, region, year of publication, and NOS score. Sensitivity analysis was conducted to evaluate the robustness and reliability of the results. Funnel plots and Egger's test were used to analyze publication bias.

Search results

Initially, we retrieved a total of 16,039 articles, which included 3422 from PubMed, 5489 from Embase, and 7128 from Web of Science. Among these, 6691 duplicates were identified and subsequently excluded, followed by the exclusion of 9,283 irrelevant articles after a screening of titles and abstracts. We conducted a comprehensive search of the full text of 65 articles, excluding one article that was unavailable. Following a detailed examination of the full texts, we excluded 41 studies for various reasons, including 21 studies lacking relevant outcomes, 11 studies with unrelated outcomes, 2 studies were letters, 1 study was review, 1 study in a non-English language, 1 study was conference abstract, and 4 studies with a NOS < 7.

Finally, a total of 23 articles involving 5858 patients diagnosed with upper gastrointestinal cancers were incorporated into this study. The flowchart of the study screening is shown in Fig.  1 (Page 30).

Flow chart of literature screening

Characteristics of included studies

We have identified 23 articles, containing 36 studies, to assess the relationship between CAG and the risk of incident upper gastrointestinal cancers [ 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 ]. Among these, 13 studies analyzed gastric cancer, 15 studies examined oesophageal cancer, and 8 studies explored oesophagogastric junction cancer. CAG was diagnosed using endoscopic histological methods (found in a total of 7 articles) and serological methods (found in a total of 18 articles), with 2 articles conducting research on both of these diagnostic approaches.

In the included literature, there were 10 case–control studies, 6 nested case–control studies, and 7 cohort studies. Detailed characteristics of these incorporated studies can be found in Table 1 (Pages 31–35). These studies were published between 1995 to 2023 and collectively involved 5858 patients diagnosed with upper gastrointestinal cancers, with two articles exclusively focused on male populations. For the source of study participants, there were 5 articles based on hospital-based research, 17 articles based on population-based research, and 1 article based on a combination of population and clinic-based research. In terms of the regional distribution of the study, 10 articles were performed in Europe, 11 articles in Asia (including 8 articles in Japan), and 2 articles in the Americas. According to the NOS scale score, 6 studies received a score of 9, 18 studies achieved a score of 8, and 12 studies were rated with a score of 7.

Risk of gastric cancer

Thirteen studies were included to assess the relationship between CAG and the incidence of GC. The heterogeneity test (I 2  = 73.6%, P < 0.1) indicated significant heterogeneity in this study. The pooled results were shown in Fig.  2 (Page 39): CAG was associated with a 4.12-fold increase in the risk of GC (pooled random effect OR = 4.12, 95%CI 3.20 ~ 5.30); The risk of incident GC, when diagnosed through histological methods for CAG, was higher (OR = 4.23, 95% CI 2.47–7.25) compared to the risk associated with diagnosing CAG through serological methods (OR = 3.88, 95% CI 3.00–5.00).

Forest plot to assess the relationship between CAG and gastric cancer. CAG chronic atrophic gastritis, OR odds ratio, CI confidence interval, IM intestinal metaplasia, AG atrophic gastritis

Significant heterogeneity was observed in this study. In order to delve the origins of heterogeneity, we conducted subgroup analyses based on the diagnosis method of CAG, study type, participant source, region, year of publication, and NOS score. The relevant results are presented in Table 2 (Page 36). There was no significant heterogeneity in nested case–control studies, European studies, or studies published between 1995 and 2010. However, significant heterogeneity was detected in all other subgroup analyses. In all subgroups, patients with CAG had a significantly increased risk of incident GC. Particularly, studies conducted in the United States showed the highest relative risk of GC incidence among patients with CAG (OR = 14.30, 95% CI 4.83–42.30). This study was both a case–control and a hospital-based study, and it showed that patients with CAG had a relatively low risk of developing GC (OR = 2.66, 95% CI 1.98–3.57). In other subgroup analyses, the risk of incident GC was very similar to the overall pooled risk.

