literature review and survey

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Organizing Your Social Sciences Research Paper

• 5. The Literature Review
• Purpose of Guide
• Design Flaws to Avoid
• Independent and Dependent Variables
• Glossary of Research Terms
• Reading Research Effectively
• Narrowing a Topic Idea
• Broadening a Topic Idea
• Extending the Timeliness of a Topic Idea
• Academic Writing Style
• Applying Critical Thinking
• Choosing a Title
• Making an Outline
• Paragraph Development
• Research Process Video Series
• Executive Summary
• The C.A.R.S. Model
• Background Information
• The Research Problem/Question
• Theoretical Framework
• Citation Tracking
• Content Alert Services
• Evaluating Sources
• Primary Sources
• Secondary Sources
• Tiertiary Sources
• Scholarly vs. Popular Publications
• Qualitative Methods
• Quantitative Methods
• Insiderness
• Using Non-Textual Elements
• Limitations of the Study
• Common Grammar Mistakes
• Writing Concisely
• Avoiding Plagiarism
• Footnotes or Endnotes?
• Further Readings
• Generative AI and Writing
• USC Libraries Tutorials and Other Guides
• Bibliography

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

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

Importance of a Good Literature Review

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

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

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

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

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

Types of Literature Reviews

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

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

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

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

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

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

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

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

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

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

Structure and Writing Style

I.  Thinking About Your Literature Review

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

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

The critical evaluation of each work should consider :

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

II.  Development of the Literature Review

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

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

III.  Ways to Organize Your Literature Review

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

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

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

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

IV.  Writing Your Literature Review

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

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

V.  Common Mistakes to Avoid

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

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

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

Writing Tip

Break Out of Your Disciplinary Box!

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

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

Another Writing Tip

Don't Just Review for Content!

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

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

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

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

Yet Another Writing Tip

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

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

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

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

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

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

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

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

There are five key steps to writing a literature review:

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

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

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Table of contents

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

• Quick Run-through
• Step 1 & 2

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

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

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

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

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

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

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

Download Word doc Download Google doc

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

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

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

Make a list of keywords

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

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

Search for relevant sources

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

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

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

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

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

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

For each publication, ask yourself:

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

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

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

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

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

Take notes and cite your sources

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

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

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

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

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

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

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

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

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

Chronological

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

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

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

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

Methodological

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

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

Theoretical

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

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

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

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

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

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

As you write, make sure to follow these tips:

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

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

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

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

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

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

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

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

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

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Writing a Literature Review

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

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

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

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

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

What are the parts of a lit review?

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

Introduction:

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

Conclusion:

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

How should I organize my lit review?

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

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

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

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

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

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

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

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

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

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

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

What are Literature Reviews?

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

Goals of Literature Reviews

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

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

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

What kinds of sources require a Literature Review?

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

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

Types of Literature Reviews

What kinds of literature reviews are written?

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

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

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

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

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

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

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

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

Literature Reviews in the Health Sciences

• UConn Health subject guide on systematic reviews Explanation of the different review types used in health sciences literature as well as tools to help you find the right review type
• << Previous: Getting Started
• Next: How to Pick a Topic >>
• Last Updated: Sep 21, 2022 2:16 PM
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How To Write A Literature Review - A Complete Guide

Table of Contents

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

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

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

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

What is a literature review?

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

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

“A literature review surveys books, scholarly articles, and any other sources relevant to a particular issue, area of research, or theory, and by so doing, provides a description, summary, and critical evaluation of these works in relation to the research problem being investigated.

Literature reviews are designed to provide an overview of sources you have explored while researching a particular topic, and to demonstrate to your readers how your research fits within a larger field of study.”

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

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

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

What is the purpose of a literature review?

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

What is the importance of a literature review?

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

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

How long should a literature review be?

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

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

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

What are the different types of literature reviews?

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

Here are the different types of literature reviews:

Argumentative review

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

Integrative review

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

Methodological review

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

Systematic review

This form consists of an overview of existing evidence pertinent to a clearly formulated research question, which uses pre-specified and standardized methods to identify and critically appraise relevant research and collect, report, and analyze data from the studies included in the review.

Meta-analysis review

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

Historical review

Historical literature reviews focus on examining research throughout a period, often starting with the first time an issue, concept, theory, or phenomenon emerged in the literature, then tracing its evolution within the scholarship of a discipline. The purpose is to place research in a historical context to show familiarity with state-of-the-art developments and identify future research's likely directions.

Theoretical Review

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

Scoping Review

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

State-of-the-Art Review

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

Can you use the first person in a literature review?

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

Do you need an abstract for a literature review?

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

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

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

Is a literature review written in the past tense?

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

How many sources for a literature review?

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

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

Quick tips on how to write a literature review

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

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

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

1. Outline and identify the purpose of  a literature review

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

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

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

2. Search relevant literature

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

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

• Google Scholar
• Microsoft Academic
• Science.gov

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

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

3. Examine and assess the sources

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

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

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

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

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

4. Discover connections

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

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

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

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

5. Structure planning to write a good literature review

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

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

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

Literature review samples

1. Standalone

2. As a section of a research paper

How SciSpace Discover makes literature review a breeze?

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

Find the right information

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

Assess credibility of papers quickly

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

Get the complete picture in no time

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

Make referring sources super easy

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

Final tips on how to write a literature review

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

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

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

Frequently Asked Questions (FAQs)

1. how to start a literature review.

• What questions do you want to answer?

• What sources do you need to answer these questions?

• What information do these sources contain?

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

2. What to include in a literature review?

• A brief background of the problem or issue

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

• A description of what you will do in your project

• How this study will contribute to research on the subject

3. Why literature review is important?

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

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

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

5. What are the components of a literature review?

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

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

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

6. What are common errors in writing literature review?

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

• Totally relying on secondary data while ignoring primary data.

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

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

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

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

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

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

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

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

8. How many sources should a literature review have?

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

9. Can literature review have diagrams?

• To represent an abstract idea or concept

• To explain the steps of a process or procedure

• To help readers understand the relationships between different concepts

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

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

11. What are the types of literature review?

• Argumentative review

• Integrative review

• Methodological review

• Systematic review

• Meta-analysis review

• Historical review

• Theoretical review

• Scoping review

• State-of-the-Art review

12. Is a literature review mandatory?

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

But before you go,

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

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By: Derek Jansen (MBA) | Expert Reviewed By: Dr. Eunice Rautenbach | October 2019

Quality research is about building onto the existing work of others , “standing on the shoulders of giants”, as Newton put it. The literature review chapter of your dissertation, thesis or research project is where you synthesise this prior work and lay the theoretical foundation for your own research.

Long story short, this chapter is a pretty big deal, which is why you want to make sure you get it right . In this post, I’ll show you exactly how to write a literature review in three straightforward steps, so you can conquer this vital chapter (the smart way).

Overview: The Literature Review Process

• Understanding the “ why “
• Finding the relevant literature
• Cataloguing and synthesising the information
• Outlining & writing up your literature review
• Example of a literature review

But first, the “why”…

Before we unpack how to write the literature review chapter, we’ve got to look at the why . To put it bluntly, if you don’t understand the function and purpose of the literature review process, there’s no way you can pull it off well. So, what exactly is the purpose of the literature review?

Well, there are (at least) four core functions:

• For you to gain an understanding (and demonstrate this understanding) of where the research is at currently, what the key arguments and disagreements are.
• For you to identify the gap(s) in the literature and then use this as justification for your own research topic.
• To help you build a conceptual framework for empirical testing (if applicable to your research topic).
• To inform your methodological choices and help you source tried and tested questionnaires (for interviews ) and measurement instruments (for surveys ).

Most students understand the first point but don’t give any thought to the rest. To get the most from the literature review process, you must keep all four points front of mind as you review the literature (more on this shortly), or you’ll land up with a wonky foundation.

Okay – with the why out the way, let’s move on to the how . As mentioned above, writing your literature review is a process, which I’ll break down into three steps:

• Finding the most suitable literature
• Understanding , distilling and organising the literature
• Planning and writing up your literature review chapter

Importantly, you must complete steps one and two before you start writing up your chapter. I know it’s very tempting, but don’t try to kill two birds with one stone and write as you read. You’ll invariably end up wasting huge amounts of time re-writing and re-shaping, or you’ll just land up with a disjointed, hard-to-digest mess . Instead, you need to read first and distil the information, then plan and execute the writing.

Step 1: Find the relevant literature

Naturally, the first step in the literature review journey is to hunt down the existing research that’s relevant to your topic. While you probably already have a decent base of this from your research proposal , you need to expand on this substantially in the dissertation or thesis itself.

Essentially, you need to be looking for any existing literature that potentially helps you answer your research question (or develop it, if that’s not yet pinned down). There are numerous ways to find relevant literature, but I’ll cover my top four tactics here. I’d suggest combining all four methods to ensure that nothing slips past you:

Method 1 – Google Scholar Scrubbing

Google’s academic search engine, Google Scholar , is a great starting point as it provides a good high-level view of the relevant journal articles for whatever keyword you throw at it. Most valuably, it tells you how many times each article has been cited, which gives you an idea of how credible (or at least, popular) it is. Some articles will be free to access, while others will require an account, which brings us to the next method.

Method 2 – University Database Scrounging

Generally, universities provide students with access to an online library, which provides access to many (but not all) of the major journals.

So, if you find an article using Google Scholar that requires paid access (which is quite likely), search for that article in your university’s database – if it’s listed there, you’ll have access. Note that, generally, the search engine capabilities of these databases are poor, so make sure you search for the exact article name, or you might not find it.

Method 3 – Journal Article Snowballing

At the end of every academic journal article, you’ll find a list of references. As with any academic writing, these references are the building blocks of the article, so if the article is relevant to your topic, there’s a good chance a portion of the referenced works will be too. Do a quick scan of the titles and see what seems relevant, then search for the relevant ones in your university’s database.

Method 4 – Dissertation Scavenging

Similar to Method 3 above, you can leverage other students’ dissertations. All you have to do is skim through literature review chapters of existing dissertations related to your topic and you’ll find a gold mine of potential literature. Usually, your university will provide you with access to previous students’ dissertations, but you can also find a much larger selection in the following databases:

• Open Access Theses & Dissertations
• Stanford SearchWorks

Keep in mind that dissertations and theses are not as academically sound as published, peer-reviewed journal articles (because they’re written by students, not professionals), so be sure to check the credibility of any sources you find using this method. You can do this by assessing the citation count of any given article in Google Scholar. If you need help with assessing the credibility of any article, or with finding relevant research in general, you can chat with one of our Research Specialists .

Alright – with a good base of literature firmly under your belt, it’s time to move onto the next step.

Need a helping hand?

Step 2: Log, catalogue and synthesise

Once you’ve built a little treasure trove of articles, it’s time to get reading and start digesting the information – what does it all mean?

While I present steps one and two (hunting and digesting) as sequential, in reality, it’s more of a back-and-forth tango – you’ll read a little , then have an idea, spot a new citation, or a new potential variable, and then go back to searching for articles. This is perfectly natural – through the reading process, your thoughts will develop , new avenues might crop up, and directional adjustments might arise. This is, after all, one of the main purposes of the literature review process (i.e. to familiarise yourself with the current state of research in your field).

As you’re working through your treasure chest, it’s essential that you simultaneously start organising the information. There are three aspects to this:

• Logging reference information
• Building an organised catalogue
• Distilling and synthesising the information

I’ll discuss each of these below:

2.1 – Log the reference information

As you read each article, you should add it to your reference management software. I usually recommend Mendeley for this purpose (see the Mendeley 101 video below), but you can use whichever software you’re comfortable with. Most importantly, make sure you load EVERY article you read into your reference manager, even if it doesn’t seem very relevant at the time.

2.2 – Build an organised catalogue

In the beginning, you might feel confident that you can remember who said what, where, and what their main arguments were. Trust me, you won’t. If you do a thorough review of the relevant literature (as you must!), you’re going to read many, many articles, and it’s simply impossible to remember who said what, when, and in what context . Also, without the bird’s eye view that a catalogue provides, you’ll miss connections between various articles, and have no view of how the research developed over time. Simply put, it’s essential to build your own catalogue of the literature.

I would suggest using Excel to build your catalogue, as it allows you to run filters, colour code and sort – all very useful when your list grows large (which it will). How you lay your spreadsheet out is up to you, but I’d suggest you have the following columns (at minimum):

• Author, date, title – Start with three columns containing this core information. This will make it easy for you to search for titles with certain words, order research by date, or group by author.
• Categories or keywords – You can either create multiple columns, one for each category/theme and then tick the relevant categories, or you can have one column with keywords.
• Key arguments/points – Use this column to succinctly convey the essence of the article, the key arguments and implications thereof for your research.
• Context – Note the socioeconomic context in which the research was undertaken. For example, US-based, respondents aged 25-35, lower- income, etc. This will be useful for making an argument about gaps in the research.
• Methodology – Note which methodology was used and why. Also, note any issues you feel arise due to the methodology. Again, you can use this to make an argument about gaps in the research.
• Quotations – Note down any quoteworthy lines you feel might be useful later.
• Notes – Make notes about anything not already covered. For example, linkages to or disagreements with other theories, questions raised but unanswered, shortcomings or limitations, and so forth.

If you’d like, you can try out our free catalog template here (see screenshot below).

2.3 – Digest and synthesise

Most importantly, as you work through the literature and build your catalogue, you need to synthesise all the information in your own mind – how does it all fit together? Look for links between the various articles and try to develop a bigger picture view of the state of the research. Some important questions to ask yourself are:

• What answers does the existing research provide to my own research questions ?
• Which points do the researchers agree (and disagree) on?
• How has the research developed over time?
• Where do the gaps in the current research lie?

To help you develop a big-picture view and synthesise all the information, you might find mind mapping software such as Freemind useful. Alternatively, if you’re a fan of physical note-taking, investing in a large whiteboard might work for you.

Step 3: Outline and write it up!

Once you’re satisfied that you have digested and distilled all the relevant literature in your mind, it’s time to put pen to paper (or rather, fingers to keyboard). There are two steps here – outlining and writing:

3.1 – Draw up your outline

Having spent so much time reading, it might be tempting to just start writing up without a clear structure in mind. However, it’s critically important to decide on your structure and develop a detailed outline before you write anything. Your literature review chapter needs to present a clear, logical and an easy to follow narrative – and that requires some planning. Don’t try to wing it!

Naturally, you won’t always follow the plan to the letter, but without a detailed outline, you’re more than likely going to end up with a disjointed pile of waffle , and then you’re going to spend a far greater amount of time re-writing, hacking and patching. The adage, “measure twice, cut once” is very suitable here.

In terms of structure, the first decision you’ll have to make is whether you’ll lay out your review thematically (into themes) or chronologically (by date/period). The right choice depends on your topic, research objectives and research questions, which we discuss in this article .

Once that’s decided, you need to draw up an outline of your entire chapter in bullet point format. Try to get as detailed as possible, so that you know exactly what you’ll cover where, how each section will connect to the next, and how your entire argument will develop throughout the chapter. Also, at this stage, it’s a good idea to allocate rough word count limits for each section, so that you can identify word count problems before you’ve spent weeks or months writing!

PS – check out our free literature review chapter template…

3.2 – Get writing

With a detailed outline at your side, it’s time to start writing up (finally!). At this stage, it’s common to feel a bit of writer’s block and find yourself procrastinating under the pressure of finally having to put something on paper. To help with this, remember that the objective of the first draft is not perfection – it’s simply to get your thoughts out of your head and onto paper, after which you can refine them. The structure might change a little, the word count allocations might shift and shuffle, and you might add or remove a section – that’s all okay. Don’t worry about all this on your first draft – just get your thoughts down on paper.

Once you’ve got a full first draft (however rough it may be), step away from it for a day or two (longer if you can) and then come back at it with fresh eyes. Pay particular attention to the flow and narrative – does it fall fit together and flow from one section to another smoothly? Now’s the time to try to improve the linkage from each section to the next, tighten up the writing to be more concise, trim down word count and sand it down into a more digestible read.

Once you’ve done that, give your writing to a friend or colleague who is not a subject matter expert and ask them if they understand the overall discussion. The best way to assess this is to ask them to explain the chapter back to you. This technique will give you a strong indication of which points were clearly communicated and which weren’t. If you’re working with Grad Coach, this is a good time to have your Research Specialist review your chapter.

Finally, tighten it up and send it off to your supervisor for comment. Some might argue that you should be sending your work to your supervisor sooner than this (indeed your university might formally require this), but in my experience, supervisors are extremely short on time (and often patience), so, the more refined your chapter is, the less time they’ll waste on addressing basic issues (which you know about already) and the more time they’ll spend on valuable feedback that will increase your mark-earning potential.

Literature Review Example

In the video below, we unpack an actual literature review so that you can see how all the core components come together in reality.

Let’s Recap

In this post, we’ve covered how to research and write up a high-quality literature review chapter. Let’s do a quick recap of the key takeaways:

• It is essential to understand the WHY of the literature review before you read or write anything. Make sure you understand the 4 core functions of the process.
• The first step is to hunt down the relevant literature . You can do this using Google Scholar, your university database, the snowballing technique and by reviewing other dissertations and theses.
• Next, you need to log all the articles in your reference manager , build your own catalogue of literature and synthesise all the research.
• Following that, you need to develop a detailed outline of your entire chapter – the more detail the better. Don’t start writing without a clear outline (on paper, not in your head!)
• Write up your first draft in rough form – don’t aim for perfection. Remember, done beats perfect.
• Refine your second draft and get a layman’s perspective on it . Then tighten it up and submit it to your supervisor.

Psst… there’s more!

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

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38 Comments

Thank you very much. This page is an eye opener and easy to comprehend.

This is awesome!

I wish I come across GradCoach earlier enough.

But all the same I’ll make use of this opportunity to the fullest.

Thank you for this good job.

Keep it up!

You’re welcome, Yinka. Thank you for the kind words. All the best writing your literature review.

Thank you for a very useful literature review session. Although I am doing most of the steps…it being my first masters an Mphil is a self study and one not sure you are on the right track. I have an amazing supervisor but one also knows they are super busy. So not wanting to bother on the minutae. Thank you.

You’re most welcome, Renee. Good luck with your literature review 🙂

This has been really helpful. Will make full use of it. 🙂

Thank you Gradcoach.

Really agreed. Admirable effort

thank you for this beautiful well explained recap.

Thank you so much for your guide of video and other instructions for the dissertation writing.

It is instrumental. It encouraged me to write a dissertation now.

Thank you the video was great – from someone that knows nothing thankyou

an amazing and very constructive way of presetting a topic, very useful, thanks for the effort,

It is timely

It is very good video of guidance for writing a research proposal and a dissertation. Since I have been watching and reading instructions, I have started my research proposal to write. I appreciate to Mr Jansen hugely.

I learn a lot from your videos. Very comprehensive and detailed.

Thank you for sharing your knowledge. As a research student, you learn better with your learning tips in research

I was really stuck in reading and gathering information but after watching these things are cleared thanks, it is so helpful.

Really helpful, Thank you for the effort in showing such information

This is super helpful thank you very much.

Thank you for this whole literature writing review.You have simplified the process.

I’m so glad I found GradCoach. Excellent information, Clear explanation, and Easy to follow, Many thanks Derek!

You’re welcome, Maithe. Good luck writing your literature review 🙂

Thank you Coach, you have greatly enriched and improved my knowledge

Great piece, so enriching and it is going to help me a great lot in my project and thesis, thanks so much

This is THE BEST site for ANYONE doing a masters or doctorate! Thank you for the sound advice and templates. You rock!

Thanks, Stephanie 🙂

This is mind blowing, the detailed explanation and simplicity is perfect.

I am doing two papers on my final year thesis, and I must stay I feel very confident to face both headlong after reading this article.

thank you so much.

if anyone is to get a paper done on time and in the best way possible, GRADCOACH is certainly the go to area!

This is very good video which is well explained with detailed explanation

Thank you excellent piece of work and great mentoring

Thanks, it was useful

Thank you very much. the video and the information were very helpful.

Good morning scholar. I’m delighted coming to know you even before the commencement of my dissertation which hopefully is expected in not more than six months from now. I would love to engage my study under your guidance from the beginning to the end. I love to know how to do good job

Thank you so much Derek for such useful information on writing up a good literature review. I am at a stage where I need to start writing my one. My proposal was accepted late last year but I honestly did not know where to start

Like the name of your YouTube implies you are GRAD (great,resource person, about dissertation). In short you are smart enough in coaching research work.

This is a very well thought out webpage. Very informative and a great read.

