how to write results in a literature review

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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How To Write A Literature Review - A Complete Guide

Table of Contents

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

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

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

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

What is a literature review?

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

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

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

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

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

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

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

What is the purpose of a literature review?

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

What is the importance of a literature review?

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

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

How long should a literature review be?

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

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

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

What are the different types of literature reviews?

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

Here are the different types of literature reviews:

Argumentative review

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

Integrative review

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

Methodological review

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

Systematic review

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

Meta-analysis review

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

Historical review

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

Theoretical Review

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

Scoping Review

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

State-of-the-Art Review

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

Can you use the first person in a literature review?

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

Do you need an abstract for a literature review?

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

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

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

Is a literature review written in the past tense?

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

How many sources for a literature review?

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

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

Quick tips on how to write a literature review

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

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

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

1. Outline and identify the purpose of  a literature review

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

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

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

2. Search relevant literature

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

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

• Google Scholar
• Microsoft Academic
• Science.gov

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

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

3. Examine and assess the sources

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

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

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

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

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

4. Discover connections

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

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

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

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

5. Structure planning to write a good literature review

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

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

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

Literature review samples

1. Standalone

2. As a section of a research paper

How SciSpace Discover makes literature review a breeze?

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

Find the right information

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

Assess credibility of papers quickly

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

Get the complete picture in no time

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

Make referring sources super easy

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

Final tips on how to write a literature review

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

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

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

Frequently Asked Questions (FAQs)

1. how to start a literature review.

• What questions do you want to answer?

• What sources do you need to answer these questions?

• What information do these sources contain?

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

2. What to include in a literature review?

• A brief background of the problem or issue

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

• A description of what you will do in your project

• How this study will contribute to research on the subject

3. Why literature review is important?

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

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

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

5. What are the components of a literature review?

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

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

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

6. What are common errors in writing literature review?

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

• Totally relying on secondary data while ignoring primary data.

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

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

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

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

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

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

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

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

8. How many sources should a literature review have?

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

9. Can literature review have diagrams?

• To represent an abstract idea or concept

• To explain the steps of a process or procedure

• To help readers understand the relationships between different concepts

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

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

11. What are the types of literature review?

• Argumentative review

• Integrative review

• Methodological review

• Systematic review

• Meta-analysis review

• Historical review

• Theoretical review

• Scoping review

• State-of-the-Art review

12. Is a literature review mandatory?

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

But before you go,

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

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• 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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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 systematic literature review [9 steps]

What is a systematic literature review?

Where are systematic literature reviews used, what types of systematic literature reviews are there, how to write a systematic literature review, 1. decide on your team, 2. formulate your question, 3. plan your research protocol, 4. search for the literature, 5. screen the literature, 6. assess the quality of the studies, 7. extract the data, 8. analyze the results, 9. interpret and present the results, registering your systematic literature review, frequently asked questions about writing a systematic literature review, related articles.

A systematic literature review is a summary, analysis, and evaluation of all the existing research on a well-formulated and specific question.

Put simply, a systematic review is a study of studies that is popular in medical and healthcare research. In this guide, we will cover:

• the definition of a systematic literature review
• the purpose of a systematic literature review
• the different types of systematic reviews
• how to write a systematic literature review

➡️ Visit our guide to the best research databases for medicine and health to find resources for your systematic review.

Systematic literature reviews can be utilized in various contexts, but they’re often relied on in clinical or healthcare settings.

Medical professionals read systematic literature reviews to stay up-to-date in their field, and granting agencies sometimes need them to make sure there’s justification for further research in an area. They can even be used as the starting point for developing clinical practice guidelines.

A classic systematic literature review can take different approaches:

• Effectiveness reviews assess the extent to which a medical intervention or therapy achieves its intended effect. They’re the most common type of systematic literature review.
• Diagnostic test accuracy reviews produce a summary of diagnostic test performance so that their accuracy can be determined before use by healthcare professionals.
• Experiential (qualitative) reviews analyze human experiences in a cultural or social context. They can be used to assess the effectiveness of an intervention from a person-centric perspective.
• Costs/economics evaluation reviews look at the cost implications of an intervention or procedure, to assess the resources needed to implement it.
• Etiology/risk reviews usually try to determine to what degree a relationship exists between an exposure and a health outcome. This can be used to better inform healthcare planning and resource allocation.
• Psychometric reviews assess the quality of health measurement tools so that the best instrument can be selected for use.
• Prevalence/incidence reviews measure both the proportion of a population who have a disease, and how often the disease occurs.
• Prognostic reviews examine the course of a disease and its potential outcomes.
• Expert opinion/policy reviews are based around expert narrative or policy. They’re often used to complement, or in the absence of, quantitative data.
• Methodology systematic reviews can be carried out to analyze any methodological issues in the design, conduct, or review of research studies.

Writing a systematic literature review can feel like an overwhelming undertaking. After all, they can often take 6 to 18 months to complete. Below we’ve prepared a step-by-step guide on how to write a systematic literature review.

• Decide on your team.
• Formulate your question.
• Plan your research protocol.
• Search for the literature.
• Screen the literature.
• Assess the quality of the studies.
• Extract the data.
• Analyze the results.
• Interpret and present the results.

When carrying out a systematic literature review, you should employ multiple reviewers in order to minimize bias and strengthen analysis. A minimum of two is a good rule of thumb, with a third to serve as a tiebreaker if needed.

You may also need to team up with a librarian to help with the search, literature screeners, a statistician to analyze the data, and the relevant subject experts.

Define your answerable question. Then ask yourself, “has someone written a systematic literature review on my question already?” If so, yours may not be needed. A librarian can help you answer this.

You should formulate a “well-built clinical question.” This is the process of generating a good search question. To do this, run through PICO:

• Patient or Population or Problem/Disease : who or what is the question about? Are there factors about them (e.g. age, race) that could be relevant to the question you’re trying to answer?
• Intervention : which main intervention or treatment are you considering for assessment?
• Comparison(s) or Control : is there an alternative intervention or treatment you’re considering? Your systematic literature review doesn’t have to contain a comparison, but you’ll want to stipulate at this stage, either way.
• Outcome(s) : what are you trying to measure or achieve? What’s the wider goal for the work you’ll be doing?

Now you need a detailed strategy for how you’re going to search for and evaluate the studies relating to your question.

The protocol for your systematic literature review should include:

• the objectives of your project
• the specific methods and processes that you’ll use
• the eligibility criteria of the individual studies
• how you plan to extract data from individual studies
• which analyses you’re going to carry out

For a full guide on how to systematically develop your protocol, take a look at the PRISMA checklist . PRISMA has been designed primarily to improve the reporting of systematic literature reviews and meta-analyses.

When writing a systematic literature review, your goal is to find all of the relevant studies relating to your question, so you need to search thoroughly .

This is where your librarian will come in handy again. They should be able to help you formulate a detailed search strategy, and point you to all of the best databases for your topic.

➡️ Read more on on how to efficiently search research databases .

The places to consider in your search are electronic scientific databases (the most popular are PubMed , MEDLINE , and Embase ), controlled clinical trial registers, non-English literature, raw data from published trials, references listed in primary sources, and unpublished sources known to experts in the field.

➡️ Take a look at our list of the top academic research databases .

Tip: Don’t miss out on “gray literature.” You’ll improve the reliability of your findings by including it.

Don’t miss out on “gray literature” sources: those sources outside of the usual academic publishing environment. They include:

• non-peer-reviewed journals
• pharmaceutical industry files
• conference proceedings
• pharmaceutical company websites
• internal reports

Gray literature sources are more likely to contain negative conclusions, so you’ll improve the reliability of your findings by including it. You should document details such as:

• The databases you search and which years they cover
• The dates you first run the searches, and when they’re updated
• Which strategies you use, including search terms
• The numbers of results obtained

➡️ Read more about gray literature .

This should be performed by your two reviewers, using the criteria documented in your research protocol. The screening is done in two phases:

• Pre-screening of all titles and abstracts, and selecting those appropriate
• Screening of the full-text articles of the selected studies

Make sure reviewers keep a log of which studies they exclude, with reasons why.

➡️ Visit our guide on what is an abstract?

Your reviewers should evaluate the methodological quality of your chosen full-text articles. Make an assessment checklist that closely aligns with your research protocol, including a consistent scoring system, calculations of the quality of each study, and sensitivity analysis.

The kinds of questions you'll come up with are:

• Were the participants really randomly allocated to their groups?
• Were the groups similar in terms of prognostic factors?
• Could the conclusions of the study have been influenced by bias?

Every step of the data extraction must be documented for transparency and replicability. Create a data extraction form and set your reviewers to work extracting data from the qualified studies.

Here’s a free detailed template for recording data extraction, from Dalhousie University. It should be adapted to your specific question.

Establish a standard measure of outcome which can be applied to each study on the basis of its effect size.

Measures of outcome for studies with:

• Binary outcomes (e.g. cured/not cured) are odds ratio and risk ratio
• Continuous outcomes (e.g. blood pressure) are means, difference in means, and standardized difference in means
• Survival or time-to-event data are hazard ratios

Design a table and populate it with your data results. Draw this out into a forest plot , which provides a simple visual representation of variation between the studies.

Then analyze the data for issues. These can include heterogeneity, which is when studies’ lines within the forest plot don’t overlap with any other studies. Again, record any excluded studies here for reference.

Consider different factors when interpreting your results. These include limitations, strength of evidence, biases, applicability, economic effects, and implications for future practice or research.

Apply appropriate grading of your evidence and consider the strength of your recommendations.

It’s best to formulate a detailed plan for how you’ll present your systematic review results. Take a look at these guidelines for interpreting results from the Cochrane Institute.

Before writing your systematic literature review, you can register it with OSF for additional guidance along the way. You could also register your completed work with PROSPERO .

Systematic literature reviews are often found in clinical or healthcare settings. Medical professionals read systematic literature reviews to stay up-to-date in their field and granting agencies sometimes need them to make sure there’s justification for further research in an area.

The first stage in carrying out a systematic literature review is to put together your team. You should employ multiple reviewers in order to minimize bias and strengthen analysis. A minimum of two is a good rule of thumb, with a third to serve as a tiebreaker if needed.

Your systematic review should include the following details:

A literature review simply provides a summary of the literature available on a topic. A systematic review, on the other hand, is more than just a summary. It also includes an analysis and evaluation of existing research. Put simply, it's a study of studies.

The final stage of conducting a systematic literature review is interpreting and presenting the results. It’s best to formulate a detailed plan for how you’ll present your systematic review results, guidelines can be found for example from the Cochrane institute .

• 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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How to Write a Systematic Review: A Narrative Review

Ali hasanpour dehkordi.

Social Determinants of Health Research Center, Shahrekord University of Medical Sciences, Shahrekord, Iran

Elaheh Mazaheri

1 Health Information Technology Research Center, Student Research Committee, Department of Medical Library and Information Sciences, School of Management and Medical Information Sciences, Isfahan University of Medical Sciences, Isfahan, Iran

Hanan A. Ibrahim

2 Department of International Relations, College of Law, Bayan University, Erbil, Kurdistan, Iraq

Sahar Dalvand

3 MSc in Biostatistics, Health Promotion Research Center, Iran University of Medical Sciences, Tehran, Iran

Reza Ghanei Gheshlagh

4 Spiritual Health Research Center, Research Institute for Health Development, Kurdistan University of Medical Sciences, Sanandaj, Iran

In recent years, published systematic reviews in the world and in Iran have been increasing. These studies are an important resource to answer evidence-based clinical questions and assist health policy-makers and students who want to identify evidence gaps in published research. Systematic review studies, with or without meta-analysis, synthesize all available evidence from studies focused on the same research question. In this study, the steps for a systematic review such as research question design and identification, the search for qualified published studies, the extraction and synthesis of information that pertain to the research question, and interpretation of the results are presented in details. This will be helpful to all interested researchers.

A systematic review, as its name suggests, is a systematic way of collecting, evaluating, integrating, and presenting findings from several studies on a specific question or topic.[ 1 ] A systematic review is a research that, by identifying and combining evidence, is tailored to and answers the research question, based on an assessment of all relevant studies.[ 2 , 3 ] To identify assess and interpret available research, identify effective and ineffective health-care interventions, provide integrated documentation to help decision-making, and identify the gap between studies is one of the most important reasons for conducting systematic review studies.[ 4 ]

In the review studies, the latest scientific information about a particular topic is criticized. In these studies, the terms of review, systematic review, and meta-analysis are used instead. A systematic review is done in one of two methods, quantitative (meta-analysis) and qualitative. In a meta-analysis, the results of two or more studies for the evaluation of say health interventions are combined to measure the effect of treatment, while in the qualitative method, the findings of other studies are combined without using statistical methods.[ 5 ]

Since 1999, various guidelines, including the QUORUM, the MOOSE, the STROBE, the CONSORT, and the QUADAS, have been introduced for reporting meta-analyses. But recently the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement has gained widespread popularity.[ 6 , 7 , 8 , 9 ] The systematic review process based on the PRISMA statement includes four steps of how to formulate research questions, define the eligibility criteria, identify all relevant studies, extract and synthesize data, and deduce and present results (answers to research questions).[ 2 ]

Systematic Review Protocol

Systematic reviews start with a protocol. The protocol is a researcher road map that outlines the goals, methodology, and outcomes of the research. Many journals advise writers to use the PRISMA statement to write the protocol.[ 10 ] The PRISMA checklist includes 27 items related to the content of a systematic review and meta-analysis and includes abstracts, methods, results, discussions, and financial resources.[ 11 ] PRISMA helps writers improve their systematic review and meta-analysis report. Reviewers and editors of medical journals acknowledge that while PRISMA may not be used as a tool to assess the methodological quality, it does help them to publish a better study article [ Figure 1 ].[ 12 ]

Screening process and articles selection according to the PRISMA guidelines

The main step in designing the protocol is to define the main objectives of the study and provide some background information. Before starting a systematic review, it is important to assess that your study is not a duplicate; therefore, in search of published research, it is necessary to review PREOSPERO and the Cochrane Database of Systematic. Sometimes it is better to search, in four databases, related systematic reviews that have already been published (PubMed, Web of Sciences, Scopus, Cochrane), published systematic review protocols (PubMed, Web of Sciences, Scopus, Cochrane), systematic review protocols that have already been registered but have not been published (PROSPERO, Cochrane), and finally related published articles (PubMed, Web of Sciences, Scopus, Cochrane). The goal is to reduce duplicate research and keep up-to-date systematic reviews.[ 13 ]

Research questions

Writing a research question is the first step in systematic review that summarizes the main goal of the study.[ 14 ] The research question determines which types of studies should be included in the analysis (quantitative, qualitative, methodic mix, review overviews, or other studies). Sometimes a research question may be broken down into several more detailed questions.[ 15 ] The vague questions (such as: is walking helpful?) makes the researcher fail to be well focused on the collected studies or analyze them appropriately.[ 16 ] On the other hand, if the research question is rigid and restrictive (e.g., walking for 43 min and 3 times a week is better than walking for 38 min and 4 times a week?), there may not be enough studies in this area to answer this question and hence the generalizability of the findings to other populations will be reduced.[ 16 , 17 ] A good question in systematic review should include components that are PICOS style which include population (P), intervention (I), comparison (C), outcome (O), and setting (S).[ 18 ] Regarding the purpose of the study, control in clinical trials or pre-poststudies can replace C.[ 19 ]

Search and identify eligible texts

After clarifying the research question and before searching the databases, it is necessary to specify searching methods, articles screening, studies eligibility check, check of the references in eligible studies, data extraction, and data analysis. This helps researchers ensure that potential biases in the selection of potential studies are minimized.[ 14 , 17 ] It should also look at details such as which published and unpublished literature have been searched, how they were searched, by which mechanism they were searched, and what are the inclusion and exclusion criteria.[ 4 ] First, all studies are searched and collected according to predefined keywords; then the title, abstract, and the entire text are screened for relevance by the authors.[ 13 ] By screening articles based on their titles, researchers can quickly decide on whether to retain or remove an article. If more information is needed, the abstracts of the articles will also be reviewed. In the next step, the full text of the articles will be reviewed to identify the relevant articles, and the reason for the removal of excluded articles is reported.[ 20 ] Finally, it is recommended that the process of searching, selecting, and screening articles be reported as a flowchart.[ 21 ] By increasing research, finding up-to-date and relevant information has become more difficult.[ 22 ]

Currently, there is no specific guideline as to which databases should be searched, which database is the best, and how many should be searched; but overall, it is advisable to search broadly. Because no database covers all health topics, it is recommended to use several databases to search.[ 23 ] According to the A MeaSurement Tool to Assess Systematic Reviews scale (AMSTAR) at least two databases should be searched in systematic and meta-analysis, although more comprehensive and accurate results can be obtained by increasing the number of searched databases.[ 24 ] The type of database to be searched depends on the systematic review question. For example, in a clinical trial study, it is recommended that Cochrane, multi-regional clinical trial (mRCTs), and International Clinical Trials Registry Platform be searched.[ 25 ]

For example, MEDLINE, a product of the National Library of Medicine in the United States of America, focuses on peer-reviewed articles in biomedical and health issues, while Embase covers the broad field of pharmacology and summaries of conferences. CINAHL is a great resource for nursing and health research and PsycINFO is a great database for psychology, psychiatry, counseling, addiction, and behavioral problems. Also, national and regional databases can be used to search related articles.[ 26 , 27 ] In addition, the search for conferences and gray literature helps to resolve the file-drawn problem (negative studies that may not be published yet).[ 26 ] If a systematic review is carried out on articles in a particular country or region, the databases in that region or country should also be investigated. For example, Iranian researchers can use national databases such as Scientific Information Database and MagIran. Comprehensive search to identify the maximum number of existing studies leads to a minimization of the selection bias. In the search process, the available databases should be used as much as possible, since many databases are overlapping.[ 17 ] Searching 12 databases (PubMed, Scopus, Web of Science, EMBASE, GHL, VHL, Cochrane, Google Scholar, Clinical trials.gov, mRCTs, POPLINE, and SIGLE) covers all articles published in the field of medicine and health.[ 25 ] Some have suggested that references management software be used to search for more easy identification and removal of duplicate articles from several different databases.[ 20 ] At least one search strategy is presented in the article.[ 21 ]

Quality assessment

The methodological quality assessment of articles is a key step in systematic review that helps identify systemic errors (bias) in results and interpretations. In systematic review studies, unlike other review studies, qualitative assessment or risk of bias is required. There are currently several tools available to review the quality of the articles. The overall score of these tools may not provide sufficient information on the strengths and weaknesses of the studies.[ 28 ] At least two reviewers should independently evaluate the quality of the articles, and if there is any objection, the third author should be asked to examine the article or the two researchers agree on the discussion. Some believe that the study of the quality of studies should be done by removing the name of the journal, title, authors, and institutions in a Blinded fashion.[ 29 ]

There are several ways for quality assessment, such as Sack's quality assessment (1988),[ 30 ] overview quality assessment questionnaire (1991),[ 31 ] CASP (Critical Appraisal Skills Program),[ 32 ] and AMSTAR (2007),[ 33 ] Besides, CASP,[ 34 ] the National Institute for Health and Care Excellence,[ 35 ] and the Joanna Briggs Institute System for the Unified Management, Assessment and Review of Information checklists.[ 30 , 36 ] However, it is worth mentioning that there is no single tool for assessing the quality of all types of reviews, but each is more applicable to some types of reviews. Often, the STROBE tool is used to check the quality of articles. It reviews the title and abstract (item 1), introduction (items 2 and 3), implementation method (items 4–12), findings (items 13–17), discussion (Items 18–21), and funding (item 22). Eighteen items are used to review all articles, but four items (6, 12, 14, and 15) apply in certain situations.[ 9 ] The quality of interventional articles is often evaluated by the JADAD tool, which consists of three sections of randomization (2 scores), blinding (2 scores), and patient count (1 scores).[ 29 ]

Data extraction

At this stage, the researchers extract the necessary information in the selected articles. Elamin believes that reviewing the titles and abstracts and data extraction is a key step in the review process, which is often carried out by two of the research team independently, and ultimately, the results are compared.[ 37 ] This step aimed to prevent selection bias and it is recommended that the chance of agreement between the two researchers (Kappa coefficient) be reported at the end.[ 26 ] Although data collection forms may differ in systematic reviews, they all have information such as first author, year of publication, sample size, target community, region, and outcome. The purpose of data synthesis is to collect the findings of eligible studies, evaluate the strengths of the findings of the studies, and summarize the results. In data synthesis, we can use different analysis frameworks such as meta-ethnography, meta-analysis, or thematic synthesis.[ 38 ] Finally, after quality assessment, data analysis is conducted. The first step in this section is to provide a descriptive evaluation of each study and present the findings in a tabular form. Reviewing this table can determine how to combine and analyze various studies.[ 28 ] The data synthesis approach depends on the nature of the research question and the nature of the initial research studies.[ 39 ] After reviewing the bias and the abstract of the data, it is decided that the synthesis is carried out quantitatively or qualitatively. In case of conceptual heterogeneity (systematic differences in the study design, population, and interventions), the generalizability of the findings will be reduced and the study will not be meta-analysis. The meta-analysis study allows the estimation of the effect size, which is reported as the odds ratio, relative risk, hazard ratio, prevalence, correlation, sensitivity, specificity, and incidence with a confidence interval.[ 26 ]

Estimation of the effect size in systematic review and meta-analysis studies varies according to the type of studies entered into the analysis. Unlike the mean, prevalence, or incidence index, in odds ratio, relative risk, and hazard ratio, it is necessary to combine logarithm and logarithmic standard error of these statistics [ Table 1 ].