Risk of oesophageal cancer

We included 15 studies that explored the association between CAG and the incidence of OC. The heterogeneity analysis indicated significant heterogeneity within this research (I 2  = 66.0%, P < 0.1). The pooled results were shown in Fig.  3 (Page 39).: CAG was associated with a 2.08-fold increase in the risk of incident OC (pooled random-effect OR = 2.08, 95% CI 1.60–2.72). The risk of incident OC was markedly higher with the diagnosis of CAG through histologic methods (OR = 2.26, 95% CI 1.58–3.23) compared to the risk associated with diagnosing CAG through serologic methods (OR = 1.93, 95%CI 1.22–3.07). Meanwhile, we assessed the relationship between CAG and the risk of incident OSCC and OAC (Figs. 4 , 5 ; Page 40). Our findings indicated that CAG was linked to a 2.29-fold increase in the risk of incident OSCC (pooled random-effects OR = 2.29, 95% CI 1.77–2.95, I 2  = 60.7%, P = 0.002). Nevertheless, there was no significant association between CAG and the risk of incident OAC (pooled random effect OR = 0.62, 95% CI 0.17–2.26, I 2  = 67.0%, P = 0.082).

Forest plot to assess the relationship between CAG and osophageal cancer. CAG chronic atrophic gastritis, OR odds ratio, CI confidence interval, FA fundic atrophy, FIM fundic intestinal metaplasia, FGA fundic gastric atrophy, OSCC oesophageal squamous cell carcinoma, OAC oesophageal adenocarcinoma

Forest plot to assess the relationship between CAG and oesophageal squamous cell carcinoma. CAG chronic atrophic gastritis, OR odds ratio, CI confidence interval, FA fundic atrophy, FIM fundic intestinal metaplasia, FGA fundic gastric atrophy

Forest plot to assess the relationship between CAG and oesophageal adenocarcinoma. CAG chronic atrophic gastritis, OR odds ratio, CI confidence interval

In order to explore the sources of heterogeneity, we performed subgroup analyses based on the diagnosis method of CAG, study type, participant source, region, year of publication, and NOS score. As shown in Table 3 (Pages 37, 38), there was no significant heterogeneity in studies where CAG diagnosis was based on histologic methods and those published from 2011 to 2023. However, significant heterogeneity was observed in all other subgroup analyses. Additionally, studies with an NOS score < 8 did not reveal a significant association between CAG and the risk of OC, whereas all other subgroup analyses indicated a significant correlation. In the nested case–control study (OR = 4.58, 95%CI 2.00–10.48) and the study conducted in the Americas (OR 5.33, 95%CL 1.55–18.30), patients with CAG had a relatively higher risk of incident OC. In studies published from 2011 to 2023, the risk of OC in patients with CAG was relatively lower (OR = 1.66, 95%CI 1.35–2.04). In all other subgroup analyses, the risk of incident cancer was similar to the overall pooled risk.

Risk of oesophagogastric junction cancer

We included 8 studies to examine the association between CAG and the risk of incident OJC. The heterogeneity test indicated a low level of heterogeneity in this study (I 2  = 18.2%, P = 0.286 > 0.1). The pooled results were displayed in Fig.  6 (Page 40): CAG was associated with a 2.77-fold increased risk of OJC (pooled fixed effect OR = 2.77, 95% CI 2.21–3.46). The risk of OJC was significantly higher when CAG was diagnosed through histological methods (OR = 3.40, 95%CI 2.04–5.67) compared to serological methods (OR = 2.63, 95%CI 2.05–3.38), and neither of these groups of studies displayed significant heterogeneity.

Forest plot to assess the relationship between CAG and oesophagogastric junction cancer. CAG chronic atrophic gastritis, OR odds ratio, CI confidence interval

Sensitivity analyses and publication bias

For GC, OC and OJC, we performed sensitivity analyses using a study-by-study exclusion approach, and our findings demonstrated the stability and reliability of the pooled results (Additional file 2 : Fig. S1a–c). To evaluate publication bias in GC and OC, we used funnel plots and Egger's tests. Visual inspection of the funnel plots (Fig.  7 ) (Page 41) showed that the distributions were generally symmetrical, indicating that there was no significant publication bias. The results of the Egger's test (Fig.  8 ) (Pages 41, 42) indicated that, in the analysis of GC (P = 0.283) and OC (P = 0.433), no significant publication bias was observed in the studies.

