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  • Step 1: Seek Out Evidence
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Writing a Case Study

Hands holding a world globe

What is a case study?

A Map of the world with hands holding a pen.

A Case study is: 

  • An in-depth research design that primarily uses a qualitative methodology but sometimes​​ includes quantitative methodology.
  • Used to examine an identifiable problem confirmed through research.
  • Used to investigate an individual, group of people, organization, or event.
  • Used to mostly answer "how" and "why" questions.

What are the different types of case studies?

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Note: These are the primary case studies. As you continue to research and learn

about case studies you will begin to find a robust list of different types. 

Who are your case study participants?

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What is triangulation ? 

Validity and credibility are an essential part of the case study. Therefore, the researcher should include triangulation to ensure trustworthiness while accurately reflecting what the researcher seeks to investigate.

Triangulation image with examples

How to write a Case Study?

When developing a case study, there are different ways you could present the information, but remember to include the five parts for your case study.

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

literature review

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

Table of Contents

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

What is a literature review?

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

case study research literature review

What is the purpose of literature review?

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

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

Literature review example

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

Literature Review on Climate Change Impacts on Biodiversity:

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

a. Habitat Loss and Species Extinction:

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

b. Range Shifts and Phenological Changes:

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

c. Ocean Acidification and Coral Reefs:

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

d. Adaptive Strategies and Conservation Efforts:

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

case study research literature review

How to write a good literature review

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

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

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

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

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

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

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

what is a literature review

Conducting a literature review

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

Choose a Topic and Define the Research Question:

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

Decide on the Scope of Your Review:

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

Select Databases for Searches:

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

Conduct Searches and Keep Track:

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

Review the Literature:

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

Organize and Write Your Literature Review:

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

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

Frequently asked questions

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

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

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

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

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

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

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

References 

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

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CC0006 Basics of Report Writing

Structure of a report (case study, literature review or survey).

  • Structure of report (Site visit)
  • Citing Sources
  • Tips and Resources

The information in the report has to be organised in the best possible way for the reader to understand the issue being investigated, analysis of the findings and recommendations or implications that relate directly to the findings. Given below are the main sections of a standard report. Click on each section heading to learn more about it.

  • Tells the reader what the report is about
  • Informative, short, catchy

Example - Sea level rise in Singapore : Causes, Impact and Solution

The title page must also include group name, group members and their matriculation numbers.

Content s Page

  • Has headings and subheadings that show the reader where the various sections of the report are located
  • Written on a separate page
  • Includes the page numbers of each section
  • Briefly summarises the report, the process of research and final conclusions
  • Provides a quick overview of the report and describes the main highlights
  • Short, usually not more than 150 words in length
  • Mention briefly why you choose this project, what are the implications and what kind of problems it will solve

Usually, the abstract is written last, ie. after writing the other sections and you know the key points to draw out from these sections. Abstracts allow readers who may be interested in the report to decide whether it is relevant to their purposes.

Introduction

  • Discusses the background and sets the context
  • Introduces the topic, significance of the problem, and the purpose of research
  • Gives the scope ie shows what it includes and excludes

In the introduction, write about what motivates your project, what makes it interesting, what questions do you aim to answer by doing your project. The introduction lays the foundation for understanding the research problem and should be written in a way that leads the reader from the general subject area of the topic to the particular topic of research.

Literature Review

  • Helps to gain an understanding of the existing research in that topic
  • To develop on your own ideas and build your ideas based on the existing knowledge
  • Prevents duplication of the research done by others

Search the existing literature for information. Identify the data pertinent to your topic. Review, extract the relevant information for eg how the study was conducted and the findings. Summarise the information. Write what is already known about the topic and what do the sources that you have reviewed say. Identify conflicts in previous studies, open questions, or gaps that may exist. If you are doing

  • Case study - look for background information and if any similar case studies have been done before.
  • Literature review - find out from literature, what is the background to the questions that you are looking into
  • Site visit - use the literature review to read up and prepare good questions before hand.
  • Survey - find out if similar surveys have been done before and what did they find?

Keep a record of the source details of any information you want to use in your report so that you can reference them accurately.

Methodology

Methodology is the approach that you take to gather data and arrive at the recommendation(s). Choose a method that is appropriate for the research topic and explain it in detail.

In this section, address the following: a) How the data was collected b) How it was analysed and c) Explain or justify why a particular method was chosen.

Usually, the methodology is written in the past tense and can be in the passive voice. Some examples of the different methods that you can use to gather data are given below. The data collected provides evidence to build your arguments. Collect data, integrate the findings and perspectives from different studies and add your own analysis of its feasibility.

  • Explore the literature/news/internet sources to know the topic in depth
  • Give a description of how you selected the literature for your project
  • Compare the studies, and highlight the findings, gaps or limitations.
  • An in-depth, detailed examination of specific cases within a real-world context.
  • Enables you to examine the data within a specific context.
  • Examine a well defined case to identify the essential factors, process and relationship.
  • Write the case description, the context and the process involved.
  • Make sense of the evidence in the case(s) to answer the research question
  • Gather data from a predefined group of respondents by asking relevant questions
  • Can be conducted in person or online
  • Why you chose this method (questionnaires, focus group, experimental procedure, etc)
  • How you carried out the survey. Include techniques and any equipment you used
  • If there were participants in your research, who were they? How did you select them and how may were there?
  • How the survey questions address the different aspects of the research question
  • Analyse the technology / policy approaches by visiting the required sites
  • Make a detailed report on its features and your understanding of it

Results and Analysis

  • Present the results of the study. You may consider visualising the results in tables and graphs, graphics etc.
  • Analyse the results to obtain answer to the research question.
  • Provide an analysis of the technical and financial feasibility, social acceptability etc

Discussion, Limitation(s) and Implication(s)

  • Discuss your interpretations of the analysis and the significance of your findings
  • Explain any new understanding or insights that emerged as a result of your research
  • Consider the different perspectives (social, economic and environmental)in the discussion
  • Explain the limitation(s)
  • Explain how could what you found be used to make a difference for sustainability

Conclusion and Recommendations

  • Summarise the significance and outcome of the study highlighting the key points.
  • Come up with alternatives and propose specific actions based on the alternatives
  • Describe the result or improvement it would achieve
  • Explain how it will be implemented

Recommendations should have an innovative approach and should be feasible. It should make a significant difference in solving the issue under discussion.

  • List the sources you have referred to in your writing
  • Use the recommended citation style consistently in your report

Appendix (if necessary/any)

Include any material relating to the report and research that does not fit in the body of the report, in the appendix. For example, you may include survey questionnaire and results in the appendix.

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Organizing Your Social Sciences Research Paper

  • 5. The Literature Review
  • Purpose of Guide
  • Design Flaws to Avoid
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  • Glossary of Research Terms
  • Reading Research Effectively
  • Narrowing a Topic Idea
  • Broadening a Topic Idea
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  • Bibliography

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

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

Importance of a Good Literature Review

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

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

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

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

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

Types of Literature Reviews

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

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

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

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

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

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

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

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

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

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

Structure and Writing Style

I.  Thinking About Your Literature Review

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

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

The critical evaluation of each work should consider :

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

II.  Development of the Literature Review

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

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

III.  Ways to Organize Your Literature Review

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

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

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

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

IV.  Writing Your Literature Review

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

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

V.  Common Mistakes to Avoid

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

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

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

Writing Tip

Break Out of Your Disciplinary Box!

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

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

Another Writing Tip

Don't Just Review for Content!

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

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

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

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

Yet Another Writing Tip

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

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

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

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

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case study research literature review

A Review of the Literature on Case Study Research

  • Patricia Anne Brown University of Calgary

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Patricia anne brown, university of calgary.

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Literature review as a key step in research processes: case study of MA dissertations written on EFL of Saudi context

Saudi Journal of Language Studies

ISSN : 2634-243X

Article publication date: 1 June 2022

Issue publication date: 4 August 2022

The aim of this study is to find out the most common types of literature review and the accuracy of citing information related to topic in question among Saudi English as a Foreign Language (EFL) postgraduate students at Al-Baha University. This study also aims at revealing the quality of the literature review written by researchers.

Design/methodology/approach

This qualitative study used content analysis to investigate 15 unpublished Master of Arts (MA) dissertations written on EFL of Saudi context. They were analyzed qualitatively using criteria modified from Snyder's (2019) model which is considered a potential method for making theoretical and practical contributions of literature review.

The findings of the study showed that students favored the systematic review over the integrative. Additionally, data showed that students were lacking in paraphrasing and organizing cited information coherently and appropriately. Moreover, students' performance was better in design, conduct, and data abstraction and analysis criterion, whereas they seemed rather weak in structuring and writing the review criteria.

Originality/value

The significance of the study is to provide researchers with methodological guidance and reference to write a comprehensive and appropriate literature review. Based on the findings, this study concluded with some implications that aim to assist researchers in carrying out their studies professionally. Furthermore, the findings provide decision-makers in higher education institutions with important practical implications. In light of the study's findings, it is suggested to carry out further research investigating postgraduate students to find out their perceptions and attitudes regarding the quality standards of scientific research writing and the paraphrasing strategies.

  • MA students
  • Literature review

Integrative review

Semi-systematic review.

  • Systematic review
  • Literature review quality
  • Paraphrasing

Alsalami, A.I. (2022), "Literature review as a key step in research processes: case study of MA dissertations written on EFL of Saudi context", Saudi Journal of Language Studies , Vol. 2 No. 3, pp. 153-169. https://doi.org/10.1108/SJLS-04-2022-0044

Emerald Publishing Limited

Copyright © 2022, Ahmed Ibrahim Alsalami

Published in Saudi Journal of Language Studies . Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

Introduction

The way a researcher is building his/her research and linking it to current knowledge is like building a block of academic research activity, no matter which discipline it relates to, thus it is a priority step ( Snyder, 2019 ). In a definition by Liberati et al. (2009) cited in Snyder (2019) “ A systematic review can be explained as a research method and process for identifying and critically appraising relevant research, as well as for collecting and analyzing data from said research .” (p. 334). A literature review is an important part of any research as it is considered a foundation of the type of research.

As in Snyder (2019) , literature review is a written text of a published study that includes current knowledge and up-to-date information about the latest findings of science on a particular topic, including substantial discoveries as well as theoretical and practical contributions from scholarly research groups. A literature review as defined by Hart (1998) (Cronin et al ., 2008 cited in Ramdhani et al ., 2014 ) “ is an objective and thorough summary and critical analysis of the relevant, available research and non-research literature on the topic being studied ” (p. 48). A literature review requires a compound series of abilities to learn topics to explore and acquire and retrieve literature searching skills. Additionally, it requires the ability to develop, analyze and synthesize data to be keen on reporting and writing normally at a limited scale of time. Scholars divided the literature review into two types. The first is “Traditional or Narrative Literature Review”. This type of review criticizes and summarizes the body of the literature to draw conclusions about the topic under consideration. The basic aim of this review is to support a reviewer with a complete review to understand the knowledge and to show the implication of new inquiries. The second one is “Systematic Literature Review” which reviews the literature in a specific subject area to employ a more rigorous and well-defined approach. A systematic literature review is often used to solve a specific medical practice question ( Parahoo, 2006 ; Davis et al ., 2014 ; Almelhes, 2020 ). Some studies regard “meta-analysis” as a type of systematic review, which is primarily a statistical method that entails evaluating the research results among many studies on the very same topic using standardized statistical tests in drawing conclusions and identify patterns and trends between research results ( Polit and Beck, 2006 ; Dundar and Fleeman, 2017 ; Almelhes, 2020 ).

The most common types of literature review among Saudi EFL postgraduate students in Al-Baha University,

The accuracy of citing information related to the topic in question and

The quality of the literature review written by the MA researchers at Al-Baha University.

What are the most common types of literature review among Saudi EFL students at Al-Baha University?

To what extent is the accuracy of citing information related to the topic in question?

To what extent is the quality of the literature review written by the MA researchers at Al-Baha University?

Steps and phases of doing a literature review

Designing the review.

Why should this literature be reviewed? Do we really need literature in this area of our topic? And what literature review would be the great type for contribution? Indeed, these questions would be better borne in the mind of a researcher before starting to review the literature because they determine the likelihood of the review and the impact it might have on the research community ( Antons and Breidbach, 2018 ). As it is a hard work to conduct a literature review, the topic must interest both author and the reader. Hence, first of all, it is better to scan the points to relate to existing knowledge. Moreover, Palmatier et al . (2018) stated that any criterion related to the on-focus topic should be directed by the research questions.

