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Writing a Literature Review

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

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

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

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

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

What are the parts of a lit review?

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

Introduction:

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

Conclusion:

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

How should I organize my lit review?

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

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

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

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

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

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

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

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

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

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

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

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

There are five key steps to writing a literature review:

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

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

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Table of contents

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

• Quick Run-through
• Step 1 & 2

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

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

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

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

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

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

Download Word doc Download Google doc

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

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

Make a list of keywords

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

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

Search for relevant sources

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

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

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

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

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

For each publication, ask yourself:

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

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

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

Take notes and cite your sources

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

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

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

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

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

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

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

Chronological

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

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

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

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

Methodological

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

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

Theoretical

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

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

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

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

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

As you write, you can follow these tips:

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

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

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

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

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

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

 Statistics

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

Research bias

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

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

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

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

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

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

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

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

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

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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. 

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

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

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

What are Literature Reviews?

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

Goals of Literature Reviews

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

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

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

What kinds of sources require a Literature Review?

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

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

Types of Literature Reviews

What kinds of literature reviews are written?

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

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

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

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

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

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

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

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

Literature Reviews in the Health Sciences

• UConn Health subject guide on systematic reviews Explanation of the different review types used in health sciences literature as well as tools to help you find the right review type
• << Previous: Getting Started
• Next: How to Pick a Topic >>
• Last Updated: Sep 21, 2022 2:16 PM
• URL: https://guides.lib.uconn.edu/literaturereview

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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.

Prevent plagiarism, run a free check.

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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• CAREER FEATURE
• 04 December 2020
• Correction 09 December 2020

How to write a superb literature review

Andy Tay is a freelance writer based in Singapore.

You can also search for this author in PubMed   Google Scholar

Credit: Getty

Literature reviews are important resources for scientists. They provide historical context for a field while offering opinions on its future trajectory. Creating them can provide inspiration for one’s own research, as well as some practice in writing. But few scientists are trained in how to write a review — or in what constitutes an excellent one. Even picking the appropriate software to use can be an involved decision (see ‘Tools and techniques’). So Nature asked editors and working scientists with well-cited reviews for their tips.

WENTING ZHAO: Be focused and avoid jargon

Assistant professor of chemical and biomedical engineering, Nanyang Technological University, Singapore.

When I was a research student, review writing improved my understanding of the history of my field. I also learnt about unmet challenges in the field that triggered ideas.

For example, while writing my first review 1 as a PhD student, I was frustrated by how poorly we understood how cells actively sense, interact with and adapt to nanoparticles used in drug delivery. This experience motivated me to study how the surface properties of nanoparticles can be modified to enhance biological sensing. When I transitioned to my postdoctoral research, this question led me to discover the role of cell-membrane curvature, which led to publications and my current research focus. I wouldn’t have started in this area without writing that review.

Collection: Careers toolkit

A common problem for students writing their first reviews is being overly ambitious. When I wrote mine, I imagined producing a comprehensive summary of every single type of nanomaterial used in biological applications. It ended up becoming a colossal piece of work, with too many papers discussed and without a clear way to categorize them. We published the work in the end, but decided to limit the discussion strictly to nanoparticles for biological sensing, rather than covering how different nanomaterials are used in biology.

My advice to students is to accept that a review is unlike a textbook: it should offer a more focused discussion, and it’s OK to skip some topics so that you do not distract your readers. Students should also consider editorial deadlines, especially for invited reviews: make sure that the review’s scope is not so extensive that it delays the writing.

A good review should also avoid jargon and explain the basic concepts for someone who is new to the field. Although I trained as an engineer, I’m interested in biology, and my research is about developing nanomaterials to manipulate proteins at the cell membrane and how this can affect ageing and cancer. As an ‘outsider’, the reviews that I find most useful for these biological topics are those that speak to me in accessible scientific language.

Bozhi Tian likes to get a variety of perspectives into a review. Credit: Aleksander Prominski

BOZHI TIAN: Have a process and develop your style

Associate professor of chemistry, University of Chicago, Illinois.

In my lab, we start by asking: what is the purpose of this review? My reasons for writing one can include the chance to contribute insights to the scientific community and identify opportunities for my research. I also see review writing as a way to train early-career researchers in soft skills such as project management and leadership. This is especially true for lead authors, because they will learn to work with their co-authors to integrate the various sections into a piece with smooth transitions and no overlaps.

After we have identified the need and purpose of a review article, I will form a team from the researchers in my lab. I try to include students with different areas of expertise, because it is useful to get a variety of perspectives. For example, in the review ‘An atlas of nano-enabled neural interfaces’ 2 , we had authors with backgrounds in biophysics, neuroengineering, neurobiology and materials sciences focusing on different sections of the review.

After this, I will discuss an outline with my team. We go through multiple iterations to make sure that we have scanned the literature sufficiently and do not repeat discussions that have appeared in other reviews. It is also important that the outline is not decided by me alone: students often have fresh ideas that they can bring to the table. Once this is done, we proceed with the writing.

I often remind my students to imagine themselves as ‘artists of science’ and encourage them to develop how they write and present information. Adding more words isn’t always the best way: for example, I enjoy using tables to summarize research progress and suggest future research trajectories. I’ve also considered including short videos in our review papers to highlight key aspects of the work. I think this can increase readership and accessibility because these videos can be easily shared on social-media platforms.

ANKITA ANIRBAN: Timeliness and figures make a huge difference

Editor, Nature Reviews Physics .

One of my roles as a journal editor is to evaluate proposals for reviews. The best proposals are timely and clearly explain why readers should pay attention to the proposed topic.

It is not enough for a review to be a summary of the latest growth in the literature: the most interesting reviews instead provide a discussion about disagreements in the field.

Careers Collection: Publishing

Scientists often centre the story of their primary research papers around their figures — but when it comes to reviews, figures often take a secondary role. In my opinion, review figures are more important than most people think. One of my favourite review-style articles 3 presents a plot bringing together data from multiple research papers (many of which directly contradict each other). This is then used to identify broad trends and suggest underlying mechanisms that could explain all of the different conclusions.

An important role of a review article is to introduce researchers to a field. For this, schematic figures can be useful to illustrate the science being discussed, in much the same way as the first slide of a talk should. That is why, at Nature Reviews, we have in-house illustrators to assist authors. However, simplicity is key, and even without support from professional illustrators, researchers can still make use of many free drawing tools to enhance the value of their review figures.

Yoojin Choi recommends that researchers be open to critiques when writing reviews. Credit: Yoojin Choi

YOOJIN CHOI: Stay updated and be open to suggestions

Research assistant professor, Korea Advanced Institute of Science and Technology, Daejeon.

I started writing the review ‘Biosynthesis of inorganic nanomaterials using microbial cells and bacteriophages’ 4 as a PhD student in 2018. It took me one year to write the first draft because I was working on the review alongside my PhD research and mostly on my own, with support from my adviser. It took a further year to complete the processes of peer review, revision and publication. During this time, many new papers and even competing reviews were published. To provide the most up-to-date and original review, I had to stay abreast of the literature. In my case, I made use of Google Scholar, which I set to send me daily updates of relevant literature based on key words.

Through my review-writing process, I also learnt to be more open to critiques to enhance the value and increase the readership of my work. Initially, my review was focused only on using microbial cells such as bacteria to produce nanomaterials, which was the subject of my PhD research. Bacteria such as these are known as biofactories: that is, organisms that produce biological material which can be modified to produce useful materials, such as magnetic nanoparticles for drug-delivery purposes.

Synchronized editing: the future of collaborative writing

However, when the first peer-review report came back, all three reviewers suggested expanding the review to cover another type of biofactory: bacteriophages. These are essentially viruses that infect bacteria, and they can also produce nanomaterials.

The feedback eventually led me to include a discussion of the differences between the various biofactories (bacteriophages, bacteria, fungi and microalgae) and their advantages and disadvantages. This turned out to be a great addition because it made the review more comprehensive.

Writing the review also led me to an idea about using nanomaterial-modified microorganisms to produce chemicals, which I’m still researching now.

PAULA MARTIN-GONZALEZ: Make good use of technology

PhD student, University of Cambridge, UK.

Just before the coronavirus lockdown, my PhD adviser and I decided to write a literature review discussing the integration of medical imaging with genomics to improve ovarian cancer management.

As I was researching the review, I noticed a trend in which some papers were consistently being cited by many other papers in the field. It was clear to me that those papers must be important, but as a new member of the field of integrated cancer biology, it was difficult to immediately find and read all of these ‘seminal papers’.

That was when I decided to code a small application to make my literature research more efficient. Using my code, users can enter a query, such as ‘ovarian cancer, computer tomography, radiomics’, and the application searches for all relevant literature archived in databases such as PubMed that feature these key words.

The code then identifies the relevant papers and creates a citation graph of all the references cited in the results of the search. The software highlights papers that have many citation relationships with other papers in the search, and could therefore be called seminal papers.

My code has substantially improved how I organize papers and has informed me of key publications and discoveries in my research field: something that would have taken more time and experience in the field otherwise. After I shared my code on GitHub, I received feedback that it can be daunting for researchers who are not used to coding. Consequently, I am hoping to build a more user-friendly interface in a form of a web page, akin to PubMed or Google Scholar, where users can simply input their queries to generate citation graphs.

Tools and techniques

Most reference managers on the market offer similar capabilities when it comes to providing a Microsoft Word plug-in and producing different citation styles. But depending on your working preferences, some might be more suitable than others.

Reference managers

Here is a comparison of the more popular collaborative writing tools, but there are other options, including Fidus Writer, Manuscript.io, Authorea and Stencila.

Collaborative writing tools

*Markdown and LaTex are code-based formatting languages favoured by physicists, mathematicians and computer scientists who code on a regular basis, and less popular in other disciplines such as biology and chemistry.

doi: https://doi.org/10.1038/d41586-020-03422-x

Interviews have been edited for length and clarity.

Updates & Corrections

Correction 09 December 2020 : An earlier version of the tables in this article included some incorrect details about the programs Zotero, Endnote and Manubot. These have now been corrected.

Hsing, I.-M., Xu, Y. & Zhao, W. Electroanalysis 19 , 755–768 (2007).

Article   Google Scholar  

Ledesma, H. A. et al. Nature Nanotechnol. 14 , 645–657 (2019).

Article   PubMed   Google Scholar  

Brahlek, M., Koirala, N., Bansal, N. & Oh, S. Solid State Commun. 215–216 , 54–62 (2015).

Choi, Y. & Lee, S. Y. Nature Rev. Chem . https://doi.org/10.1038/s41570-020-00221-w (2020).

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

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

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

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Research Methods

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• Literature Review Research
• Research Design
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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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How to Write a Literature Review: Six Steps to Get You from Start to Finish

Writing-a-literature-review-six-steps-to-get-you-from-start-to-finish.

Tanya Golash-Boza, Associate Professor of Sociology, University of California

February 03, 2022

Writing a literature review is often the most daunting part of writing an article, book, thesis, or dissertation. “The literature” seems (and often is) massive. I have found it helpful to be as systematic as possible when completing this gargantuan task.

Sonja Foss and William Walters* describe an efficient and effective way of writing a literature review. Their system provides an excellent guide for getting through the massive amounts of literature for any purpose: in a dissertation, an M.A. thesis, or preparing a research article for publication  in any field of study. Below is a  summary of the steps they outline as well as a step-by-step method for writing a literature review.

How to Write a Literature Review

Step One: Decide on your areas of research:

Before you begin to search for articles or books, decide beforehand what areas you are going to research. Make sure that you only get articles and books in those areas, even if you come across fascinating books in other areas. A literature review I am currently working on, for example, explores barriers to higher education for undocumented students.

Step Two: Search for the literature:

Conduct a comprehensive bibliographic search of books and articles in your area. Read the abstracts online and download and/or print those articles that pertain to your area of research. Find books in the library that are relevant and check them out. Set a specific time frame for how long you will search. It should not take more than two or three dedicated sessions.

Step Three: Find relevant excerpts in your books and articles:

Skim the contents of each book and article and look specifically for these five things:

1. Claims, conclusions, and findings about the constructs you are investigating

2. Definitions of terms

3. Calls for follow-up studies relevant to your project

4. Gaps you notice in the literature

5. Disagreement about the constructs you are investigating

When you find any of these five things, type the relevant excerpt directly into a Word document. Don’t summarize, as summarizing takes longer than simply typing the excerpt. Make sure to note the name of the author and the page number following each excerpt. Do this for each article and book that you have in your stack of literature. When you are done, print out your excerpts.

Step Four: Code the literature:

Get out a pair of scissors and cut each excerpt out. Now, sort the pieces of paper into similar topics. Figure out what the main themes are. Place each excerpt into a themed pile. Make sure each note goes into a pile. If there are excerpts that you can’t figure out where they belong, separate those and go over them again at the end to see if you need new categories. When you finish, place each stack of notes into an envelope labeled with the name of the theme.

Step Five: Create Your Conceptual Schema:

Type, in large font, the name of each of your coded themes. Print this out, and cut the titles into individual slips of paper. Take the slips of paper to a table or large workspace and figure out the best way to organize them. Are there ideas that go together or that are in dialogue with each other? Are there ideas that contradict each other? Move around the slips of paper until you come up with a way of organizing the codes that makes sense. Write the conceptual schema down before you forget or someone cleans up your slips of paper.

Step Six: Begin to Write Your Literature Review:

Choose any section of your conceptual schema to begin with. You can begin anywhere, because you already know the order. Find the envelope with the excerpts in them and lay them on the table in front of you. Figure out a mini-conceptual schema based on that theme by grouping together those excerpts that say the same thing. Use that mini-conceptual schema to write up your literature review based on the excerpts that you have in front of you. Don’t forget to include the citations as you write, so as not to lose track of who said what. Repeat this for each section of your literature review.

Once you complete these six steps, you will have a complete draft of your literature review. The great thing about this process is that it breaks down into manageable steps something that seems enormous: writing a literature review.

I think that Foss and Walter’s system for writing the literature review is ideal for a dissertation, because a Ph.D. candidate has already read widely in his or her field through graduate seminars and comprehensive exams.

It may be more challenging for M.A. students, unless you are already familiar with the literature. It is always hard to figure out how much you need to read for deep meaning, and how much you just need to know what others have said. That balance will depend on how much you already know.

For people writing literature reviews for articles or books, this system also could work, especially when you are writing in a field with which you are already familiar. The mere fact of having a system can make the literature review seem much less daunting, so I recommend this system for anyone who feels overwhelmed by the prospect of writing a literature review.

*Destination Dissertation: A Traveler's Guide to a Done Dissertation

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How To Structure Your Literature Review

3 options to help structure your chapter.

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

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

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

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

But wait – is this the right time?

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

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

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

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

Need a helping hand?

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

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

1: The Introduction Section

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

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

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

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

2: The Body Section

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

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

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

Option 1: Chronological (according to date)

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

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

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

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

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

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

Option 2: Thematic (grouped by theme)

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

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

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

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

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

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

Option 3: Methodological

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

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

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

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

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

3: The Conclusion Section

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

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

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

Example: Thematically Structured Review

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

Let’s Recap

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

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

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

Psst… there’s more!

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

28 Comments

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

I agree with you Marin… A great piece

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

Awesome article for my research.

I thank you immensely for this wonderful guide

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

Very educative and good time to get guide. Thank you

Great work, very insightful. Thank you.

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

Thank you very much, very helpful

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

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

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

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

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

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

Beautifully clear.nThank you!

Lucid! Thankyou!

Brilliant work, well understood, many thanks

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

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

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

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

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

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

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

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

Asking questions are actually fastidious thing if you are not understanding anything fully, but this article presents good understanding yet.

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Ten Simple Rules for Writing a Literature Review

Marco pautasso.

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

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

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

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

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

Rule 1: Define a Topic and Audience

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

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

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

Rule 2: Search and Re-search the Literature

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

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

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

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

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

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

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

Rule 3: Take Notes While Reading

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

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

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

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

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

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

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

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

Rule 6: Be Critical and Consistent

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

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

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

Rule 7: Find a Logical Structure

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

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

Rule 8: Make Use of Feedback

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

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

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

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

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

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

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

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

Acknowledgments

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

Funding Statement

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

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What is a literature review?

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

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

Why is it important?

A literature review is important because it:

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

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1. Choose a topic. Define your research question.

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

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

2. Decide on the scope of your review

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

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

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

Make a list of the databases you will search. 

Where to find databases:

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

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

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

Review the literature

Some questions to help you analyze the research:

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

Tips: 

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

A literature review is a critical analysis of the literature related to your research topic. It evaluates and critiques the literature to establish a theoretical framework for your research topic and/or identify a gap in the existing research that your research will address.

A literature review is not a summary of the literature. You need to engage deeply and critically with the literature. Your literature review should show your understanding of the literature related to your research topic and lead to presenting a rationale for your research.

A literature review focuses on:

• the context of the topic
• key concepts, ideas, theories and methodologies
• key researchers, texts and seminal works
• major issues and debates
• identifying conflicting evidence
• the main questions that have been asked around the topic
• the organisation of knowledge on the topic
• definitions, particularly those that are contested
• showing how your research will advance scholarly knowledge (generally referred to as identifying the ‘gap’).

