synthesis for the literature

Literature Syntheis 101

How To Synthesise The Existing Research (With Examples)

By: Derek Jansen (MBA) | Expert Reviewer: Eunice Rautenbach (DTech) | August 2023

One of the most common mistakes that students make when writing a literature review is that they err on the side of describing the existing literature rather than providing a critical synthesis of it. In this post, we’ll unpack what exactly synthesis means and show you how to craft a strong literature synthesis using practical examples.

This post is based on our popular online course, Literature Review Bootcamp . In the course, we walk you through the full process of developing a literature review, step by step. If it’s your first time writing a literature review, you definitely want to use this link to get 50% off the course (limited-time offer).

Overview: Literature Synthesis

• What exactly does “synthesis” mean?
• Aspect 1: Agreement
• Aspect 2: Disagreement
• Aspect 3: Key theories
• Aspect 4: Contexts
• Aspect 5: Methodologies
• Bringing it all together

What does “synthesis” actually mean?

As a starting point, let’s quickly define what exactly we mean when we use the term “synthesis” within the context of a literature review.

Simply put, literature synthesis means going beyond just describing what everyone has said and found. Instead, synthesis is about bringing together all the information from various sources to present a cohesive assessment of the current state of knowledge in relation to your study’s research aims and questions .

Put another way, a good synthesis tells the reader exactly where the current research is “at” in terms of the topic you’re interested in – specifically, what’s known , what’s not , and where there’s a need for more research .

So, how do you go about doing this?

Well, there’s no “one right way” when it comes to literature synthesis, but we’ve found that it’s particularly useful to ask yourself five key questions when you’re working on your literature review. Having done so,  you can then address them more articulately within your actual write up. So, let’s take a look at each of these questions.

1. Points Of Agreement

The first question that you need to ask yourself is: “Overall, what things seem to be agreed upon by the vast majority of the literature?”

For example, if your research aim is to identify which factors contribute toward job satisfaction, you’ll need to identify which factors are broadly agreed upon and “settled” within the literature. Naturally, there may at times be some lone contrarian that has a radical viewpoint , but, provided that the vast majority of researchers are in agreement, you can put these random outliers to the side. That is, of course, unless your research aims to explore a contrarian viewpoint and there’s a clear justification for doing so. 

Identifying what’s broadly agreed upon is an essential starting point for synthesising the literature, because you generally don’t want (or need) to reinvent the wheel or run down a road investigating something that is already well established . So, addressing this question first lays a foundation of “settled” knowledge.

Need a helping hand?

2. Points Of Disagreement

Related to the previous point, but on the other end of the spectrum, is the equally important question: “Where do the disagreements lie?” .

In other words, which things are not well agreed upon by current researchers? It’s important to clarify here that by disagreement, we don’t mean that researchers are (necessarily) fighting over it – just that there are relatively mixed findings within the empirical research , with no firm consensus amongst researchers.

This is a really important question to address as these “disagreements” will often set the stage for the research gap(s). In other words, they provide clues regarding potential opportunities for further research, which your study can then (hopefully) contribute toward filling. If you’re not familiar with the concept of a research gap, be sure to check out our explainer video covering exactly that .

3. Key Theories

The next question you need to ask yourself is: “Which key theories seem to be coming up repeatedly?” .

Within most research spaces, you’ll find that you keep running into a handful of key theories that are referred to over and over again. Apart from identifying these theories, you’ll also need to think about how they’re connected to each other. Specifically, you need to ask yourself:

• Are they all covering the same ground or do they have different focal points  or underlying assumptions ?
• Do some of them feed into each other and if so, is there an opportunity to integrate them into a more cohesive theory?
• Do some of them pull in different directions ? If so, why might this be?
• Do all of the theories define the key concepts and variables in the same way, or is there some disconnect? If so, what’s the impact of this ?

Simply put, you’ll need to pay careful attention to the key theories in your research area, as they will need to feature within your theoretical framework , which will form a critical component within your final literature review. This will set the foundation for your entire study, so it’s essential that you be critical in this area of your literature synthesis.

If this sounds a bit fluffy, don’t worry. We deep dive into the theoretical framework (as well as the conceptual framework) and look at practical examples in Literature Review Bootcamp . If you’d like to learn more, take advantage of our limited-time offer to get 60% off the standard price.

4. Contexts

The next question that you need to address in your literature synthesis is an important one, and that is: “Which contexts have (and have not) been covered by the existing research?” .

For example, sticking with our earlier hypothetical topic (factors that impact job satisfaction), you may find that most of the research has focused on white-collar , management-level staff within a primarily Western context, but little has been done on blue-collar workers in an Eastern context. Given the significant socio-cultural differences between these two groups, this is an important observation, as it could present a contextual research gap .

In practical terms, this means that you’ll need to carefully assess the context of each piece of literature that you’re engaging with, especially the empirical research (i.e., studies that have collected and analysed real-world data). Ideally, you should keep notes regarding the context of each study in some sort of catalogue or sheet, so that you can easily make sense of this before you start the writing phase. If you’d like, our free literature catalogue worksheet is a great tool for this task.

5. Methodological Approaches

Last but certainly not least, you need to ask yourself the question: “What types of research methodologies have (and haven’t) been used?”

For example, you might find that most studies have approached the topic using qualitative methods such as interviews and thematic analysis. Alternatively, you might find that most studies have used quantitative methods such as online surveys and statistical analysis.

But why does this matter?

Well, it can run in one of two potential directions . If you find that the vast majority of studies use a specific methodological approach, this could provide you with a firm foundation on which to base your own study’s methodology . In other words, you can use the methodologies of similar studies to inform (and justify) your own study’s research design .

On the other hand, you might argue that the lack of diverse methodological approaches presents a research gap , and therefore your study could contribute toward filling that gap by taking a different approach. For example, taking a qualitative approach to a research area that is typically approached quantitatively. Of course, if you’re going to go against the methodological grain, you’ll need to provide a strong justification for why your proposed approach makes sense. Nevertheless, it is something worth at least considering.

Regardless of which route you opt for, you need to pay careful attention to the methodologies used in the relevant studies and provide at least some discussion about this in your write-up. Again, it’s useful to keep track of this on some sort of spreadsheet or catalogue as you digest each article, so consider grabbing a copy of our free literature catalogue if you don’t have anything in place.

Bringing It All Together

Alright, so we’ve looked at five important questions that you need to ask (and answer) to help you develop a strong synthesis within your literature review.  To recap, these are:

• Which things are broadly agreed upon within the current research?
• Which things are the subject of disagreement (or at least, present mixed findings)?
• Which theories seem to be central to your research topic and how do they relate or compare to each other?
• Which contexts have (and haven’t) been covered?
• Which methodological approaches are most common?

Importantly, you’re not just asking yourself these questions for the sake of asking them – they’re not just a reflection exercise. You need to weave your answers to them into your actual literature review when you write it up. How exactly you do this will vary from project to project depending on the structure you opt for, but you’ll still need to address them within your literature review, whichever route you go.

The best approach is to spend some time actually writing out your answers to these questions, as opposed to just thinking about them in your head. Putting your thoughts onto paper really helps you flesh out your thinking . As you do this, don’t just write down the answers – instead, think about what they mean in terms of the research gap you’ll present , as well as the methodological approach you’ll take . Your literature synthesis needs to lay the groundwork for these two things, so it’s essential that you link all of it together in your mind, and of course, on paper.

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 .

You Might Also Like:

excellent , thank you

Submit a Comment Cancel reply

Your email address will not be published. Required fields are marked *

Save my name, email, and website in this browser for the next time I comment.

• Print Friendly

The Sheridan Libraries

• Write a Literature Review
• Sheridan Libraries
• Find This link opens in a new window
• Evaluate This link opens in a new window

Get Organized

• Lit Review Prep Use this template to help you evaluate your sources, create article summaries for an annotated bibliography, and a synthesis matrix for your lit review outline.

Synthesize your Information

Synthesize: combine separate elements to form a whole.

Synthesis Matrix

A synthesis matrix helps you record the main points of each source and document how sources relate to each other.

After summarizing and evaluating your sources, arrange them in a matrix or use a citation manager to help you see how they relate to each other and apply to each of your themes or variables.  

By arranging your sources by theme or variable, you can see how your sources relate to each other, and can start thinking about how you weave them together to create a narrative.

• Step-by-Step Approach
• Example Matrix from NSCU
• Matrix Template
• << Previous: Summarize
• Next: Integrate >>
• Last Updated: Sep 26, 2023 10:25 AM
• URL: https://guides.library.jhu.edu/lit-review

• University of Oregon Libraries
• Research Guides

How to Write a Literature Review

• 6. Synthesize
• Literature Reviews: A Recap
• Reading Journal Articles
• Does it Describe a Literature Review?
• 1. Identify the Question
• 2. Review Discipline Styles
• Searching Article Databases
• Finding Full-Text of an Article
• Citation Chaining
• When to Stop Searching
• 4. Manage Your References
• 5. Critically Analyze and Evaluate

Synthesis Visualization

Synthesis matrix example.

• 7. Write a Literature Review

• Synthesis Worksheet

About Synthesis

Approaches to synthesis.

You can sort the literature in various ways, for example:

How to Begin?

Read your sources carefully and find the main idea(s) of each source

Look for similarities in your sources – which sources are talking about the same main ideas? (for example, sources that discuss the historical background on your topic)

Use the worksheet (above) or synthesis matrix (below) to get organized

This work can be messy. Don't worry if you have to go through a few iterations of the worksheet or matrix as you work on your lit review!

Four Examples of Student Writing

In the four examples below, only ONE shows a good example of synthesis: the fourth column, or  Student D . For a web accessible version, click the link below the image.

Long description of "Four Examples of Student Writing" for web accessibility

• Download a copy of the "Four Examples of Student Writing" chart

Click on the example to view the pdf.

From Jennifer Lim

• << Previous: 5. Critically Analyze and Evaluate
• Next: 7. Write a Literature Review >>
• Last Updated: May 3, 2024 5:17 PM
• URL: https://researchguides.uoregon.edu/litreview

Contact Us Library Accessibility UO Libraries Privacy Notices and Procedures

1501 Kincaid Street Eugene, OR 97403 P: 541-346-3053 F: 541-346-3485

• Visit us on Facebook
• Visit us on Twitter
• Visit us on Youtube
• Visit us on Instagram
• Report a Concern
• Nondiscrimination and Title IX
• Accessibility
• Privacy Policy
• Find People

How to Synthesize Written Information from Multiple Sources

Shona McCombes

Content Manager

B.A., English Literature, University of Glasgow

Shona McCombes is the content manager at Scribbr, Netherlands.

Learn about our Editorial Process

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

On This Page:

When you write a literature review or essay, you have to go beyond just summarizing the articles you’ve read – you need to synthesize the literature to show how it all fits together (and how your own research fits in).

Synthesizing simply means combining. Instead of summarizing the main points of each source in turn, you put together the ideas and findings of multiple sources in order to make an overall point.

At the most basic level, this involves looking for similarities and differences between your sources. Your synthesis should show the reader where the sources overlap and where they diverge.

Unsynthesized Example

Franz (2008) studied undergraduate online students. He looked at 17 females and 18 males and found that none of them liked APA. According to Franz, the evidence suggested that all students are reluctant to learn citations style. Perez (2010) also studies undergraduate students. She looked at 42 females and 50 males and found that males were significantly more inclined to use citation software ( p < .05). Findings suggest that females might graduate sooner. Goldstein (2012) looked at British undergraduates. Among a sample of 50, all females, all confident in their abilities to cite and were eager to write their dissertations.

Synthesized Example

Studies of undergraduate students reveal conflicting conclusions regarding relationships between advanced scholarly study and citation efficacy. Although Franz (2008) found that no participants enjoyed learning citation style, Goldstein (2012) determined in a larger study that all participants watched felt comfortable citing sources, suggesting that variables among participant and control group populations must be examined more closely. Although Perez (2010) expanded on Franz’s original study with a larger, more diverse sample…

Step 1: Organize your sources

After collecting the relevant literature, you’ve got a lot of information to work through, and no clear idea of how it all fits together.

Before you can start writing, you need to organize your notes in a way that allows you to see the relationships between sources.

One way to begin synthesizing the literature is to put your notes into a table. Depending on your topic and the type of literature you’re dealing with, there are a couple of different ways you can organize this.

Summary table

A summary table collates the key points of each source under consistent headings. This is a good approach if your sources tend to have a similar structure – for instance, if they’re all empirical papers.

Each row in the table lists one source, and each column identifies a specific part of the source. You can decide which headings to include based on what’s most relevant to the literature you’re dealing with.

For example, you might include columns for things like aims, methods, variables, population, sample size, and conclusion.

For each study, you briefly summarize each of these aspects. You can also include columns for your own evaluation and analysis.

The summary table gives you a quick overview of the key points of each source. This allows you to group sources by relevant similarities, as well as noticing important differences or contradictions in their findings.

Synthesis matrix

A synthesis matrix is useful when your sources are more varied in their purpose and structure – for example, when you’re dealing with books and essays making various different arguments about a topic.

Each column in the table lists one source. Each row is labeled with a specific concept, topic or theme that recurs across all or most of the sources.