Effect size in systematic review and meta-analysis

OR=Odds ratio; RR=Relative risk; RCT= Randomized controlled trial; PPV: positive predictive value; NPV: negative predictive value; PLR: positive likelihood ratio; NLR: negative likelihood ratio; DOR: diagnostic odds ratio

Interpreting and presenting results (answers to research questions)

A systematic review ends with the interpretation of results. At this stage, the results of the study are summarized and the conclusions are presented to improve clinical and therapeutic decision-making. A systematic review with or without meta-analysis provides the best evidence available in the hierarchy of evidence-based practice.[ 14 ] Using meta-analysis can provide explicit conclusions. Conceptually, meta-analysis is used to combine the results of two or more studies that are similar to the specific intervention and the similar outcomes. In meta-analysis, instead of the simple average of the results of various studies, the weighted average of studies is reported, meaning studies with larger sample sizes account for more weight. To combine the results of various studies, we can use two models of fixed and random effects. In the fixed-effect model, it is assumed that the parameters studied are constant in all studies, and in the random-effect model, the measured parameter is assumed to be distributed between the studies and each study has measured some of it. This model offers a more conservative estimate.[ 40 ]

Three types of homogeneity tests can be used: (1) forest plot, (2) Cochrane's Q test (Chi-squared), and (3) Higgins I 2 statistics. In the forest plot, more overlap between confidence intervals indicates more homogeneity. In the Q statistic, when the P value is less than 0.1, it indicates heterogeneity exists and a random-effect model should be used.[ 41 ] Various tests such as the I 2 index are used to determine heterogeneity, values between 0 and 100; the values below 25%, between 25% and 50%, and above 75% indicate low, moderate, and high levels of heterogeneity, respectively.[ 26 , 42 ] The results of the meta-analyzing study are presented graphically using the forest plot, which shows the statistical weight of each study with a 95% confidence interval and a standard error of the mean.[ 40 ]

The importance of meta-analyses and systematic reviews in providing evidence useful in making clinical and policy decisions is ever-increasing. Nevertheless, they are prone to publication bias that occurs when positive or significant results are preferred for publication.[ 43 ] Song maintains that studies reporting a certain direction of results or powerful correlations may be more likely to be published than the studies which do not.[ 44 ] In addition, when searching for meta-analyses, gray literature (e.g., dissertations, conference abstracts, or book chapters) and unpublished studies may be missed. Moreover, meta-analyses only based on published studies may exaggerate the estimates of effect sizes; as a result, patients may be exposed to harmful or ineffective treatment methods.[ 44 , 45 ] However, there are some tests that can help in detecting negative expected results that are not included in a review due to publication bias.[ 46 ] In addition, publication bias can be reduced through searching for data that are not published.

Systematic reviews and meta-analyses have certain advantages; some of the most important ones are as follows: examining differences in the findings of different studies, summarizing results from various studies, increased accuracy of estimating effects, increased statistical power, overcoming problems related to small sample sizes, resolving controversies from disagreeing studies, increased generalizability of results, determining the possible need for new studies, overcoming the limitations of narrative reviews, and making new hypotheses for further research.[ 47 , 48 ]

Despite the importance of systematic reviews, the author may face numerous problems in searching, screening, and synthesizing data during this process. A systematic review requires extensive access to databases and journals that can be costly for nonacademic researchers.[ 13 ] Also, in reviewing the inclusion and exclusion criteria, the inevitable mindsets of browsers may be involved and the criteria are interpreted differently from each other.[ 49 ] Lee refers to some disadvantages of these studies, the most significant ones are as follows: a research field cannot be summarized by one number, publication bias, heterogeneity, combining unrelated things, being vulnerable to subjectivity, failing to account for all confounders, comparing variables that are not comparable, just focusing on main effects, and possible inconsistency with results of randomized trials.[ 47 ] Different types of programs are available to perform meta-analysis. Some of the most commonly used statistical programs are general statistical packages, including SAS, SPSS, R, and Stata. Using flexible commands in these programs, meta-analyses can be easily run and the results can be readily plotted out. However, these statistical programs are often expensive. An alternative to using statistical packages is to use programs designed for meta-analysis, including Metawin, RevMan, and Comprehensive Meta-analysis. However, these programs may have limitations, including that they can accept few data formats and do not provide much opportunity to set the graphical display of findings. Another alternative is to use Microsoft Excel. Although it is not a free software, it is usually found in many computers.[ 20 , 50 ]

A systematic review study is a powerful and valuable tool for answering research questions, generating new hypotheses, and identifying areas where there is a lack of tangible knowledge. A systematic review study provides an excellent opportunity for researchers to improve critical assessment and evidence synthesis skills.

Authors' contributions

All authors contributed equally to this work.

Financial support and sponsorship

Conflicts of interest.

There are no conflicts of interest.

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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How to Write a Literature Review

What is a literature review.

• What Is the Literature
• Writing the Review

A literature review is much more than an annotated bibliography or a list of separate reviews of articles and books. It is a critical, analytical summary and synthesis of the current knowledge of a topic. Thus it should compare and relate different theories, findings, etc, rather than just summarize them individually. In addition, it should have a particular focus or theme to organize the review. It does not have to be an exhaustive account of everything published on the topic, but it should discuss all the significant academic literature and other relevant sources important for that focus.

This is meant to be a general guide to writing a literature review: ways to structure one, what to include, how it supplements other research. For more specific help on writing a review, and especially for help on finding the literature to review, sign up for a Personal Research Session .

The specific organization of a literature review depends on the type and purpose of the review, as well as on the specific field or topic being reviewed. But in general, it is a relatively brief but thorough exploration of past and current work on a topic. Rather than a chronological listing of previous work, though, literature reviews are usually organized thematically, such as different theoretical approaches, methodologies, or specific issues or concepts involved in the topic. A thematic organization makes it much easier to examine contrasting perspectives, theoretical approaches, methodologies, findings, etc, and to analyze the strengths and weaknesses of, and point out any gaps in, previous research. And this is the heart of what a literature review is about. A literature review may offer new interpretations, theoretical approaches, or other ideas; if it is part of a research proposal or report it should demonstrate the relationship of the proposed or reported research to others' work; but whatever else it does, it must provide a critical overview of the current state of research efforts. 

Literature reviews are common and very important in the sciences and social sciences. They are less common and have a less important role in the humanities, but they do have a place, especially stand-alone reviews.

Types of Literature Reviews

There are different types of literature reviews, and different purposes for writing a review, but the most common are:

• Stand-alone literature review articles . These provide an overview and analysis of the current state of research on a topic or question. The goal is to evaluate and compare previous research on a topic to provide an analysis of what is currently known, and also to reveal controversies, weaknesses, and gaps in current work, thus pointing to directions for future research. You can find examples published in any number of academic journals, but there is a series of Annual Reviews of *Subject* which are specifically devoted to literature review articles. Writing a stand-alone review is often an effective way to get a good handle on a topic and to develop ideas for your own research program. For example, contrasting theoretical approaches or conflicting interpretations of findings can be the basis of your research project: can you find evidence supporting one interpretation against another, or can you propose an alternative interpretation that overcomes their limitations?
• Part of a research proposal . This could be a proposal for a PhD dissertation, a senior thesis, or a class project. It could also be a submission for a grant. The literature review, by pointing out the current issues and questions concerning a topic, is a crucial part of demonstrating how your proposed research will contribute to the field, and thus of convincing your thesis committee to allow you to pursue the topic of your interest or a funding agency to pay for your research efforts.
• Part of a research report . When you finish your research and write your thesis or paper to present your findings, it should include a literature review to provide the context to which your work is a contribution. Your report, in addition to detailing the methods, results, etc. of your research, should show how your work relates to others' work.

A literature review for a research report is often a revision of the review for a research proposal, which can be a revision of a stand-alone review. Each revision should be a fairly extensive revision. With the increased knowledge of and experience in the topic as you proceed, your understanding of the topic will increase. Thus, you will be in a better position to analyze and critique the literature. In addition, your focus will change as you proceed in your research. Some areas of the literature you initially reviewed will be marginal or irrelevant for your eventual research, and you will need to explore other areas more thoroughly. 

Examples of Literature Reviews

See the series of Annual Reviews of *Subject* which are specifically devoted to literature review articles to find many examples of stand-alone literature reviews in the biomedical, physical, and social sciences. 

Research report articles vary in how they are organized, but a common general structure is to have sections such as:

• Abstract - Brief summary of the contents of the article
• Introduction - A explanation of the purpose of the study, a statement of the research question(s) the study intends to address
• Literature review - A critical assessment of the work done so far on this topic, to show how the current study relates to what has already been done
• Methods - How the study was carried out (e.g. instruments or equipment, procedures, methods to gather and analyze data)
• Results - What was found in the course of the study
• Discussion - What do the results mean
• Conclusion - State the conclusions and implications of the results, and discuss how it relates to the work reviewed in the literature review; also, point to directions for further work in the area

Here are some articles that illustrate variations on this theme. There is no need to read the entire articles (unless the contents interest you); just quickly browse through to see the sections, and see how each section is introduced and what is contained in them.

The Determinants of Undergraduate Grade Point Average: The Relative Importance of Family Background, High School Resources, and Peer Group Effects , in The Journal of Human Resources , v. 34 no. 2 (Spring 1999), p. 268-293.

This article has a standard breakdown of sections:

• Introduction
• Literature Review
• Some discussion sections

First Encounters of the Bureaucratic Kind: Early Freshman Experiences with a Campus Bureaucracy , in The Journal of Higher Education , v. 67 no. 6 (Nov-Dec 1996), p. 660-691.

This one does not have a section specifically labeled as a "literature review" or "review of the literature," but the first few sections cite a long list of other sources discussing previous research in the area before the authors present their own study they are reporting.

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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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• How to Write a Discussion Section | Tips & Examples

How to Write a Discussion Section | Tips & Examples

Published on August 21, 2022 by Shona McCombes . Revised on July 18, 2023.

The discussion section is where you delve into the meaning, importance, and relevance of your results .

It should focus on explaining and evaluating what you found, showing how it relates to your literature review and paper or dissertation topic , and making an argument in support of your overall conclusion. It should not be a second results section.

There are different ways to write this section, but you can focus your writing around these key elements:

• Summary : A brief recap of your key results
• Interpretations: What do your results mean?
• Implications: Why do your results matter?
• Limitations: What can’t your results tell us?
• Recommendations: Avenues for further studies or analyses

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Table of contents

What not to include in your discussion section, step 1: summarize your key findings, step 2: give your interpretations, step 3: discuss the implications, step 4: acknowledge the limitations, step 5: share your recommendations, discussion section example, other interesting articles, frequently asked questions about discussion sections.

There are a few common mistakes to avoid when writing the discussion section of your paper.

• Don’t introduce new results: You should only discuss the data that you have already reported in your results section .
• Don’t make inflated claims: Avoid overinterpretation and speculation that isn’t directly supported by your data.
• Don’t undermine your research: The discussion of limitations should aim to strengthen your credibility, not emphasize weaknesses or failures.

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Start this section by reiterating your research problem and concisely summarizing your major findings. To speed up the process you can use a summarizer to quickly get an overview of all important findings. Don’t just repeat all the data you have already reported—aim for a clear statement of the overall result that directly answers your main research question . This should be no more than one paragraph.

Many students struggle with the differences between a discussion section and a results section . The crux of the matter is that your results sections should present your results, and your discussion section should subjectively evaluate them. Try not to blend elements of these two sections, in order to keep your paper sharp.

• The results indicate that…
• The study demonstrates a correlation between…
• This analysis supports the theory that…
• The data suggest that…

The meaning of your results may seem obvious to you, but it’s important to spell out their significance for your reader, showing exactly how they answer your research question.

The form of your interpretations will depend on the type of research, but some typical approaches to interpreting the data include:

• Identifying correlations , patterns, and relationships among the data
• Discussing whether the results met your expectations or supported your hypotheses
• Contextualizing your findings within previous research and theory
• Explaining unexpected results and evaluating their significance
• Considering possible alternative explanations and making an argument for your position

You can organize your discussion around key themes, hypotheses, or research questions, following the same structure as your results section. Alternatively, you can also begin by highlighting the most significant or unexpected results.

• In line with the hypothesis…
• Contrary to the hypothesized association…
• The results contradict the claims of Smith (2022) that…
• The results might suggest that x . However, based on the findings of similar studies, a more plausible explanation is y .

As well as giving your own interpretations, make sure to relate your results back to the scholarly work that you surveyed in the literature review . The discussion should show how your findings fit with existing knowledge, what new insights they contribute, and what consequences they have for theory or practice.

Ask yourself these questions:

• Do your results support or challenge existing theories? If they support existing theories, what new information do they contribute? If they challenge existing theories, why do you think that is?
• Are there any practical implications?

Your overall aim is to show the reader exactly what your research has contributed, and why they should care.

• These results build on existing evidence of…
• The results do not fit with the theory that…
• The experiment provides a new insight into the relationship between…
• These results should be taken into account when considering how to…
• The data contribute a clearer understanding of…
• While previous research has focused on  x , these results demonstrate that y .

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Even the best research has its limitations. Acknowledging these is important to demonstrate your credibility. Limitations aren’t about listing your errors, but about providing an accurate picture of what can and cannot be concluded from your study.

Limitations might be due to your overall research design, specific methodological choices , or unanticipated obstacles that emerged during your research process.

Here are a few common possibilities:

• If your sample size was small or limited to a specific group of people, explain how generalizability is limited.
• If you encountered problems when gathering or analyzing data, explain how these influenced the results.
• If there are potential confounding variables that you were unable to control, acknowledge the effect these may have had.

After noting the limitations, you can reiterate why the results are nonetheless valid for the purpose of answering your research question.

• The generalizability of the results is limited by…
• The reliability of these data is impacted by…
• Due to the lack of data on x , the results cannot confirm…
• The methodological choices were constrained by…
• It is beyond the scope of this study to…

Based on the discussion of your results, you can make recommendations for practical implementation or further research. Sometimes, the recommendations are saved for the conclusion .

Suggestions for further research can lead directly from the limitations. Don’t just state that more studies should be done—give concrete ideas for how future work can build on areas that your own research was unable to address.

• Further research is needed to establish…
• Future studies should take into account…
• Avenues for future research include…

If you want to know more about AI for academic writing, AI tools, or research bias, make sure to check out some of our other articles with explanations and examples or go directly to our tools!

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In the discussion , you explore the meaning and relevance of your research results , explaining how they fit with existing research and theory. Discuss:

• Your  interpretations : what do the results tell us?
• The  implications : why do the results matter?
• The  limitation s : what can’t the results tell us?

The results chapter or section simply and objectively reports what you found, without speculating on why you found these results. The discussion interprets the meaning of the results, puts them in context, and explains why they matter.

In qualitative research , results and discussion are sometimes combined. But in quantitative research , it’s considered important to separate the objective results from your interpretation of them.

In a thesis or dissertation, the discussion is an in-depth exploration of the results, going into detail about the meaning of your findings and citing relevant sources to put them in context.

The conclusion is more shorter and more general: it concisely answers your main research question and makes recommendations based on your overall findings.

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How to write a literature review introduction (+ examples)

The introduction to a literature review serves as your reader’s guide through your academic work and thought process. Explore the significance of literature review introductions in review papers, academic papers, essays, theses, and dissertations. We delve into the purpose and necessity of these introductions, explore the essential components of literature review introductions, and provide step-by-step guidance on how to craft your own, along with examples.

Why you need an introduction for a literature review

In academic writing , the introduction for a literature review is an indispensable component. Effective academic writing requires proper paragraph structuring to guide your reader through your argumentation. This includes providing an introduction to your literature review.

It is imperative to remember that you should never start sharing your findings abruptly. Even if there isn’t a dedicated introduction section .

When you need an introduction for a literature review

There are three main scenarios in which you need an introduction for a literature review:

What to include in a literature review introduction

It is crucial to customize the content and depth of your literature review introduction according to the specific format of your academic work.

In practical terms, this implies, for instance, that the introduction in an academic literature review paper, especially one derived from a systematic literature review , is quite comprehensive. Particularly compared to the rather brief one or two introductory sentences that are often found at the beginning of a literature review section in a standard academic paper. The introduction to the literature review chapter in a thesis or dissertation again adheres to different standards.

Academic literature review paper

The introduction of an academic literature review paper, which does not rely on empirical data, often necessitates a more extensive introduction than the brief literature review introductions typically found in empirical papers. It should encompass:

Regular literature review section in an academic article or essay

In a standard 8000-word journal article, the literature review section typically spans between 750 and 1250 words. The first few sentences or the first paragraph within this section often serve as an introduction. It should encompass:

In some cases, you might include:

Introduction to a literature review chapter in thesis or dissertation

Some students choose to incorporate a brief introductory section at the beginning of each chapter, including the literature review chapter. Alternatively, others opt to seamlessly integrate the introduction into the initial sentences of the literature review itself. Both approaches are acceptable, provided that you incorporate the following elements:

Examples of literature review introductions

Example 1: an effective introduction for an academic literature review paper.

To begin, let’s delve into the introduction of an academic literature review paper. We will examine the paper “How does culture influence innovation? A systematic literature review”, which was published in 2018 in the journal Management Decision.

Example 2: An effective introduction to a literature review section in an academic paper

The second example represents a typical academic paper, encompassing not only a literature review section but also empirical data, a case study, and other elements. We will closely examine the introduction to the literature review section in the paper “The environmentalism of the subalterns: a case study of environmental activism in Eastern Kurdistan/Rojhelat”, which was published in 2021 in the journal Local Environment.

The paper begins with a general introduction and then proceeds to the literature review, designated by the authors as their conceptual framework. Of particular interest is the first paragraph of this conceptual framework, comprising 142 words across five sentences:

Thus, the author successfully introduces the literature review, from which point onward it dives into the main concept (‘subalternity’) of the research, and reviews the literature on socio-economic justice and environmental degradation.

Examples 3-5: Effective introductions to literature review chapters

Numerous universities offer online repositories where you can access theses and dissertations from previous years, serving as valuable sources of reference. Many of these repositories, however, may require you to log in through your university account. Nevertheless, a few open-access repositories are accessible to anyone, such as the one by the University of Manchester . It’s important to note though that copyright restrictions apply to these resources, just as they would with published papers.

Master’s thesis literature review introduction

Phd thesis literature review chapter introduction, phd thesis literature review introduction.

The last example is the doctoral thesis Metacognitive strategies and beliefs: Child correlates and early experiences Chan, K. Y. M. (Author). 31 Dec 2020 . The author clearly conducted a systematic literature review, commencing the review section with a discussion of the methodology and approach employed in locating and analyzing the selected records.

Steps to write your own literature review introduction

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• Published: 31 August 2024

Knowledge mapping and evolution of research on older adults’ technology acceptance: a bibliometric study from 2013 to 2023

• Xianru Shang   ORCID: orcid.org/0009-0000-8906-3216 1 ,
• Zijian Liu 1 ,
• Chen Gong 1 ,
• Zhigang Hu 1 ,
• Yuexuan Wu 1 &
• Chengliang Wang   ORCID: orcid.org/0000-0003-2208-3508 2  

Humanities and Social Sciences Communications volume  11 , Article number:  1115 ( 2024 ) Cite this article

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• Science, technology and society

The rapid expansion of information technology and the intensification of population aging are two prominent features of contemporary societal development. Investigating older adults’ acceptance and use of technology is key to facilitating their integration into an information-driven society. Given this context, the technology acceptance of older adults has emerged as a prioritized research topic, attracting widespread attention in the academic community. However, existing research remains fragmented and lacks a systematic framework. To address this gap, we employed bibliometric methods, utilizing the Web of Science Core Collection to conduct a comprehensive review of literature on older adults’ technology acceptance from 2013 to 2023. Utilizing VOSviewer and CiteSpace for data assessment and visualization, we created knowledge mappings of research on older adults’ technology acceptance. Our study employed multidimensional methods such as co-occurrence analysis, clustering, and burst analysis to: (1) reveal research dynamics, key journals, and domains in this field; (2) identify leading countries, their collaborative networks, and core research institutions and authors; (3) recognize the foundational knowledge system centered on theoretical model deepening, emerging technology applications, and research methods and evaluation, uncovering seminal literature and observing a shift from early theoretical and influential factor analyses to empirical studies focusing on individual factors and emerging technologies; (4) moreover, current research hotspots are primarily in the areas of factors influencing technology adoption, human-robot interaction experiences, mobile health management, and aging-in-place technology, highlighting the evolutionary context and quality distribution of research themes. Finally, we recommend that future research should deeply explore improvements in theoretical models, long-term usage, and user experience evaluation. Overall, this study presents a clear framework of existing research in the field of older adults’ technology acceptance, providing an important reference for future theoretical exploration and innovative applications.

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Smart device interest, perceived usefulness, and preferences in rural Alabama seniors

Introduction.

In contemporary society, the rapid development of information technology has been intricately intertwined with the intensifying trend of population aging. According to the latest United Nations forecast, by 2050, the global population aged 65 and above is expected to reach 1.6 billion, representing about 16% of the total global population (UN 2023 ). Given the significant challenges of global aging, there is increasing evidence that emerging technologies have significant potential to maintain health and independence for older adults in their home and healthcare environments (Barnard et al. 2013 ; Soar 2010 ; Vancea and Solé-Casals 2016 ). This includes, but is not limited to, enhancing residential safety with smart home technologies (Touqeer et al. 2021 ; Wang et al. 2022 ), improving living independence through wearable technologies (Perez et al. 2023 ), and increasing medical accessibility via telehealth services (Kruse et al. 2020 ). Technological innovations are redefining the lifestyles of older adults, encouraging a shift from passive to active participation (González et al. 2012 ; Mostaghel 2016 ). Nevertheless, the effective application and dissemination of technology still depends on user acceptance and usage intentions (Naseri et al. 2023 ; Wang et al. 2023a ; Xia et al. 2024 ; Yu et al. 2023 ). Particularly, older adults face numerous challenges in accepting and using new technologies. These challenges include not only physical and cognitive limitations but also a lack of technological experience, along with the influences of social and economic factors (Valk et al. 2018 ; Wilson et al. 2021 ).