This module will guide you through the functions of a literature review; the typical process of conducting a literature review (including searching for literature and taking notes); structuring your literature review within your thesis and organising its internal ideas; and styling the language of your literature review.

The purposes of a literature review

A literature review serves two main purposes:

1) To show awareness of the present state of knowledge in a particular field, including:

• seminal authors
• the main empirical research
• theoretical positions
• controversies
• breakthroughs as well as links to other related areas of knowledge.

2) To provide a foundation for the author’s research. To do that, the literature review needs to:

• help the researcher define a hypothesis or a research question, and how answering the question will contribute to the body of knowledge;
• provide a rationale for investigating the problem and the selected methodology;
• provide a particular theoretical lens, support the argument, or identify gaps.

Before you engage further with this module, try the quiz below to see how much you already know about literature reviews.

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15 Literature Review Examples

Chris Drew (PhD)

Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education. [Image Descriptor: Photo of Chris]

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Literature reviews are a necessary step in a research process and often required when writing your research proposal . They involve gathering, analyzing, and evaluating existing knowledge about a topic in order to find gaps in the literature where future studies will be needed.

Ideally, once you have completed your literature review, you will be able to identify how your research project can build upon and extend existing knowledge in your area of study.

Generally, for my undergraduate research students, I recommend a narrative review, where themes can be generated in order for the students to develop sufficient understanding of the topic so they can build upon the themes using unique methods or novel research questions.

If you’re in the process of writing a literature review, I have developed a literature review template for you to use – it’s a huge time-saver and walks you through how to write a literature review step-by-step:

Get your time-saving templates here to write your own literature review.

Literature Review Examples

For the following types of literature review, I present an explanation and overview of the type, followed by links to some real-life literature reviews on the topics.

1. Narrative Review Examples

Also known as a traditional literature review, the narrative review provides a broad overview of the studies done on a particular topic.

It often includes both qualitative and quantitative studies and may cover a wide range of years.

The narrative review’s purpose is to identify commonalities, gaps, and contradictions in the literature .

I recommend to my students that they should gather their studies together, take notes on each study, then try to group them by themes that form the basis for the review (see my step-by-step instructions at the end of the article).

Example Study

Title: Communication in healthcare: a narrative review of the literature and practical recommendations

Citation: Vermeir, P., Vandijck, D., Degroote, S., Peleman, R., Verhaeghe, R., Mortier, E., … & Vogelaers, D. (2015). Communication in healthcare: a narrative review of the literature and practical recommendations. International journal of clinical practice , 69 (11), 1257-1267.

Source: https://onlinelibrary.wiley.com/doi/pdf/10.1111/ijcp.12686  

Overview: This narrative review analyzed themes emerging from 69 articles about communication in healthcare contexts. Five key themes were found in the literature: poor communication can lead to various negative outcomes, discontinuity of care, compromise of patient safety, patient dissatisfaction, and inefficient use of resources. After presenting the key themes, the authors recommend that practitioners need to approach healthcare communication in a more structured way, such as by ensuring there is a clear understanding of who is in charge of ensuring effective communication in clinical settings.

Other Examples

• Burnout in United States Healthcare Professionals: A Narrative Review (Reith, 2018) – read here
• Examining the Presence, Consequences, and Reduction of Implicit Bias in Health Care: A Narrative Review (Zestcott, Blair & Stone, 2016) – read here
• A Narrative Review of School-Based Physical Activity for Enhancing Cognition and Learning (Mavilidi et al., 2018) – read here
• A narrative review on burnout experienced by medical students and residents (Dyrbye & Shanafelt, 2015) – read here

2. Systematic Review Examples

This type of literature review is more structured and rigorous than a narrative review. It involves a detailed and comprehensive plan and search strategy derived from a set of specified research questions.

The key way you’d know a systematic review compared to a narrative review is in the methodology: the systematic review will likely have a very clear criteria for how the studies were collected, and clear explanations of exclusion/inclusion criteria. 

The goal is to gather the maximum amount of valid literature on the topic, filter out invalid or low-quality reviews, and minimize bias. Ideally, this will provide more reliable findings, leading to higher-quality conclusions and recommendations for further research.

You may note from the examples below that the ‘method’ sections in systematic reviews tend to be much more explicit, often noting rigid inclusion/exclusion criteria and exact keywords used in searches.

Title: The importance of food naturalness for consumers: Results of a systematic review  

Citation: Roman, S., Sánchez-Siles, L. M., & Siegrist, M. (2017). The importance of food naturalness for consumers: Results of a systematic review. Trends in food science & technology , 67 , 44-57.

Source: https://www.sciencedirect.com/science/article/pii/S092422441730122X  

Overview: This systematic review included 72 studies of food naturalness to explore trends in the literature about its importance for consumers. Keywords used in the data search included: food, naturalness, natural content, and natural ingredients. Studies were included if they examined consumers’ preference for food naturalness and contained empirical data. The authors found that the literature lacks clarity about how naturalness is defined and measured, but also found that food consumption is significantly influenced by perceived naturalness of goods.

• A systematic review of research on online teaching and learning from 2009 to 2018 (Martin, Sun & Westine, 2020) – read here
• Where Is Current Research on Blockchain Technology? (Yli-Huumo et al., 2016) – read here
• Universities—industry collaboration: A systematic review (Ankrah & Al-Tabbaa, 2015) – read here
• Internet of Things Applications: A Systematic Review (Asghari, Rahmani & Javadi, 2019) – read here

3. Meta-analysis

This is a type of systematic review that uses statistical methods to combine and summarize the results of several studies.

Due to its robust methodology, a meta-analysis is often considered the ‘gold standard’ of secondary research , as it provides a more precise estimate of a treatment effect than any individual study contributing to the pooled analysis.

Furthermore, by aggregating data from a range of studies, a meta-analysis can identify patterns, disagreements, or other interesting relationships that may have been hidden in individual studies.

This helps to enhance the generalizability of findings, making the conclusions drawn from a meta-analysis particularly powerful and informative for policy and practice.

Title: Cholesterol and Alzheimer’s Disease Risk: A Meta-Meta-Analysis

Citation: Sáiz-Vazquez, O., Puente-Martínez, A., Ubillos-Landa, S., Pacheco-Bonrostro, J., & Santabárbara, J. (2020). Cholesterol and Alzheimer’s disease risk: a meta-meta-analysis. Brain sciences, 10(6), 386.

Source: https://doi.org/10.3390/brainsci10060386  

O verview: This study examines the relationship between cholesterol and Alzheimer’s disease (AD). Researchers conducted a systematic search of meta-analyses and reviewed several databases, collecting 100 primary studies and five meta-analyses to analyze the connection between cholesterol and Alzheimer’s disease. They find that the literature compellingly demonstrates that low-density lipoprotein cholesterol (LDL-C) levels significantly influence the development of Alzheimer’s disease.

• The power of feedback revisited: A meta-analysis of educational feedback research (Wisniewski, Zierer & Hattie, 2020) – read here
• How Much Does Education Improve Intelligence? A Meta-Analysis (Ritchie & Tucker-Drob, 2018) – read here
• A meta-analysis of factors related to recycling (Geiger et al., 2019) – read here
• Stress management interventions for police officers and recruits (Patterson, Chung & Swan, 2014) – read here

Other Types of Reviews

• Scoping Review: This type of review is used to map the key concepts underpinning a research area and the main sources and types of evidence available. It can be undertaken as stand-alone projects in their own right, or as a precursor to a systematic review.
• Rapid Review: This type of review accelerates the systematic review process in order to produce information in a timely manner. This is achieved by simplifying or omitting stages of the systematic review process.
• Integrative Review: This review method is more inclusive than others, allowing for the simultaneous inclusion of experimental and non-experimental research. The goal is to more comprehensively understand a particular phenomenon.
• Critical Review: This is similar to a narrative review but requires a robust understanding of both the subject and the existing literature. In a critical review, the reviewer not only summarizes the existing literature, but also evaluates its strengths and weaknesses. This is common in the social sciences and humanities .
• State-of-the-Art Review: This considers the current level of advancement in a field or topic and makes recommendations for future research directions. This type of review is common in technological and scientific fields but can be applied to any discipline.

How to Write a Narrative Review (Tips for Undergrad Students)

Most undergraduate students conducting a capstone research project will be writing narrative reviews. Below is a five-step process for conducting a simple review of the literature for your project.

• Search for Relevant Literature: Use scholarly databases related to your field of study, provided by your university library, along with appropriate search terms to identify key scholarly articles that have been published on your topic.
• Evaluate and Select Sources: Filter the source list by selecting studies that are directly relevant and of sufficient quality, considering factors like credibility , objectivity, accuracy, and validity.
• Analyze and Synthesize: Review each source and summarize the main arguments  in one paragraph (or more, for postgrad). Keep these summaries in a table.
• Identify Themes: With all studies summarized, group studies that share common themes, such as studies that have similar findings or methodologies.
• Write the Review: Write your review based upon the themes or subtopics you have identified. Give a thorough overview of each theme, integrating source data, and conclude with a summary of the current state of knowledge then suggestions for future research based upon your evaluation of what is lacking in the literature.

Literature reviews don’t have to be as scary as they seem. Yes, they are difficult and require a strong degree of comprehension of academic studies. But it can be feasibly done through following a structured approach to data collection and analysis. With my undergraduate research students (who tend to conduct small-scale qualitative studies ), I encourage them to conduct a narrative literature review whereby they can identify key themes in the literature. Within each theme, students can critique key studies and their strengths and limitations , in order to get a lay of the land and come to a point where they can identify ways to contribute new insights to the existing academic conversation on their topic.

Ankrah, S., & Omar, A. T. (2015). Universities–industry collaboration: A systematic review. Scandinavian Journal of Management, 31(3), 387-408.

Asghari, P., Rahmani, A. M., & Javadi, H. H. S. (2019). Internet of Things applications: A systematic review. Computer Networks , 148 , 241-261.

Dyrbye, L., & Shanafelt, T. (2016). A narrative review on burnout experienced by medical students and residents. Medical education , 50 (1), 132-149.

Geiger, J. L., Steg, L., Van Der Werff, E., & Ünal, A. B. (2019). A meta-analysis of factors related to recycling. Journal of environmental psychology , 64 , 78-97.

Martin, F., Sun, T., & Westine, C. D. (2020). A systematic review of research on online teaching and learning from 2009 to 2018. Computers & education , 159 , 104009.

Mavilidi, M. F., Ruiter, M., Schmidt, M., Okely, A. D., Loyens, S., Chandler, P., & Paas, F. (2018). A narrative review of school-based physical activity for enhancing cognition and learning: The importance of relevancy and integration. Frontiers in psychology , 2079.

Patterson, G. T., Chung, I. W., & Swan, P. W. (2014). Stress management interventions for police officers and recruits: A meta-analysis. Journal of experimental criminology , 10 , 487-513.

Reith, T. P. (2018). Burnout in United States healthcare professionals: a narrative review. Cureus , 10 (12).

Ritchie, S. J., & Tucker-Drob, E. M. (2018). How much does education improve intelligence? A meta-analysis. Psychological science , 29 (8), 1358-1369.

Roman, S., Sánchez-Siles, L. M., & Siegrist, M. (2017). The importance of food naturalness for consumers: Results of a systematic review. Trends in food science & technology , 67 , 44-57.

Sáiz-Vazquez, O., Puente-Martínez, A., Ubillos-Landa, S., Pacheco-Bonrostro, J., & Santabárbara, J. (2020). Cholesterol and Alzheimer’s disease risk: a meta-meta-analysis. Brain sciences, 10(6), 386.

Vermeir, P., Vandijck, D., Degroote, S., Peleman, R., Verhaeghe, R., Mortier, E., … & Vogelaers, D. (2015). Communication in healthcare: a narrative review of the literature and practical recommendations. International journal of clinical practice , 69 (11), 1257-1267.

Wisniewski, B., Zierer, K., & Hattie, J. (2020). The power of feedback revisited: A meta-analysis of educational feedback research. Frontiers in Psychology , 10 , 3087.

Yli-Huumo, J., Ko, D., Choi, S., Park, S., & Smolander, K. (2016). Where is current research on blockchain technology?—a systematic review. PloS one , 11 (10), e0163477.

Zestcott, C. A., Blair, I. V., & Stone, J. (2016). Examining the presence, consequences, and reduction of implicit bias in health care: a narrative review. Group Processes & Intergroup Relations , 19 (4), 528-542

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How to Choose Titles for Literature Reviews

Simple Topics for Research Papers

At some point in your academic career, you may have to write a literature review to summarize what you've learned in your field. Writing a strong literature review takes a lot of time, research and focus, as there are many different components that go into it. However, if this is an assignment you need to do for one of your classes, all you need to do is follow a few steps to choose the right titles, and you'll have a great literature review in no time.

What Is a Literature Review?

A literature review is an essay that discusses published works in a specific subject area. It's something that many masters students may need to do for a dissertation, thesis or just a hefty assignment for a course. It's not simply a review of one piece of literature, but a well-thought-out evaluation of several pieces of literature that fall under the same topic or genre. It could be a concise summary of the works, or it can really describe the pieces in depth, usually by creating a synthesis combined with several interpretations.

Brainstorm, Research, Decide Your Topic

Before you begin writing your literature review, you will need to do some brainstorming and research. Most students generally have an idea of what their topic needs to be, but perhaps they're not sure what kind of literature pieces they should be looking for. First, check what your assignment calls for. Does it say how many sources are required, or are you able to choose? This should then give you an idea of how long your literature review will be, and how much time you need to spend searching.

Then, think of a few potential topics for your literature review, then conduct a preliminary search. Based on your results of that quick search, eliminate the topics which don't seem to have as many pieces of literature available for them. Finally, decide on your specific topic and stick to it.

Narrow Down the Kinds of Publications You Will Use

Next, you will need to decide what kind of literature you're going to look for before you search and choose the titles. Narrowing down your research to either just books, just trade journals, just websites, just articles, just peer review publications or a combination of several of these is a strategy many students use. This can help you reach the next step of actually deciding on titles that much quicker. This way, you know where you need to conduct your search, so you don't waste time looking in the wrong places.

Go to the Library or Search Online

The final step in choosing titles for your literature review is to go to the source. Most of the time, students won't know which literature pieces they want to use, mainly because they don't yet know all the publications that have been written on their specific topic. Unless you're doing a literature review of a book series you've read countless times already.

Exploring the library or finding abstracts online of articles you can purchase from journals is the best place to start. Type in the keywords of your topic with the term "article" or "publication" next to it and begin your search. Select as many titles as you see fit, including some you may have found in your preliminary search. If you're having trouble, utilize experts in the field. Perhaps you can ask your professor or a librarian to point you in the right direction. Once you have a few good solid titles that you've already skimmed, decide on which ones you will use to write your literature review.

Tips for Choosing Titles for Your Literature Review

Trying to find titles for a literature review may be a bit overwhelming, as there are likely many titles you could use to support your topic. Therefore, once you begin searching, give yourself a time limit, and only allow yourself to search within that time. Otherwise, you may end up sleeping in the library! Additionally, as you're conducting your search for titles, you may find that someone has already published a literature review on a very similar topic to your own. Don't let this frustrate you and don't start over. Just keep going with it.

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Exploring the factors driving AI adoption in production: a systematic literature review and future research agenda

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• Published: 23 August 2024

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• Heidi Heimberger   ORCID: orcid.org/0000-0003-3390-0219 1 , 2 ,
• Djerdj Horvat   ORCID: orcid.org/0000-0003-3747-3402 1 &
• Frank Schultmann   ORCID: orcid.org/0000-0001-6405-9763 1  

Our paper analyzes the current state of research on artificial intelligence (AI) adoption from a production perspective. We represent a holistic view on the topic which is necessary to get a first understanding of AI in a production-context and to build a comprehensive view on the different dimensions as well as factors influencing its adoption. We review the scientific literature published between 2010 and May 2024 to analyze the current state of research on AI in production. Following a systematic approach to select relevant studies, our literature review is based on a sample of articles that contribute to production-specific AI adoption. Our results reveal that the topic has been emerging within the last years and that AI adoption research in production is to date still in an early stage. We are able to systematize and explain 35 factors with a significant role for AI adoption in production and classify the results in a framework. Based on the factor analysis, we establish a future research agenda that serves as a basis for future research and addresses open questions. Our paper provides an overview of the current state of the research on the adoption of AI in a production-specific context, which forms a basis for further studies as well as a starting point for a better understanding of the implementation of AI in practice.

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1 Introduction

The technological change resulting from deep digitisation and the increasing use of digital technologies has reached and transformed many sectors [ 1 ]. In manufacturing, the development of a new industrial age, characterized by extensive automation and digitisation of processes [ 2 ], is changing the sector’s ‘technological reality’ [ 3 ] by integrating a wide range of information and communication technologies (such as Industry 4.0-related technologies) into production processes [ 4 ].

Although the evolution of AI traces back to the year 1956 (as part of the Dartmouth Conference) [ 5 ], its development has progressed rapidly, especially since the 2010s [ 6 ]. Driven by improvements, such as the fast and low-cost development of smart hardware, the enhancement of algorithms as well as the capability to manage big data [ 7 ], there is an increasing number of AI applications available for implementation today [ 8 ]. The integration of AI into production processes promises to boost the productivity, efficiency as well as automation of processes [ 9 ], but is currently still in its infancy [ 10 ] and manufacturing firms seem to still be hesitant to adopt AI in a production-context. This appears to be driven by the high complexity of AI combined with the lack of practical knowledge about its implementation in production and several other influencing factors [ 11 , 12 ].

