sources of literature review in research methodology

Literature review sources

Sources for literature review can be divided into three categories as illustrated in table below. In your dissertation you will need to use all three categories of literature review sources:

Sources for literature review and examples

Generally, your literature review should integrate a wide range of sources such as:

• Books . Textbooks remain as the most important source to find models and theories related to the research area. Research the most respected authorities in your selected research area and find the latest editions of books authored by them. For example, in the area of marketing the most notable authors include Philip Kotler, Seth Godin, Malcolm Gladwell, Emanuel Rosen and others.
• Magazines . Industry-specific magazines are usually rich in scholarly articles and they can be effective source to learn about the latest trends and developments in the research area. Reading industry magazines can be the most enjoyable part of the literature review, assuming that your selected research area represents an area of your personal and professional interests, which should be the case anyways.
• Newspapers can be referred to as the main source of up-to-date news about the latest events related to the research area. However, the proportion of the use of newspapers in literature review is recommended to be less compared to alternative sources of secondary data such as books and magazines. This is due to the fact that newspaper articles mainly lack depth of analyses and discussions.
• Online articles . You can find online versions of all of the above sources. However, note that the levels of reliability of online articles can be highly compromised depending on the source due to the high levels of ease with which articles can be published online. Opinions offered in a wide range of online discussion blogs cannot be usually used in literature review. Similarly, dissertation assessors are not keen to appreciate references to a wide range of blogs, unless articles in these blogs are authored by respected authorities in the research area.

Your secondary data sources may comprise certain amount of grey literature as well. The term grey literature refers to type of literature produced by government, academics, business and industry in print and electronic formats, which is not controlled by commercial publishers. It is called ‘grey’ because the status of the information in grey literature is not certain. In other words, any publication that has not been peer reviewed for publication is grey literature.

The necessity to use grey literature arises when there is no enough peer reviewed publications are available for the subject of your study.

John Dudovskiy

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• How to Write a Literature Review | Guide, Examples, & Templates

How to Write a Literature Review | Guide, Examples, & Templates

Published on January 2, 2023 by Shona McCombes . Revised on September 11, 2023.

What is a literature review? A literature review is a survey of scholarly sources on a specific topic. It provides an overview of current knowledge, allowing you to identify relevant theories, methods, and gaps in the existing research that you can later apply to your paper, thesis, or dissertation topic .

There are five key steps to writing a literature review:

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

A good literature review doesn’t just summarize sources—it analyzes, synthesizes , and critically evaluates to give a clear picture of the state of knowledge on the subject.

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Table of contents

What is the purpose of a literature review, examples of literature reviews, step 1 – search for relevant literature, step 2 – evaluate and select sources, step 3 – identify themes, debates, and gaps, step 4 – outline your literature review’s structure, step 5 – write your literature review, free lecture slides, other interesting articles, frequently asked questions, introduction.

• Quick Run-through
• Step 1 & 2

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

• Demonstrate your familiarity with the topic and its scholarly context
• Develop a theoretical framework and methodology for your research
• Position your work in relation to other researchers and theorists
• Show how your research addresses a gap or contributes to a debate
• Evaluate the current state of research and demonstrate your knowledge of the scholarly debates around your topic.

Writing literature reviews is a particularly important skill if you want to apply for graduate school or pursue a career in research. We’ve written a step-by-step guide that you can follow below.

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

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

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

Download Word doc Download Google doc

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

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

Make a list of keywords

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

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

Search for relevant sources

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

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

You can also use boolean operators to help narrow down your search.

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

You likely won’t be able to read absolutely everything that has been written on your topic, so it will be necessary to evaluate which sources are most relevant to your research question.

For each publication, ask yourself:

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

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

You can use our template to summarize and evaluate sources you’re thinking about using. Click on either button below to download.

Take notes and cite your sources

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

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

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

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

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

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

There are various approaches to organizing the body of a literature review. Depending on the length of your literature review, you can combine several of these strategies (for example, your overall structure might be thematic, but each theme is discussed chronologically).

Chronological

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

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

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

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

Methodological

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

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

Theoretical

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

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

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

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

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

As you write, you can follow these tips:

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

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

When you’ve finished writing and revising your literature review, don’t forget to proofread thoroughly before submitting. Not a language expert? Check out Scribbr’s professional proofreading services !

This article has been adapted into lecture slides that you can use to teach your students about writing a literature review.

Scribbr slides are free to use, customize, and distribute for educational purposes.

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

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

 Statistics

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

Research bias

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

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

It is often written as part of a thesis, dissertation , or research paper , in order to situate your work in relation to existing knowledge.

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

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

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

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

A literature review is a survey of credible sources on a topic, often used in dissertations , theses, and research papers . Literature reviews give an overview of knowledge on a subject, helping you identify relevant theories and methods, as well as gaps in existing research. Literature reviews are set up similarly to other  academic texts , with an introduction , a main body, and a conclusion .

An  annotated bibliography is a list of  source references that has a short description (called an annotation ) for each of the sources. It is often assigned as part of the research process for a  paper .  

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Research Methods

• Getting Started
• Literature Review Research
• Research Design
• Research Design By Discipline
• SAGE Research Methods
• Teaching with SAGE Research Methods

Literature Review

• What is a Literature Review?
• What is NOT a Literature Review?
• Purposes of a Literature Review
• Types of Literature Reviews
• Literature Reviews vs. Systematic Reviews
• Systematic vs. Meta-Analysis

Literature Review  is a comprehensive survey of the works published in a particular field of study or line of research, usually over a specific period of time, in the form of an in-depth, critical bibliographic essay or annotated list in which attention is drawn to the most significant works.

Also, we can define a literature review as the collected body of scholarly works related to a topic:

• Summarizes and analyzes previous research relevant to a topic
• Includes scholarly books and articles published in academic journals
• Can be an specific scholarly paper or a section in a research paper

The objective of a Literature Review is to find previous published scholarly works relevant to an specific topic

• Help gather ideas or information
• Keep up to date in current trends and findings
• Help develop new questions

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.
• Helps focus your own research questions or problems
• Discovers relationships between research studies/ideas.
• Suggests unexplored ideas or populations
• Identifies major themes, concepts, and researchers on a topic.
• Tests assumptions; may help counter preconceived ideas and remove unconscious bias.
• Identifies critical gaps, points of disagreement, or potentially flawed methodology or theoretical approaches.
• Indicates potential directions for future research.

All content in this section is from Literature Review Research from Old Dominion University 

Keep in mind the following, a literature review is NOT:

Not an essay 

Not an annotated bibliography  in which you summarize each article that you have reviewed.  A literature review goes beyond basic summarizing to focus on the critical analysis of the reviewed works and their relationship to your research question.

Not a research paper   where you select resources to support one side of an issue versus another.  A lit review should explain and consider all sides of an argument in order to avoid bias, and areas of agreement and disagreement should be highlighted.

A literature review serves several purposes. For example, it

• provides thorough knowledge of previous studies; introduces seminal works.
• helps focus one’s own research topic.
• identifies a conceptual framework for one’s own research questions or problems; indicates potential directions for future research.
• suggests previously unused or underused methodologies, designs, quantitative and qualitative strategies.
• identifies gaps in previous studies; identifies flawed methodologies and/or theoretical approaches; avoids replication of mistakes.
• helps the researcher avoid repetition of earlier research.
• suggests unexplored populations.
• determines whether past studies agree or disagree; identifies controversy in the literature.
• tests assumptions; may help counter preconceived ideas and remove unconscious bias.

As Kennedy (2007) notes*, 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 original studies. Third, there are the perceptions, conclusions, opinion, and interpretations that are shared informally that become part of the lore of 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 several approaches to how they can be done, depending upon the type of analysis underpinning your study. Listed below are definitions of types of literature reviews:

Argumentative Review      This form examines literature selectively in order to support or refute an argument, deeply imbedded 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 to make summary claims of the sort found in systematic reviews.

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. A well-done integrative review meets the same standards as primary research in regard to clarity, rigor, and replication.

Historical Review      Few things rest in isolation from historical precedent. Historical reviews are focused 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 [content], but how they said it [method of analysis]. This approach provides a framework of understanding at different levels (i.e. those of theory, substantive fields, research approaches and data collection and analysis techniques), enables researchers to draw on 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, and helps highlight many ethical issues which we should be aware of and consider as we go through our 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 analyse data from the studies that are included in the review. 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?"

Theoretical Review      The purpose of this form is to concretely examine the corpus of theory that has accumulated in regard to an issue, concept, theory, phenomena. The theoretical literature review help 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.

* Kennedy, Mary M. "Defining a Literature."  Educational Researcher  36 (April 2007): 139-147.

All content in this section is from The Literature Review created by Dr. Robert Larabee USC

Robinson, P. and Lowe, J. (2015),  Literature reviews vs systematic reviews.  Australian and New Zealand Journal of Public Health, 39: 103-103. doi: 10.1111/1753-6405.12393

What's in the name? The difference between a Systematic Review and a Literature Review, and why it matters . By Lynn Kysh from University of Southern California

Systematic review or meta-analysis?

A  systematic review  answers a defined research question by collecting and summarizing all empirical evidence that fits pre-specified eligibility criteria.

A  meta-analysis  is the use of statistical methods to summarize the results of these studies.

Systematic reviews, just like other research articles, can be of varying quality. They are a significant piece of work (the Centre for Reviews and Dissemination at York estimates that a team will take 9-24 months), and to be useful to other researchers and practitioners they should have:

• clearly stated objectives with pre-defined eligibility criteria for studies
• explicit, reproducible methodology
• a systematic search that attempts to identify all studies
• assessment of the validity of the findings of the included studies (e.g. risk of bias)
• systematic presentation, and synthesis, of the characteristics and findings of the included studies

Not all systematic reviews contain meta-analysis. 

Meta-analysis is the use of statistical methods to summarize the results of independent studies. By combining information from all relevant studies, meta-analysis can provide more precise estimates of the effects of health care than those derived from the individual studies included within a review.  More information on meta-analyses can be found in  Cochrane Handbook, Chapter 9 .

A meta-analysis goes beyond critique and integration and conducts secondary statistical analysis on the outcomes of similar studies.  It is a systematic review that uses quantitative methods to synthesize and summarize the results.

An advantage of a meta-analysis is the ability to be completely objective in evaluating research findings.  Not all topics, however, have sufficient research evidence to allow a meta-analysis to be conducted.  In that case, an integrative review is an appropriate strategy. 

Some of the content in this section is from Systematic reviews and meta-analyses: step by step guide created by Kate McAllister.

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• Next: Research Design >>
• Last Updated: Jul 15, 2024 10:34 AM
• URL: https://guides.lib.udel.edu/researchmethods

• 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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• Next: How to Pick a Topic >>
• Last Updated: Sep 21, 2022 2:16 PM
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Writing a Literature Review

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

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

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

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

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

What are the parts of a lit review?

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

Introduction:

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

Conclusion:

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

How should I organize my lit review?

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

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

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

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

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

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

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

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

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What is a literature review?

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.

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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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Chapter 5: The Literature Review

5.3 Acceptable sources for literature reviews

Following are a few acceptable sources for literature reviews, listed in order from what will be considered most acceptable to less acceptable sources for your literature review assignments:

• Peer reviewed journal articles.
• Edited academic books.
• Articles in professional journals.
• Statistical data from government websites.
• Website material from professional associations (use sparingly and carefully). The following sections will explain and provide examples of these various sources.

Peer Reviewed Journal Articles (Papers)

A peer reviewed journal article is a paper that has been submitted to a scholarly journal, accepted, and published. Peer review journal papers go through a rigorous, blind review process of peer review. What this means is that two to three experts in the area of research featured in the paper have reviewed and accepted the paper for publication. The names of the author(s) who are seeking to publish the research have been removed (blind review), so as to minimize any bias towards the authors of the research (albeit, sometimes a savvy reviewer can discern who has done the research based upon previous publications, etc.). This blind review process can be long (often 12 to 18 months) and may involve many back and forth edits on the behalf of the researchers, as they work to address the edits and concerns of the peers who reviewed their paper. Often, reviewers will reject the paper for a variety of reasons, such as unclear or questionable methods, lack of contribution to the field, etc. Because peer reviewed journal articles have gone through a rigorous process of review, they are considered to be the premier source for research. Peer reviewed journal articles should serve as the foundation for your literature review.

The following link will provide more information on peer reviewed journal articles. Make sure you watch the little video on the upper left-hand side of your screen, in addition to reading the material at the following website:    http://guides.lib.jjay.cuny.edu/c.php?g=288333&p=1922599

Edited Academic Books

An edited academic book is a collection of scholarly scientific papers written by different authors. The works are original papers, not published elsewhere (“Edited volume,” 2018). The papers within the text also go through a process of review; however, the review is often not a blind review because the authors have been invited to contribute to the book. Consequently, edited academic books are fine to use for your literature review, but you also want to ensure that your literature review contains mostly peer reviewed journal papers.

Articles in Professional Journals

Articles from professional journals should be used with caution for your literature review. This is because articles in trade journals are not usually peer reviewed, even though they may appear to be. A good way to find out is to read the “About Us” section of the professional journal, which should state whether or not the papers are peer reviewed. You can also find out by Googling the name of the journal and adding “peer reviewed” to the search.

Statistical Data from Governmental Websites

Governmental websites can be excellent sources for statistical data, e.g, Statistics Canada collects and publishes data related to the economy, society, and the environment.

Website Material from Professional Associations

Material from other websites can also serve as a source for statistics that you may need for your literature review. Since you want to justify the value of the research that interests you, you might make use of a professional association’s website to learn how many members they have, for example. You might want to demonstrate, as part of the introduction to your literature review, why more research on the topic of PTSD in police officers is important. You could use peer reviewed journal articles to determine the prevalence of PTSD in police officers in Canada in the last ten years, and then use the Ontario Police Officers´ Association website to determine the approximate number of police officers employed in the Province of Ontario over the last ten years. This might help you estimate how many police officers could be suffering with PTSD in Ontario. That number could potentially help to justify a research grant down the road. But again, this type of website- based material should be used with caution and sparingly.

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Does your assignment or publication require that you write a literature review? This guide is intended to help you understand what a literature is, why it is worth doing, and some quick tips composing one.

Understanding Literature Reviews

What is a literature review  .

Typically, a literature review is a written discussion that examines publications about  a particular subject area or topic. Depending on disciplines, publications, or authors a literature review may be: 

A summary of sources An organized presentation of sources A synthesis or interpretation of sources An evaluative analysis of sources

A Literature Review may be part of a process or a product. It may be:

A part of your research process A part of your final research publication An independent publication

Why do a literature review?

The Literature Review will place your research in context. It will help you and your readers:  

Locate patterns, relationships, connections, agreements, disagreements, & gaps in understanding Identify methodological and theoretical foundations Identify landmark and exemplary works Situate your voice in a broader conversation with other writers, thinkers, and scholars

The Literature Review will aid your research process. It will help you to:

Establish your knowledge Understand what has been said Define your questions Establish a relevant methodology Refine your voice Situate your voice in the conversation

What does a literature review look like?

The Literature Review structure and organization may include sections such as:  

An introduction or overview A body or organizational sub-divisions A conclusion or an explanation of significance

The body of a literature review may be organized in several ways, including:

Chronologically: organized by date of publication Methodologically: organized by type of research method used Thematically: organized by concept, trend, or theme Ideologically: organized by belief, ideology, or school of thought

• Find a focus
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Literature Review Basics

• Primary & Secondary Sources
• Literature Review Introduction
• Writing Literature Reviews
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The Literature

The Literature refers to the collection of scholarly writings on a topic. This includes peer-reviewed articles, books, dissertations and conference papers.

• When reviewing the literature, be sure to include major works as well as studies that respond to major works. You will want to focus on primary sources, though secondary sources can be valuable as well.

Primary Sources

The term primary source is used broadly to embody all sources that are original. P rimary sources provide first-hand information that is closest to the object of study. Primary sources vary by discipline.

• In the natural and social sciences, original reports of research found in academic journals detailing the methodology used in the research, in-depth descriptions, and discussions of the findings are considered primary sources of information.
• Other common examples of primary sources include speeches, letters, diaries, autobiographies, interviews, official reports, court records, artifacts, photographs, and drawings.  

Galvan, J. L. (2013). Writing literature reviews: A guide for students of the social and behavioral sciences . Glendale, CA: Pyrczak.

Secondary Sources

A secondary source is a source that provides non-original or secondhand data or information. 

• Secondary sources are written about primary sources.
• Research summaries reported in textbooks, magazines, and newspapers are considered secondary sources. They typically provide global descriptions of results with few details on the methodology. Other examples of secondary sources include biographies and critical studies of an author's work.

Secondary Source. (2005). In W. Paul Vogt (Ed.), Dictionary of Statistics & Methodology. (3 rd ed., p. 291). Thousand Oaks, CA: SAGE Publications, Inc.

Weidenborner, S., & Caruso, D. (1997). Writing research papers: A guide to the process . New York: St. Martin's Press.

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Ten Simple Rules for Writing a Literature Review

Marco pautasso.

1 Centre for Functional and Evolutionary Ecology (CEFE), CNRS, Montpellier, France

2 Centre for Biodiversity Synthesis and Analysis (CESAB), FRB, Aix-en-Provence, France

Literature reviews are in great demand in most scientific fields. Their need stems from the ever-increasing output of scientific publications [1] . For example, compared to 1991, in 2008 three, eight, and forty times more papers were indexed in Web of Science on malaria, obesity, and biodiversity, respectively [2] . Given such mountains of papers, scientists cannot be expected to examine in detail every single new paper relevant to their interests [3] . Thus, it is both advantageous and necessary to rely on regular summaries of the recent literature. Although recognition for scientists mainly comes from primary research, timely literature reviews can lead to new synthetic insights and are often widely read [4] . For such summaries to be useful, however, they need to be compiled in a professional way [5] .

When starting from scratch, reviewing the literature can require a titanic amount of work. That is why researchers who have spent their career working on a certain research issue are in a perfect position to review that literature. Some graduate schools are now offering courses in reviewing the literature, given that most research students start their project by producing an overview of what has already been done on their research issue [6] . However, it is likely that most scientists have not thought in detail about how to approach and carry out a literature review.