Then, for each source, you summarize the main points or arguments related to the theme.

The purposes of the table is to identify the common points that connect the sources, as well as identifying points where they diverge or disagree.

Step 2: Outline your structure

Now you should have a clear overview of the main connections and differences between the sources you’ve read. Next, you need to decide how you’ll group them together and the order in which you’ll discuss them.

For shorter papers, your outline can just identify the focus of each paragraph; for longer papers, you might want to divide it into sections with headings.

There are a few different approaches you can take to help you structure your synthesis.

If your sources cover a broad time period, and you found patterns in how researchers approached the topic over time, you can organize your discussion chronologically .

That doesn’t mean you just summarize each paper in chronological order; instead, you should group articles into time periods and identify what they have in common, as well as signalling important turning points or developments in the literature.

If the literature covers various different topics, you can organize it thematically .

That means that each paragraph or section focuses on a specific theme and explains how that theme is approached in the literature.

Source Used with Permission: The Chicago School

If you’re drawing on literature from various different fields or they use a wide variety of research methods, you can organize your sources methodologically .

That means grouping together studies based on the type of research they did and discussing the findings that emerged from each method.

If your topic involves a debate between different schools of thought, you can organize it theoretically .

That means comparing the different theories that have been developed and grouping together papers based on the position or perspective they take on the topic, as well as evaluating which arguments are most convincing.

Step 3: Write paragraphs with topic sentences

What sets a synthesis apart from a summary is that it combines various sources. The easiest way to think about this is that each paragraph should discuss a few different sources, and you should be able to condense the overall point of the paragraph into one sentence.

This is called a topic sentence , and it usually appears at the start of the paragraph. The topic sentence signals what the whole paragraph is about; every sentence in the paragraph should be clearly related to it.

A topic sentence can be a simple summary of the paragraph’s content:

“Early research on [x] focused heavily on [y].”

For an effective synthesis, you can use topic sentences to link back to the previous paragraph, highlighting a point of debate or critique:

“Several scholars have pointed out the flaws in this approach.” “While recent research has attempted to address the problem, many of these studies have methodological flaws that limit their validity.”

By using topic sentences, you can ensure that your paragraphs are coherent and clearly show the connections between the articles you are discussing.

As you write your paragraphs, avoid quoting directly from sources: use your own words to explain the commonalities and differences that you found in the literature.

Don’t try to cover every single point from every single source – the key to synthesizing is to extract the most important and relevant information and combine it to give your reader an overall picture of the state of knowledge on your topic.

Step 4: Revise, edit and proofread

Like any other piece of academic writing, synthesizing literature doesn’t happen all in one go – it involves redrafting, revising, editing and proofreading your work.

Checklist for Synthesis

•   Do I introduce the paragraph with a clear, focused topic sentence?
•   Do I discuss more than one source in the paragraph?
•   Do I mention only the most relevant findings, rather than describing every part of the studies?
•   Do I discuss the similarities or differences between the sources, rather than summarizing each source in turn?
•   Do I put the findings or arguments of the sources in my own words?
•   Is the paragraph organized around a single idea?
•   Is the paragraph directly relevant to my research question or topic?
•   Is there a logical transition from this paragraph to the next one?

Further Information

How to Synthesise: a Step-by-Step Approach

Help…I”ve Been Asked to Synthesize!

Learn how to Synthesise (combine information from sources)

How to write a Psychology Essay

Library Guides

Literature reviews: synthesis.

• Criticality

Synthesise Information

So, how can you create paragraphs within your literature review that demonstrates your knowledge of the scholarship that has been done in your field of study?  

You will need to present a synthesis of the texts you read.  

Doug Specht, Senior Lecturer at the Westminster School of Media and Communication, explains synthesis for us in the following video:  

Synthesising Texts  

What is synthesis? 

Synthesis is an important element of academic writing, demonstrating comprehension, analysis, evaluation and original creation.  

With synthesis you extract content from different sources to create an original text. While paraphrase and summary maintain the structure of the given source(s), with synthesis you create a new structure.  

The sources will provide different perspectives and evidence on a topic. They will be put together when agreeing, contrasted when disagreeing. The sources must be referenced.  

Perfect your synthesis by showing the flow of your reasoning, expressing critical evaluation of the sources and drawing conclusions.  

When you synthesise think of "using strategic thinking to resolve a problem requiring the integration of diverse pieces of information around a structuring theme" (Mateos and Sole 2009, p448). 

Synthesis is a complex activity, which requires a high degree of comprehension and active engagement with the subject. As you progress in higher education, so increase the expectations on your abilities to synthesise. 

How to synthesise in a literature review: 

Identify themes/issues you'd like to discuss in the literature review. Think of an outline.  

Read the literature and identify these themes/issues.  

Critically analyse the texts asking: how does the text I'm reading relate to the other texts I've read on the same topic? Is it in agreement? Does it differ in its perspective? Is it stronger or weaker? How does it differ (could be scope, methods, year of publication etc.). Draw your conclusions on the state of the literature on the topic.  

Start writing your literature review, structuring it according to the outline you planned.  

Put together sources stating the same point; contrast sources presenting counter-arguments or different points.  

Present your critical analysis.  

Always provide the references. 

The best synthesis requires a "recursive process" whereby you read the source texts, identify relevant parts, take notes, produce drafts, re-read the source texts, revise your text, re-write... (Mateos and Sole, 2009). 

What is good synthesis?  

The quality of your synthesis can be assessed considering the following (Mateos and Sole, 2009, p439):  

Integration and connection of the information from the source texts around a structuring theme. 

Selection of ideas necessary for producing the synthesis. 

Appropriateness of the interpretation.  

Elaboration of the content.  

Example of Synthesis

Original texts (fictitious): 

Synthesis: 

Animal experimentation is a subject of heated debate. Some argue that painful experiments should be banned. Indeed it has been demonstrated that such experiments make animals suffer physically and psychologically (Chowdhury 2012; Panatta and Hudson 2016). On the other hand, it has been argued that animal experimentation can save human lives and reduce harm on humans (Smith 2008). This argument is only valid for toxicological testing, not for tests that, for example, merely improve the efficacy of a cosmetic (Turner 2015). It can be suggested that animal experimentation should be regulated to only allow toxicological risk assessment, and the suffering to the animals should be minimised.   

Bibliography

Mateos, M. and Sole, I. (2009). Synthesising Information from various texts: A Study of Procedures and Products at Different Educational Levels. European Journal of Psychology of Education,  24 (4), 435-451. Available from https://doi.org/10.1007/BF03178760 [Accessed 29 June 2021].

• << Previous: Structure
• Next: Criticality >>
• Last Updated: Nov 18, 2023 10:56 PM
• URL: https://libguides.westminster.ac.uk/literature-reviews

CONNECT WITH US

Indiana University Indianapolis Indiana University Indianapolis IU Indianapolis

• Herron School of Art
• Ruth Lilly Law
• Ruth Lilly Medical
• School of Dentistry

Literature Review - A Self-Guided Tutorial

• Literature Reviews: A Recap
• Reading Journal Articles
• Does it describe a Literature Review?
• 1. Identify the question
• 2. Review discipline styles
• Searching article databases - video
• Finding the article full-text
• Citation chaining
• When to stop searching
• 4. Manage your references
• 5. Critically analyze and evaluate
• 6. Synthesize
• 7. Write literature review

Who's My Librarian?

Locate your University Library's subject librarian  for personalized assistance.

Students doing research in specific areas may also request assistance at other IUPUI libraries:

• IU School of Dentistry Library
• Ruth Lilly Law Library
• Ruth Lilly Medical Library  

You can sort the literature in various ways, for example:

Synthesis Matrix Example

From Jennifer Lim

• << Previous: 5. Critically analyze and evaluate
• Next: 7. Write literature review >>
• Last Updated: Jun 15, 2023 8:24 AM
• URL: https://iupui.libguides.com/literaturereview

Literature Review How To

• Things To Consider
• Synthesizing Sources
• Video Tutorials
• Books On Literature Reviews

What is Synthesis

What is Synthesis? Synthesis writing is a form of analysis related to comparison and contrast, classification and division. On a basic level, synthesis requires the writer to pull together two or more summaries, looking for themes in each text. In synthesis, you search for the links between various materials in order to make your point. Most advanced academic writing, including literature reviews, relies heavily on synthesis. (Temple University Writing Center)  

How To Synthesize Sources in a Literature Review

Literature reviews synthesize large amounts of information and present it in a coherent, organized fashion. In a literature review you will be combining material from several texts to create a new text – your literature review.

You will use common points among the sources you have gathered to help you synthesize the material. This will help ensure that your literature review is organized by subtopic, not by source. This means various authors' names can appear and reappear throughout the literature review, and each paragraph will mention several different authors. 

When you shift from writing summaries of the content of a source to synthesizing content from sources, there is a number things you must keep in mind: 

• Look for specific connections and or links between your sources and how those relate to your thesis or question.
• When writing and organizing your literature review be aware that your readers need to understand how and why the information from the different sources overlap.
• Organize your literature review by the themes you find within your sources or themes you have identified. 
• << Previous: Things To Consider
• Next: Video Tutorials >>
• Last Updated: Nov 30, 2018 4:51 PM
• URL: https://libguides.csun.edu/literature-review

Report ADA Problems with Library Services and Resources

Literature Review Basics

• What is a Literature Review?
• Synthesizing Research
• Using Research & Synthesis Tables
• Additional Resources

Synthesis: What is it?

First, let's be perfectly clear about what synthesizing your research isn't :

• - It isn't  just summarizing the material you read
• - It isn't  generating a collection of annotations or comments (like an annotated bibliography)
• - It isn't  compiling a report on every single thing ever written in relation to your topic

When you  synthesize  your research, your job is to help your reader understand the current state of the conversation on your topic, relative to your research question.  That may include doing the following:

• - Selecting and using representative work on the topic
• - Identifying and discussing trends in published data or results
• - Identifying and explaining the impact of common features (study populations, interventions, etc.) that appear frequently in the literature
• - Explaining controversies, disputes, or central issues in the literature that are relevant to your research question
• - Identifying gaps in the literature, where more research is needed
• - Establishing the discussion to which your own research contributes and demonstrating the value of your contribution

Essentially, you're telling your reader where they are (and where you are) in the scholarly conversation about your project.

Synthesis: How do I do it?

Synthesis, step by step.

This is what you need to do  before  you write your review.

• Identify and clearly describe your research question (you may find the Formulating PICOT Questions table at  the Additional Resources tab helpful).
• Collect sources relevant to your research question.
• Organize and describe the sources you've found -- your job is to identify what  types  of sources you've collected (reviews, clinical trials, etc.), identify their  purpose  (what are they measuring, testing, or trying to discover?), determine the  level of evidence  they represent (see the Levels of Evidence table at the Additional Resources tab ), and briefly explain their  major findings . Use a Research Table to document this step.
• Study the information you've put in your Research Table and examine your collected sources, looking for  similarities  and  differences . Pay particular attention to  populations ,   methods  (especially relative to levels of evidence), and  findings .
• Analyze what you learn in (4) using a tool like a Synthesis Table. Your goal is to identify relevant themes, trends, gaps, and issues in the research.  Your literature review will collect the results of this analysis and explain them in relation to your research question.

Analysis tips

• - Sometimes, what you  don't  find in the literature is as important as what you do find -- look for questions that the existing research hasn't answered yet.
• - If any of the sources you've collected refer to or respond to each other, keep an eye on how they're related -- it may provide a clue as to whether or not study results have been successfully replicated.
• - Sorting your collected sources by level of evidence can provide valuable insight into how a particular topic has been covered, and it may help you to identify gaps worth addressing in your own work.
• << Previous: What is a Literature Review?
• Next: Using Research & Synthesis Tables >>
• Last Updated: Sep 26, 2023 12:06 PM
• URL: https://usi.libguides.com/literature-review-basics

• Walden University
• Faculty Portal

Using Evidence: Synthesis

Synthesis video playlist.

Note that these videos were created while APA 6 was the style guide edition in use. There may be some examples of writing that have not been updated to APA 7 guidelines.

Basics of Synthesis

As you incorporate published writing into your own writing, you should aim for synthesis of the material.

Synthesizing requires critical reading and thinking in order to compare different material, highlighting similarities, differences, and connections. When writers synthesize successfully, they present new ideas based on interpretations of other evidence or arguments. You can also think of synthesis as an extension of—or a more complicated form of—analysis. One main difference is that synthesis involves multiple sources, while analysis often focuses on one source.

Conceptually, it can be helpful to think about synthesis existing at both the local (or paragraph) level and the global (or paper) level.

Local Synthesis

Local synthesis occurs at the paragraph level when writers connect individual pieces of evidence from multiple sources to support a paragraph’s main idea and advance a paper’s thesis statement. A common example in academic writing is a scholarly paragraph that includes a main idea, evidence from multiple sources, and analysis of those multiple sources together.

Global Synthesis

Global synthesis occurs at the paper (or, sometimes, section) level when writers connect ideas across paragraphs or sections to create a new narrative whole. A literature review , which can either stand alone or be a section/chapter within a capstone, is a common example of a place where global synthesis is necessary. However, in almost all academic writing, global synthesis is created by and sometimes referred to as good cohesion and flow.