In the literature, many contributions analyze AI from a technological perspective, mainly addressing underlying models, algorithms, and developments of AI tools. Various authors characterise both machine learning and deep learning as key technologies of AI [ 8 , 13 ], which are often applied in combination with other AI technologies, such as natural language recognition. While promising areas for AI application already exist in various domains such as marketing [ 14 ], procurement [ 15 ], supply chain management [ 16 ] or innovation management [ 17 ], the integration of AI into production processes also provides significant performance potentials, particularly in the areas of maintenance [ 18 ], quality control [ 19 ] and production planning and management [ 20 ]. However, AI adoption requires important technological foundations, such as the provision of data and the necessary infrastructure, which must be ensured [ 11 , 12 , 21 ]. Although the state of the art literature provides important insights into possible fields of application of AI in production, the question remains: To what extent are these versatile applications already in use and what is required for their successful adoption?

Besides the technology perspective of AI, a more human-oriented field of discussion is debated in scientific literature [ 22 ]. While new technologies play an essential role in driving business growth in the digital transformation of the production industry, the increasing interaction between humans and intelligent machines (also referred to as ‘augmentation’) creates stress challenges [ 23 ] and impacts work [ 24 ], which thus creates managerial challenges in organizations [ 25 , 26 ]. One of the widely discussed topics in this context is the fear of AI threatening jobs (including production jobs), which was triggered by e.g. a study of Frey, Osborne [ 27 ]. Another issue associated to the fear of machines replacing humans is the lack of acceptance resulting from the mistrust of technologies [ 28 , 29 ]. This can also be linked to the various ethical challenges involved in working with AI [ 22 ]. This perspective, which focuses on the interplay between AI and humans [ 30 ], reveals the tension triggered by AI. Although this is discussed from different angles, the question remains how these aspects influence the adoption of AI in production.

Another thematic stream of current literature can be observed in a series of contributions on the organizational aspects of the technology. In comparison to the two research areas discussed above, the number of publications in this area seems to be smaller. This perspective focuses on issues to implement AI, such as the importance of a profound management structure [ 31 , 32 ], leadership [ 33 ], implications on the organizational culture [ 34 ] as well as the need for digital capabilities and special organizational skills [ 33 ]. Although some studies on the general adoption of AI without a sectoral focus have already been conducted (such as by Chen, Tajdini [ 35 ] or Kinkel, Baumgartner, Cherubini [ 36 ]) and hence, some initial factors influencing the adoption of AI can be derived, the contributions from this perspective are still scarce, are usually not specifically analyzed in the context of production or lack a comprehensive view on the organization in AI adoption.

While non-industry specific AI issues have been researched in recent years, the current literature misses a production-specific analysis of AI adoption, providing an understanding of the possibilities and issues related to integrating AI into the production context. Moreover, the existing literature tells us little about relevant mechanisms and factors underlying the adoption of AI in production processes, which include both technical, human-centered as well as organizational issues. As organizational understanding of AI in a business context is currently still in its early stages, it is difficult to find an aggregate view on the factors that can support companies in implementing AI initiatives in production [ 37 , 38 ]. Addressing this gap, we aim to systematise the current scientific knowledge on AI adoption, with a focus on production. By drawing on a systematic literature review (SLR), we examine existing studies on AI adoption in production and explore the main issues regarding adoption that are covered in the analyzed articles. Building on these findings, we conduct a comprehensive analysis of the existing studies with the aim of systematically investigating the key factors influencing the adoption of AI in production. This systematic approach paves the way for the formulation of a future research agenda.

Our SLR addresses three research questions (RQs). RQ1: What are the statistical characteristics of existing research on AI adoption in production? To answer this RQ, we conduct descriptive statistics of the analyzed studies and provide information on time trends, methods used in the research, and country specifications. RQ2: What factors influence the adoption of AI in production? RQ2 specifies the adoption factors and forms the core component of our analysis. By adoption factors, we mean the factors that influence the use of AI in production (both positively and negatively) and that must therefore be analyzed and taken into account. RQ3: What research topics are of importance to advance the research field of AI adoption in production? We address this RQ by using the analyzed literature as well as the key factors of AI adoption as a starting point to derive RQs that are not addressed and thus provide an outlook on the topic.

2 Methodology

In order to create a sound information base for both policy makers and practitioners on the topic of AI adoption in production, this paper follows the systematic approach of a SLR. For many fields, including management research, a SLR is an important tool to capture the diversity of existing knowledge on a specific topic for a scientific investigation [ 39 ]. The investigator often pursues multiple goals, such as capturing and assessing the existing environment and advancing the existing body of knowledge with a proprietary RQ [ 39 ] or identifying key research topics [ 40 ].

Our SLR aims to select, analyze, and synthesize findings from the existing literature on AI adoption in production over the past 24 years. In order to identify relevant data for our literature synthesis, we follow the systematic approach of the Preferred Reporting Items for Systematic reviews (PRISMA) [ 41 ]. In evaluating the findings, we draw on a mixed-methods approach, combining some quantitative analyses, especially on the descriptive aspects of the selected publications, as well as qualitative analyses aimed at evaluating and comparing the contents of the papers. Figure  1 graphically summarizes the methodological approach that guides the content of the following sub-chapters.

Methodical procedure of our SLR following PRISMA [ 41 ]

2.1 Data identification

Following the development of the specific RQs, we searched for suitable publications. To locate relevant studies, we chose to conduct a publication analysis in the databases Scopus, Web of Science and ScienceDirect as these databases primarily contain international scientific articles and provide a broad overview of the interdisciplinary research field and its findings. To align the search with the RQs [ 42 ], we applied predefined key words to search the titles, abstracts, and keywords of Scopus, Web of Science and ScienceDirect articles. Our research team conducted several pre-tests to determine the final search commands for which the test results were on target and increased the efficiency of the search [ 42 ]. Using the combination of Boolean operators, we covered the three topics of AI, production, and adoption by searching combinations of ‘Artificial Intelligence’ AND ‘production or manufacturing’ AND ‘adopt*’ in the three scientific databases. Although ‘manufacturing’ tends to stand for the whole sector and ‘production’ refers to the process, the two terms are often used to describe the same context. We also follow the view of Burbidge, Falster, Riis, Svendsen [ 43 ] and use the terms synonymously in this paper and therefore also include both terms as keywords in the study location as well as in the analysis.

AI research has been credited with a resurgence since 2010 [ 6 ], which is the reason for our choice of time horizon. Due to the increase in publications within the last years, we selected articles published online from 2010 to May 8, 2024 for our analysis. As document types, we included conference papers, articles, reviews, book chapters, conference reviews as well as books, focusing exclusively on contributions in English in the final publication stage. The result of the study location is a list of 3,833 documents whose titles, abstracts, and keywords meet the search criteria and are therefore included in the next step of the analysis.

2.2 Data analysis

For these 3,833 documents, we then conducted an abstract analysis, ‘us[ing] a set of explicit selection criteria to assess the relevance of each study found to see if it actually does address the research question’ [ 42 ]. For this step, we again conducted double-blind screenings (including a minimum of two reviewers) as pilot searches so that all reviewers have the same understanding of the decision rules and make equal decisions regarding their inclusion for further analysis.

To ensure the paper’s focus on all three topics regarded in our research (AI, production, and adoption), we followed clearly defined rules of inclusion and exclusion that all reviewers had to follow in the review process. As a first requirement for inclusion, AI must be the technology in focus that is analysed in the publication. If AI was only mentioned and not further specified, we excluded the publication. With a second requirement, we checked the papers for the context of analysis, which in our case must be production. If the core focus is beyond production, the publication was also excluded from further analysis. The third prerequisite for further consideration of the publication is the analysis of the adoption of a technology in the paper. If technology adoption is not addressed or adoption factors are not considered, we excluded the paper. An article was only selected for full-text analysis if, after analyzing the titles, abstracts, and keywords, a clear focus on all three research areas was visible and the inclusion criteria were met for all three contexts.

By using this tripartite inclusion analysis, we were able to analyse the publications in a structured way and to reduce the 3,833 selected documents in our double-blind approach to 300 articles that were chosen for the full-text analysis. In the process of finding full versions of these publications, we had to exclude three papers as we could not access them. For the rest of the 297 articles we obtained full access and thus included them for further analysis. After a thorough examination of the full texts, we again had to exclude 249 publications because they did not meet our content-related inclusion criteria mentioned above, although the abstract analysis gave indications that they did. As a result, we finally obtained 47 selected papers on which we base the literature analysis and synthesis (see Fig.  1 ).

2.3 Descriptive analysis

Figure  2 summarises the results of the descriptive analysis on the selected literature regarding AI adoption in production that we analyse in our SLR. From Fig.  2 a), which illustrates annual publication trends (2010–2024), the increase in publications on AI adoption in production over the past 5 years is evident, yet slightly declining after a peak in 2022. After a steady increase until 2022, in which 11 articles are included in the final analysis, 2023 features ten articles, followed by three articles for 2024 until the cut-off date in May 2024. Of the 47 papers identified through our search, the majority (n = 33) are peer-reviewed journal articles and the remaining thirteen contributions conference proceedings and one book chapter (see Fig.  2 b)).

Descriptive analyses of the selected articles addressing AI adoption in production

The identified contributions reveal some additional characteristics in terms of the authors country base (Fig.  2 c)) and research methods used (Fig.  2 d)). Almost four out of ten of the publications were written in collaboration with authors from several countries (n = 19). Six of the papers were published by authors from the United States, five from Germany and four from India. In terms of the applied research methods used by the researchers, a wide range of methods is used (see Fig.  2 c), with qualitative methods (n = 22) being the most frequently used.

2.4 Factor analysis

In order to derive a comprehensive list of factors that influence the use of AI in production at different levels, we follow a qualitative content analysis. It is based on inductive category development, avoiding prefabricated categories in order to allow new categories to emerge based on the content at hand [ 44 , 45 ]. To do this, we first read the entire text to gain an understanding of the content and then derive codes [ 46 ] that seem to capture key ideas [ 45 ]. The codes are subsequently sorted into distinct categories, each of which is clearly defined and establishes meaningful connections between different codes. Based on an iterative process with feedback loops, the assigned categories are continuously reviewed and updated as revisions are made [ 44 ].

Various factors at different levels are of significance to AI and influence technology adoption [ 47 , 48 ]. To identify the specific factors that are of importance for AI adoption in production, we analyze the selected contributions in terms of the factors considered, compare them with each other and consequently obtain a list of factors through a bottom-up approach. While some of the factors are based on empirical findings, others are expected factors that result from the research findings of the respective studies. Through our analysis, a list of 35 factors emerges that influence AI adoption in production which occur with varying frequency in the studies analyzed by our SLR. Table 1 visualizes each factor in the respective contributions sorted by the frequency of occurrence.

The presence of skills is considered a particularly important factor in AI adoption in the studies analyzed (n = 35). The availability of data (n = 25) as well as the need for ethical guidelines (n = 24) are also seen as key drivers of AI adoption, as data is seen as the basis for the implementation of AI and ethical issues must be addressed in handling such an advanced technology. As such, these three factors make up the accelerants of AI adoption in production that are most frequently cited in the studies analyzed.

Also of importance are issues of managerial support (n = 22), as well as performance measures and IT infrastructure (n = 20). Some factors were also mentioned, but only addressed by one study at a time: government support, industrial sector, product complexity, batch size, and R&D Intensity. These factors are often used as quantitatively measurable adoption factors, especially in empirical surveys, such the study by Kinkel, Baumgartner, Cherubini [ 36 ].

3 Factors influencing AI adoption

The 35 factors presented characteristically in Sect.  2.4 serve as the basis for our in-depth analysis and for developing a framework of influences on AI adoption in production which are grouped into supercategories. A supercategory describes a cluster of topics to which various factors of AI adoption in production can be assigned. We were able to define seven categories that influence AI adoption in production: the internal influences of ‘business and structure’, ‘organizational effectiveness’, ‘technology and system’, ‘data management’ as well as the external influences of the ‘regulatory environment’, ‘business environment’ and ‘economic environment’ (see Fig.  3 ). The factors that were mentioned most frequently (occurrence in at least half of the papers analyzed) are marked accordingly (*) in Fig.  3 .

Framework of factors influencing AI adoption in production

3.1 Internal Environment

The internal influences on AI adoption in production refer to factors that an organization carries internally and that thus also influence adoption from within. Such factors can usually be influenced and clearly controlled by the organization itself.

3.1.1 Business and structure

The supercategory ‘business and structure’ includes the various factors and characteristics that impact a company’s performance, operations, and strategic decision-making. By considering and analyzing these business variables when implementing AI in production processes, companies can develop effective strategies to optimize their performance, increase their competitiveness, and adapt to changes in the business environment.

To understand and grasp the benefits in the use of AI, quantitative performance measures for the current and potential use of AI in industrial production systems help to clarify the value and potential benefits of AI use [ 49 , 54 , 74 , 79 , 91 ]. Assessing possible risks [ 77 ] as well as the monetary expected benefits for AI (e.g. Return on Investment (ROI)) in production plays an important role for adoption decisions in market-oriented companies [ 57 , 58 , 63 , 65 , 78 ]. Due to financial constraints, managers behave cautiously in their investments [ 78 ], so they need to evaluate AI adoption as financially viable to want to make the investment [ 61 , 63 , 93 ] and also drive acceptance [ 60 ]. AI systems can significantly improve cost–benefit structures in manufacturing, thereby increasing the profitability of production systems [ 73 ] and making companies more resilient [ 75 ]. However, in most cases, the adoption of AI requires high investments and the allocation of resources (s.a. personnel or financial) for this purpose [ 50 , 51 , 57 , 80 , 94 ]. Consequently, a lack of budgets and high expected transition costs often hinder the implementation of smart concepts [ 56 , 62 , 67 , 82 , 84 , 92 ]. It is up to management to provide necessary funding for AI adoption [ 53 , 59 , 79 ], which is required, for example, for skill development of employees [ 59 , 61 , 63 ], IT adaptation [ 62 , 66 ], AI development [ 74 ] or hardware deployment [ 68 ]. In their empirical study, Kinkel, Baumgartner, Cherubini [ 36 ] confirm a positive correlation between company size and the intensity in the use of AI technologies. Large companies generally stand out with a higher propensity to adopt [ 53 ] as they have less difficulties in comparison to small firms regarding the availability of resources [ 69 ], such as know-how, budget [ 68 , 84 ] and general data organization [ 68 ]. Others argue that small companies tend to be more open to change and are characterized by faster decision-making processes [ 68 , 93 ]. Product complexity also influences a company’s propensity for AI. Companies that produce rather simple products are more likely to digitize, which in turn offers good starting points for AI adoption. On the other hand, complex product manufacturers (often characterized by small batch sizes) are often less able to standardize and automate [ 36 ]. The company’s produced batch size has a similar influence on AI adoption. Small and medium batch sizes in particular hinder the integration of intelligent technologies, as less automation often prevails here as well. Nevertheless, even small and medium lot sizes can benefit economically from AI [ 36 ]. Since a high R&D intensity indicates a high innovation capability of a company, it is assumed to have a positive influence on AI adoption, as companies with a high R&D intensity already invest heavily in and use new innovations. This in turn speaks for existing competencies, know how and structures [ 36 ].

3.1.2 Organizational effectiveness

This supercategory focuses on the broader aspects that contribute to the effectiveness, development, and success of an organization when implementing AI in a production context. As the factors are interconnected and influence each other, decision makers should consider them carefully.