Reviewing the literature requires the ability to juggle multiple tasks, from finding and evaluating relevant material to synthesising information from various sources, from critical thinking to paraphrasing, evaluating, and citation skills [7] . In this contribution, I share ten simple rules I learned working on about 25 literature reviews as a PhD and postdoctoral student. Ideas and insights also come from discussions with coauthors and colleagues, as well as feedback from reviewers and editors.

Rule 1: Define a Topic and Audience

How to choose which topic to review? There are so many issues in contemporary science that you could spend a lifetime of attending conferences and reading the literature just pondering what to review. On the one hand, if you take several years to choose, several other people may have had the same idea in the meantime. On the other hand, only a well-considered topic is likely to lead to a brilliant literature review [8] . The topic must at least be:

• interesting to you (ideally, you should have come across a series of recent papers related to your line of work that call for a critical summary),
• an important aspect of the field (so that many readers will be interested in the review and there will be enough material to write it), and
• a well-defined issue (otherwise you could potentially include thousands of publications, which would make the review unhelpful).

Ideas for potential reviews may come from papers providing lists of key research questions to be answered [9] , but also from serendipitous moments during desultory reading and discussions. In addition to choosing your topic, you should also select a target audience. In many cases, the topic (e.g., web services in computational biology) will automatically define an audience (e.g., computational biologists), but that same topic may also be of interest to neighbouring fields (e.g., computer science, biology, etc.).

Rule 2: Search and Re-search the Literature

After having chosen your topic and audience, start by checking the literature and downloading relevant papers. Five pieces of advice here:

• keep track of the search items you use (so that your search can be replicated [10] ),
• keep a list of papers whose pdfs you cannot access immediately (so as to retrieve them later with alternative strategies),
• use a paper management system (e.g., Mendeley, Papers, Qiqqa, Sente),
• define early in the process some criteria for exclusion of irrelevant papers (these criteria can then be described in the review to help define its scope), and
• do not just look for research papers in the area you wish to review, but also seek previous reviews.

The chances are high that someone will already have published a literature review ( Figure 1 ), if not exactly on the issue you are planning to tackle, at least on a related topic. If there are already a few or several reviews of the literature on your issue, my advice is not to give up, but to carry on with your own literature review,

The bottom-right situation (many literature reviews but few research papers) is not just a theoretical situation; it applies, for example, to the study of the impacts of climate change on plant diseases, where there appear to be more literature reviews than research studies [33] .

• discussing in your review the approaches, limitations, and conclusions of past reviews,
• trying to find a new angle that has not been covered adequately in the previous reviews, and
• incorporating new material that has inevitably accumulated since their appearance.

When searching the literature for pertinent papers and reviews, the usual rules apply:

• be thorough,
• use different keywords and database sources (e.g., DBLP, Google Scholar, ISI Proceedings, JSTOR Search, Medline, Scopus, Web of Science), and
• look at who has cited past relevant papers and book chapters.

Rule 3: Take Notes While Reading

If you read the papers first, and only afterwards start writing the review, you will need a very good memory to remember who wrote what, and what your impressions and associations were while reading each single paper. My advice is, while reading, to start writing down interesting pieces of information, insights about how to organize the review, and thoughts on what to write. This way, by the time you have read the literature you selected, you will already have a rough draft of the review.

Of course, this draft will still need much rewriting, restructuring, and rethinking to obtain a text with a coherent argument [11] , but you will have avoided the danger posed by staring at a blank document. Be careful when taking notes to use quotation marks if you are provisionally copying verbatim from the literature. It is advisable then to reformulate such quotes with your own words in the final draft. It is important to be careful in noting the references already at this stage, so as to avoid misattributions. Using referencing software from the very beginning of your endeavour will save you time.

Rule 4: Choose the Type of Review You Wish to Write

After having taken notes while reading the literature, you will have a rough idea of the amount of material available for the review. This is probably a good time to decide whether to go for a mini- or a full review. Some journals are now favouring the publication of rather short reviews focusing on the last few years, with a limit on the number of words and citations. A mini-review is not necessarily a minor review: it may well attract more attention from busy readers, although it will inevitably simplify some issues and leave out some relevant material due to space limitations. A full review will have the advantage of more freedom to cover in detail the complexities of a particular scientific development, but may then be left in the pile of the very important papers “to be read” by readers with little time to spare for major monographs.

There is probably a continuum between mini- and full reviews. The same point applies to the dichotomy of descriptive vs. integrative reviews. While descriptive reviews focus on the methodology, findings, and interpretation of each reviewed study, integrative reviews attempt to find common ideas and concepts from the reviewed material [12] . A similar distinction exists between narrative and systematic reviews: while narrative reviews are qualitative, systematic reviews attempt to test a hypothesis based on the published evidence, which is gathered using a predefined protocol to reduce bias [13] , [14] . When systematic reviews analyse quantitative results in a quantitative way, they become meta-analyses. The choice between different review types will have to be made on a case-by-case basis, depending not just on the nature of the material found and the preferences of the target journal(s), but also on the time available to write the review and the number of coauthors [15] .

Rule 5: Keep the Review Focused, but Make It of Broad Interest

Whether your plan is to write a mini- or a full review, it is good advice to keep it focused 16 , 17 . Including material just for the sake of it can easily lead to reviews that are trying to do too many things at once. The need to keep a review focused can be problematic for interdisciplinary reviews, where the aim is to bridge the gap between fields [18] . If you are writing a review on, for example, how epidemiological approaches are used in modelling the spread of ideas, you may be inclined to include material from both parent fields, epidemiology and the study of cultural diffusion. This may be necessary to some extent, but in this case a focused review would only deal in detail with those studies at the interface between epidemiology and the spread of ideas.

While focus is an important feature of a successful review, this requirement has to be balanced with the need to make the review relevant to a broad audience. This square may be circled by discussing the wider implications of the reviewed topic for other disciplines.

Rule 6: Be Critical and Consistent

Reviewing the literature is not stamp collecting. A good review does not just summarize the literature, but discusses it critically, identifies methodological problems, and points out research gaps [19] . After having read a review of the literature, a reader should have a rough idea of:

• the major achievements in the reviewed field,
• the main areas of debate, and
• the outstanding research questions.

It is challenging to achieve a successful review on all these fronts. A solution can be to involve a set of complementary coauthors: some people are excellent at mapping what has been achieved, some others are very good at identifying dark clouds on the horizon, and some have instead a knack at predicting where solutions are going to come from. If your journal club has exactly this sort of team, then you should definitely write a review of the literature! In addition to critical thinking, a literature review needs consistency, for example in the choice of passive vs. active voice and present vs. past tense.

Rule 7: Find a Logical Structure

Like a well-baked cake, a good review has a number of telling features: it is worth the reader's time, timely, systematic, well written, focused, and critical. It also needs a good structure. With reviews, the usual subdivision of research papers into introduction, methods, results, and discussion does not work or is rarely used. However, a general introduction of the context and, toward the end, a recapitulation of the main points covered and take-home messages make sense also in the case of reviews. For systematic reviews, there is a trend towards including information about how the literature was searched (database, keywords, time limits) [20] .

How can you organize the flow of the main body of the review so that the reader will be drawn into and guided through it? It is generally helpful to draw a conceptual scheme of the review, e.g., with mind-mapping techniques. Such diagrams can help recognize a logical way to order and link the various sections of a review [21] . This is the case not just at the writing stage, but also for readers if the diagram is included in the review as a figure. A careful selection of diagrams and figures relevant to the reviewed topic can be very helpful to structure the text too [22] .

Rule 8: Make Use of Feedback

Reviews of the literature are normally peer-reviewed in the same way as research papers, and rightly so [23] . As a rule, incorporating feedback from reviewers greatly helps improve a review draft. Having read the review with a fresh mind, reviewers may spot inaccuracies, inconsistencies, and ambiguities that had not been noticed by the writers due to rereading the typescript too many times. It is however advisable to reread the draft one more time before submission, as a last-minute correction of typos, leaps, and muddled sentences may enable the reviewers to focus on providing advice on the content rather than the form.

Feedback is vital to writing a good review, and should be sought from a variety of colleagues, so as to obtain a diversity of views on the draft. This may lead in some cases to conflicting views on the merits of the paper, and on how to improve it, but such a situation is better than the absence of feedback. A diversity of feedback perspectives on a literature review can help identify where the consensus view stands in the landscape of the current scientific understanding of an issue [24] .

Rule 9: Include Your Own Relevant Research, but Be Objective

In many cases, reviewers of the literature will have published studies relevant to the review they are writing. This could create a conflict of interest: how can reviewers report objectively on their own work [25] ? Some scientists may be overly enthusiastic about what they have published, and thus risk giving too much importance to their own findings in the review. However, bias could also occur in the other direction: some scientists may be unduly dismissive of their own achievements, so that they will tend to downplay their contribution (if any) to a field when reviewing it.

In general, a review of the literature should neither be a public relations brochure nor an exercise in competitive self-denial. If a reviewer is up to the job of producing a well-organized and methodical review, which flows well and provides a service to the readership, then it should be possible to be objective in reviewing one's own relevant findings. In reviews written by multiple authors, this may be achieved by assigning the review of the results of a coauthor to different coauthors.

Rule 10: Be Up-to-Date, but Do Not Forget Older Studies

Given the progressive acceleration in the publication of scientific papers, today's reviews of the literature need awareness not just of the overall direction and achievements of a field of inquiry, but also of the latest studies, so as not to become out-of-date before they have been published. Ideally, a literature review should not identify as a major research gap an issue that has just been addressed in a series of papers in press (the same applies, of course, to older, overlooked studies (“sleeping beauties” [26] )). This implies that literature reviewers would do well to keep an eye on electronic lists of papers in press, given that it can take months before these appear in scientific databases. Some reviews declare that they have scanned the literature up to a certain point in time, but given that peer review can be a rather lengthy process, a full search for newly appeared literature at the revision stage may be worthwhile. Assessing the contribution of papers that have just appeared is particularly challenging, because there is little perspective with which to gauge their significance and impact on further research and society.

Inevitably, new papers on the reviewed topic (including independently written literature reviews) will appear from all quarters after the review has been published, so that there may soon be the need for an updated review. But this is the nature of science [27] – [32] . I wish everybody good luck with writing a review of the literature.

Acknowledgments

Many thanks to M. Barbosa, K. Dehnen-Schmutz, T. Döring, D. Fontaneto, M. Garbelotto, O. Holdenrieder, M. Jeger, D. Lonsdale, A. MacLeod, P. Mills, M. Moslonka-Lefebvre, G. Stancanelli, P. Weisberg, and X. Xu for insights and discussions, and to P. Bourne, T. Matoni, and D. Smith for helpful comments on a previous draft.

Funding Statement

This work was funded by the French Foundation for Research on Biodiversity (FRB) through its Centre for Synthesis and Analysis of Biodiversity data (CESAB), as part of the NETSEED research project. The funders had no role in the preparation of the manuscript.

Research Methods: Literature Reviews

• Annotated Bibliographies
• Literature Reviews
• Scoping Reviews
• Systematic Reviews
• Scholarship of Teaching and Learning
• Persuasive Arguments
• Subject Specific Methodology

A literature review involves researching, reading, analyzing, evaluating, and summarizing scholarly literature (typically journals and articles) about a specific topic. The results of a literature review may be an entire report or article OR may be part of a article, thesis, dissertation, or grant proposal. A literature review helps the author learn about the history and nature of their topic, and identify research gaps and problems.

Steps & Elements

Problem formulation

• Determine your topic and its components by asking a question
• Research: locate literature related to your topic to identify the gap(s) that can be addressed
• Read: read the articles or other sources of information
• Analyze: assess the findings for relevancy
• Evaluating: determine how the article are relevant to your research and what are the key findings
• Synthesis: write about the key findings and how it is relevant to your research

Elements of a Literature Review

• Summarize subject, issue or theory under consideration, along with objectives of the review
• Divide works under review into categories (e.g. those in support of a particular position, those against, those offering alternative theories entirely)
• Explain how each work is similar to and how it varies from the others
• Conclude 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 an area of research

Writing a Literature Review Resources

• How to Write a Literature Review From the Wesleyan University Library
• Write a Literature Review From the University of California Santa Cruz Library. A Brief overview of a literature review, includes a list of stages for writing a lit review.
• Literature Reviews From the University of North Carolina Writing Center. Detailed information about writing a literature review.
• Undertaking a literature review: a step-by-step approach Cronin, P., Ryan, F., & Coughan, M. (2008). Undertaking a literature review: A step-by-step approach. British Journal of Nursing, 17(1), p.38-43

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Literature reviews.

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• Plan your search
• Where to search
• Refine and update your search
• Finding grey literature
• Writing the review
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Research methods overview

Finding literature on research methodologies, sage research methods online.

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What are research methods?

Research methodology is the specific strategies, processes, or techniques utilised in the collection of information that is created and analysed.

The methodology section of a research paper, or thesis, enables the reader to critically evaluate the study’s validity and reliability by addressing how the data was collected or generated, and how it was analysed.

Types of research methods

There are three main types of research methods which use different designs for data collection.  

(1) Qualitative research

Qualitative research gathers data about lived experiences, emotions or behaviours, and the meanings individuals attach to them. It assists in enabling researchers to gain a better understanding of complex concepts, social interactions or cultural phenomena. This type of research is useful in the exploration of how or why things have occurred, interpreting events and describing actions.

Examples of qualitative research designs include:

• focus groups
• observations
• document analysis
• oral history or life stories  

(2) Quantitative research

Quantitative research gathers numerical data which can be ranked, measured or categorised through statistical analysis. It assists with uncovering patterns or relationships, and for making generalisations. This type of research is useful for finding out how many, how much, how often, or to what extent.

Examples of quantitative research designs include:

• surveys or questionnaires
• observation
• document screening
• experiments  

(3) Mixed method research

Mixed Methods research integrates both Qualitative research and Quantitative research. It provides a holistic approach combining and analysing the statistical data with deeper contextualised insights. Using Mixed Methods also enables triangulation, or verification, of the data from two or more sources.

Sometimes in your literature review, you might need to discuss and evaluate relevant research methodologies in order to justify your own choice of research methodology.

When searching for literature on research methodologies it is important to search across a range of sources. No single information source will supply all that you need. Selecting appropriate sources will depend upon your research topic.

Developing a robust search strategy will help reduce irrelevant results. It is good practice to plan a strategy before you start to search.

Search tips

(1) free text keywords.

Free text searching is the use of natural language words to conduct your search. Use selective free text keywords such as: phenomenological, "lived experience", "grounded theory", "life experiences", "focus groups", interview, quantitative, survey, validity, variance, correlation and statistical.

To locate books on your desired methodology, try LibrarySearch . Remember to use  refine  options such as books, ebooks, subject, and publication date.  

(2) Subject headings in Databases

Databases categorise their records using subject terms, or a controlled vocabulary (thesaurus). These subject headings may be useful to use, in addition to utilising free text keywords in a database search.

Subject headings will differ across databases, for example, the PubMed database uses 'Qualitative Research' whilst the CINHAL database uses 'Qualitative Studies.'  

(3) Limiting search results

Databases enable sets of results to be limited or filtered by specific fields, look for options such as Publication Type, Article Type, etc. and apply them to your search.  

(4) Browse the Library shelves

To find books on  research methods  browse the Library shelves at call number  001.42

• SAGE Research Methods Online SAGE Research Methods Online (SRMO) is a research tool supported by a newly devised taxonomy that links content and methods terms. It provides the most comprehensive picture available today of research methods (quantitative, qualitative and mixed methods) across the social and behavioural sciences.

SAGE Research Methods Overview  (2:07 min) by SAGE Publishing  ( YouTube ) 

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Home » Literature Review – Types Writing Guide and Examples

Literature Review – Types Writing Guide and Examples

Table of Contents

Literature Review

Definition:

A literature review is a comprehensive and critical analysis of the existing literature on a particular topic or research question. It involves identifying, evaluating, and synthesizing relevant literature, including scholarly articles, books, and other sources, to provide a summary and critical assessment of what is known about the topic.

Types of Literature Review

Types of Literature Review are as follows:

• Narrative literature review : This type of review involves a comprehensive summary and critical analysis of the available literature on a particular topic or research question. It is often used as an introductory section of a research paper.
• Systematic literature review: This is a rigorous and structured review that follows a pre-defined protocol to identify, evaluate, and synthesize all relevant studies on a specific research question. It is often used in evidence-based practice and systematic reviews.
• Meta-analysis: This is a quantitative review that uses statistical methods to combine data from multiple studies to derive a summary effect size. It provides a more precise estimate of the overall effect than any individual study.
• Scoping review: This is a preliminary review that aims to map the existing literature on a broad topic area to identify research gaps and areas for further investigation.
• Critical literature review : This type of review evaluates the strengths and weaknesses of the existing literature on a particular topic or research question. It aims to provide a critical analysis of the literature and identify areas where further research is needed.
• Conceptual literature review: This review synthesizes and integrates theories and concepts from multiple sources to provide a new perspective on a particular topic. It aims to provide a theoretical framework for understanding a particular research question.
• Rapid literature review: This is a quick review that provides a snapshot of the current state of knowledge on a specific research question or topic. It is often used when time and resources are limited.
• Thematic literature review : This review identifies and analyzes common themes and patterns across a body of literature on a particular topic. It aims to provide a comprehensive overview of the literature and identify key themes and concepts.
• Realist literature review: This review is often used in social science research and aims to identify how and why certain interventions work in certain contexts. It takes into account the context and complexities of real-world situations.
• State-of-the-art literature review : This type of review provides an overview of the current state of knowledge in a particular field, highlighting the most recent and relevant research. It is often used in fields where knowledge is rapidly evolving, such as technology or medicine.
• Integrative literature review: This type of review synthesizes and integrates findings from multiple studies on a particular topic to identify patterns, themes, and gaps in the literature. It aims to provide a comprehensive understanding of the current state of knowledge on a particular topic.
• Umbrella literature review : This review is used to provide a broad overview of a large and diverse body of literature on a particular topic. It aims to identify common themes and patterns across different areas of research.
• Historical literature review: This type of review examines the historical development of research on a particular topic or research question. It aims to provide a historical context for understanding the current state of knowledge on a particular topic.
• Problem-oriented literature review : This review focuses on a specific problem or issue and examines the literature to identify potential solutions or interventions. It aims to provide practical recommendations for addressing a particular problem or issue.
• Mixed-methods literature review : This type of review combines quantitative and qualitative methods to synthesize and analyze the available literature on a particular topic. It aims to provide a more comprehensive understanding of the research question by combining different types of evidence.