User acceptance of technology is a significant focus within information systems (IS) research (Dai et al. 2024 ), with several models developed to explain and predict user behavior towards technology usage, including the Technology Acceptance Model (TAM) (Davis 1989 ), TAM2, TAM3, and the Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh et al. 2003 ). Older adults, as a group with unique needs, exhibit different behavioral patterns during technology acceptance than other user groups, and these uniquenesses include changes in cognitive abilities, as well as motivations, attitudes, and perceptions of the use of new technologies (Chen and Chan 2011 ). The continual expansion of technology introduces considerable challenges for older adults, rendering the understanding of their technology acceptance a research priority. Thus, conducting in-depth research into older adults’ acceptance of technology is critically important for enhancing their integration into the information society and improving their quality of life through technological advancements.

Reviewing relevant literature to identify research gaps helps further solidify the theoretical foundation of the research topic. However, many existing literature reviews primarily focus on the factors influencing older adults’ acceptance or intentions to use technology. For instance, Ma et al. ( 2021 ) conducted a comprehensive analysis of the determinants of older adults’ behavioral intentions to use technology; Liu et al. ( 2022 ) categorized key variables in studies of older adults’ technology acceptance, noting a shift in focus towards social and emotional factors; Yap et al. ( 2022 ) identified seven categories of antecedents affecting older adults’ use of technology from an analysis of 26 articles, including technological, psychological, social, personal, cost, behavioral, and environmental factors; Schroeder et al. ( 2023 ) extracted 119 influencing factors from 59 articles and further categorized these into six themes covering demographics, health status, and emotional awareness. Additionally, some studies focus on the application of specific technologies, such as Ferguson et al. ( 2021 ), who explored barriers and facilitators to older adults using wearable devices for heart monitoring, and He et al. ( 2022 ) and Baer et al. ( 2022 ), who each conducted in-depth investigations into the acceptance of social assistive robots and mobile nutrition and fitness apps, respectively. In summary, current literature reviews on older adults’ technology acceptance exhibit certain limitations. Due to the interdisciplinary nature and complex knowledge structure of this field, traditional literature reviews often rely on qualitative analysis, based on literature analysis and periodic summaries, which lack sufficient objectivity and comprehensiveness. Additionally, systematic research is relatively limited, lacking a macroscopic description of the research trajectory from a holistic perspective. Over the past decade, research on older adults’ technology acceptance has experienced rapid growth, with a significant increase in literature, necessitating the adoption of new methods to review and examine the developmental trends in this field (Chen 2006 ; Van Eck and Waltman 2010 ). Bibliometric analysis, as an effective quantitative research method, analyzes published literature through visualization, offering a viable approach to extracting patterns and insights from a large volume of papers, and has been widely applied in numerous scientific research fields (Achuthan et al. 2023 ; Liu and Duffy 2023 ). Therefore, this study will employ bibliometric methods to systematically analyze research articles related to older adults’ technology acceptance published in the Web of Science Core Collection from 2013 to 2023, aiming to understand the core issues and evolutionary trends in the field, and to provide valuable references for future related research. Specifically, this study aims to explore and answer the following questions:

RQ1: What are the research dynamics in the field of older adults’ technology acceptance over the past decade? What are the main academic journals and fields that publish studies related to older adults’ technology acceptance?

RQ2: How is the productivity in older adults’ technology acceptance research distributed among countries, institutions, and authors?

RQ3: What are the knowledge base and seminal literature in older adults’ technology acceptance research? How has the research theme progressed?

RQ4: What are the current hot topics and their evolutionary trajectories in older adults’ technology acceptance research? How is the quality of research distributed?

Methodology and materials

Research method.

In recent years, bibliometrics has become one of the crucial methods for analyzing literature reviews and is widely used in disciplinary and industrial intelligence analysis (Jing et al. 2023 ; Lin and Yu 2024a ; Wang et al. 2024a ; Xu et al. 2021 ). Bibliometric software facilitates the visualization analysis of extensive literature data, intuitively displaying the network relationships and evolutionary processes between knowledge units, and revealing the underlying knowledge structure and potential information (Chen et al. 2024 ; López-Robles et al. 2018 ; Wang et al. 2024c ). This method provides new insights into the current status and trends of specific research areas, along with quantitative evidence, thereby enhancing the objectivity and scientific validity of the research conclusions (Chen et al. 2023 ; Geng et al. 2024 ). VOSviewer and CiteSpace are two widely used bibliometric software tools in academia (Pan et al. 2018 ), recognized for their robust functionalities based on the JAVA platform. Although each has its unique features, combining these two software tools effectively constructs mapping relationships between literature knowledge units and clearly displays the macrostructure of the knowledge domains. Particularly, VOSviewer, with its excellent graphical representation capabilities, serves as an ideal tool for handling large datasets and precisely identifying the focal points and hotspots of research topics. Therefore, this study utilizes VOSviewer (version 1.6.19) and CiteSpace (version 6.1.R6), combined with in-depth literature analysis, to comprehensively examine and interpret the research theme of older adults’ technology acceptance through an integrated application of quantitative and qualitative methods.

Data source

Web of Science is a comprehensively recognized database in academia, featuring literature that has undergone rigorous peer review and editorial scrutiny (Lin and Yu 2024b ; Mongeon and Paul-Hus 2016 ; Pranckutė 2021 ). This study utilizes the Web of Science Core Collection as its data source, specifically including three major citation indices: Science Citation Index Expanded (SCIE), Social Sciences Citation Index (SSCI), and Arts & Humanities Citation Index (A&HCI). These indices encompass high-quality research literature in the fields of science, social sciences, and arts and humanities, ensuring the comprehensiveness and reliability of the data. We combined “older adults” with “technology acceptance” through thematic search, with the specific search strategy being: TS = (elder OR elderly OR aging OR ageing OR senile OR senior OR old people OR “older adult*”) AND TS = (“technology acceptance” OR “user acceptance” OR “consumer acceptance”). The time span of literature search is from 2013 to 2023, with the types limited to “Article” and “Review” and the language to “English”. Additionally, the search was completed by October 27, 2023, to avoid data discrepancies caused by database updates. The initial search yielded 764 journal articles. Given that searches often retrieve articles that are superficially relevant but actually non-compliant, manual screening post-search was essential to ensure the relevance of the literature (Chen et al. 2024 ). Through manual screening, articles significantly deviating from the research theme were eliminated and rigorously reviewed. Ultimately, this study obtained 500 valid sample articles from the Web of Science Core Collection. The complete PRISMA screening process is illustrated in Fig. 1 .

Presentation of the data culling process in detail.

Data standardization

Raw data exported from databases often contain multiple expressions of the same terminology (Nguyen and Hallinger 2020 ). To ensure the accuracy and consistency of data, it is necessary to standardize the raw data (Strotmann and Zhao 2012 ). This study follows the data standardization process proposed by Taskin and Al ( 2019 ), mainly executing the following operations:

(1) Standardization of author and institution names is conducted to address different name expressions for the same author. For instance, “Chan, Alan Hoi Shou” and “Chan, Alan H. S.” are considered the same author, and distinct authors with the same name are differentiated by adding identifiers. Diverse forms of institutional names are unified to address variations caused by name changes or abbreviations, such as standardizing “FRANKFURT UNIV APPL SCI” and “Frankfurt University of Applied Sciences,” as well as “Chinese University of Hong Kong” and “University of Hong Kong” to consistent names.

(2) Different expressions of journal names are unified. For example, “International Journal of Human-Computer Interaction” and “Int J Hum Comput Interact” are standardized to a single name. This ensures consistency in journal names and prevents misclassification of literature due to differing journal names. Additionally, it involves checking if the journals have undergone name changes in the past decade to prevent any impact on the analysis due to such changes.

(3) Keywords data are cleansed by removing words that do not directly pertain to specific research content (e.g., people, review), merging synonyms (e.g., “UX” and “User Experience,” “aging-in-place” and “aging in place”), and standardizing plural forms of keywords (e.g., “assistive technologies” and “assistive technology,” “social robots” and “social robot”). This reduces redundant information in knowledge mapping.

Bibliometric results and analysis

Distribution power (rq1), literature descriptive statistical analysis.

Table 1 presents a detailed descriptive statistical overview of the literature in the field of older adults’ technology acceptance. After deduplication using the CiteSpace software, this study confirmed a valid sample size of 500 articles. Authored by 1839 researchers, the documents encompass 792 research institutions across 54 countries and are published in 217 different academic journals. As of the search cutoff date, these articles have accumulated 13,829 citations, with an annual average of 1156 citations, and an average of 27.66 citations per article. The h-index, a composite metric of quantity and quality of scientific output (Kamrani et al. 2021 ), reached 60 in this study.

Trends in publications and disciplinary distribution

The number of publications and citations are significant indicators of the research field’s development, reflecting its continuity, attention, and impact (Ale Ebrahim et al. 2014 ). The ranking of annual publications and citations in the field of older adults’ technology acceptance studies is presented chronologically in Fig. 2A . The figure shows a clear upward trend in the amount of literature in this field. Between 2013 and 2017, the number of publications increased slowly and decreased in 2018. However, in 2019, the number of publications increased rapidly to 52 and reached a peak of 108 in 2022, which is 6.75 times higher than in 2013. In 2022, the frequency of document citations reached its highest point with 3466 citations, reflecting the widespread recognition and citation of research in this field. Moreover, the curve of the annual number of publications fits a quadratic function, with a goodness-of-fit R 2 of 0.9661, indicating that the number of future publications is expected to increase even more rapidly.

A Trends in trends in annual publications and citations (2013–2023). B Overlay analysis of the distribution of discipline fields.

Figure 2B shows that research on older adults’ technology acceptance involves the integration of multidisciplinary knowledge. According to Web of Science Categories, these 500 articles are distributed across 85 different disciplines. We have tabulated the top ten disciplines by publication volume (Table 2 ), which include Medical Informatics (75 articles, 15.00%), Health Care Sciences & Services (71 articles, 14.20%), Gerontology (61 articles, 12.20%), Public Environmental & Occupational Health (57 articles, 11.40%), and Geriatrics & Gerontology (52 articles, 10.40%), among others. The high output in these disciplines reflects the concentrated global academic interest in this comprehensive research topic. Additionally, interdisciplinary research approaches provide diverse perspectives and a solid theoretical foundation for studies on older adults’ technology acceptance, also paving the way for new research directions.

Knowledge flow analysis

A dual-map overlay is a CiteSpace map superimposed on top of a base map, which shows the interrelationships between journals in different domains, representing the publication and citation activities in each domain (Chen and Leydesdorff 2014 ). The overlay map reveals the link between the citing domain (on the left side) and the cited domain (on the right side), reflecting the knowledge flow of the discipline at the journal level (Leydesdorff and Rafols 2012 ). We utilize the in-built Z-score algorithm of the software to cluster the graph, as shown in Fig. 3 .

The left side shows the citing journal, and the right side shows the cited journal.

Figure 3 shows the distribution of citing journals clusters for older adults’ technology acceptance on the left side, while the right side refers to the main cited journals clusters. Two knowledge flow citation trajectories were obtained; they are presented by the color of the cited regions, and the thickness of these trajectories is proportional to the Z-score scaled frequency of citations (Chen et al. 2014 ). Within the cited regions, the most popular fields with the most records covered are “HEALTH, NURSING, MEDICINE” and “PSYCHOLOGY, EDUCATION, SOCIAL”, and the elliptical aspect ratio of these two fields stands out. Fields have prominent elliptical aspect ratios, highlighting their significant influence on older adults’ technology acceptance research. Additionally, the major citation trajectories originate in these two areas and progress to the frontier research area of “PSYCHOLOGY, EDUCATION, HEALTH”. It is worth noting that the citation trajectory from “PSYCHOLOGY, EDUCATION, SOCIAL” has a significant Z-value (z = 6.81), emphasizing the significance and impact of this development path. In the future, “MATHEMATICS, SYSTEMS, MATHEMATICAL”, “MOLECULAR, BIOLOGY, IMMUNOLOGY”, and “NEUROLOGY, SPORTS, OPHTHALMOLOGY” may become emerging fields. The fields of “MEDICINE, MEDICAL, CLINICAL” may be emerging areas of cutting-edge research.

Main research journals analysis

Table 3 provides statistics for the top ten journals by publication volume in the field of older adults’ technology acceptance. Together, these journals have published 137 articles, accounting for 27.40% of the total publications, indicating that there is no highly concentrated core group of journals in this field, with publications being relatively dispersed. Notably, Computers in Human Behavior , Journal of Medical Internet Research , and International Journal of Human-Computer Interaction each lead with 15 publications. In terms of citation metrics, International Journal of Medical Informatics and Computers in Human Behavior stand out significantly, with the former accumulating a total of 1,904 citations, averaging 211.56 citations per article, and the latter totaling 1,449 citations, with an average of 96.60 citations per article. These figures emphasize the academic authority and widespread impact of these journals within the research field.

Research power (RQ2)

Countries and collaborations analysis.

The analysis revealed the global research pattern for country distribution and collaboration (Chen et al. 2019 ). Figure 4A shows the network of national collaborations on older adults’ technology acceptance research. The size of the bubbles represents the amount of publications in each country, while the thickness of the connecting lines expresses the closeness of the collaboration among countries. Generally, this research subject has received extensive international attention, with China and the USA publishing far more than any other countries. China has established notable research collaborations with the USA, UK and Malaysia in this field, while other countries have collaborations, but the closeness is relatively low and scattered. Figure 4B shows the annual publication volume dynamics of the top ten countries in terms of total publications. Since 2017, China has consistently increased its annual publications, while the USA has remained relatively stable. In 2019, the volume of publications in each country increased significantly, this was largely due to the global outbreak of the COVID-19 pandemic, which has led to increased reliance on information technology among the elderly for medical consultations, online socialization, and health management (Sinha et al. 2021 ). This phenomenon has led to research advances in technology acceptance among older adults in various countries. Table 4 shows that the top ten countries account for 93.20% of the total cumulative number of publications, with each country having published more than 20 papers. Among these ten countries, all of them except China are developed countries, indicating that the research field of older adults’ technology acceptance has received general attention from developed countries. Currently, China and the USA were the leading countries in terms of publications with 111 and 104 respectively, accounting for 22.20% and 20.80%. The UK, Germany, Italy, and the Netherlands also made significant contributions. The USA and China ranked first and second in terms of the number of citations, while the Netherlands had the highest average citations, indicating the high impact and quality of its research. The UK has shown outstanding performance in international cooperation, while the USA highlights its significant academic influence in this field with the highest h-index value.

A National collaboration network. B Annual volume of publications in the top 10 countries.

Institutions and authors analysis

Analyzing the number of publications and citations can reveal an institution’s or author’s research strength and influence in a particular research area (Kwiek 2021 ). Tables 5 and 6 show the statistics of the institutions and authors whose publication counts are in the top ten, respectively. As shown in Table 5 , higher education institutions hold the main position in this research field. Among the top ten institutions, City University of Hong Kong and The University of Hong Kong from China lead with 14 and 9 publications, respectively. City University of Hong Kong has the highest h-index, highlighting its significant influence in the field. It is worth noting that Tilburg University in the Netherlands is not among the top five in terms of publications, but the high average citation count (130.14) of its literature demonstrates the high quality of its research.

After analyzing the authors’ output using Price’s Law (Redner 1998 ), the highest number of publications among the authors counted ( n  = 10) defines a publication threshold of 3 for core authors in this research area. As a result of quantitative screening, a total of 63 core authors were identified. Table 6 shows that Chen from Zhejiang University, China, Ziefle from RWTH Aachen University, Germany, and Rogers from Macquarie University, Australia, were the top three authors in terms of the number of publications, with 10, 9, and 8 articles, respectively. In terms of average citation rate, Peek and Wouters, both scholars from the Netherlands, have significantly higher rates than other scholars, with 183.2 and 152.67 respectively. This suggests that their research is of high quality and widely recognized. Additionally, Chen and Rogers have high h-indices in this field.

Knowledge base and theme progress (RQ3)

Research knowledge base.

Co-citation relationships occur when two documents are cited together (Zhang and Zhu 2022 ). Co-citation mapping uses references as nodes to represent the knowledge base of a subject area (Min et al. 2021). Figure 5A illustrates co-occurrence mapping in older adults’ technology acceptance research, where larger nodes signify higher co-citation frequencies. Co-citation cluster analysis can be used to explore knowledge structure and research boundaries (Hota et al. 2020 ; Shiau et al. 2023 ). The co-citation clustering mapping of older adults’ technology acceptance research literature (Fig. 5B ) shows that the Q value of the clustering result is 0.8129 (>0.3), and the average value of the weight S is 0.9391 (>0.7), indicating that the clusters are uniformly distributed with a significant and credible structure. This further proves that the boundaries of the research field are clear and there is significant differentiation in the field. The figure features 18 cluster labels, each associated with thematic color blocks corresponding to different time slices. Highlighted emerging research themes include #2 Smart Home Technology, #7 Social Live, and #10 Customer Service. Furthermore, the clustering labels extracted are primarily classified into three categories: theoretical model deepening, emerging technology applications, research methods and evaluation, as detailed in Table 7 .

A Co-citation analysis of references. B Clustering network analysis of references.

Seminal literature analysis

The top ten nodes in terms of co-citation frequency were selected for further analysis. Table 8 displays the corresponding node information. Studies were categorized into four main groups based on content analysis. (1) Research focusing on specific technology usage by older adults includes studies by Peek et al. ( 2014 ), Ma et al. ( 2016 ), Hoque and Sorwar ( 2017 ), and Li et al. ( 2019 ), who investigated the factors influencing the use of e-technology, smartphones, mHealth, and smart wearables, respectively. (2) Concerning the development of theoretical models of technology acceptance, Chen and Chan ( 2014 ) introduced the Senior Technology Acceptance Model (STAM), and Macedo ( 2017 ) analyzed the predictive power of UTAUT2 in explaining older adults’ intentional behaviors and information technology usage. (3) In exploring older adults’ information technology adoption and behavior, Lee and Coughlin ( 2015 ) emphasized that the adoption of technology by older adults is a multifactorial process that includes performance, price, value, usability, affordability, accessibility, technical support, social support, emotion, independence, experience, and confidence. Yusif et al. ( 2016 ) conducted a literature review examining the key barriers affecting older adults’ adoption of assistive technology, including factors such as privacy, trust, functionality/added value, cost, and stigma. (4) From the perspective of research into older adults’ technology acceptance, Mitzner et al. ( 2019 ) assessed the long-term usage of computer systems designed for the elderly, whereas Guner and Acarturk ( 2020 ) compared information technology usage and acceptance between older and younger adults. The breadth and prevalence of this literature make it a vital reference for researchers in the field, also providing new perspectives and inspiration for future research directions.

Research thematic progress

Burst citation is a node of literature that guides the sudden change in dosage, which usually represents a prominent development or major change in a particular field, with innovative and forward-looking qualities. By analyzing the emergent literature, it is often easy to understand the dynamics of the subject area, mapping the emerging thematic change (Chen et al. 2022 ). Figure 6 shows the burst citation mapping in the field of older adults’ technology acceptance research, with burst citations represented by red nodes (Fig. 6A ). For the ten papers with the highest burst intensity (Fig. 6B ), this study will conduct further analysis in conjunction with literature review.

A Burst detection of co-citation. B The top 10 references with the strongest citation bursts.

As shown in Fig. 6 , Mitzner et al. ( 2010 ) broke the stereotype that older adults are fearful of technology, found that they actually have positive attitudes toward technology, and emphasized the centrality of ease of use and usefulness in the process of technology acceptance. This finding provides an important foundation for subsequent research. During the same period, Wagner et al. ( 2010 ) conducted theory-deepening and applied research on technology acceptance among older adults. The research focused on older adults’ interactions with computers from the perspective of Social Cognitive Theory (SCT). This expanded the understanding of technology acceptance, particularly regarding the relationship between behavior, environment, and other SCT elements. In addition, Pan and Jordan-Marsh ( 2010 ) extended the TAM to examine the interactions among predictors of perceived usefulness, perceived ease of use, subjective norm, and convenience conditions when older adults use the Internet, taking into account the moderating roles of gender and age. Heerink et al. ( 2010 ) adapted and extended the UTAUT, constructed a technology acceptance model specifically designed for older users’ acceptance of assistive social agents, and validated it using controlled experiments and longitudinal data, explaining intention to use by combining functional assessment and social interaction variables.

Then the research theme shifted to an in-depth analysis of the factors influencing technology acceptance among older adults. Two papers with high burst strengths emerged during this period: Peek et al. ( 2014 ) (Strength = 12.04), Chen and Chan ( 2014 ) (Strength = 9.81). Through a systematic literature review and empirical study, Peek STM and Chen K, among others, identified multidimensional factors that influence older adults’ technology acceptance. Peek et al. ( 2014 ) analyzed literature on the acceptance of in-home care technology among older adults and identified six factors that influence their acceptance: concerns about technology, expected benefits, technology needs, technology alternatives, social influences, and older adult characteristics, with a focus on differences between pre- and post-implementation factors. Chen and Chan ( 2014 ) constructed the STAM by administering a questionnaire to 1012 older adults and adding eight important factors, including technology anxiety, self-efficacy, cognitive ability, and physical function, based on the TAM. This enriches the theoretical foundation of the field. In addition, Braun ( 2013 ) highlighted the role of perceived usefulness, trust in social networks, and frequency of Internet use in older adults’ use of social networks, while ease of use and social pressure were not significant influences. These findings contribute to the study of older adults’ technology acceptance within specific technology application domains.

Recent research has focused on empirical studies of personal factors and emerging technologies. Ma et al. ( 2016 ) identified key personal factors affecting smartphone acceptance among older adults through structured questionnaires and face-to-face interviews with 120 participants. The study found that cost, self-satisfaction, and convenience were important factors influencing perceived usefulness and ease of use. This study offers empirical evidence to comprehend the main factors that drive smartphone acceptance among Chinese older adults. Additionally, Yusif et al. ( 2016 ) presented an overview of the obstacles that hinder older adults’ acceptance of assistive technologies, focusing on privacy, trust, and functionality.