Users´ trust in AI is an essential factor to enable successful AI adoption and use in production [ 52 , 68 , 78 , 79 , 88 , 90 ]. From the users´ perspective, AI often exhibits the characteristics of a black box because its inherent processes are not fully understood [ 50 , 90 ] which can lead individuals to develop a fear towards the unknown [ 71 ]. Because of this lack of understanding, successful interaction between humans and AI is not guaranteed [ 90 ], as trust is a foundation for decisions that machines are intended to make autonomously [ 52 , 91 ]. To strengthen faith in AI systems [ 76 , 80 ], AI users can be involved in AI design processes in order to understand appropriate tools [ 54 , 90 ]. In this context, trust is also discussed in close connection with transparency and regulation [ 79 ]. User resistance is considered a barrier to implementing new information technologies, as adoption requires change [ 53 , 62 , 92 ]. Ignorance, as a kind of resistance to change, is a main obstacle to successful digital transformation [ 51 , 56 , 65 ]. Some employees may resist the change brought about by AI because they fear losing their jobs [ 52 ] or have other concerns [ 78 ]. Overcoming resistance to technology adoption requires organizational change and is critical for the success of adoption [ 50 , 51 , 62 , 67 , 71 , 80 ]. Therefore, change management is important to create awareness of the importance of AI adoption and increase acceptance of the workforce [ 66 , 68 , 74 , 83 ]. Management commitment is seen as a significant driver of technology adoption [ 53 , 59 , 81 , 82 , 86 ] and a lack of commitment can negatively impact user adoption and workforce trust and lead to skepticism towards technology [ 86 ]. The top management’s understanding and support for the benefits of the adopted technology [ 53 , 56 , 67 , 78 , 93 , 94 ] enhances AI adoption, can prioritize its implementation and also affects the performance of the AI-enabled application [ 55 , 60 , 83 ]. Preparing, enabling, and thus empowering the workforce, are considered the management’s responsibility in the adoption of digital technologies [ 59 , 75 ]. This requires intelligent leadership [ 52 ] as decision makers need to integrate their workforce into decision-making processes [ 75 ]. Guidelines can support managers by providing access to best practices that help in the adoption of AI [ 50 ]. Critical measures to manage organizational change include the empowerment of visionaries or appointed AI champions leading the change and the collaborative development of digital roadmaps [ 54 , 62 ]. To demonstrate management commitment, managers can create such a dedicated role, consisting of an individual or a small group that is actively and enthusiastically committed to AI adoption in production. This body is considered the adoption manager, point of contact and internal driver of adoption [ 62 , 74 , 80 ]. AI initiatives in production do not necessarily have to be initiated by management. Although management support is essential for successful AI adoption, employees can also actively drive integration initially and thus realize pilot projects or initial trials [ 66 , 80 ]. The development of strategies as well as roadmaps is considered another enabling and necessary factor for the adoption of AI in production [ 50 , 53 , 54 , 62 , 71 , 93 ]. While many major AI strategies already exist at country level to further promote research and development of AI [ 87 ], strategy development is also important at the firm level [ 76 , 77 , 81 ]. In this context, strategies should not be delegated top-down, but be developed in a collaborative manner, i.e. by engaging the workforce [ 75 ] and be in alignment with clear visions [ 91 , 94 ]. Roadmaps are used to improve planning, support implementation, facilitate the adoption of smart technologies in manufacturing [ 93 ] and should be integrated into both business and IT strategy [ 62 , 66 ]. In practice, clear adoption roadmaps that provide approaches on how to effectively integrate AI into existing strategies and businesses are often lacking [ 56 , 87 ]. The need for AI-related skills in organizations is a widely discussed topic in AI adoption analyses [ 79 ]. In this context, the literature points both at the need for specific skills in the development and design of AI applications [ 57 , 71 , 72 , 73 , 76 , 93 ] as well as the skills in using the technology [ 53 , 65 , 73 , 74 , 75 , 84 , 93 ] which availability in the firm is not always given [ 49 ]. AI requires new digital skills [ 36 , 50 , 52 , 55 , 56 , 59 , 61 , 63 , 66 , 78 , 80 ], where e.g. advanced analytics [ 64 , 75 , 81 ], programming skills [ 68 ] and cybersecurity skills [ 78 , 93 ] gain importance. The lack of skills required for AI is seen as a major challenge of digital transformation, as a skilled workforce is considered a key resource for companies [ 51 , 54 , 56 , 60 , 62 , 67 , 69 , 70 , 82 , 93 ]. This lack of a necessary skillset hinders the adoption of AI tools in production systems [ 58 , 77 ]. Closely related to skills is the need for new training concepts, which organizations need to consider when integrating digital technologies [ 49 , 50 , 51 , 56 , 59 , 63 , 71 , 74 , 75 ]. Firms must invest in qualification in order to create necessary competences [ 73 , 78 , 80 , 81 , 92 ]. Additionally, education must target and further develop the skills required for effectively integrating intelligent technologies into manufacturing processes [ 54 , 61 , 62 , 83 ]. Regarding this issue, academic institutions must develop fitting curricula for data driven manufacturing engineering [ 64 ]. Another driving factor of AI adoption is the innovation culture of an organization, which is influenced by various drivers. For example, companies that operate in an environment with high innovation rates, facing intense competitive pressures are considered more likely to see smart technologies as a tool for strategic change [ 83 , 91 , 93 ]. These firms often invest in more expensive and advanced smart technologies as the pressure and resulting competition forces them to innovate [ 93 ]. Another way of approach this is that innovation capability can also be supported and complemented by AI, for example by intelligent systems supporting humans in innovation or even innovating on their own [ 52 ].The entrepreneurial orientation of a firm is characterized in particular by innovativeness [ 66 ], productivity [ 63 ], risk-taking [ 86 ] as well as continuous improvement [ 50 ]. Such characteristics of an innovating culture are considered essential for companies to recognise dynamic changes in the market and make adoption decisions [ 51 , 71 , 81 , 84 , 86 , 94 ]. The prevalence of a digital mindset in companies is important for technology adoption, as digital transformation affects the entire organizational culture and behavior [ 59 , 80 , 92 ] and a lack of a digital culture [ 50 , 65 ] as well as a ‘passive mindset’ [ 78 ] can hinder the digital transformation of firms. Organizations need to develop a corresponding culture [ 66 , 67 , 71 ], also referred to as ‘AI-ready-culture’ [ 54 ], that promotes development and encourages people and data through the incorporation of technology [ 71 , 75 ]. With the increasing adoption of smart technologies, a ‘new digital normal’ is emerging, characterized by hybrid work models, more human–machine interactions and an increased use of digital technologies [ 75 , 83 ].

3.1.3 Technology and System

The ‘technology and system’ supercategory focuses on the broader issues related to the technology and infrastructure that support organizational operations and provide the technical foundation for AI deployment.

By IT infrastructure we refer to issues regarding the foundational systems and IT needed for AI adoption in production. Industrial firms and their IT systems must achieve a mature technological readiness in order to enable successful AI adoption [ 51 , 60 , 67 , 69 , 83 ]. A lack of appropriate IT infrastructure [ 68 , 71 , 78 , 91 ] or small maturity of Internet of Things (IoT) technologies [ 70 ]) hinders the efficient use of data in production firms [ 56 ] which is why firms must update their foundational information systems for successful AI adoption [ 53 , 54 , 62 , 66 , 72 , 75 ]. IT and data security are fundamental for AI adoption and must be provided [ 50 , 51 , 68 , 82 ]. This requires necessary developments that can ensure security during AI implementation while complying with legal requirements [ 52 , 72 , 78 ]. Generally, security concerns are common when implementing AI innovations [ 72 , 79 , 91 , 94 ]. This fear of a lack of security can also prevent the release of (e.g. customer) data in a production environment [ 56 ]. Additionally, as industrial production systems are vulnerable to failures as well as cyberattacks, companies need to address security and cybersecurity measures [ 49 , 76 , 88 , 89 ]. Developing user-friendly AI solutions can facilitate the adoption of smart solutions by increasing user understanding and making systems easy to use by employees as well as quick to integrate [ 50 , 72 , 84 ]. When developing user-friendly solutions which satisfy user needs [ 76 ], it is particularly important to understand and integrate the user perspective in the development process [ 90 ]. If employees find technical solutions easy to use, they are more confident in its use and perceived usefulness increases [ 53 , 67 , 68 ]. The compatibility of AI with a firm and its existing systems, i.e., the extent to which AI matches existing processes, structures, and infrastructures [ 53 , 54 , 56 , 60 , 78 , 80 , 82 , 83 , 93 , 94 ], is considered an important requirement for the adoption of AI in IT systems [ 91 ]. Along with compatibility also comes connectivity, which is intended to ensure the links within the overall network and avoid silo thinking [ 59 ]. Connectivity and interoperability of AI-based processes within the company’s IT manufacturing systems must be ensured at different system levels and are considered key factors in the development of AI applications for production [ 50 , 72 , 89 ]. The design of modular AI solutions can increase system compatibility [ 84 ]. Firms deciding for AI adoption must address safety issues [ 51 , 54 , 59 , 72 , 73 , 78 ]. This includes both safety in the use and operation of AI [ 60 , 69 ]. In order to address safety concerns of integrating AI solutions in industrial systems [ 49 ], systems must secure high reliability [ 71 ]. AI can also be integrated as a safety enabler, for example, by providing technologies to monitor health and safety in the workplace to prevent fatigue and injury [ 75 ].

3.1.4 Data management

Since AI adoption in the organization is strongly data-driven, the ‘data management’ supercategory is dedicated to the comprehensive aspects related to the effective and responsible management of data within the organization.

Data privacy must be guaranteed when creating AI applications based on industrial production data [ 49 , 58 , 59 , 60 , 72 , 76 , 78 , 79 , 82 , 88 , 89 , 91 , 94 ] as ‘[M]anufacturing industries generate large volumes of unstructured and sensitive data during their daily operations’ [ 89 ]. Closely related to this is the need for anonymization and confidentiality of data [ 61 , 69 , 70 , 78 ]. The availability of large, heterogeneous data sets is essential for the digital transformation of organizations [ 52 , 59 , 78 , 80 , 88 , 89 ] and is considered one of the key drivers of AI innovation [ 62 , 68 , 72 , 86 ]. In production systems, lack of data availability is often a barrier to AI adoption [ 58 , 70 , 77 ]. In order to enable AI to establish relationships between data, the availability of large input data that is critical [ 62 , 76 , 81 ]. New AI models are trained with this data and can adapt as well as improve as they receive new data [ 59 , 62 ]. Big data can thus significantly improve the quality of AI applications [ 59 , 71 ]. As more and more data is generated in manufacturing [ 85 ], AI opens up new opportunities for companies to make use of it [ 62 ]. However, operational data are often unstructured, as they come from different sources and exist in diverse formats [ 85 , 87 ]. This challenges data processing, as data quality and origin are key factors in the management of data [ 78 , 79 , 80 , 88 , 89 , 91 ]. To make production data valuable and usable for AI, consistency of data and thus data integrity is required across manufacturing systems [ 50 , 62 , 77 , 84 ]. Another key prerequisites for AI adoption is data governance [ 56 , 59 , 67 , 68 , 71 , 78 , 88 ] which is an important asset to make use of data in production [ 50 ] and ensure the complex management of heterogenous data sets [ 89 ]. The interoperability of data and thus the foundation for the compatibility of AI with existing systems, i.e., the extent to which AI matches existing processes, structures, and infrastructures [ 53 , 56 , 84 , 93 ], is considered another important requirement for the adoption of AI in IT systems. Data interoperability in production systems can be hindered by missing data standards as different machines use different formats [ 87 ]. Data processing refers to techniques used to preparing data for analysis which is essential to obtain consistent results from data analytics in production [ 58 , 72 , 80 , 81 , 84 ]. In this process, the numerous, heterogeneous data from different sensors are processed in such a way that they can be used for further analyses [ 87 ]. The capability of production firms to process data and information is thus important to enable AI adoption [ 77 , 86 , 93 ]. With the increasing data generation in the smart and connected factory, the strategic relevance of data analytics is gaining importance [ 55 , 69 , 78 ], as it is essential for AI systems in performing advanced data analyses [ 49 , 67 , 72 , 86 , 88 ]. Using analytics, valuable insights can be gained from the production data obtained using AI systems [ 58 , 77 , 87 ]. In order to enable the processing of big data, a profound data infrastructure is necessary [ 65 , 75 , 87 ]. Facilities must be equipped with sensors, that collect data and model information, which requires investments from firms [ 72 ]. In addition, production firms must build the necessary skills, culture and capabilities for data analytics [ 54 , 75 , 87 , 93 ]. Data storage, one of the foundations and prerequisites for smart manufacturing [ 54 , 68 , 71 , 74 ], must be ensured in order to manage the larg amounts of data and thus realize the adoption of intelligent technologies in production [ 50 , 59 , 72 , 78 , 84 , 87 , 88 , 89 ].

3.2 External environment

The external drivers of AI adoption in production influence the organization through conditions and events from outside the firm and are therefore difficult to control by the organization itself.

3.2.1 Regulatory environment

This supercategory captures the broader concept of establishing rules, standards, and frameworks that guide the behavior, actions, and operations of individuals, organizations, and societies when implementing AI.

AI adoption in production faces many ethical challenges [ 70 , 72 , 79 ]. AI applications must be compliant with the requirements of organizational ethical standards and laws [ 49 , 50 , 59 , 60 , 62 , 75 ] which is why certain issues must be examined in AI adoption and AI design [ 62 , 73 , 82 , 91 ] so that fairness and justice are guaranteed [ 78 , 79 , 92 ]. Social rights, cultural values and norms must not be violated in the process [ 49 , 52 , 53 , 81 ]. In this context, the explainability and transparency of AI decisions also plays an important role [ 50 , 54 , 58 , 70 , 78 , 89 ] and can address the characteristic of AI of a black box [ 90 ]. In addition, AI applications must be compliant with legal and regulatory requirements [ 51 , 52 , 59 , 77 , 81 , 82 , 91 ] and be developed accordingly [ 49 , 76 ] in order to make organization processes using AI clear and effective [ 65 ]. At present, policies and regulation of AI are still in its infancy [ 49 ] and missing federal regulatory guidelines, standards as well as incentives hinder the adoption of AI [ 67 ] which should be expanded simultaneously to the expansion of AI technology [ 60 ]. This also includes regulations on the handling of data (e.g. anonymization of data) [ 61 , 72 ].

3.2.2 Business environment

The factors in the ‘business environment’ supercategory refer to the external conditions and influences that affect the operations, decision making, and performance of the company seeking to implement AI in a production context.

Cooperation and collaboration can influence the success of digital technology adoption [ 52 , 53 , 59 , 72 ], which is why partnerships are important for adoption [ 53 , 59 ] and can positively influence its future success [ 52 , 67 ]. Both intraorganizational and interorganizational knowledge sharing can positively influence AI adoption [ 49 ]. In collaborations, companies can use a shared knowledge base where data and process sharing [ 51 , 59 , 94 ] as well as social support systems strengthen feedback loops between departments [ 79 , 80 ]. With regard to AI adoption in firms, vendors as well as service providers need to collaborate closely to improve the compatibility and operational capability of smart technologies across different industries [ 82 , 93 ]. Without external IT support, companies can rarely integrate AI into their production processes [ 66 ], which is why thorough support from vendors can significantly facilitate the integration of AI into existing manufacturing processes [ 80 , 91 ]. Public–private collaborations can also add value and governments can target AI dissemination [ 60 , 74 ]. The support of the government also positively influences AI adoption. This includes investing in research projects and policies, building a regulatory setting as well as creating a collaborative environment [ 60 ]. Production companies are constantly exposed to changing conditions, which is why the dynamics of the environment is another factor influencing the adoption of AI [ 52 , 63 , 72 , 86 ]. Environmental dynamics influence the operational performance of firms and can favor an entrepreneurial orientation of firms [ 86 ]. In order to respond to dynamics, companies need to develop certain capabilities and resources (i.e. dynamic capabilities) [ 86 ]. This requires the development of transparency, agility, as well as resilience to unpredictable changes, which was important in the case of the COVID-19 pandemic, for example, where companies had to adapt quickly to changing environments [ 75 ]. A firm’s environment (e.g. governments, partners or customers) can also pressure companies to adopt digital technologies [ 53 , 67 , 82 , 91 ]. Companies facing intense competition are considered more likely to invest in smart technologies, as rivalry pushes them to innovate and they hope to gain competitive advantages from adoption [ 36 , 66 , 82 , 93 ].

3.2.3 Economic environment

By considering both the industrial sector and country within the subcategory ‘economic environment’, production firms can analyze the interplay between the two and understand how drivers can influence the AI adoption process in their industrial sector’s performance within a particular country.

The industrial sector of a firm influences AI adoption in production from a structural perspective, as it indicates variations in product characteristics, governmental support, the general digitalization status, the production environment as well as the use of AI technologies within the sector [ 36 ]. Another factor that influences AI adoption is the country in which a company is located. This influences not only cultural aspects, the availability of know-how and technology orientation, but also regulations, laws, standards and subsidies [ 36 ]. From another perspective, AI can also contribute to the wider socio-economic growth of economies by making new opportunities easily available and thus equipping e.g. more rural areas with advanced capabilities [ 78 ].

3.3 Future research directions

The analysis of AI adoption in production requires a comprehensive analysis of the various factors that influence the introduction of the innovation. As discussed by Kinkel, Baumgartner, Cherubini [ 36 ], our research also concludes that organizational factors have a particularly important role to play. After evaluating the individual drivers of AI adoption in production in detail in this qualitative synthesis, we draw a conclusion from the results and derive a research agenda from the analysis to serve as a basis for future research. The RQs emerged from the analyzed factors and are presented in Table  2 . We developed the questions based on the literature review and identified research gaps for every factor that was most frequently mentioned. From the factors analyzed and RQs developed, the internal environment has a strong influence on AI adoption in production, and organizational factors play a major role here.