Conducting the review

Conducting a review is required after deciding on the purpose, questions and type of approach that better suits the topic in question. Additionally, it is better to appropriately test the review process and protocol before performing the main review. To ensure the quality and reliability of the search protocol, it is important to use two reviewers to select articles depending on the nature and scope of the review ( Antons and Breidbach, 2018 ; Almelhes, 2020 ).

Analyzing the literature

To conduct appropriate analysis, it is important to consider how the articles will be used. Meanwhile, abstracting information needs to be professionally measured ( Palmatier et al ., 2018 ). They can be put into descriptive information (e.g. authors, year of publication, topic or type of study), or in effects and findings format, conceptualizations or theoretical perspective. Additionally, it is better to avoid any differences in coding and monitoring the data abstraction carefully during the review process in order to ensure quality and reliability. Researchers should ensure that their literature is appropriate to answer the selected research question.

Writing a review

The final review of any article depends on an approach that requires types of different information and different levels of details like standards and guidelines that explicitly address how literature reviews should be reported and structured (see Table 1 , below). Standards and guidelines for systematic narrative reviews ( Wong et al. , 2013 ) or guidelines for integrative reviews ( Torraco, 2005 ) should be considered in the final review too. Moreover, how literature was identified, analyzed, synthesized and reported by a researcher is necessary to describe transparently the process of designing the review literature. Literature reviews can result in a historical analysis of the development within a research field ( Carlborg et al ., 2014 ; Almelhes, 2020 ) or can be any agendas for further research ( McColl-Kennedy et al. , 2017 ), besides, conceptual model or categorization ( Snyder et al. , 2016 ; Witell et al ., 2016 ), or can be evidence of an effect ( Verlegh and Steenkamp, 1999 ).

The process of undertaking a literature review

Regardless of the method used to carry out the literature review, there seems to be a myriad of activities to be carried out and decisions made in order to build an assessment that satisfies the criteria for publication (for specific considerations with regards to each phase, as seen in Table 2 ). There are four phases that demonstrate and discuss the essential decisions and questions associated with conducting a literature review (as in Table 2 below): (1) designing the review, (2) conducting the review, (3) analysis and (4) structuring and writing the review ( Snyder, 2019 ). This procedure arose from real-world and practical experience and is a synthesis of and impact by diverse rules and specifications for literature reviews (e.g. Liberati et al. , 2009 ; Tranfield et al. , 2003 ; Wong et al. , 2013 ).

Types of literature review

Systematic literature review.

As described by Davis et al. , (2014) and later by Dundar and Fleeman (2017) , systematic reviews have first developed within medical sciences to synthesize research findings in a systematic, transparent and reproducible way. It can be a process for identifying and critically appraising relevant research for collecting and analyzing data from previous studies ( Liberati et al. , 2009 ; Almelhes, 2020 ). It aimed at identifying all empirical evidence that fits the pre-specified inclusion criteria to answer a particular research question or hypothesis. Bias can be minimized to provide reliable findings from conclusions and decisions ( Liberati et al. , 2009 ). Often statistical approaches are used to integrate the results of the topics in question. It combines results from different studies to evaluate and compare and identify patterns, disagreements or relationships ( Davis et al. , 2014 ) to assess them. It can be used to determine the continuity of effects across studies and to discover types of future studies that are required to be conducted to demonstrate the effect. Besides, techniques were used to discover which study-level or sample characteristics affect the phenomenon ( Davis et al. , 2014 ). The primary goal of a systematic review is to provide as comprehensive a list as possible of all studies whether published or unpublished, and these studies concerning a specific subject ( Ryan et al ., 2007 ; Dundar and Fleeman, 2017 ).

A systematic review needs to use standards as a roadmap for collecting studies ( Livinski et al ., 2015 ). Systematic review design has covered the following criteria: (1) studies related to students' attitudes; (2) the engagement of the learning process and (3) the outcomes of studies regarding speaking, writing and reading skills ( Antons and Breidbach, 2018 ; Almelhes, 2020 ).

The semi-systematic or narrative review approach hinders a full systematic review process. It is designed for different conceptualized and various studies that were studied by groups of researchers within various disciplines ( Wong et al. , 2013 ; Dundar and Fleeman, 2017 ).

Since it is hard to review every single article relevant to the topic, a different strategy must be developed ( McColl-Kennedy et al. , 2017 ). It aims at overviewing a topic and how research has progressed over time and developed. Generally, it seeks to identify and understand all potentially relevant research traditions and synthesize them by measuring effect size ( Wong et al. , 2013 ) and provides a considerate understanding of complex areas. It is potentially contributed to a useful analysis for detecting themes, and theoretical viewpoints of specific research disciplines as well as to identifying components of a theoretical concept ( Ward et al ., 2009 ). Thus, gain the ability to map a field of research, synthesize the state of knowledge and create an agenda for further research or the ability to provide a historical overview of a specific topic.

An integrative review is closely related to the semi-structured (integrative or critical review) approach. Usually, it has a different purpose from the semi-structured review which aims to assess, critique, and synthesize the literature in a way to develop new theoretical frameworks and perspectives ( Torraco, 2005 ). Generally, integrative literature reviews are intended to address mature or new topics. Additionally, seek to emerge topics to overview the knowledge base, critically review and potentially reconceptualize and expand on the theoretical foundation of the specific topic. It requires a more creative collection of data ( Whittemore and Knafl, 2005 ). A review of good literature does not summarize the sources, but rather analyzes, collects and evaluates them accurately to form a clear and general picture of existing knowledge or science on this topic.

Text borrowing skills

Text borrowing and incorporating other people's written ideas into one's own scholarly work are useful qualities to have in the world of academia, particularly for those pursuing higher education. Text borrowing expertise widely used in academic writing includes direct quoting, paraphrasing and summarizing. When contrasted to paraphrasing, directly quoting from the primary material is far more feasible, easier and less complex. There is really nothing inappropriate with integrating quotations; nevertheless, as Davis and Beaumont (2007) point out, overusing quotations does not really represent highly proficient writing. Rather, academic writing motivates the use of paraphrasing, drawing conclusions or synthesizing skill sets.

Paraphrasing is described as reiterating a statement in such a manner that both sentences are lexically and syntactically distinct whilst also remaining semantically equivalent ( Amoroso, 2007 ; Davis and Beaumont, 2007 ; McCarthy et al ., 2009 ). At least two echoes are implied by this description: reading process skills and writing ability. As a result, according to McCarthy et al . (2009) , paraphrasing is often used to aid comprehension, enhance previous knowledge and assist the development of writing skills.

According to cognitive psychology literature, paraphrasing is mentally demanding. As the content to be paraphrased has become more complicated, students are more likely to use simplified processing, resulting in patchwork written text (Marsh, Landau and Hick in Walker, 2008 ). Walker adds that just imagining about paraphrasing takes a substantial amount of cognitive vitality, and when the physical writing process starts, individuals have restricted opportunity to undertake thoughtful, systematic processing to ascertain if they paraphrased correctly. These complicated characteristics of paraphrasing cause some challenges. In the Japanese context, Iwasaki (1999) discovered four major areas of difficulty: varying behavioral patterns of parts of speech, subject limitation, context-specific paraphrasing and “blank” locating. There seems to be little proof, and data obtained from extensive research dedicated to examining paraphrasing-related concerns in the Indonesian context. Despite an abundance of survey participants, Kusumasondjaja's (2010) survey did not test students' paraphrasing abilities. It appears that paraphrasing is not represented, is described vaguely or is purely regarded as changing the existing source without stating the extent of adjustment.

In the Saudi context, Alaofi (2020) investigated the key problems that Saudi graduate students usually face when summarizing and paraphrasing source texts in EFL. Nine Saudi students attending university degrees in multiple fields were questioned using a qualitative approach. The study's findings revealed that a variety of barriers may exacerbate students' challenges with the skills under examination. These were students' insufficient English proficiency is the first root of complexities in summarizing and paraphrasing original text, followed by issues with students' writing styles and, finally, poor reading comprehension skillsets.

Methodology

As mentioned above, the purpose of this study is to analyze and synthesize findings from the content that is written in the literature review section of 15 unpublished MA studies. These studies were written in the Saudi context and conducted by MA postgraduate students of Al-Baha University. Additionally, to find out the most common types of literature review used by Saudi EFL postgraduate students in Al-Baha University, and to measure the accuracy of citing information related to topics in question, besides finding out the criteria and assess the quality of literature review written by MA researchers, to come out with rich findings that can guide undergraduate students in writing and reviewing knowledge related to their theses and research papers. Additionally, it can help postgraduates and other academic researchers to build a tidy content of literature and coherent procedures for research writing. Thus, this research is done qualitatively using content analysis taking into account the discipline, type of literature review, and contribution to see how successfully these researchers attract readers' attention and satisfy their needs, and in the long run, increase the quality of research and to develop better and more accurate hypotheses and questions.

To measure the research questions, 15 MA dissertations were selected randomly and carefully analyzed accordingly. The analysis of these 15 studies focused mainly on finding out the common types of literature review used by Saudi EFL students in Al-Baha University, and finding the accuracy of citing information, besides assessing the quality of the literature review of the selected MA research. Synder's (2019) model for assessing the quality of literature review is used as a criterion to analyze these MA studies. All are written in the field of English Language Teaching (ELT) settings. Therefore, it will be a potential step in making theoretical and practical contributions to literature review as a method to clarify what a literature review is, how it can be used and what criteria should be used to evaluate its quality. Thus, in this paper, the contribution differentiates between several types of literature review methodologies such as systematic, semi-systematic, and traditional/integrative approaches and how the procedures and the quality were shown (see Appendix ). Besides, presenting real practices that may be met when reviewing literature in EFL research. Additionally, it provides context and guidance to students and academics to use the literature review as a method to synthesize their research in question.

As in Appendix , the criteria used contained four phases: (1) design (includes 6 dimensions); (2) conduct (includes 5 dimensions); (3) data abstraction and analysis (includes 5 dimensions); and (4) structuring and writing the review (includes 5 dimensions). To show that the criterion has been met, the researcher used the symbol (√) as an indication system or vice versa (×) if it was not. The 15 kinds of research were coded using numbers (i.e. each research was given a number from 1 to 15). Then each research was checked according to the dimension of each criterion of each quality. These 15 unpublished MA studies were collected from the College of Arts and Humanities in Al Aqiq main campus, where the postgraduate dissertations were archived, and these studies were conducted during the period from 2013 to 2018. The reason for not selecting newer studies after 2018 is that this paid master's program has been discontinued and has resumed in mid-2021. To ensure the quality of the assessment and the analysis according to Synder's standard, the researcher got help from jury members of three PhD holders (voluntarily) who work in the Department of English at the College of Science and Arts in Qilwah. They had more than ten years of experience in the field of teaching and scientific research. The research took place in a round-held table for a number of meetings and asked them to review and evaluate the MA research according to Synder's criteria. The evaluation continued for three months, and each phase and its dimensions were discussed in separate sessions. The evaluation and discussion took place during the first term of the academic year 2021. Step by step the researcher continuously discussed with the jury members their evaluation (see Appendix ).

The analysis section was divided into two parts. The first part displayed the data gathered to measure the first and the second questions, whereas the second part displayed the third question.

Discovering common types of literature review and evaluating the accuracy of citing information

Part 1 : The main types of literature review (traditional or narrative, systematic, meta-analysis and meta-synthesis) were scrutinized and analyzed in light of their qualities and procedures. In this paper, three types are chosen to be judged accordingly. They are systematic, semi-systematic and traditional/integrative approaches. As mentioned above, the 15 MA projects were handed over to the reviewers (the researcher's colleagues). After long and regular sessions, they concluded their results to the researcher. They revealed that studies 1, 10 and 15 showed a masterpiece reflection of the systematic review approach. In this sense, these studies synthesized and compared evidence between the two studies. Another example is that these studies in the introduction section produced a clear and rationale connection between the topic and literature written in the same field of the study. These studies also showed that the information provided is reliable and based on proven facts. Additionally, the information is verified against other reliable sources. To be more realistic, we must evaluate all sources before deciding whether to incorporate what was found into the literature review ( Synder, 2019 ). Moreover, resources need to be evaluated to make sure that they contain information, which is valuable and pertinent, in this point, this study is consistent with what was found by other researchers ( Liberati et al. , 2009 ; Tranfield et al. , 2003 ; Wong et al. , 2013 ; Synder, 2019 ). These studies presented a rich literature that is displayed in various types of periodicals that include scholarly journals of high impact factors and intensive readability.