Very timely.

I appreciate.

Very comprehensive and eye opener for me as beginner in postgraduate study. Well explained and easy to understand. Appreciate and good reference in guiding me in my research journey. Thank you

Thank you. I requested to download the free literature review template, however, your website wouldn’t allow me to complete the request or complete a download. May I request that you email me the free template? Thank you.

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Literature Review versus Literature Survey. What is the difference?

I have read several articles about literature reviews. At the same time I found some guides about literature surveys . I am confused... how is a literature survey different from a literature review? What is the standard procedure to conduct a literature survey without making it a literature review?

• research-process
• literature-review
• literature-search

• 2 Welcome to Academia.SE. You have a couple of different questions in your post. We encourage multiple posts for multiple questions. See our tour and help center pages. Your questions about literature surveys and reviews are closely related and match the title. You should make a second post about how to pursue research given your background, since that it unrelated. –  Ben Norris Commented Dec 26, 2013 at 14:11

2 Answers 2

Reviewing the literature relevant to a given field is a standard part of doing research, as this serves to put your work into the context of the larger discipline in which you are working.

If there is an actual difference between the "literature survey" and the "literature review," it's that the latter can serve as a paper in and of itself, and is much more extensive than a literature survey, which is typically a major part of the introduction of a research paper.

The literature review as a standalone article could be compared to a "curated" overview of the literature in the field—who has done what, how do papers relate to one another, and what are the most important present and (possibly) future directions of work in such a field. Such papers can also be considerably longer than a traditional research paper, and some reviews might cite as many as a thousand references!

In comparison, the literature survey of a standard research article is usually much shorter (1-2 journal pages), and will not cite nearly as many papers (anywhere from 10 to 100, depending on the topic and the amount of relevant literature available).

• 2 Hi thanks for your comment. But I m still confused. I have seen survey papers are published and I have seen literature review sections in thesis. I mean aren't survey papers related to computer science are literature reviews ? –  Npn Commented Jan 1, 2014 at 14:51
• 3 In general, "review paper" is much more commonly used than "survey paper." Maybe CS prefers "survey paper," but essentially, there's no substantial difference between them. But every paper includes some sort of synopsis of existing literature; in a review or survey paper, it's the entire paper. –  aeismail Commented Jan 1, 2014 at 15:12
• Thanks ,I understood that review papers should be read to do a research. –  Npn Commented Jan 1, 2014 at 15:30

Well, I have written couple of survery/review articles published in prestigious journals here , here , and here and hence I think I can give you some hint on this question.

First View: One of the most important things to consider is that, these terms have been used differently in varied academic disciplines and even in some cases they are used interchangeably with negligible differences. Even in CS (my field), the way image processing scholars look at these terms may be different from networking researchers (I once experienced the comments I received from experts in image processing and realize how different they look at the works). So it might not be wrong if consider insignificant differences between these two terms.

What I describe here may be more applicable to CS. There are two different views at these terms that I describe here

Technically a feasible description around these two terms is that in survey works you should review the published papers and analyze, summarize, organize, and present findings in a novel way that can generate an original view to a certain aspect of the domain. For example, if researchers review the available research findings and conclude that electrical cars are emission-free vehicles, another researcher can review the same results and present an argument that building batteries themselves produce huge emission. The second contribution opens door for new research around emission-free production of car batteries. If we consider that survey paper is the result of literature survey, we can use the following definitions from CS journals.

• According to the definition of survey paper provided by IEEE Communications Surveys & Tutorials journal (one of the best CS journals), " The term survey, as applied here, is defined to mean a survey of the literature. A survey article should provide a comprehensive review of developments in a selected area ".
• In ACM Computing Survey (another prestigious CS journal), survey paper is described as “A paper that summarizes and organizes recent research results in a novel way that integrates and adds understanding to work in the field. A survey article emphasizes the classification of the existing literature, developing a perspective on the area, and evaluating trends.”
• In Elsevier journal of Computer Science Review, you will see here 4 that “Critical review of the relevant literature“ is required a component of every typical survey paper.

To summarize, these two terms can be distinguished using following notes (or maybe definitions)

Literature Survey: Is the process of analyzing, summarizing, organizing, and presenting novel conclusions from the results of technical review of large number of recently published scholarly articles. The results of the literature survey can contribute to the body of knowledge when peer-reviewed and published as survey articles

Literature Review: Is the process of technically and critically reviewing published papers to extract technical and scientific metadata from the presented contents. The metadata are usually used during literature survey to technically compare different but relevant works and draw conclusions on weaknesses and strengths of the works.

Second View: The second view over literature survey and review is that in survey, researchers usually utilize the author-provided contents available in the published works to qualitatively analyze and compare them with other related works. While in the former, you should not perform qualitative analysis. Rather it should be quantitative meaning that every research work under study should be implemented and benchmarked under certain criteria. The results of this benchmarking study can be used to compare them together and criticize or appreciate the works.

So basically you can look at current literature and find which approach is dominating in your field. Hope it helps. I try to revise it if I came a cross other points or useful comments here.

• 3 Up vote for Comprehensive answer. –  user3135645 Commented Dec 28, 2013 at 5:57
• 3 Nice answer (+1). I agree with you that the difference between the two terms is non-essential and preference in terminology depends mostly on the research discipline (field) and journal editors' preferences. Having said that, your distinction between the terms seems artificial, meaning that I don't see core logic that prevents applying both definitions to the opposite terms (unless I've missed some points). Also, I wanted to add that more accurate definitions should mention that literature survey or literature review is each both a process and an artifact , resulting from that process. –  Aleksandr Blekh Commented May 8, 2015 at 3:50

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What is a literature review?

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

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

Why is it important?

A literature review is important because it:

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

APA7 Style resources

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1. Choose a topic. Define your research question.

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

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

2. Decide on the scope of your review

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

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

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

Make a list of the databases you will search. 

Where to find databases:

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

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

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

Review the literature

Some questions to help you analyze the research:

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

Tips: 

• Review the abstracts carefully.  
• Keep careful notes so that you may track your thought processes during the research process.
• Create a matrix of the studies for easy analysis, and synthesis, across all of the studies.
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What is a Literature Review? How to Write It (with Examples)

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

Table of Contents

• What is the purpose of literature review? 
• a. Habitat Loss and Species Extinction: 
• b. Range Shifts and Phenological Changes: 
• c. Ocean Acidification and Coral Reefs: 
• d. Adaptive Strategies and Conservation Efforts: 

How to write a good literature review 

• Choose a Topic and Define the Research Question: 
• Decide on the Scope of Your Review: 
• Select Databases for Searches: 
• Conduct Searches and Keep Track: 
• Review the Literature: 
• Organize and Write Your Literature Review: 
• How to write a literature review faster with Paperpal? 
• Frequently asked questions 

What is a literature review?

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

What is the purpose of literature review?

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

1. 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. 

2. 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. 

Find academic papers related to your research topic faster. Try Research on Paperpal  

3. 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. 

4. 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. 

5. 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. 

6. 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. 

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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. 

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

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

Conducting a literature review

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

Choose a Topic and Define the Research Question:

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

Decide on the Scope of Your Review:

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

Select Databases for Searches:

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

Conduct Searches and Keep Track:

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

Review the Literature:

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

Organize and Write Your Literature Review:

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

Whether you’re exploring a new research field or finding new angles to develop an existing topic, sifting through hundreds of papers can take more time than you have to spare. But what if you could find science-backed insights with verified citations in seconds? That’s the power of Paperpal’s new Research feature!  

How to write a literature review faster with Paperpal?

Paperpal, an AI writing assistant, integrates powerful academic search capabilities within its writing platform. With the Research feature, you get 100% factual insights, with citations backed by 250M+ verified research articles, directly within your writing interface with the option to save relevant references in your Citation Library. By eliminating the need to switch tabs to find answers to all your research questions, Paperpal saves time and helps you stay focused on your writing.   

Here’s how to use the Research feature:  

• Ask a question: Get started with a new document on paperpal.com. Click on the “Research” feature and type your question in plain English. Paperpal will scour over 250 million research articles, including conference papers and preprints, to provide you with accurate insights and citations. 
• Review and Save: Paperpal summarizes the information, while citing sources and listing relevant reads. You can quickly scan the results to identify relevant references and save these directly to your built-in citations library for later access. 
• Cite with Confidence: Paperpal makes it easy to incorporate relevant citations and references into your writing, ensuring your arguments are well-supported by credible sources. This translates to a polished, well-researched literature review. 

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 good literature review is an ongoing process, and it may be necessary to revisit and update it as your research progresses. By combining effortless research with an easy citation process, Paperpal Research streamlines the literature review process and empowers you to write faster and with more confidence. Try Paperpal Research now and see for yourself.  

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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Research Methods

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

Literature Review

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

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

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

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

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

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

A literature review is important because it:

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

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

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

Not an essay 

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

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

A literature review serves several purposes. For example, it

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

As Kennedy (2007) notes*, it is important to think of knowledge in a given field as consisting of three layers. First, there are the primary studies that researchers conduct and publish. Second are the reviews of those studies that summarize and offer new interpretations built from and often extending beyond the original studies. Third, there are the perceptions, conclusions, opinion, and interpretations that are shared informally that become part of the lore of field. In composing a literature review, it is important to note that it is often this third layer of knowledge that is cited as "true" even though it often has only a loose relationship to the primary studies and secondary literature reviews.

Given this, while literature reviews are designed to provide an overview and synthesis of pertinent sources you have explored, there are several approaches to how they can be done, depending upon the type of analysis underpinning your study. Listed below are definitions of types of literature reviews:

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

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

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

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

Systematic Review      This form consists of an overview of existing evidence pertinent to a clearly formulated research question, which uses pre-specified and standardized methods to identify and critically appraise relevant research, and to collect, report, and analyse data from the studies that are included in the review. Typically it focuses on a very specific empirical question, often posed in a cause-and-effect form, such as "To what extent does A contribute to B?"

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

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

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

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

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

Systematic review or meta-analysis?

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

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

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

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

Not all systematic reviews contain meta-analysis. 

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

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

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

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

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• Next: Research Design >>
• Last Updated: Aug 21, 2023 4:07 PM
• URL: https://guides.lib.udel.edu/researchmethods

Archer Library

Quantitative research: literature review .

• Archer Library This link opens in a new window
• Research Resources handout This link opens in a new window
• Locating Books
• Library eBook Collections This link opens in a new window
• A to Z Database List This link opens in a new window
• Research & Statistics
• Literature Review Resources
• Citations & Reference

Exploring the literature review 

Literature review model: 6 steps.

Adapted from The Literature Review , Machi & McEvoy (2009, p. 13).

Your Literature Review

Step 2: search, boolean search strategies, search limiters, ★ ebsco & google drive.

1. Select a Topic

"All research begins with curiosity" (Machi & McEvoy, 2009, p. 14)

Selection of a topic, and fully defined research interest and question, is supervised (and approved) by your professor. Tips for crafting your topic include:

• Be specific. Take time to define your interest.
• Topic Focus. Fully describe and sufficiently narrow the focus for research.
• Academic Discipline. Learn more about your area of research & refine the scope.
• Avoid Bias. Be aware of bias that you (as a researcher) may have.
• Document your research. Use Google Docs to track your research process.
• Research apps. Consider using Evernote or Zotero to track your research.

Consider Purpose

What will your topic and research address?

In The Literature Review: A Step-by-Step Guide for Students , Ridley presents that literature reviews serve several purposes (2008, p. 16-17).  Included are the following points:

• Historical background for the research;
• Overview of current field provided by "contemporary debates, issues, and questions;"
• Theories and concepts related to your research;
• Introduce "relevant terminology" - or academic language - being used it the field;
• Connect to existing research - does your work "extend or challenge [this] or address a gap;" 
• Provide "supporting evidence for a practical problem or issue" that your research addresses.

★ Schedule a research appointment

At this point in your literature review, take time to meet with a librarian. Why? Understanding the subject terminology used in databases can be challenging. Archer Librarians can help you structure a search, preparing you for step two. How? Contact a librarian directly or use the online form to schedule an appointment. Details are provided in the adjacent Schedule an Appointment box.

2. Search the Literature

Collect & Select Data: Preview, select, and organize

Archer Library is your go-to resource for this step in your literature review process. The literature search will include books and ebooks, scholarly and practitioner journals, theses and dissertations, and indexes. You may also choose to include web sites, blogs, open access resources, and newspapers. This library guide provides access to resources needed to complete a literature review.

Books & eBooks: Archer Library & OhioLINK

Databases: Scholarly & Practitioner Journals

Review the Library Databases tab on this library guide, it provides links to recommended databases for Education & Psychology, Business, and General & Social Sciences.

Expand your journal search; a complete listing of available AU Library and OhioLINK databases is available on the Databases  A to Z list . Search the database by subject, type, name, or do use the search box for a general title search. The A to Z list also includes open access resources and select internet sites.

Databases: Theses & Dissertations

Review the Library Databases tab on this guide, it includes Theses & Dissertation resources. AU library also has AU student authored theses and dissertations available in print, search the library catalog for these titles.

Did you know? If you are looking for particular chapters within a dissertation that is not fully available online, it is possible to submit an ILL article request . Do this instead of requesting the entire dissertation.

Newspapers:  Databases & Internet

Consider current literature in your academic field. AU Library's database collection includes The Chronicle of Higher Education and The Wall Street Journal .  The Internet Resources tab in this guide provides links to newspapers and online journals such as Inside Higher Ed , COABE Journal , and Education Week .

Search Strategies & Boolean Operators

There are three basic boolean operators:  AND, OR, and NOT.

Used with your search terms, boolean operators will either expand or limit results. What purpose do they serve? They help to define the relationship between your search terms. For example, using the operator AND will combine the terms expanding the search. When searching some databases, and Google, the operator AND may be implied.

Overview of boolean terms

About the example: Boolean searches were conducted on November 4, 2019; result numbers may vary at a later date. No additional database limiters were set to further narrow search returns.

Database Search Limiters

Database strategies for targeted search results.

Most databases include limiters, or additional parameters, you may use to strategically focus search results.  EBSCO databases, such as Education Research Complete & Academic Search Complete provide options to:

• Limit results to full text;
• Limit results to scholarly journals, and reference available;
• Select results source type to journals, magazines, conference papers, reviews, and newspapers
• Publication date

Keep in mind that these tools are defined as limiters for a reason; adding them to a search will limit the number of results returned.  This can be a double-edged sword.  How? 

• If limiting results to full-text only, you may miss an important piece of research that could change the direction of your research. Interlibrary loan is available to students, free of charge. Request articles that are not available in full-text; they will be sent to you via email.
• If narrowing publication date, you may eliminate significant historical - or recent - research conducted on your topic.
• Limiting resource type to a specific type of material may cause bias in the research results.

Use limiters with care. When starting a search, consider opting out of limiters until the initial literature screening is complete. The second or third time through your research may be the ideal time to focus on specific time periods or material (scholarly vs newspaper).

★ Truncating Search Terms

Expanding your search term at the root.

Truncating is often referred to as 'wildcard' searching. Databases may have their own specific wildcard elements however, the most commonly used are the asterisk (*) or question mark (?).  When used within your search. they will expand returned results.

Asterisk (*) Wildcard

Using the asterisk wildcard will return varied spellings of the truncated word. In the following example, the search term education was truncated after the letter "t."

Explore these database help pages for additional information on crafting search terms.

• EBSCO Connect: Basic Searching with EBSCO
• EBSCO Connect: Searching with Boolean Operators
• EBSCO Connect: Searching with Wildcards and Truncation Symbols
• ProQuest Help: Search Tips
• ERIC: How does ERIC search work?

★ EBSCO Databases & Google Drive

Tips for saving research directly to Google drive.

Researching in an EBSCO database?

It is possible to save articles (PDF and HTML) and abstracts in EBSCOhost databases directly to Google drive. Select the Google Drive icon, authenticate using a Google account, and an EBSCO folder will be created in your account. This is a great option for managing your research. If documenting your research in a Google Doc, consider linking the information to actual articles saved in drive.

EBSCO Databases & Google Drive

EBSCOHost Databases & Google Drive: Managing your Research

This video features an overview of how to use Google Drive with EBSCO databases to help manage your research. It presents information for connecting an active Google account to EBSCO and steps needed to provide permission for EBSCO to manage a folder in Drive.

About the Video:  Closed captioning is available, select CC from the video menu.  If you need to review a specific area on the video, view on YouTube and expand the video description for access to topic time stamps.  A video transcript is provided below.

• EBSCOhost Databases & Google Scholar

Defining Literature Review

What is a literature review.

A definition from the Online Dictionary for Library and Information Sciences .

A literature review is "a comprehensive survey of the works published in a particular field of study or line of research, usually over a specific period of time, in the form of an in-depth, critical bibliographic essay or annotated list in which attention is drawn to the most significant works" (Reitz, 2014). 

A systemic review is "a literature review focused on a specific research question, which uses explicit methods to minimize bias in the identification, appraisal, selection, and synthesis of all the high-quality evidence pertinent to the question" (Reitz, 2014).

Recommended Reading

About this page

EBSCO Connect [Discovery and Search]. (2022). Searching with boolean operators. Retrieved May, 3, 2022 from https://connect.ebsco.com/s/?language=en_US

EBSCO Connect [Discover and Search]. (2022). Searching with wildcards and truncation symbols. Retrieved May 3, 2022; https://connect.ebsco.com/s/?language=en_US

Machi, L.A. & McEvoy, B.T. (2009). The literature review . Thousand Oaks, CA: Corwin Press: 

Reitz, J.M. (2014). Online dictionary for library and information science. ABC-CLIO, Libraries Unlimited . Retrieved from https://www.abc-clio.com/ODLIS/odlis_A.aspx

Ridley, D. (2008). The literature review: A step-by-step guide for students . Thousand Oaks, CA: Sage Publications, Inc.

Archer Librarians

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• v.9(7); 2013 Jul

Ten Simple Rules for Writing a Literature Review

Marco pautasso.

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

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

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

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

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

Rule 1: Define a Topic and Audience

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

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

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

Rule 2: Search and Re-search the Literature

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

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

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

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

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

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

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

Rule 3: Take Notes While Reading

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

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

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

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

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

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

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

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

Rule 6: Be Critical and Consistent

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

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

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

Rule 7: Find a Logical Structure

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

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

Rule 8: Make Use of Feedback

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

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

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

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

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

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

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

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

Acknowledgments

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

Funding Statement

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

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Literature review.

• What is a Literature Review?
• What is Its Purpose?
• 1. Select a Topic
• 2. Set the Topic in Context
• 3. Types of Information Sources
• 4. Use Information Sources
• 5. Get the Information
• 6. Organize / Manage the Information
• 7. Position the Literature Review
• 8. Write the Literature Review

A literature review is a comprehensive summary of previous research on a topic. The literature review surveys scholarly articles, books, and other sources relevant to a particular area of research.  The review should enumerate, describe, summarize, objectively evaluate and clarify this previous research.  It should give a theoretical base for the research and help you (the author) determine the nature of your research.  The literature review acknowledges the work of previous researchers, and in so doing, assures the reader that your work has been well conceived.  It is assumed that by mentioning a previous work in the field of study, that the author has read, evaluated, and assimiliated that work into the work at hand.

A literature review creates a "landscape" for the reader, giving her or him a full understanding of the developments in the field.  This landscape informs the reader that the author has indeed assimilated all (or the vast majority of) previous, significant works in the field into her or his research. 

 "In writing the literature review, the purpose is to convey to the reader what knowledge and ideas have been established on a topic, and what their strengths and weaknesses are. The literature review must be defined by a guiding concept (eg. your research objective, the problem or issue you are discussing, or your argumentative thesis). It is not just a descriptive list of the material available, or a set of summaries.( http://www.writing.utoronto.ca/advice/specific-types-of-writing/literature-review )

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Literature Review for Grad Students in Education

• Library Guide: Literature Review

Introduction to Literature Review

If you cannot access the above video, you can watch it here

What is a Literature Review

  The purpose of an academic research paper is to express and document an original idea. Literature Review is one part of that process of writing a research paper. In a research paper, you use the literature as a starting point, a building block and as evidence of a new insight. The goal of the literature review is only to summarize and synthesize the arguments and ideas of others. You should not present your original idea.

The reading that you do as part of a literature review will answer one of two questions:

“What do we know about the subject of our study?” “Based on what we know, what conclusions can we draw about the research question?”

Notice that the conclusions to be drawn are about the research question , as opposed to a novel theory. 

The types of conclusions about your research question that you want to discover are: ❖ gaps in the knowledge on a subject area ❖ questions about your topic that remain unanswered ❖ areas of disagreement in your subject area that need to be settled.