Looking at the supercategory ‘business and environment’, performance indicators and investments are considered drivers of AI adoption in production. Indicators to measure the performance of AI innovations are necessary here so that managers can perform cost–benefit analyses and make the right decision for their company. There is a need for research here to support possible calculations and show managers a comprehensive view of the costs and benefits of technology in production. In terms of budget, it should be noted that AI adoption involves a considerable financial outlay that must be carefully weighed and some capital must be available to carry out the necessary implementation efforts (e.g., staffing costs, machine retrofits, change management, and external IT service costs). Since AI adoption is a complex process and turnkey solutions can seldom be implemented easily and quickly, but require many changes (not only technologically but also on an organizational level), it is currently difficult to estimate the necessary budgets and thus make them available. Especially the factors of the supercategory ‘organizational effectiveness’ drive AI adoption in production. Trust of the workforce is considered an important driver, which must be created in order to successfully implement AI. This requires measures that can support management in building trust. Closely related to this are the necessary change management processes that must be initiated to accompany the changes in a targeted manner. Management itself must also play a clear role in the introduction of AI and communicate its support, as this also influences the adoption. The development of clear processes and measures can help here. Developing roadmaps for AI adoption can facilitate the adoption process and promote strategic integration with existing IT and business strategy. Here, best practice roadmaps and necessary action steps can be helpful for companies. Skills are considered the most important driver for AI adoption in manufacturing. Here, there is a lack of clear approaches that support companies in identifying the range of necessary skills and, associated with this, also opportunities to further develop these skills in the existing workforce. Also, building a culture of innovation requires closer research that can help companies foster a conducive environment for AI adoption and the integration of other smart technologies. Steps for developing a positive mindset require further research that can provide approaches for necessary action steps and measures in creating a positive digital culture. With regard to ‘technology and system’, the factors of IT infrastructure and security in particular are driving AI adoption in production. Existing IT systems must reach a certain maturity to enable AI adoption on a technical level. This calls for clear requirements that visualize for companies which systems and standards are in place and where developments are needed. Security must be continuously ensured, for which certain standards and action catalogs must be developed. With regard to the supercategory ‘data management’, the availability of data is considered the basis for successful AI adoption, as no AI can be successfully deployed without data. In the production context in particular, this requires developments that support companies in the provision of data, which usually arises from very heterogeneous sources and forms. Data analytics must also be closely examined, and production companies usually need external support in doing so. The multitude of data also requires big data storage capabilities. Here, groundwork is needed to show companies options about the possibilities of different storage options (e.g., on premis vs. cloud-based).

In the ‘regulatory environment’, ethics in particular is considered a driver of AI adoption in production. Here, fundamental ethical factors and frameworks need to be developed that companies can use as a guideline to ensure ethical standards throughout the process. Cooperations and environmental dynamism drive the supercategory ‘business environment’. Collaborations are necessary to successfully implement AI adoption and action is needed to create the necessary contact facilitation bodies. In a competitive environment, companies have to make quick decisions under strong pressure, which also affects AI adoption. Here, guidelines and also best practice approaches can help to simplify decisions and quickly demonstrate the advantage of the solutions. There is a need for research in this context.

4 Conclusions

The use of AI technologies in production continues to gain momentum as managers hope to increase efficiency, productivity and reduce costs [ 9 , 13 , 20 ]. Although the benefits of AI adoption speak for themselves, implementing AI is a complex decision that requires a lot of knowledge, capital and change [ 95 ] and is influenced by various internal and external factors. Therefore, managers are still cautious about implementing the technology in a production context. Our SLR seeks to examine the emergent phenomenon of AI in production with the precise aim of understanding the factors influencing AI adoption and the key topics discussed in the literature when analyzing AI in a production context. For this purpose, we use the current state of research and examine the existing studies based on the methodology of a systematic literature analysis and respond to three RQs.

We answer RQ1 by closely analyzing the literature selected in our SLR to identify trends in current research on AI adoption in production. In this process, it becomes clear that the topic is gaining importance and that research has increased over the last few years. In the field of production, AI is being examined from various angles and current research addresses aspects from a business, human and technical perspective. In our response to RQ2 we synthesized the existing literature to derive 35 factors that influence AI adoption in production at different levels from inside or outside the organization. In doing so, we find that AI adoption in production poses particularly significant challenges to organizational effectiveness compared to other digital technologies and that the relevance of data management takes on a new dimension. Production companies often operate more traditionally and are sometimes rigid when it comes to change [ 96 , 97 ], which can pose organizational challenges when adopting AI. In addition, the existing machines and systems are typically rather heterogeneous and are subject to different digitalization standards, which in turn can hinder the availability of the necessary data for AI implementation [ 98 , 99 ]. We address RQ3 by deriving a research agenda, which lays a foundation for further scientific research and deepening the understanding of AI adoption in production. The results of our analysis can further help managers to better understand AI adoption and to pay attention to the different factors that influence the adoption of this complex technology.

4.1 Contributions

Our paper takes the first step towards analysing the current state of the research on AI adoption from a production perspective. We represent a holistic view on the topic, which is necessary to get a better understanding of AI in a production-context and build a comprehensive view on the different dimensions as well as factors influencing its adoption. To the best of our knowledge, this is the first contribution that systematises research about the adoption of AI in production. As such, it makes an important contribution to current AI and production research, which is threefold:

First, we highlight the characteristics of studies conducted in recent years on the topic of AI adoption in production, from which several features and developments can be deduced. Our results confirm the topicality of the issue and the increasing relevance of research in the field.

Having laid the foundations for understanding AI in production, we focused our research on the identification and systematization of the most relevant factors influencing AI adoption in production at different levels. This brings us to the second contribution, our comprehensive factor analysis of AI adoption in production provides a framework for further research as well as a potential basis for managers to draw upon when adopting AI. By systematizing the relevant factors influencing AI adoption in production, we derived a set of 35 researched factors associated with AI adoption in production. These factors can be clustered in two areas of analysis and seven respective supercategories. The internal environment area includes four levels of analysis: ‘business and structure’ (focusing on financial aspects and firm characteristics), ‘organizational effectiveness’ (focusing on human-centred factors), ‘technology and system’ (based on the IT infrastructure and systems) as well as ‘data management’ (including all data related factors). Three categories are assigned to the external environment: the ‘regulatory environment’ (such as ethics and the regulatory forms), the ‘business environment’ (focused on cooperation activities and dynamics in the firm environment) and the ‘economic environment’ (related to sectoral and country specifics).

Third, the developed research plan as outlined in Table  2 serves as an additional outcome of the SLR, identifying key RQs in the analyzed areas that can serve as a foundation for researchers to expand the research area of AI adoption in production. These RQs are related to the mostly cited factors analyzed in our SLR and aim to broaden the understanding on the emerging topic.

The resulting insights can serve as the basis for strategic decisions by production companies looking to integrate AI into their processes. Our findings on the factors influencing AI adoption as well as the developed research agenda enhance the practical understanding of a production-specific adoption. Hence, they can serve as the basis for strategic decisions for companies on the path to an effective AI adoption. Managers can, for example, analyse the individual factors in light of their company as well as take necessary steps to develop further aspects in a targeted manner. Researchers, on the other hand, can use the future research agenda in order to assess open RQs and can expand the state of research on AI adoption in production.

4.2 Limitations

Since a literature review must be restricted in its scope in order to make the analyses feasible, our study provides a starting point for further research. Hence, there is a need for further qualitative and quantitative empirical research on the heterogeneous nature of how firms configure their AI adoption process. Along these lines, the following aspects would be of particular interest for future research to improve and further validate the analytical power of the proposed framework.

First, the lack of research on AI adoption in production leads to a limited number of papers included in this SLR. As visualized in Fig.  2 , the number of publications related to the adoption of AI in production has been increasing since 2018 but is, to date, still at an early stage. For this reason, only 47 papers published until May 2024 addressing the production-specific adoption of AI were identified and therefore included in our analysis for in-depth investigation. This rather small number of papers included in the full-text analysis gives a limited view on AI adoption in production but allows a more detailed analysis. As the number of publications in this research field increases, there seems to be a lot of research happening in this field which is why new findings might be constantly added and developed as relevant in the future [ 39 ]. Moreover, in order to research AI adoption from a more practical perspective and thus to build up a broader, continuously updated view on AI adoption in production, future literature analyses could include other publication formats, e.g. study reports of research institutions and companies, as well discussion papers.

Second, the scope of the application areas of AI in production has been increasing rapidly. Even though our overview of the three main areas covered in the recent literature serves as a good basis for identifying the most dominant fields for AI adoption in production, a more detailed analysis could provide a better overview of possibilities for manufacturing companies. Hence, a further systematisation as well as evaluation of application areas for AI in production can provide managers with the information needed to decide where AI applications might be of interest for the specific company needs.

Third, the systematisation of the 35 factors influencing AI adoption in production serve as a good ground for identifying relevant areas influenced by and in turn influencing the adoption of AI. Further analyses should be conducted in order to extend this view and extend the framework. For example, our review could be combined with explorative research methods (such as case studies in production firms) in order to add the practical insights from firms adopting AI. This integration of practical experiences can also help exploit and monitor more AI-specific factors by observing AI adoption processes. In enriching the factors through in-depth analyses, the results of the identified AI adoption factors could also be examined in light of theoretical contributions like the technology-organization-environment (TOE) framework [ 47 ] and other adoption theories.

Fourth, in order to examine the special relevance of identified factors for AI adoption process and thus to distinguish it from the common factors influencing the adoption of more general digital technologies, there is a further need for more in-depth (ethnographic) research into their impacts on the adoption processes, particularly in the production context. Similarly, further research could use the framework introduced in this paper as a basis to develop new indicators and measurement concepts as well as to examine their impacts on production performance using quantitative methods.

Benner MJ, Waldfogel J (2020) Changing the channel: digitization and the rise of “middle tail” strategies. Strat Mgmt J 86:1–24. https://doi.org/10.1002/smj.3130

Article   Google Scholar  

Roblek V, Meško M, Krapež A (2016) A complex view of industry 4.0. SAGE Open. https://doi.org/10.1177/2158244016653987

Oliveira BG, Liboni LB, Cezarino LO et al (2020) Industry 4.0 in systems thinking: from a narrow to a broad spectrum. Syst Res Behav Sci 37:593–606. https://doi.org/10.1002/sres.2703

Li B, Hou B, Yu W et al (2017) Applications of artificial intelligence in intelligent manufacturing: a review. Frontiers Inf Technol Electronic Eng 18:86–96. https://doi.org/10.1631/FITEE.1601885

Dhamija P, Bag S (2020) Role of artificial intelligence in operations environment: a review and bibliometric analysis. TQM 32:869–896. https://doi.org/10.1108/TQM-10-2019-0243

Collins C, Dennehy D, Conboy K et al (2021) Artificial intelligence in information systems research: a systematic literature review and research agenda. Int J Inf Manage 60:102383. https://doi.org/10.1016/j.ijinfomgt.2021.102383

Chien C-F, Dauzère-Pérès S, Huh WT et al (2020) Artificial intelligence in manufacturing and logistics systems: algorithms, applications, and case studies. Int J Prod Res 58:2730–2731. https://doi.org/10.1080/00207543.2020.1752488

Chen H (2019) Success factors impacting artificial intelligence adoption: perspective from the telecom industry in China, Old Dominion University

Sanchez M, Exposito E, Aguilar J (2020) Autonomic computing in manufacturing process coordination in industry 4.0 context. J Industrial Inf Integr. https://doi.org/10.1016/j.jii.2020.100159

Lee J, Davari H, Singh J et al (2018) Industrial artificial intelligence for industry 4.0-based manufacturing systems. Manufacturing Letters 18:20–23. https://doi.org/10.1016/j.mfglet.2018.09.002

Heimberger H, Horvat D, Schultmann F (2023) Assessing AI-readiness in production—A conceptual approach. In: Huang C-Y, Dekkers R, Chiu SF et al. (eds) intelligent and transformative production in pandemic times. Springer, Cham, pp 249–257

Horvat D, Heimberger H (2023) AI Readiness: An Integrated Socio-technical Framework. In: Deschamps F, Pinheiro de Lima E, Da Gouvêa Costa SE et al. (eds) Proceedings of the 11 th international conference on production research—Americas: ICPR Americas 2022, 1 st ed. 2023. Springer Nature Switzerland; Imprint Springer, Cham, pp 548–557

Wang J, Ma Y, Zhang L et al (2018) Deep learning for smart manufacturing: methods and applications. J Manuf Syst 48:144–156. https://doi.org/10.1016/J.JMSY.2018.01.003

Davenport T, Guha A, Grewal D et al (2020) How artificial intelligence will change the future of marketing. J Acad Mark Sci 48:24–42. https://doi.org/10.1007/s11747-019-00696-0

Cui R, Li M, Zhang S (2022) AI and procurement. Manufacturing Serv Operations Manag 24(691):706. https://doi.org/10.1287/msom.2021.0989

Pournader M, Ghaderi H, Hassanzadegan A et al (2021) Artificial intelligence applications in supply chain management. Int J Prod Econ 241:108250. https://doi.org/10.1016/j.ijpe.2021.108250

Su H, Li L, Tian S et al (2024) Innovation mechanism of AI empowering manufacturing enterprises: case study of an industrial internet platform. Inf Technol Manag. https://doi.org/10.1007/s10799-024-00423-4

Venkatesh V, Raman R, Cruz-Jesus F (2024) AI and emerging technology adoption: a research agenda for operations management. Int J Prod Res 62:5367–5377. https://doi.org/10.1080/00207543.2023.2192309

Senoner J, Netland T, Feuerriegel S (2022) Using explainable artificial intelligence to improve process quality: evidence from semiconductor manufacturing. Manage Sci 68:5704–5723. https://doi.org/10.1287/mnsc.2021.4190

Fosso Wamba S, Queiroz MM, Ngai EWT et al (2024) The interplay between artificial intelligence, production systems, and operations management resilience. Int J Prod Res 62:5361–5366. https://doi.org/10.1080/00207543.2024.2321826

Uren V, Edwards JS (2023) Technology readiness and the organizational journey towards AI adoption: an empirical study. Int J Inf Manage 68:102588. https://doi.org/10.1016/j.ijinfomgt.2022.102588

Berente N, Gu B, Recker J (2021) Managing artificial intelligence special issue managing AI. MIS Quarterly 45:1433–1450

Google Scholar  

Scafà M, Papetti A, Brunzini A et al (2019) How to improve worker’s well-being and company performance: a method to identify effective corrective actions. Procedia CIRP 81:162–167. https://doi.org/10.1016/j.procir.2019.03.029

Wang H, Qiu F (2023) AI adoption and labor cost stickiness: based on natural language and machine learning. Inf Technol Manag. https://doi.org/10.1007/s10799-023-00408-9

Lindebaum D, Vesa M, den Hond F (2020) Insights from “the machine stops ” to better understand rational assumptions in algorithmic decision making and its implications for organizations. Acad Manag Rev 45:247–263. https://doi.org/10.5465/amr.2018.0181

Baskerville RL, Myers MD, Yoo Y (2020) Digital first: the ontological reversal and new challenges for information systems research. MIS Quarterly 44:509–523

Frey CB, Osborne MA (2017) The future of employment: How susceptible are jobs to computerisation? Technol Forecast Soc Chang 114:254–280. https://doi.org/10.1016/J.TECHFORE.2016.08.019

Jarrahi MH (2018) Artificial intelligence and the future of work: human-AI symbiosis in organizational decision making. Bus Horiz 61:577–586. https://doi.org/10.1016/j.bushor.2018.03.007

Fügener A, Grahl J, Gupta A et al (2021) Will humans-in-the-loop become borgs? Merits and pitfalls of working with AI. MIS Quarterly 45:1527–1556

Klumpp M (2018) Automation and artificial intelligence in business logistics systems: human reactions and collaboration requirements. Int J Log Res Appl 21:224–242. https://doi.org/10.1080/13675567.2017.1384451

Schrettenbrunnner MB (2020) Artificial-Intelligence-driven management. IEEE Eng Manag Rev 48:15–19. https://doi.org/10.1109/EMR.2020.2990933

Li J, Li M, Wang X et al (2021) Strategic directions for AI: the role of CIOs and boards of directors. MIS Quarterly 45:1603–1644

Brock JK-U, von Wangenheim F (2019) Demystifying AI: What digital transformation leaders can teach you about realistic artificial intelligence. Calif Manage Rev 61:110–134. https://doi.org/10.1177/1536504219865226

Lee J, Suh T, Roy D et al (2019) Emerging technology and business model innovation: the case of artificial intelligence. JOItmC 5:44. https://doi.org/10.3390/joitmc5030044

Chen J, Tajdini S (2024) A moderated model of artificial intelligence adoption in firms and its effects on their performance. Inf Technol Manag. https://doi.org/10.1007/s10799-024-00422-5

Kinkel S, Baumgartner M, Cherubini E (2022) Prerequisites for the adoption of AI technologies in manufacturing—evidence from a worldwide sample of manufacturing companies. Technovation 110:102375. https://doi.org/10.1016/j.technovation.2021.102375

Mikalef P, Gupta M (2021) Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organizational creativity and firm performance. Inf Manag 58:103434. https://doi.org/10.1016/j.im.2021.103434

McElheran K, Li JF, Brynjolfsson E et al (2024) AI adoption in America: Who, what, and where. Economics Manag Strategy 33:375–415. https://doi.org/10.1111/jems.12576

Tranfield D, Denyer D, Smart P (2003) Towards a methodology for developing evidence-informed management knowledge by means of systematic review. Br J Manag 14:207–222. https://doi.org/10.1111/1467-8551.00375

Cooper H, Hedges LV, Valentine JC (2009) Handbook of research synthesis and meta-analysis. Russell Sage Foundation, New York

Page MJ, McKenzie JE, Bossuyt PM et al (2021) The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 372:n71. https://doi.org/10.1136/bmj.n71

Denyer D, Tranfield D (2011) Producing a systematic review. In: Buchanan DA, Bryman A (eds) The Sage handbook of organizational research methods. Sage Publications Inc, Thousand Oaks, CA, pp 671–689

Burbidge JL, Falster P, Riis JO et al (1987) Integration in manufacturing. Comput Ind 9:297–305. https://doi.org/10.1016/0166-3615(87)90103-5

Mayring P (2000) Qualitative content analysis. Forum qualitative Sozialforschung/Forum: Qualitative social research, Vol 1, No 2 (2000): Qualitative methods in various disciplines I: Psychology. https://doi.org/10.17169/fqs-1.2.1089

Hsieh H-F, Shannon SE (2005) Three approaches to qualitative content analysis. Qual Health Res 15:1277–1288. https://doi.org/10.1177/1049732305276687

Miles MB, Huberman AM (2009) Qualitative data analysis: An expanded sourcebook, 2nd edn. Sage, Thousand Oaks, Calif

Tornatzky LG, Fleischer M (1990) The processes of technological innovation. Issues in organization and management series. Lexington Books, Lexington, Mass.