Parts of Literature Review

Parts of a literature review are as follows:

Introduction

The introduction of a literature review typically provides background information on the research topic and why it is important. It outlines the objectives of the review, the research question or hypothesis, and the scope of the review.

Literature Search

This section outlines the search strategy and databases used to identify relevant literature. The search terms used, inclusion and exclusion criteria, and any limitations of the search are described.

Literature Analysis

The literature analysis is the main body of the literature review. This section summarizes and synthesizes the literature that is relevant to the research question or hypothesis. The review should be organized thematically, chronologically, or by methodology, depending on the research objectives.

Critical Evaluation

Critical evaluation involves assessing the quality and validity of the literature. This includes evaluating the reliability and validity of the studies reviewed, the methodology used, and the strength of the evidence.

The conclusion of the literature review should summarize the main findings, identify any gaps in the literature, and suggest areas for future research. It should also reiterate the importance of the research question or hypothesis and the contribution of the literature review to the overall research project.

The references list includes all the sources cited in the literature review, and follows a specific referencing style (e.g., APA, MLA, Harvard).

How to write Literature Review

Here are some steps to follow when writing a literature review:

• Define your research question or topic : Before starting your literature review, it is essential to define your research question or topic. This will help you identify relevant literature and determine the scope of your review.
• Conduct a comprehensive search: Use databases and search engines to find relevant literature. Look for peer-reviewed articles, books, and other academic sources that are relevant to your research question or topic.
• Evaluate the sources: Once you have found potential sources, evaluate them critically to determine their relevance, credibility, and quality. Look for recent publications, reputable authors, and reliable sources of data and evidence.
• Organize your sources: Group the sources by theme, method, or research question. This will help you identify similarities and differences among the literature, and provide a structure for your literature review.
• Analyze and synthesize the literature : Analyze each source in depth, identifying the key findings, methodologies, and conclusions. Then, synthesize the information from the sources, identifying patterns and themes in the literature.
• Write the literature review : Start with an introduction that provides an overview of the topic and the purpose of the literature review. Then, organize the literature according to your chosen structure, and analyze and synthesize the sources. Finally, provide a conclusion that summarizes the key findings of the literature review, identifies gaps in knowledge, and suggests areas for future research.
• Edit and proofread: Once you have written your literature review, edit and proofread it carefully to ensure that it is well-organized, clear, and concise.

Examples of Literature Review

Here’s an example of how a literature review can be conducted for a thesis on the topic of “ The Impact of Social Media on Teenagers’ Mental Health”:

• Start by identifying the key terms related to your research topic. In this case, the key terms are “social media,” “teenagers,” and “mental health.”
• Use academic databases like Google Scholar, JSTOR, or PubMed to search for relevant articles, books, and other publications. Use these keywords in your search to narrow down your results.
• Evaluate the sources you find to determine if they are relevant to your research question. You may want to consider the publication date, author’s credentials, and the journal or book publisher.
• Begin reading and taking notes on each source, paying attention to key findings, methodologies used, and any gaps in the research.
• Organize your findings into themes or categories. For example, you might categorize your sources into those that examine the impact of social media on self-esteem, those that explore the effects of cyberbullying, and those that investigate the relationship between social media use and depression.
• Synthesize your findings by summarizing the key themes and highlighting any gaps or inconsistencies in the research. Identify areas where further research is needed.
• Use your literature review to inform your research questions and hypotheses for your thesis.

For example, after conducting a literature review on the impact of social media on teenagers’ mental health, a thesis might look like this:

“Using a mixed-methods approach, this study aims to investigate the relationship between social media use and mental health outcomes in teenagers. Specifically, the study will examine the effects of cyberbullying, social comparison, and excessive social media use on self-esteem, anxiety, and depression. Through an analysis of survey data and qualitative interviews with teenagers, the study will provide insight into the complex relationship between social media use and mental health outcomes, and identify strategies for promoting positive mental health outcomes in young people.”

Reference: Smith, J., Jones, M., & Lee, S. (2019). The effects of social media use on adolescent mental health: A systematic review. Journal of Adolescent Health, 65(2), 154-165. doi:10.1016/j.jadohealth.2019.03.024

Reference Example: Author, A. A., Author, B. B., & Author, C. C. (Year). Title of article. Title of Journal, volume number(issue number), page range. doi:0000000/000000000000 or URL

Applications of Literature Review

some applications of literature review in different fields:

• Social Sciences: In social sciences, literature reviews are used to identify gaps in existing research, to develop research questions, and to provide a theoretical framework for research. Literature reviews are commonly used in fields such as sociology, psychology, anthropology, and political science.
• Natural Sciences: In natural sciences, literature reviews are used to summarize and evaluate the current state of knowledge in a particular field or subfield. Literature reviews can help researchers identify areas where more research is needed and provide insights into the latest developments in a particular field. Fields such as biology, chemistry, and physics commonly use literature reviews.
• Health Sciences: In health sciences, literature reviews are used to evaluate the effectiveness of treatments, identify best practices, and determine areas where more research is needed. Literature reviews are commonly used in fields such as medicine, nursing, and public health.
• Humanities: In humanities, literature reviews are used to identify gaps in existing knowledge, develop new interpretations of texts or cultural artifacts, and provide a theoretical framework for research. Literature reviews are commonly used in fields such as history, literary studies, and philosophy.

Role of Literature Review in Research

Here are some applications of literature review in research:

• Identifying Research Gaps : Literature review helps researchers identify gaps in existing research and literature related to their research question. This allows them to develop new research questions and hypotheses to fill those gaps.
• Developing Theoretical Framework: Literature review helps researchers develop a theoretical framework for their research. By analyzing and synthesizing existing literature, researchers can identify the key concepts, theories, and models that are relevant to their research.
• Selecting Research Methods : Literature review helps researchers select appropriate research methods and techniques based on previous research. It also helps researchers to identify potential biases or limitations of certain methods and techniques.
• Data Collection and Analysis: Literature review helps researchers in data collection and analysis by providing a foundation for the development of data collection instruments and methods. It also helps researchers to identify relevant data sources and identify potential data analysis techniques.
• Communicating Results: Literature review helps researchers to communicate their results effectively by providing a context for their research. It also helps to justify the significance of their findings in relation to existing research and literature.

Purpose of Literature Review

Some of the specific purposes of a literature review are as follows:

• To provide context: A literature review helps to provide context for your research by situating it within the broader body of literature on the topic.
• To identify gaps and inconsistencies: A literature review helps to identify areas where further research is needed or where there are inconsistencies in the existing literature.
• To synthesize information: A literature review helps to synthesize the information from multiple sources and present a coherent and comprehensive picture of the current state of knowledge on the topic.
• To identify key concepts and theories : A literature review helps to identify key concepts and theories that are relevant to your research question and provide a theoretical framework for your study.
• To inform research design: A literature review can inform the design of your research study by identifying appropriate research methods, data sources, and research questions.

Characteristics of Literature Review

Some Characteristics of Literature Review are as follows:

• Identifying gaps in knowledge: A literature review helps to identify gaps in the existing knowledge and research on a specific topic or research question. By analyzing and synthesizing the literature, you can identify areas where further research is needed and where new insights can be gained.
• Establishing the significance of your research: A literature review helps to establish the significance of your own research by placing it in the context of existing research. By demonstrating the relevance of your research to the existing literature, you can establish its importance and value.
• Informing research design and methodology : A literature review helps to inform research design and methodology by identifying the most appropriate research methods, techniques, and instruments. By reviewing the literature, you can identify the strengths and limitations of different research methods and techniques, and select the most appropriate ones for your own research.
• Supporting arguments and claims: A literature review provides evidence to support arguments and claims made in academic writing. By citing and analyzing the literature, you can provide a solid foundation for your own arguments and claims.
• I dentifying potential collaborators and mentors: A literature review can help identify potential collaborators and mentors by identifying researchers and practitioners who are working on related topics or using similar methods. By building relationships with these individuals, you can gain valuable insights and support for your own research and practice.
• Keeping up-to-date with the latest research : A literature review helps to keep you up-to-date with the latest research on a specific topic or research question. By regularly reviewing the literature, you can stay informed about the latest findings and developments in your field.

Advantages of Literature Review

There are several advantages to conducting a literature review as part of a research project, including:

• Establishing the significance of the research : A literature review helps to establish the significance of the research by demonstrating the gap or problem in the existing literature that the study aims to address.
• Identifying key concepts and theories: A literature review can help to identify key concepts and theories that are relevant to the research question, and provide a theoretical framework for the study.
• Supporting the research methodology : A literature review can inform the research methodology by identifying appropriate research methods, data sources, and research questions.
• Providing a comprehensive overview of the literature : A literature review provides a comprehensive overview of the current state of knowledge on a topic, allowing the researcher to identify key themes, debates, and areas of agreement or disagreement.
• Identifying potential research questions: A literature review can help to identify potential research questions and areas for further investigation.
• Avoiding duplication of research: A literature review can help to avoid duplication of research by identifying what has already been done on a topic, and what remains to be done.
• Enhancing the credibility of the research : A literature review helps to enhance the credibility of the research by demonstrating the researcher’s knowledge of the existing literature and their ability to situate their research within a broader context.

Limitations of Literature Review

Limitations of Literature Review are as follows:

• Limited scope : Literature reviews can only cover the existing literature on a particular topic, which may be limited in scope or depth.
• Publication bias : Literature reviews may be influenced by publication bias, which occurs when researchers are more likely to publish positive results than negative ones. This can lead to an incomplete or biased picture of the literature.
• Quality of sources : The quality of the literature reviewed can vary widely, and not all sources may be reliable or valid.
• Time-limited: Literature reviews can become quickly outdated as new research is published, making it difficult to keep up with the latest developments in a field.
• Subjective interpretation : Literature reviews can be subjective, and the interpretation of the findings can vary depending on the researcher’s perspective or bias.
• Lack of original data : Literature reviews do not generate new data, but rather rely on the analysis of existing studies.
• Risk of plagiarism: It is important to ensure that literature reviews do not inadvertently contain plagiarism, which can occur when researchers use the work of others without proper attribution.

About the author

Muhammad Hassan

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• Open access
• Published: 22 August 2024

Research on the relationship of coupling coordination between digitalization and green development

• Qunzhi She 1 ,
• Jing Qian 1 &
• Liangxi He 2  

Scientific Reports volume  14 , Article number:  19569 ( 2024 ) Cite this article

Metrics details

• Environmental economics
• Environmental social sciences

The coupling coordination of digitalization and green development has become an inevitable requirement for building a new development pattern and achieving high-quality development of China’s economy. Based on the panel data of 284 Chinese cities from 2011 to 2021, this study uses the coupling coordination degree model, Dagum Gini coefficient, spatial convergence, Markov transfer probability matrix, and panel Tobit model to quantitatively analyze the spatial–temporal evolution characteristics and influencing factors of the coupling coordination degree of digitization and green development. The study results show that the coupling coordination degree (CCD) of digitalization and green development has an overall increasing trend during the study period, and the eastern region is higher than other regions which showing spatial non-equilibrium characteristics. The spatial difference of the CCD continues to downward, and inter-regional differences are the main source of the CCD. In the long run, there is a “catch-up effect” between cities with low CCD and those with high CCD, and the CCD of digitalization and green development will tend to a steady state. The transfer type of the CCD has the characteristics of “club convergence”, the probability of maintaining the original state is high, and the overall CCD shows a good development trend in the future. Factors such as environmental regulation, green innovation, industrial structure upgrading and financial efficiency can significantly contribute to the CCD of digitalization and green development. The above findings provide empirical evidence of the CCD of digitalization and green development to achieve high-quality economic development.

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Introduction.

The coupling coordination of digitalization and green development, as two important trends in the new round of technological revolution and industrial change, provides an important field for high-quality economic development. Digital economy, as a new economic form, has been deeply integrated into the economy and society with its powerful penetration ability, wide coverage and far-reaching influence. The digital economy has become a new hand of China’s strategy of “changing mode, adjusting structure, and replacing kinetic energy” and an important engine to lead China’s high-quality economic development 1 . Green development is a great way of economic growth and social development that aims at efficiency, harmony and sustainability, and is an inevitable requirement for the economy to shift to high-quality development 2 . The digital economy help society achieve green development, and green development can balance the relationship between the digital economy and the protection of environmental resources 3 . Digitalization and green development are gradually evolving from “flying in tandem” to “integration and symbiosis”, ultimately realizing a “win–win” situation for economic and social development and environmental protection.

The specific connotation of the coupling coordination of digitalization and green development can be summarized as “digitalization empowers the green development, and green development leads the upgrading of digitalization”. Specifically, the use of big data, the Internet of Things, cloud computing and other digital technologies to help energy saving, carbon reduction and pollution reduction, to achieve optimal use of resources, contributing to a win–win situation for economic and environmental benefits; the greening process of the energy structure transformation, the low-carbon technologies application, resource recycling, etc. put forward a higher demand for digital technology to promote the in-depth integration of digital technology and various industries to achieve a comprehensive green development. In the relationship between digital empowerment and green traction, digitalization and green development will be promoting each other and deeply synergistic. Ultimately, digitalization and green development will be achieving coupling coordination development. The specific coupling coordination of digitalization and green development model is shown in Fig.  1 .

The coupling coordination of digitalization and green development model.

The digitalization and green development, as an important driving force and objective function of economic transformation and development, the relationship between two remains underexplored. It is of great theoretical and practical significance for achieving sustainable economic development to accurately understand the coupling coordination degree of digitalization and green development, and to quantitatively analyze whether digitalization and green development can achieve double-wheel synergistic drive. This paper enriches existing research by analyzing the CCD of digitization and green development in 284 Chinese cities from 2011 to 2021. By constructing a comprehensive evaluation system for both digitization and green development, this paper employs the entropy weight-TOPSIS method to evaluate the respective levels of digitization and green development, and the coupled coordination degree model is used to evaluate their interactions. This paper study the spatial and temporal differences, distribution dynamics and convergence and the influence factors of the CCD of digitalization and green development by using Dagum’s Gini coefficient, β-convergence, Markov chain analysis, and panel Tobit model.

The main contributions of this paper are as follows: (1) This paper explore the CCD of digitalization green development at the city level, which provides a detailed understanding of the spatial and temporal differences in the CCD of digitalization and green development; (2) With the help of methods and models such as entropy weight-TOPSIS method, coupled coordination model, Dagum’s Gini coefficient, convergence, Markov chain analysis etc., this paper systematically analyses the dynamic evolution and convergence trend of the CCD of digitalization and green development, providing empirical evidence for CCD of digitalization and green development research;(3) This paper also explores the influencing factors affecting the CCD of digitalization and green development with the help of the panel Tobit model, which provides an effective contribution to the subsequent research on CCD of digitalization and green development. By analyzing the regional differences and temporal characteristics of CCD of digitalization and green development in cities, this paper will help to theoretically understand the interaction between digitization and green development, and provide a theoretical basis and policy recommendations for further promoting digital greening synergistic development.

Literature review

The research in this paper focuses on the literature related to the measurement of digitization and its influencing effects, the evaluation indicators and influencing factors of greening and the interrelationships of digitization and green development.

First, the research related to digitalization, early research on digitalization mainly around its connotation, in 1996, the economist Don Tapscott first formally put forward the concept of ‘digital economy’ 4 , and then the definition of digitalization from the digital industry, a narrow concept of the digital economy 5 , to a broader concept of the digital economy, specifically digital economy is a series of economic activities which takes data resources as key production factors, modern information networks as important carriers and communication technology as a driving force for efficiency improvement and economic structure optimization 6 . With the enrichment of the connotation of digital economy, scholars have begun to explore the measurement of digitization 7 , 8 , 9 , the economic effect of digitization 10 and the environmental effect of digitization 11 , 12 . And the greening of digitization has gradually attracted the attention of scholars. The ICT industry itself is an energy-intensive industry 13 . With the development of social digitization, the use of digital industrial equipment generates a large amount of digital pollution 14 . Kyaw Than Oo et al 15 found that although digital technology is becoming more and more important in our daily life, it is also due to digital technology that our carbon footprint increases significantly and causes serious ecological consequences.

Second, the studies related to green development. Many scholars have studied green economy accounting and green development capacity measurement from the perspective of macroeconomic development 16 , 17 , 18 . Nicolas constructed an evaluation index system for green development by selecting dozens of statistical variables from the three dimensions of economy, society and environment 19 . In terms of the influencing factors of urban green development, in addition to exploring the impact of technological innovation 20 , 21 , industrial agglomeration 22 , 23 , foreign direct investment 24 , 25 , trade openness 26 , environmental regulation 27 , 28 , the opening of high-speed railways 29 , 30 , scholars have also carried out a large number of in-depth studies on the impact of digitization on green development 31 , 32 , 33 , 34 , 35 .

The research on the relationship between digitalization and green development was first discussed and explored by scholars from a theoretical perspective. Qian et al. 36 elaborated from the macro policy level that the green economy and digital economy are a relationship of mutual need and mutual assistance. Jiang 37 analyzed from three perspectives that digitalization is the new driving force for high-quality development, green economy transformation is the fundamental way for high-quality development, and digitalization is an important path to achieve the dual-carbon goal. They also analyzed that the integrated development of the green economy and the digital economy is an inevitable choice for the future of the sustainable digital era. With the proposal of the CCD of digitalization and green development, scholars have gradually begun to quantitatively analyze the relevant aspects of CCD of digitalization and green development. Wu Xiaoxu et al. 38 explored the CCD of technological innovation and green development from a systems theory perspective based on 2004–2019 Chinese urban panel data, and found that the CCD of technological innovation and green development in the Yellow River Basin was only 0.3363, which was at a relatively low level. Zhao Huixin and Meng Yujie 39 empirically analyzed the CCD of digital economy and green technological innovation in 271 cities in China based on 2013–2018 data, and found that the CCD between the two showed an upward trend, but the CCD was only moderate, and there were significant regional and urban differences. Zhen Junjie et al. 40 started with provincial panel data and explored the CCD of digital innovation and high-quality economic development in China. They found that most of China’s digital innovation and high-quality economic development are in a moderate or mild state of imbalance, and the fundamental reason for this long-term imbalance is that digital innovation lags behind high-quality economic development for a long time.