Purpose of Literature Review?

There are a number of differing descriptions of the purpose of a literature review. Primarily it is a tool for

❖ researching the history of scholarly publication on a topic

❖ becoming aware of the scholarly debate within a topic

❖  a summary or restatement of conclusions from research which has been published

❖ synthesis or recombining, comparing and contrasting, the ideas of others.

❖ evaluate sources

❖ search for gaps

A literature review provides a comprehensive overview of a topic , supporting the fundamental purpose of a research paper, which is to present a new point of view or insight on a topic. The literature review supports the new insight. It does not present or argue for it.

Structure of Literature Review

• Choose a topic
• Find research
• Organize sources/notetaking
• Evaluate Sources
• Synthesize: think of this phase as a narrative . 

There are various ways of organizing the literature review process- if one of these seems closer to your purpose, try it out.

Different Types of Literature Sources

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Frequently asked questions

What is the purpose of a literature review.

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

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

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

Frequently asked questions: Academic writing

A rhetorical tautology is the repetition of an idea of concept using different words.

Rhetorical tautologies occur when additional words are used to convey a meaning that has already been expressed or implied. For example, the phrase “armed gunman” is a tautology because a “gunman” is by definition “armed.”

A logical tautology is a statement that is always true because it includes all logical possibilities.

Logical tautologies often take the form of “either/or” statements (e.g., “It will rain, or it will not rain”) or employ circular reasoning (e.g., “she is untrustworthy because she can’t be trusted”).

You may have seen both “appendices” or “appendixes” as pluralizations of “ appendix .” Either spelling can be used, but “appendices” is more common (including in APA Style ). Consistency is key here: make sure you use the same spelling throughout your paper.

The purpose of a lab report is to demonstrate your understanding of the scientific method with a hands-on lab experiment. Course instructors will often provide you with an experimental design and procedure. Your task is to write up how you actually performed the experiment and evaluate the outcome.

In contrast, a research paper requires you to independently develop an original argument. It involves more in-depth research and interpretation of sources and data.

A lab report is usually shorter than a research paper.

The sections of a lab report can vary between scientific fields and course requirements, but it usually contains the following:

• Title: expresses the topic of your study
• Abstract: summarizes your research aims, methods, results, and conclusions
• Introduction: establishes the context needed to understand the topic
• Method: describes the materials and procedures used in the experiment
• Results: reports all descriptive and inferential statistical analyses
• Discussion: interprets and evaluates results and identifies limitations
• Conclusion: sums up the main findings of your experiment
• References: list of all sources cited using a specific style (e.g. APA)
• Appendices: contains lengthy materials, procedures, tables or figures

A lab report conveys the aim, methods, results, and conclusions of a scientific experiment . Lab reports are commonly assigned in science, technology, engineering, and mathematics (STEM) fields.

The abstract is the very last thing you write. You should only write it after your research is complete, so that you can accurately summarize the entirety of your thesis , dissertation or research paper .

If you’ve gone over the word limit set for your assignment, shorten your sentences and cut repetition and redundancy during the editing process. If you use a lot of long quotes , consider shortening them to just the essentials.

If you need to remove a lot of words, you may have to cut certain passages. Remember that everything in the text should be there to support your argument; look for any information that’s not essential to your point and remove it.

To make this process easier and faster, you can use a paraphrasing tool . With this tool, you can rewrite your text to make it simpler and shorter. If that’s not enough, you can copy-paste your paraphrased text into the summarizer . This tool will distill your text to its core message.

Revising, proofreading, and editing are different stages of the writing process .

• Revising is making structural and logical changes to your text—reformulating arguments and reordering information.
• Editing refers to making more local changes to things like sentence structure and phrasing to make sure your meaning is conveyed clearly and concisely.
• Proofreading involves looking at the text closely, line by line, to spot any typos and issues with consistency and correct them.

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

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

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

Avoid citing sources in your abstract . There are two reasons for this:

• The abstract should focus on your original research, not on the work of others.
• The abstract should be self-contained and fully understandable without reference to other sources.

There are some circumstances where you might need to mention other sources in an abstract: for example, if your research responds directly to another study or focuses on the work of a single theorist. In general, though, don’t include citations unless absolutely necessary.

An abstract is a concise summary of an academic text (such as a journal article or dissertation ). It serves two main purposes:

• To help potential readers determine the relevance of your paper for their own research.
• To communicate your key findings to those who don’t have time to read the whole paper.

Abstracts are often indexed along with keywords on academic databases, so they make your work more easily findable. Since the abstract is the first thing any reader sees, it’s important that it clearly and accurately summarizes the contents of your paper.

In a scientific paper, the methodology always comes after the introduction and before the results , discussion and conclusion . The same basic structure also applies to a thesis, dissertation , or research proposal .

Depending on the length and type of document, you might also include a literature review or theoretical framework before the methodology.

Whether you’re publishing a blog, submitting a research paper , or even just writing an important email, there are a few techniques you can use to make sure it’s error-free:

• Take a break : Set your work aside for at least a few hours so that you can look at it with fresh eyes.
• Proofread a printout : Staring at a screen for too long can cause fatigue – sit down with a pen and paper to check the final version.
• Use digital shortcuts : Take note of any recurring mistakes (for example, misspelling a particular word, switching between US and UK English , or inconsistently capitalizing a term), and use Find and Replace to fix it throughout the document.

If you want to be confident that an important text is error-free, it might be worth choosing a professional proofreading service instead.

Editing and proofreading are different steps in the process of revising a text.

Editing comes first, and can involve major changes to content, structure and language. The first stages of editing are often done by authors themselves, while a professional editor makes the final improvements to grammar and style (for example, by improving sentence structure and word choice ).

Proofreading is the final stage of checking a text before it is published or shared. It focuses on correcting minor errors and inconsistencies (for example, in punctuation and capitalization ). Proofreaders often also check for formatting issues, especially in print publishing.

The cost of proofreading depends on the type and length of text, the turnaround time, and the level of services required. Most proofreading companies charge per word or page, while freelancers sometimes charge an hourly rate.

For proofreading alone, which involves only basic corrections of typos and formatting mistakes, you might pay as little as $0.01 per word, but in many cases, your text will also require some level of editing , which costs slightly more.

It’s often possible to purchase combined proofreading and editing services and calculate the price in advance based on your requirements.

There are many different routes to becoming a professional proofreader or editor. The necessary qualifications depend on the field – to be an academic or scientific proofreader, for example, you will need at least a university degree in a relevant subject.

For most proofreading jobs, experience and demonstrated skills are more important than specific qualifications. Often your skills will be tested as part of the application process.

To learn practical proofreading skills, you can choose to take a course with a professional organization such as the Society for Editors and Proofreaders . Alternatively, you can apply to companies that offer specialized on-the-job training programmes, such as the Scribbr Academy .

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Writing a Literature Review

• Steps for Conducting a Lit Review
• Finding "The Literature"
• Organizing/Writing
• Peer Review
• Citation/Style Guides

Reference & Instruction Librarian

What is a Literature Review?

A literature review is not:

• just a summary of the sources
• a grouping of broad, unrelated sources
• a compilation of everything that has been written on a particular topic
• literature criticism (think English) or a book review.

So, what is it then?

A literature review :

• Surveys all of the scholarship that has been written about a particular topic (your research question).
• Provides a description , summary , and evaluation of each scholarly work.
• Synthesizes and organizes the previous research by comparing and contrasting the findings or methodology of those previous writings.

"A literature review is an account of what has been published on a topic by accredited scholars and researchers. Occasionally, you will be asked to write one as a separate assignment, ..., but more often, it is part of the introduction to an essay, research report, or thesis. In writing the literature review, you aim to convey to your reader what knowledge and ideas have been established on a topic and their strengths and weaknesses. As a piece of writing, the literature review must be defined by a guiding concept (e.g., your research objective, the problem or issue you are discussing, or your argumentative thesis). It is not just a descriptive list of the material available or a set of summaries."  

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

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

Why is it important?

A literature review is important because it:

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

Where Can I Find a Lit Review?

The Literature Review portion of a scholarly article is usually close to the beginning. It often follows the introduction , or may be combined with the introduction. The writer may discuss his or her research question first, or may choose to explain it while surveying previous literature.

If you are lucky, there will be a section heading that includes " literature review ".  If not, look for the section of the article with the most citations or footnotes .

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Resources on the web.

• Writing a Literature Review Brendan Rapple, Boston College Libraries
• Next: Steps for Conducting a Lit Review >>
• Last Updated: Jun 18, 2024 1:28 PM
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Estimation of the Prevalence of Progressive Fibrosing Interstitial Lung Diseases: Systematic Literature Review and Data from a Physician Survey

Affiliations.

• 1 Interstitial Lung Disease Program, Department of Medicine, National Jewish Health, Denver, CO, USA. [email protected].
• 2 Boehringer Ingelheim International GmbH, Ingelheim am Rhein, Germany.
• 3 Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, CT, USA.
• 4 Boehringer Ingelheim Pharma GmbH & Co. KG, Ingelheim am Rhein, Germany.
• 5 Department of Respiratory Medicine, Hospices Civils de Lyon, National Reference Center for Rare Pulmonary Diseases, Louis Pradel Hospital, Lyon, France.
• 6 Fondazione Policlinico Universitario A. Gemelli IRCCS, Università Cattolica del Sacro Cuore, Rome, Italy.
• 7 Department of Rheumatology, Oslo University Hospital, Oslo, Norway.
• 8 National Reference Center for Rare Pulmonary Diseases, Louis Pradel Hospital, UMR 754, University Claude Bernard Lyon 1, Lyon, France.
• PMID: 33315170
• PMCID: PMC7889674
• DOI: 10.1007/s12325-020-01578-6

Some patients with interstitial lung diseases (ILDs) other than idiopathic pulmonary fibrosis exhibit a progressive clinical phenotype. These chronic progressive fibrosing ILDs have a variety of underlying diseases, and their prevalence is currently unknown. Here we carry out the first systematic review of literature on the prevalence of fibrosing ILDs and progressive fibrosing ILDs using data from physician surveys to estimate frequency of progression among different ILDs. We searched MEDLINE and Embase for studies assessing prevalence of ILD, individual ILDs associated with fibrosis and progressive fibrosing ILDs. These were combined with data from previously published physician surveys to obtain prevalence estimates of each chronic fibrosing ILD with a progressive phenotype and of progressive fibrosing ILDs overall. We identified 16 publications, including five reporting overall ILD prevalence, estimated at 6.3-76.0 per 100,000 people in Europe (four studies) and 74.3 per 100,000 in the USA (one study). In total, 13-40% of ILDs were estimated to develop a progressive fibrosing phenotype, with overall prevalence estimates for progressive fibrosing ILDs of 2.2-20.0 per 100,000 in Europe and 28.0 per 100,000 in the USA. Prevalence estimates for individual progressive fibrosing ILDs varied up to 16.7 per 100,000 people. These conditions represent a sizeable fraction of chronic respiratory disorders and have a high unmet need.

Keywords: Epidemiology; Fibrosis; Interstitial lung disease; Prevalence; Progressive.

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Conceptual diagram of prevalence estimation…

Conceptual diagram of prevalence estimation for progressive fibrosing ILDs [5]. Figure is not…

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Recent trends in crowd management using deep learning techniques: a systematic literature review

• Open access
• Published: 20 June 2024

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• Aisha M. Alasmari 1 ,
• Norah S. Farooqi 2 , 3 &
• Youseef A. Alotaibi 4  

Crowd management has become an integral part of urban planning in abnormality in the crowd and predict its future issues. Big data in social media is a rich source for researchers in crowd data analysis. In this systematic literature review (SLR), modern societies. It can organize the flow of the crowd, perform counting, recognize the related works are analyzed, which includes crowd management from both global and local sides (Hajj events—Saudi Arabia) based on deep learning (DL) methods. This survey concerns crowd management research published from 2010 to 2023. It has specified 45 primary studies that accomplish the objectives of the research questions (RQs), namely, investigation of the taxonomies, approaches, and comprehensive studies of crowd management both globally and locally and focusing on the most commonly used techniques of DL. We found both supervised and unsupervised DL techniques have achieved high accuracy, with different strengths and weaknesses for each approach. A lot of these studies discuss aspects of scene analysis of crowds, that are captured by installed cameras in the place. However, there is a dilemma regarding exploiting data provided on social media to use in the crowd analysis domain. Which we believe that the analysis of big data may raise crowd management to the upper level of enhancement. To this end, motivated by the findings of this SLR. The primary purpose of this review is strived to illustrate obstacles and dilemmas in crowd analysis fields to provide a road map for future researchers. Furthermore, it aims to find research gaps existing to focus on it in the future studies. The results indicate that the lack of Hajj research, especially in sentiment analysis and the study of the pilgrims' behavior.

Avoid common mistakes on your manuscript.

1 Introduction

A crowd is defined as a gathering of humans in the same area. If the number of individuals exceeds normal conditions, congestion becomes a concern regarding safety, health, or what may affect human choices due to herd culture. The concept of congestion differs depending on the culture of communities.

For example, gathering over 100 people in India is considered normal, while in other countries like Canada it may be considered a crowd [ 1 ]. Analysis, detection, management, and monitoring of crowds are a growing trend in computer sciences to study the behavior of human crowds in any event. Human gatherings may happen due to religious rituals (such as Hajj for Muslims at Makkah, Saudi Arabia, and Kumbh Mela for Hindus at Haridwar, India), sporting events (such as FIFA World Cup and Olympic Games), concerts, or annual carnivals (such as Carnival Parade and Riyadh Season [ 2 ]). Moreover, demonstrations, popular protests, and political or social riots (such as a political rally in Los Angeles [ 3 ]) are considered gatherings that may impact a crowd risk index and bring many unexpected reactions. Each type of human gathering has its own features: purposes of the individuals, behavior, place, and time. To avoid accidents, the organizers must perform prior analyses and studies for the mass gatherings.

Crowd analysis is one of the most crucial tools for crowd management [ 4 ]. Hence, crowd management requires profound and comprehensive plans in advance and flexible and agile strategies to take vigorous and accurate action if unexpected incidents occur.

Examples of common general issues in crowd management in the context of urban planning for smart cities are traffic, crowded pedestrians, pollution, energy consumption, etc. In urban planning for smart cities, it can be possible to predict crowd behavior abnormalities and the future evolution of these situations in order to prevent them and do the best decision-making and planning. In addition, the capacity to monitor, control, and predict the behavior of crowds is a fundamental enabling driver. Where predicting such notifications can be of effective help in a large variety of situations, such as organizing events, organizing pedestrians, managing situations of emergency, or even tracking how the pandemic spread through the urban areas. A violation of crowd management will lead to several consequences that may result in a loss of lives or property, besides the loss of people's confidence in the organization responsible for organizing the event in the future.

Billions of people around the world now have accounts on social media platforms to freely express their beliefs, opinions, or impressions about some things. This huge streamed data gives an opportunity for researchers in the data analysis domain to explore about behavior of people through their text content [ 5 ]. We believe big data may open other horizons in crowd management. Abnormal behavior detection or crowd-counting is now possible through these data. However, a lot of works of crowd management lack to attention the textual data analysis aspect of social media, especially in local crowd management works.

This review has conducted extensive examinations in this area, however, a lot of works for crowd management still have limited in using one particular data namely visual data. The main drawbacks and limitations faced by current crowd management are discussed as follows:

Existing works for crowd management are currently recurrent, meaning they do not take into account the collected data sources changes about the people during the behavior detection. Hence, current models may not fully apply on the multi-dataset, limiting their effectiveness with similar scenarios.

Collecting the datasets for existing models requires consideration of equipment or hardware such as installed cameras, live streaming channels, etc., that increases the cost of running the processes and maintenance besides the computational cost of the models.

Most of the existing research uses the same video dataset to study the behavior detection of crowds. Therefore, limiting their model's effectiveness with learning new patterns.

There is no dependency on data of social networks as one of the sources of data collection.

For these reasons, the objectives of this SLR are an overall survey of the concept of crowd management from two perspectives, crowd management in various world events and Hajj events especially. The authors endeavor through this work to make it a great reference point for other researchers in the crowd management domain. This systematic review provides a theoretical understanding of deep-learning techniques used in the various branches of crowd management. The review will also highlight factors that impact crowd modeling works such as limited patterns of datasets, applications generalizability, and evaluation metrics. Moreover, the review highlights the importance of urban planning integration, which leads to improving the quality of life for individuals and society. This work emphasizes is also necessary to draw attention to exploiting the various big data in social media as an important tributary of building novel datasets with a diversity of knowledge and patterns. The main contribution of the paper is to examine and summarize the state-of-art technologies and methodologies in the behavior detection of a crowd to apply them in Hajj research to improve the experience of pilgrims and provided services. Hence, the review scope determines three main points as follows: First, our survey summarizes the various technologies, approaches, and models that have been utilized to design and execute solutions to detect behaviors that control and monitor the crowds during any world events. Next, the survey summarizes and review the methods used for Hajj issues. Last, our survey covers shortcomings or defects in previous Hajj studies and how other research related to various crowd management may help improve the management, monitoring, and control of crowds during the Hajj season.

This paper aims to highlight these three points through a comprehensive literature survey and focuses on crowd behavior detection for crowd surveillance and prediction. The purpose of RQs is to give a high level of precise topics which is extremely focused on examining the previous literature. The RQs have extreme significance in an SLR, due to controlling the distinguishing and identification of primary research needed to be involved in the review. Consequently, well-defined, logical, interesting, and relevant research questions should be articulated [ 6 ], at the discretion of the authors [ 7 ]. The review's contributions will answer the following research questions (RQs):

RQ1: What is the taxonomy of crowd analysis for Deep Learning-based works?

RQ1 aims to find the taxonomies of previous studies based on deep learning (DL) approaches. The answer is explained in Sect. 3 : “Related Work.”

RQ2: What are the approaches used in crowd management works?

RQ2 aims to identify the DL approaches used for crowd management at various places around the world. The answer is explained in Sect. 4 : “A Comprehensive Study of Crowd Management.”

RQ3: What are the approaches used in Hajj crowd management works?

RQ3 aims to identify the DL approaches used for crowd management during the Hajj season. The answer appears in Sect. 4.6 : “Crowd Management at Hajj Event.”

RQ4: What are the most commonly used techniques and algorithms in prior works? and the challenges faced them?

RQ4 aims to discover the most used techniques and algorithms of DL in prior works for crowd management at global around the world and local scope during the Hajj season. The answer is explained in Sect. 5 : “Analysis of Comprehensive Study of Crowd Management”.

In conclusion, a systematic review of the research studies in terms of global perspectives on crowd management can help provide insights into the scope and development of this field in Hajj events and establish a comprehensive conceptual framework, which can ultimately improve the pilgrims' experience and the religious rites practices comfortably. The rest of this paper is organized as follows. Section 2 explains the research methodology. Taxonomies of previous studies based on DL approaches appear in Sect. 3 . A summarization of the current methodologies of crowd management at various events appears in Sect. 4 . Section 5 summarizes the current approaches utilized during the Hajj events from 2010 until 2023. Section 5 displays analysis of comprehensive study of crowd management also analysis of crowd management at hajj event. The authors discuss gaps and directions in Hajj studies and compare them with state-of-the-art research on other events in Sect. 6 . Finally, Sect. 7 presents a conclusion of the survey and discuss future work approaches are presented.

2 Research methodology

This section offers the methodology followed to complete this research. The paper [ 8 ] has presented several steps for writing a systematic literature review (SLR). An SLR draws a thoughtful methodology to determine the mechanisms of exclusion and inclusion criteria for scientific papers articles. Moreover, the guidelines of SLR identify gaps in current research and extracts final results based on our RQs. This review was performed in four phases, and the following sections explain each phase. Figure  1 shows the review protocol that illustrates the plan to complete this paper.

Protocol of review to complete this paper

2.1 Phase (1): preliminary search

Initially, verification of previous related work. The authors checked that no SLR covers the topic of crowd management by the analysis of textual data of users. The enormous amount of data spread every second across various Social Media Platforms (SMP), such as Twitter, Facebook, Instagram, and many others, is adequate evidence that aspect extraction of textual data to study it has become urgent. Therefore, the authors use this review of the outputs from past related works to address their gaps and shortcomings.