Publication bias. A Funnel plot of studies assessing the relationship between CAG and risk of gastric cancer. B Funnel plot of studies assessing the relationship between CAG and risk of oesophageal cancer

Publication bias. A Egger’ s test evaluating for the relationship between CAG and risk of gastric cancer. B Egger’ s test evaluating for the relationship between CAG and risk of oesophageal cancer

In this meta-analysis, we included a total of 23 studies involving 5858 patients diagnosed with upper gastrointestinal cancers. Our objective was to analyze the connection between CAG and the incidence of upper gastrointestinal cancers. The results clearly pointed to a significant 4.12-fold elevation in the risk of GC, a 2.77-fold increase in the risk of OJC, and a 2.08-fold rise in the risk of OC among patients with CAG. Furthermore, our findings indicated a 2.29-fold increased risk of OSCC in CAG patients. However, no significant association was detected with the risk of OAC. Intriguingly, when considering the same upper gastrointestinal cancer, the risk of developing cancer was higher with CAG diagnosed through histologic methods rather than serologic methods.

This study represents the first comprehensive assessment of the association between CAG and the incidence of upper gastrointestinal cancers. Our findings reveal a substantial increase in the risk of upper gastrointestinal cancers linked to CAG, which is both consistent and inconsistent with previously published meta-analyses in different regards. Previously, gastric atrophy has been correlated with a 2.89-fold elevated risk of Cardia Cancer when diagnosed through serologic methods [ 12 ]. In contrast, our current study explores the risk of CAG and the incidence of OJC, employing both histologic and serologic diagnostic methods. Additionally, Gastric Atrophy has previously exhibited associations with the risk of OSCC and OAC, with a 1.94-fold heightened risk of OSCC incidence but a reduced risk of OAC development [ 12 ]. In this study, we have not only reported the link between CAG and an elevated risk for developing OSCC and OAC but have also indicated its relevance to the risk of developing EC. Worth noting is that patients with Intestinal Metaplasia (IM) have been previously reported to exhibit a significant 3.58-fold increase in the risk of GC, particularly when IM develops in the gastric body or presents as incomplete IM [ 42 ]; A systematic review and meta-analysis conducted by Sui [ 43 ] indicated that there was a significant 2.91-fold increase in the risk of GC associated with gastric atrophy; These results correspond with the trends observed in our own study. Furthermore, Sui's study further reported that the risk of developing GC was higher with CAG diagnosed through serum pepsinogen levels rather than endoscopy [ 43 ]. Interestingly, this result contradicts the findings of our study.

We hypothesize several potential mechanisms underlying the association between CAG and upper gastrointestinal cancers. First and foremost, CAG is predominantly attributed to H. pylori infection. H. pylori can generate a multitude of virulence factors that target gastric mucosal tissues, disrupting intracellular signalling pathways and lowering the threshold for tumour transformation. Notably, the primary virulence factors of H. pylori include cytotoxin-associated gene A (CagA) and its pathogenicity island (Cag PAI), as well as vacuolating cytotoxin A (VacA). The Wnt signalling pathway, known for its role in cancer development, is implicated in GC through the upregulation of Wnt10A in gastric mucosa-associated cells, further activating the Wnt-β-catenin-Tcf signalling pathway, significantly contributing to GC development [ 44 ]. Similarly, the upregulation of Wnt10A may also be a factor in OC development [ 45 ], as subsequent studies have indicated its enhancement of invasion and migration in OSCC [ 46 ]. Secondly, CAG induced by H. pylori infection is characterized by reduced or complete abstention of gastric acid secretion, leading to the creation of a hypochlorhydric microenvironment. Such a microenvironment fosters the proliferation of oncogenic microorganisms within the stomach and augments the production of N-nitroso compounds, which significantly increases the risk of GC and OSCC [ 47 , 48 , 49 ]. The incidence risk of OAC is positively linked to gastroesophageal reflux symptoms [ 50 ] but negatively associated with H. pylori infection [ 41 ]. Consequently, CAG triggered by H. pylori infection would seem to either reduce the occurrence of OAC or have no discernible impact. The risk of OJC may exhibit two potential scenarios: some cases, similar to OAC, OJC could have a negative correlation or no association with CAG. meanwhile, others, resembling GC, may show a positive correlation with CAG. Lastly, chronic inflammation is one of the potential mechanisms contributing to cancer development, and this applies equally to upper gastrointestinal cancers. When tissue damage occurs, inflammatory cells gather and release inflammatory cytokines, thereby promoting the generation of reactive oxygen species (ROS). These ROS induce cellular proliferation, causing oxidative damage to DNA and, in turn, amplifying the risk of cancer development [ 4 ]. CAG remains in a chronic inflammatory state, particularly following H. pylori infection, which triggers the upregulation of multiple pro-inflammatory factors, including interleukin-8 (IL-8), nuclear factor-κB (NF-κB), tumour necrosis factor-α (TNF-α), and interleukin-6 (IL-6) and others. The upregulation of IL-8 and activation of NF-κB in gastric epithelial cells play pivotal roles in the mechanisms underlying chronic inflammation and the development of GC [ 51 ]. Additionally, NF-κB is closely associated with metastasis, inflammation, and poor prognosis in OC patients [ 52 ].