Synthesis in Literature Reviews

While any types of scholarly writing can include synthesis, it is most often discussed in the context of literature reviews. Visit our literature review pages for more information about synthesis in literature reviews.

Related Webinars

Didn't find what you need? Email us at [email protected] .

• Previous Page: Analysis
• Next Page: Citing Sources Properly
• Office of Student Disability Services

Walden Resources

Departments.

• Academic Residencies
• Academic Skills
• Career Planning and Development
• Customer Care Team
• Field Experience
• Military Services
• Student Success Advising
• Writing Skills

Centers and Offices

• Center for Social Change
• Office of Academic Support and Instructional Services
• Office of Degree Acceleration
• Office of Research and Doctoral Services
• Office of Student Affairs

Student Resources

• Doctoral Writing Assessment
• Form & Style Review
• Quick Answers
• ScholarWorks
• SKIL Courses and Workshops
• Walden Bookstore
• Walden Catalog & Student Handbook
• Student Safety/Title IX
• Legal & Consumer Information
• Website Terms and Conditions
• Cookie Policy
• Accessibility
• Accreditation
• State Authorization
• Net Price Calculator
• Contact Walden

Walden University is a member of Adtalem Global Education, Inc. www.adtalem.com Walden University is certified to operate by SCHEV © 2024 Walden University LLC. All rights reserved.

Chapter 5: Writing a Summary and Synthesizing

5.5 Synthesis and Literature Reviews

Literature reviews : synthesis and research.

Why do we seek to understand the ways that authors or sources “converse” with one another? So that we can synthesize various perspectives on a topic to more deeply understand it.

In academic writing, this understanding of the “conversation” may become the content of an explanatory  synthesis  paper – a paper in which you, the writer, point out various various themes or key points from a conversation on a particular topic. Notice that the example of synthesis in “What Synthesis Is” acknowledges that guns and gun control inspire passionate responses in Americans, that more than one kind of weapon is involved in gun violence, that guns in America are both legally and illegally owned, and that there are many constituencies whose experience with guns needs to considered if sound gun-control policy is to be achieved. The writer of this synthesis isn’t “pretending” to be objective (“Although gun violence is a problem in American today, people who want to increase gun control clearly don’t understand the Second Amendment”); nor is the writer arguing a point or attempting to persuade the audience to accept one perspective. The writer is making a claim about gun control that demonstrates his or her deepest understanding of the issue.

Another assignment that you may complete that also applies your synthesis skills is a l iterature review .  Literature reviews are often found in the beginning of scholarly journal articles to contextualize the author’s own research. Sometimes, literature reviews are done for their own sake; some scholarly articles are  just  Literature reviews.

Literature reviews (sometimes shortened to “lit reviews”) synthesize previous research that has been done on a particular topic, summarizing important works in the history of research on that topic. The literature review provides context for the author’s own new research. It is the basis and background out of which the author’s research grows. Context = credibility in academic writing. When writers are able to produce a literature review, they demonstrate the breadth of their knowledge about how others have already studied and discussed their topic.

• Literature reviews are most often  arranged by topic or theme , much like a traditional explanatory synthesis paper.
• If one is looking at a topic that has a long history of research and scholarship, one may conduct a chronological  literature review, one that looks at how the research topic has been studied and discussed in various time periods (i.e., what was published ten years ago, five years ago, and within the last year, for example).
• Finally, in some instances, one might seek to craft a literature review that is organized  by discipline or field. This type of literature review could offer information about how different academic fields have examined a particular topic (i.e., what is the current research being done by biologists on this topic? What is the current research being done by psychologists on this topic? What is the current research being done by [ insert academic discipline] on this topic?).

A Literature Review offers  only  a report on what others have already written about. The Literature Review does not reflect the author’s own argument or contributions to the field of research. Instead, it indicates that the author has read others’ important contributions and understands what has come before him or her. Sometimes, literature reviews are stand alone assignments or publications. Sometimes, they fit into a larger essay or article (especially in many of the scholarly articles that you will read throughout college. For more information on how literature reviews are a part of scholarly articles, see chapter 10.5 )

A Guide to Rhetoric, Genre, and Success in First-Year Writing by Melanie Gagich & Emilie Zickel is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

Feedback/Errata

Comments are closed.

Want to create or adapt books like this? Learn more about how Pressbooks supports open publishing practices.

Chapter 7: Synthesizing Sources

Learning objectives.

At the conclusion of this chapter, you will be able to:

• synthesize key sources connecting them with the research question and topic area.

7.1 Overview of synthesizing

7.1.1 putting the pieces together.

Combining separate elements into a whole is the dictionary definition of synthesis.  It is a way to make connections among and between numerous and varied source materials.  A literature review is not an annotated bibliography, organized by title, author, or date of publication.  Rather, it is grouped by topic to create a whole view of the literature relevant to your research question.

Your synthesis must demonstrate a critical analysis of the papers you collected as well as your ability to integrate the results of your analysis into your own literature review.  Each paper collected should be critically evaluated and weighed for “adequacy, appropriateness, and thoroughness” ( Garrard, 2017 ) before inclusion in your own review.  Papers that do not meet this criteria likely should not be included in your literature review.

Begin the synthesis process by creating a grid, table, or an outline where you will summarize, using common themes you have identified and the sources you have found. The summary grid or outline will help you compare and contrast the themes so you can see the relationships among them as well as areas where you may need to do more searching. Whichever method you choose, this type of organization will help you to both understand the information you find and structure the writing of your review.  Remember, although “the means of summarizing can vary, the key at this point is to make sure you understand what you’ve found and how it relates to your topic and research question” ( Bennard et al., 2014 ).

As you read through the material you gather, look for common themes as they may provide the structure for your literature review.  And, remember, research is an iterative process: it is not unusual to go back and search information sources for more material.

At one extreme, if you are claiming, ‘There are no prior publications on this topic,’ it is more likely that you have not found them yet and may need to broaden your search.  At another extreme, writing a complete literature review can be difficult with a well-trod topic.  Do not cite it all; instead cite what is most relevant.  If that still leaves too much to include, be sure to reference influential sources…as well as high-quality work that clearly connects to the points you make. ( Klingner, Scanlon, & Pressley, 2005 ).

7.2 Creating a summary table

Literature reviews can be organized sequentially or by topic, theme, method, results, theory, or argument.  It’s important to develop categories that are meaningful and relevant to your research question.  Take detailed notes on each article and use a consistent format for capturing all the information each article provides.  These notes and the summary table can be done manually, using note cards.  However, given the amount of information you will be recording, an electronic file created in a word processing or spreadsheet is more manageable. Examples of fields you may want to capture in your notes include:

• Authors’ names
• Article title
• Publication year
• Main purpose of the article
• Methodology or research design
• Participants
• Measurement
• Conclusions

  Other fields that will be useful when you begin to synthesize the sum total of your research:

• Specific details of the article or research that are especially relevant to your study
• Key terms and definitions
• Strengths or weaknesses in research design
• Relationships to other studies
• Possible gaps in the research or literature (for example, many research articles conclude with the statement “more research is needed in this area”)
• Finally, note how closely each article relates to your topic.  You may want to rank these as high, medium, or low relevance.  For papers that you decide not to include, you may want to note your reasoning for exclusion, such as ‘small sample size’, ‘local case study,’ or ‘lacks evidence to support assertion.’

This short video demonstrates how a nursing researcher might create a summary table.

7.2.1 Creating a Summary Table

  Summary tables can be organized by author or by theme, for example:

For a summary table template, see http://blogs.monm.edu/writingatmc/files/2013/04/Synthesis-Matrix-Template.pdf

7.3 Creating a summary outline

An alternate way to organize your articles for synthesis it to create an outline. After you have collected the articles you intend to use (and have put aside the ones you won’t be using), it’s time to identify the conclusions that can be drawn from the articles as a group.

  Based on your review of the collected articles, group them by categories.  You may wish to further organize them by topic and then chronologically or alphabetically by author.  For each topic or subtopic you identified during your critical analysis of the paper, determine what those papers have in common.  Likewise, determine which ones in the group differ.  If there are contradictory findings, you may be able to identify methodological or theoretical differences that could account for the contradiction (for example, differences in population demographics).  Determine what general conclusions you can report about the topic or subtopic as the entire group of studies relate to it.  For example, you may have several studies that agree on outcome, such as ‘hands on learning is best for science in elementary school’ or that ‘continuing education is the best method for updating nursing certification.’ In that case, you may want to organize by methodology used in the studies rather than by outcome.

Organize your outline in a logical order and prepare to write the first draft of your literature review.  That order might be from broad to more specific, or it may be sequential or chronological, going from foundational literature to more current.  Remember, “an effective literature review need not denote the entire historical record, but rather establish the raison d’etre for the current study and in doing so cite that literature distinctly pertinent for theoretical, methodological, or empirical reasons.” ( Milardo, 2015, p. 22 ).

As you organize the summarized documents into a logical structure, you are also appraising and synthesizing complex information from multiple sources.  Your literature review is the result of your research that synthesizes new and old information and creates new knowledge.

7.4 Additional resources:

Literature Reviews: Using a Matrix to Organize Research / Saint Mary’s University of Minnesota

Literature Review: Synthesizing Multiple Sources / Indiana University

Writing a Literature Review and Using a Synthesis Matrix / Florida International University

 Sample Literature Reviews Grid / Complied by Lindsay Roberts

Select three or four articles on a single topic of interest to you. Then enter them into an outline or table in the categories you feel are important to a research question. Try both the grid and the outline if you can to see which suits you better. The attached grid contains the fields suggested in the video .

Literature Review Table  

Test yourself.

• Select two articles from your own summary table or outline and write a paragraph explaining how and why the sources relate to each other and your review of the literature.
• In your literature review, under what topic or subtopic will you place the paragraph you just wrote?

Image attribution

Literature Reviews for Education and Nursing Graduate Students Copyright © by Linda Frederiksen is licensed under a Creative Commons Attribution 4.0 International License , except where otherwise noted.

Share This Book

Purdue Online Writing Lab Purdue OWL® College of Liberal Arts

Synthesizing Sources

Welcome to the Purdue OWL

This page is brought to you by the OWL at Purdue University. When printing this page, you must include the entire legal notice.

Copyright ©1995-2018 by The Writing Lab & The OWL at Purdue and Purdue University. All rights reserved. This material may not be published, reproduced, broadcast, rewritten, or redistributed without permission. Use of this site constitutes acceptance of our terms and conditions of fair use.

When you look for areas where your sources agree or disagree and try to draw broader conclusions about your topic based on what your sources say, you are engaging in synthesis. Writing a research paper usually requires synthesizing the available sources in order to provide new insight or a different perspective into your particular topic (as opposed to simply restating what each individual source says about your research topic).

Note that synthesizing is not the same as summarizing.  

• A summary restates the information in one or more sources without providing new insight or reaching new conclusions.
• A synthesis draws on multiple sources to reach a broader conclusion.

There are two types of syntheses: explanatory syntheses and argumentative syntheses . Explanatory syntheses seek to bring sources together to explain a perspective and the reasoning behind it. Argumentative syntheses seek to bring sources together to make an argument. Both types of synthesis involve looking for relationships between sources and drawing conclusions.

In order to successfully synthesize your sources, you might begin by grouping your sources by topic and looking for connections. For example, if you were researching the pros and cons of encouraging healthy eating in children, you would want to separate your sources to find which ones agree with each other and which ones disagree.

After you have a good idea of what your sources are saying, you want to construct your body paragraphs in a way that acknowledges different sources and highlights where you can draw new conclusions.

As you continue synthesizing, here are a few points to remember:

• Don’t force a relationship between sources if there isn’t one. Not all of your sources have to complement one another.
• Do your best to highlight the relationships between sources in very clear ways.
• Don’t ignore any outliers in your research. It’s important to take note of every perspective (even those that disagree with your broader conclusions).

Example Syntheses

Below are two examples of synthesis: one where synthesis is NOT utilized well, and one where it is.

Parents are always trying to find ways to encourage healthy eating in their children. Elena Pearl Ben-Joseph, a doctor and writer for KidsHealth , encourages parents to be role models for their children by not dieting or vocalizing concerns about their body image. The first popular diet began in 1863. William Banting named it the “Banting” diet after himself, and it consisted of eating fruits, vegetables, meat, and dry wine. Despite the fact that dieting has been around for over a hundred and fifty years, parents should not diet because it hinders children’s understanding of healthy eating.

In this sample paragraph, the paragraph begins with one idea then drastically shifts to another. Rather than comparing the sources, the author simply describes their content. This leads the paragraph to veer in an different direction at the end, and it prevents the paragraph from expressing any strong arguments or conclusions.

An example of a stronger synthesis can be found below.