Second, identification of relevant online databases. The authors selected the superior databases that are interested in computer science: SpringerLink, Science-Direct, IEEE Xplore Digital Library, ACM Digital Library, MDPI, Google Scholar and Web of Sciences. Next, the authors determined the starting and ending publishing dates for the articles in the review. This review selected 2010 as the starting date and 2023 as the ending date. This timeframe was chosen because it is the growth of AI research. In the early 2010s, researchers began to use neural networks for speech recognition and image processing, which has significantly improved performance and then spread neural networks widely in the commercial, healthcare, finance, transportation, and crowd control fields. In 2013, the field of computer vision began to transition using neural networks. The same transition occurred in natural language processing in 2016 until today [ 9 ]. In the future, similar revolutions will occur in visual robotics and many other AI fields. The searches were narrowed to journals published during the desired span. Table 1 presents the number of scientific paper articles obtained from each database and clarification for the initial and final results of the search.

Third, detection of keywords and their synonyms used in crowd management. Keywords of research that have been applied for finding articles in these databases are as follows: Crowd AND (“Management” OR “Analysis” OR “Tracking” OR “Monitoring” OR “Controlling” OR “Counting” OR “Density Estimation” OR “Abnormality Detection” OR “Behavior Analysis” OR “Crowd flow” OR “Mass Gathering” OR “Congestion Analysis Detection” OR “Predicting Human Behaviors” OR “Pedestrian”) AND (“Sentiment Analysis” OR “Opinion mining”) AND (“Deep Learning” OR “Machine Learning” OR “Convolutional Neural Network” OR “CNN”) AND (“Social Media” OR “Twitter”) AND (“Hajj” OR “Makkah” OR “Mecca”).

2.2 Phase (2): investigative search

Criteria of inclusion and exclusion. We selected strict criteria to pick studies to be included in our review and those that must be excluded. The objective of inclusion criteria is to choose all papers describing the concept of opinions mining of crowds through DL techniques. Otherwise, it will be exclusion criteria of papers in order to limit the scope of the review and remain focused on the targeted RQs. Inclusion criteria are as follows:

Papers that were published from the year 2010 to 2023.

Papers written in the English language.

Papers selected for publication in a journal.

In terms of exclusion criteria are as follows:

Papers that are from a conference or a book.

Papers that do not extract specific databases.

Duplicate papers.

Papers that contain irrelevant keywords.

Figure  2 illustrates the criteria of exclusion and inclusion followed for this review.

Criteria of exclusion and inclusion for this review

2.3 Phase (3): study quality assessment

Quality assessment (QA) of selected studies is a critical strategy for data synthesis and analysis to avoid bias and increase the selection of literature. The QA questions estimate the relevance, truthfulness, and rigorousness of the selected studies. Every one of the questions has only three optional answers derived from the study in [ 10 ], where “YES” = 1, “NO” = 0, and “Partly” = 0.5. as shown in Table  2 . Besides the QA questions, it has placed other criteria to prevent potential biases. For instance, clarification of studies included and excluded accurately. Comprehensive examination during the selection and publication stages several times. Formulating review protocols according to the sober methodology [ 8 ]. The assessment selection was from one of the researchers of this paper. The researchers have followed the mentioned standards rigorously to avoid the dominance of individual personal opinions and potentially biased decisions. The included papers should be achieved at least 2 of QA, otherwise, it will be overridden, as shown in Table  3 .

2.4 Phase (4): analysis of search

Transparency during the assessment process is conceived as a non-functional quality of the stakeholders of projects. Transparency is an essential factor that can be performed to ensure the stakeholder's satisfaction with the quality of assessment [ 11 ]. Therefore, transparency requirements should be clarified regarding the inclusion and exclusion criteria that are used for selecting the primary studies, which have to fulfill them to sustainability for quality and transparency of research. Consequently, our methodology identified 45 studies that we applied to the assessment of objectives of this paper. Figure  3 illustrates the peak appearance of research in the publication year 2021. Whereas Fig.  4 displays the percentage of papers obtained from each database.

Distribution of the papers from 2010 to 2023

Percentage of papers obtained from each database

According to our criteria of exclusion and inclusion papers, as shown in the Figs.  3 and 4 , the papers started spread from 2014 to 2023, the researchers note that the publication was at the highest levels in 2019, 2020, and 2021 years. In addition, the SpringerLink database was achieved highest published, whereas ACM database was got the lowest published than other databases. Finally, after applying the above filters of standards did not obtain unique papers in both Google Scholar and Web of Science. Most of the existing papers were duplicates of papers in another publishing database or did not meet our requirements and standards.

3 Related work

Since the last decade, the preceding reviews have illustrated that crowd analysis is studied from several different aspects. For instance, there are computer science [ 12 ], sociology-based [ 13 ], biology-based [ 14 ], and physics-based [ 15 ] approaches. Some of these works concentrate on the research axis, and others concentrate on various sides of the research axes as subtopics. In terms of computer science, there are two main types: traditional approaches from the period of pre-DL methods and DL methods [ 16 ]. DL techniques are a valuable addition to constructing the ideal models in many fields like Defect Prediction in Software (DeP) [ 17 ], improving Search-Based Software Testing (SBST) [ 18 ], improving the mechanisms of Detection of DDoS Attack[ 19 ], remotely imagery classification for unmanned aerial vehicles (UAV) [ 20 ]. Generally, achieving high-level intelligence, high robustness, high accuracy, big data, and low power consumption for artificial intelligence approaches are considered the critical challenges that faces the researchers. The authors in [ 21 , 22 , 23 , 24 ] have sought to address these issues. In this section, our review discusses the most other important reviews. Those that focus on the DL side and large datasets. DL algorithms are more properly suited and effective to address concerns related to the variety, volume, and accuracy of big data analytics. Furthermore, DL algorithms inherently exploit the availability of enormous amounts of data to explore and understand the higher-level complexities of various data patterns. Thus, minimizing the need for human experts to extract features from data [ 25 ].

The reviews aim to offer a panoramic vision of crowd analysis in the deep learning domain. Each previous survey was studied and organized into subsections to classify its authors.

Grant and Flynn [ 26 ] divided crowd analysis into two wide classes, crowd behavior analysis and crowd counting, which include several subsections. Crowd behavior analysis has four subsections: abnormal behavior analysis, dominant motion extraction, crowd analysis and tracking, and group behavior analysis. It focuses on behavior detection of individual scenes at first. Then, it describes group behavior within a crowd, crowd motion, and detection of an abnormal event. On the other hand, crowd counting contains six subsections: density mapping, joint detection and counting, line counting, texture-level analysis, object-level analysis, and pixel-level analysis. It focuses on behavior detection of individual scenes at first. Then, it describes group behavior within a crowd, crowd motion, and detection of an abnormal event. On the other hand, crowd counting contains six subsections: density mapping, joint detection and counting, line counting, texture-level analysis, object-level analysis, and pixel-level analysis.

It discussed the metrics used to estimate the density of a crowd, the Level of Service (LoS), and traffic flow. Moreover, they displayed datasets available according to crowd activity video research. Datasets fell into five categories: crowd counting (UCF_CC_50 dataset [ 69 ], UCSD dataset [ 70 ], and WorldExpo’10 Dataset [ 71 ]), group detection (Collective Motion dataset, The Museum Visitors dataset, student003 dataset, The Mall dataset [ 72 ], and the Grand Central Station dataset), behavior understanding (PETS2009 dataset [ 73 ], Collective Activity dataset, and The Unusual Crowd Activity dataset), holistic crowd movement (Chinese University of Hong Kong dataset (CUHK) [ 74 , 75 ], The Meta-Tracking dataset, Data-Driven Crowd Analysis dataset, and Crowd Segmentation dataset), and synthetic (The Agoraset dataset, Seven Environments/scenes).

Tripathi et al. [ 1 ] concentrated on studies that included Convolutional Neural Networks (CNNs). The authors have divided the previous studies into four classes: The first class summarizes influential portions of the CNN for handling crowd behavior analysis. The second class summarizes the primary studies proposed that focus on CNNs. The third summarizes studies that use CNNs incorporated with other architectures from deep learning. It includes four types, crowd counting, crowd density estimation, crowded abnormality analysis, and crowded scene analysis. The fourth summarizes studies that use CNNs to extract features and classifiers. Moreover, the authors highlighted opportunities, features, and challenges for future research in the crowd analysis domain. Furthermore, the authors displayed some of the datasets used in CNN-based crowd analysis: WorldEx po10, PETS2009 [ 73 ], WorldExpo’10 [ 71 ], Pedestrian dataset, UCLA, Dyntex++, DynTex, (WWW) crowd dataset, BEHAVE, NUS-HGA, UCF_CC_50 [ 69 ], ShanghaiTech [ 76 ], UMN [ 77 ], Mall [ 72 ], Rare Events Dataset (RED) [ 78 ], and City Dataset [ 79 ].

Li et al. [ 80 ] summarized the main concepts of crowd behavior analysis in terms of the Crowd Dynamics concept. It considers a crowd as either a set of individuals such as the Social Force Model or a fluid such as concepts of thermodynamics and statistical mechanics by computer vision. The survey divided the reviewed studies into three classes, anomaly detection, motion pattern segmentation, and behavior recognition. First, crowd motion pattern segmentation analyzes motion patterns in areas of crowded scenes. Several methods have been proposed based on the cluster of the motions or segment principle. For instance, flow-based segmentation, similarity-based clustering, and probability-model-based clustering. Next, crowded anomaly detection has been classified into two sections, global anomaly detection and local anomaly detection, i.e., where does the anomaly occur? Does the scene include an anomaly case or not? Lastly, crowd behavior recognition is classified into object and holistic-based.

Kiran et al. [ 81 ] discussed the detection and prediction of anomalies by defining rare events and detecting unseen objects. Furthermore, the authors present the related works that used DL, unsupervised and semi-supervised methods for anomaly detection in video scenes. They classified their survey according to detection criteria and types of models (deep generative models, predictive models, and reconstruction learning models). Each of these types has several subtypes. Representation learning for reconstruction uses models and methods of normal behavior in surveillance videos to represent deviations in poorly reconstructed anomalies. Examples include principal component analysis, autoencoders, convolutional autoencoders (CAEs), CAEs for video anomaly detection, contractive autoencoders, and other deep models (like stacked DAEs (SDAEs), de-noising autoencoders (DAE), and deep belief networks (DBNs)). Predictive modeling contains four subsections, composite model, convolutional Long Short-Term Memory (LSTM), 3D-autoencoder and predictor, and slow feature analysis (SFA). SFA is used to view video frames as time series or temporal patterns to predict the existing frame or its encoded representation utilizing the previous frames. Lastly, Deep generative models consist of eight subsections: Generative vs. Discriminative, Variational Autoencoders (VAEs), Anomaly Detection Using VAE, Generative Adversarial Networks (GANs), GANs for Anomaly Detection in Images, Adversarial Discriminators Using Cross-Channel Prediction, Adversarial Autoencoders (AAEs), and Controlling Reconstruction for Anomaly Detection. They are employed to model the probability of samples of normal video in a deep learning framework.

Bendali-Braham et al. [ 16 ] proposed a novel taxonomy for crowd analysis that includes two branches, crowd behavior analysis and crowd statistics. Crowd statistics determine the number of people currently in a scene. It includes two subbranches, crowd counting and density estimation. Crowded scene analysis is divided into crowd behavior recognition, motion tracking and prediction, and group behavior recognition for human behavior analysis in a crowded scene. Furthermore, crowd activities and motion patterns are described in video scenes and when crowd statistics determine the LoS. Al-Shaery et al. [ 82 ] tackled an inclusive review of crowd management, from the discovery of crowded places to crowd monitoring and management. They focus attention on systems of crowd management that require a well-designed decision support system (DSS), as well as the systems that have early warning capabilities to realize the primary goal of gatherings which is crowd safety. They divided their taxonomy into two branches: crowd detection and crowd monitoring and tracking analysis. The last section includes the crowd management and control stage that leads to the crowd DSS stage. They considered the crowd management stage as the intermediate between monitoring and the Crowd DSS stage. Ebrahimpour et al. [ 62 ] reviewed the studies of crowd analysis based on various data sources. They divided their taxonomy into three classes, crowd social media analysis, crowd spatiotemporal analysis, and crowd video analysis with some subsections. Crowd spatiotemporal analysis uses a data source generated by transportation that is monitored with Global Positioning System (GPS), such as shared bikes or buses. In terms of crowd social media analysis, it exploits check-in data that have been taken from geo-tagged social microblogs for crowd analysis. The data analysis process contains four steps, discovery, gathering, preparation, and analysis. Finally, crowd video analysis includes two sections with subsections inside them: crowd video behavior analysis (microscopic modeling and macroscopic modeling) for generating trustworthy trajectories for pedestrians as well as crowd video action recognition (single person action recognition and group activity recognition) for single or group activity surveillance, tracking people, objects, sports video analysis, and action recognition.

In summary, the studies and surveys above used various taxonomy according to their perspectives. Most of these studies focused on crowd behavior and motion analysis based on the captured video scenes. One of them focused on crowd spatiotemporal analysis based on GPS data, owing to the ability to collect data automatically remotely by mobile sensing and mobile computing [ 83 ]. Obviously, there is no exploit on social media data, this paper investigates this scope with the best technologies. Our review is distinguished from others that we study general cases of crowd management and analysis, in addition to local studies in the Hajj season to discover the flaws and difficulties facing the Hajj authorities in order to avoid disasters and accidents among crowds.

4 A comprehensive study of crowd management

Literature that discusses crowd management in various past universal events. Through a methodical literature review, they have classified crowd analysis into several types according to the purpose of the study. Crowd scene analysis, social media-based analysis, and crowd sound emotion recognition are the main types of crowd management. Each one has some subsections below, according to our taxonomy in Fig.  5 . Studies discussing the analysis of crowds with various purposes employ DL algorithms. Researchers seek to use the newest of these technologies to achieve the highest performance and accuracy possible. Table 4 illustrates the statistics for papers obtained from each subsection.

Taxonomy of crowd management

4.1 Crowd detection

To avoid accidents, it is crucial to know when the people will gather. Then, the organizers must perform in-depth prior analyses and develop comprehensive plans for these mass gatherings. Crowd analysis is a vital tool for crowd management [ 4 ]. Ordinarily, there will be an advance notice for well-known human gatherings, either religious, sports, carnival events, or always-crowded places such as airports, train stations, stadiums, etc.

Every human gathering has special features regarding the purpose, location, and time as well as the behavior of the people, their beliefs, affiliations, and race. For instance, in 1987, a group of Iranian pilgrims rioted during the performance of the Hajj rituals at Makkah, Saudi Arabia, and, as a result, 402 people were killed and injured [ 61 ]. To give another example of religious events in India, Hindus gather to bathe at the Ganga River, Saraswati River, Kshipra River, and Godavari River, where heavy crowds are expected at specific times. On 31 December 2014, on Shanghai New Year’s Eve, there was a stampede, resulting in 36 individuals killed and 47 others injured [ 60 ]. Table 5 summarizes the tragedies that happened previously. Therefore, it is critical to adopt crowd management and propose rigorous and flexible strategies to prepare for unforeseen occurrences at any time. If crowd management fails, it will lead to a loss of lives or properties.

4.2 Crowd statistics

Crowd counting and density estimation are characteristic types of crowd analysis. Calculation of crowd counting, and density can be beneficial in planning crowd security and safety. If the crowd size can be estimated at crowded places, such as temples, stadiums, airports, or metro stations, in advance, it would be extremely beneficial for planning alternate strategies for crowd control.

4.2.1 Crowd counting

Several methods have been developed for crowd counting, which include three classes under the methodologies of DL: (1) CNN-based methods [ 36 , 42 ]; (2) detection-based methods [ 87 ]; and (3) regression-based methods [ 88 , 89 ]. Briefly, detection-based methods utilize detection algorithms, which consider that a crowd consists of the sliding-window detector and individual entities to compute the number of object instances in the detected image [ 33 , 87 ].

Regression-based methods exist to solve the problem of occlusion. The main ideas of this method are learning a density map and extracting its features from an image to estimate crowd density [ 33 , 88 , 89 ].

Lastly, many works have been developed by CNN-based methods in the crowd counting field due to their successful applications in computer vision.

Kang et al. [ 27 ] proposed an adaptive convolutional neural network (ACNN)-based model for counting. It improves the counting precision compared to an ordinary CNN with a similar number of parameters.

Marsden et al. [ 28 ] had developed a previous model in [ 76 ] of convolutional crowd counting for the high-density crowd. They added several contributions, including a training set increase to minimize redundancy between samples of training to improve counting performance. They also use a single column, deep, fully convolutional network (FCN) for analyzing images with any aspect and resolution ratio.

Sheng et al. [ 54 ] proposed a framework based on locality-aware features (LAF) integrated with CNN features to capture more semantic spatial and attributes of the image. Furthermore, they used a vector of locally aggregated descriptors (VLAD) which consider the weights of the coefficients.

Hu et al. [ 47 ] used a convolutional neural network (convNet or CNN) structure to extract features of a crowd in a single image to estimate the crowd count. Their approach was based on CNN and appropriate for a mid-level or high-level crowd. Similarly, Kumagai [ 29 ] adopted CNNs with fixed weights to reduce the fault rate when counting a crowd.

Dai et al. [ 84 ] proposed improved approaches to crowd flow prediction, whose goal is to count the incoming and outgoing numbers of people in urban regions. The approaches were based on a spatiotemporal attention mechanism with a simplified deep spatiotemporal residual network. The first one captures information about the spatial correlations on crowd flows and finds the regions with positive impacts. The second one reduces training time and gives the best prediction performance compared with similar approaches.

Gong et al. [ 30 ] used existing images on social media to estimate the number of people in crowds at city events. This study is the first to count crowds from this side, unlike prior studies that used datasets from popular sources such as video surveillance data. They constructed a novel dataset of images collected from social media for diverse events and major activities in the city. Each image is annotated with its characteristics and the size of the crowd. They applied four methods of two types, direct methods (Faceplusplus and Darknet Yolo) and indirect methods (Cascaded method A and B), to crowd size estimation analysis. The results showed that direct methods achieve higher accuracy than indirect methods. Specifically, Darknet Yolo achieves the best accuracy in estimating the crowd size level (72.01%) and the number of people (38.09%). This study provides a novel method to count people via the advantage of their visual posts on social media.

Huang et al. [ 31 ] solved the problem of noise in the areas with different densities, which appeared in a previous study that used a multi-column convolutional neural network (MCNN) method. The authors proposed a novel method named a segmentation-aware prior network (SAPNet). Using a map of coarse head-segmentation, they produced a map of high-quality density without noise. SAPNet contains two networks, CR-CNN as the back end and FS-CNN as the front end. They are a crowd-regression convolutional neural network and a foreground-segmentation convolutional neural network, respectively. FS-CNN produces a map of coarse head-segmentation, then this map is inputted to CR-CNN to perform a highly accurate crowd counting to produce a high-quality density map. The four datasets that tested their approach were WorldExpo’10 [ 71 ], UCF-CC-50 [ 90 ], UCSD [ 70 ], and ShanghaiTech [ 76 ]. It has achieved high performances on the UCF-CC-50 and ShanghaiTech part B datasets. However, the WorldExpo’10 dataset [ 71 ] was unsuitable for their method because the raw images are of low precision. Furthermore, a poor Canny-edge map can lead to the generation of a faulty segmentation map. This study succeeds in an efficient solution to the problem of noise in areas with different densities. It will be very beneficial in high-congestion places such as train stations, stadiums, religious gathering.

In the same context, Jiang et al. [ 32 ] produced a novel PSDENet method, the people segmentation-based density estimation network. At first, the PSDENet model performs learning and pre-training on virtual synthetic data, then, it transfers these tests to real data. The proposed method has proven effective even though it uses two independent networks, PSDENet and people segmentation network (PSNet). It requires the consumption of much computation.

Zhang et al. [ 33 ] proposed a two-task convolutional neural network (T 2 CNN). It is a novel method for crowd counting that concomitantly learns two tasks, the density map estimation of images and the classification of the tasks of dense degree. Each image has different degrees of density, and local regions inside them have different degrees of density. Determining the density degrees of images helps the estimation of the density maps. For this purpose, researchers incorporate the module of T 2 CNN with dense degree classification (DDC). T 2 CNN takes the scale of the adaptive CNN as the density maps estimator, then classifies images into several categories based on degrees of density. Therefore, that model is an efficient way to treat the perspective and scale variations in crowd images, according to experimental results performed on common datasets: WorldExpo’10 [ 71 ], UCF_CC_50 [ 69 ], and ShanghaiTech [ 76 ].