In summary, research on older adults’ technology acceptance has shifted from early theoretical deepening and analysis of influencing factors to empirical studies in the areas of personal factors and emerging technologies, which have greatly enriched the theoretical basis of older adults’ technology acceptance and provided practical guidance for the design of emerging technology products.

Research hotspots, evolutionary trends, and quality distribution (RQ4)

Core keywords analysis.

Keywords concise the main idea and core of the literature, and are a refined summary of the research content (Huang et al. 2021 ). In CiteSpace, nodes with a centrality value greater than 0.1 are considered to be critical nodes. Analyzing keywords with high frequency and centrality helps to visualize the hot topics in the research field (Park et al. 2018 ). The merged keywords were imported into CiteSpace, and the top 10 keywords were counted and sorted by frequency and centrality respectively, as shown in Table 9 . The results show that the keyword “TAM” has the highest frequency (92), followed by “UTAUT” (24), which reflects that the in-depth study of the existing technology acceptance model and its theoretical expansion occupy a central position in research related to older adults’ technology acceptance. Furthermore, the terms ‘assistive technology’ and ‘virtual reality’ are both high-frequency and high-centrality terms (frequency = 17, centrality = 0.10), indicating that the research on assistive technology and virtual reality for older adults is the focus of current academic attention.

Research hotspots analysis

Using VOSviewer for keyword co-occurrence analysis organizes keywords into groups or clusters based on their intrinsic connections and frequencies, clearly highlighting the research field’s hot topics. The connectivity among keywords reveals correlations between different topics. To ensure accuracy, the analysis only considered the authors’ keywords. Subsequently, the keywords were filtered by setting the keyword frequency to 5 to obtain the keyword clustering map of the research on older adults’ technology acceptance research keyword clustering mapping (Fig. 7 ), combined with the keyword co-occurrence clustering network (Fig. 7A ) and the corresponding density situation (Fig. 7B ) to make a detailed analysis of the following four groups of clustered themes.

A Co-occurrence clustering network. B Keyword density.

Cluster #1—Research on the factors influencing technology adoption among older adults is a prominent topic, covering age, gender, self-efficacy, attitude, and and intention to use (Berkowsky et al. 2017 ; Wang et al. 2017 ). It also examined older adults’ attitudes towards and acceptance of digital health technologies (Ahmad and Mozelius, 2022 ). Moreover, the COVID-19 pandemic, significantly impacting older adults’ technology attitudes and usage, has underscored the study’s importance and urgency. Therefore, it is crucial to conduct in-depth studies on how older adults accept, adopt, and effectively use new technologies, to address their needs and help them overcome the digital divide within digital inclusion. This will improve their quality of life and healthcare experiences.

Cluster #2—Research focuses on how older adults interact with assistive technologies, especially assistive robots and health monitoring devices, emphasizing trust, usability, and user experience as crucial factors (Halim et al. 2022 ). Moreover, health monitoring technologies effectively track and manage health issues common in older adults, like dementia and mild cognitive impairment (Lussier et al. 2018 ; Piau et al. 2019 ). Interactive exercise games and virtual reality have been deployed to encourage more physical and cognitive engagement among older adults (Campo-Prieto et al. 2021 ). Personalized and innovative technology significantly enhances older adults’ participation, improving their health and well-being.

Cluster #3—Optimizing health management for older adults using mobile technology. With the development of mobile health (mHealth) and health information technology, mobile applications, smartphones, and smart wearable devices have become effective tools to help older users better manage chronic conditions, conduct real-time health monitoring, and even receive telehealth services (Dupuis and Tsotsos 2018 ; Olmedo-Aguirre et al. 2022 ; Kim et al. 2014 ). Additionally, these technologies can mitigate the problem of healthcare resource inequality, especially in developing countries. Older adults’ acceptance and use of these technologies are significantly influenced by their behavioral intentions, motivational factors, and self-management skills. These internal motivational factors, along with external factors, jointly affect older adults’ performance in health management and quality of life.

Cluster #4—Research on technology-assisted home care for older adults is gaining popularity. Environmentally assisted living enhances older adults’ independence and comfort at home, offering essential support and security. This has a crucial impact on promoting healthy aging (Friesen et al. 2016 ; Wahlroos et al. 2023 ). The smart home is a core application in this field, providing a range of solutions that facilitate independent living for the elderly in a highly integrated and user-friendly manner. This fulfills different dimensions of living and health needs (Majumder et al. 2017 ). Moreover, eHealth offers accurate and personalized health management and healthcare services for older adults (Delmastro et al. 2018 ), ensuring their needs are met at home. Research in this field often employs qualitative methods and structural equation modeling to fully understand older adults’ needs and experiences at home and analyze factors influencing technology adoption.

Evolutionary trends analysis

To gain a deeper understanding of the evolutionary trends in research hotspots within the field of older adults’ technology acceptance, we conducted a statistical analysis of the average appearance times of keywords, using CiteSpace to generate the time-zone evolution mapping (Fig. 8 ) and burst keywords. The time-zone mapping visually displays the evolution of keywords over time, intuitively reflecting the frequency and initial appearance of keywords in research, commonly used to identify trends in research topics (Jing et al. 2024a ; Kumar et al. 2021 ). Table 10 lists the top 15 keywords by burst strength, with the red sections indicating high-frequency citations and their burst strength in specific years. These burst keywords reveal the focus and trends of research themes over different periods (Kleinberg 2002 ). Combining insights from the time-zone mapping and burst keywords provides more objective and accurate research insights (Wang et al. 2023b ).

Reflecting the frequency and time of first appearance of keywords in the study.

An integrated analysis of Fig. 8 and Table 10 shows that early research on older adults’ technology acceptance primarily focused on factors such as perceived usefulness, ease of use, and attitudes towards information technology, including their use of computers and the internet (Pan and Jordan-Marsh 2010 ), as well as differences in technology use between older adults and other age groups (Guner and Acarturk 2020 ). Subsequently, the research focus expanded to improving the quality of life for older adults, exploring how technology can optimize health management and enhance the possibility of independent living, emphasizing the significant role of technology in improving the quality of life for the elderly. With ongoing technological advancements, recent research has shifted towards areas such as “virtual reality,” “telehealth,” and “human-robot interaction,” with a focus on the user experience of older adults (Halim et al. 2022 ). The appearance of keywords such as “physical activity” and “exercise” highlights the value of technology in promoting physical activity and health among older adults. This phase of research tends to make cutting-edge technology genuinely serve the practical needs of older adults, achieving its widespread application in daily life. Additionally, research has focused on expanding and quantifying theoretical models of older adults’ technology acceptance, involving keywords such as “perceived risk”, “validation” and “UTAUT”.

In summary, from 2013 to 2023, the field of older adults’ technology acceptance has evolved from initial explorations of influencing factors, to comprehensive enhancements in quality of life and health management, and further to the application and deepening of theoretical models and cutting-edge technologies. This research not only reflects the diversity and complexity of the field but also demonstrates a comprehensive and in-depth understanding of older adults’ interactions with technology across various life scenarios and needs.

Research quality distribution

To reveal the distribution of research quality in the field of older adults’ technology acceptance, a strategic diagram analysis is employed to calculate and illustrate the internal development and interrelationships among various research themes (Xie et al. 2020 ). The strategic diagram uses Centrality as the X-axis and Density as the Y-axis to divide into four quadrants, where the X-axis represents the strength of the connection between thematic clusters and other themes, with higher values indicating a central position in the research field; the Y-axis indicates the level of development within the thematic clusters, with higher values denoting a more mature and widely recognized field (Li and Zhou 2020 ).

Through cluster analysis and manual verification, this study categorized 61 core keywords (Frequency ≥5) into 11 thematic clusters. Subsequently, based on the keywords covered by each thematic cluster, the research themes and their directions for each cluster were summarized (Table 11 ), and the centrality and density coordinates for each cluster were precisely calculated (Table 12 ). Finally, a strategic diagram of the older adults’ technology acceptance research field was constructed (Fig. 9 ). Based on the distribution of thematic clusters across the quadrants in the strategic diagram, the structure and developmental trends of the field were interpreted.

Classification and visualization of theme clusters based on density and centrality.

As illustrated in Fig. 9 , (1) the theme clusters of #3 Usage Experience and #4 Assisted Living Technology are in the first quadrant, characterized by high centrality and density. Their internal cohesion and close links with other themes indicate their mature development, systematic research content or directions have been formed, and they have a significant influence on other themes. These themes play a central role in the field of older adults’ technology acceptance and have promising prospects. (2) The theme clusters of #6 Smart Devices, #9 Theoretical Models, and #10 Mobile Health Applications are in the second quadrant, with higher density but lower centrality. These themes have strong internal connections but weaker external links, indicating that these three themes have received widespread attention from researchers and have been the subject of related research, but more as self-contained systems and exhibit independence. Therefore, future research should further explore in-depth cooperation and cross-application with other themes. (3) The theme clusters of #7 Human-Robot Interaction, #8 Characteristics of the Elderly, and #11 Research Methods are in the third quadrant, with lower centrality and density. These themes are loosely connected internally and have weak links with others, indicating their developmental immaturity. Compared to other topics, they belong to the lower attention edge and niche themes, and there is a need for further investigation. (4) The theme clusters of #1 Digital Healthcare Technology, #2 Psychological Factors, and #5 Socio-Cultural Factors are located in the fourth quadrant, with high centrality but low density. Although closely associated with other research themes, the internal cohesion within these clusters is relatively weak. This suggests that while these themes are closely linked to other research areas, their own development remains underdeveloped, indicating a core immaturity. Nevertheless, these themes are crucial within the research domain of elderly technology acceptance and possess significant potential for future exploration.

Discussion on distribution power (RQ1)

Over the past decade, academic interest and influence in the area of older adults’ technology acceptance have significantly increased. This trend is evidenced by a quantitative analysis of publication and citation volumes, particularly noticeable in 2019 and 2022, where there was a substantial rise in both metrics. The rise is closely linked to the widespread adoption of emerging technologies such as smart homes, wearable devices, and telemedicine among older adults. While these technologies have enhanced their quality of life, they also pose numerous challenges, sparking extensive research into their acceptance, usage behaviors, and influencing factors among the older adults (Pirzada et al. 2022 ; Garcia Reyes et al. 2023 ). Furthermore, the COVID-19 pandemic led to a surge in technology demand among older adults, especially in areas like medical consultation, online socialization, and health management, further highlighting the importance and challenges of technology. Health risks and social isolation have compelled older adults to rely on technology for daily activities, accelerating its adoption and application within this demographic. This phenomenon has made technology acceptance a critical issue, driving societal and academic focus on the study of technology acceptance among older adults.

The flow of knowledge at the level of high-output disciplines and journals, along with the primary publishing outlets, indicates the highly interdisciplinary nature of research into older adults’ technology acceptance. This reflects the complexity and breadth of issues related to older adults’ technology acceptance, necessitating the integration of multidisciplinary knowledge and approaches. Currently, research is primarily focused on medical health and human-computer interaction, demonstrating academic interest in improving health and quality of life for older adults and addressing the urgent needs related to their interactions with technology. In the field of medical health, research aims to provide advanced and innovative healthcare technologies and services to meet the challenges of an aging population while improving the quality of life for older adults (Abdi et al. 2020 ; Wilson et al. 2021 ). In the field of human-computer interaction, research is focused on developing smarter and more user-friendly interaction models to meet the needs of older adults in the digital age, enabling them to actively participate in social activities and enjoy a higher quality of life (Sayago, 2019 ). These studies are crucial for addressing the challenges faced by aging societies, providing increased support and opportunities for the health, welfare, and social participation of older adults.

Discussion on research power (RQ2)

This study analyzes leading countries and collaboration networks, core institutions and authors, revealing the global research landscape and distribution of research strength in the field of older adults’ technology acceptance, and presents quantitative data on global research trends. From the analysis of country distribution and collaborations, China and the USA hold dominant positions in this field, with developed countries like the UK, Germany, Italy, and the Netherlands also excelling in international cooperation and research influence. The significant investment in technological research and the focus on the technological needs of older adults by many developed countries reflect their rapidly aging societies, policy support, and resource allocation.

China is the only developing country that has become a major contributor in this field, indicating its growing research capabilities and high priority given to aging societies and technological innovation. Additionally, China has close collaborations with countries such as USA, the UK, and Malaysia, driven not only by technological research needs but also by shared challenges and complementarities in aging issues among these nations. For instance, the UK has extensive experience in social welfare and aging research, providing valuable theoretical guidance and practical experience. International collaborations, aimed at addressing the challenges of aging, integrate the strengths of various countries, advancing in-depth and widespread development in the research of technology acceptance among older adults.

At the institutional and author level, City University of Hong Kong leads in publication volume, with research teams led by Chan and Chen demonstrating significant academic activity and contributions. Their research primarily focuses on older adults’ acceptance and usage behaviors of various technologies, including smartphones, smart wearables, and social robots (Chen et al. 2015 ; Li et al. 2019 ; Ma et al. 2016 ). These studies, targeting specific needs and product characteristics of older adults, have developed new models of technology acceptance based on existing frameworks, enhancing the integration of these technologies into their daily lives and laying a foundation for further advancements in the field. Although Tilburg University has a smaller publication output, it holds significant influence in the field of older adults’ technology acceptance. Particularly, the high citation rate of Peek’s studies highlights their excellence in research. Peek extensively explored older adults’ acceptance and usage of home care technologies, revealing the complexity and dynamics of their technology use behaviors. His research spans from identifying systemic influencing factors (Peek et al. 2014 ; Peek et al. 2016 ), emphasizing familial impacts (Luijkx et al. 2015 ), to constructing comprehensive models (Peek et al. 2017 ), and examining the dynamics of long-term usage (Peek et al. 2019 ), fully reflecting the evolving technology landscape and the changing needs of older adults. Additionally, the ongoing contributions of researchers like Ziefle, Rogers, and Wouters in the field of older adults’ technology acceptance demonstrate their research influence and leadership. These researchers have significantly enriched the knowledge base in this area with their diverse perspectives. For instance, Ziefle has uncovered the complex attitudes of older adults towards technology usage, especially the trade-offs between privacy and security, and how different types of activities affect their privacy needs (Maidhof et al. 2023 ; Mujirishvili et al. 2023 ; Schomakers and Ziefle 2023 ; Wilkowska et al. 2022 ), reflecting a deep exploration and ongoing innovation in the field of older adults’ technology acceptance.

Discussion on knowledge base and thematic progress (RQ3)

Through co-citation analysis and systematic review of seminal literature, this study reveals the knowledge foundation and thematic progress in the field of older adults’ technology acceptance. Co-citation networks and cluster analyses illustrate the structural themes of the research, delineating the differentiation and boundaries within this field. Additionally, burst detection analysis offers a valuable perspective for understanding the thematic evolution in the field of technology acceptance among older adults. The development and innovation of theoretical models are foundational to this research. Researchers enhance the explanatory power of constructed models by deepening and expanding existing technology acceptance theories to address theoretical limitations. For instance, Heerink et al. ( 2010 ) modified and expanded the UTAUT model by integrating functional assessment and social interaction variables to create the almere model. This model significantly enhances the ability to explain the intentions of older users in utilizing assistive social agents and improves the explanation of actual usage behaviors. Additionally, Chen and Chan ( 2014 ) extended the TAM to include age-related health and capability features of older adults, creating the STAM, which substantially improves predictions of older adults’ technology usage behaviors. Personal attributes, health and capability features, and facilitating conditions have a direct impact on technology acceptance. These factors more effectively predict older adults’ technology usage behaviors than traditional attitudinal factors.

With the advancement of technology and the application of emerging technologies, new research topics have emerged, increasingly focusing on older adults’ acceptance and use of these technologies. Prior to this, the study by Mitzner et al. ( 2010 ) challenged the stereotype of older adults’ conservative attitudes towards technology, highlighting the central roles of usability and usefulness in the technology acceptance process. This discovery laid an important foundation for subsequent research. Research fields such as “smart home technology,” “social life,” and “customer service” are emerging, indicating a shift in focus towards the practical and social applications of technology in older adults’ lives. Research not only focuses on the technology itself but also on how these technologies integrate into older adults’ daily lives and how they can improve the quality of life through technology. For instance, studies such as those by Ma et al. ( 2016 ), Hoque and Sorwar ( 2017 ), and Li et al. ( 2019 ) have explored factors influencing older adults’ use of smartphones, mHealth, and smart wearable devices.

Furthermore, the diversification of research methodologies and innovation in evaluation techniques, such as the use of mixed methods, structural equation modeling (SEM), and neural network (NN) approaches, have enhanced the rigor and reliability of the findings, enabling more precise identification of the factors and mechanisms influencing technology acceptance. Talukder et al. ( 2020 ) employed an effective multimethodological strategy by integrating SEM and NN to leverage the complementary strengths of both approaches, thus overcoming their individual limitations and more accurately analyzing and predicting older adults’ acceptance of wearable health technologies (WHT). SEM is utilized to assess the determinants’ impact on the adoption of WHT, while neural network models validate SEM outcomes and predict the significance of key determinants. This combined approach not only boosts the models’ reliability and explanatory power but also provides a nuanced understanding of the motivations and barriers behind older adults’ acceptance of WHT, offering deep research insights.

Overall, co-citation analysis of the literature in the field of older adults’ technology acceptance has uncovered deeper theoretical modeling and empirical studies on emerging technologies, while emphasizing the importance of research methodological and evaluation innovations in understanding complex social science issues. These findings are crucial for guiding the design and marketing strategies of future technology products, especially in the rapidly growing market of older adults.

Discussion on research hotspots and evolutionary trends (RQ4)

By analyzing core keywords, we can gain deep insights into the hot topics, evolutionary trends, and quality distribution of research in the field of older adults’ technology acceptance. The frequent occurrence of the keywords “TAM” and “UTAUT” indicates that the applicability and theoretical extension of existing technology acceptance models among older adults remain a focal point in academia. This phenomenon underscores the enduring influence of the studies by Davis ( 1989 ) and Venkatesh et al. ( 2003 ), whose models provide a robust theoretical framework for explaining and predicting older adults’ acceptance and usage of emerging technologies. With the widespread application of artificial intelligence (AI) and big data technologies, these theoretical models have incorporated new variables such as perceived risk, trust, and privacy issues (Amin et al. 2024 ; Chen et al. 2024 ; Jing et al. 2024b ; Seibert et al. 2021 ; Wang et al. 2024b ), advancing the theoretical depth and empirical research in this field.

Keyword co-occurrence cluster analysis has revealed multiple research hotspots in the field, including factors influencing technology adoption, interactive experiences between older adults and assistive technologies, the application of mobile health technology in health management, and technology-assisted home care. These studies primarily focus on enhancing the quality of life and health management of older adults through emerging technologies, particularly in the areas of ambient assisted living, smart health monitoring, and intelligent medical care. In these domains, the role of AI technology is increasingly significant (Qian et al. 2021 ; Ho 2020 ). With the evolution of next-generation information technologies, AI is increasingly integrated into elder care systems, offering intelligent, efficient, and personalized service solutions by analyzing the lifestyles and health conditions of older adults. This integration aims to enhance older adults’ quality of life in aspects such as health monitoring and alerts, rehabilitation assistance, daily health management, and emotional support (Lee et al. 2023 ). A survey indicates that 83% of older adults prefer AI-driven solutions when selecting smart products, demonstrating the increasing acceptance of AI in elder care (Zhao and Li 2024 ). Integrating AI into elder care presents both opportunities and challenges, particularly in terms of user acceptance, trust, and long-term usage effects, which warrant further exploration (Mhlanga 2023 ). These studies will help better understand the profound impact of AI technology on the lifestyles of older adults and provide critical references for optimizing AI-driven elder care services.

The Time-zone evolution mapping and burst keyword analysis further reveal the evolutionary trends of research hotspots. Early studies focused on basic technology acceptance models and user perceptions, later expanding to include quality of life and health management. In recent years, research has increasingly focused on cutting-edge technologies such as virtual reality, telehealth, and human-robot interaction, with a concurrent emphasis on the user experience of older adults. This evolutionary process demonstrates a deepening shift from theoretical models to practical applications, underscoring the significant role of technology in enhancing the quality of life for older adults. Furthermore, the strategic coordinate mapping analysis clearly demonstrates the development and mutual influence of different research themes. High centrality and density in the themes of Usage Experience and Assisted Living Technology indicate their mature research status and significant impact on other themes. The themes of Smart Devices, Theoretical Models, and Mobile Health Applications demonstrate self-contained research trends. The themes of Human-Robot Interaction, Characteristics of the Elderly, and Research Methods are not yet mature, but they hold potential for development. Themes of Digital Healthcare Technology, Psychological Factors, and Socio-Cultural Factors are closely related to other themes, displaying core immaturity but significant potential.

In summary, the research hotspots in the field of older adults’ technology acceptance are diverse and dynamic, demonstrating the academic community’s profound understanding of how older adults interact with technology across various life contexts and needs. Under the influence of AI and big data, research should continue to focus on the application of emerging technologies among older adults, exploring in depth how they adapt to and effectively use these technologies. This not only enhances the quality of life and healthcare experiences for older adults but also drives ongoing innovation and development in this field.

Research agenda

Based on the above research findings, to further understand and promote technology acceptance and usage among older adults, we recommend future studies focus on refining theoretical models, exploring long-term usage, and assessing user experience in the following detailed aspects:

Refinement and validation of specific technology acceptance models for older adults: Future research should focus on developing and validating technology acceptance models based on individual characteristics, particularly considering variations in technology acceptance among older adults across different educational levels and cultural backgrounds. This includes factors such as age, gender, educational background, and cultural differences. Additionally, research should examine how well specific technologies, such as wearable devices and mobile health applications, meet the needs of older adults. Building on existing theoretical models, this research should integrate insights from multiple disciplines such as psychology, sociology, design, and engineering through interdisciplinary collaboration to create more accurate and comprehensive models, which should then be validated in relevant contexts.