Parents are always trying to find ways to encourage healthy eating in their children. Different scientists and educators have different strategies for promoting a well-rounded diet while still encouraging body positivity in children. David R. Just and Joseph Price suggest in their article “Using Incentives to Encourage Healthy Eating in Children” that children are more likely to eat fruits and vegetables if they are given a reward (855-856). Similarly, Elena Pearl Ben-Joseph, a doctor and writer for Kids Health , encourages parents to be role models for their children. She states that “parents who are always dieting or complaining about their bodies may foster these same negative feelings in their kids. Try to keep a positive approach about food” (Ben-Joseph). Martha J. Nepper and Weiwen Chai support Ben-Joseph’s suggestions in their article “Parents’ Barriers and Strategies to Promote Healthy Eating among School-age Children.” Nepper and Chai note, “Parents felt that patience, consistency, educating themselves on proper nutrition, and having more healthy foods available in the home were important strategies when developing healthy eating habits for their children.” By following some of these ideas, parents can help their children develop healthy eating habits while still maintaining body positivity.

In this example, the author puts different sources in conversation with one another. Rather than simply describing the content of the sources in order, the author uses transitions (like "similarly") and makes the relationship between the sources evident.

Synthesising the literature as part of a literature review

Affiliation.

• 1 University of Manchester, England.
• PMID: 25783281
• DOI: 10.7748/ns.29.29.44.e8957

This article examines how to synthesise and critique research literature. To place the process of synthesising the research literature into context, the article explores the critiquing process by breaking it down into seven sequential steps. The article explains how and why these steps need to be kept in mind if a robust comprehensive literature search and analysis are to be achieved. The article outlines how to engage in the critiquing process and explains how the literature review needs to be assembled to generate a logical and reasoned debate to examine a topic of interest or research in more detail.

Keywords: Critical analysis; critique; evaluation; integrative review; literature review; literature search; research; research question; search strategy; synthesis.

• Research / standards*
• Research Design*
• Review Literature as Topic*

Subject Guides

Literature Review and Evidence Synthesis

• Reviews as Assignments
• Annotated Bibliography
• Narrative Literature Review
• Integrative Review
• Scoping Review This link opens in a new window
• Systematic Review This link opens in a new window
• Other Review Types
• Subject Librarian Assistance with Reviews
• Grey Literature This link opens in a new window

Citation Managers

Review tools.

Citation managers are tools that can help you stay organized during the searching stage of a systematic review. 

• Keep track of  search results
• De-deduplicate your search results
• Allow for group projects
• Provide notification of retracted articles
• Cite and Write capabilities
• Bibliographic formatting

Citation Management Subject Guide : a library guide which provides details regarding the various types of citation managers and other resources. 

Covidence:  

• Covidence is a web-based screening and data extraction tool
• Covidence Knowledge Base tutorials
• Covidence Academy
• Introductory demonstration video

Rayyan:  

• An AI powered tool for systematic reviews

Citation Chaser

Citation Chaser can be used to easily identify articles that are citing or are being cited by specific articles you have identified as being relevant to your research topic.

PubMed PubReMiner

The PubMed PubReMiner can be used to identify the most used subject headings for your exemplar articles, to help you identify relevant MeSH terms for your search strategy.

Yale MeSH Analyzer

A MeSH analysis grid can help identify the problems in your search strategy by presenting the ways articles are indexed in the MEDLINE database in an easy-to-scan tabular format. Librarians can then easily scan the grid and identify appropriate MesH terms, term variants, indexing consistency, and the reasons why some articles are retrieved and others are not. This inevitably leads to fresh iterations of the search strategy to include missing important terms.

MeSH On Demand

This simple tool from the NLM will automatically identify potential MeSH terms for a given text, such as a title, abstract, or research question.

Medsyntax  

Medsyntax is  a free, open-source tool for visualizing and editing literature searches. It transforms search terms into HTML elements to visualize the search strategy effectively, provides an inline scope-driven editor and offers real-time error detection. 

Polyglot Search

Polyglot is a tool that will automatically translate your search from PubMed to other major databases such as Scopus and CINAHL. Note that Polyglot can only translate search syntax, so you will still need to manually translate your controlled vocabulary terms.

Systematic Review Accelator

The Systematic Review Accelerator is a collection of tools to help automate and streamline the SR process.

The Systematic Review Toolbox

The Systematic Review Toolbox is an online catalogue of tools that support various tasks within the systematic review and wider evidence synthesis process. You can use the toolbox to search for help with a specific task, or browse tools by what stage of the systematic review you are working on.

• << Previous: Grey Literature
• Last Updated: May 7, 2024 3:25 PM
• URL: https://libraryguides.binghamton.edu/literaturereview
• share facebook
• share twitter
• share pinterest
• share linkedin
• share email

ChatGPT in higher education - a synthesis of the literature and a future research agenda

• Open access
• Published: 02 May 2024

Cite this article

You have full access to this open access article

• Pritpal Singh Bhullar 1 ,
• Mahesh Joshi 2 &
• Ritesh Chugh   ORCID: orcid.org/0000-0003-0061-7206 3  

1011 Accesses

20 Altmetric

Explore all metrics

ChatGPT has emerged as a significant subject of research and exploration, casting a critical spotlight on teaching and learning practices in the higher education domain. This study examines the most influential articles, leading journals, and productive countries concerning citations and publications related to ChatGPT in higher education, while also shedding light on emerging thematic and geographic clusters within research on ChatGPT’s role and challenges in teaching and learning at higher education institutions. Forty-seven research papers from the Scopus database were shortlisted for bibliometric analysis. The findings indicate that the use of ChatGPT in higher education, particularly issues of academic integrity and research, has been studied extensively by scholars in the United States, who have produced the largest volume of publications, alongside the highest number of citations. This study uncovers four distinct thematic clusters (academic integrity, learning environment, student engagement, and scholarly research) and highlights the predominant areas of focus in research related to ChatGPT in higher education, including student examinations, academic integrity, student learning, and field-specific research, through a country-based bibliographic analysis. Plagiarism is a significant concern in the use of ChatGPT, which may reduce students’ ability to produce imaginative, inventive, and original material. This study offers valuable insights into the current state of ChatGPT in higher education literature, providing essential guidance for scholars, researchers, and policymakers.

Similar content being viewed by others

Students’ voices on generative AI: perceptions, benefits, and challenges in higher education

Artificial Intelligence (AI) Student Assistants in the Classroom: Designing Chatbots to Support Student Success

Examining science education in chatgpt: an exploratory study of generative artificial intelligence.

Avoid common mistakes on your manuscript.

1 Introduction

ChatGPT, or Chat Generative Pre-trained Transformer, is a popular generative Artificial Intelligence (AI) chatbot developed by OpenAI, employing natural language processing to deliver interactive human-like conversational experiences (Jeon et al., 2023 ; Angelis et al., 2023 ). ChatGPT utilises a pre-trained language learning model, derived from an extensive big-data corpus, to predict outcomes based on a given prompt (Crawford et al., 2023 ; Geerling et al., 2023 ; Li et al., 2023 ). Since its inception, ChatGPT has attracted widespread attention and popularity and has the potential to disrupt the education sector (Rana, 2023 ). According to a research survey of adults conducted by the Pew Research Centre, approximately 60% of adults in the United States and 78% of adults in Asia possess knowledge of ChatGPT; furthermore, men are more familiar with ChatGPT than women (Vogels, 2023 ). The study also found that among ethnic groups globally, individuals of Asian descent have the highest level of familiarity with AI-based large language models (LLMs).

People have found value in using ChatGPT for a wide range of purposes, including generating creative content, answering questions, providing explanations, offering suggestions, and even having casual conversations (Crawford et al., 2023 ; Throp, 2023 ; Wu et al., 2023 ). Furthermore, ChatGPT is an effective digital assistant for facilitating a thorough understanding of diverse and intricate subjects using simple and accessible language. Given these features, ChatGPT has the potential to bring about a paradigm shift in traditional methods of delivering instruction and revolutionise the future of education (Tlili et al., 2023 ). ChatGPT stands out as a promising tool for open education, enhancing the independence and autonomy of autodidactic learners through personalised support, guidance, and feedback, potentially fostering increased motivation and engagement (Firat, 2023 ). Its capabilities encompass facilitating complex learning, asynchronous communication, feedback provision, and cognitive offloading (Memarian & Doleck, 2023 ).

However, the rapid expansion of ChatGPT has also aroused apprehensions in the academic world, particularly after reports surfaced that the New York Department of Education had unexpectedly imposed a ban on access to the tool due to concerns about academic integrity violations (Sun et al., 2023 ; Neumann et al., 2023 ; Crawford et al., 2023 ). Students who use ChatGPT to produce superior written assignments may have an unfair advantage over peers who lack access (Farrokhnia et al., 2023 ; Cotton et al., 2023 ). Ethical concerns about the deployment of LLMs include the potential for bias, effects on employment, misuse and unethical deployment, and loss of integrity. However, there has been little research on the potential dangers that a sophisticated chatbot such as ChatGPT poses in the realm of higher education, particularly through the lens of a systematic literature review and bibliometric techniques.

In this light, this paper explores the literature on the application of ChatGPT in higher education institutions and the obstacles encountered in various disciplines from the perspectives of both faculty and students. The paper aims to analyse the current state of the field by addressing the following overarching research questions using bibliographic coupling, co-occurrence analysis, citation analysis, and co-authorship analysis:

What are the most influential articles in terms of citations in research related to ChatGPT in education?

What are the top journals and countries in terms of publication productivity related to the implications of ChatGPT in higher education institutions?

What are the emerging thematic clusters in research on the role and challenges of ChatGPT in teaching and learning in higher education institutions?

What are the geographic clusters in research on the role and challenges of ChatGPT in teaching and learning in higher education institutions?

2 Methodology

In conducting this study, publications on the impact of ChatGPT on various aspects of higher education institutions were systematically identified through an extensive search using Elsevier’s Scopus database, a comprehensive repository hosting over 20,000 globally ranked, peer-reviewed journals (Mishra et al., 2017 ; Palomo et al., 2017 ; Vijaya & Mathur, 2023 ). Scopus is a widely used database for bibliometric analyses and is considered one of the “largest curated databases covering scientific journals” (pg. 5116) in different subject areas (Singh et al., 2021 ). Widely acclaimed for its comprehensive coverage, Scopus has been extensively employed in bibliometric analyses across diverse disciplines, as evidenced by studies in capital structure theories, business research, entrepreneurial orientation and blockchain security (Bajaj et al., 2020 ; Donthu et al., 2020 ; Gupta et al., 2021 ; Patrício & Ferreira, 2020 ). Notably, despite the “extremely high” correlation between the Web of Science and Scopus databases, Scopus’s status as a superior and versatile data source for literature extraction is reinforced by its broader coverage of subject areas and categories compared to the narrower journal scope of Web of Science, facilitating scholars in locating literature most pertinent to the review area (Archambault et al., 2009 ; Paul et al., 2021 ). To ensure a systematic literature review, we adhered to the preferred reporting items for systematic reviews and meta-analysis (PRISMA) guidelines (Page et al., 2021 ) for the search, identification, selection, reading, and data extraction from the articles retrieved through the Scopus database (Fig.  1 ). Reliance on a single database is acceptable within the PRISMA framework (Moher et al., 2009 ).

Employing Boolean-assisted search queries, we aimed to capture a comprehensive range of topics related to ChatGPT’s impact on higher education institutions. Specific search queries were carefully selected to ensure a broad yet relevant search scope and included the following:

“ChatGPT and Teaching learning in universities” OR “Effect of ChatGPT in higher education institution” OR “ChatGPT and student assessment in higher education” OR “ChatGPT and academic integrity” OR “ChatGPT and teaching pedagogy in higher education institution” OR “ChatGPT and cheating student course assignment” OR “ChatGPT and teaching in higher education” OR “Implications of ChatGPT in higher education institutions” OR “ChatGPT and evaluation criteria in higher education institution” OR “ChatGPT in universities” OR “ChatGPT and student learnings. ”

The study includes papers published and included in the Scopus database on or before May 26, 2023 on the theme of ChatGPT and higher education. This timeframe was chosen to encompass the most recent and relevant literature available up to the point of data retrieval. Papers identified through the search queries underwent inclusion or exclusion based on predetermined criteria. Specifically, only papers published in journals were considered for this study, as these undergo a peer-review process and are subject to stringent selection criteria set by the journals, ensuring their quality and reliability. Papers in conference proceedings were excluded from the start of the search. Only papers written in English were included to maintain consistency and clarity, whereas others were excluded. Of the 48 research papers that were initially identified, 47 were ultimately selected for the bibliometric analysis, which was conducted using VOSviewer, a bibliometric analysis tool.

PRISMA Flowchart

From the identified pool of 47 articles, the analysis uncovered a nuanced distribution of research methodologies. Specifically, 11 studies were grounded in quantitative research methodologies, underscoring a quantitative focus within the literature. In contrast, a substantial majority of 31 articles embraced a qualitative framework, showcasing a diverse spectrum that included pure qualitative research, editorials, letters to the editor, and opinion pieces. Furthermore, the review brought to light four literature reviews, signifying a synthesis of existing knowledge, and identified one study that strategically employed a mixed-methods approach, blending both qualitative and quantitative research techniques.

To address the research questions, the selected publications underwent analysis using various bibliometric techniques. For the first and second research questions, citation analysis was employed. For the third and fourth research questions, bibliographic analysis was performed in VOSviewer software to generate clusters.

3 Findings and discussion

3.1 publication trend.