Shang et al. [ 34 ] developed a new architecture to deal with the perspective variation problems for estimating the number of people in images on the web. The proposed approach has two-stage processing: policy network and count network. A policy network is an estimation of perspective by a regular CNN, while a counting network is a normalization of perspective for the input patches into a scale-specific CNN. Then, given the arranged inputs, they adjusted the scale-specific counting network and their approach to deal with a large perspective variation in web images. In this context, the evaluation metrics were used to verify the model of Xu et al. [ 91 ], which gives an average enhancement of 4.68% of Grid Average Mean Absolute Error (GAME), 6.7% of Mean Squared Error (MSE), and 3.68% of Mean Absolute Error (MAE). Also, their experiments were performed on datasets following UCF_CC_50 [ 69 ], UCF-QNRF [ 92 ], RGBT-CC [ 93 ], and ShanghaiTech [ 76 ].

Jiang and Jin [ 35 ] discussed estimating high-quality crowd density maps and counting crowds by revisiting the design of CNNs to get high-quality density maps as well as high resolution on datasets of crowd counting. For instance, these datasets include UCF_CC_50 [ 69 ], UCSD [ 70 ], and ShanghaiTech datasets [ 76 ]. Their proposed method, multilayer perception counting (MPC), realized high results in a high-quality density map, which is better than counting the crowd. Their method relies on diverse deep supervision (DDS) rather than general supervision, which uses all the intermediate layers or hierarchical in the network. Moreover, MPC is considered the ideal way for cases requiring prediction in real-time.

Khan and Basalamah [ 36 ] proposed a unified model to detect human heads in visual images for crowds using regression models with CNNs. The model is based on DenseNet, which contains 174 layers. It handles a wide range of scale differences by integrating scale-specific detectors within the network. Therefore, the network parameters are improved in an end-to-end fashion. The model was applied to difficult benchmark datasets, such as UCSD [ 70 ] and UCF-QNRF, and achieved the best results.

Liu et al. [ 52 ] proposed a global density feature to add to the multi-column convolution neural network (MCNN) to improve its performance using the cascaded learning method. This model differs from existing works because it concentrates on uneven crowd distribution. Furthermore, deconvolutional layers and the max pooling were utilized to generate a thorough density map and to restore the missing details of the accuracy of the density map during the down-sampling process. The results of experiments prove that this model has higher accuracy and stability when applied to ShanghaiTech [ 76 ] and UCF_CC_50 datasets [ 69 ].

Kizrak and Bolat [ 4 ] used video images or static images to estimate the number of people in a crowd by utilizing CNN with modules of capsule network-based attention. They have proposed a 75,442 VOLUME to crowd analysis using a CNN and two-column cascade and CapsNet as an attention module. The positive impact of the Capsule attention was proven to detect the number of people in images of a crowd. However, this method is still not effective in terms of computational complexity.

Elharrouss et al. [ 53 ] provided two contributions, a new method using CNN and the creation of a novel crowd counting dataset taken from the Football Supporters Crowd (FSC-Set). It contains 6000 annotated images of various scenes. FSC-Set can be used for other domains such as localization of individuals, image supporter recognition, and face recognition. The proposed method named FSCNet used several modules: channel-wise attention, spatial-wise attention, and context-aware attention for crowd counting. The results were satisfactory on all the datasets. This research provides a solution to counting people in crowded places based on several attributes. This method can be contributed to aid other studies of crowd counting.

Khan et al. [ 55 ] developed a framework using end-to-end semantic scene segmentation (SSS) based on CNN for counting people in a densely crowded image. The framework consists of three components: Density Estimation (DE), classification using optimized CNN, and SSS. Moreover, to solve the problem of scaling variations in images, they used four fields that had sixteen filters to feed output at every stage. Their method has validated four standard datasets such as Shanghai Tech, World Expo, NWPU_Crowd [ 94 ], and UCF_CC_50 [ 69 ]. Furthermore, they claimed that the crowd counting domain is still an immature research area due to limited data in deep learning.

Zou et al. [ 67 ] proposed a model to address ignoring the massive temporal information among consecutive frames when process each video frame independently. The model namely, temporal channel-aware (TCA), it realizes exploiting the temporal interdependencies between video sequences through fusion of 3D kernels of convolution in order to encode local spatio-temporal attributes.

Du et al. [ 68 ] redesigned a classical multi-scale neural network to treat challenging of crowd counting. The scheme merges multi-scale density maps. The network uses both the local counting map and the crowd density map to optimization. The experiments results proved that the novel scheme fulfills the state-of-the-art performance on five public datasets such as UCF_CC_50, JHU-CROWD++, ShanghaiTech, Trancos, and NWPU-Crowd.

At the end, Most of studies above developed their architectures based on CNN features to count crowd. Moreover, they used the famous benchmarks datasets such as Shanghai Tech, World Expo and others to perform experimentation on these architectures.

4.2.2 Crowd density estimation

Density estimation of a crowd is an extended part of crowd counting. Density computation is important to support preset plans and strategies to avoid overcrowding. The authors of [ 51 ] discussed the flow patterns of a crowd. They used an unsupervised methodology to cluster people patterns in large public infrastructures. The proposed approach has been applied to an international airport. Their approach successfully summarized the representative patterns and provided the required data for airport management.

The work of [ 44 ] proposed a model to estimate crowd density via an optimized ConvNet. The model has two ConvNet classifiers to improve its speed and accuracy. In the same context, the work of [ 63 ] used LSTM-combined Node2Vec graph embedding to extract spatial features.

4.3 Crowd scene analysis

Crowd Scene Analysis is most important to study normal or abnormal human behavior. This aspect includes Crowd Motion Analysis and Tracking using the most common approach is video surveillance to detect alarms and anomalies.

4.3.1 Crowd monitoring and tracking

[ 95 ] developed a new framework for an online gating neural network. It consists of two phases: the offline training phase and the online predicting phase. In the first phase, their training set is trained daily using a gated recurrent unit-based predictor of human mobility. In the second phase, they constructed an online adaptive predictor of human mobility. Moreover, it switched between offline pre-trained and online adaptive human predictors using a gating neural network. They have adopted a real-world GPS-log dataset for training Tokyo and Osaka cities, where this approach realized a higher prediction accuracy for this approach. This framework can be employed for several purposes, for instance, incorporating additional data such as event information or weather data to predict human mobility. The framework minimizes unnecessary information by performing more than one online training simultaneously. Moreover, the used dataset is considered a little representation of the real world. However, that system is unstable due to the sparse data.

Shi et al. [ 77 ] proposed a novel model for the trajectory prediction of pedestrians in highly crowded scenarios. The model relies on using LSTM and contains a trained decoder and encoder by truncated backpropagation. The experiments used data from the trajectory train station in Tokyo, Japan. This model has proven stable concerning predictions of varying lengths. In addition, it realized an average for both Evaluation Metrics Of The Prediction Errors (Average Displacement Error And Final Displacement Error) Of 21.0%.

In the same context, [ 57 ] studied the prediction of the trajectories of foreign tourists using lstm. Nevertheless, there is a difference. The first layer of lstm is fed with the input sequence, and every other layer of lstm is fed with the layer's output that precedes it. They claimed that the proposed method outperformed classical approaches.

Zhang et al. [ 79 ] studied monitoring passenger flow in a passenger metro by creating a cnn-based platform. The proposed method has three parts: the first is a cnn group used to extract features from images. Then, the second is a module of feature extraction utilized to enhance multiscale. Finally, transposed convolution is applied to the sample to create a high-quality density map.

Lastly, some of these works used cnns with lstm methods to extract images feature in order to examine and analyze crowd scene, they have accomplished high-quality. In every case, the integration of cnns with lstm is considered an effective method to produce a high-quality density map, and thus it can give good results.

4.3.2 Crowd behavior analysis

Swathi et al. [ 37 ] developed a vigorous model, which integrates features of deep learning AlexNet (alippi, disabato and roveri, 2018) with high-dimensional features of the gray-level co-occurrence matrix (GLCM) that have hybrid deep statistical features. Moreover, it used a multi-feed forward neural network model (MFNN) to execute multi-category classification. AlexNet and GLCM provide a wealth of information on spatiotemporal features to make ideal classification decisions. The MFNN algorithm helps ideal multi-class classification. The model has achieved an accuracy rate of crowd behavior classification of 91.35%, 89.92% precision, 89.12% f-measure, and recall of 88.34%.

Zhang et al. [ 65 ] proposed a framework to predict crowd behavior in complex scenarios. The framework consists of three components: the module of scene feature extraction, the discriminator, and the generator. The first component captures the environment's visual signal, the spatial layout, and the interrelationship of pedestrians. The second component measures the similarities between the real trajectories and the generated ones. The third component consists of the encoder and the decoder parts that use lstm for inputting. Experiments are executed on the standard crowd benchmarks datasets, such as the chinese university of hong kong(cuhk) crowd (shao, change loy and wang, 2014; shao, loy and wang, 2016), the eth zurich university(eth) datasets [ 97 ], the crowd-flow, and the university of cyprus (ucy)datasets [ 98 ]. These experiments confirm that the proposed framework successfully predicts the behaviors of crowds in complex scenarios.

According to above, integration alexnet features with glcm have achieved a good accuracy rate for classification.

4.3.3 Crowd abnormality detection

Abnormal behavior is an unusual event occurring in overcrowded scenes. Therefore, crowd abnormality detection in crowded areas plays a pivotal role in preventing any disasters due to riots. The domain of anomaly detection has gained the interest of researchers in computer science in recent years.

Video anomaly detection (VAD) uses algorithms of temporal video segmentation to detect shot boundaries in sequential frames of video [ 99 ]. VAD challenges relate to crowded and complex scenes, small anomaly datasets, and anomaly localization [ 49 ]. Moreover, the challenge of false-positive detection results is that the system incorrectly discovers normal events as abnormal ones [ 49 ]. For these reasons, deep learning methods are more suitable than traditional methods [ 69 , 95 , 100 ]. In particular, unsupervised deep learning methods are the best solution [ 49 ].

Ganokratanaa et al. [ 49 ] proposed a new unsupervised deep residual spatiotemporal translation network (named DR-STN). The proposed approach has embedded with DR-cGAN and OHNM, which refer to Deep Residual conditional Generative Adversarial Network and Online Hard Negative Mining, respectively. The authors claim that their approach reduces the detection of a false-positive anomaly. Furthermore, it increases anomaly localization accuracy with a rate of 96.73%.

Wang et al. [ 38 ] proposed a novel algorithm to solve the problem of visual abnormality detection in crowd scenes. The abnormal frame is called a global abnormal event (GAE). However, determining the abnormal area in one frame is called a local abnormal event (LAE). This process uses a feature descriptor extraction of MHOFO (motion descriptor, namely a multi-frame descriptor). The motion information is represented by this descriptor after capturing it as a multi-frame. After that, captured samples are trained via a cascade deep autoencoder (CDA) as a generative network to detect abnormal behavior. Their experiment was performed on three benchmark datasets, University of California, San Diego (UCSD) [ 70 ], PETS2009 [ 73 ], and UMN [ 77 ]. They have proven that their algorithm shows competitive results. Although their model is slower than the SCL method, it is better in terms of performance. The SCL is the fastest method in the published papers for anomaly detection.

Ammar and Cherif [ 39 ] proposed a model to treat the problem of panic behavior detection in abnormal situations, which is named DeepROD. This technique worked in real time, online, and offline. It relies on statistical characterization and LTMS neural networks to predict future values of features. They claimed that their model is proven by experiments on well-known datasets (both public databases and livestreaming sources). Specifically, online training has given a better performance than offline training for the crowded scenes. Furthermore, it provided good processing time and accuracy. Nevertheless, DeepROD has lower accuracy when tested on a livestreaming source, such as a festival video.

Khan et al. [ 59 ] proposed an AlexNet-based crowd anomaly detection model to detect the anomaly in the image frame. Their model was comprised of three fully connected layers, four convolution layers, with additional the rectified linear unit (ReLU) was used as an activation function. The experiment has been performed on a personal computer using fewer computational resources, it appeared that the proposed model outperformed other studies and fulfilled 98%.

Basalamah et al. [ 50 ] proposed a Bi-LSTM framework using motion information to detect congestion rather than count pedestrians.

4.3.4 Group activity detection

Vahora et al. [ 45 ] proposed a novel model using a deep neural network for the recognition of group activity via video monitoring. The model has a multi-layer deep architecture, which integrates CNN with RNN. CNN model was used to capture information, feature, and level semantics from the scene for recognizing mysterious group activities. The RNN model used the LSTM model and gated recurrent unit (GRU) model to handle the problem of long-term dependency for the RNN model.

4.4 Social media-based analysis

Over the last few years, several smartphone social network applications (apps) have come to market. These apps enable users to exchange their information, location, and temporal data, usually called check-in data. Day by day, social network apps have become more utilized by people. Especially popular are apps based on geotagged social microblogs and location-based social networks (LBSNs) such as Twitter, Facebook, Instagram, and LinkedIn. An advantage of social media (SM) is that users share their interests and purposes when, where, and why they go out. A result is an enormous source of data that may help researchers in different domains to perform crowd analysis, such as sports, religious, and carnival events, as well as in the marketing domain and trend detections. From another perspective, the data sources of SM open other horizons in the analysis domain, including counting people, computing individual tracks, and detecting normal and abnormal behavior in a crowd [ 101 ]. Moreover, they show how much impact these data have to create a crowd or influence their behavior [ 102 ]. Figure  6 illustrates trends of analysis via social media.

Analysis trends via Social Media

4.4.1 Opinion/sentiment analysis

Öztürk and Ayvaz [ 46 ] collected all tweets in English and Turkish languages that discuss humanitarian issues concerning the Syrian refugee crisis to perform sentiment analysis on them. They used the twitter package to collect data from twitter. Then, they utilized the Rsentiment package. Both packages were developed in the r programming language. Rsentiment contains a comprehensive sentiment dictionary in English and provides a sentiment score. Whereas in the Turkish language, the authors have developed a sentiment lexicon of 5405 words. Finally, the results of these analytics, overall sentiments were positive about Syrian issues. While only 12% of the tweets in English were positive, the tweets in Turkish were equally distributed among neutral, negative, and positive sentiments. It is good to adopt this model to suit different languages.

In the same context, Malik et al. [ 64 ] created an alert system for Pakistan government authorities in order to determine the public emotions of people against upcoming anti-government.

Duan et al. [ 60 ] studied a stampede on shanghai new year’s eve in 2014. This study investigated the reasons for this crowd behavior through the viewpoint of social media data. The authors developed a framework using check-in data of the Weibo platform of three trends, the emotional fluctuations of citizens, the topic changes in posts, and the collection level of check-in data. The framework processes are executed as follows. At first, the location information of check-in data is taken from Weibo to analyze the spatial and temporal using Moran’s i index. Next, the textual data of Weibo is analyzed through topic modeling using the Latent Dirichlet Allocation (LDA) method. Finally, sentiment analysis is analyzed and divided into five groups to extract percentages of negative and positive sentiments. As a result of this study, the geographical features can directly reflect changes in crowd flow, as well as the psychological states of people before and after accidents. However, it still faced some challenges.

4.4.2 Geo-located analysis

Redondo et al. [ 48 ] proposed a hybrid solution based on clustering techniques and entropy analysis to early detect unexpected behaviors in social media. Data is collected from Location-based Social Networks (LBSNs). The authors used the Instagram platform for this study because it is a good source for geo-located data. Moreover, the APIs of some social media platforms impose limitations on the access of visual data by developers.

Finally, previous works has studied crowd flow behavior by analyzing textual data. Thus, Duan et al. [ 18 ] claimed that prior knowledge of people's psychological and behavioral states may help in understanding crowd behavior.

4.5 Crowd sound emotion recognition

Franzoni et al. [ 40 ] introduced the first model to study sound emotions for the crowd. The model integrates CNN and spectrogram-based techniques. According to their claims, they have not compared the results of their experiments with any prior study with a similar domain (crowd). However, they compared these results with studies focused on analyzing individual-speech emotions. The model has a 10% improvement in average accuracy. Their study proved that the AlexNet-CNN spectrogram-based method is appropriate to analyze the sound emotions of the crowds.

At the end of this section, this paper demonstrates the limitations of the above papers. There are some problems during the process of data extraction. The information inferred was insufficient due to a lack of data on procedure, methods, and performance, which may be reflected by the QA.

4.6 Crowd management at Hajj event

This part will display all studies that support Hajj research. Hajj ritual is the fifth pillar of Islamic, every Muslim should visit to the holy places in Makkah, Saudi Arabia once at least in his life. They should able financially and physically to perform worships of Hajj. The period of Hajj is between 8 and 12th of the 12th month every year, it is called (Dhulhijjah) in the Islamic (lunar) calendar. Hajj's crowd of up to three million people comprised of pilgrims from all over the world in one sacred spot. The geographic area of the holy sites for performing Hajj rituals is not exceeding 33 km 2 . This makes the Hajj authorities to face a great challenge to deal with the overcrowding of the Hajj in a specific period and place, firstly relating to the security and safety of pilgrims. The objective of our work is to discover the efficient practices of crowd management in the holy biggest event in Saudi Arabia, it is the Hajj ritual [ 103 , 104 ]. All methods currently applied in the field of Hajj crowd management are still lack of attention and development from researchers, especially in terms of exploiting of textual data to analysis of crowd's emotions, sentiments, or opinions. The two papers are picked below according to our criteria in this survey.

Farooq et al. [ 41 ] presented a novel method for abnormal behavior detection for crowds that may lead to dangerous disasters, such as a stampede. The model captures motion in the form of images, then classifies these images according to crowd divergence behavior using a CNN method, where the CNN has been trained on motion-shape images (MSIs). Moreover, the finite-time Lyapunov exponent (FTLE) domain is acquired when the optical flow (OPF) is computed first. LCS (Lagrangian coherent structure) in the FTLE domain represents dominant motion for the crowd. Finally, a scheme of ridge extraction transforms the LCS-to-grayscale MSIs. The model is tested on six real-world low and high-density datasets. They claimed that the experiments produced effective results for their method in terms of detecting divergence accurately, as well as detecting starting points of congestion at high and at low density. Furthermore, they presented two new datasets, including video scenes of normal and abnormal behaviors for a high-density crowd. In the Hajj case, the authors have applied their model to pilgrims’ crowds at Makkah, Saudi Arabia. It used recorded Video data (the PILGRIM dataset) taken from a live broadcast of the Makkah TV channel. They have generated three behavior videos from every single video. The proposed method also has outperformed this dataset.

Habib et al. [ 61 ] developed a novel framework to identify abnormal activity for pilgrims at Makkah. A lightweight CNN model was trained on the dataset of pilgrims. This dataset was captured from installed CCTV et al.-Haram. The images’ frames were passed to the proposed model for the extraction of spatial features. Then, an LSTM network was created for the extraction of temporal features. Lastly, the system will make an alarm when an emergency occurs, such as an accident or violent activity, to inform the authorities to take the appropriate action. They have performed experiments on two violent activity datasets: Hockey Fight and Surveillance Fight. The model achieved good accuracies of 98.00 and 81.05, respectively. However, this model suffers from the shortcoming of recognizing violent activity from one perspective only. And it is the best that recognizes violent activity from multiple perspectives to obtain insights into the activities.

Finally, the review concludes from Sects. 4 and 5 that most of these studies have been concerned with CNN methodology and integrated with other techniques to benefit further and improve the accuracy of model performance, Table  6 summarizes all studies that used CNN approach with their advantages and disadvantages. Table 7 displays that used the methodologies of RNN such as LSTM approach. While Table  8 illustrates studies that used different methodologies to create models.

According to our viewpoint, the models of crowd counting still need development for several problems as follows: Detecting large objects as people, but do not detect small objects. Most of models cannot be generalized on all datasets, where they give good results with some datasets and inefficient results with others. Classifying some objects as people by mistake. The accuracy of captured image/video varies according to the installed camera angles. Hence, the challenges can be minimized as possible, installing cameras at every angle in the place to ensure the monitoring of all people and improving the accuracy of image/video pixels for the extraction of features efficiently. At last, internet of things (IoT) devices can improve counting crowds besides DL models. In terms of analysis of social media, geographic locations feature should be exploited for processes analytic of crowds. Furthermore, the various languages should be supported just like the English language. Consideration of the backgrounds of psychological, social, and beliefs of people when studying their expression on social media.

5 Results analysis of comprehensive study of crowd management

In this study, the comprehensive study is divided into two domains. The first one is crowd management in various events in the world. The second one is crowd management in local area named Hajj event in Makkah, Saudia Arabia. All these studies focus on approaches that applied DL techniques. In terms of comprehensive study of crowd management in various events, the related works are divided into four sections, everyone has two or more subsections. The sections are crowd statistics, crowd scene analysis, social media-based analysis, and crowd sound emotion recognition.