Deepening the exploration of the relationship between long-term technology use and quality of life among older adults: The acceptance and use of technology by users is a complex and dynamic process (Seuwou et al. 2016 ). Existing research predominantly focuses on older adults’ initial acceptance or short-term use of new technologies; however, the impact of long-term use on their quality of life and health is more significant. Future research should focus on the evolution of older adults’ experiences and needs during long-term technology usage, and the enduring effects of technology on their social interactions, mental health, and life satisfaction. Through longitudinal studies and qualitative analysis, this research reveals the specific needs and challenges of older adults in long-term technology use, providing a basis for developing technologies and strategies that better meet their requirements. This understanding aids in comprehensively assessing the impact of technology on older adults’ quality of life and guiding the optimization and improvement of technological products.

Evaluating the Importance of User Experience in Research on Older Adults’ Technology Acceptance: Understanding the mechanisms of information technology acceptance and use is central to human-computer interaction research. Although technology acceptance models and user experience models differ in objectives, they share many potential intersections. Technology acceptance research focuses on structured prediction and assessment, while user experience research concentrates on interpreting design impacts and new frameworks. Integrating user experience to assess older adults’ acceptance of technology products and systems is crucial (Codfrey et al. 2022 ; Wang et al. 2019 ), particularly for older users, where specific product designs should emphasize practicality and usability (Fisk et al. 2020 ). Researchers need to explore innovative age-appropriate design methods to enhance older adults’ usage experience. This includes studying older users’ actual usage preferences and behaviors, optimizing user interfaces, and interaction designs. Integrating feedback from older adults to tailor products to their needs can further promote their acceptance and continued use of technology products.

Conclusions

This study conducted a systematic review of the literature on older adults’ technology acceptance over the past decade through bibliometric analysis, focusing on the distribution power, research power, knowledge base and theme progress, research hotspots, evolutionary trends, and quality distribution. Using a combination of quantitative and qualitative methods, this study has reached the following conclusions:

Technology acceptance among older adults has become a hot topic in the international academic community, involving the integration of knowledge across multiple disciplines, including Medical Informatics, Health Care Sciences Services, and Ergonomics. In terms of journals, “PSYCHOLOGY, EDUCATION, HEALTH” represents a leading field, with key publications including Computers in Human Behavior , Journal of Medical Internet Research , and International Journal of Human-Computer Interaction . These journals possess significant academic authority and extensive influence in the field.

Research on technology acceptance among older adults is particularly active in developed countries, with China and USA publishing significantly more than other nations. The Netherlands leads in high average citation rates, indicating the depth and impact of its research. Meanwhile, the UK stands out in terms of international collaboration. At the institutional level, City University of Hong Kong and The University of Hong Kong in China are in leading positions. Tilburg University in the Netherlands demonstrates exceptional research quality through its high average citation count. At the author level, Chen from China has the highest number of publications, while Peek from the Netherlands has the highest average citation count.

Co-citation analysis of references indicates that the knowledge base in this field is divided into three main categories: theoretical model deepening, emerging technology applications, and research methods and evaluation. Seminal literature focuses on four areas: specific technology use by older adults, expansion of theoretical models of technology acceptance, information technology adoption behavior, and research perspectives. Research themes have evolved from initial theoretical deepening and analysis of influencing factors to empirical studies on individual factors and emerging technologies.

Keyword analysis indicates that TAM and UTAUT are the most frequently occurring terms, while “assistive technology” and “virtual reality” are focal points with high frequency and centrality. Keyword clustering analysis reveals that research hotspots are concentrated on the influencing factors of technology adoption, human-robot interaction experiences, mobile health management, and technology for aging in place. Time-zone evolution mapping and burst keyword analysis have revealed the research evolution from preliminary exploration of influencing factors, to enhancements in quality of life and health management, and onto advanced technology applications and deepening of theoretical models. Furthermore, analysis of research quality distribution indicates that Usage Experience and Assisted Living Technology have become core topics, while Smart Devices, Theoretical Models, and Mobile Health Applications point towards future research directions.

Through this study, we have systematically reviewed the dynamics, core issues, and evolutionary trends in the field of older adults’ technology acceptance, constructing a comprehensive Knowledge Mapping of the domain and presenting a clear framework of existing research. This not only lays the foundation for subsequent theoretical discussions and innovative applications in the field but also provides an important reference for relevant scholars.

Limitations

To our knowledge, this is the first bibliometric analysis concerning technology acceptance among older adults, and we adhered strictly to bibliometric standards throughout our research. However, this study relies on the Web of Science Core Collection, and while its authority and breadth are widely recognized, this choice may have missed relevant literature published in other significant databases such as PubMed, Scopus, and Google Scholar, potentially overlooking some critical academic contributions. Moreover, given that our analysis was confined to literature in English, it may not reflect studies published in other languages, somewhat limiting the global representativeness of our data sample.

It is noteworthy that with the rapid development of AI technology, its increasingly widespread application in elderly care services is significantly transforming traditional care models. AI is profoundly altering the lifestyles of the elderly, from health monitoring and smart diagnostics to intelligent home systems and personalized care, significantly enhancing their quality of life and health care standards. The potential for AI technology within the elderly population is immense, and research in this area is rapidly expanding. However, due to the restrictive nature of the search terms used in this study, it did not fully cover research in this critical area, particularly in addressing key issues such as trust, privacy, and ethics.

Consequently, future research should not only expand data sources, incorporating multilingual and multidatabase literature, but also particularly focus on exploring older adults’ acceptance of AI technology and its applications, in order to construct a more comprehensive academic landscape of older adults’ technology acceptance, thereby enriching and extending the knowledge system and academic trends in this field.

Data availability

The datasets analyzed during the current study are available in the Dataverse repository: https://doi.org/10.7910/DVN/6K0GJH .

Abdi S, de Witte L, Hawley M (2020) Emerging technologies with potential care and support applications for older people: review of gray literature. JMIR Aging 3(2):e17286. https://doi.org/10.2196/17286

Article   PubMed   PubMed Central   Google Scholar  

Achuthan K, Nair VK, Kowalski R, Ramanathan S, Raman R (2023) Cyberbullying research—Alignment to sustainable development and impact of COVID-19: Bibliometrics and science mapping analysis. Comput Human Behav 140:107566. https://doi.org/10.1016/j.chb.2022.107566

Article   Google Scholar  

Ahmad A, Mozelius P (2022) Human-Computer Interaction for Older Adults: a Literature Review on Technology Acceptance of eHealth Systems. J Eng Res Sci 1(4):119–126. https://doi.org/10.55708/js0104014

Ale Ebrahim N, Salehi H, Embi MA, Habibi F, Gholizadeh H, Motahar SM (2014) Visibility and citation impact. Int Educ Stud 7(4):120–125. https://doi.org/10.5539/ies.v7n4p120

Amin MS, Johnson VL, Prybutok V, Koh CE (2024) An investigation into factors affecting the willingness to disclose personal health information when using AI-enabled caregiver robots. Ind Manag Data Syst 124(4):1677–1699. https://doi.org/10.1108/IMDS-09-2023-0608

Baer NR, Vietzke J, Schenk L (2022) Middle-aged and older adults’ acceptance of mobile nutrition and fitness apps: a systematic mixed studies review. PLoS One 17(12):e0278879. https://doi.org/10.1371/journal.pone.0278879

Barnard Y, Bradley MD, Hodgson F, Lloyd AD (2013) Learning to use new technologies by older adults: Perceived difficulties, experimentation behaviour and usability. Comput Human Behav 29(4):1715–1724. https://doi.org/10.1016/j.chb.2013.02.006

Berkowsky RW, Sharit J, Czaja SJ (2017) Factors predicting decisions about technology adoption among older adults. Innov Aging 3(1):igy002. https://doi.org/10.1093/geroni/igy002

Braun MT (2013) Obstacles to social networking website use among older adults. Comput Human Behav 29(3):673–680. https://doi.org/10.1016/j.chb.2012.12.004

Article   MathSciNet   Google Scholar  

Campo-Prieto P, Rodríguez-Fuentes G, Cancela-Carral JM (2021) Immersive virtual reality exergame promotes the practice of physical activity in older people: An opportunity during COVID-19. Multimodal Technol Interact 5(9):52. https://doi.org/10.3390/mti5090052

Chen C (2006) CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature. J Am Soc Inf Sci Technol 57(3):359–377. https://doi.org/10.1002/asi.20317

Chen C, Dubin R, Kim MC (2014) Emerging trends and new developments in regenerative medicine: a scientometric update (2000–2014). Expert Opin Biol Ther 14(9):1295–1317. https://doi.org/10.1517/14712598.2014.920813

Article   PubMed   Google Scholar  

Chen C, Leydesdorff L (2014) Patterns of connections and movements in dual‐map overlays: A new method of publication portfolio analysis. J Assoc Inf Sci Technol 65(2):334–351. https://doi.org/10.1002/asi.22968

Chen J, Wang C, Tang Y (2022) Knowledge mapping of volunteer motivation: A bibliometric analysis and cross-cultural comparative study. Front Psychol 13:883150. https://doi.org/10.3389/fpsyg.2022.883150

Chen JY, Liu YD, Dai J, Wang CL (2023) Development and status of moral education research: Visual analysis based on knowledge graph. Front Psychol 13:1079955. https://doi.org/10.3389/fpsyg.2022.1079955

Chen K, Chan AH (2011) A review of technology acceptance by older adults. Gerontechnology 10(1):1–12. https://doi.org/10.4017/gt.2011.10.01.006.00

Chen K, Chan AH (2014) Gerontechnology acceptance by elderly Hong Kong Chinese: a senior technology acceptance model (STAM). Ergonomics 57(5):635–652. https://doi.org/10.1080/00140139.2014.895855

Chen K, Zhang Y, Fu X (2019) International research collaboration: An emerging domain of innovation studies? Res Policy 48(1):149–168. https://doi.org/10.1016/j.respol.2018.08.005

Chen X, Hu Z, Wang C (2024) Empowering education development through AIGC: A systematic literature review. Educ Inf Technol 1–53. https://doi.org/10.1007/s10639-024-12549-7

Chen Y, Chen CM, Liu ZY, Hu ZG, Wang XW (2015) The methodology function of CiteSpace mapping knowledge domains. Stud Sci Sci 33(2):242–253. https://doi.org/10.16192/j.cnki.1003-2053.2015.02.009

Codfrey GS, Baharum A, Zain NHM, Omar M, Deris FD (2022) User Experience in Product Design and Development: Perspectives and Strategies. Math Stat Eng Appl 71(2):257–262. https://doi.org/10.17762/msea.v71i2.83

Dai J, Zhang X, Wang CL (2024) A meta-analysis of learners’ continuance intention toward online education platforms. Educ Inf Technol 1–36. https://doi.org/10.1007/s10639-024-12654-7

Davis FD (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q 13(3):319–340. https://doi.org/10.2307/249008

Delmastro F, Dolciotti C, Palumbo F, Magrini M, Di Martino F, La Rosa D, Barcaro U (2018) Long-term care: how to improve the quality of life with mobile and e-health services. In 2018 14th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), pp. 12–19. IEEE. https://doi.org/10.1109/WiMOB.2018.8589157

Dupuis K, Tsotsos LE (2018) Technology for remote health monitoring in an older population: a role for mobile devices. Multimodal Technol Interact 2(3):43. https://doi.org/10.3390/mti2030043

Ferguson C, Hickman LD, Turkmani S, Breen P, Gargiulo G, Inglis SC (2021) Wearables only work on patients that wear them”: Barriers and facilitators to the adoption of wearable cardiac monitoring technologies. Cardiovasc Digit Health J 2(2):137–147. https://doi.org/10.1016/j.cvdhj.2021.02.001

Fisk AD, Czaja SJ, Rogers WA, Charness N, Sharit J (2020) Designing for older adults: Principles and creative human factors approaches. CRC Press. https://doi.org/10.1201/9781420080681

Friesen S, Brémault-Phillips S, Rudrum L, Rogers LG (2016) Environmental design that supports healthy aging: Evaluating a new supportive living facility. J Hous Elderly 30(1):18–34. https://doi.org/10.1080/02763893.2015.1129380

Garcia Reyes EP, Kelly R, Buchanan G, Waycott J (2023) Understanding Older Adults’ Experiences With Technologies for Health Self-management: Interview Study. JMIR Aging 6:e43197. https://doi.org/10.2196/43197

Geng Z, Wang J, Liu J, Miao J (2024) Bibliometric analysis of the development, current status, and trends in adult degenerative scoliosis research: A systematic review from 1998 to 2023. J Pain Res 17:153–169. https://doi.org/10.2147/JPR.S437575

González A, Ramírez MP, Viadel V (2012) Attitudes of the elderly toward information and communications technologies. Educ Gerontol 38(9):585–594. https://doi.org/10.1080/03601277.2011.595314

Guner H, Acarturk C (2020) The use and acceptance of ICT by senior citizens: a comparison of technology acceptance model (TAM) for elderly and young adults. Univ Access Inf Soc 19(2):311–330. https://doi.org/10.1007/s10209-018-0642-4

Halim I, Saptari A, Perumal PA, Abdullah Z, Abdullah S, Muhammad MN (2022) A Review on Usability and User Experience of Assistive Social Robots for Older Persons. Int J Integr Eng 14(6):102–124. https://penerbit.uthm.edu.my/ojs/index.php/ijie/article/view/8566

He Y, He Q, Liu Q (2022) Technology acceptance in socially assistive robots: Scoping review of models, measurement, and influencing factors. J Healthc Eng 2022(1):6334732. https://doi.org/10.1155/2022/6334732

Heerink M, Kröse B, Evers V, Wielinga B (2010) Assessing acceptance of assistive social agent technology by older adults: the almere model. Int J Soc Robot 2:361–375. https://doi.org/10.1007/s12369-010-0068-5

Ho A (2020) Are we ready for artificial intelligence health monitoring in elder care? BMC Geriatr 20(1):358. https://doi.org/10.1186/s12877-020-01764-9

Hoque R, Sorwar G (2017) Understanding factors influencing the adoption of mHealth by the elderly: An extension of the UTAUT model. Int J Med Inform 101:75–84. https://doi.org/10.1016/j.ijmedinf.2017.02.002

Hota PK, Subramanian B, Narayanamurthy G (2020) Mapping the intellectual structure of social entrepreneurship research: A citation/co-citation analysis. J Bus Ethics 166(1):89–114. https://doi.org/10.1007/s10551-019-04129-4

Huang R, Yan P, Yang X (2021) Knowledge map visualization of technology hotspots and development trends in China’s textile manufacturing industry. IET Collab Intell Manuf 3(3):243–251. https://doi.org/10.1049/cim2.12024

Article   ADS   Google Scholar  

Jing Y, Wang C, Chen Y, Wang H, Yu T, Shadiev R (2023) Bibliometric mapping techniques in educational technology research: A systematic literature review. Educ Inf Technol 1–29. https://doi.org/10.1007/s10639-023-12178-6

Jing YH, Wang CL, Chen ZY, Shen SS, Shadiev R (2024a) A Bibliometric Analysis of Studies on Technology-Supported Learning Environments: Hotopics and Frontier Evolution. J Comput Assist Learn 1–16. https://doi.org/10.1111/jcal.12934

Jing YH, Wang HM, Chen XJ, Wang CL (2024b) What factors will affect the effectiveness of using ChatGPT to solve programming problems? A quasi-experimental study. Humanit Soc Sci Commun 11:319. https://doi.org/10.1057/s41599-024-02751-w

Kamrani P, Dorsch I, Stock WG (2021) Do researchers know what the h-index is? And how do they estimate its importance? Scientometrics 126(7):5489–5508. https://doi.org/10.1007/s11192-021-03968-1

Kim HS, Lee KH, Kim H, Kim JH (2014) Using mobile phones in healthcare management for the elderly. Maturitas 79(4):381–388. https://doi.org/10.1016/j.maturitas.2014.08.013

Article   MathSciNet   PubMed   Google Scholar  

Kleinberg J (2002) Bursty and hierarchical structure in streams. In Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 91–101. https://doi.org/10.1145/775047.775061

Kruse C, Fohn J, Wilson N, Patlan EN, Zipp S, Mileski M (2020) Utilization barriers and medical outcomes commensurate with the use of telehealth among older adults: systematic review. JMIR Med Inform 8(8):e20359. https://doi.org/10.2196/20359

Kumar S, Lim WM, Pandey N, Christopher Westland J (2021) 20 years of electronic commerce research. Electron Commer Res 21:1–40. https://doi.org/10.1007/s10660-021-09464-1

Kwiek M (2021) What large-scale publication and citation data tell us about international research collaboration in Europe: Changing national patterns in global contexts. Stud High Educ 46(12):2629–2649. https://doi.org/10.1080/03075079.2020.1749254

Lee C, Coughlin JF (2015) PERSPECTIVE: Older adults’ adoption of technology: an integrated approach to identifying determinants and barriers. J Prod Innov Manag 32(5):747–759. https://doi.org/10.1111/jpim.12176

Lee CH, Wang C, Fan X, Li F, Chen CH (2023) Artificial intelligence-enabled digital transformation in elderly healthcare field: scoping review. Adv Eng Inform 55:101874. https://doi.org/10.1016/j.aei.2023.101874

Leydesdorff L, Rafols I (2012) Interactive overlays: A new method for generating global journal maps from Web-of-Science data. J Informetr 6(2):318–332. https://doi.org/10.1016/j.joi.2011.11.003

Li J, Ma Q, Chan AH, Man S (2019) Health monitoring through wearable technologies for older adults: Smart wearables acceptance model. Appl Ergon 75:162–169. https://doi.org/10.1016/j.apergo.2018.10.006

Article   ADS   PubMed   Google Scholar  

Li X, Zhou D (2020) Product design requirement information visualization approach for intelligent manufacturing services. China Mech Eng 31(07):871, http://www.cmemo.org.cn/EN/Y2020/V31/I07/871

Google Scholar  

Lin Y, Yu Z (2024a) An integrated bibliometric analysis and systematic review modelling students’ technostress in higher education. Behav Inf Technol 1–25. https://doi.org/10.1080/0144929X.2024.2332458

Lin Y, Yu Z (2024b) A bibliometric analysis of artificial intelligence chatbots in educational contexts. Interact Technol Smart Educ 21(2):189–213. https://doi.org/10.1108/ITSE-12-2022-0165

Liu L, Duffy VG (2023) Exploring the future development of Artificial Intelligence (AI) applications in chatbots: a bibliometric analysis. Int J Soc Robot 15(5):703–716. https://doi.org/10.1007/s12369-022-00956-0

Liu R, Li X, Chu J (2022) Evolution of applied variables in the research on technology acceptance of the elderly. In: International Conference on Human-Computer Interaction, Cham: Springer International Publishing, pp 500–520. https://doi.org/10.1007/978-3-031-05581-23_5

Luijkx K, Peek S, Wouters E (2015) “Grandma, you should do it—It’s cool” Older Adults and the Role of Family Members in Their Acceptance of Technology. Int J Environ Res Public Health 12(12):15470–15485. https://doi.org/10.3390/ijerph121214999

Lussier M, Lavoie M, Giroux S, Consel C, Guay M, Macoir J, Bier N (2018) Early detection of mild cognitive impairment with in-home monitoring sensor technologies using functional measures: a systematic review. IEEE J Biomed Health Inform 23(2):838–847. https://doi.org/10.1109/JBHI.2018.2834317

López-Robles JR, Otegi-Olaso JR, Porto Gomez I, Gamboa-Rosales NK, Gamboa-Rosales H, Robles-Berumen H (2018) Bibliometric network analysis to identify the intellectual structure and evolution of the big data research field. In: International Conference on Intelligent Data Engineering and Automated Learning, Cham: Springer International Publishing, pp 113–120. https://doi.org/10.1007/978-3-030-03496-2_13

Ma Q, Chan AH, Chen K (2016) Personal and other factors affecting acceptance of smartphone technology by older Chinese adults. Appl Ergon 54:62–71. https://doi.org/10.1016/j.apergo.2015.11.015

Ma Q, Chan AHS, Teh PL (2021) Insights into Older Adults’ Technology Acceptance through Meta-Analysis. Int J Hum-Comput Interact 37(11):1049–1062. https://doi.org/10.1080/10447318.2020.1865005

Macedo IM (2017) Predicting the acceptance and use of information and communication technology by older adults: An empirical examination of the revised UTAUT2. Comput Human Behav 75:935–948. https://doi.org/10.1016/j.chb.2017.06.013

Maidhof C, Offermann J, Ziefle M (2023) Eyes on privacy: acceptance of video-based AAL impacted by activities being filmed. Front Public Health 11:1186944. https://doi.org/10.3389/fpubh.2023.1186944

Majumder S, Aghayi E, Noferesti M, Memarzadeh-Tehran H, Mondal T, Pang Z, Deen MJ (2017) Smart homes for elderly healthcare—Recent advances and research challenges. Sensors 17(11):2496. https://doi.org/10.3390/s17112496

Article   ADS   PubMed   PubMed Central   Google Scholar  

Mhlanga D (2023) Artificial Intelligence in elderly care: Navigating ethical and responsible AI adoption for seniors. Available at SSRN 4675564. 4675564 min) Identifying citation patterns of scientific breakthroughs: A perspective of dynamic citation process. Inf Process Manag 58(1):102428. https://doi.org/10.1016/j.ipm.2020.102428

Mitzner TL, Boron JB, Fausset CB, Adams AE, Charness N, Czaja SJ, Sharit J (2010) Older adults talk technology: Technology usage and attitudes. Comput Human Behav 26(6):1710–1721. https://doi.org/10.1016/j.chb.2010.06.020

Mitzner TL, Savla J, Boot WR, Sharit J, Charness N, Czaja SJ, Rogers WA (2019) Technology adoption by older adults: Findings from the PRISM trial. Gerontologist 59(1):34–44. https://doi.org/10.1093/geront/gny113

Mongeon P, Paul-Hus A (2016) The journal coverage of Web of Science and Scopus: a comparative analysis. Scientometrics 106:213–228. https://doi.org/10.1007/s11192-015-1765-5