In summary, existing independent research on urban digitalization and green development is relatively rich, scholars have explored in depth the economic and environmental effects of digitalization, the path mechanism to achieve green development, while there is a relative lack of research on the relationship between digitalization and green development. Although some scholars have paid attention to the CCD of digitization and green development, there has been no quantitative analysis of the CCD of digitization and green development, and no in-depth exploration of the spatial and temporal characteristics and dynamic evolution trends of the CCD of digitization and green development. Based on this, this paper takes 284 cities in China from 2011 to 2021 as the research object, constructs a comprehensive evaluation system for the CCD of digitization and green development, and applies the entropy weight TOPSIS method, the coupling coordination degree model, the Dagum’s Gini coefficient, the spatial autocorrelation model, the Markov model, and the panel Tobit model to analyze the CCD of digitalization and green development, the regional differences, convergence, dynamic evolution trends and their influencing factors. The study aims to answer the question of what is the CCD of digitalization and green development of Chinese prefectural cities in different time and space? What are the sources of regional differences in the CCD? What are the characteristics of spatial convergence? What is the trend of spatial and temporal dynamics? What are the factors influencing the CCD of digitalization and green development? A series of questions are raised to provide micro-data support for the promotion of digitalization and green development.

Research methods and data sources

Indicator selection and data explanation, construction of indicator system.

This paper follows the principles of scientificity, comprehensiveness, representativeness, and operability to construct the evaluation index system for the CCD of digitalization and green development. For urban digitalization indicators, this paper refers to the research of Zhao et al. 41 and constructs the urban digitalization indicator system from the three aspects of digitalization foundation, digital industrialization, and industrial digitalization. In terms of urban green development indicators, this paper refers to the research of Zheng et al. 42 and constructs the urban green development indicator system from the four aspects of economic quality, resource consumption, environmental pollution, and environmental governance (see Table 1 for details).

Data description

This paper selects the panel data of 284 cities in China from 2011 to 2021 (due to the availability of data, the study does not involve Hong Kong, Macao, Taiwan and Xizang) as samples, and conducts a series of screening on the samples: the data of Sansha city, Danzhou city, Bijie city and Tongren city in the sample are missing for four consecutive years, so the above four city samples are deleted; During the study sample period, the administrative divisions of Chaohu city, Laiwu city, Haidong city, Turpan city, and Hami city were adjusted, therefore the above city samples were deleted.

Urban economy and environment panel data, mainly from China Urban Statistical Yearbook and statistical yearbooks of provinces, counties and cities in the EPS database, China Energy Statistical Yearbook and China Environmental Statistical Yearbook. The digital inclusive finance data are from the China Digital Inclusive Finance Index of Peking University. Referring to the studies of Ma and Wang 43 and Teng et al. 44 , this paper selected the three major urban energy consumption data, including the whole society electricity consumption, the amount of gas supply of coal gas, and the amount of gas supply of liquefied petroleum gas, and their corresponding energy conversion correlation coefficients (0.1229 kg of standard coal/kWh, 1.33 kg of standard coal/m3, and 1.7143 kg standard coal/kg) to measure the energy consumption of 10,000 yuan GDP. Some of the missing data were supplemented by the National Economic and Social Statistics Development Bulletin of each city, and continuous missing data were filled in using the epolate command in Stata 17.0 software.

Research methods

The entropy weight -topsis method.

The evaluation of digitalization and green development is a comprehensive evaluation system involving multiple dimensions, elements and indicators. Compared with existing subjective weighting methods (AHP, Delphi, etc.) and objective weighting methods (entropy method, factor analysis, etc.), the entropy weight-TOPSIS evaluation model integrates the excellent characteristics of the entropy method in objective weighting methods and the TOPSIS method in quality evaluation. It ranks the evaluation objects based on their degree of approximation to the idealized target, making the measurement results more objective and scientific 45 . In order to determine how far the digitalization and green development have progressed, the entropy weight-TOPSIS method is applied. The specific measurement steps are as follows:

Data standardization. In order to eliminate the difference in the scale of the indicators and enhance the comparability of the data, the positive and negative indicators are standardized separately, and the specific formulas are as follows. Among them, \({x}_{ij}\) is the original value of the \(j\) th indicator of the digitalization and the green development system, and the value of \(i\) is \(1,2,\dots ,n\) .

For positive indicators:

For negative indicators:

Determine the weights of indicators. This paper adopts the entropy weight method to assign weights to the indicators. The principle is to determine the weights according to the size of the information reflected in the values of the indicators. The specific formula is as follows. Where, \({e}_{j}\) 、 \({w}_{j}\) , respectively, represents the entropy value and weight of the \(j\) th indicator.

Construct the weighted normalization matrix. The data of each standardized indicator is weighted according to the indicators’ determined weights, resulting in a weighted normalization matrix \(A={({a}_{ij})}_{m*n}\) .

Determination of positive and negative ideal values. Positive ideal value is the assumed optimal program, the value of each indicator is the optimal value among the remaining alternatives; negative ideal value is the assumed worst program, the value of each indicator is the worst value among the remaining alternatives. The specific formulas are as follows:

Calculate the relative closeness of each indicator to the ideal value. According to the weighted normalization matrix and the positive and negative ideal values, this paper calculates the distance between each indicator and the positive and negative ideal values.

And further calculate the relative closeness between each indicator and the ideal values

Coupling coordination degree model

Dual-system coupling coordination model is widely used to measure the CCD between different systems 46 , 47 , this paper will construct a dual-system coupling coordination model of digitization ( \({W}_{1}\) ) and green development ( \({W}_{2}\) ) to examine the CCD of digitization and green development in Chinese prefecture-level cities. The specific procedures for determining the CCD of digitalization and green development are as follows. Among them, \(C\) is the system coupling degree, which indicates the matching degree of the interrelationship between the digitalization subsystem and the greening subsystem; and α β are the relative importance of the two subsystems. In exploring the relationship between digitalization and green development, the two subsystems are equally important, therefore, this paper takes 0.5 for each; \(D\) indicates the CCD of digitalization and green development in China’s prefecture-level cities and \(D\in \left[\text{0,1}\right]\) , the closer its value is to 1, the higher the CCD of digitalization and green development is.

With reference to existing studies 48 , 49 , this paper further classifies the types of CCD into low-quality coordination stage, antagonistic stage, teething stage, transformation stage and high-quality coordination stage. Specific CCD is categorized as listed in Table 2 .

Dagum’s Gini coefficient and its decomposition

To identify the sources of regional differences in the CCD of digitalization and green development for Chinese prefecture-level cities, this paper adopts the Dagum’s Gini coefficient to measure and decompose the regional differences in Chinese prefecture-level cities’ CCD of digitalization and green development. According to the decomposition method of Dagum’s Gini coefficient, the overall Gini coefficient \(G\) of the CCD can be decomposed into within-region differences \({G}_{w}\) , inter-region differences \({G}_{nb}\) , and hypervariable density \({G}_{t}\) . According to geographic divisions, this paper analyses the regional differences by dividing the study area into three major economic zones in the east, middle and west. The specific calculation formula is as follows:

where \({y}_{ji}\) ( \({y}_{hr}\) ) is the cities CCD of digitalization and green development in region \(j(h)\) , \(k\) is the number of regions, and \({n}_{j}\) ( \({n}_{h}\) ) is the number of cities in the region \(j(h)\) , \(\overline{y }\) is the average value of CCD of digitalization and green development in each cities.

where, \({p}_{j}={n}_{j}/\overline{y }\) , \({s}_{j}={n}_{j}\overline{{y }_{j}}/n\overline{y }\) ; \({D}_{jh}\) is the relative impact of the CCD of digitalization and green development in regions \(j\) and \(h\) ; \({F}_{j}\) ( \({F}_{h}\) ) is the regional cumulative density distribution function; \({d}_{jh}\) is the mathematical expectation of all \({y}_{ji}-{y}_{hr}>0\) in regions \(j\) and \(h\) ; \({p}_{jh}\) is the mathematical expectation of all \({y}_{ji}-{y}_{hr}<0\) in regions \(j\) and \(h\) ; \({G}_{jj}\) is the Gini coefficient of the region \(j\) ; \({G}_{jh}\) is the interregional Gini coefficient of the regions \(j\) and \(h\) ; \({G}_{w}\) is the within-region differences, \({G}_{nb}\) is the net inter-region differences, and \({G}_{t}\) is the hypervariable density.

\(\beta\) convergence model

This paper uses convergence to analyze whether there is a trend of narrowing the spatial change rate gap in the CCD of digitalization and green development over time. Convergence reflects the fact that in the variance process for the CCD of digitalization and green development, cities with a lower CCD have a higher growth rate, thus narrowing the gap with higher CCD cities, and ultimately realizing the convergence of the CCD of digitalization and green development. The traditional absolute \(\beta\) convergence model is:

where \(\text{ln}\left(\frac{{D}_{i,t+1}}{{D}_{i,t}}\right)\) denotes the growth rate of the CCD of digitalization and green development in region \(i\) from time \(t\) to time \(t+1\) , \(\beta\) is the convergence coefficient, if \(\beta <0\) , it means that there is a trend of convergence in the CCD of digitalization and green development; \({u}_{i}\) denotes the region effect; \({v}_{t}\) denotes the time effect; and \({\varepsilon }_{i,t}\) denotes the random perturbation term obeying an independent homogeneous distribution.

To fully consider the spatial effect between cities, this paper adds spatial weight matrix on the basis of the traditional convergence model, and applies SAR, SEM and SDM models to carry out spatial convergence analysis, the specific spatial model is:

where, \(\rho\) is the spatial lag coefficient, \(\lambda\) is the spatial error coefficient, \(\theta\) is the effect of the CCD spatial lag term in the base period on the CCD growth rate , and \({\omega }_{ij}\) is the spatial weight matrix.

Markov chain analysis

This paper analyses the probability of the CCD of digitalization and green development moving from one state to another by constructing a Markov transfer probability matrix, so as to explore the internal dynamic evolution trend of the CCD of digitalization and green development over time. The basic method of constructing the Markov transfer probability matrix is to discretize the CCD of digitalization and green development into k state types, calculate the changes of various types and their probabilities, so as to approximate the evolution process of the CCD as a Markov process. The specific process is as follows:

Considering the influence of spatial spillover effect due to geographical proximity on the evolution of the CCD of digitalization and green development of cities 50 , this paper introduces the concept of spatial lag based on the transfer probability matrix of the traditional Markov chain, and transforms the transfer probability matrix of the \(k*k\) order into \(k\) conditional transfer probability matrix of \(k*k\) order, so as to analyze the dynamic evolution trend of the CCD of digitalization and green development under the influence of its neighboring cities.

• Panel Tobit model

To further study the factors that affect the CCD of digitalization and green development, this paper will use the calculated CCD of digitalization and green development in 284 prefecture level cities as the dependent variable and influencing factor as the explanatory variable to establish a regression model. Considering that the range of values for the CCD is between (0,1), if the least squares method is directly used for regression, it may lead to biased and inconsistent regression results. Therefore, this paper uses a restricted dependent variable Tobit model for regression. The specific form as follow:

Among them, \(Y\) is the restricted dependent variable and \(X\) is the independent variable, \(\alpha\) is intercept term, \(\beta\) is regression coefficient, and \(\tau\) is a random error.

Results analysis

The ccd of digitalization and green development analysis.

The characteristics of the CCD of digitalization and green development in prefecture level cities in China reflect the interaction between the two in the development process, which is of great significance for further realizing the CCD of digitalization and green development. This paper calculates the CCD based on a coupling coordination model and takes the average of each year to represent the CCD of digitalization and green development in the country and various regions for that year. The specific results are shown in Fig.  2 . The average CCD of digitalization and green development in 284 prefecture level cities in China has increased from 0.163 in 2011 to 0.262 in 2021, with an average annual growth rate of 4.89%. From the perspective of coordination interval, from 2011 to 2013, the average CCD among cities was less than 0.2, indicating a serious imbalance stage. From 2014 to 2021, it was in a moderate imbalance stage. From the regional perspective, the CCD in the eastern region is higher than the national average, increasing from 0.184 in 2011 to 0.288 in 2021, with an average annual growth rate of 4.6%. The CCD in the central region is slightly lower than the national average, increasing from 0.154 in 2011 to 0.248 in 2021, with an average annual growth rate of 4.91%. The CCD in the western region is much lower than the national average, increasing from 0.148 in 2011 to 0.246 in 2021, with an average annual growth rate of 5.24%. During the sample period, the difference in the CCD of digitalization and green development between the eastern and western regions decreased from 1.26 times to 1.17 times, indicating that the differences between regions in China are gradually narrowing.

The CCD of digitalization and green development in China, 2011–2021.

To examine the structural changes in the CCD of digitalization and green development, this paper further calculated the number and proportion of cities in each coordinated type in 2011, 2016, and 2021, as shown in Fig.  3 .

The structural evolution trend of CCD among regions in China, 2011–2021.

From Fig.  3 , the CCD structure of cities at various levels in China is continuously optimizing, with the proportion of low CCD cities gradually decreasing and the proportion of high CCD cities gradually expanding. In 2011, the proportion of cities with extreme disorder CCD was the highest, with only Shenzhen experiencing mildly disorder CCD. In 2016, the proportion of cities with moderate disorder CCD was the highest, but there are still cities with extreme disorder CCD, and the proportion is relatively large. In 2021, all cities achieved moderate disorder or above CCD. Beijing, Suzhou, Hangzhou, Jinhua, Guangzhou, and Dongguan have entered a stage of nearly disorder CCD, while Shenzhen and Shanghai have achieved barely coordination.

Regional differences and sources

In order to describe the spatial differences in the CCD of digitalization and green development and their sources, this paper uses Dagum Gini coefficient and decomposition method to measure the overall Gini coefficient, within-region Gini coefficient, inter-region Gini coefficient of CCD in 284 prefecture level cities and three major regions in China from 2011 to 2021. The results of the measurements are shown in Table 3 .

The overall differences

The differences in the CCD of digitalization and green development in China show an overall fluctuating downward trend, and the differences between the CCD in 2013 and 2019 have a small increase. However, the Gini coefficient of the national CCD declined from 0.117 to 0.084 over the entire inspection period, with an average annual decline of 2.9%. This indicates that the regional imbalance in the CCD in China has been alleviated. It is worth noting that although the Gini coefficient of the CCD has decreased from 2011 to 2021, its absolute value is relatively large, indicating that the regional imbalance problem of the CCD is still significant, and that narrowing the regional imbalance of CCD is still worth paying attention to.

The within-region differences

Figure  4 a depicts the trend of the Gini coefficient variation of the CCD in China and the three major regions during the sample study period. In terms of the degree of spatial differentiation within the three regions, the largest within-region difference in the CCD is found in the eastern region (the mean value of the Gini coefficient in the eastern region during the sample period is 0.110); and the within-region difference in the central region and the western region is relatively small (the mean values of the Gini coefficients in the central and western regions during the sample period are 0.057 and 0.065)). In terms of the trend variation the Gini coefficients of the eastern, central and western regions all showed a fluctuating downward trend during the sample period. Among them, the Gini coefficients of the central and western regions changed significantly, while the within-region differences in the eastern region changed relatively small. This indicates that there are obvious spatial differentiation features in the CCD in each region of China, with the within-region differences in the CCD in the central and western regions significantly narrowing, but both need to be further stabilized and the differentiation degree in the eastern region being larger and the magnitude of change is relatively stable. The above results once again confirm that the CCD of digitalization and green development within each region in China is unevenly developed, and that the development characteristics of each region need to be taken into account when formulating policies for coordinated regional development.

The Gini coefficient variation and contribution rate of the CCD in China. ( a ) Overall and regional differences degree ( b ) Inter-region differences degree ( c ) Contribution rate of difference sources.

The inter-region differences

Figure  4 b depicts the trend of the Gini coefficient of the CCD among the three major regions of China during the sample period. During the whole study period, the difference of the CCD between the eastern and western regions is the largest (the mean value of the Gini coefficient is 0.113), the difference between the eastern and central regions is the second largest (the mean value of the Gini coefficient is 0.104), and the difference between the central and western regions is the smallest (the mean value of the Gini coefficient is 0.063). From the trend variation, the overall degree of spatial differentiation between regions shows a decreasing trend, with the Gini coefficient between the central and western regions showing the largest decrease, with an average annual decrease of 5.58%; The average annual decrease in Gini coefficient between the eastern and western regions is 3%; The Gini coefficient between the eastern and central regions has the smallest decrease, with an average annual decrease of 1.59%. This means that the CCD of digitalization and green development in high and low development regions is converging towards the national average.

Sources of regional differences

Figure  4 c portrays the contribution rate of within-region differences, inter-region differences and hypervariable density to the overall difference. Throughout the examination period, the contribution of inter-region differences to the overall difference is the largest, showing a change trend of first increasing (from 42.78% in 2011 to 48.42% in 2016) and then decreasing (43.63% in 2021); followed by the contribution of within-region differences, and the change in its contribution to the overall difference is mainly stable in each year; the hypervariable density has the smallest contribution to the overall difference, showing a change trend of first decreasing (from 27% in 2011 to 21.27% in 2016) and then decreasing (25.36% in 2021). In terms of the magnitude of the contribution, inter-region differences have the highest average contribution, with a mean value of 45.19%. This is followed by the within-region differences contribution with a mean value of 30.51%, which is slightly higher than the hypervariable density contribution (24.3%). This indicates that the inter-region differences have a more pronounced impact on the overall differences in the CCD of digitalization and green development in Chinese cities.

Convergence analysis

Moran’s i analysis.

This paper uses a geographic distance matrix to test the spatial correlation of the CCD in prefecture level cities in China. The test results show that Moran’s I for the CCD in Chinese prefecture level cities from 2012 to 2021 is significantly positive at the 1% level, ranging from 0.094 to 0.110, indicating a significant spatial correlation in the CCD in Chinese prefecture level cities.