5.1 Crowd statistics

Many new hybrid approaches have been developed by CNN-based methods to improve crowd counting and crowd density estimation fields. The outcomes of combining two or more methods have confirmed that hybrid techniques enhance performance, increase accuracy, and prevent many obstacles in computer vision projects. This has been displayed using the adaptive convolutional neural network (ACNN)-based model, locality-aware features (LAF) integrated with CNN features, multi-column convolutional neural network (MCNN) method, two-task convolutional neural network (T2CNN) with dense degree classification (DDC), and end-to-end semantic scene segmentation (SSS) based on CNN for calculation of crowd counting and density.

5.2 Crowd scene analysis

Many works have attempted to find the successful solutions for normal or abnormal human behavior analysis. Videos scene analysis for human behavior detection is faced many challenges relate to crowded and complex scenes, anomaly localization, small anomaly datasets, and false-positive detection [ 56 ]. To solve these reasons, DL techniques are more suitable and successful solutions than traditional methods to treat problems and challenges. The researches have been developed by CNN-based methods integrated with other techniques. The works of Shi et al. [ 50 ] and Crivellari and Beinat [ 51 ] have used backpropagation processing through the LSTM technique. LSTM in the first layer feeds subsequent layers and every other layer of LSTM is provided with the layer's output that precedes it. Furthermore, the model of Zhang et al. [ 54 ] used LSTM in third component for inputting stage to improve accuracy rate for classification. Moreover, Ammar and Cherif [ 61 ] have integrated LTMS neural networks and statistical characterization to predict future values of features. Vahora et al. [ 31 ] used LSTM beside GRU to handle the problem of long-term dependency, also used CNN to capture features from the scenes.

Finally, some of these works used CNNs with RNN methods such as LSTM and GRU to treat long-term dependency problems, increase improve extraction of scene features, and accomplish high-quality to anomaly behavior detection.

5.3 Social media-based analysis

Some of the works focus on studying crowd management through text data analysis is less compared to analyzing image and video scenes. Due to of the difficulties associated with natural language processing that make it difficult to understand the intentions of people's feelings and emotions towards events and situations. Moreover, It would be excellent if there is prior knowledge of people's social, psychological and behavioral states in order to understand crowd behavior to prevent emergency cases proactively to ensure crowd safety [ 43 ].

5.4 Crowd sound emotion recognition

There is one research that has presented to study emotion detection by sounds, where it used AlexNet-CNN spectrogram-based method to analyze the sound emotions of the crowds. Spectrogram-based method is appropriate for crowd sounds analysis.

5.5 Crowd management at Hajj event

In terms of crowd management at hajj event, the flow of data during a Hajj period is huge, whether it is visual, text, or audio data. This digital wealth must be greatly exploited by the Hajj authorities to reduce the terrible effects that may be when proactive solutions are not developed to control crowds. Like previous studies, CNN with LSTM have been used to effectively extract visual attributes to classify anomalous or anomalous crowd behavior, this achieved excellent accuracy results.

5.6 Addressing of used methodologies limitations

It is clear from the review of existing works that crowd management is plagued by drawbacks and challenges that have restricted its rapid improvement in recent years. Hence, we made several important considerations when building crowd models.

It can be noticed most of the works of literature is that they still remain density-dependent. It means their models developed for macro-analysis independently from micro-analysis, while applications of real-world require crowd analysis to be conducted starting at macro-level and branching down into the micro-level. Therefore, it is important in future works in terms of modelling surveillance, behavioral understanding of crowds, must concern on the enhancement at both macro-and micro-levels and integrated between them.

Furthermore, it can be observed that most of the literature based on computer vision is performed under strong and restrictive conditions, for example, the perspective of the installed camera in the place, surrounding environment, estimating density of crowds, noise, etc. It is vital to realize that these requirements are inherited from the computer vision field since they are viewed as extension techniques for crowd modeling. There is a common sense of acceptance of these challenges for researchers. Whereas in this work, we recommend the integration of some techniques that collect data about people to reduce absolute dependence on traditional equipment. We claim that utilizing various data on social media will make a vital source for video surveillance domain and counting crowd density, behavior, or abnormality crowd detection, which increases the cognitive diversity and learning new patterns for datasets. Hence, the crowd models will be generalizability on the different environments. It has increased the number of large-scale events in the world; thus, the organizers should benefit from the deepest insights about attendees’ characteristics besides events' characteristics. It becomes possible to describe the behavior of people during crowd events using social media data, this is paving the path for crowd monitoring and management by using real-time applications [ 105 ]. The work of [ 106 ] is a good example of exploiting the data in streaming channels and social media during the Hajj season. We believe that, in the future, social media data related to expressing people’s daily lives will become close to understanding the behavior of crowds during events.

The future research must be concerned with the complementarity of the models to solve challenges and drawbacks rather than with minor developments to increase the accuracy of the model only. For these reasons, it is important to understand the differences between the kinds of supervised and unsupervised DL techniques. Many of the relevant concepts may confused together when building large or complex models. Table 9 clears the most important strengths and weaknesses of ML and DL algorithms.

One of the main problems with the majority of local works during Hajj season is that most research is performed in isolation as urban planning for smart cities and the variety of needs regarding crowd management. Urban crowd management is an integral activity for any event, such as crowd flow, estimating density, monitoring street grid, movement of buses [ 107 ], crowd trajectory [ 108 ], impact of a pandemic on crowds [ 109 ], etc. Integration Urban provides good decision support for the development of the city in all respects. Big data and advanced intelligence computational techniques can help the planning, design, management, analysis, and simulation of smart cities. For instance, early planning of safety evacuations in the midst of a natural disaster incident based on location data of mobile phones leveraging both machine learning approaches [ 110 ]. Use crowd-harvested data to study the population's sentiments, traffic patterns, and perceptions of neighborhoods, in addition, to simulating the model urban systems more realistically, which is crowdsourcing effective the analyzing and modeling of urban morphology at much finer social scales, temporal, and spatial [ 111 ]. Hence, smart cities will be able to control and monitor dynamic changes as they happen inside the city during crowded events. For instance, using the FOPID controllers controls systems with nonlinear dynamics, also improves the complex systems performance in various applications [ 112 ], and using DETDO optimizer to solve real-world engineering design problems [ 113 ].

6 Discussion

In this SLR, about 45 DL-based articles are reviewed. According to the detailed analysis of various crowd management approaches and their state-of-the-art performance in this survey, our survey forecasts that DL-based methods will predominate future research in the crowd analysis and management fields. It can be noticed that most methods have been integrated with other DL methods, such as CNN with LSTM, to increase the accuracy performance. Moreover, variations in types of input, layers, or fed to in the CNN. It utilizes popular datasets or creates a novel dataset for performing testing on proposed approaches.

Most of these papers focused on crowd scene analysis in the computer vision field. Therefore, the major challenge for crowd management is the lack of sentiment analysis of crowd-based big data on social media. There is also a lack of custom datasets to feed textual data analysis. Owing to the challenges related to natural language processing, it makes difficult to understand people's emotions towards events and situations by textual expression. Furthermore, studying of people's psychological and behavioral it may reduce the severity of these challenges. Furthermore, its open scope for a greater understanding of what is behind the meanings and words. Thus, investigation of the crowd’s behavior from all aspects is greatly crucial for crowd safety, also to prevent dangerous emergency situations before they happened [ 43 ].

6.1 Current study vision discussion

This section discusses our vision of this study compared to previous state-of-the-art studies. The main objective of this survey is to spotlight the shortcomings or defects of previous papers. New approaches must provide effective solutions for crowd video analysis in real-time, while traditional approaches are not able to handle efficient solutions in a time-bounded manner. Traditional approaches are insufficient for crowd analysis cause the size of the crowd is huge and dynamic in real-world scenarios. In addition, the behavior and actions of individuals are difficult to identify. The shortcomings can be identified in existing approaches as follows: real-world dynamics, time complexity, bad weather conditions, overlapping of objects [ 119 ], and unexpected incidents. All existing approaches were handling the shortcomings independently. It can be observed that there seem to be almost no concerns about the lack of research in sentiment analysis of crowd-based big data on social media in the world, especially during Hajj events. It can be perceived as a missed chance to learn from different visions. Thus, this study seeks to change imbalance research by configuring new Integrative frameworks and methodologies and highlighting the prior good practices in this domain. It is significant that the researcher community realizes these gaps when constructing existing systems and continuing to monitor the development of integrated research in crowd management.

This paper aims to support Hajj research through the enhancement of the pilgrims' behavior analysis and work to cover the above aspects. Moreover, we will provide datasets of pilgrims taken from social media and will make them publicly available to be useful to other researchers. The authors are seeking “actionable SM-based crowd management”. In this sense, traditional crowd management needs a new multidimensional conception. To build a new robust infrastructure, it must be integrated as follows; “AI algorithm + computing power + big data = smart service” [ 120 ]. It is significant that utilize the best optimizers to improve the performance of complex systems such as FOPID [ 112 ], DETDO [ 113 ], Genghis Khan shark [ 121 ], Geyser Inspired Algorithm [ 122 ], Prairie Dog Optimization Algorithm [ 123 ], Dwarf Mongoose Optimization Algorithm [ 124 ], and Gazelle Optimization Algorithm [ 125 ].

The advantage of this work is the crowd management domain may rise to another sophisticated level if considering the attention on social media big data. Presenting a new taxonomy of crowd management based on deep learning algorithms, including all domains of analyzing data: visual, audio, and textual. Presenting the comprehensive examination of the global crowd management works in order to benefit Hajj authorities to apply the best practices locally. The following research [ 53 , 126 ] can be contributed to addressing weaknesses in Hajj research regarding counting crowds, where the model focuses on the attention of CNN channel-wise, spatial-wise attention, and context-aware. In addition, the model can be used for other purposes, such as image supporter recognition, localization of individuals, and face recognition. Furthermore in [ 46 ], the authors provide a good model for the analysis of textual data and understanding the emotions of users, but it needs some modifications to suit other languages like Arabic.

There are some lessons that can be learnt from this SLR. First, our practice of SLR has emphasized the lack of Hajj data analysis topics. SLR employment is valuable to stay informed about those topics to support the data or knowledge of Hajj. Second, this SLR discovered that the future direction of data analysis and prediction depends on the development of CNN models. Third, crowd analysis studies focus on the analysis aspect of video surveillance more than textual data.

Limitations of this SLR include intentionally ignoring conference papers because they contain incomplete models or studies. Thus, we limited our sources to academic articles only. During data extraction, we found insufficient information related to the environment, evaluation, accuracy, and procedure in some papers, which may be reflected by the QA. As a result, some inferred data may have inaccuracies due to unclear information in the papers. Table 10 shows the summarization of the learning lesson, limitations, and future research directions.

7 Conclusion

In this SLR, the researchers explored comprehensive crowd management from the aspect of DL methods. This survey has performed a wide investigation for relevant related works published in the interval 2010 to 2023. Moreover, the survey elicited pivotal information based on our research questions (RQs). The research goals have been fulfilled effectively through these RQs that were established to examine and analyze the scope of the research. Moreover, ensuring that the key findings and contributions have been performed usefulness for future researchers, also the gaps and obstacles that faced crowd management have been discussed in the Sects. 5.6 and 6 . The four RQs raised in this SLR, and their findings are as follows:

RQ1: Most previous works have been classified into two categories, crowd scene analysis and crowd statistics. However, these previous works omit the opinion mining of users on social media to predict future crowd actions.

RQ2: Supervised and unsupervised DL methods provide high accuracy in general, which supported computer vision in crowd analysis in many studies, especially in architectures based on the CNN model. Because of its high efficiency and accuracy, it has become the most reliability model for researchers.

RQ3: We observed there is the fewest number of studies regarding crowd management at Hajj. As well they focused on the detection of abnormalities in crowded scenes.

The primary aim of our review is to investigate crowd analysis fields in every gathering around the world. Furthermore, the local gathering, especially crowd analysis in a Hajj event for example. The paper aims to illustrate the dilemmas and obstacles that have been faced in every study. Moreover, it aims to find research gaps existing to focus on it in future studies. Finally, we observe that most studies were about crowd scene analysis via private/publicly available datasets or live-streaming surveillance, whether using supervised or unsupervised techniques. They ignored the behavior analytics and predicted it by textual data on social media. In addition, the literature indicates the lack of Hajj research, especially in sentiment analysis and the study of the pilgrims' behavior. Overall, the systematic literature review links the widespread knowledge transfer debate of crowd management in terms of the study behavior of entities via SM big data and predicting the actions. Thus, the current study enriches the research communities and academic discourse.

Availability of data and materials

Availability upon request from the Corresponding author.

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Excess mortality during the COVID-19 pandemic in low-and lower-middle-income countries: a systematic review and meta-analysis

• Jonathan Mawutor Gmanyami 1 , 2 , 3 ,
• Wilm Quentin 2 , 4 , 5 ,
• Oscar Lambert 1 ,
• Andrzej Jarynowski 6 ,
• Vitaly Belik 6 &
• John Humphrey Amuasi 1 , 2 , 3 , 7  

BMC Public Health volume  24 , Article number:  1643 ( 2024 ) Cite this article

Metrics details

Although the COVID-19 pandemic claimed a great deal of lives, it is still unclear how it affected mortality in low- and lower-middle-income countries (LLMICs). This review summarized the available literature on excess mortality during the COVID-19 pandemic in LLMICs, including methods, sources of data, and potential contributing factors that might have influenced excess mortality.

We conducted a systematic review and meta-analysis on excess mortality during the COVID-19 pandemic in LLMICs in line with the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) 2020 guidelines We searched PubMed, Embase, Web of Science, Cochrane Library, Google Scholar, and Scopus. We included studies published from 2019 onwards with a non-COVID-19 period of at least one year as a comparator. The meta-analysis included studies reporting data on population size, as well as observed and expected deaths. We used the Mantel–Haenszel method to estimate the pooled risk ratio with 95% confidence intervals. The protocol was registered in PROSPERO (ID: CRD42022378267).

The review covered 29 countries, with 10 countries included in the meta-analysis. The pooled meta-analysis included 1,405,128,717 individuals, for which 2,152,474 deaths were expected, and 3,555,880 deaths were reported. Calculated excess mortality was 100.3 deaths per 100,000 population per year, with an excess risk of death of 1.65 (95% CI: 1.649, 1.655, p  < 0.001). The data sources used in the studies included civil registration systems, surveys, public cemeteries, funeral counts, obituary notifications, burial site imaging, and demographic surveillance systems. The primary techniques used to estimate excess mortality were statistical forecast modelling and geospatial analysis. One out of the 24 studies found higher excess mortality in urban settings.

Our findings demonstrate that excess mortality in LLMICs during the pandemic was substantial. However, estimates of excess mortality are uncertain due to relatively poor data. Understanding the drivers of excess mortality, will require more research using various techniques and data sources.

Peer Review reports

Introduction

Only six viruses within the coronavirus family, namely 229E, NL63, OC43, HKU1, SARS-CoV, and MERS-CoV, have been known to cause respiratory tract infections in humans [ 1 ]. The SARS-CoV-2 virus, identified in 2019 as the cause of COVID-19, emerged in Wuhan, China [ 2 ]. Despite containment efforts, the virus spread globally, leading the World Health Organization (WHO) to declare it a pandemic in March 2020 [ 3 ]. To date, over 6.5 million deaths and 623 million infections have been reported worldwide, with Africa recording nearly 9 million cases and over 173,000 deaths [ 4 ].

Numerous non-pharmaceutical interventions were adopted globally to combat COVID-19, such as lockdowns and mask mandates [ 5 , 6 , 7 ]. While these measures aimed to reduce the transmission of the virus, [ 8 , 9 ] may have inadvertently increased mortality among chronically ill patients by hindering timely medical care access [ 10 , 11 ]. Additionally, the pandemic response contributed to higher fatalities from domestic violence, suicide, and mental health issues [ 9 , 12 , 13 ].

Confirmed COVID-19 deaths alone may not fully reflect the pandemic's impact [ 14 ]. Excess mortality offers a more comprehensive view, capturing both direct and indirect effects. As per the World Health Organization (WHO), excess mortality is the difference between actual deaths during a crisis and expected deaths without it [ 15 ], encompassing COVID-19-related deaths and those indirectly influenced by the pandemic, including socio-economic challenges like compromised food security, disruptions in supply chains, and limited access to healthcare [ 16 , 17 , 18 ].

Studies have shown that the pandemic exacerbated food insecurity due to lockdowns and economic downturns, which affected the nutritional status and health outcomes of vulnerable populations. Additionally, disruptions in healthcare services led to delays in treatment for chronic conditions and reduced access to essential medical care, further increasing mortality. Mental health issues and increased domestic violence during lockdowns also contributed to higher death rates indirectly associated with the pandemic. These multifaceted impacts highlight the necessity of assessing excess mortality to gain a full understanding of the pandemic's toll, particularly in low- and lower-middle-income countries (LLMICs), where healthcare systems and social safety nets are often less robust. The estimated excess mortality rate from COVID-19 could be 5 to 25-fold higher than reported COVID-19 mortality rates [ 14 ].

Understanding and accurately reporting mortality statistics is crucial for global health policy and resource allocation. In low- and lower-middle-income countries (LLMICs), mortality reporting remains a significant challenge. These countries often face systemic challenges, including incomplete civil registration systems, and under-resourced statistical offices, which contribute to incomplete or inaccurate mortality data. Hence knowledge on excess mortality during the COVID-19 pandemic in LLMICs remains limited [ 19 , 20 , 21 , 22 ]. Vital registration systems and other data sources are often incomplete or inaccurate, lacking routine mortality reporting [ 5 , 20 , 23 ]. To address these limitations, various methods like data interpolation and extrapolation have been proposed [ 24 ]. Innovative approaches such as using satellite imagery to track new graves and participatory epidemiology have also been employed to estimate excess mortality [ 25 , 26 , 27 ] and these unique circumstances and innovative solutions emerging from LLMICs require focused attention.

In addition, to estimating excess mortality using available data, Shang et al. observed a higher pooled excess mortality in developing countries compared to developed ones but did not delve into specific LLMIC results or assess methodologies and data in these contexts [ 28 ]. This systematic review and meta-analysis presents a focused and current summary of excess mortality literature in LLMICs. This study helps to fill a critical gap in the literature by systematically reviewing and analyzing excess mortality in LLMICs during the COVID-19 pandemic. This will not only enhance our understanding of the pandemic's true impact but also support the development of more effective public health responses in these vulnerable regions.The objectives included summarizing existing studies on excess mortality during the COVID-19 pandemic, describing estimation methods and data sources, and identifying drivers of excess mortality in these settings.

This systematic review and meta-analysis focused on studies from low- and lower-middle-income countries.

This review, guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) [ 29 ], focused on estimating excess mortality levels, examining the methodologies and data used for estimation, and identifying factors influencing excess mortality in LLMICs. Quantitative methods were utilized to conduct a meta-analysis, providing a summary estimate of the excess mortality.

Protocol registration

The protocol for conducting this systematic review and meta-analysis was registered in the International Prospective Register of Systematic Reviews (PROSPERO) (ID: CRD42022378267).

We conducted searches in electronic bibliographic databases including PubMed, Embase, Web of Science, Cochrane Library, Google Scholar, and Scopus. Additionally, we reviewed the reference lists of included studies and relevant publications. The search strategy comprised terms related to key review concepts: COVID-19 and/or SARS-CoV-2, excess mortality, and low- and lower-middle-income countries. Each term was operationalized with various synonyms and tailored for specific databases. The search strategy used Medical Subject Headings (MeSH) terms and involved key terms with the appropriate Boolean operators (AND, OR) to ensure comprehensive coverage.

No language restrictions were applied, and the searches were restricted to studies published between 2019 and the date of the searches. In September 2023, the searches were rerun before the final analyses, resulting in additional studies for inclusion.

Study selection procedures

The inclusion and exclusion criteria were defined based on the Participants, Intervention/Exposure, Comparator, and Outcome (PICO) framework, as detailed below:

Participants/population

The review included population-level or cohort studies from LLMICs, independent of the administrative level (district, region, nation). Facility-based studies were considered to examine covariates and the methods used, but disease-specific studies were excluded.

Intervention(s)/exposure

The exposure of interest was the COVID-19 pandemic. This referred to the period from when the WHO declared COVID-19 a pandemic on March 11, 2020, to the most current wave of COVID-19 infection that was reported in the population under review.