Information from the Scopus database indicates that academics began focusing on investigating various aspects of ChatGPT’s potential in higher education in 2022, as they published their findings in 2023. All academic articles in reputable publications in the Scopus database were published in 2023.

3.2 Citation analysis

Table  1 presents the top ten articles according to the number of citations. The number of articles increased significantly in 2023, consistent with the emerging nature and growing relevance of the topic. Exploring the ramifications of ChatGPT in higher education is a recent focal point for scholars, with numerous aspects warranting deeper investigation. The limited citation count, as anticipated, underscores that publications from 2023 are in the early stages of gaining visibility and recognition within the academic community.

The article by Thorp ( 2023 ), entitled “ChatGPT is fun, but not an author”, has received the highest number of citations (79). Thorp stresses the risks associated with implementing ChatGPT in the classroom. Although ChatGPT is an innovative AI tool, significant barriers remain to its implementation in the field of education. According to Thorp, using ChatGPT in academic writing is still inefficient. Thorp also expresses concerns about the rising prevalence of ChatGPT in the fabrication of scientific publications. The second most-cited work, “How Does ChatGPT Perform on the United States Medical Licensing Examination?” by Gilson and colleagues, has received 27 citations. Gilson et al. ( 2023 ) evaluated the accuracy, speed and clarity of ChatGPT’s responses to questions on the United States Medical Licensing Examination’s Step 1 and Step 2 tests. The text responses generated by ChatGPT were evaluated using three qualitative metrics: the logical justification of the chosen answer, the inclusion of information relevant to the question, and the inclusion of information extraneous to the question. The model attained a level of proficiency comparable to that of a third-year medical student. The study demonstrates the potential utility of ChatGPT as an interactive educational resource in the field of medicine to facilitate the acquisition of knowledge and skills. Third is Kasneci et al.’s article “ChatGPT for good? On opportunities and challenges of large language models for education”, with 13 citations. This paper examines the benefits and drawbacks of using language models in the classroom from the perspectives of both teachers and students. The authors find that these comprehensive language models can serve as a supplement rather than a replacement for classroom instruction. Each of the remaining top-ten articles mentioned the impact of ChatGPT on academic integrity in education and had received fewer than ten citations at the time of analysis.

Table  2 presents the top 10 journals in terms of the number of citations of publications related to the topic of ChatGPT in higher education. The journal Science , which published “ChatGPT is fun, but not an author,” was deemed most influential because it received the highest number of citations (79). JMIR Medical Education has published two articles that have been cited by 30 other research articles on the same topic. Journal of University Teaching and Learning Practise has published the most articles: three. Innovations in Education and Teaching International has published two articles on this topic, which together have been cited by six articles.

As shown in Table  3 , the majority of research articles pertaining to ChatGPT and higher education have originated from countries in Asia. Six of the top 10 countries for publishing articles on this topic are located in the Asian continent. However, the most influential studies in terms of citations have been produced by the United States, Germany, Australia, and the United Kingdom. Combined, these countries have received a total of 63 citations, with individual counts of 36, 17, 7, and 7, respectively. These four countries have 90% of the total citations of the top 10 most productive countries in the field of research on higher education perspectives on ChatGPT.

3.3 Bibliographic coupling

3.3.1 thematic clusters.

Four thematic clusters (TCs) were identified from the included research articles, as shown in Table  4 . VOSviewer was used to perform clustering based on bibliographic coupling. This method identifies relations between documents by examining publications that cite the same sources (Boyack & Klavans, 2010 ). VOSviewer clusters articles with a common knowledge base, assigning each publication to exactly one cluster. To implement this clustering technique, we assessed the co-occurrence of bibliographic references among articles within our dataset. Co-occurrence was determined by identifying shared references between articles, indicating a thematic connection (Boyack & Klavans, 2010 ). Articles sharing common references were considered to co-occur, enabling us to quantify the extent of thematic relationships based on the frequency of shared references. We identified and categorised thematic clusters within our dataset through the combined approach of VOSviewer clustering and co-occurrence analysis. This method typically results in a distribution of clusters, with a limited number of larger clusters and a more substantial number of smaller clusters.

The clusters were derived through an analysis of subordinate articles extracted from the Scopus database. VOSviewer systematically organised similar articles into distinct clusters based on the shared patterns of bibliographic references (Van Eck & Waltman, 2010 ). To ensure methodological transparency and robustness, we established clear criteria and parameters for clustering. Specifically, keywords with a minimum frequency ( n  = 5) were included in the analysis, and co-occurrence was calculated based on a pairwise comparison method. This systematic approach ensured the meaningful representation of thematic relationships within the dataset, guided by insights from previous literature (Jarneving, 2007 ). Using cluster analysis techniques, the articles were organised into cohesive groups characterised by the degree of thematic homogeneity guided by the nature of the research findings. This approach ensured a robust representation of the underlying thematic structure (Jarneving, 2007 ).

Furthermore, to mitigate the risk of subjective bias in thematic categorisation, a counter-coding approach was employed. A second researcher independently categorised thematic clusters identified by VOSviewer to assess inter-rater agreement. The level of agreement between the two researchers was assessed using Cohen’s kappa coefficient, ensuring the reliability and validity of the thematic classification process. The resulting kappa coefficient (0.69) indicated substantial agreement, suggesting a high level of agreement beyond what would be expected by chance alone (Gisev et al., 2013 ). Furthermore, the nomenclature assigned to each cluster was finalised based on the predominant research theme emerging from the analysis, providing a concise and informative label for each group.

TC1: ChatGPT and Academic Integrity: Cotton et al. ( 2023 ) describe ChatGPT as a double-edged sword that potentially threatens academic integrity. AI essay writing systems are programmed to churn out essays based on specific guidelines or prompts, and it can be difficult to distinguish between human and machine-generated writing. Thus, students could potentially use these systems to cheat by submitting essays that are not their original work (Dehouche, 2021 ). Kasneci et al. ( 2023 ) argue that effective pedagogical practices must be developed in order to implement large language models in classrooms. These skills include not only a deep understanding of the technology but also an appreciation of its constraints and the vulnerability of complex systems in general. In addition, educational institutions need to develop a clearly articulated plan for the successful integration and optimal use of big language models in educational contexts and teaching curricula. In addition, students need to be taught how to verify information through a teaching strategy emphasising critical thinking effectively. Possible bias in the generated output, the need for continuous human supervision, and the likelihood of unforeseen effects are just a few of the challenges that come with the employment of AI systems. Continuous monitoring and transparency are necessary to ensure academic integrity while using ChatGPT. Lim et al. ( 2023 ) report that ChatGPT poses academic integrity challenges for the faculty of higher education institutions, who must verify whether academic work (assignments, research reports, etc.) submitted by students is derived from the fresh perspective of data analysis or plagiarised and recycled (copying and pasting original work) by ChatGPT. ChatGPT may threaten student learning and classroom engagement if students have access to information and course assignments without assessing their integrity. Perkins ( 2023 ) also expresses concerns regarding academic integrity in the use of ChatGPT. Students are utilising ChatGPT to complete their course assignments without attribution rather than producing original work. Higher education institutions must establish clear boundaries regarding academic integrity and plagiarism in light of the growing utilisation of AI tools in academic and research settings. In addition, the challenges posed by AI essay writing systems like ChatGPT necessitate a multifaceted approach to safeguard academic integrity. Educational institutions should invest in comprehensive educational programs that not only teach students the ethical use of technology but also incorporate rigorous assessments of critical thinking skills. Additionally, integrating AI literacy into the curriculum, with a focus on understanding the limitations and potential biases of big language models, can empower students to discern between human and machine-generated content.

TC2: ChatGPT and Learning Environment: According to Crawford et al. ( 2023 ), increased stress levels and peer pressure among university students have created a favourable environment for the use of AI tools. ChatGPT provides enhanced educational opportunities for college-level students. It can help students identify areas they may have overlooked, offer guidance on additional reading materials, and enhance existing peer and teacher connections. In addition, ChatGPT can propose alternative methods of evaluating students beyond conventional assignments. Crawford et al. ( 2023 ) recommend providing practical assignments incorporating ChatGPT as a supplementary tool to reduce plagiarism. Su ( 2023 ) documents that ChatGPT can provide students with a personalised learning experience based on their specific needs. In addition, the ChatGPT platform can be used to create a virtual coaching system that offers prompt feedback to educators during their classroom evaluations. This approach fosters critical thinking and supports early childhood educators in refining their teaching methodologies to optimise interactive learning outcomes for students. Tang ( 2023b ) proposes that bolstering research integrity can be achieved by imposing restrictions on the utilisation of NLP-generated content in research papers. Additionally, the author advocates for transparency from researchers, emphasising the importance of explicitly stating the proportion of NLP-generated content incorporated in their papers. This recommendation prompts a critical examination of the role of AI-generated content in scholarly work, emphasising the importance of nurturing independent research and writing skills for both students and researchers.

TC3: ChatGPT and Student Engagement: Lee ( 2023 ) examines the ability of ChatGPT to provide an interactive learning experience and boost student engagement beyond textbook pedagogy. Iskender ( 2023 ) explains that ChatGPT provides a mechanism for students to generate and investigate diverse concepts expeditiously, thereby helping them engage in imaginative and evaluative thinking on specific subject matter. This approach has the potential to optimise time management for students and allow them to concentrate on more advanced cognitive activities. AI tools such as ChatGPT can potentially enhance the personalisation of learning materials by providing visual aids and summaries that can aid the learning process and significantly improve students’ competencies. Hence, leveraging ChatGPT in education can revolutionise learning by facilitating interactive experiences, nurturing imaginative thinking, and optimising time management for students.

TC4: ChatGPT and Scholarly Research: Ivanov and Soliman ( 2023 ) and Yan ( 2023 ) focus on the practical applications and implications of LLMs like ChatGPT in educational settings and scholarly research within the context of language learning, writing, and tourism. Yan’s investigation into ChatGPT’s application in second-language writing examines its effectiveness in addressing specific writing tasks at the undergraduate level. The findings underscore the nuanced balance between the strengths of ChatGPT and the inherent limitations in handling demanding academic writing tasks. Nevertheless, ChatGPT is also labelled as an ‘all-in-one’ solution for scholarly research and writing (Yan, 2023 ). In parallel, Ivanov and Soliman ( 2023 ) highlight that ChatGPT can assist scholars in the field of tourism research by composing preliminary literature reviews, substantiating their chosen methodologies, and creating visual aids such as tables and charts. Furthermore, the researchers outline that ChatGPT could provide valuable methodological ideas and insights by helping researchers generate questions and corresponding scales for inclusion in questionnaires. Hence, ChatGPT has the potential to become a valuable ally as a facilitator in academic writing processes and has the potential to transform the research workflow.

3.3.2 Geographic clusters

The results of the country-based bibliographic analysis are summarised in Table  5 . The present study utilised the prevailing research theme in the existing literature as a framework for categorising the countries into four distinct clusters on the basis of the number of documents published from different countries.

Cluster 1: Implications of ChatGPT for Student Examinations and Education : Cluster 1 is composed of five countries: Germany, Ireland, South Korea, Taiwan, and the United States. Researchers in these countries have emphasised the potential role of ChatGPT in higher education within the context of AI language models. Eleven research articles related to this theme were published by researchers based in the United States, the most in this cluster. The top three articles in Table  1 are from the United States. The study entitled “Opportunities and Challenges of Large Language Models for Education,” was authored by German researchers (Kasneci et al., 2023 ) and has been widely cited in the academic community (13 citations). The remaining studies were conducted by researchers from South Korea and Taiwan and focused on the impact of ChatGPT on the education sector and its associated opportunities and challenges. This cluster demonstrates that students could benefit greatly from using ChatGPT in performing various academic tasks, such as reviewing and revising their work, verifying the accuracy of homework answers, and improving the quality of their essays. It has also aided postgraduates whose first language is not English improve their writing, as ChatGPT can be instructed to rewrite a paragraph in a scholarly tone from scratch. The outcomes have demonstrated significant efficacy, thereby alleviating the cognitive load associated with translation for these students, enabling them to concentrate on the substance of their writing rather than the intricacies of composing in an unfamiliar language. To harness the potential benefits, future research could focus on developing targeted training programs for students and educators that emphasise the effective utilisation of ChatGPT to enhance not only academic tasks but also language proficiency for non-native English speakers, addressing both cognitive load and language intricacies.