Mostaghel R (2016) Innovation and technology for the elderly: Systematic literature review. J Bus Res 69(11):4896–4900. https://doi.org/10.1016/j.jbusres.2016.04.049

Mujirishvili T, Maidhof C, Florez-Revuelta F, Ziefle M, Richart-Martinez M, Cabrero-García J (2023) Acceptance and privacy perceptions toward video-based active and assisted living technologies: Scoping review. J Med Internet Res 25:e45297. https://doi.org/10.2196/45297

Naseri RNN, Azis SN, Abas N (2023) A Review of Technology Acceptance and Adoption Models in Consumer Study. FIRM J Manage Stud 8(2):188–199. https://doi.org/10.33021/firm.v8i2.4536

Nguyen UP, Hallinger P (2020) Assessing the distinctive contributions of Simulation & Gaming to the literature, 1970–2019: A bibliometric review. Simul Gaming 51(6):744–769. https://doi.org/10.1177/1046878120941569

Olmedo-Aguirre JO, Reyes-Campos J, Alor-Hernández G, Machorro-Cano I, Rodríguez-Mazahua L, Sánchez-Cervantes JL (2022) Remote healthcare for elderly people using wearables: A review. Biosensors 12(2):73. https://doi.org/10.3390/bios12020073

Pan S, Jordan-Marsh M (2010) Internet use intention and adoption among Chinese older adults: From the expanded technology acceptance model perspective. Comput Human Behav 26(5):1111–1119. https://doi.org/10.1016/j.chb.2010.03.015

Pan X, Yan E, Cui M, Hua W (2018) Examining the usage, citation, and diffusion patterns of bibliometric map software: A comparative study of three tools. J Informetr 12(2):481–493. https://doi.org/10.1016/j.joi.2018.03.005

Park JS, Kim NR, Han EJ (2018) Analysis of trends in science and technology using keyword network analysis. J Korea Ind Inf Syst Res 23(2):63–73. https://doi.org/10.9723/jksiis.2018.23.2.063

Peek ST, Luijkx KG, Rijnaard MD, Nieboer ME, Van Der Voort CS, Aarts S, Wouters EJ (2016) Older adults’ reasons for using technology while aging in place. Gerontology 62(2):226–237. https://doi.org/10.1159/000430949

Peek ST, Luijkx KG, Vrijhoef HJ, Nieboer ME, Aarts S, van der Voort CS, Wouters EJ (2017) Origins and consequences of technology acquirement by independent-living seniors: Towards an integrative model. BMC Geriatr 17:1–18. https://doi.org/10.1186/s12877-017-0582-5

Peek ST, Wouters EJ, Van Hoof J, Luijkx KG, Boeije HR, Vrijhoef HJ (2014) Factors influencing acceptance of technology for aging in place: a systematic review. Int J Med Inform 83(4):235–248. https://doi.org/10.1016/j.ijmedinf.2014.01.004

Peek STM, Luijkx KG, Vrijhoef HJM, Nieboer ME, Aarts S, Van Der Voort CS, Wouters EJM (2019) Understanding changes and stability in the long-term use of technologies by seniors who are aging in place: a dynamical framework. BMC Geriatr 19:1–13. https://doi.org/10.1186/s12877-019-1241-9

Perez AJ, Siddiqui F, Zeadally S, Lane D (2023) A review of IoT systems to enable independence for the elderly and disabled individuals. Internet Things 21:100653. https://doi.org/10.1016/j.iot.2022.100653

Piau A, Wild K, Mattek N, Kaye J (2019) Current state of digital biomarker technologies for real-life, home-based monitoring of cognitive function for mild cognitive impairment to mild Alzheimer disease and implications for clinical care: systematic review. J Med Internet Res 21(8):e12785. https://doi.org/10.2196/12785

Pirzada P, Wilde A, Doherty GH, Harris-Birtill D (2022) Ethics and acceptance of smart homes for older adults. Inform Health Soc Care 47(1):10–37. https://doi.org/10.1080/17538157.2021.1923500

Pranckutė R (2021) Web of Science (WoS) and Scopus: The titans of bibliographic information in today’s academic world. Publications 9(1):12. https://doi.org/10.3390/publications9010012

Qian K, Zhang Z, Yamamoto Y, Schuller BW (2021) Artificial intelligence internet of things for the elderly: From assisted living to health-care monitoring. IEEE Signal Process Mag 38(4):78–88. https://doi.org/10.1109/MSP.2021.3057298

Redner S (1998) How popular is your paper? An empirical study of the citation distribution. Eur Phys J B-Condens Matter Complex Syst 4(2):131–134. https://doi.org/10.1007/s100510050359

Sayago S (ed.) (2019) Perspectives on human-computer interaction research with older people. Switzerland: Springer International Publishing. https://doi.org/10.1007/978-3-030-06076-3

Schomakers EM, Ziefle M (2023) Privacy vs. security: trade-offs in the acceptance of smart technologies for aging-in-place. Int J Hum Comput Interact 39(5):1043–1058. https://doi.org/10.1080/10447318.2022.2078463

Schroeder T, Dodds L, Georgiou A, Gewald H, Siette J (2023) Older adults and new technology: Mapping review of the factors associated with older adults’ intention to adopt digital technologies. JMIR Aging 6(1):e44564. https://doi.org/10.2196/44564

Seibert K, Domhoff D, Bruch D, Schulte-Althoff M, Fürstenau D, Biessmann F, Wolf-Ostermann K (2021) Application scenarios for artificial intelligence in nursing care: rapid review. J Med Internet Res 23(11):e26522. https://doi.org/10.2196/26522

Seuwou P, Banissi E, Ubakanma G (2016) User acceptance of information technology: A critical review of technology acceptance models and the decision to invest in Information Security. In: Global Security, Safety and Sustainability-The Security Challenges of the Connected World: 11th International Conference, ICGS3 2017, London, UK, January 18-20, 2017, Proceedings 11:230-251. Springer International Publishing. https://doi.org/10.1007/978-3-319-51064-4_19

Shiau WL, Wang X, Zheng F (2023) What are the trend and core knowledge of information security? A citation and co-citation analysis. Inf Manag 60(3):103774. https://doi.org/10.1016/j.im.2023.103774

Sinha S, Verma A, Tiwari P (2021) Technology: Saving and enriching life during COVID-19. Front Psychol 12:647681. https://doi.org/10.3389/fpsyg.2021.647681

Soar J (2010) The potential of information and communication technologies to support ageing and independent living. Ann Telecommun 65:479–483. https://doi.org/10.1007/s12243-010-0167-1

Strotmann A, Zhao D (2012) Author name disambiguation: What difference does it make in author‐based citation analysis? J Am Soc Inf Sci Technol 63(9):1820–1833. https://doi.org/10.1002/asi.22695

Talukder MS, Sorwar G, Bao Y, Ahmed JU, Palash MAS (2020) Predicting antecedents of wearable healthcare technology acceptance by elderly: A combined SEM-Neural Network approach. Technol Forecast Soc Change 150:119793. https://doi.org/10.1016/j.techfore.2019.119793

Taskin Z, Al U (2019) Natural language processing applications in library and information science. Online Inf Rev 43(4):676–690. https://doi.org/10.1108/oir-07-2018-0217

Touqeer H, Zaman S, Amin R, Hussain M, Al-Turjman F, Bilal M (2021) Smart home security: challenges, issues and solutions at different IoT layers. J Supercomput 77(12):14053–14089. https://doi.org/10.1007/s11227-021-03825-1

United Nations Department of Economic and Social Affairs (2023) World population ageing 2023: Highlights. https://www.un.org/zh/193220

Valk CAL, Lu Y, Randriambelonoro M, Jessen J (2018) Designing for technology acceptance of wearable and mobile technologies for senior citizen users. In: 21st DMI: Academic Design Management Conference (ADMC 2018), Design Management Institute, pp 1361–1373. https://www.dmi.org/page/ADMC2018

Van Eck N, Waltman L (2010) Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics 84(2):523–538. https://doi.org/10.1007/s11192-009-0146-3

Vancea M, Solé-Casals J (2016) Population aging in the European Information Societies: towards a comprehensive research agenda in eHealth innovations for elderly. Aging Dis 7(4):526. https://doi.org/10.14336/AD.2015.1214

Venkatesh V, Morris MG, Davis GB, Davis FD (2003) User acceptance of information technology: Toward a unified view. MIS Q 27(3):425–478. https://doi.org/10.2307/30036540

Wagner N, Hassanein K, Head M (2010) Computer use by older adults: A multi-disciplinary review. Comput Human Behav 26(5):870–882. https://doi.org/10.1016/j.chb.2010.03.029

Wahlroos N, Narsakka N, Stolt M, Suhonen R (2023) Physical environment maintaining independence and self-management of older people in long-term care settings—An integrative literature review. J Aging Environ 37(3):295–313. https://doi.org/10.1080/26892618.2022.2092927

Wang CL, Chen XJ, Yu T, Liu YD, Jing YH (2024a) Education reform and change driven by digital technology: a bibliometric study from a global perspective. Humanit Soc Sci Commun 11(1):1–17. https://doi.org/10.1057/s41599-024-02717-y

Wang CL, Dai J, Zhu KK, Yu T, Gu XQ (2023a) Understanding the Continuance Intention of College Students Toward New E-learning Spaces Based on an Integrated Model of the TAM and TTF. Int J Hum-comput Int 1–14. https://doi.org/10.1080/10447318.2023.2291609

Wang CL, Wang HM, Li YY, Dai J, Gu XQ, Yu T (2024b) Factors Influencing University Students’ Behavioral Intention to Use Generative Artificial Intelligence: Integrating the Theory of Planned Behavior and AI Literacy. Int J Hum-comput Int 1–23. https://doi.org/10.1080/10447318.2024.2383033

Wang J, Zhao W, Zhang Z, Liu X, Xie T, Wang L, Zhang Y (2024c) A journey of challenges and victories: a bibliometric worldview of nanomedicine since the 21st century. Adv Mater 36(15):2308915. https://doi.org/10.1002/adma.202308915

Wang J, Chen Y, Huo S, Mai L, Jia F (2023b) Research hotspots and trends of social robot interaction design: A bibliometric analysis. Sensors 23(23):9369. https://doi.org/10.3390/s23239369

Wang KH, Chen G, Chen HG (2017) A model of technology adoption by older adults. Soc Behav Personal 45(4):563–572. https://doi.org/10.2224/sbp.5778

Wang S, Bolling K, Mao W, Reichstadt J, Jeste D, Kim HC, Nebeker C (2019) Technology to Support Aging in Place: Older Adults’ Perspectives. Healthcare 7(2):60. https://doi.org/10.3390/healthcare7020060

Wang Z, Liu D, Sun Y, Pang X, Sun P, Lin F, Ren K (2022) A survey on IoT-enabled home automation systems: Attacks and defenses. IEEE Commun Surv Tutor 24(4):2292–2328. https://doi.org/10.1109/COMST.2022.3201557

Wilkowska W, Offermann J, Spinsante S, Poli A, Ziefle M (2022) Analyzing technology acceptance and perception of privacy in ambient assisted living for using sensor-based technologies. PloS One 17(7):e0269642. https://doi.org/10.1371/journal.pone.0269642

Wilson J, Heinsch M, Betts D, Booth D, Kay-Lambkin F (2021) Barriers and facilitators to the use of e-health by older adults: a scoping review. BMC Public Health 21:1–12. https://doi.org/10.1186/s12889-021-11623-w

Xia YQ, Deng YL, Tao XY, Zhang SN, Wang CL (2024) Digital art exhibitions and psychological well-being in Chinese Generation Z: An analysis based on the S-O-R framework. Humanit Soc Sci Commun 11:266. https://doi.org/10.1057/s41599-024-02718-x

Xie H, Zhang Y, Duan K (2020) Evolutionary overview of urban expansion based on bibliometric analysis in Web of Science from 1990 to 2019. Habitat Int 95:102100. https://doi.org/10.1016/j.habitatint.2019.10210

Xu Z, Ge Z, Wang X, Skare M (2021) Bibliometric analysis of technology adoption literature published from 1997 to 2020. Technol Forecast Soc Change 170:120896. https://doi.org/10.1016/j.techfore.2021.120896

Yap YY, Tan SH, Choon SW (2022) Elderly’s intention to use technologies: a systematic literature review. Heliyon 8(1). https://doi.org/10.1016/j.heliyon.2022.e08765

Yu T, Dai J, Wang CL (2023) Adoption of blended learning: Chinese university students’ perspectives. Humanit Soc Sci Commun 10:390. https://doi.org/10.1057/s41599-023-01904-7

Yusif S, Soar J, Hafeez-Baig A (2016) Older people, assistive technologies, and the barriers to adoption: A systematic review. Int J Med Inform 94:112–116. https://doi.org/10.1016/j.ijmedinf.2016.07.004

Zhang J, Zhu L (2022) Citation recommendation using semantic representation of cited papers’ relations and content. Expert Syst Appl 187:115826. https://doi.org/10.1016/j.eswa.2021.115826

Zhao Y, Li J (2024) Opportunities and challenges of integrating artificial intelligence in China’s elderly care services. Sci Rep 14(1):9254. https://doi.org/10.1038/s41598-024-60067-w

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This research was supported by the Social Science Foundation of Shaanxi Province in China (Grant No. 2023J014).

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Shang, X., Liu, Z., Gong, C. et al. Knowledge mapping and evolution of research on older adults’ technology acceptance: a bibliometric study from 2013 to 2023. Humanit Soc Sci Commun 11 , 1115 (2024). https://doi.org/10.1057/s41599-024-03658-2

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Title: multimodal methods for analyzing learning and training environments: a systematic literature review.

Abstract: Recent technological advancements have enhanced our ability to collect and analyze rich multimodal data (e.g., speech, video, and eye gaze) to better inform learning and training experiences. While previous reviews have focused on parts of the multimodal pipeline (e.g., conceptual models and data fusion), a comprehensive literature review on the methods informing multimodal learning and training environments has not been conducted. This literature review provides an in-depth analysis of research methods in these environments, proposing a taxonomy and framework that encapsulates recent methodological advances in this field and characterizes the multimodal domain in terms of five modality groups: Natural Language, Video, Sensors, Human-Centered, and Environment Logs. We introduce a novel data fusion category -- mid fusion -- and a graph-based technique for refining literature reviews, termed citation graph pruning. Our analysis reveals that leveraging multiple modalities offers a more holistic understanding of the behaviors and outcomes of learners and trainees. Even when multimodality does not enhance predictive accuracy, it often uncovers patterns that contextualize and elucidate unimodal data, revealing subtleties that a single modality may miss. However, there remains a need for further research to bridge the divide between multimodal learning and training studies and foundational AI research.

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Impacts of pfas exposure on neurodevelopment: a comprehensive literature review.