Generally, studies (1, 3, 4, 6, 8, 10, 11, 12, 13, 14 and 15) used systematic reviews to answer their highly structured and specific research questions. They undertook a more rigorous approach in reviewing the literature they presented in their research. In contrast, a traditional or narrative literature review usually adopts a critical approach in a way that analyzes and summarizes to address intensive information to shed light on new ideas, bridge gaps or/and cover weaknesses of previous research, studies endeavored a very high and accurate criterion of evaluating literature review Ryan et al. (2007) . On the other hand, studies (2, 5, 7 and 9) used both semi-systematic and integrative/traditional literature reviews. This clearly showed that the research questions were broad. On the other hand, in the introduction section, these studies used a semi-systematic literature review. For accuracy purposes, these studies presented a piece of reliable information. All the information displayed in these studies was error-free. Additionally, it is easy to say that the information shown was based on proven facts and can be verified against other reliable sources. All that cited in these studies in the literature review section was taken from famous and well-known periodicals. They can be completely described as facts shown without any bias. When looking back to what the researchers presented, it is easy to see that information presented was currently published to show the currency matter of the researchers' topics. The coverage of information has met in-depth the information needed to build up a literature review process. Accordingly, the researchers reviewed rich and accurate literature written about the focus topics to rationalize their objectives in conducting their research. All the information shown by researchers was presented without any bias. Thus, each study presented more than four references to show the accurateness of the literature. Additionally, the information presented is highly met and covered the needed information, and provided a basic and in-depth coverage. To meet the aims of systematic review (as in Dundar and Fleeman, 2017 ), to some extent, these studies provided a complete list of all possible published and unpublished studies relating to the researcher's subject matter.

To deal with the accuracy of citing information, in studies (2, 3, 4, 5, 9, 10, 11, 12, 14 and 15) one can find that, from the beginning, in the introduction section, these studies started citing from very recently published researches. Most interestingly, the researchers used the paraphrasing method to cite information related to the researchers' topic. However, they did not paraphrase appropriately. These studies used a paraphrasing method to make the information cited more reliable, error-free, based on proven facts and can be verified against other reliable sources. In this sense, these studies presented information that can be more accurate. But unexpectedly, those who used the paraphrasing method lacked professionality in treating the original text and formulating it using their own words (i.e. there is an apparent weakness in meaning between the original source and the paraphrased text). Again, the studies showed that researchers intended the purpose of the information in a precise way initiating that in the introduction. The studies also presented facts that were proven by famous writers.

Assessing the quality of a literature review

Part 2: As empirical research, literature reviews need assessment and evaluation ( Palmatier et al. , 2018 ). The literature review quality must have both depth and rigor to determine a suitable strategy for choosing topics and apprehending data and insights and to recite previous studies slightly. The quality of the literature review needs to be replicable to make the reader easily replicate the topic and reaches similar findings. Additionally, they must be useful for scholars and practitioners. Normally, the evaluation of different types of literature reviews is considered to be challenging. However, some guidelines could be used as a starting point to help researchers in evaluating literature reviews, to examine and to assess the review criteria for rigor and depth. To assess the literature review quality related to MA studies (the 15 selected samples) in question, Snyder (2019 , p. 338) suggested some guidelines as seen in Appendix .

Therefore, to find out a suitable step-by-step approach that can guide students and academics in undertaking a valid, comprehensive and helpful literature review, appropriate literature reviews have been gathered for this inquiry to investigate the criteria and quality of literature presented by selected MA studies (see Appendix ). Depending on the purpose of the topic, various literature studies may be highly useful to suggest which strategy may suit the analysis and synthesis stages that greatly help in the selection and writing of the literature review on EFL context, mainly Saudi context. Thus, the selected reviews were scrutinized and analyzed considering their qualities and procedures. In this paper, only 15 MA studies were chosen to be measured accordingly.

As in Appendix , the quality of these projects was checked and graded by the reviewers (the researchers' colleagues). Looking at the reviewers' evaluation of these dissertations, one can easily find that only one out of the 15 showed complete performance and was valuable in all criteria. Meanwhile, the others showed strength in the first and second dimensions of the design criteria. However, their performance in the other parameters deteriorated greatly. In total, seven out of them performed moderately in design criteria (i.e. they achieved in dimensions, 1, 2 and 6, whereas they failed in the other 3, 4 and 5); as the other seven researchers performed in four dimensions moderately. Concerning the conduct criteria, they did very well. Therefore, ten out of the fifteen researchers fulfilled perfectly in all dimensions, however, only five performed somehow moderately in only four out of the five dimensions in the conduct criteria. Additionally, seven out of the fifteen achieved in all dimensions in data abstraction and analysis, whereas three contented in only four dimensions, meanwhile other three of them fulfilled only three, while the other two achieved two dimensions. Although researchers did very well in design, conduct, and data abstraction and analysis criterion, they seemed very weak in structuring and writing the review. They only achieved in the fourth and fifth dimensions of this criteria. However, they got zero achievements in the first dimension. Additionally, only six out of the fifteen researchers fulfilled the third dimension, whereas only five achieved the second one.

Findings and discussion

As mentioned above, the purpose of this study is to find out the common types of literature review used by Saudi EFL postgraduate students in Al-Baha University; and to find out the accuracy of citing information related to the topics in question; as well as to assess the quality of the literature review written by selected researchers. From the analysis, it was found that most researchers (11 out of 15) used a systematic review of the literature. Systematic reviews are the thorough and openly transparent type of literature review. Moreover, the most reliable and comprehensive statement about what works is that systematic reviews embark on identification, synthesis and assessment of the available proof, or qualitative and/or quantitative, as a way of generating a well-researched, and empirically derived answer to a specified research question (Petrosino et al. , cited in van der Knaap, 2008 ). The analysis also showed that most researchers utilized paraphrasing in their citing information. Even though it eases work for the researcher, paraphrasing may poorly present information if not used well. As advised, it is better to understand the readings and put them in your own words to preserve the accuracy of the information. Thus, understanding information and then properly paraphrasing will make the work look more original and refined. In this study, the researchers in many parts of the research failed to do an accurate performance in paraphrasing (i.e. there is an apparent weakness in meaning between the original source and the paraphrased text). This demonstrated that there was no accuracy in the paraphrasing used to cite information on the topics in question.

Regarding the quality of the literature review written by selected researchers, the data were gathered using a checklist by the evaluators who voluntarily distributed it into the inquiry to help the researcher to rate the performance of the 15 MA students in their dissertations. Generally, the results showed that students (the MA researchers) were keen on the conduct phase and then to some extent on data abstraction and analysis. Therefore, they know how to conduct their research, especially they have proper measures to ensure quality data abstraction. Moreover, chose data analysis techniques appropriately concerning the overall research questions and the data abstracted. Thus, they accurately search the process for types of reviews, and they did the inclusion and exclusion processes of articles transparent which makes their sample appropriate and in concordance with the overall purpose of the review. Additionally, in the design, concerning the relationship to the overall research field, their literature review was needed, and it makes a substantial, practical and theoretical contribution; the motivation, the purpose and the research questions were clearly stated and motivated; the methodology and the search strategy were clearly and transparently described. On the other hand, they were weak in phase 1 (design), item 3 “Does the review account for the previous literature review and other relevant literature ?”, and they did not clearly state the approaches for the literature review. Finally, the study found that they showed a weak achievement in structuring and writing the review, especially they did not organize articles coherently about the overall approach and research question, and the overall method of conducting the literature review was not sufficiently described, thus their studies could not be replicated.

Therefore, as shown in the purpose of this research, the review of intellectual production is most often the introduction to various theses or peer-review research articles, before presenting the methods and results, and its use is common in most academic research. Thus, the literature review represents one of the important parts of the scientific research plan ( Baumeister and Leary, 1997 ; Torraco, 2005 ). It is the second part that is related to the theoretical framework of the presented research methodology. Meanwhile, it is directly and closely related to the topic. Additionally, it represents an information-rich ground for those who have the desire to know all aspects of the problem or hypothesis in question. It consumes time and requires strong analytical skills from the researchers to make a great contribution successfully as mentioned by other scholars ( Boyd and Solarino, 2016 ; Mazumdar et al. , 2005 , pp. 84–102; Rodell et al ., 2016 ). As in the study questions, and to rationalize the topic, the findings concluded in this paper showed that the analysis and criticism of the literature review may require personal experiences, and others depend on the methodological foundations. The analysis and the criticism should include various dimensions (content, methodology, the sample, reliability and results). This was evident in the performance of these students in analyzing, criticizing and citing the previous studies they refer to. Thus, a researcher should have appropriate insight and wisdom to comment on previous studies and critique them constructively through compelling scientific evidence as well as to be objective and distant from any internal ideologies or personal bias. Therefore, some ideas and techniques that contribute to the process of editing, analyzing and criticizing literature review must be known by researchers ( MacInnis, 2011 ). Additionally, more attention should be given to structuring and writing the review mainly the organization of the review in relation to the overall approach and research questions.

Implications

The study came up with some implications that can help researchers in conducting their studies skillfully. These implications were drawn from the study's findings which may be very important for practice or conducting a literature review.

First: How to criticize the literature?

When looking at the literature review, one should focus on five main points that a study can follow. They are (1) content, (2) methodology, (3) the study sample, (4) credibility and (5) results. Content criticism: in this case, the researcher must express his/her point of view that the content of the previous studies does not include the technical framework that must be followed, and in that case, the study loses the advantage of comprehensiveness and moves away from objectivity in the way it is refuted.

Criticism related to methodology

Here, the researcher must clarify the negative and positive points in the scientific method followed in previous studies, and it is not a requirement that the literature might be negative or positive in its entirety. Accordingly, this is subject to the researcher's opinion, which is an expression of his/her point of view, and he/she has to present this according to convincing evidence which varies from one researcher to another.

Criticism related to the study sample

The researcher must mention any deficiencies in the sample under study which may be ineffective in judging previous literature, and it was possible to increase the sample size. To clarify a matter related to the research problem, the sample may not be represented in an appropriate statistical way, etc.

Credibility criticism

The researcher must verify the reliability of previous studies, and the method of ascertaining. This differs according to the methodology followed by the review studies (i.e. there is the descriptive, experimental and historical approach. For example, the historical method is distinguished by its credibility from others, and the researcher must refute that matter and follow the precise criteria in judging that, etc.). To judge the reliability of literature, the researcher must be familiar with all scientific research methods, their advantages and disadvantages, and the research hypotheses and theories that are compatible with those approaches.

Results criticism

The researcher may disagree with the results shown in previous studies. Because there is an error in the method of analyzing and presenting the data, so, the researcher must clarify the comparison between his/her findings and what was presented in other studies and indicate the extent of objectivity in each of them ( Snyder et al ., 2016 ; Verlegh and Steenkamp, 1999 ; Witell et al. , 2016 ). Additionally, the researcher should address only the previous studies related to the research topic, and the link must be clear to the reader, so it makes no sense to refer to previous research or studies that do not touch the research problem from near or far.

Second: How to comment on literature?

Previous studies help clarify the theoretical foundations of the subject of the research to be carried out by the researcher.

They save time and effort for the researcher by choosing the framework for the topic of the research plan.

They are a wake-up call for the researcher when writing a paper by defining a method that would avoid the researcher making mistakes made by previous researchers.

Present the correct methodological approach to the topic of research in general.

They give the researcher an exemplary method to extract recommendations, findings and other proposals related to the research.

Literature helps the researcher in identifying references for his/her research and facilitates the process of writing.

They have an important role in the researcher's comparison process between the research he provides and those studies and sources.