This meta-analysis reveals a certain degree of heterogeneity. To ensure the robustness of our findings, we conducted a sensitivity analysis, which confirmed the stability of the pooled results. In our assessment of GC and OC studies, both funnel plots and Egger's tests were employed, and the results consistently showed no clear evidence of publication bias.

In the subgroup analyses, notable findings emerged. In the GC study, all subgroup analyses consistently indicated a significant increase in GC risk among patients with CAG. It is worth highlighting that the studies conducted in the United States (US) reported the highest incidence of GC, even though GC is relatively uncommon in the US. This discovery emphasizes the potential relevance of serum pepsin as a predictive marker for GC in the US [ 32 ]. Among Asian research, Japan remains the sole contributor to relevant studies, emphasizing the necessity for broader participation from other Asian regions in future observational research. Notably, there was a study that served as both a case–control study and hospital-based research, revealing a comparatively lower risk level, possibly associated with the control group's population selection process. In the field of OC research, studies with NOS scores below 8 did not reveal any significant risk association. Nevertheless, all other subgroup analyses consistently pointed to a marked increase in OC incidence risk associated with CAG. Studies conducted in Latin America indicated the highest risk of OC, whereas research published between 2011 and 2023 showed a comparatively lower OC risk. Hospital-based studies showed a comparatively higher OC risk than population-based studies, possibly due to the inclusion of more severe cases from hospital settings.

Another crucial aspect of our study is the exploration of the association between CAG diagnosed through two different diagnostic methods and the risk of upper gastrointestinal cancers. In studies assessing GC risk in relation to CAG, histological confirmation of CAG was linked to a 35% increased risk of GC compared to serological diagnosis. Similarly, regarding the relationship between CAG and OC risk, histologic diagnosis of CAG was connected to a 33% higher risk of OC compared to serologic diagnosis. Moreover, in the investigation of the risk of OJC associated with CAG, histological confirmation of CAG was associated with a 77% elevated risk of OJC compared to serological diagnosis. In general, for GC, OC and OJC, the risk of cancer development was linked to a 33%-77% higher when CAG is diagnosed histologically compared to serologically. It's important to note that the guidelines for managing precancerous gastric epithelial lesions and other lesions recommend serum pepsinogen level as the best noninvasive test for detecting atrophic gastritis. However, in cases of low serum pepsinogen levels, reliance on gastroscopy is necessary [ 53 ]. The accuracy of endoscopic biopsy results can be influenced by a range of factors, including the quality of biopsy samples, specimen handling, and the expertise of pathologists [ 54 ]. Furthermore, the use of different analytical methods and threshold values with serum pepsinogen diagnosis can result in varying levels of specificity and sensitivity [ 55 ]. Therefore, further research and investigation are essential to comprehensively assess the risk associated with CAG diagnosis for upper gastrointestinal cancers using these two methods.