Absolute \(\beta\) convergence test

In this paper, the results of LM test, LR test and Hausman test were used to select the optimal model for absolute convergence analysis. Based on these model results, the SDM model was selected for absolute convergence analysis in the national, eastern and central regions, and the SEM model was selected for absolute convergence analysis in the western region. Table 4 reports the absolute convergence results for the CCD of digitalization and green development in Chinese cities. Without considering spatial correlation, the absolute convergence coefficient \(\beta\) are significantly negative at the 1% level, indicating that there is absolute convergence in the CCD of digitalization and green development across the country, eastern, central, and western regions. In other words, without considering the influence of other exogenous variables, cities with lower CCD of digitalization and green development have greater room for improvement compared to cities with higher CCD. As time goes on, the CCD of digitalization and green development in each region will eventually tend to a stable state, where cities with lower CCD will have a “catch-up effect” on cities with higher CCD. After considering the spatial correlation, the absolute convergence coefficient \(\beta\) is also significantly negative at the 1% level, indicating that there is spatial absolute convergence in the CCD of digitalization and green development after incorporating spatial factors into the model, and that the gap in the CCD of digitalization and green development between the cities will be gradually narrowed over time. In terms of the convergence speed, the absolute value of the spatial convergence model coefficient \(\beta\) is larger, indicating that convergence speed is faster (According to Mankiw’s research, there is a positive relationship between the convergence speed \(\delta\) and the absolute value of absolute convergence coefficient \(\beta\) ) 51 . This shows that spatial effect is one of the important factors for the convergence of the CCD of digitalization and green development in Chinese cities. Meanwhile, the convergence speed in the western region is much higher than that of the whole country as well as the eastern and central regions, indicating that the polarization of the overall CCD will improve significantly with the time goes on.

Dynamic evolution trend analysis

In order to further analyze the dynamic evolution trend of the CCD digitalization and green development in Chinese cities, this paper constructs a traditional Markov transfer probability matrix and a spatial-based Markov transfer probability matrix to explore the dynamic variation in the relative positions of the CCD digitalization and green development and the probability of the state transition.

Traditional Markov transfer probability matrix analysis

In this paper, the CCD digitalization and green development in Chinese 284 prefecture level cities is divided into four states: low level, medium–low level, medium–high level and high level, which are respectively represented by k = I, II, III, IV. Table 5 shows the Markov transfer probability matrix of the CCD from 2011 to 2021. The results show that: (1) The transfer probability on the diagonal is greater than that on the non-diagonal. The maximum value of the data on the diagonal is 0.977, while the minimum value is 0.648, indicating that the transition type of the CCD digitalization and green development in Chinese cities is stable, and the probability of maintaining the original state is large which means the CCD has the characteristics of club convergence. (2) The upward transfer probability is greater than the downward transfer probability (the value of the upper triangle in the matrix is greater than the value of the lower triangle), indicating that the overall CCD digitalization and green development has a positive trend in the future. At the same time, the upward transfer probability of medium–low level cities is higher than that of low-level cities and medium–high level cities, which may be due to the fact that the economic development level of low-level cities is difficult to support their digitalization and green development. It is necessary to accumulate a certain amount of capital elements before they can be upwardly transferred. In the process of medium–high level cities’ transformation to high-level, the barriers encountered are higher. In addition to the reasonable allocation of elements, it is more necessary to promote policies, both of which are indispensable. (3) In the adjacent years, the probability of realizing “leapfrog” development for the type of CCD is small, and the probability of realizing cross-level transfer for each state type is less than 5%.

Spatial Markov transfer probability matrix analysis

The spatial Markov transfer probability matrix is based on the traditional Markov chain transfer probability matrix and adds the spatial lag condition to analyze the transfer probability of the CCD digitalization and green development under different neighborhood backgrounds. Table 5 shows the Markov transfer probability matrix of the CCD from 2011 to 2021. The results show that: (1) The neighborhood background plays an important role in the transfer process of the CCD digitalization and green development in Chinese cities. By comparing the traditional Markov transfer probability matrix, the transfer probability of the CCD digitalization and green development in Chinese cities has changed significantly under the different background fields. After considering the spatial factors, the transfer probabilities on the diagonal are greater than those on the non-diagonal, which fully shows that even considering the influence of spatial factors, the CCD of digitalization and green development in Chinese cities still has the characteristics of club convergence. (2) The downward transfer probability of the city’s CCD will increase if the city neighboring a region with a low CCD of digitalization and green development, and the upward transfer probability of the city’s CCD will increase if the city neighboring a region with a high CCD of digitalization and green development. For example, under the conditions of a neighborhood with lower CCD, \({P}_{32|1}\left(0.070\right)>{P}_{32}(0.022)\) . Under the conditions of a neighborhood with higher CCD, \({P}_{23|4}(0.730)>{P}_{23}(0.340)\) . Generally speaking, the low-level neighborhoods will hinder the development of the region and even pull down its CCD of digitalization and green development; while the high-level neighborhoods play a positive pulling effect on the development of the region and reduces the downward transfer probability. (3) The CCD of digitalization and green development in cities is synergetic with the CCD type of neighborhood. When the neighborhood type is I, the number of cities with lower CCD is significantly more than that of other types. When the neighborhood type is IV, the number of cities with higher CCD is significantly more than that of other types of cities.

After considering the impact of regional proximity, the transfer of CCD in Chinese cities has changed significantly, indicating that the dynamic evolution trend of CCD has spatial spillover effect. To verify the statistical significance of spatial spillover effect, this paper conducts a hypothesis test through the following formula:

where, \(k\) is the state type of the CCD in cities; \({m}_{ij}\) is the traditional Markov transfer probability; \({m}_{ij}(S)\) is the spatial Markov transfer probability for the \(S\) neighborhood type. The test statistic is 279.3349, which passes the significance test at the 5% level. Therefore, it is reasonable to reject the hypothesis that the transfer of CCD digitalization and green development in cities is independent of each other and independent of the neighborhood type.

Influencing factors analysis

For thorough explore the influencing factors of CCD, this paper constructs a panel Tobit model for empirical analysis:

where, \({D}_{it}\) is the CCD of digitalization and green development for \(i\) city in \(t\) year; \({\beta }_{0}\) is constant term; \({Envo}_{it}\) 、 \({Greinno}_{it}\) 、 \({Indus}_{it}\) 、 \({Fina}_{it}\) are factors that may affect the CCD of digitalization and green development. LR test results show that \(Prob >= chibar2 = 0.000\) , it is reasonable to reject the original hypothesis. Therefore, we can consider that there are individual effects, and panel Tobit regression with random effects should be used.

The specific influencing factors are: (1) Regional environmental regulation ( \({Envo}_{it}\) ), expressed by the proportion of environmental related vocabulary in the government work report with reference to the practices of Chen and Chen 52 and Chen et al. 53 . As a profit seeking organization, enterprises have incentives to improve existing production processes, realize green transformation and upgrading, and indirectly achieve the goal of green development. The wide application of digital technology in the process of green upgrading has promoted the green transformation of enterprises and achieved green development. At the same time, the strong environmental regulation and the green demand for digital technology also force the digital industry to carry out green innovation and realize the CCD of digitalization and green development; (2) Regional green innovation ( \({Greinno}_{it}\) ), expressed by the sum of the number of invention patents and utility patents applied by the city every year referring to the practice of Tan et al. 54 . Green innovation itself is an important driving force for greening development 55 . Enterprises’ green-new product R&D and green innovation investment can generate more green and high-quality production capacity, eliminate backward production capacity, and promote the greening and digital transformation of traditional industries 56 . At the same time, digital investment is indispensable in the process of green innovation. The development of the Internet, digital platforms for information exchange and technology sharing provides a low-cost, time-sensitive way of dissemination 57 . The input of information technology helps to improve the level of digitalization. R&D, design and production are inseparable from the application of digital infrastructure, and the input demand of these resources also pulls the digital development 58 . Therefore, green innovation can promote the CCD of digitalization and green development; (3) Regional industrial structure ( \({Indus}_{it}\) ), expressed using the ratio of value added in the tertiary sector to value added in the secondary sector. In the process of realizing green development, cities will force the industrial structure upgrading. The application of digital technology provides technical and platform support for the industrial structure upgrading, it also realizes the greening of digital industry itself and the progress of digital industry. Therefore, the industrial structure upgrading can promote the CCD of digitalization and green development; (4) Regional financial efficiency ( \({Fina}_{it}\) ), expressed by the ratio of loan balance to deposit balance of regional financial institutions referring to the practice of Chen et al. 59 . The development of regional digitalization and green development cannot be separated from the support of financial resources. The improvement of financial efficiency can reduce the problem of capital mismatch to a certain extent, provide financial support for the urban digitalization and green development, and encourage market players with maximum profits to actively carry out digitalization and green development, so as to realize the CCD of regional digitalization and green development.

The regression results in column (1) of Table 6 show that regional environmental regulation, green innovation, industrial structure upgrading, and financial efficiency can significantly promote the CCD of digitalization and green development. From a subregional perspective, regional environmental regulation, green innovation, industrial structure upgrading, and financial efficiency can also promote the CCD of digitalization and green development in the eastern, central, and western regions. Only the environmental regulation coefficient of eastern region is not significant. The possible reason is that the eastern region, as an economically developed region, has a relatively high CCD of digitalization and green development, resulting in lower marginal effects of environmental regulations promoting the CCD of digitalization and green development.

Conclusions and recommendations

Conclusions.

To explore the spatial–temporal evolution characteristics, regional differences, dynamic evolution trend of spatial convergence and its influencing factors of the CCD in Chinese cities, this paper constructs a comprehensive evaluation system of the digitalization and green development and measures the CCD of digitalization and green development in Chinese cities from 2011 to 2021 with the help of the two-systems coupling and coordination model. At the same time, Dagum Gini coefficient, spatial convergence model, Markov transfer probability model and panel Tobit model are used to comprehensively analyze the regional differences and differences sources of CCD in Chinese cities, the dynamic evolution trend of spatial convergence characteristics and their influencing factors. The main conclusions are as follows:

(1) As the whole, the CCD of digitalization and green development in Chinese cities is relatively low. Although some cities’ CCD has achieved barely disorder, most cities are still in the antagonistic stage of moderate and mildly disorder. From the regional level, the CCD of digitalization and green development in the eastern region is higher than the national average level, while the average CCD of digitalization and green development in the central and western regions is lower than the national average level, but the average annual growth rate is high.

(2) Dagum Gini coefficient results show that the regional differences of CCD in Chinese cities are shrinking year by year, and the overall regional differences are gradually shrinking. However, the greater the regional differences (East–West), the smaller the decline of the differences, while the smaller the regional differences (Center-West), the faster and easier it is to narrow the regional differences. As far as the sources of regional differences are concerned, inter-region differences are the main sources of CCD’s spatial differentiation.

(3) The results of convergence analysis show that, there is a “catch-up effect” between cities with lower CCD and cities with higher CCD, whether spatial correlation is considered. The gap between cities in the CCD of digitalization and green development will gradually narrow over time. At the same time, the convergence speed of the western region is much higher than that of the whole country and the eastern and central regions, indicating that the polarization of the CCD will be significantly improved with the time goes on.

(4) The results of dynamic evolution trend analysis show that the overall CCD of digitalization and green development has a positive trend in the future, but the probability of achieving “leapfrog” development is small, and the realization of CCD needs to be down-to-earth and steady progress. At the same time, low CCD neighborhoods will hinder the development of the region, and even pull down the CCD of digitalization and green development; the high CCD neighborhood plays a positive role in the region development and can reduce the downward transfer probability.

(5) The analysis results of influencing factors show that regional environmental regulation, green innovation, industrial structure upgrading, and financial efficiency can significantly promote the CCD of digitalization and green development, both at the national level and at the subregional level.

Recommendations

First, vigorously promote the CCD of digitalization and green development, and promote the organic integration of the two. On the one hand, we should lead the green reform of production mode, circulation mode and consumption mode, improve the efficiency of resource allocation by digitization, drive the transformation and upgrading of industrial structure, realize the optimal utilization of resources, and promote the win–win of economic and environmental benefits. On the other hand, although digitalization has strong permeability and significant economies of scale, its energy consumption and carbon dioxide emissions are huge. We should promote digitalization with greening and reduce the repeated consumption that hinders greening in the process of digital transformation.

Second, formulate differentiated regional development policies according to local conditions to narrow the regional development gap. In view of the unbalanced development of digitalization and greening in China, the government should carry out reasonable macro-control, give full play to government functions, tilt policy resources to the central and western regions with poor development level, and guide the CCD of digitalization and green development in the central and western regions. Local governments should face up to the differences in capital, human resources, technology and other aspects between themselves and areas, formulate development strategies that are in line with their own resource endowment, and realize the promotion of digital and green collaborative development level.

Third, it is important to dynamically grasp the law and process of CCD. The CCD of digitalization and green development is a dynamic process. The uneven level of CCD between regions, the interaction between fields, and the lag between policy promulgation and policy implementation pose challenges to the steady development of CCD. We should fully understand the characteristics of the CCD, establish an information sharing and monitoring mechanism for different characteristics of the CCD.

Limitations and future research directions

This study provides a detailed assessment of the interaction between digitalization and green development through a rigorous and careful selection of indicators related to digitalization and green development. The application of coupled coordination models, Markov chain analysis and panel Tobit models further enriches our analysis and facilitates a nuanced exploration of the topic. Although we have done a very comprehensive analysis of the temporal and spatial differences and dynamic evolution of CCD of digitalization and green development, the CCD of digitalization and green development need further investigation. Based on the in-depth exploration of the relationship between digitalization and green development, we found that the CCD of digitalization and green development in Chinese cities is relatively low and highly polarized. Meanwhile, digitalization and green development are characterized by high uncertainty and high transformation costs. Therefore, in the future, we should also analyze how to promote the CCD of digital greening and explore the factors affecting the CCD of two and the internal mechanism, so as to provide more empirical evidence for enriching the research related to the CCD of digitalization and green development and promoting the realization of the CCD.

Data availability

All the data is publicly available, and proper sources have been cited in the text.

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This work was supported by the Fundamental Research Funds for the Central Universities of Zhongnan University of Economics and Law, Grant No.202410304.

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She, Q., Qian, J. & He, L. Research on the relationship of coupling coordination between digitalization and green development. Sci Rep 14 , 19569 (2024). https://doi.org/10.1038/s41598-024-70581-6

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DOI : https://doi.org/10.1038/s41598-024-70581-6

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Trends in physiotherapy of chronic low back pain research: knowledge synthesis based on bibliometric analysis.

1. Introduction

• What is the volume, scope and dynamics of the research literature production on physiotherapy in CLBP?
• What is the spatial distribution of physiotherapy in CLBP literature production among the most prolific source titles, institutions, countries and funding institutions?
• What is the most prolific physiotherapy in CLBP research themes, how have they evolved over time and what is their association?

2. Materials and Methods

2.1. search procedure, 2.2. data analysis, 2.3. thematic analysis, 3.1. volume and prevalence of the research literature production, 3.2. the dynamics of the research literature production, 3.3. the thematic analysis, 3.4. the chronological analysis.

• Development of pain assessment tools: pain measurement → pain assessment → pain management . These tools first measure and evaluate pain, in order to ultimately contribute to the most functional treatment possible;
• Development of CLBP processing: disease severity → disability evaluation → disease duration → treatment duration → clinical outcomes and effectiveness . The evolution of CLBP processing first began with assessing the severity and then the inability to perform normal bodily functions caused by the pain. The latter affected the duration of the disease, which in turn resulted in the duration of the treatment. Research in this area has continued in the field of studying the clinical outcomes and effectiveness of therapeutic methods of treating CLBP;
• Development of study methodology: follow-up studies → comparative studies → randomized control trials → meta-analysis → cohort analysis . The methodological design first started with follow-up studies, followed by comparative studies and later by randomized control trials. Based on the conclusions of these studies, after further research authors began to summarize the main findings and suggest further possibilities for the development of physiotherapy for CLBP in meta-analysis. They were followed by cohort analyses studying causal factors over time.

4. Discussion

5. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

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Šajnović, U.; Kokol, P.; Završnik, J.; Vošner, H.B. Trends in Physiotherapy of Chronic Low Back Pain Research: Knowledge Synthesis Based on Bibliometric Analysis. Healthcare 2024 , 12 , 1676. https://doi.org/10.3390/healthcare12161676

Šajnović U, Kokol P, Završnik J, Vošner HB. Trends in Physiotherapy of Chronic Low Back Pain Research: Knowledge Synthesis Based on Bibliometric Analysis. Healthcare . 2024; 12(16):1676. https://doi.org/10.3390/healthcare12161676

Šajnović, Urška, Peter Kokol, Jernej Završnik, and Helena Blažun Vošner. 2024. "Trends in Physiotherapy of Chronic Low Back Pain Research: Knowledge Synthesis Based on Bibliometric Analysis" Healthcare 12, no. 16: 1676. https://doi.org/10.3390/healthcare12161676

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Published on 19.8.2024 in Vol 26 (2024)

This is a member publication of Open University

Prevalence of Health Misinformation on Social Media—Challenges and Mitigation Before, During, and Beyond the COVID-19 Pandemic: Scoping Literature Review

Authors of this article:

• Dhouha Kbaier 1 , PhD   ; 
• Annemarie Kane 2 , PhD   ; 
• Mark McJury 3   ; 
• Ian Kenny 1 , PhD  

1 School of Computing and Communications, The Open University, Milton Keynes, United Kingdom

2 Faculty of Arts and Social Sciences, The Open University, Milton Keynes, United Kingdom

3 School of Physical Sciences, The Open University, Milton Keynes, United Kingdom

Corresponding Author:

Dhouha Kbaier, PhD

School of Computing and Communications

The Open University

Walton Hall

Milton Keynes, MK7 6AA

United Kingdom

Email: [email protected]

Background: This scoping review accompanies our research study “The Experience of Health Professionals With Misinformation and Its Impact on Their Job Practice: Qualitative Interview Study.” It surveys online health misinformation and is intended to provide an understanding of the communication context in which health professionals must operate.

Objective: Our objective was to illustrate the impact of social media in introducing additional sources of misinformation that impact health practitioners’ ability to communicate effectively with their patients. In addition, we considered how the level of knowledge of practitioners mitigated the effect of misinformation and additional stress factors associated with dealing with outbreaks, such as the COVID-19 pandemic, that affect communication with patients.

Methods: This study used a 5-step scoping review methodology following Arksey and O’Malley’s methodology to map relevant literature published in English between January 2012 and March 2024, focusing on health misinformation on social media platforms. We defined health misinformation as a false or misleading health-related claim that is not based on valid evidence or scientific knowledge. Electronic searches were performed on PubMed, Scopus, Web of Science, and Google Scholar. We included studies on the extent and impact of health misinformation in social media, mitigation strategies, and health practitioners’ experiences of confronting health misinformation. Our independent reviewers identified relevant articles for data extraction.