As many EFL MA researchers find it difficult to choose and handle a suitable literature review that approves their writing quality, thus, this study was conducted to find out a suitable step-by-step approach that can help to undertake a valid, comprehensive and helpful literature review. In conclusion, EFL MA researchers need to search for the quality and trustworthiness of their reviews to build a rich and adequate literature review. As found in this paper, it is seen that most MA Saudi researchers favored using the systematic review rather than the integrative type. More or less, they try to avoid comparing the review rather than identifying and synthesizing, as it may seem a more complicated process. Obviously, reviewing any article that could be relevant to the topic is not a simple task; therefore, a different strategy must be developed and used carefully to fulfill the quality of literature review along with the topic in question. More interestingly and generally, the researcher found that a semi-systematic review method often possesses similarities to approaches used in qualitative research ( Dundar and Fleeman, 2017 ), but it can also be combined with a statistical meta-analysis approach. Due to the integrative approach liability to yield a creative collection of data, it is widely used to combine perspectives and insights from previous research. Thus, the integrative approach seems to be the best method that can be used in the field of EFL because its purpose is to compare and combine rather than cover all related topics. Additionally, as the study found that students did not accurately paraphrase/summarize appropriately from other sources, additional sessions impeding paraphrasing procedures and processes will have valuable benefits and will make students better at writing research in the future. Concerning the phases of the quality of conducting research, it is important to ensure the proper measurement that qualifies the quality of data abstraction and analysis techniques that deal with the overall research questions accurately. Furthermore, searching for proper types of reviews, article transparency and the appropriate sample should fit the purpose of the review. Finally, among the broader implications of the study, it is expected that the construction of master's programs (courses path) should be reviewed, and focus should be given to teach students the quality standards of research writing and how to analyze and critique them in a better way.

Approaches to literature reviews

Note(s): *Adopted from Snyder's (2019 , p. 338) model “Guidelines to assess the quality of a literature review”

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Dhaulagiri Journal of Sociology and Anthropology

Thakur P R A S A D Bhatta

Case study research though increasingly popular in social sciences for positivist and intrepretivist research, a kind of confusion is prevalent when it is used ignoring its philosophical position. Arguably, the case study research is considered more appropriate for qualitative research because of its foremost strength ˗ the in-depth study of complex issues. This paper, drawing from the literature, discusses the philosophical position of case study research and argues that qualitative case study research is appropriate for theory building. For theory building, this paper follows the inductive approach guided by qualitative research paradigm and argues that it is not appropriate to assess theory building from the perspective of quantitative research. Very similar to other research methods, it is natural that the case study research has certain challenges; however, most of the challenges and misunderstandings overlap causing difficulty to understand the role of case study research. Hence, this paper aims to contribute to the understandings of the challenges and misunderstandings associated with the theory building from case study research. This paper argues that most of the challenges associated with theory building from case study can be addressed employing appropriate research strategies particularly clear understanding of philosophical stance and selection of appropriate case. The misunderstandings, on the other hand, are arisen due to the differences in the researcher's perspectives particularly positivistic thinking of them rather than the shortcomings inherent in the qualitative case study research design.

Florian Kohlbacher

This paper aims at exploring and discus­ sing the possibilities of applying qualitative content analysis as a (text) interpretation method in case study research. First, case study research as a research strategy within qualitative social research is briefly presented. Then, a basic introduction to (qualitative) content analysis as an interpretation method for qualitative interviews and other data material is given.

Assessment of Qualitative

15th NCVER conference

John Guenther

milton malaya

Lesley Bartlett

casestudies journal

Qualitative case-study research has experienced an upsurge in business management fields of inquiry in the recent past. A methodology is selection, justification and sequential arranging of activities, procedures and tasks in a research project. Research methodology can no longer be confined to a set of universally applicable rules, conventions and traditions. A research paradigm is a set of propositions that explains how the world is perceived. There are three basic paradigms: positivist, interpretive and critical. Qualitative " approaches to research " , " strategies of inquiry " and " varieties of methodologies " classified into five " types " or " traditions " namely; biography, phenomenology, grounded theory, ethnography and case study. The major criticism made of qualitative methods is that they are impressionistic and non-verifiable, post-positivists who reject this charge claiming that qualitative data is auditable and therefore dependable. The less structured qualitative methodologies reject many of the positivists " constructions over what constitutes rigour, favouring instead the flexibility, creativity and otherwise inaccessible insights afforded by alternative routes of inquiry that embrace storytelling, recollection, and dialogue. Case study research is not really a " methodology " or a method, rather an approach to research. Case studies can be ethnographic or not and some scholars identified it as a strategy of social inquiry. It is argued that, case studies are more appropriate to investigate causal relationships prevailing both in the business field as well as in wider society in general.

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  • Published: 08 May 2024

A meta-analysis on global change drivers and the risk of infectious disease

  • Michael B. Mahon   ORCID: orcid.org/0000-0002-9436-2998 1 , 2   na1 ,
  • Alexandra Sack 1 , 3   na1 ,
  • O. Alejandro Aleuy 1 ,
  • Carly Barbera 1 ,
  • Ethan Brown   ORCID: orcid.org/0000-0003-0827-4906 1 ,
  • Heather Buelow   ORCID: orcid.org/0000-0003-3535-4151 1 ,
  • David J. Civitello 4 ,
  • Jeremy M. Cohen   ORCID: orcid.org/0000-0001-9611-9150 5 ,
  • Luz A. de Wit   ORCID: orcid.org/0000-0002-3045-4017 1 ,
  • Meghan Forstchen 1 , 3 ,
  • Fletcher W. Halliday 6 ,
  • Patrick Heffernan 1 ,
  • Sarah A. Knutie 7 ,
  • Alexis Korotasz 1 ,
  • Joanna G. Larson   ORCID: orcid.org/0000-0002-1401-7837 1 ,
  • Samantha L. Rumschlag   ORCID: orcid.org/0000-0003-3125-8402 1 , 2 ,
  • Emily Selland   ORCID: orcid.org/0000-0002-4527-297X 1 , 3 ,
  • Alexander Shepack 1 ,
  • Nitin Vincent   ORCID: orcid.org/0000-0002-8593-1116 1 &
  • Jason R. Rohr   ORCID: orcid.org/0000-0001-8285-4912 1 , 2 , 3   na1  

Nature ( 2024 ) Cite this article

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  • Infectious diseases

Anthropogenic change is contributing to the rise in emerging infectious diseases, which are significantly correlated with socioeconomic, environmental and ecological factors 1 . Studies have shown that infectious disease risk is modified by changes to biodiversity 2 , 3 , 4 , 5 , 6 , climate change 7 , 8 , 9 , 10 , 11 , chemical pollution 12 , 13 , 14 , landscape transformations 15 , 16 , 17 , 18 , 19 , 20 and species introductions 21 . However, it remains unclear which global change drivers most increase disease and under what contexts. Here we amassed a dataset from the literature that contains 2,938 observations of infectious disease responses to global change drivers across 1,497 host–parasite combinations, including plant, animal and human hosts. We found that biodiversity loss, chemical pollution, climate change and introduced species are associated with increases in disease-related end points or harm, whereas urbanization is associated with decreases in disease end points. Natural biodiversity gradients, deforestation and forest fragmentation are comparatively unimportant or idiosyncratic as drivers of disease. Overall, these results are consistent across human and non-human diseases. Nevertheless, context-dependent effects of the global change drivers on disease were found to be common. The findings uncovered by this meta-analysis should help target disease management and surveillance efforts towards global change drivers that increase disease. Specifically, reducing greenhouse gas emissions, managing ecosystem health, and preventing biological invasions and biodiversity loss could help to reduce the burden of plant, animal and human diseases, especially when coupled with improvements to social and economic determinants of health.

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Data availability.

All the data for this Article have been deposited at Zenodo ( https://doi.org/10.5281/zenodo.8169979 ) 52 and GitHub ( https://github.com/mahonmb/GCDofDisease ) 53 .

Code availability

All the code for this Article has been deposited at Zenodo ( https://doi.org/10.5281/zenodo.8169979 ) 52 and GitHub ( https://github.com/mahonmb/GCDofDisease ) 53 . R markdown is provided in Supplementary Data 1 .

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Acknowledgements

We thank C. Mitchell for contributing data on enemy release; L. Albert and B. Shayhorn for assisting with data collection; J. Gurevitch, M. Lajeunesse and G. Stewart for providing comments on an earlier version of this manuscript; and C. Carlson and two anonymous reviewers for improving this paper. This research was supported by grants from the National Science Foundation (DEB-2109293, DEB-2017785, DEB-1518681, IOS-1754868), National Institutes of Health (R01TW010286) and US Department of Agriculture (2021-38420-34065) to J.R.R.; a US Geological Survey Powell grant to J.R.R. and S.L.R.; University of Connecticut Start-up funds to S.A.K.; grants from the National Science Foundation (IOS-1755002) and National Institutes of Health (R01 AI150774) to D.J.C.; and an Ambizione grant (PZ00P3_202027) from the Swiss National Science Foundation to F.W.H. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Author information

These authors contributed equally: Michael B. Mahon, Alexandra Sack, Jason R. Rohr

Authors and Affiliations

Department of Biological Sciences, University of Notre Dame, Notre Dame, IN, USA

Michael B. Mahon, Alexandra Sack, O. Alejandro Aleuy, Carly Barbera, Ethan Brown, Heather Buelow, Luz A. de Wit, Meghan Forstchen, Patrick Heffernan, Alexis Korotasz, Joanna G. Larson, Samantha L. Rumschlag, Emily Selland, Alexander Shepack, Nitin Vincent & Jason R. Rohr

Environmental Change Initiative, University of Notre Dame, Notre Dame, IN, USA

Michael B. Mahon, Samantha L. Rumschlag & Jason R. Rohr

Eck Institute of Global Health, University of Notre Dame, Notre Dame, IN, USA

Alexandra Sack, Meghan Forstchen, Emily Selland & Jason R. Rohr

Department of Biology, Emory University, Atlanta, GA, USA

David J. Civitello

Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, USA

Jeremy M. Cohen

Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR, USA

Fletcher W. Halliday

Department of Ecology and Evolutionary Biology, Institute for Systems Genomics, University of Connecticut, Storrs, CT, USA

Sarah A. Knutie

You can also search for this author in PubMed   Google Scholar

Contributions

J.R.R. conceptualized the study. All of the authors contributed to the methodology. All of the authors contributed to investigation. Visualization was performed by M.B.M. The initial study list and related information were compiled by D.J.C., J.M.C., F.W.H., S.A.K., S.L.R. and J.R.R. Data extraction was performed by M.B.M., A.S., O.A.A., C.B., E.B., H.B., L.A.d.W., M.F., P.H., A.K., J.G.L., E.S., A.S. and N.V. Data were checked for accuracy by M.B.M. and A.S. Analyses were performed by M.B.M. and J.R.R. Funding was acquired by D.J.C., J.R.R., S.A.K. and S.L.R. Project administration was done by J.R.R. J.R.R. supervised the study. J.R.R. and M.B.M. wrote the original draft. All of the authors reviewed and edited the manuscript. J.R.R. and M.B.M. responded to reviewers.

Corresponding author

Correspondence to Jason R. Rohr .

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Competing interests.

The authors declare no competing interests.

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Nature thanks Colin Carlson and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data figures and tables

Extended data fig. 1 prisma flowchart..

The PRISMA flow diagram of the search and selection of studies included in this meta-analysis. Note that 77 studies came from the Halliday et al. 3 database on biodiversity change.

Extended Data Fig. 2 Summary of the number of studies (A-F) and parasite taxa (G-L) in the infectious disease database across ecological contexts.

The contexts are global change driver ( A , G ), parasite taxa ( B , H ), host taxa ( C , I ), experimental venue ( D , J ), study habitat ( E , K ), and human parasite status ( F , L ).

Extended Data Fig. 3 Summary of the number of effect sizes (A-I), studies (J-R), and parasite taxa (S-a) in the infectious disease database for various parasite and host contexts.

Shown are parasite type ( A , J , S ), host thermy ( B , K , T ), vector status ( C , L , U ), vector-borne status ( D , M , V ), parasite transmission ( E , N , W ), free living stages ( F , O , X ), host (e.g. disease, host growth, host survival) or parasite (e.g. parasite abundance, prevalence, fecundity) endpoint ( G , P , Y ), micro- vs macroparasite ( H , Q , Z ), and zoonotic status ( I , R , a ).

Extended Data Fig. 4 The effects of global change drivers and subsequent subcategories on disease responses with Log Response Ratio instead of Hedge’s g.