Comparator(s)/control

The comparator in the estimation of the excess mortality was all-cause mortality in the non-COVID-19 period (registered or estimated). This comparator period included data from at least one year before March 2020.

Main outcome

The main review outcome was excess mortality in the population under investigation.

Additional outcome

Additional outcomes included the methods and data sources used in estimating excess mortality and factors that influenced excess mortality in LLMICs.

Eligibility criteria

Articles that reported on excess mortality with the COVID-19 pandemic as the exposure of interest

Articles conducted in Low and Lower-Middle Income Countries as defined by the World Bank

Studies published between the years 2019 and to date

Population-level, cohort studies or facility-based studies, independent of the administrative level (district, region, nation)

Studies with a comparator of all-cause mortality in the non-COVID-19 period being at least one year before March 2020

Study inclusion

Two independent investigators (JMG and OL) used the eligibility criteria to select studies for inclusion in the review. Any disagreement was resolved by discussion and/or a third reviewer (WQ) was consulted for a consensus to be reached. A meta-analysis was conducted for a subset of the included studies in the review. Studies were included in the meta-analysis only if they provided the following information: a clearly defined estimate for excess mortality, a documented method for estimating excess mortality, a specified population size for the study, as well as an observed, and expected death count for the period reported.

Data extraction

We extracted the following data: author (s), publication year, study country, study period, World Bank income level, estimated excess mortality, disaggregated results for differences in socio-economic groups, estimated and registered COVID-19 mortality, mortality data sources, methods used to estimate excess mortality, identified drivers of excess mortality, type of population (geographical region, cohort), and population baseline characteristics. Mendeley Desktop Version 1.19.8 was used to identify duplicate records.

Measures of effect

The review’s primary outcome was estimated excess mortality as reported in primary studies. Studies that did not indicate the expected (i.e. baseline) deaths and the observed/estimated deaths were not included in the meta-analysis. Secondary outcomes included methods for estimating excess mortality, disaggregated measures of excess mortality (e.g. mortality by socio-economic status) and factors influencing excess mortality.

Data analysis and synthesis

Reported estimates of excess mortality were summarized in tabular format and synthesized narratively. The methods and data that were used for estimating excess mortality and identifying factors that influenced excess mortality, and the socioeconomic disparities in the estimates of excess mortality were summarized and synthesized into thematic narratives.

A meta-analysis was conducted to estimate the rate of excess mortality in LLMICs. Data analysis was conducted using StataSE 16 statistical software from StataCorp, College Station, Texas, USA.. Mortality rates estimated before and during the pandemic were calculated and summarized. The Mantel–Haenszel random-effects method was adopted to estimate the pooled risk ratio at 95% confidence intervals (CIs) and heterogeneity among the studies was estimated using I 2  values. The I 2 quantified the degree of heterogeneity in the meta-analysis.

Sensitivity analysis

Sensitivity analyses were carried out to investigate how non-eligible research may have an impact on risk differences. This was accomplished by running the data through a meta-analysis twice. For studies that did not have full details based on the eligibility criteria, first, we included all studies and second, only included those that were known to be eligible. Only studies that were known to be eligible were included in the final meta-analysis.

Risk of bias (quality) assessment

The quality of the included studies was assessed using appropriate tools. Quality assessment was performed by two independent reviewers based on the Newcastle- Ottawa Scale (NOS) score and any disparity was solved by discussion and/or consulting a third reviewer (Appendix 1). In this assessment, all studies included in the review and meta-analysis were at minimal risk of bias. In addition to the NOS score, we also considered the methodological rigor of each study, including factors such as study design, sample size, and data collection methods. This comprehensive assessment ensured a thorough evaluation of the quality of the included studies and provided confidence in the robustness of our findings.

Figure  1 summarizes the results of the study search and selection process. A total of 10,196 studies were identified in the databases after removal of duplicates. During title and abstract screening, 10,068 were excluded, leaving 129 studies for full-text review, of which, 24 studies were included in the systematic review and 6 in the meta-analysis.

Flow diagram of the study selection procedure

The main reasons for exclusion in the review were (1) Reports outside the study scope, (2) Studies not related to review objectives, (3) estimation of excess mortality among patients with a specific disease instead of a population and/or cohort, and (4) the use of a comparator which was less than 1 year in the estimation of the expected number of deaths in the calculation of excess mortality. The main reasons for exclusion from the meta-analysis were that studies did not specify the population size, the number of expected deaths (all-cause mortality), the number of observed deaths, or the methods for estimating excess mortality.

Characteristics of included eligible studies

The characteristics of the 24 included studies are summarized in Table 1 . Studies were published between 2020 and 2023 but most were published in 2021 (13 studies). Five studies were conducted in low-income countries and 19 in lower-middle-income countries (Fig. 2 ). Most of the studies were conducted in Asia, including Iran (7). India (4), Bangladesh (2), and Indonesia (2). There were 6 studies from Africa and none from Latin America or the Caribbean. Sanmarchi et al. [ 30 ] reported estimates from 5 countries, making it a total of 29 countries in the review (Fig. 3 ).

Number of studies classified by World Bank income level

Countries and their represented number of included number of studies

For the meta-analysis, 10 countries were included from 6 studies. In 7 countries, the observed deaths were higher than expected ([India (2), Iran (1), Kyrgyzstan (1), Uzbekistan (1), Tunisia(1), and Bolivia (1)]. In three countries (Indonesia, Kenya and Mongolia), negative excess mortality was recorded, thus the observed deaths were lower than the number expected in the absence of the pandemic.

Estimate of excess mortality in LLMICs

Table 2 provides an overview of population and mortality data reported by the studies included in the meta-analysis. During the COVID-19 pandemic, of the total 1,398,858,717 individuals/populations, 3,555,880 all-cause deaths were reported, while 2,152,474 deaths were expected from the eleven countries. The pooled excess mortality was 100.3 deaths per 100,000 population. The excess risk of death was 1.65 (95% CI: 1.649, 1.655 p  < 0.001). There was a high heterogeneity as indicated by the I 2 of 100% among the studies (Fig.  4 ).

Adjusted Pooled estimate of excess mortality

In 7 countries, the observed deaths were higher than expected, whilst, in three countries, negative excess mortality was recorded, thus the observed deaths were lower than the number expected in the absence of the pandemic.

Methods in estimating excess mortality in LLMICs

The 24 articles used four distinct methods/study designs to determine excess mortality. The largest group of studies (15 articles) used retrospective data of already existing mortality datasets [Bangladesh (1), Iran (5), India (4), Kenya(1); Syria(1), Madagascar(1), Indonesia(1), Uganda(1)] to estimate excess mortality. Two studies used quantification of burial sites by observing the increase in the number of burial grounds to estimate excess mortality [Yemen(1), Somalia(1)]. One study used a cross-sectional survey through a household census (Bangladesh) and another used grey literature (use of already published figures from journalists and organizations) (India) to estimate excess mortality.

Concerning the source of data, four studies used more than one data source to estimate excess mortality. This included burials in public cemeteries + civil death registration + health authority death registration (Indonesia), daily mortality/incidence data from the Syrian Ministry of Health + Excess all-cause mortality data from a statement by the Damascus governorate + obituary notification data from Facebook page (Syria), National survey data + health facility deaths Jha et al. [ 49 ] (India) and figures published by regional governments and Indian journalists + government hospital data + funeral counts + handwritten death registers (India).

All other studies relied on only one data source. Five studies used National Civil Registration Data (4 studies from Iran and 1 India). Two studies each used the Health and Demographic Surveillance System (Kenya and Bangladesh), death registers (India and Madagascar) and imaging of burial sites/grounds (a study each from Yemen and Somalia). One study (in Bangladesh) used only primary data (census/survey) data and another study (in Iran and Indonesis) used Bureau of Vital Statistics data to estimate excess mortality.

Studies used several different methods to determine the expected deaths that were used to calculate excess mortality. Twelve studies used modelling techniques to estimate excess mortality. Of these, five studies used linear regression [India(2), Indonesia(1); Iran(2)], two studies used auto-regression modelling techniques. Two other studies (In Madagascar and Iran) used geospatial analysis which involves identifying new grave plots and measuring changes in burial surface area over a period ( In Yemen and Somalia) and two studies used estimation of death counts (In Uganda and Indonesia). Other modelling techniques used included Cox proportional hazard models, Auto-Regressive Integrated Moving Average, model fit, multilevel regression model (full bayesian model).

Factors influencing excess mortality in LLMICs

In assessing the factors that might have influenced excess mortality, of the 24 studies, only one (in India) reported differences in mortality between rural and urban areas. They found that excess deaths in the first wave of the pandemic were concentrated in urban areas, while deaths in the second wave affected both urban and rural areas. Other studies speculated what could have caused excess morality without empirical evidence in their data. No study reported disaggregated information by socio-economic status.

Discussion of key findings

This is the first systematic review and meta-analysis of studies estimating excess mortality during the COVID-19 pandemic in low- and lower-middle-income countries (LLMICs), exploring methods in estimating excess mortality and the factors that might have influenced excess morality in LLMICs.

The results of the meta-analysis indicate that excess mortality in LLMICs was substantial. There were an estimated 1,403,406 excess deaths in the 10 countries covered by the included studies, representing 100.3 excess deaths per 100,000 population or a 1.65 excess risk of death (95% CI: 1.649, 1.655 p  < 0.001) during the pandemic. Expected deaths were mostly estimated based on secondary data analysis. Other studies quantified an increase in burial grounds and other household surveys. This review identified only one study that assessed factors associated with excess mortality. According to that study, excess deaths were concentrated in urban areas during the first wave of the pandemic but affected both urban and rural areas in the second wave [ 49 ].

A previous review and meta-analysis of global excess mortality reported a slightly higher estimate of excess mortality for lower-middle-income countries [133.45 (95% CI: 75.10–189.38) per 100,000]. Also, according to the COVID-19 Excess Mortality Collaborators, globally, the number of excess deaths due to the COVID-19 pandemic was largest in the regions of South Asia, north Africa the Middle East, and Eastern Europe. India (4·07 million [3·71–4·36]), the USA (1·13 million [1·08–1·18]), Russia (1·07 million [1·06–1·08]), Mexico (798,000 [741000–867000]), Brazil (792,000 [730000–847000]), Indonesia (736,000 [594000–955000]), and Pakistan (664,000 [498000–847000]) were estimated to have the highest cumulative excess deaths due to COVID-19 at the national level. They highlighted that across countries, the ratios showed significant variation, with New Zealand having the lowest at -17.10 (-26.06 to -8.84) and the Central African Republic the highest at 139.24 (88.86–213.67). South Africa, the only sub-Saharan African nation with available direct estimates of excess mortality from vital registration data, had a ratio of 3.31 (3.15–3.64). In South Asia, national-level ratios ranged from 8.33 (7.58–8.92) in India to 36.06 (15.14–53.25) in Bhutan. Within India and Pakistan, the most extreme ratios were observed at the state and province level, spanning from 0.96 (0.44–1.41) in Goa, India to 49.64 (28.94–72.74) in Balochistan, Pakistan [ 50 ].

By examining the methods employed in estimating excess mortality, we provide valuable insights into the diverse approaches used in LLMIC contexts. Notably, innovative techniques such as quantifying burial sites and utilizing geospatial analysis emerged during the pandemic, offering alternative means of mortality surveillance in resource-constrained settings. The methods of studies included in this review align with the methods of other studies conducted in high-income countries. 50− Retrospective data analysis, while essential for calculating excess mortality, can be limited by delays in death registration, leading to potential underestimation at the time of analysis. This design was however suitable at the time of the pandemic and further corresponded to WHO recommendations. 53 Estimating excess mortality requires an estimate of a certain level of baseline mortality to enable computation of excess mortality. Quantification of burial sites using geospatial analysis is a new method that emerged during the pandemic and was found to have considerable advantages for rapidly monitoring population mortality in settings without effective vital registrations [ 25 ]. However, this method could result in underestimation due to moderate precision because of missing grave counts in satellite images [ 26 ].

A few studies used burial site expansion before and after the pandemic to quantify excess mortality.

Some studies from the review used a combination of two or more methods, ranging from death registries, burial ground quantifications, journal reports and demographic survey data. The use of multiple methods is not new. It has been used in other studies [ 32 , 51 ]. In this current review, linear regression models were widely used to estimate the number of deaths that would have occurred in the absence of the pandemic. This aligns with other estimation methods proven to be statistically efficient in estimating excess mortality [ 34 ].

There is relatively limited information on factors that influence excess mortality in LLMICs. Only one study included in our review [ 52 ] reported that excess mortality was associated with sociodemographic and clinical characteristics. [ 34 ], whereas in several high-income countries, socioeconomic disparity in excess mortality has been studied extensively. In England for example, it was observed that excess mortality was consistently higher for essential workers throughout 2020, particularly for healthcare workers [ 39 ]. In Korea, the pandemic has disproportionately affected those of lower socioeconomic status and has exacerbated inequalities in mortality [ 37 ]. Unfortunately, similar evidence is unavailable for LLMICs.

In this study, it is evident that the overall estimate is greatly influenced by the data from India due to its significant population size, constituting 65% of the weight. Consequently, the observed excess mortality rates in other countries appear considerably lower. This substantial variance could potentially be attributed to this influential factor for the high rates of excess mortality in LLMICs. It is plausible to speculate that excess mortality has been impacted by a wide range of factors, including limited health sector capacities to detect and treat COVID-19, more constrained resources to take care of other diseases, and fewer resources to cushion the negative social consequences of the pandemic [ 14 ].

The findings of this review reconfirm that the true impact of the pandemic is considerably higher than the reported number of COVID-19 deaths, which have been estimated at 100.3 /100,000 for the 10 LLMICs covered by studies included in our meta-analysis. Overall, our review shows the importance of addressing excess mortality in LLMICs and provides a foundation for ongoing research and policy initiatives aimed at improving pandemic preparedness and response strategies in these settings.

Our review has some limitations. First, a low number of primary studies met the criteria for inclusion and large variation in methods of included studies limited our ability to include studies in the meta-analysis. Second, our results are not representative of all LLMICs given insufficient numbers of studies from some parts of the world. Nevertheless, the results of this study provide a better understanding of the effect of the pandemic on mortality in LLMICs and may inform future analyses of excess mortality. The need to enhance death registration systems in LLMICs is essential for better pandemic monitoring.

Our review shows that excess mortality during the COVID-19 pandemic was substantial in LLMICs. It was above excess mortality levels reported for HIC and much higher than reported COVID-19 deaths in LLMIC. Most studies used retrospective and linear regression models to estimate excess mortality. More research and better data are needed to identify the drivers of excess mortality in LLMICs.

Availability of data and materials

No datasets were generated or analysed during the current study.

Abbreviations

All-Cause Mortality

Berlin University Alliance

Coronavirus Disease 2019

German-West African Centre for Global Health and Pandemic Prevention

High-Income Countries

Low-Income Countries

Lower-Middle-Income Countries

Low- and Lower-Middle-Income Countries

Newcastle–Ottawa Scale

Preferred Reporting Items for Systematic Review and Meta-Analysis

Participants, Intervention, Comparator, and Outcome

World Health Organization

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Acknowledgements

A big thank you to the management of the German-West African Centre for Global Health and Pandemic Prevention (G-WAC) / Berlin University Alliance (BUA) for their financial and technical support. I extend my sincere thanks to the leadership of the Global Health and Infectious Diseases Research Group at the Kumasi Centre for Collaborative Research in Tropical Medicine, Ghana for their understanding in excusing the Principal Investigator (JMG) to carry out this study.

The work has been made possible by the German-West African Centre for Global Health and Pandemic Prevention (G-WAC) scholarship of the German Academic Exchange Service (DAAD) as part of the Global Centres Programme funded by the German Federal Foreign Office. Additional financial support for supervision was made available by the Flattening the Curve Project of the Berlin University Alliance (BUA).

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JMG, JHA, WQ, AJ and VB made substantial contributions to the conception and design of this systematic review and meta-analysis. JMG performed the screening, study selection and data extraction from all studies using the eligibility criteria. OL independently screened the titles and abstracts of the identified studies. All authors approved the final version of this manuscript.

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Gmanyami, J.M., Quentin, W., Lambert, O. et al. Excess mortality during the COVID-19 pandemic in low-and lower-middle-income countries: a systematic review and meta-analysis. BMC Public Health 24 , 1643 (2024). https://doi.org/10.1186/s12889-024-19154-w

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Families’ importance in nursing care–families’ opinions: a cross-sectional survey study in the homecare setting

• Josien M. Woldring 1 , 2 ,
• Wolter Paans 1 , 3 ,
• Reinold Gans 2 ,
• Laura Dorland 4 &
• Marie Louise Luttik 1  

Archives of Public Health volume  82 , Article number:  87 ( 2024 ) Cite this article

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Informal care is an essential part of support provided in the homecare setting. To ensure effective healthcare provision, good communication and collaboration between informal and formal care providers are crucial. To achieve this aim, it is necessary to have a clear understanding of the perspectives of all stakeholders. In the scientific literature, limited knowledge is available regarding family members’ opinions about their involvement in care. To date, no instruments have been developed that accurately measure these opinions. This study aims to elucidate the opinions of family members about their involvement in nursing care.

A cross-sectional survey approach was employed. The methodological steps in this study were (1) convert the Families’ Importance in Nursing Care–Nurses’ Attitudes (FINC-NA) from a nurses’ perspective to a family perspective and thus develop the Families’ Importance in Nursing Care–Families’ Opinions (FINC-FO) and (2) measure families’ opinions regarding their involvement in home nursing care. The questionnaire was sent to 3,800 patients with activated patient portals, which accounts for about 17% of the total patient base. Responses were received from 1,339 family members, a response rate of 35%.

The developed FINC-FO questionnaire showed homogeneity and internal consistency. The results of the questionnaire indicate that family members consider it important to be involved in care and that they wish to be acknowledged as participants in discussions about care (planning) but are less inclined to actively participate in the provision of care by nurses. Family members expressed less explicit opinions about their own support needs. Factors such as level of education, type of partnership, and amount of care provided are seemingly associated with these opinions.

Conclusions

Family members in the homecare setting wish to be involved in discussions about care (planning). The transition in care from primarily formal to more informal care necessitates an awareness and clear definition—on part of both healthcare professionals and families—of their respective roles in the provision of care. Communication about wishes, expectations, and the need for support in care is essential to ensure quality of care and that the family can sustain caregiving.

Peer Review reports

Informal family care is an essential aspect of healthcare that involves the provision of support to family members who are ill, disabled, or vulnerable [ 1 ]. Family caregivers (e.g., partner, child, neighbor, friend) are vital for patients’ support and informal care [ 2 , 3 ]. In recent years, the need for support from family caregivers at home has increased due to societal changes, such as the aging population and the decreasing availability of institutionalized professional care for daily support. As a result, vulnerable, dependent elderly people continue to live at home for longer periods but are less able to rely on professional care. These societal changes necessitate an appropriate transition from primarily formal to more informal care. Informal care provided by family benefits patients’ wellbeing; however, it is also associated with a range of practical, physical, and emotional challenges for family members [ 4 , 5 ].

To make this transition of care successful, a need exists for targeted, effective communication that facilitates collaboration between healthcare professionals and informal family caregivers. Healthcare professionals should view family caregivers as partners in the care process to meet patient and family needs [ 6 ]. Earlier research indicates that preparedness for caregiving depends on the support that families receive from healthcare professionals [ 7 ]. To achieve good communication and collaboration between healthcare professionals and family caregivers, it is important to know both families’ and healthcare professionals’ opinions regarding the role of family members in caring for patients. Earlier research further indicates that nurses who generally have positive attitudes toward involving families as partners in patient care are more likely to communicate and collaborate with families [ 8 ]. With the increasing importance of family caregivers at home, it is implicitly expected that in general, family members wish to be involved in care. However, limited research has been conducted on families’ opinions regarding their involvement in direct nursing care and, subsequently, how they prefer to communicate and collaborate with nurses [ 9 ]. Involvement in the care for a family member is likely to be imagined differently by and between family members, which may differ from what is expected by nurses [ 10 , 11 ]. It is thus crucial to understand the opinions of family members regarding their involvement in nursing care and determine whether families’ wishes and expectations align with the principles of care envisioned by nurses. As such, this study aims to explore family members’ opinions regarding their involvement in nursing care for relatives in a homecare setting.

Instruments exploring family members’ opinions regarding their involvement in nursing care are currently lacking. As such, we have adapted the widely used Families’ Importance in Nursing Care–Nurses’ Attitudes (FINC-NA) from a nursing to a family perspective.