Results: Our review synthesized findings from 70 sources on online health misinformation. It revealed a consensus regarding the significant problem of health misinformation disseminated on social network platforms. While users seek trustworthy sources of health information, they often lack adequate health and digital literacies, which is exacerbated by social and economic inequalities. Cultural contexts influence the reception of such misinformation, and health practitioners may be vulnerable, too. The effectiveness of online mitigation strategies like user correction and automatic detection are complicated by malicious actors and politicization. The role of health practitioners in this context is a challenging one. Although they are still best placed to combat health misinformation, this review identified stressors that create barriers to their abilities to do this well. Investment in health information management at local and global levels could enhance their capacity for effective communication with patients.

Conclusions: This scoping review underscores the significance of addressing online health misinformation, particularly in the postpandemic era. It highlights the necessity for a collaborative global interdisciplinary effort to ensure equitable access to accurate health information, thereby empowering health practitioners to effectively combat the impact of online health misinformation. Academic research will need to be disseminated into the public domain in a way that is accessible to the public. Without equipping populations with health and digital literacies, the prevalence of online health misinformation will continue to pose a threat to global public health efforts.

Introduction

The global adoption of the internet has made health information more accessible, and the development of digital technology has enabled its rapid dissemination. However, the internet has also made possible the dissemination of false and misleading health misinformation and disinformation, with negative consequences, including the potential to exacerbate health inequalities. Health practitioners have found themselves at the forefront of communicating with patients who have taken on board health misinformation in the context of its proliferation on the web. This paper (associated with the study by Ismail et al [ 1 ]) surveyed the current literature concerning online health misinformation to establish the extent and scope of the problem, with special reference to the needs of health practitioners in their efforts to mitigate its impact. Several studies have established useful definitions of the terms misinformation and disinformation and distinctions between them. Misinformation has been defined as information that is not supported by evidence and contradicts the best-supported evidence available [ 2 , 3 ]. Wang et al [ 4 ] made a further distinction between online misinformation and disinformation, in particular on social media platforms. For Wang et al [ 4 ], misinformation is information that is not known to be false and is shared without malice. By contrast, disinformation involves the knowing and sharing of false information with the purpose of causing harm. This paper follows the distinctions of Wang et al [ 4 ] to use the terms misinformation and disinformation as appropriate.

It is important to acknowledge at the outset that digital technology in health and social contexts presents both risks and opportunities for equity among different information audiences [ 5 ]. However, there has recently been a change in the reception and assessment of the role of the internet, social media in particular, among researchers, even predating the COVID-19 pandemic. In the early days of social media, researchers largely identified prosocial and altruistic uses of social media platforms such as Facebook and Twitter by the public. However, considerable disquiet about the impact of social media and its potential for the spread of “fake news” and the amplification of conspiracy theories has displaced the more positive evaluation that was apparent when social media was in its infancy [ 6 ]. In the majority of the current research, there is a view that digital technology, particularly social media, has amplified the problem of health misinformation. The risk most frequently identified, either explicitly or implicitly, is the susceptibility of ordinary users, who may be lacking sophisticated levels of health and digital literacies, to health misinformation. Further risks noted in the literature include disinformation disseminated by organized trolling networks and bots that can be hard to distinguish from human users. The recognition of these risks underpins an emerging policy discourse about the threat of health misinformation, particularly the role of social media in its spread, in which health information and misinformation has become a politicized issue. From one policy perspective, there is an assumption that social media users are vulnerable, even passive, recipients of health misinformation rather than reflective interpreters of the available information. The corollary of this is that correcting misinformation with authoritative knowledge will solve the problem. However, a survey of the literature suggested that neither assumption fully expresses the complexity of how health misinformation is disseminated, received, and used via the internet. This may be because although there is a growing body of evidence on the extent of online health misinformation, there is much less research about what users do with health misinformation, why users consume health misinformation, and why (and which) people believe health misinformation [ 7 - 9 ].

In this scoping review, we reviewed the current state of knowledge regarding the prevalence of online misinformation before and during the COVID-19 pandemic and the impact that has on users’ understanding of health information. We considered this context with special reference to patients’ understanding, health practitioners’ practice in response to that, and policy makers’ concerns. The pressures and distractions that health professionals face in attempting to mitigate the impacts of online health misinformation are discussed in relation to patients’ health and digital literacies and the politicization of health information and misinformation.

Information Sources

We conducted a comprehensive literature search to identify relevant studies that explored health misinformation on social media platforms. The search was conducted across multiple electronic databases, including PubMed, Scopus, Web of Science, and Google Scholar.

The search terms included a combination of relevant keywords and phrases, including “health misinformation,” “social media,” “online health communities,” and “COVID-19 pandemic.” The search was not limited by publication date. Detailed search strategies are provided in Multimedia Appendix 1 .

Study Selection

Our study selection process followed a scoping approach, where we aimed to identify and include studies that provided insights into the prevalence and challenges of health misinformation on social media platforms. Initially, 2 researchers independently screened titles and abstracts of the identified articles to determine their relevance. Articles that did not meet the inclusion criteria were excluded at this stage.

Inclusion Criteria

Articles were included if they discussed health misinformation on social media, addressed the challenges posed by health misinformation, or were relevant to the period before, during, and after the COVID-19 pandemic.

Any disagreements between the 2 researchers were resolved through discussion and consensus. Full-text articles were then retrieved for the remaining studies, and a further assessment of eligibility was conducted based on the same inclusion criteria.

Data Extraction

We gathered information on (1) study objectives, (2) research methods, (3) findings, and (4) key themes related to health misinformation. This process was performed independently by 2 researchers, and any discrepancies were resolved through discussion.

Data Synthesis and Analysis

We adopted a scoping review content analysis approach to analyze the data extracted from the selected articles. The analysis process involved identifying key themes and patterns related to health misinformation on social media. The content analysis allowed us to gain a deeper understanding of the challenges posed by health misinformation and the strategies for its mitigation, both before and during the COVID-19 pandemic.

Results of Search

In our article selection process ( Figure 1 ), we initiated our search by identifying a total of 4563 articles from various databases. Following the removal of duplicates, 1295 articles were excluded, leaving us with 3268 unique articles. Subsequently, these articles underwent an initial screening, which involved evaluating their abstracts and titles, resulting in the exclusion of 2635 articles that did not align with our inclusion criteria. Further scrutiny was applied during full-text screening, which was conducted on 633 articles. Among these, 563 articles were found ineligible due to reasons such as not meeting the inclusion criteria (n=378 articles), being classified as literature reviews, editorials, or letters (n=174 articles), or the full texts being inaccessible (n=11 articles). A total of 70 articles were ultimately included in this scoping review.

Characteristics of Included Documents (n=70)

The majority (65/70, 93%) of documents were published in the last 10 years and originated predominantly in North America (42/70, 60%), Europe (19/70, 27%), and Asia (11/70, 16%). The funding sources were mainly public (61/70, 87%). The documents were classified as original research papers (38/70, 54%), subjective “opinion” articles (editorials, viewpoints, commentaries, and letters to the journal; 11/70, 16%), and knowledge syntheses or reviews (9/70, 13%) which included systematic reviews (n=6), descriptive reviews (n=2), and 1 integrated theoretic review.

Extent and Impact of Health Misinformation Disseminated Across a Range of Outlets

This section will review the literature concerning the extent and impact of the problem of health misinformation, including the spread of antivaccination discourse. In a study by Wood et al [ 10 ] among health practitioners in North Carolina, 94.2% of the respondents reported encounters with patient health misinformation within the previous year. While the sources of this misinformation were not broken down and identified by Wood et al [ 10 ], several other studies linked patient health misinformation to the prevalence of health misinformation on social media sites, identifying the latter as a significant problem [ 4 , 11 - 15 ]. There is a growing consensus among researchers, health professionals, and policy makers about the need to confront, challenge, and even prevent the online dissemination of health misinformation [ 16 ]. Since the emergence of online social networks, users have increasingly sought and shared health information on social media sites. It is estimated that around 70% of adult internet users search health matters on the web. With the emergence of social media platforms, there has been a rise in “peer-to-peer health care,” through which individuals seek and share health information, forming online health communities with others who have similar health concerns [ 3 ]. In addition, health organizations and health professionals are increasingly using social media to disseminate and promote health information and advice. The opportunities for sharing and promoting good health information via the internet are evident, and it is important to acknowledge that in online health communities, users share experiences and receive and give different kinds of support, including emotional support, to cope with specific health conditions. However, the medium has also enabled the dissemination of health misinformation, and the prosocial aspects of sharing are also likely to involve the sharing of misinformation, putting the health of users at risk [ 3 ].

Misinformation Spreads on Social Media

There is a high degree of consensus among researchers that mainly because of the increasing popularity of social media, the internet has become a space for the dissemination and amplification of “fake news,” misleading information, and rumor, including health misinformation and antivaccine conspiracy theories [ 17 ]. The COVID-19 pandemic has heightened these concerns, resulting in a proliferation of recent studies and rapid reviews focusing on the online spread of misinformation. Lee et al [ 18 ] proposed that the proliferation of health misinformation during the COVID-19 pandemic became a major public health issue. At the earliest signs of the emerging COVID-19 pandemic, the director-general of the World Health Organization, Tedros Adhanom Ghebreyesus, speaking at the February 2020 Munich Security Conference, expressed concern about the risk of an infodemic of health misinformation disseminated via social media, identifying “vaccine hesitancy” as 1 of the top 10 global health threats [ 19 ]. Bapaye and Bapaye [ 20 ] agreed that the risks of misinformation on social networking sites constitute a global issue, referring specifically to the COVID-19 infodemic.

However, this is not in itself a new problem; longstanding concerns about “fake news” and misinformation in traditional media have been evident since the early decades of the 20th century [ 21 ], and the prevalence of misinformation on internet platforms certainly predates the COVID-19 pandemic. Therefore, because the COVID-19 pandemic has only intensified the concern regarding health misinformation, it might be more appropriate to see the pandemic as symptomatic of, and crystallizing, the challenges of countering health misinformation in the digital age, as the development of digital technology and the internet have brought about profound changes in the capacity of both misinformation and disinformation to spread globally and amplify rapidly [ 4 ].

Suarez-Lledo and Alvarez-Galvez [ 16 ] undertook a review of 69 studies of health misinformation on social media to identify the main health misinformation topics and their frequency on different social media platforms. The studies surveyed used a variety of research methods, including social network analysis (28%), evaluation of content (26%), evaluation of quality (24%), content/text analysis (16%), and sentiment analysis (6%). Suarez-Lledo and Alvarez-Galvez [ 16 ] concluded that the incidence of health misinformation was highest on Twitter, in particular, regarding the use of tobacco and other drugs, with some studies citing 87% of such posts containing misinformation. However, health misinformation about vaccines was also prevalent, with around 43% of posts containing misinformation, with the human papillomavirus vaccine being the most affected. This review by Suarez-Lledo and Alvarez-Galvez [ 16 ] confirmed many of the findings from earlier surveys. For example, in their survey of 57 articles, Wang et al [ 4 ] found that the most frequently discussed topics were regarding vaccination and infectious diseases, including Ebola and the Zika virus. Other topics such as nutrition, cancer, water fluoridation, and smoking were also prevalent. The studies they surveyed had tended to find that a high degree of misinformation on these topics was being shared and liked on social media.

Lee et al [ 18 ] conducted a cross-sectional online survey in South Korea to examine the prevalence of COVID-19 misinformation and the impact of exposure to COVID-19 misinformation on beliefs and behaviors. They found that exposure to COVID-19 misinformation was associated with misinformation belief, which then resulted in fewer preventive behaviors. Therefore, they highlighted the potential of misinformation to undermine global efforts in disease control and argued that public health strategies are needed to combat the proliferation of misinformation. Bapaye and Bapaye [ 20 ] conducted a cross-sectional online questionnaire survey of 1137 WhatsApp users in India. They noted that most research on the prevalence of misinformation in social media has focused on Twitter and Facebook and on the Global North. Measured by age, researchers found that users aged >65 years were the most vulnerable to accepting the veracity of messages containing health misinformation (K=0.38, 95% CI 0.341-0.419) Respondents aged 19 to 25 years displayed much lower vulnerability (K=0.31, 95% CI 0.301-0.319) than those aged >25 years ( P <.05). Measured by occupational category, users employed in nonprofessional occupations had the highest vulnerability (K=0.38, 95% CI 0.356-0.404); this was significantly higher than those of professionals and students ( P <.05). Notably, the vulnerability of health professionals was not significantly different from those of other occupation groups ( P >.05).

The authors concluded that in a developing country, WhatsApp users aged >65 years and those involved in nonprofessional occupations are the most vulnerable to false information disseminated via WhatsApp. Crucially, they noted that health care workers, who might be expected by laypersons to have expert knowledge, were as likely to be vulnerable to health misinformation as other occupation groups.

Antivaxxer Spread Before, During, and Beyond the COVID-19 Pandemic

Much of the current unease from researchers, understandably, centers on health misinformation about vaccines in the wake of the COVID-19 pandemic. In particular, there is concern about the growth and spread of so-called antivaxxer misinformation and beliefs. In 2019, the United States had its biggest measles outbreak in 30 years, with most cases involving people who had not been vaccinated. Hotez [ 22 ] claimed that much of the reason for the growth of antivaccine beliefs is because of a campaign of misinformation. He argued that social media sites are meeting places for the sharing of antivaccine views. To evade social media platforms’ automated moderation tools, which tend to focus on words, several antivaxxer groups, including one with around 250,000 members, began using visual codes, such as the carrot emoji, to hide antivaxxer content.

However, some of the misinformation has gained credibility because it has come from sources that laypersons would expect to be trustworthy. For example, in 1998, the British medical journal The Lancet published a paper by Dr Andrew Wakefield claiming a link between the measles, mumps, rubella vaccine and the onset of autism spectrum disorder. Wakefield’s paper was later rebutted, and an overwhelming body of evidence now refutes its conclusions [ 23 ]. However, despite long being discredited, Wakefield’s claims have remained a part of the antivaccine discourse. The persistence of the antivaccination narrative demonstrates the power of such discourses even in the face of evidence to challenge them.

Although strong antivaccine beliefs, and the more ambivalent attitude of vaccine hesitancy, have been around as long as there have been vaccines, until recent decades, they were on the margins. However, evidence supports the claim that they have been gaining momentum in the United States and Europe.

A survey by Skafle et al [ 24 ] aimed to synthesize the results from 19 studies in which the effect of social media misinformation on vaccine hesitancy was measured or discussed. The authors noted that the “vast majority” of studies were from industrialized Western countries. Only 1 study contained misinformation about autism as a side effect of COVID-19 vaccines. Nevertheless, the studies implied that information spread on social media had a negative effect on vaccine hesitancy and uptake. The conclusions from Skafle et al [ 24 ] were supported by data from online polling agencies. For example, a US YouGov poll from May 2020 found that only 55% of respondents would definitely take a COVID-19 vaccine if one were to become available, whereas 19% of respondents said that they would refuse and 26% were still undecided [ 25 ].

While much of the research about online vaccine discourse comes from the United States, there is also evidence that vaccine hesitancy has risen elsewhere. For example, in an Ipsos-MORI survey taken in December 2020, only 40% of respondents in France said they would take a COVID-19 vaccine, a figure symptomatic of a steep and swift decline in vaccine confidence in France [ 26 ]. However, interestingly, the same Ipsos-MORI poll indicated a rise in vaccine confidence among respondents in the United States since the earlier YouGov poll, cited earlier, by approximately 10% to 65%, and respondents in the United Kingdom expressed a still higher willingness to take a COVID-19 vaccine at approximately 77%. It is notable that in the United States and United Kingdom, the Ipsos-MORI results came after a period of intermittent lockdowns. The contrast with the results from France is, nevertheless, striking.

Understanding the Challenges Surrounding Health Misinformation

Here, we consider the challenges created by health misinformation on the web: (1) the role played by malicious actors on social media in spreading vaccine disinformation and misinformation and (2) how contextual and cultural issues have different effects on patients’ understanding of what is considered genuine, valid, and authentic health information.

Spread of Health Misinformation on Social Media by Malicious Actors

One strand of research presents the issue of health misinformation as a contest between trolls and bots on the one hand and the voices of trustworthy public health agencies on the other [ 6 ]. This view was supported by Hotez [ 22 ] and Broniatowski et al [ 11 ]. The latter investigated the role of bots and trolls as malicious actors mobilizing vaccination discourse on the web. Their study focused specifically on vaccine-related health messaging on Twitter. Comparing the rates of vaccine-related messages, they found that sophisticated bots and Russian trolls tweeted at higher rates than “average users.” However, the respective content from bots and trolls differed. Whereas bots communicated antivaccine messages, Russian troll accounts provided a seemingly balanced discussion of both provaccination and antivaccination arguments, implying an equivalence between them. The authors argued that amplifying and normalizing a debate is done with the purpose of sowing discord and may lead to undermining public confidence in scientific consensus about the effectiveness of vaccines. Wang et al [ 4 ] acknowledged that it is a challenge to readily distinguish between misinformation and disinformation on the web. They noted that disinformation, such as antivaccine propaganda, can unknowingly be spread by users with genuine concerns [ 4 ], as individuals increasingly seek health and healthy lifestyle information via the internet.

Contextual Factors Influencing the Reception of and Responses to Misinformation: Politicization of the Problem of Health Misinformation

The identification of online trolls, bots, and orchestrated networks as major contributors to the spread of health disinformation and misinformation is now part of mainstream political discourse in the United States. On July 16, 2021, a quarrel broke out between the president of the United States, Joe Biden, and Facebook over the spread of health misinformation on the company’s social media platforms. Speaking to journalists, Biden blamed social media companies for a rise in the number of deaths from COVID-19 among the unvaccinated in the United States. Referring explicitly to Facebook, the president claimed that by allowing the proliferation of health misinformation on its platforms, the company was “killing people” [ 27 ]. Discursive interventions from politicians are never neutral; nevertheless, Biden’s claim about the impact of health misinformation on social media is backed up by many of the studies surveyed for this paper. Facebook immediately rebutted Biden’s accusation by citing their rules, introduced in February 2021, which banned posts that make identifiably false claims about vaccines. Furthermore, Facebook challenged Biden’s claim by asserting that not only has Facebook provided more authoritative information about COVID-19 and vaccines than any other internet site, reaching 2 billion people with such posts, but also that the platform’s vaccine finder tool had been used by more than 3 million Americans.