Here, Log Response Ratio shows similar trends to that of Hedge’s g presented in the main text. The displayed points represent the mean predicted values (with 95% confidence intervals) from a meta-analytical model with separate random intercepts for study. Points that do not share letters are significantly different from one another (p < 0.05) based on a two-sided Tukey’s posthoc multiple comparison test with adjustment for multiple comparisons. See Table S 3 for pairwise comparison results. Effects of the five common global change drivers ( A ) have the same directionality, similar magnitude, and significance as those presented in Fig. 2 . Global change driver effects are significant when confidence intervals do not overlap with zero and explicitly tested with two-tailed t-test (indicated by asterisks; t 80.62  = 2.16, p = 0.034 for CP; t 71.42  = 2.10, p = 0.039 for CC; t 131.79  = −3.52, p < 0.001 for HLC; t 61.9  = 2.10, p = 0.040 for IS). The subcategories ( B ) also show similar patterns as those presented in Fig. 3 . Subcategories are significant when confidence intervals do not overlap with zero and were explicitly tested with two-tailed one sample t-test (t 30.52  = 2.17, p = 0.038 for CO 2 ; t 40.03  = 4.64, p < 0.001 for Enemy Release; t 47.45  = 2.18, p = 0.034 for Mean Temperature; t 110.81  = −4.05, p < 0.001 for Urbanization); all other subcategories have p > 0.20. Note that effect size and study numbers are lower here than in Figs. 3 and 4 , because log response ratios cannot be calculated for studies that provide coefficients (e.g., odds ratio) rather than raw data; as such, all observations within BC did not have associated RR values. Despite strong differences in sample size, patterns are consistent across effect sizes, and therefore, we can be confident that the results presented in the main text are not biased because of effect size selection.

Extended Data Fig. 5 Average standard errors of the effect sizes (A) and sample sizes per effect size (B) for each of the five global change drivers.

The displayed points represent the mean predicted values (with 95% confidence intervals) from the generalized linear mixed effects models with separate random intercepts for study (Gaussian distribution for standard error model, A ; Poisson distribution for sample size model, B ). Points that do not share letters are significantly different from one another (p < 0.05) based on a two-sided Tukey’s posthoc multiple comparison test with adjustment for multiple comparisons. Sample sizes (number of studies, n, and effect sizes, k) for each driver are as follows: n = 77, k = 392 for BC; n = 124, k = 364 for CP; n = 202, k = 380 for CC; n = 517, k = 1449 for HLC; n = 96, k = 355 for IS.

Extended Data Fig. 6 Forest plots of effect sizes, associated variances, and relative weights (A), Funnel plots (B), and Egger’s Test plots (C) for each of the five global change drivers and leave-one-out publication bias analyses (D).

In panel A , points are the individual effect sizes (Hedge’s G), error bars are standard errors of the effect size, and size of the points is the relative weight of the observation in the model, with larger points representing observations with higher weight in the model. Sample sizes are provided for each effect size in the meta-analytic database. Effect sizes were plotted in a random order. Egger’s tests indicated significant asymmetries (p < 0.05) in Biodiversity Change (worst asymmetry – likely not bias, just real effect of positive relationship between diversity and disease), Climate Change – (weak asymmetry, again likely not bias, climate change generally increases disease), and Introduced Species (relatively weak asymmetry – unclear whether this is a bias, may be driven by some outliers). No significant asymmetries (p > 0.05) were found in Chemical Pollution and Habitat Loss/Change, suggesting negligible publication bias in reported disease responses across these global change drivers ( B , C ). Egger’s test included publication year as moderator but found no significant relationship between Hedge’s g and publication year (p > 0.05) implying no temporal bias in effect size magnitude or direction. In panel D , the horizontal red lines denote the grand mean and SE of Hedge’s g and (g = 0.1009, SE = 0.0338). Grey points and error bars indicate the Hedge’s g and SEs, respectively, using the leave-one-out method (grand mean is recalculated after a given study is removed from dataset). While the removal of certain studies resulted in values that differed from the grand mean, all estimated Hedge’s g values fell well within the standard error of the grand mean. This sensitivity analysis indicates that our results were robust to the iterative exclusion of individual studies.

Extended Data Fig. 7 The effects of habitat loss/change on disease depend on parasite taxa and land use conversion contexts.

A) Enemy type influences the magnitude of the effect of urbanization on disease: helminths, protists, and arthropods were all negatively associated with urbanization, whereas viruses were non-significantly positively associated with urbanization. B) Reference (control) land use type influences the magnitude of the effect of urbanization on disease: disease was reduced in urban settings compared to rural and peri-urban settings, whereas there were no differences in disease along urbanization gradients or between urban and natural settings. C) The effect of forest fragmentation depends on whether a large/continuous habitat patch is compared to a small patch or whether disease it is measured along an increasing fragmentation gradient (Z = −2.828, p = 0.005). Conversely, the effect of deforestation on disease does not depend on whether the habitat has been destroyed and allowed to regrow (e.g., clearcutting, second growth forests, etc.) or whether it has been replaced with agriculture (e.g., row crop, agroforestry, livestock grazing; Z = 1.809, p = 0.0705). The displayed points represent the mean predicted values (with 95% confidence intervals) from a metafor model where the response variable was a Hedge’s g (representing the effect on an infectious disease endpoint relative to control), study was treated as a random effect, and the independent variables included enemy type (A), reference land use type (B), or land use conversion type (C). Data for (A) and (B) were only those studies that were within the “urbanization” subcategory; data for (C) were only those studies that were within the “deforestation” and “forest fragmentation” subcategories. Sample sizes (number of studies, n, and effect sizes, k) in (A) for each enemy are n = 48, k = 98 for Virus; n = 193, k = 343 for Protist; n = 159, k = 490 for Helminth; n = 10, k = 24 for Fungi; n = 103, k = 223 for Bacteria; and n = 30, k = 73 for Arthropod. Sample sizes in (B) for each reference land use type are n = 391, k = 1073 for Rural; n = 29, k = 74 for Peri-urban; n = 33, k = 83 for Natural; and n = 24, k = 58 for Urban Gradient. Sample sizes in (C) for each land use conversion type are n = 7, k = 47 for Continuous Gradient; n = 16, k = 44 for High/Low Fragmentation; n = 11, k = 27 for Clearcut/Regrowth; and n = 21, k = 43 for Agriculture.

Extended Data Fig. 8 The effects of common global change drivers on mean infectious disease responses in the literature depends on whether the endpoint is the host or parasite; whether the parasite is a vector, is vector-borne, has a complex or direct life cycle, or is a macroparasite; whether the host is an ectotherm or endotherm; or the venue and habitat in which the study was conducted.

A ) Parasite endpoints. B ) Vector-borne status. C ) Parasite transmission route. D ) Parasite size. E ) Venue. F ) Habitat. G ) Host thermy. H ) Parasite type (ecto- or endoparasite). See Table S 2 for number of studies and effect sizes across ecological contexts and global change drivers. See Table S 3 for pairwise comparison results. The displayed points represent the mean predicted values (with 95% confidence intervals) from a metafor model where the response variable was a Hedge’s g (representing the effect on an infectious disease endpoint relative to control), study was treated as a random effect, and the independent variables included the main effects and an interaction between global change driver and the focal independent variable (whether the endpoint measured was a host or parasite, whether the parasite is vector-borne, has a complex or direct life cycle, is a macroparasite, whether the study was conducted in the field or lab, habitat, the host is ectothermic, or the parasite is an ectoparasite).

Extended Data Fig. 9 The effects of five common global change drivers on mean infectious disease responses in the literature only occasionally depend on location, host taxon, and parasite taxon.

A ) Continent in which the field study occurred. Lack of replication in chemical pollution precluded us from including South America, Australia, and Africa in this analysis. B ) Host taxa. C ) Enemy taxa. See Table S 2 for number of studies and effect sizes across ecological contexts and global change drivers. See Table S 3 for pairwise comparison results. The displayed points represent the mean predicted values (with 95% confidence intervals) from a metafor model where the response variable was a Hedge’s g (representing the effect on an infectious disease endpoint relative to control), study was treated as a random effect, and the independent variables included the main effects and an interaction between global change driver and continent, host taxon, and enemy taxon.

Extended Data Fig. 10 The effects of human vs. non-human endpoints for the zoonotic disease subset of database and wild vs. domesticated animal endpoints for the non-human animal subset of database are consistent across global change drivers.

(A) Zoonotic disease responses measured on human hosts responded less positively (closer to zero when positive, further from zero when negative) than those measured on non-human (animal) hosts (Z = 2.306, p = 0.021). Note, IS studies were removed because of missing cells. (B) Disease responses measured on domestic animal hosts responded less positively (closer to zero when positive, further from zero when negative) than those measured on wild animal hosts (Z = 2.636, p = 0.008). These results were consistent across global change drivers (i.e., no significant interaction between endpoint and global change driver). As many of the global change drivers increase zoonotic parasites in non-human animals and all parasites in wild animals, this may suggest that anthropogenic change might increase the occurrence of parasite spillover from animals to humans and thus also pandemic risk. The displayed points represent the mean predicted values (with 95% confidence intervals) from a metafor model where the response variable was a Hedge’s g (representing the effect on an infectious disease endpoint relative to control), study was treated as a random effect, and the independent variable of global change driver and human/non-human hosts. Data for (A) were only those diseases that are considered “zoonotic”; data for (B) were only those endpoints that were measured on non-human animals. Sample sizes in (A) for zoonotic disease measured on human endpoints across global change drivers are n = 3, k = 17 for BC; n = 2, k = 6 for CP; n = 25, k = 39 for CC; and n = 175, k = 331 for HLC. Sample sizes in (A) for zoonotic disease measured on non-human endpoints across global change drivers are n = 25, k = 52 for BC; n = 2, k = 3 for CP; n = 18, k = 29 for CC; n = 126, k = 289 for HLC. Sample sizes in (B) for wild animal endpoints across global change drivers are n = 28, k = 69 for BC; n = 21, k = 44 for CP; n = 50, k = 89 for CC; n = 121, k = 360 for HLC; and n = 29, k = 45 for IS. Sample sizes in (B) for domesticated animal endpoints across global change drivers are n = 2, k = 4 for BC; n = 4, k = 11 for CP; n = 7, k = 20 for CC; n = 78, k = 197 for HLC; and n = 1, k = 2 for IS.

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Machine learning models for abstract screening task - A systematic literature review application for health economics and outcome research

  • Jingcheng Du 1 ,
  • Ekin Soysal 1 , 3 ,
  • Dong Wang 2 ,
  • Long He 1 ,
  • Bin Lin 1 ,
  • Jingqi Wang 1 ,
  • Frank J. Manion 1 ,
  • Yeran Li 2 ,
  • Elise Wu 2 &
  • Lixia Yao 2  

BMC Medical Research Methodology volume  24 , Article number:  108 ( 2024 ) Cite this article

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Systematic literature reviews (SLRs) are critical for life-science research. However, the manual selection and retrieval of relevant publications can be a time-consuming process. This study aims to (1) develop two disease-specific annotated corpora, one for human papillomavirus (HPV) associated diseases and the other for pneumococcal-associated pediatric diseases (PAPD), and (2) optimize machine- and deep-learning models to facilitate automation of the SLR abstract screening.

This study constructed two disease-specific SLR screening corpora for HPV and PAPD, which contained citation metadata and corresponding abstracts. Performance was evaluated using precision, recall, accuracy, and F1-score of multiple combinations of machine- and deep-learning algorithms and features such as keywords and MeSH terms.

Results and conclusions

The HPV corpus contained 1697 entries, with 538 relevant and 1159 irrelevant articles. The PAPD corpus included 2865 entries, with 711 relevant and 2154 irrelevant articles. Adding additional features beyond title and abstract improved the performance (measured in Accuracy) of machine learning models by 3% for HPV corpus and 2% for PAPD corpus. Transformer-based deep learning models that consistently outperformed conventional machine learning algorithms, highlighting the strength of domain-specific pre-trained language models for SLR abstract screening. This study provides a foundation for the development of more intelligent SLR systems.

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Introduction

Systematic literature reviews (SLRs) are an essential tool in many areas of health sciences, enabling researchers to understand the current knowledge around a topic and identify future research and development directions. In the field of health economics and outcomes research (HEOR), SLRs play a crucial role in synthesizing evidence around unmet medical needs, comparing treatment options, and preparing the design and execution of future real-world evidence studies. SLRs provide a comprehensive and transparent analysis of available evidence, allowing researchers to make informed decisions and improve patient outcomes.

Conducting a SLR involves synthesizing high-quality evidence from biomedical literature in a transparent and reproducible manner, and seeks to include all available evidence on a given research question, and provides some assessment regarding quality of the evidence [ 1 , 2 ]. To conduct an SLR one or more bibliographic databases are queried based on a given research question and a corresponding set of inclusion and exclusion criteria, resulting in the selection of a relevant set of abstracts. The abstracts are reviewed, further refining the set of articles that are used to address the research question. Finally, appropriate data is systematically extracted from the articles and summarized [ 1 , 3 ].