Alsheibani S, Cheung Y, Messom C (2018) Artificial Intelligence Adoption: AI-readiness at Firm-Level: Research-in-Progress. Twenty-Second Pacific Asia Conference on Information Systems

Akinsolu MO (2023) Applied artificial intelligence in manufacturing and industrial production systems: PEST considerations for engineering managers. IEEE Eng Manag Rev 51:52–62. https://doi.org/10.1109/EMR.2022.3209891

Bettoni A, Matteri D, Montini E et al (2021) An AI adoption model for SMEs: a conceptual framework. IFAC-PapersOnLine 54:702–708. https://doi.org/10.1016/j.ifacol.2021.08.082

Boavida N, Candeias M (2021) Recent automation trends in portugal: implications on industrial productivity and employment in automotive sector. Societies 11:101. https://doi.org/10.3390/soc11030101

Botha AP (2019) A mind model for intelligent machine innovation using future thinking principles. Jnl of Manu Tech Mnagmnt 30:1250–1264. https://doi.org/10.1108/JMTM-01-2018-0021

Chatterjee S, Rana NP, Dwivedi YK et al (2021) Understanding AI adoption in manufacturing and production firms using an integrated TAM-TOE model. Technol Forecast Soc Chang 170:120880. https://doi.org/10.1016/j.techfore.2021.120880

Chiang LH, Braun B, Wang Z et al (2022) Towards artificial intelligence at scale in the chemical industry. AIChE J. https://doi.org/10.1002/aic.17644

Chouchene A, Carvalho A, Lima TM et al. (2020) Artificial intelligence for product quality inspection toward smart industries: quality control of vehicle Non-conformities. In: Garengo P (ed) 2020 9th International Conference on Industrial Technology and Management: ICITM 2020 February 11–13, 2020, Oxford, United Kingdom. IEEE, pp 127–131

Corti D, Masiero S, Gladysz B (2021) Impact of Industry 4.0 on Quality Management: identification of main challenges towards a Quality 4.0 approach. In: 2021 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC). IEEE, pp 1–8

Demlehner Q, Schoemer D, Laumer S (2021) How can artificial intelligence enhance car manufacturing? A Delphi study-based identification and assessment of general use cases. Int J Inf Manage 58:102317. https://doi.org/10.1016/j.ijinfomgt.2021.102317

Dohale V, Akarte M, Gunasekaran A et al (2022) (2022) Exploring the role of artificial intelligence in building production resilience: learnings from the COVID-19 pandemic. Int J Prod Res 10(1080/00207543):2127961

Drobot AT (2020) Industrial Transformation and the Digital Revolution: A Focus on artificial intelligence, data science and data engineering. In: 2020 ITU Kaleidoscope: Industry-Driven Digital Transformation (ITU K). IEEE, pp 1–11

Ghani EK, Ariffin N, Sukmadilaga C (2022) Factors influencing artificial intelligence adoption in publicly listed manufacturing companies: a technology, organisation, and environment approach. IJAEFA 14:108–117

Hammer A, Karmakar S (2021) Automation, AI and the future of work in India. ER 43:1327–1341. https://doi.org/10.1108/ER-12-2019-0452

Hartley JL, Sawaya WJ (2019) Tortoise, not the hare: digital transformation of supply chain business processes. Bus Horiz 62:707–715. https://doi.org/10.1016/j.bushor.2019.07.006

Kyvik Nordås H, Klügl F (2021) Drivers of automation and consequences for jobs in engineering services: an agent-based modelling approach. Front Robot AI 8:637125. https://doi.org/10.3389/frobt.2021.637125

Mubarok K, Arriaga EF (2020) Building a smart and intelligent factory of the future with industry 4.0 technologies. J Phys Conf Ser. https://doi.org/10.1088/1742-6596/1569/3/032031

Muriel-Pera YdJ, Diaz-Piraquive FN, Rodriguez-Bernal LP et al. (2018) Adoption of strategies the fourth industrial revolution by micro, small and medium enterprises in bogota D.C. In: Lozano Garzón CA (ed) 2018 Congreso Internacional de Innovación y Tendencias en Ingeniería (CONIITI). IEEE, pp 1–6

Olsowski S, Schlögl S, Richter E et al. (2022) Investigating the Potential of AutoML as an Instrument for Fostering AI Adoption in SMEs. In: Uden L, Ting I-H, Feldmann B (eds) Knowledge Management in Organisations: 16th International Conference, KMO 2022, Hagen, Germany, July 11–14, 2022, Proceedings, 1st ed. 2022, vol 1593. Springer, Cham, pp 360–371

Rodríguez-Espíndola O, Chowdhury S, Dey PK et al (2022) Analysis of the adoption of emergent technologies for risk management in the era of digital manufacturing. Technol Forecast Soc Chang 178:121562. https://doi.org/10.1016/j.techfore.2022.121562

Schkarin T, Dobhan A (2022) Prerequisites for Applying Artificial Intelligence for Scheduling in Small- and Medium-sized Enterprises. In: Proceedings of the 24 th International Conference on Enterprise Information Systems. SCITEPRESS—Science and Technology Publications, pp 529–536

Sharma P, Shah J, Patel R (2022) Artificial intelligence framework for MSME sectors with focus on design and manufacturing industries. Mater Today: Proc 62:6962–6966. https://doi.org/10.1016/j.matpr.2021.12.360

Siaterlis G, Nikolakis N, Alexopoulos K et al. (2022) Adoption of AI in EU Manufacturing. Gaps and Challenges. In: Katalinic B (ed) Proceedings of the 33 rd International DAAAM Symposium 2022, vol 1. DAAAM International Vienna, pp 547–550

Tariq MU, Poulin M, Abonamah AA (2021) Achieving operational excellence through artificial intelligence: driving forces and barriers. Front Psychol 12:686624. https://doi.org/10.3389/fpsyg.2021.686624

Trakadas P, Simoens P, Gkonis P et al (2020) An artificial intelligence-based collaboration approach in industrial IoT manufacturing: key concepts. Architectural Ext Potential Applications Sens. https://doi.org/10.3390/s20195480

Vernim S, Bauer H, Rauch E et al (2022) A value sensitive design approach for designing AI-based worker assistance systems in manufacturing. Procedia Computer Sci 200:505–516. https://doi.org/10.1016/j.procs.2022.01.248

Williams G, Meisel NA, Simpson TW et al (2022) Design for artificial intelligence: proposing a conceptual framework grounded in data wrangling. J Computing Inf Sci Eng 10(1115/1):4055854

Wuest T, Romero D, Cavuoto LA et al (2020) Empowering the workforce in Post–COVID-19 smart manufacturing systems. Smart Sustain Manuf Syst 4:20200043. https://doi.org/10.1520/SSMS20200043

Javaid M, Haleem A, Singh RP (2023) A study on ChatGPT for Industry 4.0: background, potentials, challenges, and eventualities. J Economy Technol 1:127–143. https://doi.org/10.1016/j.ject.2023.08.001

Rathore AS, Nikita S, Thakur G et al (2023) Artificial intelligence and machine learning applications in biopharmaceutical manufacturing. Trends Biotechnol 41:497–510. https://doi.org/10.1016/j.tibtech.2022.08.007

Jan Z, Ahamed F, Mayer W et al (2023) Artificial intelligence for industry 4.0: systematic review of applications, challenges, and opportunities. Expert Syst Applications 216:119456

Waschull S, Emmanouilidis C (2023) Assessing human-centricity in AI enabled manufacturing systems: a socio-technical evaluation methodology. IFAC-PapersOnLine 56:1791–1796. https://doi.org/10.1016/j.ifacol.2023.10.1891

Stohr A, Ollig P, Keller R et al (2024) Generative mechanisms of AI implementation: a critical realist perspective on predictive maintenance. Inf Organ 34:100503. https://doi.org/10.1016/j.infoandorg.2024.100503

Pazhayattil AB, Konyu-Fogel G (2023) ML and AI Implementation Insights for Bio/Pharma Manufacturing. BioPharm International 36:24–29

Ronaghi MH (2023) The influence of artificial intelligence adoption on circular economy practices in manufacturing industries. Environ Dev Sustain 25:14355–14380. https://doi.org/10.1007/s10668-022-02670-3

Rath SP, Tripathy R, Jain NK (2024) Assessing the factors influencing the adoption of generative artificial intelligence (GenAI) in the manufacturing sector. In: Sharma SK, Dwivedi YK, Metri B et al (eds) Transfer, diffusion and adoption of next-generation digital technologies, vol 697. Springer Nature Switzerland, Cham

Bonnard R, Da Arantes MS, Lorbieski R et al (2021) Big data/analytics platform for Industry 4.0 implementation in advanced manufacturing context. Int J Adv Manuf Technol 117:1959–1973. https://doi.org/10.1007/s00170-021-07834-5

Confalonieri M, Barni A, Valente A et al. (2015) An AI based decision support system for preventive maintenance and production optimization in energy intensive manufacturing plants. In: 2015 IEEE international conference on engineering, technology and innovation/ international technology management conference (ICE/ITMC). IEEE, pp 1–8

Dubey R, Gunasekaran A, Childe SJ et al (2020) Big data analytics and artificial intelligence pathway to operational performance under the effects of entrepreneurial orientation and environmental dynamism: a study of manufacturing organisations. Int J Prod Econ 226:107599. https://doi.org/10.1016/j.ijpe.2019.107599

Lee J, Singh J, Azamfar M et al (2020) Industrial AI: a systematic framework for AI in industrial applications. China Mechanical Eng 31:37–48

Turner CJ, Emmanouilidis C, Tomiyama T et al (2019) Intelligent decision support for maintenance: an overview and future trends. Int J Comput Integr Manuf 32:936–959. https://doi.org/10.1080/0951192X.2019.1667033

Agostinho C, Dikopoulou Z, Lavasa E et al (2023) Explainability as the key ingredient for AI adoption in Industry 5.0 settings. Front Artif Intell. https://doi.org/10.3389/frai.2023.1264372

Csiszar A, Hein P, Wachter M et al. (2020) Towards a user-centered development process of machine learning applications for manufacturing domain experts. In: 2020 third international conference on artificial intelligence for industries (AI4I). IEEE, pp 36–39

Merhi MI (2023) Harfouche A (2023) Enablers of artificial intelligence adoption and implementation in production systems. Int J Prod Res. https://doi.org/10.1080/00207543.2023.2167014

Demlehner Q, Laumer S (2024) How the terminator might affect the car manufacturing industry: examining the role of pre-announcement bias for AI-based IS adoptions. Inf Manag 61:103881. https://doi.org/10.1016/j.im.2023.103881

Ghobakhloo M, Ching NT (2019) Adoption of digital technologies of smart manufacturing in SMEs. J Ind Inf Integr 16:100107. https://doi.org/10.1016/j.jii.2019.100107

Binsaeed RH, Yousaf Z, Grigorescu A et al (2023) Knowledge sharing key issue for digital technology and artificial intelligence adoption. Systems 11:316. https://doi.org/10.3390/systems11070316

Papadopoulos T, Sivarajah U, Spanaki K et al (2022) Editorial: artificial Intelligence (AI) and data sharing in manufacturing, production and operations management research. Int J Prod Res 60:4361–4364. https://doi.org/10.1080/00207543.2021.2010979

Chirumalla K (2021) Building digitally-enabled process innovation in the process industries: a dynamic capabilities approach. Technovation 105:102256. https://doi.org/10.1016/j.technovation.2021.102256

Fragapane G, Ivanov D, Peron M et al (2022) Increasing flexibility and productivity in Industry 4.0 production networks with autonomous mobile robots and smart intralogistics. Ann Oper Res 308:125–143. https://doi.org/10.1007/s10479-020-03526-7

Shahbazi Z, Byun Y-C (2021) Integration of Blockchain, IoT and machine learning for multistage quality control and enhancing security in smart manufacturing. Sensors (Basel). https://doi.org/10.3390/s21041467

Javaid M, Haleem A, Singh RP et al (2021) Significance of sensors for industry 4.0: roles, capabilities, and applications. Sensors Int 2:100110. https://doi.org/10.1016/j.sintl.2021.100110

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Heimberger, H., Horvat, D. & Schultmann, F. Exploring the factors driving AI adoption in production: a systematic literature review and future research agenda. Inf Technol Manag (2024). https://doi.org/10.1007/s10799-024-00436-z

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Palliative care in small-scale living facilities: a scoping review

• Brittany S. DeGraves 1 ,
• Judith M. M. Meijers 2 , 3 ,
• Carole A. Estabrooks 1 &
• Hilde Verbeek 2 , 3  

BMC Geriatrics volume  24 , Article number:  700 ( 2024 ) Cite this article

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Innovative small-scale facilities for dementia focus on providing quality of life and maintaining the functional abilities of residents while offering residents a home for life. To fulfill the home-for-life principle, palliative care approaches are necessary to maintain quality of life in these facilities. Few studies have reported on how palliative care is provided to residents in small-scale facilities. The aim of our review is to determine the extent to which palliative care approaches are reported in small-scale facilities.

A scoping review of the literature using recommended methods from the Joanna Briggs Institute. Four databases, CINAHL, PubMed, PsycINFO, and Web of Science, were searched for studies published from 1995 to 2023. One reviewer completed the title, abstract and full-text screening and data extraction; two additional team members piloted the screening and extraction process and met with the main reviewer to make decisions about article inclusion and ensure consistency and accuracy in the review process. The extracted data was open-coded and analyzed using thematic analysis. The data was then synthesized into themes using palliative care domains for dementia.

Of the 800 articles obtained in the search, only ten met the inclusion criteria: six from Japan, two from the Netherlands, and one each from Austria and the United States. In most small-scale facilities, palliative care is important, with facilities prioritizing family involvement and person-centred care, minimizing resident discomfort and enhancing residents’ remaining abilities until the end of life. The included studies did not discuss palliative care policies or professional staff training in depth.

Conclusions

This study provides an overview of the literature on palliative care in small-scale facilities for individuals with dementia. Most facilities focus on residents’ wishes at the end of life to enhance comfort and provide a home-like environment. However, more research is needed to further understand the quality of palliative care approaches in these homes.

Peer Review reports

Innovative small-scale care environments are designed to meet the complex needs of residents with dementia by maintaining their functional ability and quality of life in a person-centred way while maintaining a true home-like setting [ 1 , 2 , 3 ]. Small-scale facilities provide physical and psychosocial care for older adults or individuals who are no longer able to live independently. Small-scale facilities differ from long-term care facilities because they have a smaller number of residents (six to fifteen on average). These facilities provide a community environment and person-centred care while stimulating resident autonomy by promoting active participation in social activities, household chores, and decision-making surrounding daily schedules [ 1 , 2 , 3 , 4 , 5 ]. To create a home-like environment, these facilities include home-like kitchens, living rooms, and private bedrooms while also allowing residents to bring pets and furniture from home [ 1 , 3 , 6 ]. Staff in these environments are often responsible for multiple additional tasks, including cooking and cleaning [ 3 ]. Small-scale facilities are also “a home for life”, meaning that residents can stay and live a purposeful life within these homes until their death [ 3 , 7 ].

There are multiple types of small-scale facilities internationally [ 3 ]. These include Group Living/Homes (Japan/Sweden), Small-scale Living Facilities (Netherlands/Belgium), Green Care Farms (Netherlands), Residential Groups (Germany), Cantou (France), Care Housing (Scotland), Domuses (United Kingdom), Woodside Place (Canada/United States), and Green Houses (United States) [ 3 , 8 ]. Recently, research has focused on the outcomes of living in small-scale homes compared to traditional long-term care; however, few studies have reported on palliative care approaches in these homes [ 3 , 4 , 5 , 9 ]. With these studies reporting that residents in small-scale homes have increased social and physical engagement and functioning compared to residents in long-term care and with these facilities growing in popularity, it is critical to understand if these facilities can provide palliative care and a home for life for residents with dementia. Therefore, factors surrounding palliative care in these innovative facilities, including the quality of palliative care and what can be improved, need to be identified [ 1 , 10 ].

To live within these small-scale settings until death, a palliative approach is essential, as it promotes a focus on person-centred, family-centred and holistic care while trying to improve the quality of dying [ 11 , 12 ]. Palliative care is also essential for providing residents with peace at the end of life, as only half of individuals with dementia in long-term care die peacefully, according to their families [ 13 ]. The quality of care that residents receive toward the end of life is also a more relevant care goal than increasing the length of residents’ lives due to the complicated nature and symptom burden associated with dementia [ 12 , 14 , 15 ].