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• Morris-Rosendahl, D.J.; Crocq, M.A. Neurodevelopmental disorders—The history and future of a diagnostic concept. Dialogues Clin. Neurosci. 2020 , 22 , 65–72. [ Google Scholar ] [ CrossRef ]
• Graf, W.D.; Kekatpure, M.V.; Kosofsky, B.E. Prenatal-onset neurodevelopmental disorders secondary to toxins, nutritional deficiencies, and maternal illness. Handb. Clin. Neurol. 2013 , 111 , 143–159. [ Google Scholar ]
• Ijomone, O.M.; Olung, N.F.; Akingbade, G.T.; Okoh, C.O.A.; Aschner, M. Environmental influence on neurodevelopmental disorders: Potential association of heavy metal exposure and autism. J. Trace Elem. Med. Biol. 2020 , 62 , 126638. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Landrigan, P.J.; Lambertini, L.; Birnbaum, L.S. A research strategy to discover the environmental causes of autism and neurodevelopmental disabilities. Environ. Health Perspect. 2012 , 120 , a258–a260. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Grandjean, P.; Landrigan, P.J. Developmental neurotoxicity of industrial chemicals. Lancet 2006 , 368 , 2167–2178. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Giordano, G.; Costa, L.G. Developmental neurotoxicity: Some old and new issues. ISRN Toxicol. 2012 , 2012 , 814795. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Makris, S.L.; Raffaele, K.; Allen, S.; Bowers, W.J.; Hass, U.; Alleva, E.; Calamandrei, G.; Sheets, L.; Amcoff, P.; Delrue, N.; et al. A retrospective performance assessment of the developmental neurotoxicity study in support of OECD test guideline 426. Environ. Health Perspect. 2009 , 117 , 17–25. [ Google Scholar ] [ CrossRef ]
• Panieri, E.; Baralic, K.; Djukic-Cosic, D.; Buha Djordjevic, A.; Saso, L. PFAS Molecules: A Major Concern for the Human Health and the Environment. Toxics 2022 , 10 , 44. [ Google Scholar ] [ CrossRef ]
• Di Nisio, A.; Pannella, M.; Vogiatzis, S.; Sut, S.; Dall’Acqua, S.; Santa Rocca, M.; Antonini, A.; Porzionato, A.; De Caro, R.; Bortolozzi, M.; et al. Toni and C. Foresta. Impairment of human dopaminergic neurons at different developmental stages by perfluoro-octanoic acid (PFOA) and differential human brain areas accumulation of perfluoroalkyl chemicals. Environ. Int. 2022 , 158 , 106982. [ Google Scholar ] [ CrossRef ]
• Sunderland, E.M.; Hu, X.C.; Dassuncao, C.; Tokranov, A.K.; Wagner, C.C.; Allen, J.G. A review of the pathways of human exposure to poly- and perfluoroalkyl substances (PFASs) and present understanding of health effects. J. Expo. Sci. Environ. Epidemiol. 2019 , 29 , 131–147. [ Google Scholar ] [ CrossRef ]
• Spratlen, M.J.; Perera, F.P.; Lederman, S.A.; Rauh, V.A.; Robinson, M.; Kannan, K.; Trasande, L.; Herbstman, J. The association between prenatal exposure to perfluoroalkyl substances and childhood neurodevelopment. Environ. Pollut. 2020 , 263 Pt B , 114444. [ Google Scholar ] [ CrossRef ]
• Trudel, D.; Horowitz, L.; Wormuth, M.; Scheringer, M.; Cousins, I.T.; Hungerbühler, K. Estimating consumer exposure to PFOS and PFOA. Risk Anal. 2008 , 28 , 251–269. [ Google Scholar ] [ CrossRef ]
• Death, C.; Bell, C.; Champness, D.; Milne, C.; Reichman, S.; Hagen, T. Per-and polyfluoroalkyl substances (PFAS) in livestock and game species: A review. Sci. Total Environ. 2021 , 774 , 144795. [ Google Scholar ] [ CrossRef ]
• Ericson, I.M.; Nadal, B.; van Bavel, G.; Lindstrom, J.L. Domingo. Levels of perfluorochemicals in water samples from Catalonia, Spain: Is drinking water a significant contribution to human exposure? Environ. Sci. Pollut. Res. Int. 2008 , 15 , 614–619. [ Google Scholar ] [ CrossRef ]
• Banzhaf, S.; Filipovic, M.; Lewis, J.; Sparrenbom, C.J.; Barthel, R. A review of contamination of surface-, ground-, and drinking water in Sweden by perfluoroalkyl and polyfluoroalkyl substances (PFASs). Ambio 2017 , 46 , 335–346. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Domingo, J.L.; Nadal, M. Human exposure to per- and polyfluoroalkyl substances (PFAS) through drinking water: A review of the recent scientific literature. Environ. Res. 2019 , 177 , 108648. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Cousins, I.T.; DeWitt, J.C.; Glüge, J.; Goldenman, G.; Herzke, D.; Lohmann, R.; Ng, C.A.; Scheringer, M.; Wang, Z. The high persistence of PFAS is sufficient for their management as a chemical class. Environ. Sci. Process. Impacts 2020 , 22 , 2307–2312. [ Google Scholar ] [ CrossRef ]
• Cui, Q.; Pan, Y.; Wang, J.; Liu, H.; Yao, B.; Dai, J. Exposure to per- and polyfluoroalkyl substances (PFASs) in serum versus semen and their association with male reproductive hormones. Environ. Pollut. 2020 , 266 Pt 2 , 115330. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Gardener, H.; Sun, Q.; Grandjean, P. PFAS concentration during pregnancy in relation to cardiometabolic health and birth outcomes. Environ. Res. 2021 , 192 , 110287. [ Google Scholar ] [ CrossRef ]
• Stein, C.R.; McGovern, K.J.; Pajak, A.M.; Maglione, P.J.; Wolff, M.S. Perfluoroalkyl and polyfluoroalkyl substances and indicators of immune function in children aged 12–19 y: National Health and Nutrition Examination Survey. Pediatr. Res. 2016 , 79 , 348–357. [ Google Scholar ] [ CrossRef ]
• Papadopoulou, E.; Stratakis, N.; Basagaña, X.; Brantsæter, A.L.; Casas, M.; Fossati, S.; Gražulevičienė, R.; Haug, L.S.; Heude, B.; Maitre, L.; et al. Prenatal and postnatal exposure to PFAS and cardiometabolic factors and inflammation status in children from six European cohorts. Environ. Int. 2021 , 157 , 106853. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Alderete, T.L.; Jin, R.; Walker, D.I.; Valvi, D.; Chen, Z.; Jones, D.P.; Peng, C.; Gilliland, F.D.; Berhane, K.; Conti, D.V.; et al. Perfluoroalkyl substances, metabolomic profiling, and alterations in glucose homeostasis among overweight and obese Hispanic children: A proof-of-concept analysis. Environ. Int. 2019 , 126 , 445–453. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Chen, Z.; Yang, T.; Walker, D.I.; Thomas, D.C.; Qiu, C.; Chatzi, L.; Alderete, T.L.; Kim, J.S.; Conti, D.V.; Breton, C.V.; et al. Dysregulated lipid and fatty acid metabolism link perfluoroalkyl substances exposure and impaired glucose metabolism in young adults. Environ. Int. 2020 , 145 , 106091. [ Google Scholar ] [ CrossRef ]
• Fan, Y.; Li, X.; Xu, Q.; Zhang, Y.; Yang, X.; Han, X.; Du, G.; Xia, Y.; Wang, X.; Lu, C. Serum albumin mediates the effect of multiple per- and polyfluoroalkyl substances on serum lipid levels. Environ. Pollut. 2020 , 266 Pt 2 , 115138. [ Google Scholar ] [ CrossRef ]
• Blomberg, A.J.; Shih, Y.-H.; Messerlian, C.; Jørgensen, L.H.; Weihe, P.; Grandjean, P. Early-life associations between per- and polyfluoroalkyl substances and serum lipids in a longitudinal birth cohort. Environ. Res. 2021 , 200 , 111400. [ Google Scholar ] [ CrossRef ]
• Ojo, A.F.; Xia, Q.; Peng, C.; Ng, J.C. Evaluation of the individual and combined toxicity of perfluoroalkyl substances to human liver cells using biomarkers of oxidative stress. Chemosphere 2021 , 281 , 130808. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Lind, P.M.; Salihovic, S.; van Bavel, B.; Lind, L. Circulating levels of perfluoroalkyl substances (PFASs) and carotid artery atherosclerosis. Environ. Res. 2017 , 152 , 157–164. [ Google Scholar ] [ CrossRef ]
• Bjorke-Monsen, A.-L.; Varsi, K.; Averina, M.; Brox, J.; Huber, S. Perfluoroalkyl substances (PFASs) and mercury in never-pregnant women of fertile age: Association with fish consumption and unfavorable lipid profile. BMJ Nutr. Prev. Health 2020 , 3 , 277–284. [ Google Scholar ] [ CrossRef ]
• Carstens, K.E.; Freudenrich, T.; Wallace, K.; Choo, S.; Carpenter, A.; Smeltz, M.; Clifton, M.S.; Henderson, W.M.; Richard, A.M.; Patlewicz, G.; et al. Evaluation of Per- and Polyfluoroalkyl Substances (PFAS) In Vitro Toxicity Testing for Developmental Neurotoxicity. Chem. Res. Toxicol. 2023 , 36 , 402–419. [ Google Scholar ] [ CrossRef ]
• Chen, N.; Li, J.; Li, D.; Yang, Y.; He, D. Chronic exposure to perfluorooctane sulfonate induces behavior defects and neurotoxicity through oxidative damages, in vivo and in vitro. PLoS ONE 2014 , 9 , 113453. [ Google Scholar ] [ CrossRef ]
• Oh, J.; Shin, H.-M.; Kannan, K.; Busgang, S.A.; Schmidt, R.J.; Schweitzer, J.B.; Hertz-Picciotto, I.; Bennett, D.H. Childhood exposure to per- and polyfluoroalkyl substances and neurodevelopment in the CHARGE case-control study. Environ. Res. 2022 , 215 Pt 2 , 114322. [ Google Scholar ] [ CrossRef ]
• Yao, H.; Fu, Y.; Weng, X.; Zeng, Z.; Tan, Y.; Wu, X.; Zeng, H.; Yang, Z.; Li, Y.; Liang, H.; et al. The Association between Prenatal Per- and Polyfluoroalkyl Substances Exposure and Neurobehavioral Problems in Offspring: A Meta-Analysis. Int. J. Environ. Res. Public Health 2023 , 20 , 1668. [ Google Scholar ] [ CrossRef ]
• Rock, K.D.; Patisaul, H.B. Environmental Mechanisms of Neurodevelopmental Toxicity. Curr. Environ. Health Rep. 2018 , 5 , 145–157. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Costa, L.G.; Cole, T.B.; Dao, K.; Chang, Y.-C.; Garrick, J.M. Developmental impact of air pollution on brain function. Neurochem. Int. 2019 , 131 , 104580. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Hamm, M.P.; Cherry, N.M.; Chan, E.; Martin, J.W.; Burstyn, I. Maternal exposure to perfluorinated acids and fetal growth. J. Expo. Sci. Environ. Epidemiol. 2010 , 20 , 589–597. [ Google Scholar ] [ CrossRef ]
• Szilagyi, J.T.; Avula, V.; Fry, R.C. Perfluoroalkyl Substances (PFAS) and Their Effects on the Placenta, Pregnancy, and Child Development: A Potential Mechanistic Role for Placental Peroxisome Proliferator-Activated Receptors (PPARs). Curr. Environ. Health Rep. 2020 , 7 , 222–230. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Erinc, A.; Davis, M.B.; Padmanabhan, V.; Langen, E.; Goodrich, J.M. Considering environmental exposures to per- and polyfluoroalkyl substances (PFAS) as risk factors for hypertensive disorders of pregnancy. Environ. Res. 2021 , 197 , 111113. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Blake, B.E.; Fenton, S.E. Early life exposure to per- and polyfluoroalkyl substances (PFAS) and latent health outcomes: A review including the placenta as a target tissue and possible driver of peri- and postnatal effects. Toxicology 2020 , 443 , 152565. [ Google Scholar ] [ CrossRef ]
• Liu, D.; Yan, S.; Liu, Y.; Chen, Q.; Ren, S. Association of prenatal exposure to perfluorinated and polyfluoroalkyl substances with childhood neurodevelopment: A systematic review and meta-analysis. Ecotoxicol. Environ. Saf. 2024 , 271 , 115939. [ Google Scholar ] [ CrossRef ]
• McAdam, J.; Bell, E.M. Determinants of maternal and neonatal PFAS concentrations: A review. Environ. Health 2023 , 22 , 41. [ Google Scholar ] [ CrossRef ]
• Cai, D.; Li, Q.-Q.; Chu, C.; Wang, S.-Z.; Tang, Y.-T.; Appleton, A.A.; Qiu, R.-L.; Yang, B.-Y.; Hu, L.-W.; Dong, G.-H.; et al. High trans-placental transfer of perfluoroalkyl substances alternatives in the matched maternal-cord blood serum: Evidence from a birth cohort study. Sci. Total Environ. 2020 , 705 , 135885. [ Google Scholar ] [ CrossRef ]
• Gützkow, K.B.; Haug, L.S.; Thomsen, C.; Sabaredzovic, A.; Becher, G.; Brunborg, G. Placental transfer of perfluorinated compounds is selective—A Norwegian Mother and Child sub-cohort study. Int. J. Hyg. Environ. Health 2012 , 215 , 216–219. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Bloom, M.S.; Varde, M.; Newman, R.B. Environmental toxicants and placental function. Best Pract. Res. Clin. Obstet. Gynaecol. 2022 , 85 Pt B , 105–120. [ Google Scholar ] [ CrossRef ]
• Liu, Y.; Li, A.; Buchanan, S.; Liu, W. Exposure characteristics for congeners, isomers, and enantiomers of perfluoroalkyl substances in mothers and infants. Environ. Int. 2020 , 144 , 106012. [ Google Scholar ] [ CrossRef ]
• Brantsæter, A.; Whitworth, K.; Ydersbond, T.; Haug, L.; Haugen, M.; Knutsen, H.; Thomsen, C.; Meltzer, H.; Becher, G.; Sabaredzovic, A.; et al. Determinants of plasma concentrations of perfluoroalkyl substances in pregnant Norwegian women. Environ. Int. 2013 , 54 , 74–84. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Liew, Z.; Goudarzi, H.; Oulhote, Y. Developmental Exposures to Perfluoroalkyl Substances (PFASs): An Update of Associated Health Outcomes. Curr. Environ. Health Rep. 2018 , 5 , 1–19. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Gao, X.-X.; Zuo, Q.-L.; Fu, X.-H.; Song, L.-L.; Cen, M.-Q.; Wu, J. Association between prenatal exposure to per- and polyfluoroalkyl substances and neurodevelopment in children: Evidence based on birth cohort. Environ. Res. 2023 , 236 Pt 2 , 116812. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Mullin, A.P.; Gokhale, A.; Moreno-De-Luca, A.; Sanyal, S.; Waddington, J.L.; Faundez, V. Neurodevelopmental disorders: Mechanisms and boundary definitions from genomes, interactomes and proteomes. Transl. Psychiatry 2013 , 3 , 329. [ Google Scholar ] [ CrossRef ]
• Lewis, R.C.; Johns, L.E.; Meeker, J.D. Serum Biomarkers of Exposure to Perfluoroalkyl Substances in Relation to Serum Testosterone and Measures of Thyroid Function among Adults and Adolescents from NHANES 2011–2012. Int. J. Environ. Res. Public Health 2015 , 12 , 6098–6114. [ Google Scholar ] [ CrossRef ]
• Da Silva, B.F.; Ahmadireskety, A.; Aristizabal-Henao, J.J.; Bowden, J.A. A rapid and simple method to quantify per- and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX 2020 , 7 , 101111. [ Google Scholar ] [ CrossRef ]
• Marra, V.; Abballe, A.; Dellatte, E.; Iacovella, N.; Ingelido, A.M.; De Felip, E. A Simple and Rapid Method for Quantitative HPLC MS/MS Determination of Selected Perfluorocarboxylic Acids and Perfluorosulfonates in Human Serum. Int. J. Anal. Chem. 2020 , 2020 , 8878618. [ Google Scholar ] [ CrossRef ]
• Henn, B.C.; Bellinger, D.C.; Hopkins, M.R.; Coull, B.A.; Ettinger, A.S.; Jim, R.; Hatley, E.; Christiani, D.C.; Wright, R.O. Maternal and Cord Blood Manganese Concentrations and Early Childhood Neurodevelopment among Residents near a Mining-Impacted Superfund Site. Environ. Health Perspect. 2017 , 125 , 067020. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Gansler, D.A.; Varvaris, M.; Schretlen, D.J. The use of neuropsychological tests to assess intelligence. Clin. Neuropsychol. 2017 , 31 , 1073–1086. [ Google Scholar ] [ CrossRef ]
• Smelror, R.E.; Ueland, T. Cognitive functioning in early-onset psychosis. In Adolescent Psychosis ; Elsevier: Amsterdam, The Netherlands, 2023; Volume 13, pp. 127–152. [ Google Scholar ]
• Chatham, C.H.; Taylor, K.I.; Charman, T.; D’Ardhuy, X.L.; Eule, E.; Fedele, A.; Hardan, A.Y.; Loth, E.; Murtagh, L.; Rubido, M.d.V.; et al. Adaptive behavior in autism: Minimal clinically important differences on the Vineland-II. Autism Res. 2018 , 11 , 270–283. [ Google Scholar ] [ CrossRef ]
• Burns, T.G.; King, T.Z.; Spencer, K.S. Mullen scales of early learning: The utility in assessing children diagnosed with autism spectrum disorders, cerebral palsy, and epilepsy. Appl. Neuropsychol. Child 2013 , 2 , 33–42. [ Google Scholar ] [ CrossRef ]
• Tsujii, N.; Usami, M.; Naya, N.; Tsuji, T.; Mishima, H.; Horie, J.; Fujiwara, M.; Iida, J. Efficacy and Safety of Medication for Attention-Deficit Hyperactivity Disorder in Children and Adolescents with Common Comorbidities: A Systematic Review. Neurol. Ther. 2021 , 10 , 499–522. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Biederman, J.; DiSalvo, M.; Vaudreuil, C.; Wozniak, J.; Uchida, M.; Woodworth, K.Y.; Green, A.; Farrell, A.; Faraone, S.V. The child behavior checklist can aid in characterizing suspected comorbid psychopathology in clinically referred youth with ADHD. J. Psychiatr. Res. 2021 , 138 , 477–484. [ Google Scholar ] [ CrossRef ]
• Goodman, C.V.; Till, C.; Green, R.; El-Sabbagh, J.; Arbuckle, T.E.; Hornung, R.; Lanphear, B.; Seguin, J.R.; Booij, L.; Fisher, M.; et al. Prenatal exposure to legacy PFAS and neurodevelopment in preschool-aged Canadian children: The MIREC cohort. Neurotoxicol. Teratol. 2023 , 98 , 107181. [ Google Scholar ] [ CrossRef ]
• Beck, I.H.; Bilenberg, N.; Möller, S.; Nielsen, F.; Grandjean, P.; Højsager, F.D.; Halldorsson, T.I.; Nielsen, C.; Jensen, T.K. Association Between Prenatal and Early Postnatal Exposure to Perfluoroalkyl Substances and IQ Score in 7-Year-Old Children From the Odense Child Cohort. Am. J. Epidemiol. 2023 , 192 , 1522–1535. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Vuong, A.M.; Webster, G.M.; Yolton, K.; Calafat, A.M.; Muckle, G.; Lanphear, B.P.; Chen, A. Prenatal exposure to per- and polyfluoroalkyl substances (PFAS) and neurobehavior in US children through 8 years of age: The HOME study. Environ. Res. 2021 , 195 , 110825. [ Google Scholar ] [ CrossRef ]
• Wang, H.; Luo, F.; Zhang, Y.; Yang, X.; Zhang, S.; Zhang, J.; Tian, Y.; Zheng, L. Prenatal exposure to perfluoroalkyl substances and child intelligence quotient: Evidence from the Shanghai birth cohort. Environ. Int. 2023 , 174 , 107912. [ Google Scholar ] [ CrossRef ]
• Liew, Z.; Ritz, B.; Bach, C.C.; Asarnow, R.F.; Bech, B.H.; Nohr, E.A.; Bossi, R.; Henriksen, T.B.; Bonefeld-Jørgensen, E.C.; Olsen, J. Prenatal Exposure to Perfluoroalkyl Substances and IQ Scores at Age 5; a Study in the Danish National Birth Cohort. Environ. Health Perspect. 2018 , 126 , 067004. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Wang, Y.; Rogan, W.J.; Chen, H.-Y.; Chen, P.-C.; Su, P.-H.; Chen, H.-Y.; Wang, S.-L. Prenatal exposure to perfluroalkyl substances and children’‘s’ IQ: The Taiwan maternal and infant cohort study. Int. J. Hyg. Environ. Health 2015 , 218 , 639–644. [ Google Scholar ] [ CrossRef ]
• Harris, M.H.; Oken, E.; Rifas-Shiman, S.L.; Calafat, A.M.; Ye, X.; Bellinger, D.C.; Webster, T.F.; White, R.F.; Sagiv, S.K. Prenatal and childhood exposure to per- and polyfluoroalkyl substances (PFASs) and child cognition. Environ. Int. 2018 , 115 , 358–369. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Skogheim, T.S.; Villanger, G.D.; Weyde, K.V.F.; Engel, S.M.; Surén, P.; Øie, M.G.; Skogan, A.H.; Biele, G.; Zeiner, P.; Øvergaard, K.R.; et al. Prenatal exposure to perfluoroalkyl substances and associations with symptoms of attention-deficit/hyperactivity disorder and cognitive functions in preschool children. Int. J. Hyg. Environ. Health 2020 , 223 , 80–92. [ Google Scholar ] [ CrossRef ]
• Zhang, B.; Wang, Z.; Zhang, J.; Dai, Y.; Ding, J.; Guo, J.; Qi, X.; Wu, C.; Zhou, Z. Prenatal exposure to per- and polyfluoroalkyl substances, fetal thyroid function, and intelligence quotient at 7 years of age: Findings from the Sheyang Mini Birth Cohort Study. Environ. Int. 2024 , 187 , 108720. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Bünger, A.; Grieder, S.; Schweizer, F.; Grob, A. The comparability of intelligence test results: Group- and individual-level comparisons of seven intelligence tests. J. Sch. Psychol. 2021 , 88 , 101–117. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Vuong, A.M.; Yolton, K.; Xie, C.; Dietrich, K.N.; Braun, J.M.; Webster, G.M.; Calafat, A.M.; Lanphear, B.P.; Chen, A. Prenatal and childhood exposure to poly- and perfluoroalkyl substances (PFAS) and cognitive development in children at age 8 years. Environ. Res. 2019 , 172 , 242–248. [ Google Scholar ] [ CrossRef ]
• Forns, J.; Verner, M.-A.; Iszatt, N.; Nowack, N.; Bach, C.C.; Vrijheid, M.; Costa, O.; Andiarena, A.; Sovcikova, E.; Høyer, B.B.; et al. Early Life Exposure to Perfluoroalkyl Substances (PFAS) and ADHD: A Meta-Analysis of Nine European Population-Based Studies. Environ. Health Perspect. 2020 , 128 , 57002. [ Google Scholar ] [ CrossRef ]
• Dalsager, L.; Jensen, T.K.; Nielsen, F.; Grandjean, P.; Bilenberg, N.; Andersen, H.R. No association between maternal and child PFAS concentrations and repeated measures of ADHD symptoms at age 2(1/2) and 5 years in children from the Odense Child Cohort. Neurotoxicol. Teratol. 2021 , 88 , 107031. [ Google Scholar ] [ CrossRef ]
• Kim, J.I.; Kim, B.-N.; Lee, Y.A.; Shin, C.H.; Hong, Y.-C.; Døssing, L.D.; Hildebrandt, G.; Lim, Y.-H. Association between early-childhood exposure to perfluoroalkyl substances and ADHD symptoms: A prospective cohort study. Sci. Total Environ. 2023 , 879 , 163081. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Liew, Z.; Ritz, B.; von Ehrenstein, O.S.; Bech, B.H.; Nohr, E.A.; Fei, C.; Bossi, R.; Henriksen, T.B.; Bonefeld-Jørgensen, E.C.; Olsen, J. Attention deficit/hyperactivity disorder and childhood autism in association with prenatal exposure to perfluoroalkyl substances: A nested case-control study in the Danish National Birth Cohort. Environ. Health Perspect. 2015 , 123 , 367–373. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Skogheim, T.S.; Weyde, K.V.F.; Aase, H.; Engel, S.M.; Surén, P.; Øie, M.G.; Biele, G.; Reichborn-Kjennerud, T.; Brantsæter, A.L.; Haug, L.S.; et al. Prenatal exposure to per- and polyfluoroalkyl substances (PFAS) and associations with attention-deficit/hyperactivity disorder and autism spectrum disorder in children. Environ. Res. 2021 , 202 , 111692. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Itoh, S.; Yamazaki, K.; Suyama, S.; Ikeda-Araki, A.; Miyashita, C.; Bamai, Y.A.; Kobayashi, S.; Masuda, H.; Yamaguchi, T.; Goudarzi, H.; et al. The association between prenatal perfluoroalkyl substance exposure and symptoms of attention-deficit/hyperactivity disorder in 8-year-old children and the mediating role of thyroid hormones in the Hokkaido study. Environ. Int. 2022 , 159 , 107026. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Quaak, I.; De Cock, M.; De Boer, M.; Lamoree, P.; Leonards, P.; Van de Bor, M. Prenatal Exposure to Perfluoroalkyl Substances and Behavioral Development in Children. Int. J. Environ. Res. Public. Health 2016 , 13 , 511. [ Google Scholar ] [ CrossRef ]
• Oh, J.; Bennett, D.H.; Calafat, A.M.; Tancredi, D.; Roa, D.L.; Schmidt, R.J.; Hertz-Picciotto, I.; Shin, H.-M. Prenatal exposure to per- and polyfluoroalkyl substances in association with autism spectrum disorder in the MARBLES study. Environ. Int. 2021 , 147 , 106328. [ Google Scholar ] [ CrossRef ]
• Choi, J.W.; Oh, J.; Bennett, D.H.; Calafat, A.M.; Schmidt, R.J.; Shin, H.-M. Prenatal exposure to per- and polyfluoroalkyl substances and child behavioral problems. Environ. Res. 2024 , 251 Pt 1 , 118511. [ Google Scholar ] [ CrossRef ]
• Shin, H.-M.; Bennett, D.H.; Calafat, A.M.; Tancredi, D.; Hertz-Picciotto, I. Modeled prenatal exposure to per- and polyfluoroalkyl substances in association with child autism spectrum disorder: A case-control study. Environ. Res. 2020 , 186 , 109514. [ Google Scholar ] [ CrossRef ]
• Lyall, K.; Yau, V.M.; Hansen, R.; Kharrazi, M.; Yoshida, C.K.; Calafat, A.M.; Windham, G.; Croen, L.A. Prenatal Maternal Serum Concentrations of Per- and Polyfluoroalkyl Substances in Association with Autism Spectrum Disorder and Intellectual Disability. Environ. Health Perspect. 2018 , 126 , 017001. [ Google Scholar ] [ CrossRef ]
• Hoadley, L.; Watters, M.; Rogers, R.; Werner, L.S.; Markiewicz, K.V.; Forrester, T.; McLanahan, E.D. Public health evaluation of PFAS exposures and breastfeeding: A systematic literature review. Toxicol. Sci. 2023 , 194 , 121–137. [ Google Scholar ] [ CrossRef ]
• Mamsen, L.S.; Björvang, R.D.; Mucs, D.; Vinnars, M.-T.; Papadogiannakis, N.; Lindh, C.H.; Andersen, C.Y.; Damdimopoulou, P. Concentrations of perfluoroalkyl substances (PFASs) in human embryonic and fetal organs from first, second, and third trimester pregnancies. Environ. Int. 2019 , 124 , 482–492. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Hanssen, L.; Dudarev, A.A.; Huber, S.; Odland, J.; Nieboer, E.; Sandanger, T.M. Partition of perfluoroalkyl substances (PFASs) in whole blood and plasma, assessed in maternal and umbilical cord samples from inhabitants of arctic Russia and Uzbekistan. Sci. Total Environ. 2013 , 447 , 430–437. [ Google Scholar ] [ CrossRef ]
• Chen, F.; Yin, S.; Kelly, B.C.; Liu, W. Isomer-Specific Transplacental Transfer of Perfluoroalkyl Acids: Results from a Survey of Paired Maternal, Cord Sera, and Placentas. Environ. Sci. Technol. 2017 , 51 , 5756–5763. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Macheka-Tendenguwo, L.R.; Olowoyo, J.O.; Mugivhisa, L.L.; Abafe, O.A. Per- and polyfluoroalkyl substances in human breast milk and current analytical methods. Environ. Sci. Pollut. Res. Int. 2018 , 25 , 36064–36086. [ Google Scholar ] [ CrossRef ]
• Timmermann, A.; Avenbuan, O.N.; Romano, M.E.; Braun, J.M.; Tolstrup, J.S.; Vandenberg, L.N.; Fenton, S.E. Per- and Polyfluoroalkyl Substances and Breastfeeding as a Vulnerable Function: A Systematic Review of Epidemiological Studies. Toxics 2023 , 11 , 325. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Jian, J.-M.; Chen, D.; Han, F.-J.; Guo, Y.; Zeng, L.; Lu, X.; Wang, F. A short review on human exposure to and tissue distribution of per- and polyfluoroalkyl substances (PFASs). Sci. Total Environ. 2018 , 636 , 1058–1069. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Ragnarsdottir, O.; Abdallah, M.A.; Harrad, S. Dermal uptake: An important pathway of human exposure to perfluoroalkyl substances? Environ. Pollut. 2022 , 307 , 119478. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Lin, C.-Y.; Lin, L.-Y.; Wen, T.-W.; Lien, G.-W.; Chien, K.-L.; Hsu, S.H.; Liao, C.-C.; Sung, F.-C.; Chen, P.-C.; Su, T.-C. Association between levels of serum perfluorooctane sulfate and carotid artery intima-media thickness in adolescents and young adults. Int. J. Cardiol. 2013 , 168 , 3309–3316. [ Google Scholar ] [ CrossRef ]
• Grandjean, P.; Andersen, E.W.; Budtz-Jørgensen, E.; Nielsen, F.; Mølbak, K.; Weihe, P.; Heilmann, C. Serum vaccine antibody concentrations in children exposed to perfluorinated compounds. JAMA 2012 , 307 , 391–397. [ Google Scholar ] [ CrossRef ]
• Granum, B.; Haug, L.S.; Namork, E.; Stølevik, S.B.; Thomsen, C.; Aaberge, I.S.; van Loveren, H.; Løvik, M.; Nygaard, U.C. Pre-natal exposure to perfluoroalkyl substances may be associated with altered vaccine antibody levels and immune-related health outcomes in early childhood. J. Immunotoxicol. 2013 , 10 , 373–379. [ Google Scholar ] [ CrossRef ]
• White, S.S.; Stanko, J.P.; Kato, K.; Calafat, A.M.; Hines, E.P.; Fenton, S.E. Gestational and chronic low-dose PFOA exposures and mammary gland growth and differentiation in three generations of CD-1 mice. Environ. Health Perspect. 2011 , 119 , 1070–1076. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Yang, C.; Tan, Y.S.; Harkema, J.R.; Haslam, S.Z. Differential effects of peripubertal exposure to perfluorooctanoic acid on mammary gland development in C57Bl/6 and Balb/c mouse strains. Reprod. Toxicol. 2009 , 27 , 299–306. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Lopez-Espinosa, M.-J.; Mondal, D.; Armstrong, B.; Bloom, M.S.; Fletcher, T. Thyroid function and perfluoroalkyl acids in children living near a chemical plant. Environ. Health Perspect. 2012 , 120 , 1036–1041. [ Google Scholar ] [ CrossRef ]
• Tsai, M.-S.; Lin, C.-C.; Chen, M.-H.; Hsieh, W.-S.; Chen, P.-C. Perfluoroalkyl substances and thyroid hormones in cord blood. Environ. Pollut. 2017 , 222 , 543–548. [ Google Scholar ] [ CrossRef ]
• Lin, C.-Y.; Wen, L.-L.; Lin, L.-Y.; Wen, T.-W.; Lien, G.-W.; Hsu, S.H.; Chien, K.-L.; Liao, C.-C.; Sung, F.-C.; Chen, P.-C.; et al. The associations between serum perfluorinated chemicals and thyroid function in adolescents and young adults. J. Hazard. Mater. 2013 , 244–245 , 637–644. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Kataria, A.; Trachtman, H.; Malaga-Dieguez, L.; Trasande, L. Association between perfluoroalkyl acids and kidney function in a cross-sectional study of adolescents. Environ. Health 2015 , 14 , 89. [ Google Scholar ] [ CrossRef ]
• Qin, X.-D.; Qian, Z.; Vaughn, M.G.; Huang, J.; Ward, P.; Zeng, X.-W.; Zhou, Y.; Zhu, Y.; Yuan, P.; Li, M.; et al. Positive associations of serum perfluoroalkyl substances with uric acid and hyperuricemia in children from Taiwan. Environ. Pollut. 2016 , 212 , 519–524. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Fei, C.; McLaughlin, J.K.; Lipworth, L.; Olsen, J. Prenatal exposure to perfluorooctanoate (PFOA) and perfluorooctanesulfonate (PFOS) and maternally reported developmental milestones in infancy. Environ. Health Perspect. 2008 , 116 , 1391–1395. [ Google Scholar ] [ CrossRef ]
• Goudarzi, H.; Nakajima, S.; Ikeno, T.; Sasaki, S.; Kobayashi, S.; Miyashita, C.; Ito, S.; Araki, A.; Nakazawa, H.; Kishi, R. Prenatal exposure to perfluorinated chemicals and neurodevelopment in early infancy: The Hokkaido Study. Sci. Total Environ. 2016 , 541 , 1002–1010. [ Google Scholar ] [ CrossRef ]
• Stein, C.R.; Savitz, D.A.; Bellinger, D.C. Perfluorooctanoate and neuropsychological outcomes in children. Epidemiology 2013 , 24 , 590–599. [ Google Scholar ] [ CrossRef ]
• Parenti, I.; Rabaneda, L.G.; Schoen, H.; Novarino, G. Neurodevelopmental Disorders: From Genetics to Functional Pathways. Trends Neurosci. 2020 , 43 , 608–621. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Antolini, G.; Colizzi, M. Where Do Neurodevelopmental Disorders Go? Casting the Eye Away from Childhood towards Adulthood. Healthcare 2023 , 11 , 1015. [ Google Scholar ] [ CrossRef ]
• Bragg, M.; Chavarro, J.E.; Hamra, G.B.; Hart, J.E.; Tabb, L.P.; Weisskopf, M.G.; Volk, H.E.; Lyall, K. Prenatal Diet as a Modifier of Environmental Risk Factors for Autism and Related Neurodevelopmental Outcomes. Curr. Environ. Health Rep. 2022 , 9 , 324–338. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Brabhukumr, A.; Malhi, P.; Ravindra, K.; Lakshmi, P. Exposure to household air pollution during first 3 years of life and IQ level among 6–8-year-old children in India- A cross-sectional study. Sci. Total Environ. 2020 , 709 , 135110. [ Google Scholar ] [ CrossRef ]
• Carroll, J.B. Psychometrics, intelligence, and public perception. Intelligence 1997 , 24 , 25–52. [ Google Scholar ] [ CrossRef ]
• Iqubal, A.; Ahmed, M.; Ahmad, S.; Sahoo, C.R.; Iqubal, M.K.; Haque, S.E. Environmental neurotoxic pollutants: Review. Environ. Sci. Pollut. Res. 2020 , 27 , 41175–41198. [ Google Scholar ] [ CrossRef ]
• Thapar, A.; Cooper, M. Attention deficit hyperactivity disorder. Lancet 2016 , 387 , 1240–1250. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Koutsoklenis, A.; Honkasilta, J. ADHD in the DSM-5-TR: What has changed and what has not. Front. Psychiatry 2022 , 13 , 1064141. [ Google Scholar ] [ CrossRef ]
• Association, A.P. Diagnostic and Statistical Manual of Mental Disorders ; American Psychiatric Association: Washington, DC, USA, 2000. [ Google Scholar ]
• Wang, L.; Wang, B.; Wu, C.; Wang, J.; Sun, M. Autism Spectrum Disorder: Neurodevelopmental Risk Factors, Biological Mechanism, and Precision Therapy. Int. J. Mol. Sci. 2023 , 24 , 1819. [ Google Scholar ] [ CrossRef ]
• Hirota, T.; King, B.H. Autism Spectrum Disorder: A Review. JAMA 2023 , 329 , 157–168. [ Google Scholar ] [ CrossRef ]
• Rosen, T.E.; Mazefsky, C.A.; Vasa, R.A.; Lerner, M.D. Co-occurring psychiatric conditions in autism spectrum disorder. Int. Rev. Psychiatry 2018 , 30 , 40–61. [ Google Scholar ] [ CrossRef ] [ PubMed ]