The current approach to conducting a SLR is through manual review, with data collection, and summary done by domain experts against pre-specified eligibility criteria. This is time-consuming, labor-intensive, expensive, and non-scalable given the current more-than linear growth of the biomedical literature [ 4 ]. Michelson and Reuter estimate that each SLR costs approximately $141,194.80 and that on average major pharmaceutical companies conduct 23.36 SLRs, and major academic centers 177.32 SLRs per year, though the cost may vary based on the scope of different reviews [ 4 ]. Clearly automated methods are needed, both from a cost/time savings perspective, and for the ability to effectively scan and identify increasing amounts of literature, thereby allowing the domain experts to spend more time analyzing the data and gleaning the insights.

One major task of SLR project that involves large amounts of manual effort, is the abstract screening task. For this task, selection criteria are developed and the citation metadata and abstract for articles tentatively meeting these criteria are retrieved from one or more bibliographic databases (e.g., PubMed). The abstracts are then examined in more detail to determine if they are relevant to the research question(s) and should be included or excluded from further consideration. Consequently, the task of determining whether articles are relevant or not based on their titles, abstracts and metadata can be treated as a binary classification task, which can be addressed by natural language processing (NLP). NLP involves recognizing entities and relationships expressed in text and leverages machine-learning (ML) and deep-learning (DL) algorithms together with computational semantics to extract information. The past decade has witnessed significant advances in these areas for biomedical literature mining. A comprehensive review on how NLP techniques in particular are being applied for automatic mining and knowledge extraction from biomedical literature can be found in Zhao et al. [ 5 ].

Materials and methods

The aims of this study were to: (1) identify and develop two disease-specific corpora, one for human papillomavirus (HPV) associated diseases and the other for pneumococcal-associated pediatric diseases suitable for training the ML and DL models underlying the necessary NLP functions; (2) investigate and optimize the performance of the ML and DL models using different sets of features (e.g., keywords, Medical Subject Heading (MeSH) terms [ 6 ]) to facilitate automation of the abstract screening tasks necessary to construct a SLR. Note that these screening corpora can be used as training data to build different NLP models. We intend to freely share these two corpora with the entire scientific community so they can serve as benchmark corpora for future NLP model development in this area.

SLR corpora preparation

Two completed disease-specific SLR studies by Merck & Co., Inc., Rahway, NJ, USA were used as the basis to construct corpora for abstract-level screening. The two SLR studies were both relevant to health economics and outcome research, including one for human papillomavirus (HPV) associated diseases (referred to as the HPV corpus), and one for pneumococcal-associated pediatric diseases (which we refer to as the PAPD corpus). Both of the original SLR studies contained literature from PubMed/MEDLINE and EMBASE. Since we intended for the screening corpora to be released to the community, we only kept citations found from PubMed/MEDLINE in the finalized corpora. Because the original SLR studies did not contain the PubMed ID (PMID) for each article, we matched each article’s citation information (if available) against PubMed and then collected meta-data such as authors, journals, keywords, MeSH terms, publication types, etc., using PubMed Entrez Programming Utilities (E-utilities) Application Programming Interface (API). The detailed description of the two corpora can be seen in Table  1 . Both of the resulting corpora are publicly available at [ https://github.com/Merck/NLP-SLR-corpora ].

Machine learning algorithms

Although deep learning algorithms have demonstrated superior performance on many NLP tasks, conventional machine learning algorithms have certain advantages, such as low computation costs and faster training and prediction speed.

We evaluated four traditional ML-based document classification algorithms, XGBoost [ 7 ], Support Vector Machines (SVM) [ 8 ], Logistic regression (LR) [ 9 ], and Random Forest [ 10 ] on the binary inclusion/exclusion classification task for abstract screening. Salient characteristics of these models are as follows:

XGBoost: Short for “eXtreme Gradient Boosting”, XGBoost is a boosting-based ensemble of algorithms that turn weak learners into strong learners by focusing on where the individual models went wrong. In Gradient Boosting, individual weak models train upon the difference between the prediction and the actual results [ 7 ]. We set max_depth at 3, n_estimators at 150 and learning rate at 0.7.

Support vector machine (SVM): SVM is one of the most robust prediction methods based on statistical learning frameworks. It aims to find a hyperplane in an N-dimensional space (where N = the number of features) that distinctly classifies the data points [ 8 ]. We set C at 100, gamma at 0.005 and kernel as radial basis function.

Logistic regression (LR): LR is a classic statistical model that in its basic form uses a logistic function to model a binary dependent variable [ 9 ]. We set C at 5 and penalty as l2.

Random forest (RF): RF is a machine learning technique that utilizes ensemble learning to combine many decision trees classifiers through bagging or bootstrap aggregating [ 10 ]. We set n_estimators at 100 and max_depth at 14.

These four algorithms were trained for both the HPV screening task and the PAPD screening task using the corresponding training corpus.

For each of the four algorithms, we examined performance using (1) only the baseline feature criteria (title and abstract of each article), and (2) with five additional meta-data features (MeSH, Authors, Keywords, Journal, Publication types.) retrieved from each article using the PubMed E-utilities API. Conventionally, title and abstract are the first information a human reviewer would depend on when making a judgment for inclusion or exclusion of an article. Consequently, we used title and abstract as the baseline features to classify whether an abstract should be included at the abstract screening stage. We further evaluated the performance with additional features that can be retrieved by PubMed E-utilities API, including MeSH terms, authors, journal, keywords and publication type. For baseline evaluation, we concatenated the titles and abstracts and extracted the TF-IDF (term frequency-inverse document frequency) vector for the corpus. TF-IDF evaluates how relevant a word is to a document in a collection of documents. For additional features, we extracted TF-IDF vector using each feature respectively and then concatenated the extracted vectors with title and abstract vector. XGBoost was selected for the feature evaluation process, due to its relatively quick computational running time and robust performance.

Deep learning algorithms

Conventional ML methods rely heavily on manually designed features and suffer from the challenges of data sparsity and poor transportability when applied to new use cases. Deep learning (DL) is a set of machine learning algorithms based on deep neural networks that has advanced performance of text classification along with many other NLP tasks. Transformer-based deep learning models, such as BERT (Bidirectional encoder representations from transformers), have achieved state-of-the-art performance in many NLP tasks [ 11 ]. A Transformer is an emerging architecture of deep learning models designed to handle sequential input data such as natural language by adopting the mechanisms of attention to differentially weigh the significance of each part of the input data [ 12 ]. The BERT model and its variants (which use Transformer as a basic unit) leverage the power of transfer learning by first pre-training the models over 100’s of millions of parameters using large volumes of unlabeled textual data. The resulting model is then fine-tuned for a particular downstream NLP application, such as text classification, named entity recognition, relation extraction, etc. The following three BERT models were evaluated against both the HPV and Pediatric pneumococcal corpus using two sets of features (title and abstract versus adding all additional features into the text). For all BERT models, we used Adam optimizer with weight decay. We set learning rate at 1e-5, batch size at 8 and number of epochs at 20.

BERT base: this is the original BERT model released by Google. The BERT base model was pre-trained on textual data in the general domain, i.e., BooksCorpus (800 M words) and English Wikipedia (2500 M words) [ 11 ].

BioBERT base: as the biomedical language is different from general language, the BERT models trained on general textual data may not work well on biomedical NLP tasks. BioBERT was further pre-trained (based on original BERT models) in the large-scale biomedical corpora, including PubMed abstracts (4.5B words) and PubMed Central Full-text articles (13.5B words) [ 13 ].

PubMedBERT: PubMedBERT was pre-trained from scratch using abstracts from PubMed. This model has achieved state-of-the-art performance on several biomedical NLP tasks on Biomedical Language Understanding and Reasoning Benchmark [ 14 ].

Text pre-processing and libraries that were used

We have removed special characters and common English words as a part of text pre-processing. Default tokenizer from scikit-learn was adopted for tokenization. Scikit-learn was also used for TF-IDF feature extraction and machine learning algorithms implementation. Transformers libraries from Hugging Face were used for deep learning algorithms implementation.

Evaluation datasets were constructed from the HPV and Pediatric pneumococcal corpora and were split into training, validation and testing sets with a ratio of 8:1:1 for the two evaluation tasks: (1) ML algorithms performance assessment; and (2) DL algorithms performance assessment. Models were fitted on the training sets, and model hyperparameters were optimized on the validation sets and the performance were evaluated on the testing sets. The following major metrics are expressed by the noted calculations:

Where True positive is an outcome where the model correctly predicts the positive (e.g., “included” in our tasks) class. Similarly, a True negative is an outcome where the model correctly predicts the negative class (e.g., “excluded” in our tasks). False positive is an outcome where the model incorrectly predicts the positive class, and a False negative is an outcome where the model incorrectly predicts the negative class. We have repeated all experiments five times and reported the mean scores with standard deviation.

Table  2 shows the baseline comparison using different feature combinations for the SLR text classification tasks using XGBoost. As noted, adding additional features in addition to title and abstract was effective in further improving the classification accuracy. Specifically, using all available features for the HPV classification increased accuracy by ? ∼  3% and F1 score by ? ∼  3%; using all available features for Pediatric pneumococcal classification increased accuracy by ? ∼  2% and F1 score by ? ∼  4%. As observed, adding additional features provided a stronger boost in precision, which contributed to the overall performance improvement.

The comparison of the article inclusion/exclusion classification task for four machine learning algorithms with all features is shown in Table  3 . XGBoost achieved the highest accuracy and F-1 scores in both tasks. Table  4 shows the comparison between XGBoost and deep learning algorithms on the classification tasks for each disease. Both XGBoost and deep learning models consistently have achieved higher accuracy scores when using all features as input. Among all models, BioBERT has achieved the highest accuracy at 0.88, compared with XGBoost at 0.86. XGBoost has the highest F1 score at 0.8 and the highest recall score at 0.9 for inclusion prediction.

Discussions and conclusions

Abstract screening is a crucial step in conducting a systematic literature review (SLR), as it helps to identify relevant citations and reduces the effort required for full-text screening and data element extraction. However, screening thousands of abstracts can be a time-consuming and burdensome task for scientific reviewers. In this study, we systematically investigated the use of various machine learning and deep learning algorithms, using different sets of features, to automate abstract screening tasks. We evaluated these algorithms using disease-focused SLR corpora, including one for human papillomavirus (HPV) associated diseases and another for pneumococcal-associated pediatric diseases (PADA). The publicly available corpora used in this study can be used by the scientific community for advanced algorithm development and evaluation. Our findings suggest that machine learning and deep learning algorithms can effectively automate abstract screening tasks, saving valuable time and effort in the SLR process.

Although machine learning and deep learning algorithms trained on the two SLR corpora showed some variations in performance, there were also some consistencies. Firstly, adding additional citation features significantly improved the performance of conventional machine learning algorithms, although the improvement was not as strong in transformer-based deep learning models. This may be because transformer models were mostly pre-trained on abstracts, which do not include additional citation information like MeSH terms, keywords, and journal names. Secondly, when using only title and abstract as input, transformer models consistently outperformed conventional machine learning algorithms, highlighting the strength of subject domain-specific pre-trained language models. When all citation features were combined as input, conventional machine learning algorithms showed comparable performance to deep learning models. Given the much lower computation costs and faster training and prediction time, XGBoost or support vector machines with all citation features could be an excellent choice for developing an abstract screening system.

Some limitations remain for this study. Although we’ve evaluated cutting-edge machine learning and deep learning algorithms on two SLR corpora, we did not conduct much task-specific customization to the learning algorithms, including task-specific feature engineering and rule-based post-processing, which could offer additional benefits to the performance. As the focus of this study is to provide generalizable strategies for employing machine learning to abstract screening tasks, we leave the task-specific customization to future improvement. The corpora we evaluated in this study mainly focus on health economics and outcome research, the generalizability of learning algorithms to another domain will benefit from formal examination.

Extensive studies have shown the superiority of transformer-based deep learning models for many NLP tasks [ 11 , 13 , 14 , 15 , 16 ]. Based on our experiments, however, adding features to the pre-trained language models that have not seen these features before may not significantly boost their performance. It would be interesting to find a better way of encoding additional features to these pre-trained language models to maximize their performance. In addition, transfer learning has proven to be an effective technique to improve the performance on a target task by leveraging annotation data from a source task [ 17 , 18 , 19 ]. Thus, for a new SLR abstract screening task, it would be worthwhile to investigate the use of transfer learning by adapting our (publicly available) corpora to the new target task.