Cluster 2: ChatGPT and Academic Integrity : Cluster 2 comprises research studies conducted by authors from Japan, Bangladesh, Hong Kong, Nigeria, Pakistan, UAE, the UK, Vietnam and the Netherlands. The most influential study in this cluster, “Unlocking the power of ChatGPT: A framework for applying Generative AI in education”, was authored by researchers from Hong Kong (Su & Yang, 2023 ). They document that ChatGPT can be used to respond to student inquiries, reducing the time and effort required of educators and allowing them to focus their resources on other activities, such as scholarly investigations. Farrokhnia et al. ( 2023 ) and Yeadon et al. ( 2023 ) state that ChatGPT can write scientific abstracts with fabricated data and essays that can evade detection by reviewers. According to Liebrenz et al. ( 2023 ), ChatGPT tends to produce erroneous and incoherent responses, thereby raising the potential for disseminating inaccurate information in scholarly literature. The higher-order cognitive abilities of ChatGPT are relatively low, especially in areas related to creativity, critical thinking, reasoning, and problem-solving. ChatGPT could reduce students’ motivation to explore topics independently, draw their own conclusions, and solve problems independently (Kasneci et al., 2023 ). Ibrahim et al. ( 2023 ) find that ChatGPT can engage students in their academic pursuits. ChatGPT can enhance the writing abilities of non-native English speakers to allow them to concentrate on higher-order cognitive processes. This technological development allows faculty members to allocate more attention to conceptualisation and writing rather than focusing on the mechanics of grammar and spelling. However, there is a debate among intellectuals regarding the implications of AI for content creation, with some asserting that it detracts from innovative content development. The possibility that ChatGPT threatens academic honesty by facilitating essay plagiarism is being acknowledged. In addition, in the absence of appropriate citations, this textual content may violate copyright regulations. Cotton et al. ( 2023 ) express concerns about the potential impact of ChatGPT on academic integrity and plagiarism. Their work corroborates Dehouche’s ( 2021 ) assertion that students may use ChatGPT to engage in academic dishonesty by submitting essays that are not their original work. According to Cotton et al. ( 2023 ), ChatGPT users have a competitive advantage over non-users and can achieve higher grades on their coursework assignments by utilising the AI-based language tool. They classify ChatGPT as a versatile instrument with the potential to pose a threat to academic integrity, noting that AI essay writing systems are specifically programmed to generate content based on specific parameters or prompts, thereby challenging the discernment between human-authored and machine-generated content. Distinguishing between the academic work produced by students and the content of ChatGPT when evaluating assignments is a significant challenge for faculty. It is recommended that academic staff continually monitor student assignments for academic misconduct infractions, coupled with transparent communication about the potential risks associated with AI-generated content.

Cluster 3: ChatGPT and Students’ Learning : Cluster 3 comprises Malaysia, China and Australia. This cluster mainly includes studies of the role of AI-based models in student learning. Researchers from Australia (Crawford et al., 2023 ; Lim et al., 2023 ; Lawrie, 2023 ; Li et al., 2023 ; Seth et al., 2023 ; Cingillioglu, 2023 ; Skavronskaya, 2023 ; and Johinke, 2023 ) have contributed the most (8 studies) to this cluster and put their weight behind the role of AI and student learning in various disciplines. One of the most influential papers, “Generative AI and the future of education: Ragnarök or reformation? A paradoxical perspective from management educators”, was authored by researchers from both Australia and Malaysia (Lim et al., 2023 ) and reflected on the role of AI in classroom learning and teaching. Rather than banning AI tools, the authors advocate for the productive use of these tools in classrooms to facilitate more engaging student learning. Another Australian study titled, “Leadership is needed for ethical ChatGPT: Character, assessment, and learning using artificial intelligence (AI)” (Crawford et al., 2023 ) highlights AI as an alternative path of learning for students. ChatGPT can promptly evaluate students’ assignments and help them identify areas of weakness. Educators have the option to provide innovative assessments to their students instead of adhering solely to conventional assessments. ChatGPT can augment pedagogical approaches, evaluation structures, and the comprehensive educational milieu by reinforcing the trilateral association among instructors, learners, and technology. The implementation of ChatGPT can provide students with a personalised and interactive learning and research experience facilitated by virtual tutors and customised recommendations. In light of the research in this cluster, the integration of ChatGPT into education should inspire a paradigm shift towards a more dynamic and personalised learning environment. Institutions can explore strategic partnerships with AI researchers to develop context-specific applications of ChatGPT that cater to diverse educational needs, promoting a symbiotic relationship between human instructors, students, and technology for an enriched learning experience.

Cluster 4: ChatGPT and Field-specific Research : This cluster includes research by authors in Asian and European countries (India, Oman, Bulgaria and New Zealand) that has emphasised the potential role of ChatGPT in the medical and tourism industries. Authors from India explored the role of ChatGPT in the medical field (Seetharaman, 2023 ; Subramani et al., 2023 ). Seetharaman ( 2023 ) reports that ChatGPT offers supplementary language assistance to students who are not proficient in English, enabling them to enhance their language proficiency and effectively communicate in English, the principal language of instruction in medical establishments. The ChatGPT platform has the potential to serve as a tool for medical students to replicate patient interactions in a simulated environment, such as accurately obtaining medical histories and documenting symptoms. According to Subramani et al. ( 2023 ), ChatGPT is a highly efficient and user-friendly AI technology that can aid healthcare professionals in various aspects, such as diagnosis, critical decision-making, and devising appropriate treatment plans. ChatGPT has demonstrated impressive performance on medical exams, indicating its potential as a valuable resource for enhancing medical education and assessment (Subramani et al., 2023 ) and can support interdisciplinarity in tourism research (Nautiyal et al., 2023 ). Ivanov and Soliman ( 2023 ) note the potential of ChatGPT to serve as a digital instructor to provide students with enhanced and effective learning experiences and outcomes. Digital instructors can impart knowledge in diverse languages and thus can be used to educate individuals of varying nationalities and backgrounds in the field of tourism. Furthermore, LLM-based chatbots, including ChatGPT, can assess written assignments and provide direction on linguistic proficiency, syntax, and composition, ultimately enhancing students’ scholarly writing proficiency. In exploring the intersection of ChatGPT with medical education, institutions can pioneer innovative approaches by using the platform to create immersive, simulated patient interactions that go beyond language assistance, allowing medical students to practice nuanced skills such as medical history gathering and symptom documentation. Simultaneously, leveraging ChatGPT as a versatile digital instructor offers a unique opportunity to provide cross-cultural and multilingual education, contributing to a more inclusive and globally competent workforce within the tourism industry.

3.4 Challenges of ChatGPT in higher education

In addition to some previously mentioned challenges, such as the potential for plagiarism, the investigation also identified other key challenges in implementing ChatGPT within the context of higher education’s teaching and learning environment. Wu and Yu ( 2023 ) found that the benefits of AI-based ChatGPT are more in higher education as compared to primary and secondary education. The study also reported that the novelty effects of AI chatbots may enhance learning outcomes in brief interventions, but their efficacy diminishes in longer interventions.

First, the implementation of ChatGPT within the educational context engenders learning impediments. In the absence of adequate monitoring and regulation, the technology could lead to human unintelligence and unlearning, but teachers will become more adaptive and create authentic assessments to enhance student learning (Alafnan et al., 2023 ; Lawrie, 2023 ). Second, the technology could be used in a manner that violates students’ privacy. If the model is not adequately secured, it could surreptitiously gather confidential data from students without their explicit awareness or authorisation (Kanseci, 2023). Third, the technology could facilitate discrimination against particular students. If the model is not trained on a dataset that accurately represents the entire student population, it has the potential to create disparities in educational access (Cingillioglu, 2023 ; Lin et al., 2023 ). Fourth, according to Ivanov and Soloman (2023), ChatGPT lacks access to real-time data. Therefore, its responses may be inconsequential, inaccurate, or outdated. The information provided in response to a specific query may also be insufficient. Gao et al. (2022) highlight the need for further investigation of the precision and scholarly authenticity of ChatGPT. Fifth, it may be difficult for ChatGPT to comprehend the context and subtleties of complex academic subjects and answer complex questions (Adetayo, 2023 ; Eysenbach, 2023 ; Neumann et al., 2023 ). The system can misinterpret inquiries, offer inadequate or inaccurate responses, or struggle to comprehend the fundamental purpose behind questions (Clark, 2023 ). In particular, ChatGPT may not have the requisite expertise in highly specialised or advanced subjects such as advanced mathematics or specific sciences. Hence, it may not deliver precise and accurate answers (Neumann et al., 2023 ; Fergus et al., 2023 ). Karaali ( 2023 ) claimed that the primary emphasis in the field of AI is currently directed towards the enhancement of advanced cognitive abilities and mental processes associated with quantitative literacy and quantitative reasoning. However, it is important to acknowledge that fundamental skills such as writing, critical thinking, and numeracy continue to serve as essential foundational components among students. Although AI is making significant progress in fundamental domains, it appears that students are experiencing a decline in performance in the context of fundamental skills. Consequently, NLP-based adaptive learner support and education require further investigation (Bauer et al., 2023 ).

In addressing the challenges of ChatGPT in education, educators need to adapt and develop authentic assessments that mitigate the risk of human unlearning, ensuring that technology enhances, rather than hinders, student learning experiences. Simultaneously, recognising the limitations of ChatGPT in comprehending the nuances of highly specialised subjects underscores the importance of balancing advancements in AI’s cognitive abilities with continued emphasis on fundamental skills like critical thinking, writing, and numeracy, urging a reevaluation of priorities in AI-driven educational research towards comprehensive learner support.

4 Conclusion, implications and agenda for future research

This study identified the most influential articles and top journals and countries in terms of citations and publication productivity related to ChatGPT in higher education, as well as highlighted emerging thematic clusters and geographic clusters in research on the role and challenges of ChatGPT in teaching and learning in higher education institutions. Articles on the topic of ChatGPT in higher education published up to May 2023 were identified by searching the Scopus database. Given the emergent nature of ChatGPT starting in late 2022, all the included articles were published in 2023. Thus, this specific research domain remains relatively unexplored. The findings of this analysis reveal that the United States is the most productive country in terms of research on the role of ChatGPT in higher education, especially relating to academic integrity and research. US researchers also emerged as the most influential in terms of number of citations in the literature. Our findings corroborate those of previous research (Crompton & Burke, 2023 ). However, 60% of the articles in our shortlisted literature emanated from Asian countries.

Four thematic clusters (academic integrity, student engagement, learning environment and research) were identified. Furthermore, the country-based bibliographic analysis revealed that research has focused on student examinations, academic integrity, student learning and field-specific research in medical and tourism education (Nautiyal et al., 2023 ; Subramani et al., 2023 ). Plagiarism is recognised as a major challenge that hinders students’ creativity, innovativeness and originality when using ChatGPT in their academic pursuits. To mitigate the potential drawbacks of using ChatGPT in educational and research settings, proactive measures should be taken to educate students and researchers alike on the nature of plagiarism, its negative impacts and academic integrity (Shoufan, 2023 ; Teixeira, 2023 ) Educators may ask students to provide a written acknowledgement of the authenticity of their assignments and their non-reliance on ChatGPT. Such an acknowledgement would discourage students from utilising ChatGPT in their academic and research endeavours and establish accountability for their academic pursuits. In addition, educators should develop authentic assessments that are ChatGPT-proof.

ChatGPT lacks emotional intelligence and empathy, both of which are crucial in effectively addressing the emotional and psychological dimensions of the learning process (Farrokhnia et al., 2023 ; Neumann et al., 2023 ). Higher education institutions may encounter challenges in using ChatGPT to deliver suitable assistance, comprehension, or direction to students needing emotional or mental health support. The significance of human interaction in learning cannot be overstated. Achieving a balance between using AI and the advantages of human guidance and mentorship is a persistent challenge that requires attention (Neumann et al., 2023 ; Rahman et al., 2023 ). Strzelecki ( 2023 ) observed in his research that behavioural intention and personal innovativeness are the two major determinants behind the adoption of ChatGPT among students.

4.1 Implications

The findings of the present study have numerous important implications. This study provides insight into the current state of ChatGPT in higher education and thus can serve as valuable guidance for academics, practitioners, and policymakers. The study’s findings contribute to the literature by providing new insights into the role of ChatGPT and strategies for mitigating its negative aspects and emphasising its positive attributes.

First, the implementation of AI in education can improve academic performance and student motivation, particularly by facilitating personalised learning. Educational institutions should monitor and regulate students’ use of such technologies proactively. Higher education institutions also ought to prioritise the training of their educators in effectively utilising AI technologies, including ChatGPT. Concurrently, it is imperative for these institutions to equip students with comprehensive academic integrity training, shedding light on the appropriate and inappropriate applications of AI tools like ChatGPT. This includes creating awareness about the potential consequences of utilising these technologies for dishonest practices. Furthermore, educational establishments need to urgently revisit and refine their academic integrity policies to address the evolving landscape shaped by the integration of artificial intelligence tools in various academic facets. This proactive approach will foster a learning environment that embraces technological advancements and upholds the principles of honesty and responsible use. Institutional regulations on accountability and transparency should guide the frameworks that govern the use of AI in the campus environment (Pechenkina, 2023 ; Sun & Hoelscher, 2023 ; Dencik & Sanchez-Monedero, 2022 ).

Second, faculty members must proactively replace traditional coursework with modern alternatives that foster elevated levels of critical thinking among students, as suggested by Zhai ( 2022 ). Educators and learners can augment the academic material produced by ChatGPT with their own insights and information obtained from credible scholarly resources (Emenike & Emenike, 2023 ).

Third, ChatGPT should not be considered a threat to the education sector but a supplementary tool for human instruction that can enhance teaching and learning. It is imperative to acknowledge that the vital role of human educators cannot be replaced (Karaali, 2023 ) Moreover, ChatGPT can potentially enhance the accessibility and inclusivity of higher education. Alternative formats, linguistic support, and individualised explanations can help students who are studying English as a second language, are not native English speakers, or have other unique learning needs. Furthermore, Alnaqbi and Fouda ( 2023 ) highlight the implications of AI in evaluating the teaching style of faculty in higher education by collecting the feedback of students through social media and ChatGPT.