No review has yet to be completed on the topic of palliative care in small-scale facilities. Our purpose in conducting a scoping review was to identify the current body of knowledge and to identify research gaps in this field. Our research question was “To what extent are palliative care approaches reported in small-scale home-like facilities internationally?”

We conducted a scoping review to identify the available literature and determine how palliative care approaches are used in small-scale facilities [ 16 , 17 ]. Our search strategy and review were based on the framework proposed by the Joanna Briggs Institute Reviewers Manual for scoping reviews [ 17 ]. This framework proposes enhancements made to Arksey and O’Malley’s framework [ 16 ]. We followed the recommended steps of (1) defining the objectives and research questions, (2) developing inclusion criteria and aligning them with the research question, (3) describing a planned approach to searching, data extraction and presentation, (4) searching for evidence, (5) selecting the studies or evidence, (6) data extraction, (7) analysis of data and evidence, (8) presentation of results, and (9) connecting the evidence to the purpose of the review and stating the implications of the findings [ 17 ].

Search strategy and study identification

To identify keywords and create a search string for our literature search, Medline, Google Scholar, and CINAHL were searched to analyze the text words and abstracts of the retrieved papers. A health sciences librarian, in addition to the writers, helped define terminology and add to the search strategy. The final search used all identified terms in the steps described in Table  1 .

Index terms were constructed once the search strategy was finalized in all the following databases: CINAHL, PubMed, PsycINFO, and Web of Science. Our literature search covered from 1995 onward; for the full search strategy, please see Additional File 1 , PubMed Final Search Strategy. The decision to search from 1995 onward was made in partnership with research team members and a health sciences librarian who had familiarity with the literature and discussed this as an adequate timeline to explore both critical concepts identified in our study (palliative care for individuals with dementia, and small-scale dementia care facilities). We also completed an ancestry search of the reference lists of the retrieved papers. We conducted a grey literature search using the search engine Google Scholar. Our initial search was conducted in July 2019 and was updated in September 2023.

We also consulted six experts in palliative care and small-scale living home-like facilities in multiple countries (North America and Europe) to determine if they had access to additional literature focused on this subject area; four answered our inquiry.

Selection criteria

Inclusion criteria.

Inclusion criteria were: (1) studies must have collected primary data; (2) the study aims had to have explicitly addressed small-scale residential models (settings that resemble home-like environments, including having a maximum of 15 residents per house or unit, having staff, residents, and their family form a household together sharing responsibilities, staff performing integrated tasks both medical and personal [ 3 , 5 ]); (3) studies must have described palliative care or end-of-life care approaches; (4) study samples had to include adults aged 65 years or older; (5) studies must have focused primarily on residents with dementia; and (6) studies must have been in English, Dutch, or German languages.

Exclusion criterion

Studies could not have been conducted in a hospice or traditional long-term care facility.

Study selection

Before conducting the review, the selection criteria and review processes were discussed until a consensus was reached between BD, HV, and JM. The selection criteria were piloted in title/abstract and full-text screenings by BD, HV and JM to ensure the criteria were straightforward and to determine agreement between team members. Based on the selection criteria, one reviewer (BD) screened all titles, abstracts, and full-text articles. Two additional team members, HV and JM, each conducted title/abstract and full-text screenings on a subsection of the retrieved articles to ensure consistency and accuracy with BD’s screening decisions. HV and JM also reviewed BD’s screening decisions and notes throughout the screening process. During the screening process, articles that did not directly match the criteria or were deemed questionable by BD were reviewed individually by the three reviewers, who then met to determine the eligibility and make decisions about article inclusion. During these meetings, all decisions and questions that arose during the screening process were discussed with the team to ensure transparency and consistency and reach a consensus. Each full-text article was also discussed in meetings between the three team members (BD, HV, and JM), and an agreement was reached on which papers were to be included.

Database management

We exported the retrieved studies to Endnote X9 for management and deduplication. The review update was conducted using Covidence. Thematic analysis was performed with the assistance of NVIVO-12, which we used to open-code the extracted data and cluster the data into themes.

Data extraction

The extraction process was piloted by three reviewers (BD, HV, JM). Data from the retrieved articles were extracted and summarized by BD, and the extraction tables were reviewed for accuracy and consistency by two team members (JM and HV). We extracted the following information from each study: (1) title of the literature, (2) study design, (3) research question, (4) country of data collection, (5) study sample, (6) type of housing, (6) results and discussion, and (7) study limitations.

Analysis and synthesis of results

The extracted data were synthesized using thematic analysis, where the author read and became familiar with the data, began to open-code included studies and grouped these codes into sub-themes. The subthemes were then clustered into themes using van der Steen et al.’s [ 15 ] domains of palliative care [ 18 ]. These domains of palliative care received international consensus from experts in multiple countries in a European Association for Palliative Care (EAPC) whitepaper to promote high-quality care for individuals with dementia, as there are no preexisting guidelines for end-of-life care for individuals with dementia [ 15 ]. For an in-depth overview of van der Steen et al.’s [ 15 ]. palliative care domains for dementia, please see Table  2 .

The data were reported based on the 2018 PRISMA Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) Checklist [ 19 ]. This was performed by BD and checked by JM and HV for clarity and to reach a consensus on the data charting and extraction methods.

Our search retrieved a total of 800 references from PsycINFO, PubMed, CINAHL, and Web of Science databases; 213 duplicates were removed. After title and abstract screening, 99 articles met our criteria for full-text review. Figure  1 shows the PRISMA diagram [ 20 ]. Our final sample of ten reports included eight papers from the initial search and two records (one policy document and one unpublished dataset) from the grey literature.

PRISMA flow diagram [ 20 ]

The articles included in the scoping review were from Japan (6), Austria (1), the Netherlands (2), and the United States (1). Nine papers were in English, and one was in German [ 21 ]. The article in German [ 21 ] was initially translated by Google Translate, and the translation was reviewed by a research associate fluent in German. Of the ten papers, six focused on group homes (GH) in Japan, [ 2 , 22 , 23 , 24 , 25 , 26 ] which house 5–9 residents with mild to moderate dementia and encourage residents to participate in activities of daily living in a home-like setting [ 2 , 3 ]. The concept of group homes in Japan is similar to other homes included in this study, including small-scale facilities in the Netherlands, shared housing (WG’s) in Austria, and Green Houses in the United States, which also have shared home-like kitchen and living areas and private bedrooms and recommend participation in daily activities [ 3 ]. For the characteristics of the included reports, please see Table  3 .

Study characteristics and design

Seven of the final ten reports had the primary goal of investigating palliative care in dementia [ 2 , 21 , 23 , 24 , 25 , 27 , 29 ]. Two studies [ 22 , 28 ] had a more general aim in which palliative care was only mentioned briefly. The last study, Takada et al. (2022) [ 26 ] aimed to develop an advanced care planning inventory and compare this inventory to the quality of death of residents with dementia.

Four studies used qualitative techniques and explored more detailed descriptions of palliative care approaches in small-scale homes [ 2 , 21 , 22 , 27 ]. Five studies used quantitative assessments to compare palliative care practices among a larger population [ 23 , 24 , 25 , 26 , 29 ]. One article focused on examining palliative care practices in one home [ 28 ].

Below, we summarize findings based on van der Steen et al.’s domains of palliative care [ 15 ]. An in-depth summary of the thematic analysis results is provided in Table  4 .

Domain 1: applicability of palliative care

Palliative care services are important in small-scale facilities due to residents’ increasing age and their dementia diagnosis [ 21 , 28 ]. Maintaining a familiar lifestyle, minimizing discomfort, proactively utilizing medical care, and collaborating with family members are essential to end-of-life care [ 2 ].

Hirakawa et al. (2006) [ 23 ] state that despite most group homes reporting that it was possible to provide palliative care (76.4%), 27.5% of these homes would not provide this care, and only 22.3% provided end-of-life care.

Domain 2: person-centred care, communication, and shared decision-making

Having the residents’ wishes as the first priority and including residents in care was discussed in six studies. For example, asking residents’ wishes for end-of-life and incorporating wishes into regular routines, such as asking about preferences for meals, music, and activities [ 2 , 21 , 22 , 23 , 27 ]. In some group homes, residents regularly discussed end-of-life wishes (i.e., location of death) with other residents during regular resident council meetings [ 22 ]. Takada et al. (2022) [ 26 ] also identified a significant relationship between having conversations with residents to express end-of-life wishes (ACP-PI component) and improved quality of end-of-care (increases in the QOD-LTC scores) of individuals who had passed away in group homes in Japan.

Domain 3: advanced care planning and care goals

Managing directors (60.6%) were the primary palliative care planners in group homes and were responsible for confirming resident wishes and directing care, such as organizing staff training to prepare for resident deterioration [ 2 , 24 ]. In Reitinger et al.’s (2010) study, homes described contradictory views on living wills (advanced directives). Some homes preferred living wills to be written as soon as possible (i.e., upon admission), while other homes only used them as a safeguard for the staff or did not require them at all [ 21 ].

Hirakawa et al. (2006) [ 23 ] reported that 68% of staff members asked families about their wishes for end-of-life care, and 65.5% of staff members asked residents about their wishes. Residents with dementia in many homes were viewed as capable of discussing end-of-life wishes and care planning [ 2 , 22 , 28 ]. Similarly, Takada et al. (2022) [ 26 ] emphasized the significance of advanced care planning for residents with dementia, as they reported that the advanced care planning practice inventory (ACP-PI) had a significant association ( p  < 0.001) with improvements in the quality of end of life care (QOD-LTC) of residents who had passed away in group homes.

Identifying and respecting residents’ wishes at the end of life did not occur in all group homes; for example, in Nakanishi and Honda’s (2009) [ 24 ] study of 33 end-of-life cases, residents’ preferred place of death was confirmed in only 18.2% of cases.

Domain 4: continuity of care

Group homes and green care farms aim to maintain optimal continuity of care by having staff closely observe and record resident conditions to provide detailed information to other healthcare professionals [ 2 , 23 , 27 ]. These collaborations included close contact between healthcare workers, physicians and psychologists. Healthcare workers shared how a guideline for end-of-life care within the home for all disciplines would be beneficial [ 27 ]. Group homes also report collaborative relationships with medical institutions, which are often mandatory; however, Hirakawa et al. (2006) [ 23 ] report that group homes with progressive end-of-life care policies were less likely to have these affiliations with in-home institutions. Managers in group homes set criteria for physicians to follow during end-of-life consultations and treatment. If the criteria were not met, physicians were replaced [ 2 , 23 ].

Reitinger et al. (2010) [ 21 ] report avoiding or shortening hospitalizations of residents at the end of life with methods including encouraging residents, families, and staff to work together to maintain continuity of care by avoiding hospitalizations. This was found to be an important component of care, as hospitals were identified to not be suitable for residents with dementia as they were often left unattended and lacking in basic dignity while in this setting [ 2 , 21 ]. However, group homes in Japan associated themselves with hospitals to provide end-of-life or emergent care [ 2 , 23 ].

None of the 10 studies reported how the continuity of care between facilities was maintained, especially at the end of life, nor did they report barriers to care or care transfers.

Domain 5: prognostication and timely recognition of dying

Staff reported anticipating resident death through accurate assessments, such as recognizing that a decline in the residents’ appetite and changes in activities of daily living including how becoming dependent on personal hygiene signals the beginning of the end-of-life period [ 2 , 24 ]. Smit et al. (2022) also described how the end-of-life phase is often short in green care farms, possibly due to the encouragement of activity up until death, and this sometimes results in deaths that are sudden and may come as a surprise to staff and family members [ 27 ].

Domain 6: avoiding overly aggressive, burdensome, or futile treatment

Avoiding aggressive treatment is achieved by carefully examining therapeutic measures; for example, care homes try to avoid hospitalization due to these environments, often leading to poor outcomes [ 2 , 21 ].

However, Nakanishi et al. (2016) [ 25 ] report more frequent use of physical restraint and antipsychotics with residents in Japanese group homes than in those receiving home care (in-home long-term care support or multiple care providers). These treatments were used regardless of the professionals’ attitudes and knowledge regarding palliative and dementia care. The authors do not identify in their results why group homes have more aggressive treatments compared to other community providers [ 25 ].

Domain 7: optimal treatment of symptoms and providing comfort

Contrary to the findings of Nakanishi et al. (2016) [ 25 ], minimizing mental and physical discomfort is essential in end-of-life care. In many cases, staff compensate for decreased residents’ ability to maintain quality of life, such as assisting with impaired mobility to enhance residents’ remaining abilities [ 2 ]. Staff use many methods to provide physical and psychological comfort, such as supporting a comfortable posture, touch, and massage while providing optimal treatment for discomfort and pain [ 2 , 23 , 27 ].

However, in van der Steen’s (2016) [ 29 ] unpublished data from the Dutch End of Life in Dementia (DEOLD) study of 330 care homes, small-scale facilities exhibited no difference in comfort at dying but a better quality of dying compared to traditional long-term care.

Domain 8: psychosocial and spiritual support

Group homes provide residents with opportunities for discussion of feelings and provision of grief support near the end of life. These homes also promote a familiar lifestyle and comfort by encouraging interactions with other residents and maintaining familiar relationships, as this helps decrease agitation and promotes quality of life in the end-of-life period [ 2 , 21 , 23 ]. Similarly, Nakanishi et al. (2016) [ 25 ] found that compared to in-home and multiple small-scale home providers, residents in group homes had higher scores of interactions with their surroundings and self-expression closer to the end of life.

Group homes also report a smaller opportunity to heal religiously and provide education about property law within their facilities [ 23 ].

Domain 9: family care and involvement

Family involvement is encouraged by staff by providing the family with a bed to stay at the residents’ bedside at the end of life and encouraging the family to participate in care, such as by picking out residents’ clothes [ 2 , 27 ]. Family education also includes palliative care services and objective health changes experienced by residents to help families make end-of-life care decisions [ 2 , 23 , 27 ]. However, Hirakawa et al. (2006) [ 23 ] found that only 37.2% of group homes within their study provided families with information about palliative care services in their homes.

Most homes focused on family involvement in medical treatment and end-of-life decision-making, including asking about wishes for their loved one’s care. These discussions were held on multiple occasions, including at the beginning of the resident’s stay and as the resident’s condition deteriorated [ 2 , 24 , 27 ]. In some homes, the managing director handled discrepancies between residents’ and families’ wishes [ 2 , 24 ].

In many group homes, aftercare rituals and grief support for staff and families are important in honouring the resident and supporting the community after the resident’s death [ 21 , 22 ]. These rituals include planning ceremonies with families and maintaining cultural practices to honour the resident’s relationships with the family, staff, and residents [ 22 ]. Group homes with more progressive policies on palliative care also reported providing more grief support to families. In contrast, only 69% of group homes reported providing this via various methods, such as phone calls [ 23 ].

Domain 10: education of the healthcare team

Nursing staff regard competence in providing care support as critical for providing end-of-life care [ 21 ]. Staff also describe feeling anxious about providing care when they lack detailed knowledge about the decline of the resident’s condition [ 2 ]. Education surrounding palliative care in group homes includes various topics, such as living wills, communication skills, mental support for residents and family, and end-of-life symptoms and care, to adequately prepare staff to provide palliative care services [ 23 ]. These educational resources have become more common in small-scale homes and are provided via various methods, such as manuals, case studies, or work experience. Teaching sessions also provide staff members with mental health support surrounding their positions as palliative care providers [ 2 , 21 , 23 ].

Increases in quality of life, self-expression, interaction with the surrounding environment, and exhibition of minimum negative behaviour in residents are associated with caregivers having greater knowledge and positive attitudes toward palliative and dementia care [ 25 ].

Domain 11: societal and ethical issues

Kobayashi et al. (2008) [ 2 ] describe that despite financial and staffing restrictions from the Japanese long-term care insurance system that result in these facilities being ill equipped to provide palliative care, administrators choose to provide this care to maintain residents’ quality of life until death. However, many group homes in Hirakawa et al. (2006) report that homes will only provide palliative care when the resident requires no medical intervention, there is no complaint of pain from the resident, and when there is an understanding by all parties surrounding the limitations to care that the group home can provide [ 23 ].

Takada et al. (2022) [ 26 ] was the only study to briefly address national strategies or incentives to provide palliative care. They discussed an end-of-life care bonus, which incentivized nursing homes and group homes to improve the quality of care and advanced care planning at the end of life. In particular, this study revealed that homes that received this national incentive had a significant association with higher QOD-LTC scores and, therefore, higher quality end-of-life care.

Smit et al. (2022) [ 27 ] discuss the implications of COVID-19 for end-of-life care, particularly how staff and caregivers identified barriers to providing care due to specific national guidelines implemented during the pandemic.

No papers discuss the training of caregivers during their professional education domain [ 15 ].

Main findings

To our knowledge, this scoping review is the first to provide an overview of palliative care approaches in innovative small-scale dementia care homes. We found few studies discussing palliative care in small-scale facilities; however, the included studies identified that it is possible to provide palliative care approaches and a “home for life” for residents with dementia in these innovative facilities.