When labeled data is available, supervised machine learning algorithms can be very effective and efficient for article screening. However, as there is increasing need for explainability and transparency in NLP-assisted SLR workflow, supervised machine learning algorithms are facing challenges in explaining why certain papers fail to fulfill the criteria. The recent advances in large language models (LLMs), such as ChatGPT [ 20 ] and Gemini [ 21 ], show remarkable performance on NLP tasks and good potentials in explainablity. Although there are some concerns on the bias and hallucinations that LLMs could bring, it would be worthwhile to evaluate further how LLMs could be applied to SLR tasks and understand the performance of using LLMs to take free-text article screening criteria as the input and provide explainanation for article screening decisions.

Data availability

The annotated corpora underlying this article are available at https://github.com/Merck/NLP-SLR-corpora .

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Acknowledgements

We thank Dr. Majid Rastegar-Mojarad for conducting some additional experiments during revision.

This research was supported by Merck Sharp & Dohme LLC, a subsidiary of Merck & Co., Inc., Rahway, NJ, USA.

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Study concept and design: JD and LY Corpus preparation: DW, YL and LY Experiments: JD and ES Draft of the manuscript: JD, DW, FJM and LY Acquisition, analysis, or interpretation of data: JD, ES, DW and LY Critical revision of the manuscript for important intellectual content: JD, ES, DW, LH, BL, JW, FJM, YL, EW, LY Study supervision: LY.

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DW is an employee of Merck Sharp & Dohme LLC, a subsidiary of Merck & Co., Inc., Rahway, NJ, USA. EW, YL, and LY were employees of Merck Sharp & Dohme LLC, a subsidiary of Merck & Co., Inc., Rahway, NJ, USA for this work. JD, LH, JW, and FJM are employees of Intelligent Medical Objects. ES was an employee of Intelligent Medical Objects during his contributions, and is currently an employee of EBSCO Information Services. All the other authors declare no competing interest.

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Du, J., Soysal, E., Wang, D. et al. Machine learning models for abstract screening task - A systematic literature review application for health economics and outcome research. BMC Med Res Methodol 24 , 108 (2024). https://doi.org/10.1186/s12874-024-02224-3

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  • http://orcid.org/0000-0001-9784-416X Rikisha Shah Gupta 1 , 2 ,
  • Ardita Koteci 3 , 4 ,
  • Ann Morgan 3 , 4 ,
  • Peter M George 5 and
  • Jennifer K Quint 1 , 3
  • 1 National Heart and Lung Institute , Imperial College London , London , UK
  • 2 Real-World Evidence , Gilead Sciences , Foster City , CA , USA
  • 3 Imperial College London , London , UK
  • 4 NIHR Imperial Biomedical Research Centre , London , UK
  • 5 Royal Brompton and Harefield NHS Foundation Trust , London , UK
  • Correspondence to Rikisha Shah Gupta; r.shah20{at}imperial.ac.uk

Interstitial lung disease (ILD) is a collective term representing a diverse group of pulmonary fibrotic and inflammatory conditions. Due to the diversity of ILD conditions, paucity of guidance and updates to diagnostic criteria over time, it has been challenging to precisely determine ILD incidence and prevalence. This systematic review provides a synthesis of published data at a global level and highlights gaps in the current knowledge base. Medline and Embase databases were searched systematically for studies reporting incidence and prevalence of various ILDs. Randomised controlled trials, case reports and conference abstracts were excluded. 80 studies were included, the most described subgroup was autoimmune-related ILD, and the most studied conditions were rheumatoid arthritis (RA)-associated ILD, systemic sclerosis associated (SSc) ILD and idiopathic pulmonary fibrosis (IPF). The prevalence of IPF was mostly established using healthcare datasets, whereas the prevalence of autoimmune ILD tended to be reported in smaller autoimmune cohorts. The prevalence of IPF ranged from 7 to 1650 per 100 000 persons. Prevalence of SSc ILD and RA ILD ranged from 26.1% to 88.1% and 0.6% to 63.7%, respectively. Significant heterogeneity was observed in the reported incidence of various ILD subtypes. This review demonstrates the challenges in establishing trends over time across regions and highlights a need to standardise ILD diagnostic criteria.PROSPERO registration number: CRD42020203035.

  • Asbestos Induced Lung Disease
  • Clinical Epidemiology
  • Interstitial Fibrosis
  • Systemic disease and lungs

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Introduction

Interstitial lung disease (ILD) is a collective term representing a diverse group of lung conditions characterised by the presence of non-infective infiltrates, most commonly in the pulmonary interstitium and alveoli, which in certain cases manifest as architectural distortion and irreversible fibrosis. These conditions vary in their aetiology, clinical pathways, severity and prognosis. 1 Some conditions resolve completely without pharmacological intervention, whereas others, such as idiopathic pulmonary fibrosis (IPF) and non-IPF progressive fibrosing (PF) ILDs, inexorably progress to respiratory failure and premature mortality despite treatment.

Given its universally progressive nature and poor prognosis, IPF has attracted the most research attention and the current literature suggests a wide variation in disease distribution across Europe and USA. IPF prevalence varies between 0.63 and 7.6 per 100 000 persons in the USA and Europe 2 3 with a sharp increase with age.

More recently, there have been several studies investigating the incidence and prevalence of non-IPF ILDs, mainly autoimmune ILDs. Most of these reviews included studies drawn from single centres. Epidemiological data for non-IPF ILDs is inconsistent which makes it challenging to fully appreciate the ILD landscape. A recent review reported the prevalence of ILD in myositis conditions ranged from 23% in America to 50% in Asia. 4 Sambataro et al 5 reported about 20% of primary Sjogren’s syndrome patients were diagnosed with ILD. Additionally, there have been a few studies evaluating the incidence of drug induced ILD (DILD). 6–8 Guo et al 9 reported ILD incidence ranged from 4.6 to 31.5 per 100 000 persons in Europe and North America. A recent study using Global Burden of Disease data indicated the global ILD incidence in the past 10 years has risen by 51% (313.2 cases in 1990 to 207.2 per 1 00 000 cases in 2019). 10 These published estimates highlight a discernible variation in the ILD epidemiology across countries. It is unclear whether this is an ‘actual’ difference in the numbers across regions or whether the heterogeneity is driven by lack of guidelines and inconsistencies in ILD diagnostic pathways and standards of care. Likewise, while evidence suggests that the incidence of ILD has been rising over time, 9 whether this increase reflects a true increase in the disease burden, possibly related to an ageing population or whether this is due to improvements in detection, increased availability of cross-sectional imaging or coding practices over time is unknown.

This systematic review appraises the published literature on the incidence and prevalence of various ILDs over the last 6 years. We aimed to provide a comprehensive understanding of global incidence and prevalence. Specifically, we sought to identify areas where data are robust, to better appreciate the burden of ILD conditions and to comprehend the implications on healthcare utilisation and resources. We also set out to highlight areas where there remains a need for further study.

Study registration

This protocol has been drafted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols guidelines 11 and registered with the International Prospective Register of Systematic Reviews, PROSPERO ( CRD42020203035 ). Please refer to the online supplemental material for the full study protocol.

Supplemental material

Search strategy and selection criteria.

A systematic search of Medline and Embase was carried out in September 2021 to identify relevant studies investigating the incidence and prevalence of various ILDs. The search criteria were developed with support of librarian ( online supplemental figure E1 ). Due to the high volume of papers, we restricted this study period to papers published in the past 6 years. This search was limited to human studies written in English that were published between 2015 and 2021. The full search strategy and data sources included are described in online supplemental material .

Study population

Inclusion criteria included observational studies reporting the incidence and/or prevalence of individual ILDs, with study participants aged over 18 years old. Randomised controlled trials, case reports, reviews and conference abstracts were excluded. Studies which referred to DILD only were excluded because (1) there were many abstracts reporting on DILD, therefore this could be a standalone review and (2) epidemiology of DILD was a subject of a recent systematic review. 12 The first author (RG) screened all records by title and abstract; to begin with, the second reviewer (AK) independently screened 10% of all records. If there was a disagreement between RG and AK, an additional 15% were screened by AK. All studies identified as eligible for full text review were reviewed by RG, with AK reviewing 50% of eligible studies. Any disagreement was resolved through discussion with other authors, including an ILD expert. Reference of included studies were searched for additional literature.

Following full text review, RG carried out data extraction for eligible studies. AK independently extracted data for 25% of studies using the same template. RG assessed the quality for all included studies, reporting incidence and/or prevalence using a modified Newcastle Ottawa Scale (NOS). There were two NOS modified scales, one each for studies reporting prevalence and/incidence. AK independently assessed the quality of 25% of included studies. If there was a discrepancy between the data extraction and/or quality assessment conducted by RG and AK, then additional 15% were extracted and/or reviewed by AK.

It was noted that for IPF, many authors adopted what they termed ‘broad’ and ‘narrow’ case definitions. For example, Raghu et al 2 defined patients with International Classification of Disease, Ninth Revision (ICD-9) code 516.3 as a broadly defined case of IPF, and those who had this ICD-9 code alongside a claim for a surgical lung biopsy, transbronchial lung biopsy, or CT thorax as a narrowly defined case. We summarised the data using various reported case definitions. If multiple estimates were reported in a study, only the most recent estimate was included in this review.

There were two common themes around the reporting of prevalence. Studies drawn from the general population (reported prevalence per 100 000 persons) and studies drawn from multicentre or single centres (reported prevalence as the proportion of patients with ILD in the study cohort).

For this review, we have classified ILDs based on aetiology, grouped by conditions linked to environmental or occupational exposures, conditions typified by granulomatous inflammation, autoimmune ILDs and ILDs with no known cause ( online supplemental figure E2 ). 1

Evidence synthesis

The initial plan for this review was to conduct meta-analysis. However, due to high heterogeneity, we were unable to meta-analyse. Therefore, we have proceeded with data synthesis across the ILD subgroups.

Total number of included studies

The literature search yielded a total of 12 924 studies, of which 80 were included in this review. Online supplemental figure E3 demonstrates the selection process for all studies and highlights reasons for exclusion at each stage.

Although 80 unique publications were included, some papers explored the epidemiology of more than one ILD, the total count of reported estimates is 88. Half of the included publications explored autoimmune-related ILDs (n=44/88)( online supplemental figure E4 ).

Geographically, ILD publications represented all major world regions, but were predominantly from Asia (n=30, 34.1%) and Europe (n=23, 26.1%) ( figure 1 ).

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Geographical distribution of publications included.

Studies reporting prevalence

Eight studies reported the prevalence of IPF in general population. Prevalence of IPF was commonly reported applying ‘primary’, ‘broad’, ‘intermediate’ and/or ‘narrow’ case definitions. In the general population, the prevalence of IPF ranged from 7 to 1650 per 100 000 persons ( table 1 ). When explored within various case definitions, the prevalence for ‘broad’ cases ranged from 11 (USA, 2010) 2 to 1160 (USA, 2021) 16 ; for ‘narrow’ cases, this ranged from 7 (USA, 2010) 2 to 725 (USA, 2019). 16 There was only one study that reported IPF prevalence of 8.6% using a multicentre study setting. 19

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Studies reporting IPF prevalence per 100 000 persons by various case definitions

Twelve studies reported estimates for non-IPF ILDs in the general population ( online supplemental figure E5 ), with most of these conducted in the USA. The prevalence of systemic sclerosis (SSc) ILD in the general population ranged from 2.3 (Canada, 2018) 20 to 19 (USA, 2017) 21 per 100 000 persons. The highest SSc-ILD prevalence was reported in Medicare data which included patients aged 65 years and above. 21 22 For rheumatoid arthritis (RA) ILD, prevalence in an RA Medicare cohort was 2%. 23

Forty-six studies reported the prevalence of autoimmune-related ILD in cohorts of patients with an autoimmune condition or occupational ILD in workers with specific exposures. These studies primarily reported prevalence as a proportion, with the denominator representing patients with an autoimmune disorder or people working at a factory with exposure to certain agents, such as silica or asbestosis ( figure 2 ). Most of these estimates were drawn from cohorts at single or multiple tertiary centres, disease registries or a factory in the case of occupational ILD. Significant heterogeneity was noted in the reported prevalence of ILD associated with SSc, RA and Sjogren’s ( figure 2 ). The prevalence of ILD in SSc ranged from 26.1% (Australia, 2015) 36 to 88.1% (India, 2013). 44 Similarly, Sjogren’s ILD ranged from 1% (Sweden, 2011) 55 to 87.8% (Saudi Arabia, 2021). 56 In addition to dissimilarities in the prevalence across various regions, we also observed variation within region-specific estimates. For example, the 4 studies 47 50–52 which reported Sjogren’s ILD prevalence within China, estimated a 4-fold variation in magnitude (18.6% in 2011 47 to 78.6% in 2014). 52 Likewise, for RA ILD, there was substantial variation in the reported prevalence in Egypt (0.8% vs 63.7%). 31 32 Among the occupational-related ILDs ( figure 2 ), silicosis was the most explored condition (n=8)). Among these eight studies, there was a considerable variation in the reported prevalence of silicosis. Souza et al 61 reported an approximately 7-fold higher estimate of silicosis prevalence than that reported by Siribaddana et al (37% vs 5.6%, respectively). 65

Studies reporting non-IPF prevalence as percentage of study population. DM, dermatomyositis; HP, hypersensitivity pneumonitis; IIP, idiopathic interstitial pneumonia; ILD, interstitial lung disease; LAM, lymphangioleiomyomatosis; MCTD, mixed connective tissue disorder; multiC, multicentre; PLCH, pulmonary langerhans cell histiocytosis; PM, polymyositis; RA, rheumatoid arthritis; reg, registry; single, single centre; SSc, systemic sclerosis. Details on the study population, sample size and ILD diagnosis methods are summarised in online supplemental tables E1–E31 .