The methodological steps employed in this study were to (1) convert FINC-NA from a nursing to a family perspective and thus develop the Families’ Importance in Nursing Care–Families’ Opinions (FINC-FO) and (2) measure families’ opinions regarding their involvement in nursing care at home. A cross-sectional survey approach adhering to the “Strengthening the Reporting of Observational Studies in Epidemiology” guidelines for articles reporting cross-sectional studies was employed [ 12 ].

FINC-NA, a widely used instrument to measure nurses’ attitudes toward the importance of involving families in nursing care [ 13 , 14 ], is based on family systems nursing theory and has been validated in different healthcare settings and countries [ 15 , 16 ]. The study of Hagedoorn et al. (2018) provides an overview of countries that have validated the FINC-NA. Examples of nurses and care settings described in this study are registered nurses in Sweden, psychiatric nurses in Iceland and Taiwan, primary healthcare nurses in Portugal and hospital nurses in Portugal and Australia [ 16 ]. In educational attainment, there are slight variations, but al nurses maintain an educational level comparable to registered nurses.

The FINC-NA comprises four subscales: family as a resource in nursing care , referring to a positive attitude toward families’ presence in nursing care; family as a conversational partner , referring to the acknowledgment of patients’ families as conversational partners; family as a burden , referring to statements of experiencing family as a burden; and family as its own resource , referring to families’ own resources for coping [ 17 ]. Other instruments exist that measure families’ perspectives toward family involvement, but these typically involve a specific context and focus on families’ experiences with care, rather than their opinions about how they want to be involved. As such, we have adapted FINC-NA from a nursing to a family perspective.

Converting the survey items

The FINC-NA questionnaire has undergone translation into Dutch and subsequent psychometric testing. Hagedoorn et al. (2018) details this linguistic validation process, which involved translating the original Swedish questionnaire to Dutch [ 16 ]. This Dutch version of FINC-NA, comprising 26 statements utilizing a 5-point Likert scale, was converted from a nursing to a family perspective, resulting in the Dutch FINC-FO. To remain as close as possible to the original statements of the validated list, initially, only the concept of “nurse” was converted to that of “family” (or vice versa). The statements were subsequently evaluated and adjusted by two researchers (MLL and LD) with expertise in family care, who aimed to maintain the intention of the statements while ensuring that they were also easily understandable and applicable from a family perspective. Most of the adjustments involved the addition of the words “I consider it important…”. Only one item from FINC-NA, on the subscale family as resource in nursing care (“The presence of families gives me a feeling of security”), could not be transferred to a family perspective. As this statement relates to nurses’ emotions and perceptions, it was not considered something that the family could express an opinion on.

The content validity of the FINC-FO items was established by homecare patients and experienced informal caregivers (4 in total) who were members of an official customer council within a homecare organization. The FINC-FO was sent to the council by e-mail. Members of the council were asked to review all 26 statements for clarity and relevance and provided written feedback to the research team. Some statements were assessed as unclear, which could subsequently be resolved by changes in word-order or word-choice. All experts agreed that the statements in the final version of FINC-FO were clear and relevant to examine families’ opinions about their involvement in care at home.

The converted questionnaire resulted in an FINC-FO list comprising 25 statements exploring the four subscales using a 5-point Likert scale (1 = strongly disagree–5 = strongly agree) aligning with the original FINC-NA. Items were presented per subscale, starting with family as a resource in nursing care , with nine items, followed by family as a conversational partner , with eight items, then family as a burden , with four items, and finally family as its own resource , also comprising four items [ 12 ].

Reliability and construct validity

An item-total correlation correcting for overlap was conducted to evaluate the homogeneity and discrimination ability of the items. This correlation should be higher than 0.30 [ 18 ]. Cronbach’s alpha was used as a measure of the internal consistency or reliability of FINC-FO and its subscales. An alpha value of 0.70 or higher is generally considered acceptable, while values of 0.80 or higher are considered excellent [ 18 ]. To analyze the questionnaire’s construct validity, a confirmatory factor analysis was used. Since FINC-FO is based on the theory of FINC-NA, a deductive theory-based approach with the original, pre-specified factor structure of the four constructs was tested. A one-factor analysis per subscale was used to investigate the size of loadings (i.e., the items’ degree of association with the latent factor). Stevens (2002) recommends interpreting factor loadings with absolute values above 0.40 as sufficient [ 19 ].

Sample and setting

FINC-FO was distributed among the family members of patients receiving care from three home healthcare organizations in the northern region of the Netherlands. In the Dutch research context, homecare institutions are defined as organizations that deliver varying levels of care within individuals’ homes, serving to different levels of complexity. These organizations match the complexity of care required with the training and competency level of the healthcare professional, typically categorized by nursing levels. This coordination is facilitated through a nursing assessment performed by registered nurses. This model of healthcare organization is generally analogous to home healthcare organization in other European countries and North America.

As the FINC-FO questionnaire was made available exclusively through the electronic health record system’s patient portal (Caren-Nedap), only family members admitted to the patient portal were able to participate. The questionnaire was sent to 3,800 patients with activated patient portals, which accounts for about 17% of the total patient base. Responses were received from 1,339 family members, a response rate of 35%.

Data collection

In April 2022, FINC-FO was administered to family caregivers through the patients’ electronic health record system. The questionnaire was accessible via a link within the patient’s care file, visible to both patients and their families. Demographic characteristics such as age, gender, level of education, type of relationship with the patient, number of hours of caregiving, and working status were subsequently collected. The entire data collection process took 4 weeks.

Data analysis

Only completed questionnaires were included in the data analysis. Of the 1,339 questionnaires, 64 were excluded due to incomplete responses, resulting in 1,275 questionnaires for data analysis. As in FINC-NA, items on the subscale family as a burden were reverse scored, so the scores on this scale were recoded before analysis. Education level was categorized as high (tertiary education), middle (secondary education), or low (primary education), and the categories of relationship to the patient were merged into three: spouse, parent/child, and other. Data were analyzed using SPSS for Windows (release 28.0.1.1), and descriptive statistics were used to describe the study population and the responses to the FINC-FO questionnaire on item levels. Higher scores indicate more positive opinions. An independent t-test and an ANOVA were used to compare differences in attitudes related to background variables. For these analyses, the continuous variables age and caregiving hours were dichotomized. Mean or median was used as the cut-off point for the distribution. Multivariable linear regression analyses were performed to determine the individual contribution of each background variable to the FINC-FO and subscale scores. The significance level was set at p  ≤ 0.05.

FINC-FO questionnaire

The questionnaire was completed by 1,275 respondents. Table 1 illustrates the subscales, with the associated FINC-FO items. Subscales and items are shown in the same order as they appear in the questionnaire. All items on the subscales have been translated from Dutch to English by a certified translation agency with the original English FINC-NA terminology serving as a reference. They are expressed in truncated sentences to save space. Table 1 shows the homogeneity of the total FINC-FO scale with item-total correlations, internal consistency with the Cronbach’s alpha, and factor loadings per subscale.

The total FINC-FO questionnaire and the subscales family as a resource in nursing care , family as a conversation partner , and family as its own resource demonstrated strong internal consistency, with Cronbach’s alpha scores exceeding 0.80 across these scales. Most item-total correlations surpassed 0.40, with the exception of two items (RCN-1 and CP-5), which exhibited lower correlations. These two items also displayed inadequate factor loadings, below 0.40. Excluding them resulted in a slight improved Cronbach’s alpha. The Cronbach’s alpha for the subscale family as a burden was moderate, with one item showing a negative item-total correlation and the remaining items falling below 0.30.

Additionally, these FINC-FO score seem comparable to the Dutch FINC-NA questionnaire [ 16 ] which demonstrated similar reliability, with Cronbach’s alpha of 0.88 and 0.82 for the total score of the FINC-NA and subscale family as a resource in nursing care , respectively. However, the subscales family as a conversational partner and family as its own resource exhibited slightly lower Cronbach’s alpha values (0.74 and 0.73, respectively) compared to their counterparts in the FINC-FO. Conversely, the subscale family as a burden demonstrated slightly higher Cronbach’s alpha in the FINC-NA compared to the FINC-FO [ 16 ].

Measuring families’ opinions

Study population.

Table 2 illustrates the characteristics of the 1,275 respondents who completed the questionnaire. The average age of respondents was 60.7 years, and over 90% were between 40 and 80 years old. Over 70% were female, and more than half (57%) reported having paid employment. On average, these respondents worked 28 h a week, with 30% working 32 h a week or more. More than half of the respondents (59%) spent 8 h or less on caregiving tasks (ranging from 0 to 168 h), with 11.5% reporting spending at least 35 h on caregiving and 6.5% providing caregiving tasks 24 h a day.

Scores on FINC-FO

The total score of 92.3 (SD 11.5; range 25–125), as well as the scores on the subscales of the FINC-FO questionnaire, represented approximately 70% of the maximum possible score (see Table 3). Table 1 illustrates the response percentages per category.

Family as a resource in nursing care

Almost all respondents indicated that a good relationship with nurses gives them a positive feeling (95%), and most (75%) indicated having valuable knowledge that can be useful in caring for the patient or their family members. About half of the respondents indicated that their presence in care at home was meaningful (54%), made the work of a nurse easier (43%), and gave them a sense of purpose (52%). Family members also considered it important to actively participate in discussions about care (planning) and for nurses to allocate time for them. Fewer family members (19%) found it important to be present during actual care moments.

Family as a conversational partner

Of the family members, 87% found it important that nurses identify those who belong to the family, while less than half (43%) indicated that this had occurred in their situation. Most respondents (86%) considered it important to be invited for a conversation at the start of care provision, and 72% of respondents believed that this would save time. They also wished to be engaged in conversation at the end of care provision (77%), during changes (95%), or to regularly discuss progress (68%). Less than half (42%) found it important to be actively invited to participate in care provision.

Family as a burden

Most respondents (86%) did not believe that they hindered nurses in their work. Additionally, 67% did not feel that nurses found it difficult when family was present during care provision. Approximately 10% felt that they needed to monitor care provision to ensure that everything went well.

Family as its own resource

Nearly two-thirds (64%) of the respondents considered it important for nurses to view them as collaborative partners, while 10% did not find this important. Almost half of the respondents (46%) found it important to be asked how they could be supported, while 51% wanted support from nurses in coping with the situation. One-third (36%) found it important to be encouraged to cope with the situation as best as possible, while 19% did not find it important, and 45% had no opinion.

Differences according to background variables

Table 4 shows the scores for both the total FINC-FO questionnaire and the subscales related to the background variables.

A significant difference was found in the scores between the age groups. Older (> 60 years) family members scored higher compared to younger family members on the overall FINC-FO and on the three subscales family as a resource in nursing care , family as a burden , and family as its own resource ( p  ≤ 0.005).

Gender showed no significant difference in scores, except on the subscale family as a resource in nursing care. On this subscale, male family members scored higher than female family members ( p  = 0.03).

Education level

Family members with low education levels showed a significant higher score on the overall FINC-FO compared to middle and high education levels ( p  < 0.001). This difference was also observed on the subscale family as its own resource . The subscale family as a resource in nursing care showed a statistically significant difference among family members of all education levels ( p  < 0.001).

Relationship to the patient

Spouses of patients scored significantly higher compared to other relationships on the total FINC-FO and on the three subscales family as a resource in nursing care , family as a burden , and family as its own resource ( p  < 0.001).

Paid employment

Family members who had paid employment scored significantly lower than family members who were unemployed or doing volunteer work on the total score of FINC-FO ( p  < 0.001) as well as on the three subscales family as a resource in nursing care , family as a burden , and family as its own resource ( p  ≤ 0.03).

Caregiving hours

The more care hours were provided by family members, the higher the scores on FINC-FO. Significant higher scores were seen in the total score of FINC-FO and on the subscales family as a resource in nursing care , family as a conversational partner , and family as its own resource ( p  < 0.001).

Multiple linear regression

To determine the unique contribution of each background variable (see Table 4), multivariable linear regression models were performed for the FINC-FO questionnaire and its subscales (see Table 5). The number of caregiving hours made the greatest contribution for all subscales except family as a burden , and more caregiving hours resulted in a higher total FINC-FO score (β = 0.18; p  < 0.001). The family relationship of spouses made the same contribution as caregiving hours on the subscale family as a resource in nursing care (β = 0.15; p  < 0.001). Spouses made a significant contribution to the overall FINC-FO score (β = 0.09; p  = 0.03), and on all subscales except family as a conversational partner . Low education level also contributed to the total FINC-FO score (β = 0.06; p  = 0.04), as well as the subscales family as a resource in nursing care (β = 0.07; p  = 0.02) and family as its own resource (β = 0.08; p  = 0.02). Families with low education levels scored higher than those with middle education levels. For the subscale family as a burden , age made the greatest contribution (β = 0.10; p  = 0.01).

Table 5 shows that only 2–9% is explained by the selected background variables.

In this study, we gained insight into families’ opinions regarding their involvement in nursing care at home using the developed FINC-FO questionnaire. The results specifically reveal that family members consider it important to be acknowledged as participants in discussions about care and care planning and that they wish for their knowledge and input to be appreciated. Family members seem less inclined to actively participate in care and express less explicit opinions about their own support needs. Overall, FINC-FO seems to be a feasible questionnaire to capture families’ opinions regarding their involvement in nursing care in the home setting.

Our study indicates that primarily, level of education, type of relationship, and amount of care provided are associated with opinions regarding involvement in care. In particular, spouses, family caregivers with a relative low level of education compared to middle and high level educated family members, and family caregivers providing more than eight hours of care express the wish to be involved in care for their relatives. As demonstrated in previous studies, the influences of these background characteristics often interconnect [ 20 ]. It seems obvious that spouses, who spend more time with patients, have the opportunity to provide more informal care. Also, people with lower resources in terms of education and income more often provide informal care because they are less inclined to utilize professional care and often have smaller social networks to assist with caregiving, and as a result, bear the burden of care themselves [ 21 , 22 , 23 , 24 ]. Healthcare professionals must be aware of these associations and the impact of these variables, as the desire for a high involvement in care and the inability to mobilize other resources to organize care might eventually contribute to the overloading of family members, which often happens gradually and when it becomes apparent it will become a crisis [ 25 ]. Prevention necessitates an approach that considers the entire care situation. Regular communication between patients, families, and healthcare professionals about collaborative caregiving and the division of roles and tasks is essential to ensure quality care in the long term and the sustainability of family caregiving.

Background variables discussed above explain only up to 9% of the variance regarding family involvement in care. This suggests that several other unidentified factors influence family members’ opinions and highlights the need for further research on this topic.

Although family members express a desire to be acknowledged as participants in discussions about care and care planning, they seem less inclined to be actively involved in actual care provision by nurses. Before healthcare professionals become involved, family members frequently perform myriad caregiving tasks. However, these responsibilities seem to shift when healthcare professionals become involved and take over the provision of care [ 26 ]. With the need for a transition from primarily formal care to a higher level of involvement of informal care, healthcare professionals should consider what care is already being provided by a family and discuss which additional aspects of care the family is willing and able to deliver by discussing the possibilities, wishes, and expectations in the provision of care with the family. This necessitates an awareness—on the part of both healthcare professionals and family members—of their respective roles and tasks in the provision of care [ 8 ]. In addition, it seems desirable that healthcare professionals and family members harmonize their principles, values, and mutual expectations regarding the provision of care for the patient. Such conversations will promote better collaboration and coordination based on mutual understanding.

Family members responded more neutrally on the subscale family as its own resource , which suggests that family members are focused primarily on the patient and less on themselves and their needs as family caregivers. Family members may be unaware of their need for support or expect nurses to be primarily dedicated to the patient, not to family members. However, from the perspective of family systems nursing, the focus of nurses should not be solely on the patient but on the care situation as a whole and the family as the unit of care [ 27 ]. Considering the transition from formal to more informal care, the awareness that families may need support seems relevant among healthcare professionals, and among the patients and families themselves [ 28 ].

Strengths and limitations

The FINC-FO questionnaire was distributed via an electronic health record system, so it reached not the entire population of family members within the organization but only those who utilized the electronic patient portal. As a result, a possibility of bias in the results exists; family members who use the electronic patient portal may be more closely involved than those who do not. The sample size of 1275 allowed us to perform psychometric testing of the FINC-FO, indicating that the FINC-FO seems to be a feasible questionnaire to capture families’ opinions regarding their involvement in nursing care in the home setting. However, with a final response rate representing 35% of the total population, only cautious conclusions can be drawn about the population of family members of patients receiving homecare using the electronic patient portal. Further research is needed, employing alternative strategies to engage more respondents, in order to be able to generalize findings to a broader family population.

In this study, a questionnaire that has not yet demonstrated validity was employed. Nevertheless, the FINC-FO offer a sufficiently reliable and differentiated picture of family members’ opinions regarding their involvement in nursing care in the home setting, which suggests that this instrument can be recommend for use in future studies. However, it should be noted that the psychometric test conducted in this study indicates that the subscale family as a burden had moderate internal consistency as a subscale and a low item-total correlation with the total questionnaire. Depending on the primary questions in such studies, consideration may be given to adjusting or removing the subscale family as a burden ; this domain seems to answer a nurse related topic as it concerns the perception of families toward nurses and is not related to family involvement. Therefore this subscale seems not to contribute meaningfully to the research question we posed as the starting point in our study. The internal consistency of the three other subscales had good reliability but could potentially be improved by removing two specific items (RNC-1: Having a good relationship with nurses gives me a good feeling ; CP-5: The nurses found out who the family members are ). These items also had the lowest factor loadings of the subscales, so removing or reformulating these items should be considered. RNC-1 seems to be more associated with generating positive emotions than functioning as a resource, while C-5 is not an opinion item. It asks about specific experiences, which does not fit in this questionnaire.

Further research will be needed to examine the performance of the FINC-FO questionnaire following further psychometric refinement and suitability in different (institutional) healthcare settings.

While many studies have investigated the perspective of nurses with regarding the role of family members in patient care, this study investigated how family members perceive their own role in patient care. Exploring how family members experience the involvement of nurses in the care for their loved-one, could also be an interesting lens to study in future research since nurses, at some point, enter the existing family system that initially takes up the care of the patient.

Despite the limit sample size in this study, it is vital to prioritize policy implications surrounding awareness among healthcare professionals and families regarding their caregiving roles. Interventions should be developed and implemented to enhance communication and fostering collaboration between healthcare providers and families. Healthcare education should emphasize the important of communication and implementation regarding the division of roles between nurses and family members in caregiving.

In general, the family members of homecare patients want to be involved in nursing care. They wish to be acknowledged in discussions about care and care planning as participants with valuable knowledge. Family members are less inclined to actively participate in the care provided by nurses and are less explicit in their opinions about their own support needs.

The transition from primarily formal to more informal care necessitates an awareness on the part of both healthcare professionals and families of their respective roles in the provision of care. Communication about wishes, expectations, and the need for support in care is essential to ensuring quality care and that family members can sustain caregiving. With some suggestions for adjustment and improvement, FINC-FO is a feasible questionnaire to capture families’ opinions about their involvement in care.

Data availability

The FINC-FO questionnaire, meta data and The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines used to support the findings of this study has been deposited in the Dataverse repository. Available at : https://doi.org/10.34894/OYDOU4.

Abbreviations

Families’ Importance in Nursing Care–Nurses’ Attitudes

Families’ Importance in Nursing Care–Families’ Opinions

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Acknowledgements

The authors would like to thank Sabine van der Ham, library specialist, for supporting in data storage and nursing students Anna van der Heide and Lisa Oolders for their contribution in data collection.

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Contributions

Conceptualization, Methodology, Validation: All authors; Formal analysis: JW, WP, MLL and LD; Investigation: JW and LD; Resources: JW, MLL and LD; Data curation, Writing original draft, Supervision and project administration : JW Writing-reviewing and editing: WP, RG, MLL and LD.

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Correspondence to Josien M. Woldring .

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The study was approved by the ethical committee of Hanze University Groningen (heac.T2023.028). Patients and family members were informed about the aim of the study, and the participation of family members was voluntary. Family members were asked for informed consent before beginning the online FINC-FO questionnaire. The researchers received anonymized responses, and answers could not be tracked to individuals.

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Woldring, J.M., Paans, W., Gans, R. et al. Families’ importance in nursing care–families’ opinions: a cross-sectional survey study in the homecare setting. Arch Public Health 82 , 87 (2024). https://doi.org/10.1186/s13690-024-01314-4

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DOI : https://doi.org/10.1186/s13690-024-01314-4

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