These figures suggest that although antivaxxer groups find ways to evade detection, their reach may be countered by that of information grounded in current science. A spokesperson for the company said that, far from killing people, “The facts show that Facebook is helping save lives. Period” [ 27 ]. The argument between Biden and Facebook may indeed signal more lay awareness of the problem and echo the concerns of the recent academic research about the dissemination of health misinformation by organized bot and troll networks. Framed as it is, in terms of apportioning the blame for the spread of health misinformation, Biden’s intervention mirrors much of the academic discourse in the United States on the subject. However, it is also symptomatic of the politicization of health misinformation, arguably accelerated by the COVID-19 pandemic, which may thwart evidence-based decision-making. This point was emphasized strongly by Kyabaggu et al [ 5 ]. They framed the problem of pervasive misinformation and disinformation in terms of prime movers and beneficiaries who use it to advance sociopolitical agendas and entrench asymmetrical power, especially in times of uncertainty and threat, such as the COVID-19 pandemic.

Kyabaggu et al [ 5 ] identified government failures to adopt evidence-informed decision-making. They noted that such failures have costs that not only are economic but, crucially, result in poorer health outcomes. They cited as an example the United Kingdom government’s initial prevaccine herd immunity strategy. The intention of this strategy was to allow SARS-CoV-2 to indiscriminately spread to a critical mass to build up population immunity. The authors noted that this was “a particularly concerning example of evidence framing by a government.” Kyabaggu et al [ 5 ] argued that public acceptance of health risk messages and adoption of health-protecting behaviors is highly contingent on the degree to which governments engage in evidence-informed decision-making and communicate this basis effectively. The authors cited several instances of government actors failing to recognize misinformation, disseminating inconsistent or inaccurate information, and not using evidence- and information-based decision-making processes. In recent years, the public policy discourse in the United Kingdom has been veering away from evidence- and information-based decision-making, as politicians have denounced “experts” and their “influence” on policy [ 28 , 29 ].

Finally, Gruzd et al [ 30 ] reported on the impact of coordinated link-sharing behavior to spread and amplify conspiracy-related misinformation. They found a coalition of Facebook accounts that engaged in coordinated link sharing behavior to promote COVID-19 related misinformation. This coalition included US-based pro-Trump, QAnon, and antivaccination accounts.

Contextual Factors Influencing the Reception of and Responses to Misinformation: Health Literacies and Inequality

While the approach of Broniatowski et al [ 11 ], for example, provided a persuasive account of ways in which online health misinformation can be disseminated, there are limitations to this approach, as it did not provide an account of how users respond to the misinformation they encounter. The responses of ordinary users were assumed rather than investigated. Research by Vosoughi et al [ 31 ] provided a caveat to the claim that it is bots that accelerate the spread of misinformation. Their work supported that of Broniatowski et al [ 11 ] in suggesting that bots spread accurate and false information at the same rate. However, Vosoughi et al [ 31 ] also explained that misinformation spreads more rapidly than accurate information because humans, rather than bots, are more likely to spread misinformation [ 31 ]. This claim was further supported by Wang [ 32 ], who suggested that in democracies, where ideas compete for attention in a marketplace, accurate scientific information, which, for the layperson, may be boring or difficult to understand, is easily crowded out by information that is more easily grasped or sensational. Mokhtari and Mirzaei [ 12 ] located this problem specifically in the context of the COVID-19 pandemic. They considered that high mortality from COVID-19, its complexity, and its unknown features resulted in fear, anxiety, and mental pressure among people worldwide. To allay anxiety, people needed health information literacy, defined by the American Library Association as a set of abilities individuals require to recognize when information is needed and to locate, evaluate, and use it effectively [ 33 ]. In addition, Wang [ 32 ] noted that individuals are differentially vulnerable to health misinformation depending on their level of health literacy and that models need to account for this. Mokhtari and Mirzaei [ 12 ] argued that not only information and health literacies but also media literacy are needed. However, studies in the field of health literacy suggest that significant inequalities in health and digital literacies exist.

Researchers have argued that “vastly undervalued and unrecognized” health literacy ought to be considered the best “social vaccine” for preventing COVID-19 in populations [ 5 ]. However, inequalities in health literacy persist. Kyabaggu et al [ 5 ] defined health literacy as encompassing cognitive and social skills that determine individuals’ motivation and ability to access, understand, and use information, including quantitative health risk information, in ways that promote and maintain good health across the life course. They asserted that health literacy is an essential self-management skill and community resource for health, noting that health literacy is positively associated with patients’ involvement in clinical decision-making, willingness to express health concerns, and compliance with clinical guidance. However, despite research demonstrating the importance of health literacy, evidence, even from high-income countries, suggested relatively low levels of health literacy.

Kyabaggu et al [ 5 ] drew a link between health literacy and digital literacy. They suggested that the latter can be understood as health literacy in digital information and technology spaces. They argued that inequalities in health outcomes are exacerbated by a widening digital divide. While digital technology in health and social contexts presents both new risks and opportunities for equity in different information audiences, the ways in which power and privilege operated in the COVID-19 misinformation discourse have not been sufficiently examined. Although socially and economically disadvantaged groups were at a greater risk of exposure to COVID-19, their voices and experiences were often marginalized. In addition, inequalities in access to accurate information are not only related to issues of digital access and literacy but are also situational. For example, disadvantaged individuals may have fewer social connections, and low pay may necessitate longer working hours, militating against individuals having the resources of time and energy to seek out accurate health information and enhance their level of health literacy.

The experiences of specific groups may also go unreported. Quraishi [ 34 ] addressed the impact of misinformation on South Asian students—a fast-growing group in the United States, but one that often receives little media attention. Quraishi [ 34 ] concluded that there is a relationship between the COVID-19 pandemic and students’ academic performance and mental health, as well as an increase in the spread of misinformation regarding COVID-19 public safety guidelines.

Older adults can be a vulnerable group in relation to their comparatively poor digital literacy. Zhou et al [ 35 ] reported on the accuracy of older adults in judging health information credibility. They found that on average, participants only successfully judged 41.38% of health articles. Attractive headlines increased participant credibility judgments on the content, and of the articles shared with others, 62.5% contained falsehoods.

Contextual Factors Influencing the Reception of and Responses to Misinformation: Cultures and Values

Larson and Broniatowski [ 19 ] argued that developing the kinds of literacy advocated by Mokhtari and Mirzaei [ 12 ] and Tully et al [ 2 ] will not address the deep-seated problems they identified. The work by Kyabaggu et al [ 5 ] supported this, and noted that the infodemic crisis is not merely a health and digital literacy issue. Some demographics may be more vulnerable to persuasive communication from broader sociocultural forces. Kyabaggu et al [ 5 ] argued that in considering the social determinants of health, attention must be paid not only to digital and health literacies but also to the ways in which these literacies coexist and interact with other influences. Larson and Broniatowski [ 19 ] suggested that one of the strongest determinants of vaccine confidence or vaccine hesitancy is the level of trust or distrust in the institutions that produce vaccines. A higher level of trust encourages the willingness to accept a high level of risk for a greater benefit. A lower level of trust militates against the acceptance of even a low level of perceived risk. For Larson and Broniatowski [ 19 ], it is not simply the presence of misinformation on social media networks but the social and cultural context of users’ reception of that information that influences responses. Health information operates in a complex and contentious social world. Individuals and communities respond to new information in terms of already developed political, cultural, and social values that influence whether they trust or distrust authority. Populations may be characterized by trust or mistrust of scientific institutions and government. Trust has been eroded through the exposure of fraud, research scandals, and misconduct by major multinational pharmaceutical companies, for example. Communities may be predisposed to distrust the government and its agents depending on their own status or identity. According to Goldenberg [ 36 ], these contexts can make misinformation and health conspiracy theories compelling.

Strategies to Correct Online Misinformation

We address the additional pressures on health professionals in communicating accurate information to mitigate the effects of misinformation, particularly with regard to the additional requirements imposed as a result of the precautions being taken during the pandemic. One area of disagreement in the literature concerns the usefulness of user correction response.

Research Into User Correction Strategies

There is some disagreement as to whether engagement with misinformation by users spreads and reinforces it or even whether extended debates over health misinformation cause users to doubt the possibility of knowable facts. For example, Broniatowski et al [ 11 ] argued that when ordinary users directly confront vaccine-skeptic messages from bots, it only serves to legitimize the “debate.” By contrast, Tully et al [ 2 ] argued that social media users have a role to play in either spreading or stopping the spread of misinformation across platforms. Their research aimed to uncover what factors influenced users’ responses. Tully et al [ 2 ] acknowledged that a range of factors can influence the spread or prevention of misinformation, including the behavior of malicious actors such as bots and trolls; the platform’s terms of service; and content moderation policies. As already noted, while most users are not creators of misinformation, they may spread and amplify it by liking, sharing, or replying. In opposition to the work of Broniatowski et al [ 11 ], Tully et al [ 2 ] argued that the content of engagement is particularly important, as their research suggested that multiple corrections by social media users may be required to reduce misperceptions. However, they claimed that most people simply ignore misinformation when they see it on social media.

Tully et al [ 2 ] noted the promise in mobilizing users to engage in such correction, given the vast numbers of users on these sites, in comparison with professional fact-checkers and health authorities.

They considered whether the tone of a correction would influence perceptions of the credibility of the message. However, despite some mixed evidence, they concluded that overall, the tone was not a significant factor and that neutral, affirmative, and uncivil corrections were all effective at reducing misperceptions. They found that participants were generally unlikely to reply to the misinformation tweet. However, their content analysis of hypothetical replies suggested that when users did reply, they mainly provided correct information, particularly after seeing other corrections. Tully et al [ 2 ] concluded that user corrections offer “untapped potential” in responding to misinformation on social media, but further work is needed to consider how users can be mobilized to provide corrections, given their overall unwillingness to reply. However, a limitation of the experimental approach of Tully et al [ 2 ], acknowledged by the researchers, is that in asking individuals what they would hypothetically do, this may not reflect what they actually do in a real social media setting, especially in relation to an issue they care more strongly about. Although the experiment gauged attitudes, it did not delve into how strongly these attitudes were held. It is also not clear to what degree corrections were effective at reducing misperceptions and how reductions were measured.

By contrast, the results of experimental studies by Ittefaq [ 37 ] and Mourali and Drake [ 38 ] suggested that correcting misinformation is by no means a straightforward proposition. They noted the previous research on rebuttal, which suggested that properly designed corrections can mitigate the effects of misinformation. However, such studies have tended to compare responses to misinformation followed by correction with responses of a control group that receives no correction or receives an alternative correction. Mourali and Drake [ 38 ] argued that this static approach misses the dynamic nature of social media debate. They noted that the correction of misinformation is generally followed up with a rebuke by the original poster, inciting further correction and prolonged back-and-forth debate. Mourali and Drake [ 38 ] cited previous studies showing that exposure to conflicting information about health topics, including mammography, nutrition, and the human papillomavirus vaccine, may increase confusion and negative attitudes toward that particular health topic. The researchers found that initial exposure to misinformation had a negative impact on attitudes and intentions toward masking, consistent with previous studies that concluded that exposure to misinformation negatively impacts attitudes and intentions toward behaviors favored by science. Also consistent with previous research, they found that the first correction of the false claim improved attitudes and intentions toward masking. The authors suggested that this effect is partially explained by a decrease in the perceived strength of the argument underlying the false claim. However, this initial improvement diminished on further exposure to false claims and refutation attempts. This finding confirmed their hypothesis that extended exposure to false claims and refutation attempts appears to weaken belief in the possibility of objective knowledge, leading to less positive reactions toward masking as a science-based behavior. They concluded that the level of exposure to contradictory information needs to reach a certain threshold before it affects perceived truth objectivity. However, although people are more likely to share misinformation when its content is consistent with their existing beliefs or when its message is simple, direct, or sensational, correcting misinformation does reduce its likelihood of being shared on social media, an effect that persists even after multiple exposures.

Mourali and Drake [ 38 ] noted that each social media platform exhibits particular interaction norms, which may impact how users interpret the conversation. As their study was limited to a single platform, Reddit, and the debate was restricted to 4 exchanges between only 2 protagonists, the researchers acknowledged that these aspects limit the generalizability of the results. They suggested that future research could attempt to replicate their findings on different social media platforms, and to include more than 2 protagonists and more than 4 exchanges. They noted further that although extended debates are common on social media, it is not known how frequently they occur, echoing the comments by Suarez-Lledo and Alvarez-Galvez [ 16 ] that the extent of misinformation is not clear.

In contrast to the fairly sanguine view of Tully et al [ 2 ] about the potential of users to spread corrective information, Mourali and Drake [ 38 ] problematized the position, pointing to the potential for more complex and uncertain outcomes, whereas Larson and Broniatowski [ 19 ] argued that although the importance of correcting misinformation, item by item, should not be diminished, only if underlying issues driving misinformation are addressed can, for example, long-term vaccine confidence in populations be sustained. They argue that simply responding to misinformation with factual corrections is not likely to reverse the dissent that has been evident among antivaxxers or to necessarily persuade the more ambivalent vaccine-hesitant individuals. They identified deeper social and cultural issues at play, which have been discussed in this paper in the previous sections.

Research Into Effective Models to Accomplish the Automatic Detection of Health Misinformation in Online Health Communities

Here, we consider examples of research into the automatic detection of health misinformation in online health communities. Zhao et al [ 3 ] began from the premise that there is a vast amount of health misinformation, creating a challenge for health communities in identifying misinformation. Rather than relying on users’ ability to correct misinformation, they proposed that there is a need for an effective model to achieve automatic detection of health misinformation in online health communities. This view was also put forward by Weinzierl and Harabagiu [ 39 ]. Focusing specifically on COVID-19 vaccine misinformation, they argued that automatic detection of misinformation on social media is an essential first step in delivering interventions designed to address vaccine hesitancy.

Zhao et al [ 3 ] identified much of the existing analysis as concentrating on the linguistic features of communications only. They wanted to examine the underresearched area of whether integrating user behavioral features with linguistic features, sentiment features, and topic features could effectively distinguish misinformation from accurate information in online health communities. Their study combined the aforementioned features to build a detection model targeting misinformation in online health communities’ contexts. The behavioral features targeted were discussion initiation, interaction engagement, influential scope, relational mediation, and informational independence. Descriptions of these behavioral features are reproduced in Table 1 .

The authors tested their detection model on a data set collected from a real online health community, selecting as their data source Zibizheng Ba, an autism forum on the Baidu Tieba online health community site hosted by the Chinese web service Baidu. Baidu Tieba claims to be one of the largest interest-based discussion platforms in China. Users can generate topic-based discussion forums on the platform, share information, and make friends with other users. Posts on Baidu Tieba are indexed by Baidu, China’s most popular search engine, so users can readily find misinformation when searching for health-related information through the search engine. The authors developed a python-based web crawler to collect data from the forum. To train the health misinformation detection model, 5000 records were sampled from the whole data set by stratification according to 3 types of records (ie, thread, reply, and reply to reply) using stratified sampling methods. Therefore, the constituent types of the records (ie, thread, reply, and reply to reply) in the sample data set were consistent with the composition of the whole data set.

The researchers applied the elaboration likelihood model (ELM). The model, originally developed by Petty and Cacioppo [ 40 ] to explain attitude change, has been used extensively in advertising to try to influence consumers.

Overall, 4 types of misinformation were identified through their coding analysis, and the model correctly detected about 85% of the health misinformation. Their results also indicated that behavioral features were more informative than linguistic features in detecting misinformation. The authors concluded that their results not only demonstrated the efficacy of behavioral features in health misinformation detection but also offered both methodological and theoretical contributions to misinformation detection by integrating the features of messages as well as the features of message creators. Others have also highlighted the problems posed by misleading visual information [ 41 ].

It is worth noting that during the pandemic, the UK National Health Service (NHS) began using Twitter to promote provaccine messaging, which closely follows a combination of the features suggested by Zhao et al [ 3 ]. When users searched for the term “vaccine” or related terms, the top post was a message prominently displaying the NHS logo, identifying it as reputable and trustworthy. The tweets contained links to NHS websites providing information about vaccines and COVID-19. The posts differed in linguistic content and visual design. For example, one featured only written text on a white background and stated in bold, “Know the facts.” Another featured a large image of a happy minority ethnic family, washing dishes together, with the message that the COVID-19 vaccine decreases household transmission by up to half. The contrasting designs suggest that the message was targeted specifically to users’ timelines. It was also apparent that elements of ELM were being applied, combining the features identified by Zhao et al [ 3 ] in different ways.

Weinzierl and Harabagiu [ 39 ] adopted a different method than Zhao et al [ 3 ], reversing the more commonly used classification approach. The authors of each study claimed strong results in identifying health misinformation on social media platforms. However, Nabożny et al [ 42 ] argued that the current automatic systems for assessing the credibility of health information are not sufficiently precise to be used without supervision by human medical expert annotators.

Barve and Saini [ 43 ] have reported on their use of automated fact-checking using a coded content similarity measure (CSM). In this approach, the CSM showed improved accuracy (91.06%) compared to the accuracy of the Jaccard similarity measure (74.26%). Further, the algorithmic approach outperformed the feature-based method.

Neither Zhao et al [ 3 ] nor Weinzierl and Harabagiu [ 39 ] recorded what happens when misinformation is detected. Research from Broniatowksi et al [ 44 ] suggested that once detected, steps taken by social media platforms such as content removal or deplatforming may not be effective in stemming the spread of misinformation and may even be counterproductive. Social media platforms use a combination of “hard” and “soft” content remedies to reduce the spread of health misinformation. Soft remedies include warning labels attached to content and downranking of some content in web searches, whereas hard remedies include content removal and deplatforming of accounts. Hard remedies are controversial and have given rise to accusations of censorship. For the authors, short-term evidence for the effectiveness of hard remedies is in any case mixed, and long-term evidence is yet to be examined. Their study focused on Facebook and found that while hard remedies did reduce the number of antivaccine posts, they also produced unintended consequences. Provaccine content was removed, and engagement with the remaining antivaccine content repeatedly recovered to prepolicy levels. Worryingly, this content became more misinformative, more politically polarized, and more likely to be seen in users’ news feeds. The authors explain these results as a product of Facebook’s architecture, which is designed to promote community formation. Members of communities dedicated to vaccine refusal seek out misinformation. To meet this demand, and to circumvent content moderation efforts, antivaccine content producers post links to external sources of misinformative content, such as Bitchute, Rumble, Gab, and Telegram, in lieu of more mainstream platforms that had implemented similar content removal policies (eg, YouTube and Twitter). Broniatowski et al [ 44 ] argued that Facebook’s policy reduced the number of posts in antivaccine venues but was not successful in inducing a sustained reduction in engagement with antivaccine content, including misinformation. The authors noted that alternative platforms often host politically extreme right-wing content. Therefore, they argued that Facebook’s content removal policies may have the unintended consequence of radicalizing their audiences, and their findings suggested the need to address how social media platform architecture enables community formation and mobilization around misinformative topics when managing the spread of online content.