Our meta-analysis has also additional important strengths. As previously mentioned, our study aims to provide the most comprehensive evaluation of the connection between CAG and the risk of upper gastrointestinal cancers to date. We have included data from Asia, Europe, and the Americas, ensuring that the selected studies adhere to a high standard of quality.

However, there are certain limitations to our study. Firstly, the pooled results are constrained by the scarcity of studies focusing on the association between CAG and the risk of incident OAC. Future large-scale observational studies are imperative to delve deeper into the relationship between CAG and the incidence of OAC. Furthermore, the studies we have incorporated into our analysis display differences in adjusted factors and involve differing study designs, potentially introducing additional bias into the pooled findings. The data in our study was primarily sourced from medical records and cancer registries, which might introduce a degree of selection bias into the dataset. Finally, the primary diagnostic modalities for CAG include endoscopic histology and serum pepsinogen levels. While these two methods are widely used in current medical practice, they still exhibit certain limitations. The former can be influenced by factors such as the endoscopist's skill, specimen handling protocols, and diagnostic interpretation by the pathologist, whereas the results of the latter may fluctuate based on specimen analysis techniques and the selection of critical values.

This meta-analysis showed a two- to fourfold increased risk of GC, EC and EJC in patients with CAG. Importantly, for the same upper gastrointestinal cancer, the risk of incident cancer was higher when CAG was diagnosed through histological methods compared to serological methods. Further rigorous study designs are required to explore the impact of CAG diagnosed through both diagnostic methods on the risk of upper gastrointestinal cancers.

Availability of data and materials

All data generated or analyzed during this study are included in this published article [and its Additional files].

Abbreviations

• Chronic atrophic gastritis

Confidence interval

• Gastric cancer
• Oesophagogastric junction cancer
• Oesophageal cancer

Oesophageal adenocarcinoma

Oesophageal squamous cell carcinoma

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

Newcastle–Ottawa Scale score

Hazard ratio

Relative risk

Intestinal metaplasia

Atrophic gastritis

Fundic atrophy

Fundic intestinal metaplasia

Fundic gastric atrophy

Interleukin-8

Nuclear factor-κB

Tumour necrosis factor-α

Interleukin-6

The United States

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Acknowledgements

This work was supported by the support from the National Natural Science Foundation of China (82174240); the Shanghai Pudong New Area Science and Technology Development Fund Project (NO: PKJ2021-Y69); and the Shanghai Pudong Famous Chinese Medicine Training Program (NO: PWRzm2020-03).

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Junqiu Li and Jielu Pan have contributed equally to this work.

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Department II of Digestive Diseases, Longhua Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, 200032, China

Junqiu Li, Jielu Pan, Dinghong Xiao, Nan Shen, Ruiqing Wang, Hongyv Miao, Peimin Pu, Haiyan Zhang, Xiao Yv & Lianjun Xing

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JQL, JLP, XY and LJX contributed research ideas; JQL and XY contributed to the literature screening and data extraction; JQL and JLP contributed to the study quality assessment; DHX, NS and RQW and contributed software applications and statistical analyses; JQL, HYM, PMP and HYZ contributed writing and preparation of the original manuscript; LJX contributed research supervision; All authors contributed to the original writing and review of the manuscript. All authors read and reviewed the final version of the manuscript.

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Supplementary Information

Additional file 1: file 1.

Search strategy.

Additional file 2: Fig. S1.

Sensitivity analysis was performed for gastric cancer (GC), oesophageal cancer (OC), and oesophagogastric junction cancer (OJC) using a study-by-study exclusion approach.

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Li, J., Pan, J., Xiao, D. et al. Chronic atrophic gastritis and risk of incident upper gastrointestinal cancers: a systematic review and meta-analysis. J Transl Med 22 , 429 (2024). https://doi.org/10.1186/s12967-023-04736-w

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Received : 01 October 2023

Accepted : 15 November 2023

Published : 06 May 2024

DOI : https://doi.org/10.1186/s12967-023-04736-w

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• Upper gastrointestinal cancers
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Journal of Translational Medicine

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