The findings in the 10 included articles suggest that it is possible to provide palliative care for individuals with dementia within innovative small-scale facilities. The homes in this review prioritized resident and family-centred palliative care approaches while providing a familiar environment for residents, avoiding hospital admissions, and providing quality psychosocial and physical care up until death [ 2 , 21 , 22 , 23 , 25 , 27 ]. By maintaining these priorities, these small-scale homes are prioritizing a “home-for-life” principle, which involves maintaining an environment that provides comprehensive care to residents with dementia and a place where they can live and maintain their quality of life up until death [ 3 , 7 , 27 , 30 ]. The home-for-life principle and quality palliative care approaches in these homes support residents’ and families’ wishes when they need it the most [ 11 , 12 ].

Barriers to palliative care

While our results suggest that palliative care is possible in these homes, the included studies rarely discussed barriers to palliative care. Identifying and considering how barriers may influence the ability to provide quality palliative care in these settings is important. One particular barrier identified was the COVID-19 pandemic, which influenced the ability of staff to maintain resident comfort, particularly due to visitation restrictions for family caregivers [ 27 ]. Additional barriers to providing palliative care for dementia in traditional long-term care homes include time commitment, lack of equipment, and inadequate staffing [ 31 ]. Additional research is needed to identify the barriers and potential solutions in innovative small-scale facilities, including barriers newly introduced by the COVID-19 pandemic.

Palliative care approaches in small-scale facilities internationally

The papers in this review touched on all general themes of van der Steen et al.’s [ 15 ] palliative care domains for dementia and applied them to palliative care within these innovative homes. Most of the papers in this review were from Japan. Therefore, our results must be interpreted with some caution because they are likely influenced by cultural factors specific to Japanese group homes. This includes factors such as the end-of-life bonus implemented in Japan in 2006 to care homes (including group homes) to incentivize the quality of palliative care and advanced care planning in care homes toward the end of life [ 26 , 32 ]. Studies in this review, such as Hirakawa et al. (2006) [ 23 ], were published in the early years of this program, and the group homes included in this paper were the only small-scale facilities in our review with strong relationships with hospitals. These relationships may provide additional care resources and relate to Japan’s national strategy for dementia, which emphasizes avoiding hospitalizations of residents by using a trained outreach team to treat individuals with dementia in the community [ 2 , 23 , 24 , 32 , 33 ]. This is particularly important for Japanese group homes, as not all group homes are constructed to provide end-of-life care and are not required to have trained medical professionals on site; this differs from other small-scale homes, such as green houses in the United States, which hold hospice principles and have some specialized palliative care training [ 21 , 24 , 28 ]. Avoiding hospitalizations is a common theme in many homes included in this review. This may be due to the association of hospital use with poor outcomes for residents with dementia, including aggressive treatments, functional decline, falls, and dehydration [ 2 , 21 , 34 , 35 ]. This is consistent with our findings that many small-scale homes prioritized similar palliative care domains, such as reducing discomfort [ 15 ].

Another example of the influence of culture and end-of-life care policies on end-of-life care is how resident autonomy and advanced care planning are treated near the end of life. Hirakawa [ 36 ] describes that resident autonomy is a key factor in the cultural difference between Japan and Western Countries, as Western Countries have high respect for patient autonomy, while in Japan, when an individual lacks decision-making capacity, both the family and physicians play an important role in decision making. Hirakawa [ 36 ] also describes how patients in Japan often have submissive attitudes toward medical professionals concerning their concept of life and death. Similarly, Groenewoud et al. [ 37 ] discuss how Japanese individuals were less likely than Dutch individuals in their study to want to discuss end-of-life care in advance, and more Japanese individuals reported that they would be a burden to family members if they were dependent on help at the end of life. Nakanishi et al. [ 33 ] also explored the differences between end-of-life care policies for dementia in multiple countries using van der Steen et al.’s [ 15 ] recommendations for palliative care for dementia. Nakanishi et al. [ 33 ] found that palliative care policies vary significantly among countries, including the Netherlands, Japan, and the United States, on topics such as the applicability of palliative care, staff education, and person-centred care. This finding is consistent with that of Krikorian et al. [ 38 ], who report that ideas about a good death or end-of-life care relate to financial issues, religion, disease, and cultural factors. Despite the cultural factors that may have influenced our findings, many components of palliative care remain consistent despite cultural and geographical contexts, particularly pain and symptom control [ 39 ]. While the studies included in the review did not identify the cultural or contextual implications influencing palliative care, this research gap should be addressed in the future.

Palliative care domains for dementia

Some of van der Steen et al.’s [ 15 ] recommendations were covered to a greater extent in some of the papers included in this review. The studies included in this review did not adequately describe all palliative care components. This may be the case, as many of the studies included did not aim to describe palliative care in terms of the van der Steen et al. [ 15 ] domains. Palliative care domains such as advanced care planning, palliative care policies, and palliative care education require more research to determine how these processes occur in small-scale facilities. This is important as a focus on palliative care and improving palliative care education is needed both within small-scale facilities and at the public policy level to improve care at the end of life for individuals with dementia and reduce the emotional distress of family and staff members [ 40 , 41 ].

Strengths & limitations

Strengths. We used a rigorous review approach, including using the Joanna Briggs Institute Reviewers Manual for a scoping review, to structure our search and review process [ 17 ]. The van der Steen et al.’s domains for palliative care with dementia, which we used to interpret our findings, have received international consensus from experts in multiple countries [ 15 ]. Using these domains, we identified key gaps surrounding what is currently known about palliative care approaches in these small-scale dementia care facilities.

Limitations. Only papers written in English, German, or Dutch were included in this study, which may limit the number of relevant papers included in the review. The included studies were from four high-income countries, with the majority from Japan. Thus, this paper may not account for the variation in small-scale facilities in other countries. Differences in culture, national policies, and facilities, such as access to resources, may also influence the palliative care approaches of various small-scale facilities, limiting our findings’ generalizability. For example, while there are similarities between small-scale homes, there are differences in terms of access to outdoor space, participation in group activities, staffing, and the inclusion of cultural rituals that may affect palliative care approaches in these facilities [ 3 , 22 ]. The decision to have a single reviewer conduct most of our article screenings may have influenced the sensitivity of our screening process and the number of papers included in our review. However, we aimed to reduce that risk by (1) using strict selection criteria, (2) piloting our selection criteria, and (3) having two additional reviewers conduct subsections of the screening process and reviewing the screening notes and decisions made by the primary reviewer (BD).

Implications

This review identifies the current knowledge base and practices used in small-scale innovative facilities to maintain quality of life and end-of-life for residents living with dementia. The findings of our review can help inform future research in this area by identifying research gaps surrounding palliative care in these innovative facilities. Specifically, future research is needed to identify the following:

Outcomes of palliative care approaches in small-scale facilities compared to traditional homes.

Differences and similarities between countries and cultures regarding palliative care in small-scale facilities.

Various outcomes and practices related to palliative care in different models of small-scale living facilities (comparative evaluation). This includes research on the quality of palliative care, barriers to palliative care, advanced care planning, policies, and education.

This scoping review is the first of which we are aware that attempts to characterize palliative care in small-scale innovative dementia care facilities. Our results suggest that it is possible to provide palliative care and a “home for life” for individuals with dementia in these settings. This paper offers a glimpse into the palliative care approaches in these innovative facilities, particularly their focus on minimizing discomfort and prioritizing patient and family-centred care at the end of life. Most studies in this area have focused primarily on Japanese Group Homes; therefore, cultural factors may have influenced our results. Future research is, therefore, needed to understand the palliative care approaches in small-scale homes internationally and how these innovative facilities compare to traditional long-term care homes.

Data availability

No datasets were generated or analysed during the current study.

Abbreviations

Advanced care planning practice inventory

Cumulative index to nursing and allied health literature

Dutch end-of-life in dementia

European association for palliative care

Green care farm

Group home (Japan)

Preferred reporting items for systematic reviews and meta-analysis

Quality of dying long-term care scale

Wolfarts and welfare mix (Austria shared housing)

te Boekhorst S, Depla, MFIA, de Lange J, Pot AM, Eefsting JA. The effects of group living homes on older people with dementia: a comparison with traditional nursing home care. Int J Geriatr Psychiatry. 2009;24(9):970–8.

Article   Google Scholar  

Kobayashi S, Yamamoto-Mitani N, Nagata S, Murashima S. End-of-life care for older adults with dementia living in group homes in Japan. Japan J Nurs Science: JJNS. 2008;5(1):31–40.

Article   PubMed   Google Scholar  

Verbeek H, van Rossum E, Zwakhalen SMG, Kempen, GIJM, Hamers JPH. Small, homelike care environments for older people with dementia: a literature review. Int Psychogeriatr. 2009;21(2):252–64.

Ausserhofer D, Deschodt M, De Geest S, van Achterberg T, Meyer G, Verbeek H, et al. There’s no place like home: a scoping review on the impact of homelike residential care models on resident-, family-, and staff-related outcomes. J Am Med Dir Assoc. 2016;17(8):685–93.

Verbeek H, van Rossum E, Zwakhalen SMG, Ambergen T, Kempen, GIJM, Hamers JPH. The effects of small-scale, homelike facilities for older people with dementia on residents, family caregivers and staff: design of a longitudinal, quasi-experimental study. BMC Geriatr. 2009;9:3.

Article   PubMed   PubMed Central   Google Scholar  

Kane RA, Lum TY, Cutler LJ, Degenholtz HB, Yu T. Resident outcomes in small-house nursing homes: a longitudinal evaluation of the initial Green House program. J Am Geriatr Soc (JAGS). 2007;55(6):832–9.

Cohen LW, Zimmerman S, Reed D, Brown P, Bowers BJ, Nolet K, et al. The Green House Model of Nursing Home Care in design and implementation. Health Serv Res. 2016;51(S1):352–77.

Marshall M. Small scale, domestic style, long stay accommodation for people with dementia. Stirling: University of Stirling, Dementia Services Development Centre; 1993.

Google Scholar  

Verbeek H, Kane RA, van Rossum E, Hamers JPH. Promoting resilience in small-scale, homelike residential care settings for older people with dementia: experiences from the Netherlands and the United States. In: Resnick B, Gwyther L, Roberto K, editors. Resilience in aging. New York, NY: Springer New York; 2010. pp. 289–304.

de Rooij AH, Luijkx KG, Schaafsma J, Declercq A, Emmerink PM, Schols JM. Quality of life of residents with dementia in traditional versus small-scale long-term care settings: a quasi-experimental study. Int J Nurs Stud. 2012;49(8):931–40.

Sawatzky R, Porterfield P, Lee J, Dixon D, Lounsbury K, Pesut B, et al. Conceptual foundations of a palliative approach: a knowledge synthesis. BMC Palliat care. 2016;15:5.

van der Steen JT, Lemos Dekker N, Gijsberts MJHE, Vermeulen LH, Mahler MM, The BAM. Palliative care for people with dementia in the terminal phase: a mixed-methods qualitative study to inform service development. BMC Palliat care. 2017;16:28.

De Roo ML, Albers G, Deliens L, de Vet HCW, Francke AL, Van Den Noortgate N, et al. Physical and psychological distress are related to dying peacefully in residents with dementia in long-term care facilities. J Pain Symp Man. 2015;50(1):1–8.

Froggatt KA, Wilson D, Justice C, MacAdam M, Leibovici K, Kinch J, et al. End-of-life care in long-term care settings for older people: a literature review. Int J Older People Nurs. 2006;1(1):45–50.

van der Steen JT, Radbruch L, Hertogh CMPM, de Boer ME, Hughes JC, Larkin P, et al. White paper defining optimal palliative care in older people with dementia: a Delphi study and recommendations from the European Association for Palliative Care. Palliat Med. 2014;28(3):197–209.

Arksey H, O’Malley L. Scoping studies: towards a methodological framework. Int J Soc Res Methodol. 2005;8(1):19–32.

Peters MDJ, Godfrey C, McInerney P, Munn Z, Tricco AC, Khalil H. Scoping Reviews. In: Aromataris E and Munn Z, editors Joanna Briggs Institute Manual for Evidence Synthesis 2010.

Braun V, Clarke V. Using thematic analysis in psychology. Qualitative Res Psychol. 2006;3(2):77–101.

Tricco AC, Lillie E, Zarin W, O’Brien KK, Colquhoun H, Levac D et al. PRISMA Extension for scoping reviews (PRISMA-ScR): Checklist and Explanation. Ann Inter Med. 2018;169(7):467–73.

Moher D, Liberati A, Tetzlaff J, Altman DG, The PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Ann Inte Med. 2009;151(4):264–9.

Reitinger E, Pleschberger S, Schumann F. Living and dying in community based housing for people with dementia. An exploratory qualitative study. Zeitschrift für Gerontologie Und Geriatrie. 2010;43(5):285–90.

Article   CAS   PubMed   Google Scholar  

Anbäcken E, Minemoto K, Fujii M. Expressions of identity and self in daily life at a Group Home for older persons with dementia in Japan. Care Manag J. 2015;16(2):64–78.

Hirakawa Y, Masuda Y, Uemura K, Kuzuya M, Kimata T, Iguchi A. End-of-life care at group homes for patients with dementia in Japan: Findings from an analysis of policy-related differences. Arch Gerontol Geriatr. 2006;42(3):233–45.

Nakanishi M, Honda T. Processes of decision making and end-of-life care for patients with dementia in group homes in Japan. Arch Gerontol Geriatr. 2009;48(3):296–9.

Nakanishi M, Hirooka K, Morimoto Y, Nishida A. Quality of care for people with dementia and professional caregivers’ perspectives regarding palliative care in Japanese community care settings. Int J Geriatr Psychiatry. 2016;32(12):1342–51.

Takada S, Ogata Y, Yumoto Y, Ikeda M. Implementation of an Advance Care Planning Inventory and its possible effect on quality of dying: A nationwide cross-sectional study in Group Homes for persons with dementia in Japan. Healthcare. 2021;10(1):62.

Smit KD, Bolt SR, De Boer B, Verbeek H, Meijers JMM. End-of-life care for people with dementia on a green care farm during the COVID-19 pandemic: a qualitative study. BMC Geriatr. 2022;22:956.

The Green House Project. Core values and practices. The Green House Project, Maryland, US: Report; 2012.

van der Steen JT. Dutch End of Life in Dementia (DEOLD). Unpublished Raw Data. 2016.

Wild D, Nelson S, Szczepura A. A ‘home for life’ in residential homes for older people in England: exploring the enhancers and inhibitors. Housing, Care and Support. 2010;13(2):26–35.

Brazil K, Bédard M, Krueger P, Taniguchi A, Kelley ML, McAiney C, et al. Barriers to providing palliative care in long-term care facilities. Can Fam Physician. 2006;52(4):472–3.

PubMed   PubMed Central   Google Scholar  

Nishiguchi S, Sugaya N, Sakamaki K, Mizushima S. End-of-life care bonus promoting end-of-life care in nursing homes: an 11-year retrospective longitudinal prefecture-wide study in Japan. BST. 2017;11:54–61.

Nakanishi M, Nakashima T, Shindo Y, Miyamoto Y, Gove D, Radbruch L, et al. An evaluation of palliative care contents in national dementia strategies in reference to the European Association for Palliative Care white paper. Int Psychogeriatr. 2015;27(9):1551–61.

Dewing J, Dijk S. What is the current state of care for older people with dementia in general hospitals? A literature review. Dementia. 2016;15(1):106–24.

Palan Lopez R, Mitchell SL, Givens JL. Preventing burdensome transitions of nursing home residents with Advanced Dementia: it’s more than advance directives. J Palliat Med. 2017;20(11):1205–9.

Hirakawa Y. Palliative care for the elderly: a Japanese perspective. In E.Chang (editor), Contemporary and Innovative Practice Palliative Care 2012;271–90.

Groenewoud AS, Sasaki N, Westert GP, Imanaka Y. Preferences in end of life care substantially differ between the Netherlands and Japan: results from a cross-sectional survey study. Medicine. 2020;99(44):e22743.

Krikorian A, Maldonado C, Pastrana T. Patient’s perspectives on the notion of a good death: a systematic review of the literature. J Pain Symptom Manag. 2020;59(1):152–64.

Nishimura M, Dening KH, Sampson EL, et al. Cross-cultural conceptualization of a good end of life with dementia: a qualitative study. BMC Palliat Care. 2022;21:106.

Abbey J, Froggatt KA, Parker D, Abbey B. Palliative care in long-term care: a system in change. Int J Older People Nurs. 2006;1(1):56–63.

Vandervoort A, Houttekier D, Vander Stichele R, van der Steen JT, Van den Block L. Quality of dying in nursing home residents dying with dementia: does advanced care planning matter? A nationwide postmortem study. PLoS One. 2014;9(3):e91130.

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The authors disclosed receipt of the following financial support for this article’s research and/or publication: B. DeGraves’ inclusion was supported by the Mitacs Globalink Research Award [grant reference number IT14027]. The authors received no other financial support for the research, authorship, or publication of this article.

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BD, JM, and HV drafted the research question and scoping design. BD collected and analyzed the literature and wrote the review. JM, HV, and CE assisted in writing and reviewing the paper. All authors read and approved the final manuscript.

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DeGraves, B.S., Meijers, J.M.M., Estabrooks, C.A. et al. Palliative care in small-scale living facilities: a scoping review. BMC Geriatr 24 , 700 (2024). https://doi.org/10.1186/s12877-024-05259-9

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