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Currie, S.D.; Wang, J.-S.; Tang, L. Impacts of PFAS Exposure on Neurodevelopment: A Comprehensive Literature Review. Environments 2024 , 11 , 188. https://doi.org/10.3390/environments11090188

Currie SD, Wang J-S, Tang L. Impacts of PFAS Exposure on Neurodevelopment: A Comprehensive Literature Review. Environments . 2024; 11(9):188. https://doi.org/10.3390/environments11090188

Currie, Seth D., Jia-Sheng Wang, and Lili Tang. 2024. "Impacts of PFAS Exposure on Neurodevelopment: A Comprehensive Literature Review" Environments 11, no. 9: 188. https://doi.org/10.3390/environments11090188

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Exploring Integration of Multimodal Deep Learning Approaches for Enhanced Alzheimer's Disease Diagnosis: A Review of Recent Literature

• Review Article
• Published: 02 September 2024
• Volume 5 , article number  852 , ( 2024 )

Cite this article

• Sonali Deshpande 1 &
• Nilima Kulkarni 1  

Alzheimer's disease (AD), is the most common form of dementia that affects the nervous system. In the past few years, non-invasive early AD diagnosis has become more popular as a way to improve patient care and treatment results. Imaging methods, electroencephalogram (EEG) tests, and sound evaluations are some of the new ways that researchers have looked into. This review covers 60 papers published from 2020. They are compared in terms of how they use basic deep learning models such as CNN, LSTM, Alex Net, Inception Net, VGG19, and ResNet to identify AD. But not many studies use more than one method together, like image and EEG, EEG and sounds, or images and sounds. The information from the Scopus database makes it easy to look at the newest information and work. This means that using more than one method to find AD isn't getting as much attention. Our review says that combining the best parts of each method in a mixed way could make Alzheimer's research much more useful and lead to better ways to diagnose. The paper talks about problems and opportunities in the field right now as well as possible study topics and issues for the future.

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Data Availability

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Prince M, Wimo A, Guerchet M, Ali G-C, Wu Y-T, Prina M. World Alzheimer report 2015. The global impact of dementia. An analysis of prevalence, incidence, cost, and trends. 2015.

Kumar Y. Recent advancement of machine learning and deep learning in the field of healthcare system. 2021; p. 77–98.

Ghazal TM, Hasan MK, Alshurideh MT, Alzoubi HM, Ahmad M, Akbar SS, Al Kurdi B, Akour IA. IoT for smart cities: Machine learning approaches in smart healthcare—a review. Future Internet. 2021;13(8):218.

Article   Google Scholar  

Bind S, Tiwari A, Kumar A. A survey of machine learning-based approaches for Parkinson disease prediction. 2022.

Fleming R, Zeisel J, Bennett K. World Alzheimer Report 2020: Design Dignity Dementia: dementia-related design and the built environment, vol. 1. London: Alzheimer’s Disease International; 2020.

Google Scholar  

Twarowski B, Herbet M. Inflammatory processes in Alzheimer’s disease—pathomechanism, diagnosis, and treatment: a review. Int J Mol Sci. 2023;24:6518.

Muhammed Niyas KP, Thiyagarajan P. A systematic review on early prediction of mild cognitive impairment to Alzheimer using machine learning algorithms. Int J Intell Netw. 2023;4:74–88.

Khojaste-Sarakhsi M, Haghighi SS, Fatemi Ghomi SMT, Marchiori E. Deep learning for Alzheimer’s disease diagnosis: A survey. Artif Intell Med. 2022;130:102332.

Gao S, Lima D. A review of the application of deep learning in the detection of Alzheimer’s disease. Int J Cognit Comput Eng. 2022;3:1–8.

Jehosheba Margaret M, Masoodhu Banu NM. Performance analysis of EEG based emotion recognition using deep learning models. Brain-Comput Interfaces. 2023;10(2–4):79–98.

Kulkarni N. Color thresholding method for image segmentation of natural images. Int J Image Graph Signal Process. 2012;4:02.

Meng Lu, Zhang Q. Research on early diagnosis of Alzheimer’s disease based on dual fusion cluster graph convolutional network. Biomed Signal Process Control. 2023;86: 105212.

Chabib CM, Hadjileontiadis LJ, Al Shehhi A. Deepcurvmri: Deep convolutional curvelet transform-based mri approach for early detection of Alzheimer’s disease. IEEE Access. 2023;11:44650–9.

Minaee S, Kafieh R, Sonka M, Yazdani S, Soufi GJ. Deep-covid: Predicting COVID-19 from chest x-ray images using deep transfer learning. Med Image Anal. 2020;65:101794.

Kinge A, Oswal Y, Khangal T, Kulkarni N, Jha P. Comparative study on different classification models for customer churnproblem. 2022; p. 153–164.

Mofrad SA, Lundervold A, Lundervold AS. A predictive framework based on brain volume trajectories enabling early detection of Alzheimer’s disease. Comput Med Imaging Graph. 2021;90:101910.

Khan A, Zubair S. Development of a three-tiered cognitive hybrid machine learning algorithm for effective diagnosis of Alzheimer’s disease. J King Saud Univ Comput Inform Sci. 2022;34(10, Part A):8000–18.

Sharma S, Guleria K, Tiwari S, Kumar S. A deep learning-based convolutional neural network model with vgg16 feature extractor for the detection of Alzheimer disease using mri scans. Meas Sens. 2022;24:100506.

Mccombe N, Ding X, Prasad G, Gillespie P, Finn DP, Todd S, Mcclean PL, Wong-Lin K. Alzheimer’s disease assessments optimized for diagnostic accuracy and administration time. IEEE J Transl Eng Health Med. 2022;10:1–9.

Akbar S, Ali H, Ahmad A, Sarker MR, Saeed A, Salwana E, Gul S, Khan A, Ali F. Prediction of amyloid proteins using embedded evolutionary ensemble feature selection based descriptors with extreme gradient boosting model. IEEE Access. 2023;11:39024–36.

Shukla A, Tiwari R, Tiwari S. Review on Alzheimer disease detection methods: Automatic pipelines and machine learning techniques. Science. 2023;5(1):13.

Chauhan N, Choi B-J. Classification of Alzheimer’s disease using maximal information coefficient-based functional connectivity with an extreme learning machine. Brain Sci. 2023;13(7):1046.

Dang M, Chen Q, Zhao X, Chen K, Li X, Zhang J, Jie Lu, Ai L, Chen Y, Zhang Z. Tau as a biomarker of cognitive impairment and neuropsychiatric symptom in Alzheimer’s disease. Hum Brain Mapp. 2022;44:08.

Khan A, Kulkarni N, Kumar A, Kamat A. D-cnn and image processing based approach for diabetic retinopathy classification. 2022; p. 283–291.

Kale A, Jawade I, Kakade P, Jadhav R, Kulkarni N. Pairnet: a deep learning-based object detection and segmentationsystem. 2022; p.ages 423–436.

Marwa EL-Geneedy M, El-Din Moustafa H, Khalifa F, Khater H, AbdElhalim E. An MRI-based deep learning approach for accurate detection of Alzheimer’s disease. Alex Eng J. 2023;63:211–21.

Balaji P, Chaurasia M, Bilfaqih S, Muniasamy A, Elzubir L. Hybridized deep learning approach for detecting Alzheimer’s disease. Biomedicines. 2023;11:1–16.

Hu Z, Wang Z, Jin Y, Hou W. Vgg-tswinformer: Transformer-based deep learning model for early Alzheimer’s disease prediction. Comput Methods Programs Biomed. 2023;229:107291.

Sethuraman SK, Malaiyappan N, Ramalingam R, Basheer S, Rashid M, Ahmad N. Predicting Alzheimer disease using deep neuro-functional networks with resting-state fMRI. Electronics. 2023;12(4):1031.

Ismail WN, Fathimathul Rajeena PP, Ali MAS. A meta-heuristic multi-objective optimization method for Alzheimer’s disease detection based on multi-modal data. Mathematics. 2023;11(4):957.

Menagadevi M, Mangai S, Madian N, Thiyagarajan D. Automated prediction system for Alzheimer detection based on deep residual auto encoder and support vector machine. Optik. 2023;272:170212.

Leela M, Helenprabha K, Sharmila L. Prediction and classification of Alzheimer disease categories using integrated deep transfer learning approach. Meas Sensors. 2023;27:100749.

Vakli P, Weiss B, Szalma J, Barsi P, Gyuricza I, Kemenczky P, Somogyi E, Nárai A, Gál V, Petra H, Vidnyánszky Z. Automatic brain MRI motion artifact detection based on end-to-end deep learning is similarly effective as traditional machine learning trained on image quality metrics. Med Image Anal. 2023;88:102850.

Javed Mehedi Shamrat FM, Akter S, Azam S, Karim A, Ghosh P, Tasnim Z, Hasib KM, De Boer F, Ahmed K. Alzheimernet: An effective deep learning based proposition for Alzheimer’s disease stages classification from functional brain changes in magnetic resonance images. IEEE Access. 2023;11:16376–95.

Chelladurai A, Narayan DL, Divakarachari PB, Loganathan U. fMRI-based Alzheimer disease detection using the sas method with a multi-layer perceptron network. Brain Sci. 2023;13(6):893.

Imani M. Alzheimer’s disease diagnosis using fusion of high informative bilstm and cnn features of EEG signal. Biomed Signal Process Control. 2023;86: 105298.

Miltiadous A, Gionanidis E, Tzimourta KD, Giannakeas N, Tzallas AT. Dice-net: a novel convolution-transformer architecture for Alzheimer detection in EEG signals. IEEE Access. 2023;11:71840–58.

Fouad IA, Labib FEM. Identification of Alzheimer’s disease from central lobe eeg signals utilizing machine learning and residual neural network. Biomed Signal Process Control. 2023;86:105266.

Rajaguru S. A greedy optimized intelligent framework for early detection of Alzheimer’s disease using eeg signal. Comput Intell Neurosci. 2023;2023:1–10.

Jiao B, Li R, Zhou H, Qing K, Liu H, Pan H, Lei Y, Wenjin Fu, Wang X, Xiao X, Liu X, Yang Q, Liao X, Zhou Y, Fang L, Dong Y, Yang Y, Jiang H, Huang S, Shen Lu. Neural biomarker diagnosis and prediction to mild cognitive impairment and Alzheimer’s disease using eeg technology. Alzheimer’s Res Ther. 2023;15:02.

Khare SK, Rajendra Acharya U. Adazd-net: Automated adaptive and explainable Alzheimer’s disease detection system using EEG signals. Knowl-Based Syst. 2023;278:110858.

jae Kim M, Youn YC, Paik J. Deep learning-based eeg analysis to classify normal, mild cognitive impairment, and dementia: algorithms and dataset. Neuroimage. 2023;272:120054.

Alessandrini M, Biagetti G, Crippa P, Falaschetti L, Luzzi S, Turchetti C. EEG-based Alzheimer disease recognition using robust-pca and LSTM recurrent neural network. Sensors. 2022;22(10):3696.

Pirrone D, Weitschek E, Paolo P, De Salvo S, De Cola M. Eeg signal processing and supervised machine learning to early diagnose Alzheimer’s disease. Appl Sci. 2022;12:5413.

Al-Nuaimi AH, Blūma M, Al-Juboori SS, Eke CS, Jammeh E, Sun L, Ifeachor E. Robust eeg based biomarkers to detect Alzheimer’s disease. Brain Sci. 2021;11(8):1026.

Tripathi T, Kumar R. Speech-based detection of multi-class Alzheimer disease classification using machine learning. 2023.

Karande S, Kulkarni V. Automated prognosis of Alzheimer’s disease using machine learning classifiers on spontaneous speech features. Int J Intell Syst Appl Eng. 2023;11(2):245–51.

Mahajan P, Baths V. Acoustic and language-based deep learning approaches for Alzheimer’s dementia detection from spontaneous speech. Front Aging Neurosci. 2021;13:02.

Kurtz E, Zhu Y, Driesse T, Tran B, Batsis JA, Roth RM, Liang X. Early detection of cognitive decline using voice assistant commands. 2023; p. 1–5.

Yamada Y, Shinkawa K, Nemoto M, Nemoto K, Arai T. A mobile application using automatic speech analysis for classifying Alzheimer’s disease and mild cognitive impairment. Comput Speech Lang. 2023;81: 101514.

Liu J, Fu F, Li L, Yu J, Zhong D, Zhu S, Zhou Y, Liu B, Li J. Efficient pause extraction and encode strategy for Alzheimer’s disease detection using only acoustic features from spontaneous speech. Brain Sci. 2023;13(3):477.

Weiner MW (2004) Alzheimer’s Disease Neuroimaging Initiative. http://adni.loni.usc.edu . Accessed 28 Apr 2024.

Deenadayalan T, Shantharajah SP. An early-stage Alzheimer’s disease detection using various imaging modalities and techniques—a mini-review. J Integr Sci Technol. 2024;12(5):803.

OASIS: OASIS Brains Dataset https://www.oasis-brains.org/ . Accessed 28 Apr 2024.

AIBL: AIBL. https://aibl.csiro.au/ . Accessed 28 Apr 2024.

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The authors acknowledged the MIT Art, Design and Technology University, Pune, India for supporting the research work by providing the facilities.

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Deshpande, S., Kulkarni, N. Exploring Integration of Multimodal Deep Learning Approaches for Enhanced Alzheimer's Disease Diagnosis: A Review of Recent Literature. SN COMPUT. SCI. 5 , 852 (2024). https://doi.org/10.1007/s42979-024-03084-w

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Published : 02 September 2024

DOI : https://doi.org/10.1007/s42979-024-03084-w

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• Alzheimer's disease (AD)
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