Studies reporting incidence

Significant discrepancies were observed in reported ILD incidence across subgroups and individual conditions, mainly due to differences in the study setting. Depending on the study setting and type of data source used, some authors reported an incidence rate (per 100 000 person-years), while others reported incidence proportion. Table 2 lists IPF incidence by case classification and country, and figure 3 provides a list of studies reporting incidence of non-IPF ILDs.

Published estimates of IPF incidence, stratified by various case definitions

Studies reporting ILD incidence, grouped by ILD subgroups. ICD-9-CM, International Classification of Disease, Ninth Revision, Clinical Modification; ILD, interstitial lung disease; py, person-years; RA, rheumatoid arthritis; SSc, systemic sclerosis. Ɨ Narrow silicosis definition used: Medicare beneficiaries with any claim that included ICD-9-CM code 502, pneumoconiosis due to other silica or silicates, listed in any position during 1999–2014, with at least one inpatient, skilled nursing or home health agency claim, or at least two outpatient provider claims within 365 days of each other and cases with a chest X-ray or CT scan 30 days before or 30 days after a silicosis claim. Details on the study population, sample size and ILD diagnosis methods are summarised in online supplemental tables E1–E31 .

In this review, we synthesised the evidence for the incidence and prevalence of ILDs from studies published between 2015 and 2021. Considering the changing ILD nomenclature and the desire to reflect more current estimates, in this review, we decided to restrict the study period to past 6 years. We took this conscious effort with the aim to limit the heterogeneity across reported estimates. We evaluated 39 incidence and 78 prevalence estimates for individual ILD disorders that were distributed globally. We noted an increase in the number of studies investigating non-IPF ILDs and more specifically autoimmune ILDs in recent years. There was a 6-fold rise in the autoimmune ILDs studies, in 2021 when compared with 2015 (18 vs 3 studies, respectively). This increase in non-IPF ILD studies may be related to the emergence of antifibrotic therapies for non-IPF fibrosing lung diseases. 91–93 Interestingly, the publication trend for IPF has remained unchanged.

This review revealed considerable inconsistencies in the incidence and prevalence estimated of the main ILD subgroups. The reported prevalence of IPF ranged from 7 to 1650 per 100 000 persons, 2 16 an approximately 800-fold difference across case definitions, despite most studies reporting IPF prevalence in the general population. The incidence and prevalence estimates reported by Zhang et al 16 were a notable outlier; this study was based on the USA veterans’ healthcare database which included mostly White patients aged over 70 years—the demographic in which IPF is most common. Aside from this study, the majority of studies reported a prevalence of IPF ranging from 7 to 42 per 100 000 persons across different case definitions. 2 17

Unlike prevalence, we found considerable inconsistencies in how the incidence of IPF is reported. An important factor is the lack of uniformity in reporting units. Half of the studies reported incidence using person-years, whereas others reported per 100 000 person-years. We were, therefore, unable to compare incidence estimates in a similar fashion to prevalence. It is also important to note that changes in diagnostic guidelines for IPF over the years may have made it more challenging to accurately estimate its burden and temporal trends. 94–96

For non-IPF subgroups, such as autoimmune ILDs, there were wide variations in prevalence estimates between countries and within different healthcare settings in the same country. Overall, the variation in prevalence and incidence estimates was even greater for non-IPF ILDs than IPF. This can be attributed to several factors. First, in clinical practice, it is common for the clinical presentation and serological autoantibody profiles to result in overlap syndromes. Autoimmune conditions can coexist and patients with occupational ILDs may also have autoimmune conditions. Such fluidity of diagnoses at a clinical level reflects the challenges in estimating non-IPF ILDs. Second, the denominator more frequently differs for non-IPF ILDs, resulting in lack of standardised reporting. Unlike IPF, for which there are published validated algorithms to identify ‘true’ cases in the general population. 18 24 97 For non-IPF ILDs, studies relied on disease registries or were conducted at single/multispecialist clinics.

Majority of the autoimmune-related ILD estimates were in RA and SSc ILD. When assessing SSc ILD prevalence, we observed a wide range (26.1% to 88.1%) 37 44 in reported estimates, but when studies were dichotomised into single-centre studies and multicentre studies, it became clear that the highest variability was contributed by single centre studies (SSc prevalence, 31.2%–88.1%). 43–46 Owing to a smaller number of studies reporting incidence, we were unable to observe whether the same challenge existed.

The prevalence of silicosis ranged from 5.6% 65 to 37% 61 in workers exposed to silica. Occupational ILD studies were conducted at a factory, in a neighbourhood with proximity to industries, a registry or multicentre settings. Therefore, lack of generalisability and applicability of findings only to certain populations contributed largely to the wide variabilities of these reported estimates. The geographical distribution of occupational ILD papers alludes to dominance of exposure related ILDs in low-income and middle-income countries in Asia and South America (42.8% were in Asia).

While historical diagnostic classification has been founded on underlying aetiology or clinical pathways, there is now a growing emphasis on disease behaviour. 98 99 Attention has focused on a subgroup of ILD patients who go on to develop a PF phenotype. IPF is the archetypal PF ILD but other ILDs such as chronic hypersensitivity pneumonitis (HP), SSc ILD can exhibit ‘IPF-like’ behaviour, including rapid decline in lung function and early mortality. 100 The epidemiology of PF ILD is particularly challenging to examine as accepted guidelines on definition and diagnosis have yet to be published The reported prevalence of PF ILDs (per 100 000 persons) was 19.4 in France and 57.8 in the USA. 88 89 The future direction of research will likely focus on PF ILD as a phenotype which transcends previously adhered-to diagnostic labels and is associated with poorer outcomes and increased mortality. 100 101

Among the 39 studies reporting ILD incidence ( online supplemental figure E6 ), most studies were categorised as medium risk (n=25/39, 64.1%). Two studies were categorised as high-risk primarily because of lack of information on ILD diagnosis and poor quality of reporting estimates (ie, descriptive statistics were not reported, were incomplete or did not include proper measures of dispersion).

Similarly, there were 78 prevalence assessments ( online supplemental figure E7 ) of which approximately 18% (n=14/78) were categorised as high risk, 64.1% (n=50/78) as medium risk and 18% (n=14/76) as low risk. Most studies assessed as high risk were studies reporting autoimmune ILDs, mainly because of ILD diagnosis, single-centre studies or small sample size. Most of the studies reporting prevalence based on large healthcare datasets or disease registries were classified as low risk.

There are several strengths of this systematic review. We have provided an assessment of the incidence and prevalence of several ILD conditions globally and have grouped ILDs based on their aetiology to allow the appraisal of incidence and/prevalence at a disease level with as much granularity as possible. This review underlines the need for standardisation of diagnostic classifications for non-IPF ILDs—the narrower estimates for IPF provide the evidence that clear and consistent diagnostic guidelines are of great clinical utility. Guidelines have recently emerged for the diagnosis of HP 102 103 which we envisage will further improve the epidemiological reporting of this important condition, although incorporation of guidelines into routine clinical practice and then into epidemiological estimates takes time. Cross-specialty guideline groups will undoubtedly improve standardisation of reporting for autoimmune driven ILDs.

It is possible that genetic differences between individuals from different ethnic backgrounds may play a role in the global variability in incidence and prevalence. For example, the MUC5B promoter polymorphism (rs35705950) is the dominant risk factor for IPF 104 and is also a key risk factor for other ILDs such as RA. 105 This gain of function polymorphism is frequent in those of European decent but almost completely absent in those of African ancestry. 106 As more research is performed unravelling the complex interplay between genetics and environment in the development of ILD, it is likely that genetic variability will be found to play an important role in the global variability of ILD.

Despite the strengths, there are limitations to this systematic review. The certainty of the ILD case definition varied across studies. It was not always possible to be sure of how reliable the ascertainment method was. However, we attempted to reflect the differences in the ILD diagnostic methods in our risk of bias quality assessment. Along with the uncertainty in the diagnosis of ILD, there were different disease definitions used across studies. Therefore, in this review due to high heterogeneity, in how ILD was defined, we were unable to perform a meta-analysis. In this review, we have only included studies reporting ILD estimates in general populations, registries or populations with a specific disorder of interest. For single-centre studies reporting incidence and/or prevalence of autoimmune or exposure ILDs, the estimates were not generalisable and this has been reflected in the risk of bias quality assessment score. This review is limited to English publications only. However, due to high volume of papers found with the study period, we are confident it has a minimal effect on the overall conclusion. 107

This review highlights the lack of uniformity in the published estimates of incidence and prevalence of ILD conditions. In addition, there is a dissimilarity in disease definitions across the studies and geographical regions. Owing to these discrepancies, we were unable to derive estimates for the global incidence and prevalence of ILD and moreover unable to confirm whether there has been a ‘true’ increase in ILD incidence over time. Revisions to diagnostic criteria have augmented the challenges of estimating incidence and prevalence of individual ILD conditions and determining the drivers for temporal trends in incidence. Improving our estimates of the burden of fibrosing lung conditions is essential for future health service planning, a need that has been heightened by the development of new antifibrotic treatments. Guidelines have recently emerged for non-IPF ILDs, we envisage this may improve the epidemiological reporting for future research. There is a fundamental need to standardise ILD diagnosis, disease definitions and reporting in order to provide the data which will drive the provision of a consistently high level of care for these patients across the globe. 108

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Supplementary materials

Supplementary data.

This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

  • Data supplement 1

Twitter @DrPeter_George

Contributors RG, AM, PMG and JKQ developed the research question. RG, AM, PMG and JKQ developed the study protocol. RG developed the search strategy with input from AM and JKQ. RG screened the studies for inclusion, extracted the data from included studies and carried out quality assessment of the data. AK was the secondary reviewer for screening, data extraction and quality assessment. PMG supported with the understanding of various ILD diseases and their clinical pathways. All authors interpreted the review results. RG drafted the manuscript. All authors read, commented on and approved the manuscript.

Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

Map disclaimer The inclusion of any map (including the depiction of any boundaries therein), or of any geographic or locational reference, does not imply the expression of any opinion whatsoever on the part of BMJ concerning the legal status of any country, territory, jurisdiction or area or of its authorities. Any such expression remains solely that of the relevant source and is not endorsed by BMJ. Maps are provided without any warranty of any kind, either express or implied.

Competing interests RG is a current employee of Gilead Sciences, outside the submitted work. JKQ has received grants from The Health Foundation, MRC, GSK, Bayer, BI, British Lung Foundation, IQVIA, Chiesi AZ, Insmed and Asthma UK. JKQ has received personal fees for advisory board participation or speaking fees from GlaxoSmithKline, Boehringer Ingelheim, AstraZeneca, Bayer and Insmed. PMG has received grants from the MRC, Boehringer Ingelheim and Roche Pharmaceuticals and personal fees from Boehringer Ingelheim, Roche Pharmaceuticals, Teva, Cippla, AZ and Brainomix. AK and AM have nothing to disclose.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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IMAGES

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