These studies advocate for the automatic detection of health misinformation. However, work that calls into question the ability of automatic detection to operate without human intervention has also been discussed. In addition, there are questions raised in the literature about what should be done when misinformation is detected and concerns about whether content removal or deplatforming of accounts are the most effective ways to reduce the spread of health misinformation or may even be counterproductive.

The Roles of Health Practitioners

The discussion so far has highlighted the complex and multifaceted dimensions of the context of online health misinformation in which health practitioners must operate. As noted in our introduction, a study of health practitioners in North Carolina found that nearly 95% had encountered patient health misinformation within the previous year [ 10 ]. There is very little research on the amount or effectiveness of training received by health professionals to prepare them for engaging with patients about health misinformation. Wood et al [ 10 ] found that most respondents had not received relevant training despite overwhelmingly reporting encountering health misinformation.

Nevertheless, within the literature, there is no shortage of advice from researchers and health professionals addressed to health practitioners on how to approach and correct health misinformation. This advice stems from both original research studies and reviews of best practices featured in peer-reviewed medical and health journals. Such advice centers on the need for health practitioners to understand misinformation and how to address it. Health practitioners are advised of the need to be aware of health myths and urged to dismantle them in providing accurate health guidance [ 45 , 46 ]. Practitioners are further advised that misinformation and pseudoscience are appealing to those seeking certainty because they present information in absolutes, whereas medical science is often ambiguous and contingent. Health practitioners are also encouraged to learn how to message more clearly and to mimic the strategies of misinformation [ 45 ]. One study recommends that “practitioners familiarize themselves with the tools of scientific enquiry and consider the pros and cons of various conspiracy evaluation guidelines” [ 47 ]. Thompson [ 48 ] reports on the activity of health professional influencers and pedagogues in combating misinformation. However, the effectiveness of such social media influencers who are also health professionals remains unclear. At the same time, there is some acknowledgment in this body of literature that misinformation cannot simply be offset with facts, confirming the challenges, discussed earlier, of simply engaging in online refutation. Addressing misinformation also depends on meeting patients’ emotional needs [ 45 , 49 ].

In this context, the one-to-one patient-provider relationship in the practice setting is perceived as paramount [ 45 ]. As suggested by much of the research, source credibility, or trust, is understood to be the strongest driver of effective correction strategies [ 50 ]. It is argued that health care practitioners have the unique opportunity to guide patients toward high-quality, evidence-based medical information [ 10 ]. However, it is also noted that practitioners will need patience in their efforts to persuade patients to abandon strongly held self-beliefs, however harmful. Doing so may mean patients relinquishing membership of online communities that have become integral in their lives and even their identities. As noted earlier, belief in misinformation is often persistent in the face of evidence. Success is more likely when individuals are encouraged to reexamine their information sources, alongside new information providing additional context, rather than simply characterizing the individual’s beliefs as wrong [ 51 ]. Kyabaggu et al [ 5 ] commented that good health communication needs to be tailored to the underlying cause of the misinformation problem, and efforts should be made to take on board inequalities within populations to create accurate, low-barrier, targeted health risk messaging. Skafle et al [ 24 ] contended that to challenge misconceptions, false claims need to be openly addressed and discussed with both cultural and religious awareness in mind. Guidance for practitioners noted that while responding to patient questions about alternative or unproven therapies may become laborious, a strong bond of trust between health practitioner and patient gives a patient a feeling of being supported and increases their adherence to treatment [ 52 ]. Rather than waiting for patients to raise misinformation issues, health care practitioners are advised to anticipate and proactively address potential misinformation and myths with patients. For example, the mortality rate for pediatric cancer has risen during the COVID-19 pandemic because of delayed access to medical care, but misinformation related to COVID-19 may also be a contributing factor [ 53 ]. The literature highlights the challenge of navigating the information and misinformation and the need for health practitioners to communicate with their patients more effectively. However, such efforts are not always successful. Some of the factors that may prevent effective communication of good health information have already been raised in this paper. They are revisited and discussed in the next section, along with other stressors for health practitioners.

Stressors for Health Practitioners

Challenges for health practitioners include time pressures and the additional burdens placed on them during the COVID-19 pandemic. These additional pressures add to the issues health practitioners face in trying to mitigate the impact of misinformation. The following is a brief overview of these issues.

On the one hand, administrative burdens placed on practitioners frequently deny them time for dialogue with their patients [ 52 ]. On the other, in different contexts, practitioners may be coping with a lack of proper facilities; poor infrastructure for patient care; insufficient or ineffective personal protective equipment; lack of awareness among the general population; poor compliance with preventive methods; and the fear of being infected with the virus, as they too are exposed to misinformation. During the COVID-19 pandemic, health practitioners were considered more vulnerable than other workers to developing psychological problems and other stress-related disorders, as they treated patients confirmed with COVID-19 while also dealing with misinformation [ 54 ].

As noted above, practitioners are recommended to invest in developing high levels of patient trust and to proactively correct health misinformation. However, recommendations presuppose that health practitioners necessarily have the resources to do these things well. Some of the materials produced to educate patients are not always reliable or evidence based, resulting ultimately in a loss of trust on the part of patients [ 52 ]. In addition, as noted previously, health practitioners themselves are not necessarily immune from accepting health misinformation as credible. Evidence about the level of knowledge and understanding of COVID-19 among practitioners reveals its unevenness. A study of dentists and oral health practitioners’ knowledge about COVID-19 suggested that their knowledge was at a relatively high level [ 55 ]. By contrast, a study of 310 eye care professionals in Nepal revealed some knowledge but also some acceptance of misinformation. Symptoms of COVID-19 were known to 94% of participants, but only 49% of participants were aware of how the disease is transmitted. More significantly, 41% of participants believed that the consumption of hot drinks helps to destroy the virus, in contradiction to World Health Organization information. The mean overall “knowledge” performance score, as measured by the benchmarks set by the researchers, was 69.65% [ 56 ].

A qualitative study to investigate primary health care practitioners’ perceptions and understanding of the COVID-19 pandemic was conducted in KwaZulu-Natal, South Africa. The study collected data from 15 participants at 2 different clinics situated in rural KwaZulu-Natal. Participants comprised nurses, physiotherapists, pharmacists, community caregivers, social workers, and clinical associates. Data were collected through individual, in-depth face-to-face interviews using a semistructured interview guide. The participants reported prepandemic and pandemic experiences of fear or denial. There was a perception of poor preparation for the COVID-19 outbreak. The findings also revealed participants’ misperceptions regarding the nature of the COVID-19 pandemic. Researchers concluded that respondents’ misunderstandings regarding the pandemic were primarily a result of misinformation found on social media [ 57 ].

The discussion in this section so far has highlighted the significant potential of health practitioners in mitigating the impact of online health misinformation. However, it has also underlined factors that may militate against health practitioners’ ability to do so effectively. Not least of these is the issue of health practitioners’ own knowledge, which coexists with other stressors for health practitioners in combating misinformation. The discussion will now consider health information management (HIM) as a tool for supporting health practitioners’ knowledge base as one element in a multifaceted strategy for combating misinformation on the web.

HIM as a Mitigation Strategy

We have seen there is a need for health practitioners to be supported with evidence-based knowledge that they can share with patients. Kyabaggu et al [ 5 ] argued that the COVID-19 pandemic has demonstrated that in an infectious health crisis, the gathering of accurate and reliable data to assist with the public health response is essential. They highlighted the importance of HIM professionals in supporting contact tracing and syndromic surveillance, as well as in mapping and forecasting health data. They noted that the generation of health information supports the continuum of care and the setting of targets and indicators and aids the planning, monitoring, and evaluation of health programs locally and globally. The health information produced also underpins the development of equitable, efficient, and accessible health care systems, contributing to improving public health initiatives and outcomes. Kyabaggu et al [ 5 ] emphasized the importance of an area of HIM, currently in its early stages, that deals with gathering and identifying evidence about the structural inequalities that underlie the disparities in vulnerability to health misinformation discussed in this paper. The collection of rich, high-quality information, including patient-reported experience, outcome measures, and culturally appropriate identity data, can enable health practitioners and public health advisers serving the most disadvantaged and underrepresented communities to use more tools of advocacy for patients.

The authors noted that advances in technology, including artificial intelligence, have the potential to relieve some of the pressures and constraints on health practitioners working on the front line during crises such as the COVID-19 pandemic, allowing more time for one-to-one engagement with patients. Kyabaggu et al [ 5 ] advocated for the content expertise of health information managers to serve health practitioners by delivering patient-facing information triaging services; constructing user-friendly knowledge representations, such as data visualizations; and developing information interpretation tools, such as decision aids, plain language summaries, and supplementary explanatory information and metadata. Kyabaggu et al [ 5 ] identified the interdisciplinary underpinnings of HIM as essential in contributing to the educational, informational, and decision-making support for addressing current and future infodemic management crises.

Summary of Results

Within the literature, there is a consensus that there exists a significant problem of online health misinformation disseminated via the internet on social network platforms, often by online health communities. It is apparent that while users seek trustworthy sources of health information, they are unequally equipped to assess its credibility. This is partly because some groups lack sufficient levels of health and digital literacies, which may be exacerbated by concomitant social and economic inequalities. Reception of, and response to, online health misinformation is also shaped by users’ cultural contexts, values, and experiences, which may hinder trust in scientific institutions and governments. Evidence suggests that some demographics are more vulnerable to accepting health misinformation as credible and that health practitioners are unevenly prepared in the context of new global health crises, such as the COVID-19 pandemic. Furthermore, the evidence of disparities in positive and negative attitudes toward vaccination highlights a need to pay specific attention to regional and national settings, even in the current global context. Preexisting levels of local trust in vaccine providers may be a significant factor to consider. While the validity and reliability of YouGov polls are limited, nevertheless, the data from an admittedly narrow range of sources suggests that vaccine confidence may have become more fluctuating and potentially vulnerable to destabilization in the digital era.

While online mitigation strategies such as user correction and automatic detection may have their uses, their effectiveness is contested, and some studies suggest they may even be counterproductive. Our analysis of the available literature indicates that the effectiveness of these strategies varies and needs further evaluation [ 42 , 58 ]. The issue of online health misinformation is further complicated by the operation of malicious actors and politicization of the issue, particularly during the COVID-19 pandemic, militating against the equitable and trusted dissemination of evidence-based knowledge. The role of health practitioners in this context is a challenging one. Research suggests that on the one hand, they are still best placed, at the front line of care, to combat health misinformation with science-based knowledge and advice. On the other hand, the stressors identified in this review create barriers to their abilities to do this well. Constraints of time and lack of supporting infrastructure add to the knowledge deficit noted earlier. Our review underlines the complexity of the environment in which health practitioners operate and calls for greater support and resources to enable effective mitigation of health misinformation [ 59 ]. Investment in HIM at local and global levels could address all 3 deficits, creating the potential for health practitioners to enhance their capacity to build trust via knowledgeable one-to-one communication with patients.

Limitations

The limitations of this study are the following: First, the constraints of time and space have necessarily limited the scale and scope of the survey. Second, the study of online health misinformation is a growing field, and inevitably, the nature of the issue means that new evidence is emerging at a rapid rate. In particular, new knowledge and further reflection in the wake of the COVID-19 pandemic will continue to shed new light on the subject. Our study acknowledges these limitations and emphasizes the dynamic nature of the field.

Conclusions

Our survey of the literature on online health misinformation has revealed a complex and multifaceted context in which health practitioners must operate. As the world renormalizes following the pandemic, a collaborative global interdisciplinary effort to provide equitable access to timely, accurate, and complete health information will be needed to support health practitioners in combating the impact of online health misinformation. Academic research will need to be disseminated into the public domain in a way that is accessible to the public to counter misinformation and educate populations concerning how science is carried out. Our conclusions drawn from this review stress the urgency of effective strategies and collaborative efforts to mitigate the prevalence and impact of health misinformation on a global scale. Without strategies for equipping populations with the health and digital literacies required to interpret and use information appropriately, the prevalence of online health misinformation will continue to pose a threat to global public health efforts, disproportionately affecting vulnerable and resource-limited populations. Although social media platforms have a responsibility to correct misinformation, governments will need to engage in evidence-informed decision-making and invest in HIM to support frontline health practitioners in their work, enhance population health literacy, and strengthen evidence-informed decision-making at all levels.

Several issues for further investigation arise from the findings of this review. These include the following:

• The long-term impact of COVID-19 vaccine hesitancy
• Whether the COVID-19 pandemic has intensified or diminished information literacy, and the related question of whether the pandemic will incentivize health information literacy
• The effects of social and cultural differences on the long-term traction of future health misinformation
• Whether social and economic inequalities will become less or more pronounced in the face of a global pandemic
• The comparative effectiveness of strategies to enhance populations’ media and digital literacies to facilitate the mitigation of health misinformation and its effects
• The influence of state actors on the propagation of health misinformation on the web
• The extent to which academic research has been disseminated into the public domain in a way that is accessible to the public, and the effectiveness of strategies to do so to counter misinformation and educate populations concerning how science is carried out

Acknowledgments

This research was funded by the School of Computing and Communications at the Open University. It allowed researchers across several faculties to collaborate and build a research team that focused on the experience of health practitioners with misinformation and its impact on their job practice. The authors would also like to thank Tracie Farrell and Nashwa Ismail for their invaluable suggestions and recommendations, as well as their assistance in the article screening process.

Data Availability

The data analyzed in this study are derived from published articles available on Google Scholar. All articles included in the review are cited in the reference list. No additional data or code were collected or generated as part of this study.

Authors' Contributions

The study was conceptualized by DK; funding acquisition was managed by DK; data were curated by DK, AK, MM, and IK; formal analysis was conducted by DK and MM; the investigation was carried out by AK and MM; the methodology was designed by DK and MM; project administration was overseen by DK; resources were provided by DK; supervision was carried out by DK; validation was conducted by DK, AK, MM, and IK; visualization was handled by DK and MM; writing (original draft preparation) was done by DK; and writing (review and editing) was carried out by DK, AK, and MM. All authors reviewed and approved the final version.

Conflicts of Interest

None declared.

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Abbreviations

Edited by G Eysenbach, T Leung; submitted 15.04.22; peer-reviewed by G Nneji, S-F Tsao; comments to author 07.06.22; revised version received 29.09.22; accepted 12.07.24; published 19.08.24.

©Dhouha Kbaier, Annemarie Kane, Mark McJury, Ian Kenny. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 19.08.2024.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research (ISSN 1438-8871), is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.

A review of groundwater iodine mobilization, and application of isotopes in high iodine groundwater

• Review Paper
• Published: 21 August 2024
• Volume 46 , article number  388 , ( 2024 )

Cite this article

• Yulu Zheng 1 , 2 ,
• Haiming Li 1 , 2 ,
• Mengdi Li 1 , 2 , 3 ,
• Cuixia Zhang 1 , 2 ,
• Sihui Su 1 , 2 &
• Han Xiao 4  

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Excessive intake of iodine will do harm to human health. In recent years, high iodine groundwater has become a global concern after high arsenic and high fluorine groundwater. A deep understanding of the environmental factors affecting iodine accumulation in groundwater and the mechanism of migration and transformation is the scientific prerequisite for effective prevention and control of iodine pollution in groundwater. The paper comprehensively investigated the relevant literature on iodine pollution of groundwater and summarized the present spatial distribution and hydrochemical characteristics of iodine-enriched groundwater. Environmental factors and hydrogeological conditions affecting iodine enrichment in aquifers are systematically summarized. An in-depth analysis of the hydrologic geochemistry, physical chemistry, biogeochemistry and human impacts of iodine transport and transformation in the surface environment was conducted, the results and conclusions in the field of high iodine groundwater research are summarized comprehensively and systematically. Stable isotope can be used as a powerful tool to track the sources of hydrochemical components, biogeochemistry processes, recharge sources and flow paths of groundwater in hydrogeological systems, to provide effective research methods and means for the study of high iodine groundwater system, and deepen the understanding of the formation mechanism of high iodine groundwater, the application of isotopic technique in high iodine groundwater is also systematically summarized, which enriches the method and theory of high iodine groundwater research. This paper provides more scientific basis for the prevention and control of groundwater iodine pollution and the management of groundwater resources in water-scarce areas.

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Iodine enrichment and the underlying mechanism in deep groundwater in the Cangzhou Region, North China

Iodine in major danish aquifers, iodine in groundwater of the guanzhong basin, china: sources and hydrogeochemical controls on its distribution, explore related subjects.

• Environmental Chemistry

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No datasets were generated or analysed during the current study.

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Acknowledgements

We thank the experts and editors for their valuable revisions to this paper during the review process.

The authors are grateful for the financial support from the National Natural Science Foundation of China (Biogeochemical mechanism of iodine transport enrichment in coastal shallow salty groundwater: 42102299); the Open Fund Project of the MOE Key Laboratory of Groundwater Circulation and Environmental Evolution (Sulphur Biogeochemical Mechanism of Iodine Transport Enrichment in Coastal Shallow Underground Salty Water); and the National Natural Science Foundation of China (Study on the Characteristics of Salinization of Water Quality in Coastal Reservoirs and the Mechanisms of Hydrogeochemistry, 42072288).

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Yulu Zheng, Haiming Li, Mengdi Li, Cuixia Zhang & Sihui Su

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Zheng, Y., Li, H., Li, M. et al. A review of groundwater iodine mobilization, and application of isotopes in high iodine groundwater. Environ Geochem Health 46 , 388 (2024). https://doi.org/10.1007/s10653-024-02156-3

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DOI : https://doi.org/10.1007/s10653-024-02156-3

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