Fourth, the faculty in higher education institutions could address ethical concerns by providing students with explicit and comprehensive guidelines about the prescribed structure of academic assignments (Cotton et al., 2023 ; Gardner & Giordano, 2023 ). This practice can facilitate the production of more cohesive assignments. In addition, teachers can use rubrics to assess assignments and blend automated and manual assessment methodologies to evaluate students’ comprehension of the subject matter (Cotton et al., 2023 ; Shoufan, 2023 ).

In summary, using ChatGPT is recommended for enhancing creativity, refining writing proficiency, and improving research abilities. Nonetheless, it is crucial to emphasise that ChatGPT should not be employed as a substitute for critical thinking and producing original work. While it serves as a valuable tool for augmentation, upholding the integrity of independent thought and authentic content creation in academic endeavours is essential.

4.2 Limitations

The present study acknowledges several limitations. Firstly, the reliance on Scopus as the primary data source for bibliometric analysis may have limitations in capturing the full landscape of relevant literature. Future research may consider incorporating additional databases like Web of Science to ensure a comprehensive assessment. Secondly, due to the English language restriction in the review, potentially relevant studies may have been omitted. Future research could enhance inclusivity by extending its scope to encompass papers written in languages other than English. Thirdly, the current study exclusively focused on journal articles. Expanding the scope to include diverse sources, such as conference proceedings or book chapters, could offer a more comprehensive overview.

Additionally, as a rapidly evolving field, literature published after our inclusion dates need capturing, and future studies should consider adjusting their inclusion criteria to accommodate the dynamic nature of the subject matter. Lastly, the specificity of the bibliometric data search, centred around terms like ChatGPT, AI, higher education, and academic integrity, may have excluded certain relevant articles. Future studies should consider employing more generalised search parameters to encompass synonyms associated with these terms.

4.3 Future scope

The findings of the study suggest new avenues for future research. The effectiveness of evaluation criteria for assessments incorporating ChatGPT-generated text needs to be investigated. Specifically, the appropriate level of ChatGPT-produced text that students may use in academic tasks or assessments has not been established. Research on the ethical implications of using AI tools such as ChatGPT in higher education is also needed. Issues pertaining to data confidentiality, bias, and transparency in algorithms used for decision-making remain to be addressed. Feasible approaches for mitigating the excessive reliance of scholars and learners on ChatGPT or similar AI models are needed. Researchers could also explore the implementation of verification processes that go beyond traditional plagiarism detection methods, accounting for the unique challenges posed by AI systems. Future research in this domain could focus on establishing guidelines and best practices for the integration of AI tools like ChatGPT in academic settings, ensuring a balance between technological innovation and the preservation of academic rigour. Finally, the literature on ChatGPT in higher education has largely focused on the medical and tourism sectors. Future researchers must explore applications of ChatGPT in other disciplines.

Data availability

The datasets generated during and/or analysed during the current study are available from the corresponding author upon reasonable request.

Adetayo, A. J. (2023). ChatGPT and librarians for reference consultations. Internet Reference Services Quarterly , 27 (3), 131–147.

Article   Google Scholar  

AlAfnan, M. A., Dishari, S., Jovic, M., & Lomidze, K. (2023). ChatGPT as an educational tool: Opportunities, challenges, and recommendations for communication, business writing, and composition courses. Journal of Artificial Intelligence and Technology , 3 (2), 60–68. https://doi.org/10.37965/jait.2023.0184 .

Alnaqbi, N. M., & Fouda, W. (2023). Exploring the role of ChatGPT and social media in enhancing student evaluation of teaching style in higher education using Neutrosophic sets. International Journal of Neutrosophic Science , 20 (4), 181–190.

Angelis, L. D., Baglivo, F., Arzilli, G., Privitera, G. P., Ferragina, P., Tozzi, A. E., & Rizzo, C. (2023). ChatGPT and the rise of large language models: The new AI-driven infodemic threat in public health. Frontiers in Public Health , 11 , 1–8.

Archambault, E., Campbell, D., Gingras, Y., & Larivière, V. (2009). Comparing bibliometric statistics obtained from the web of Science and Scopus. Journal of the American Society for Information Science and Technology , 60 (7), 1320–1326.

Bajaj, Y., Kashiramka, S., & Singh, S. (2020). Application of capital structure theories: A systematic review. Journal of Advances in Management Research , 18 (2), 173–199. https://doi.org/10.1108/JAMR-01-2020-001 .

Bauer, E., Greisel, M., Kuznetsov, I., Berndt, M., Kollar, I., Dresel, M., Fischer, M. R., & Fischer, F. (2023). Using natural language processing to support peer-feedback in the age of artificial intelligence: A cross-disciplinary framework and a research agenda. British Journal of Educational Technology , 54 (5), 1222–1245.

Boyack, K. W., & Klavans, R. (2010). Co-citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately? Journal of the American Society for Information Science and Technology , 61 (12), 2389–2404.

Cingillioglu, I. (2023). Detecting AI-generated essays: The ChatGPT challenge. International Journal of Information and Learning Technology , 40 (3), 259–268. https://doi.org/10.1108/IJILT-03-2023-0043 .

Clark, T. M. (2023). Investigating the Use of an Artificial Intelligence Chatbot with General Chemistry exam questions. Journal of Chemical Education , 100 (5), 1905–1916.

Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2023). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International , 1–13. https://doi.org/10.1080/14703297.2023.2190148 .

Crawford, J., Cowling, M., & Allen, K. (2023). Leadership is needed for ethical ChatGPT: Character, assessment, and learning using artificial intelligence (AI). Journal of University Teaching & Learning Practice , 20 (3), 1–21. https://doi.org/10.53761/1.20.3.02 .

Crompton, H., & Burke, D. (2023). Artificial intelligence and higher education: The state of the field. International Journal of Educational Technology in Higher Education , 20 , 1–22. https://doi.org/10.1186/s41239-023-00392-8 .

Dehouche, N. (2021). Plagiarism in the age of massive generative pre-trained transformers (GPT-3). Ethics in Science and Environmental Politics , 2 , 17–23. https://doi.org/10.3354/esep00195 .

Dencik, L., & Sanchez-Monedero, J. (2022). Data justice. Internet Policy Review , 11 (1), 1–16. https://doi.org/10.14763/2022.1.1615 .

Donthu, N., Kumar, S., & Pattnaik, D. (2020). Forty-five years of Journal of Business Research : A bibliometric analysis. Journal of Business Research , 109 , 1–14. https://doi.org/10.1016/j.jbusres.2019.10.039 .

Emenike, M., & Emenike, B. (2023). Was this title generated by ChatGPT? Considerations for artificial intelligence text-generation software programs for chemists and chemistry educators. Journal of Chemical Education , 100 (4), 1413–1418. https://doi.org/10.1021/acs.jchemed.3c00063 .

Eysenbach, G. (2023). The role of ChatGPT, generative language models, and artificial intelligence in medical education: A conversation with ChatGPT and a call for papers. JMIR Medical Education , 6 (9), 1–13. https://doi.org/10.2196/46885 .

Farrokhnia, M., Banihashem, K. S., Noroozi, O., & Wals, A. (2023). A SWOT analysis of ChatGPT: Implications for educational practice and research. Innovations in Education and Teaching International , 1–15. https://doi.org/10.1080/14703297.2023.2195846 .

Fergus, S., Botha, M., & Ostovar, M. (2023). Evaluating academic answers generated using ChatGPT. Journal of Chemical Education , 100 (4), 1672–1675. https://doi.org/10.1021/acs.jchemed.3c00087 .

Firat, M. (2023). How chat GPT can transform autodidactic experiences and open education. Department of Distance Education, Open Education Faculty , Anadolu University, 1–6. https://doi.org/10.31219/osf.io/9ge8m .

Gardner, D. E., & Giordano, A. E. (2023). The challenges and value of undergraduate oral exams in the physical chemistry classrooms: A useful tool in the assessment toolbox. Journal of Chemical Education , 100 (5), 1705–1709.

Geerling, W., Mateer, G. D., Wooten, J., & Damodaran, N. (2023). ChatGPT has aced the test of understanding in college economics: Now what? The American Economist , 68 (2), 233–245.

Gilson, A., Safranek, C. W., Huang, T., Socrates, V., Chi, L., Taylor, R. A., & Chartash, D. (2023). How does ChatGPT perform on the United States medical licensing examination? The implications of large language models for medical education and knowledge assessment. JMIR Medical Education , 9 , 1–9. https://doi.org/10.2196/45312 .

Gisev, N., Bell, J. S., & Chen, T. F. (2013). Interrater agreement and interrater reliability: Key concepts, approaches, and applications. Research in Social and Administrative Pharmacy , 9 (3), 330–338.

Gupta, R., Pandey, R., & Sebastian, V. J. (2021). International entrepreneurial orientation (IEO): A bibliometric overview of scholarly research. Journal of Business Research , 125 , 74–88. https://doi.org/10.1016/j.jbusres.2020.12.00 .

Ibrahim, H., Asim, R., & Zaffar, F. (2023). Rethinking homework in the age of artificial intelligence. Intelligent Systems , 38 (2), 24–27.

Google Scholar  

Iskender, A. (2023). Holy or Unholy? Interview with Open AI’s ChatGPT. European Journal of Tourism Research , 34 , 3414. https://doi.org/10.54055/ejtr.v34i.3169 .

Ivanov, S., & Soliman, M. (2023). Game of algorithms: ChatGPT implications for the future of tourism education and research. Journal of Tourism Futures , 9 (2), 214–221.

Jarneving, B. (2007). Bibliographic coupling and its application to research-front and other core documents. Journal of Informetrics , 1 (4), 287–307.

Jeon, J., Lee, S., & Cho, S. (2023). A systematic review of research on speech-recognition chatbots for language learning: Implications for future directions in the era of large language models. Interactive Learning Environment , 1–19. https://doi.org/10.1080/10494820.2023.2204343 .

Johinke, R., Cummings, R., & Di Lauro, F. (2023). Reclaiming the technology of higher education for teaching digital writing in a post-pandemic world. Journal of University Teaching and Learning Practice , 20 (2), 1–18. https://doi.org/10.53761/1.20.02.01 .

Karaali, G. (2023). Artificial Intelligence, Basic skills, and quantitative literacy. Numeracy , 16 (1), 1–22. https://doi.org/10.5038/1936-4660.16.1.1438 .

Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., & Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences , 103 (2023), 102274–102271. https://doi.org/10.1016/j.lindif.2023.102274 .

Lawrie, G. (2023). Establishing a delicate balance in the relationship between artificial intelligence and authenticate assessment in student learning. Chemistry Education Research and Practice , 24 (2), 392–393.

Lee, H. (2023). The rise of ChatGPT: Exploring its potential in medical education. Anatomical Science Education , 1–6. https://doi.org/10.1002/ase.2270 .

Li, Y., Sha, L., Yan, L., Lin, J., Raković, M., Galbraith, K., Lyons, K., Gašević, D., & Chen, G. (2023). Can large language models write reflectively. Computer and Education: Artificial Intelligence , 4 (2023), 100140–100141.

Liebrenz, M., Schleifer, R., Buadze, A., Bhugra, D., & Smith, A. (2023). Generating scholarly content with ChatGPT: Ethical challenges for medical publishing. Lancet Digital Health , 5 (3), e105–106. https://doi.org/10.1016/S2589-7500(23)00019-5 .

Lim, W. M., Gunasekara, A., Pallant, J. L., Pallant, J. I., & Pechenkina, E. (2023). Generative AI and the future of education: Ragnarök or reformation? A paradoxical perspective from management educators. The International Journal of Management Education , 21 (2), 1–13.

Lin, C. C., Huang, A. Y. Q., Stephen, J. H., & Yang (2023). A review of AI-Driven conversational chatbots implementation methodologies and challenges (1999–2022). Sustainability , 15 (5), 4012. https://doi.org/10.3390/su15054012 .

Memarian, B., & Doleck, T. (2023). ChatGPT in education: Methods, potentials and limitations. Computers in Human Behavior: Artificial Humans , 100022 , 1–11.

Mishra, D., Gunasekaran, A., Papadopoulos, T., & Hazen, B. (2017). Green supply chain performance measures: A review and bibliometric analysis. Sustainable Production and Consumption , 10 , 85–99. https://doi.org/10.1016/j.spc.2017.01.003

Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & The PRISMA Group. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. Annals of Internal Medicine , 151 (4), 264–269.

Nautiyal, R., Albrecht, J. N., & Nautiyal, A. (2023). ChatGPT and tourism academia. Annals of Tourism Research , 99 , 1–3.

Neumann, M., Rauschenberger, M., & Schon, E-M. (2023). 2023 IEEE/ACM 5th International Workshop on Software Engineering Education for the Next Generation (SEENG), Melbourne, Australia, 2023, pp. 29–32, https://doi.org/10.1109/SEENG59157.2023.00010 .

Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., … & Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ , 372 (71), 1–9. https://doi.org/10.1136/bmj.n71

Palomo, J., Figueroa-Domecq, C., & Laguna, P. (2017). Women, peace and security state-of-art: A bibliometric analysis in social sciences based on SCOPUS database. Scientometrics , 113 (1), 123–148. https://doi.org/10.1007/s11192-017-2484-x .

Patrício, L. D., & Ferreira, J. J. (2020). Blockchain security research: Theorizing through bibliographic-coupling analysis. Journal of Advances in Management Research , 18 (1), 1–35. https://doi.org/10.1108/JAMR-04-2020-0051 .

Paul, J., Lim, W. M., O’Cass, A., Hao, A. W., & Bresciani, S. (2021). Scientific procedures and rationales for systematic literature reviews (SPAR-4-SLR). International Journal of Consumer Studies . https://doi.org/10.1111/ijcs.12695 .

Pechenkina, K. (2023). Artificial intelligence for good? Challenges and possibilities of AI in higher education from a data justice perspective. In L. Czerniewicz, & C. Cronin (Eds.), Higher education for good: Teaching and learning futures (#HE4Good) . Open Book.

Perkins, M. (2023). Academic integrity considerations of AI large Language models in the post-pandemic era: ChatGPT and beyond. Journal of University Teaching & Learning Practice , 20 (2), 1–26. https://doi.org/10.53761/1.20.02.07 .

Rahman, M., Mostafizer, & Yutaka Watanobe. (2023). ChatGPT for Education and Research: Opportunities, threats, and strategies. Applied Sciences , 13 (9), 1–21. https://doi.org/10.3390/app13095783 .

Rana, S. (2023). AI and GPT for Management scholars and practitioners: Guidelines and implications. FIIB Business Review , 12 (1), 7–9.

Seetharaman, R. (2023). Revolutionising medical education: Can ChatGPT boost subjective learning and expression? Journal of Medical System , 47 (61), 1–4. https://doi.org/10.1007/s10916-023-01957-w .

Seth, I., Bulloch, G., & Lee, C. H. A. (2023). Redefining academic integrity, authorship, and innovation: The impact of ChatGPT on surgical research. Annals of Surgical Oncology , 30 , 5284–5285. https://doi.org/10.1245/s10434-023-13642-w .

Shoufan, A. (2023). Exploring students’ perceptions of ChatGPT: Thematic analysis and follow-up survey. IEEE Access , 11, 38805–38818, 2023, https://doi.org/10.1109/ACCESS.2023.3268224 .

Singh, V. K., Singh, P., Karmakar, M., Leta, J., & Mayr, P. (2021). The journal coverage of web of Science, Scopus and dimensions: A comparative analysis. Scientometrics , 126 , 5113–5142.

Skavronskaya, L., Hadinejad, A., & Cotterell, D. (2023). Reversing the threat of artificial intelligence to opportunity: A discussion of ChatGPT in tourism education. Journal of Teaching in Travel & Tourism , 23 , 1–6. https://doi.org/10.1080/15313220.2023.2196658 .

Strzelecki, A. (2023). To use or not to use ChatGPT in higher education? A study of students’ acceptance and use of technology. Interactive Learning Environments , 1–15. https://doi.org/10.1080/10494820.2023.2209881 .

Su, J., & Yang, W. (2023). Unlocking the power of ChatGPT: A framework for applying generative AI in education. ECNU Review of Education , 6 (3), 355–366.

Subramani, M., Jallel, I., & Mohan, S. K. (2023). Evaluating the performance of ChatGPT in medical physiology university examination of phase I MBBS. Advances in Physical Education , 47 , 270–271.

Sun, G. H., & Hoelscher, S. H. (2023). The ChatGPT Storm and what Faculty can do. Nurse Educator , 48 , 119–124.

Tang, G. (2023a). Academic journals cannot simply require authors to declare that they used ChatGPT. Irish Journal of Medical Science , 192 (6), 3195–3196.

Tang, G. (2023b). Letter to editor: Academic journals should clarify the proportion of NLP-generated content in papers. Accountability in Research , 1–3. https://doi.org/10.1080/08989621.2023.2180359 .

Teixeira da Silva, J. A. (2023). How are authors’ contributions verified in the ICMJE model? Plant Cell Reports , 42 , 1529–1153. https://doi.org/10.1007/s00299-023-03022-9 .

Thorp, H. H. (2023). ChatGPT is fun, but not an author. Science , 379 (6630), 313–313.

Tlili, A., Shehata, B., Adarkwah, M., Bozkurt, A., Hickey, D. T., Huang, R., & Agyemang, B. (2023). What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education. Smart Learning Environments , 10 (15), 1–24.

Van Eck, N., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics , 84 (2), 523–538.

Vijaya, V., & Mathur, H. P. (2023). A decade of donation-based crowdfunding: A bibliometric analysis using the SCOPUS Database. Purushartha , 15 (2), 32–51.

Vogels, E. A. (2023). A majority of Americans have heard of ChatGPT, but few have tried it themselves, https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ .

Wu, R., & Yu, Z. (2023). Do AI Chatbots improve students learning outcome? Evidence from a meta analysis. British Journal of Educational Technology . https://doi.org/10.1111/bjet.13334 .

Wu, T. Y., He, S. Z., Liu, J. P., Sun, S. Q., Liu, K., Han, Q. L., & Tang, Y. (2023). A brief overview of ChatGPT: The history, status quo and potential future development. IEEE/CAA Journal of Automatica Sinica , 10 (5), 1122–1136. https://doi.org/10.1109/JAS.2023.123618 .

Yan, D. (2023). Impact of ChatGPT on learners in a L2 writing practicum: An exploratory investigation. Education and Information Technologies , 1–25. https://doi.org/10.1007/s10639-023-11742-4 .

Yeadon, W., Inyang, O-O., Mizouri, A., Peach, A., & Testrow, C. P. (May 2023). The death of the short-term physics essay in the coming AI revolution. Physics Education , 58 , 1–13.

Zhai, X. (2022). ChatGPT user experience: Implications for education. SSRN , 4312418 , 1–18.

Download references

Open Access funding enabled and organized by CAUL and its Member Institutions

Author information

Authors and affiliations.

University Business School, Maharaja Ranjit Singh Punjab Technical University, Punjab, India

Pritpal Singh Bhullar

Department of Financial Planning and Tax, School of Accounting, Information Systems and Supply Chain, RMIT University, Melbourne, Australia

Mahesh Joshi

School of Engineering and Technology, CML‑NET & CREATE Research Centres, Central Queensland University, Queensland, Australia

Ritesh Chugh

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Ritesh Chugh .

Ethics declarations

Conflict of interest.

No Conflict of Interest.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Bhullar, P.S., Joshi, M. & Chugh, R. ChatGPT in higher education - a synthesis of the literature and a future research agenda. Educ Inf Technol (2024). https://doi.org/10.1007/s10639-024-12723-x

Download citation

Received : 04 October 2023

Accepted : 16 April 2024

Published : 02 May 2024

DOI : https://doi.org/10.1007/s10639-024-12723-x

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Artificial Intelligence
• Generative AI
• Higher education
• Academic integrity
• Systematic review
• Bibliometric analysis
• Find a journal
• Publish with us
• Track your research

Multilevel determinants of digital health equity: a literature synthesis to advance the field

Author:  Adrian Aguilera Publication date:  April 30, 2023 Publication type:  Journal Article Citation:  Lyles, C. R., Nguyen, O. K., Khoong, E. C., Aguilera, A., & Sarkar, U. (2023). Multilevel determinants of digital health equity: a literature synthesis to advance the field. Annual review of public health, 44, 383-405.

• Digital Interventions topic page
• Health and Healthcare Disparities topic page
• Health - Physical topic page

Literature Seminar: Synthesis, Structure, and Applications of Conjugated Polymer Semiconductors

Mr. Vincent Wedekind, University of Maryland

Log in using your username and password

• Search More Search for this keyword Advanced search
• Latest content
• Current issue
• Instructions for Authors
• BMJ Journals More You are viewing from: Google Indexer

You are here

• Volume 14, Issue e1
• Gypsy, Traveller and Roma experiences, views and needs in palliative and end of life care: a systematic literature review and narrative synthesis
• Article Text
• Article info
• Citation Tools
• Rapid Responses
• Article metrics

• http://orcid.org/0000-0002-6565-6057 Kathryn Charlotte Dixon 1 ,
• Rebecca Ferris 2 ,
• Isla Kuhn 3 ,
• Anna Spathis 1 and
• http://orcid.org/0000-0002-4505-7743 Stephen Barclay 1
• 1 Department of Public Health and Primary Care , University of Cambridge , Cambridge , Cambridgeshire , UK
• 2 Cambridge Postgraduate Medical Centre , Addenbrooke's Hospital , Cambridge , Cambridgeshire , UK
• 3 Medical Library , University of Cambridge , Cambridge , Cambridgeshire , UK
• Correspondence to Kathryn Charlotte Dixon, University of Cambridge Department of Public Health and Primary Care, Cambridge, UK; kcd23{at}medschl.cam.ac.uk

Background Gypsy, Traveller and Roma communities are known to experience health inequalities. There has been little focus on palliative care in these communities despite the well-recognised inequalities of access to palliative care in other minority ethnic groups.

Methods Systematic review and thematic analysis of the current evidence concerning palliative care experiences, views and needs of Gypsy, Traveller and Roma communities. Medline, Embase, Emcare, CINAHL, PsycINFO, Web of Science, Scopus, AMED, Global Health, Psychological and Behavioural Sciences Collection and BNI were searched up to November 2020, alongside author and citation searching. NHS England, Hospice UK, National Audit Office and OpenGrey were searched as grey literature sources. Gough’s ‘Weight of Evidence’ framework was used for quality appraisal.

Results Thirteen papers from eight studies were included in the synthesis. Although there was variation between communities, three overarching and inter-related themes were identified. (1) Strong family and community values include a preference for healthcare to be provided from within the community, duty to demonstrate respect by attending the bedside and illness as a community problem with decision-making extending beyond the patient. (2) Distinct health beliefs regarding superstitions around illness, personal care, death rituals and bereavement. (3) Practical barriers to non-community healthcare provision include communication difficulties, limited awareness of and access to services, tensions between patients and healthcare professionals and lack of training in delivering culturally appropriate care.

Conclusion A wide range of factors influence Gypsy, Traveller and Roma community access to palliative care. Community diversity requires sensitive and highly individualised approaches to patient care.

PROSPERO registration number 42019147905.

• cultural issues
• methodological research

https://doi.org/10.1136/bmjspcare-2020-002676

Statistics from Altmetric.com

Request permissions.

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

Introduction

Gypsy, Traveller and Roma communities are Europe’s largest minority ethnic group. 1 Although these communities are culturally diverse, they are frequently grouped together within healthcare policy and also by the communities themselves. 1–3 The Council of Europe uses the term ‘Roma’ to refer to itinerant groups within Europe. 2 Although Irish Travellers are included within the Council of Europe’s definition of ‘Roma’, they are genetically distinct from European Roma, 4 with Irish ancestry as opposed to Indian. 2

Despite a traditional nomadic lifestyle, up to 85% of travelling communities in Europe today are settled in one place with those maintaining a travelling way of life found mainly in France, the Benelux countries, Switzerland, Ireland and the UK. 2 When settled, they may live in permanent bricks-and-mortar housing or in mobile homes or caravans and some groups are seminomadic, travelling within the summer months. 5

Gypsy, Traveller and Roma communities experience significant health inequalities in multiple areas of health and social care. 6 7 These include reduced life expectancy, ranging from 10 to 20 years lower than the general population, higher maternal and infant mortality, lower uptake of immunisations and therefore higher rates of vaccine-preventable diseases, higher prevalence of anxiety and depression and higher prevalence of chronic diseases such as diabetes, asthma, cardiovascular disease and hypertension. 5 7–10 There is recognised reduced access to and engagement with services across the healthcare setting and a multitude of barriers to healthcare including illiteracy, discrimination and reduced awareness of services available. 11

Inequality of access to palliative care is a global health problem and the WHO is spearheading efforts to reduce this. 12 13 Providers of palliative care are increasingly focusing on ‘hard-to-reach groups’ in an attempt to enhance access. 10 14 It is already known that Gypsy, Traveller and Roma communities have poor access to, and engagement across, healthcare services generally, 11 and it is likely that this extends to palliative and end of life care services. Good end of life care should be an integral part of all health systems. 13

Given the known inequalities in healthcare for patients from minority ethnic groups, and specifically for Gypsy, Traveller and Roma patients, and the importance of providing culturally and socially appropriate palliative care, a systematic review of palliative and end of life care for patients in these communities is highly topical. Previous systematic reviews have evaluated Gypsy, Traveller and Roma access to and engagement with health services in general 11 and palliative care within black and Asian minority ethnic groups in the UK. 15 This is the first systematic review to address the palliative and end of life care experiences, views and needs within travelling communities.

Search strategy

The search strategy was developed with a specialist information technologist (IK). Search terms to identify articles about Gypsy, Traveller and Roma peoples were adapted from those used by McFadden et al . 11 The search strategy was tailored for each database searched (Medline, Embase, Emcare, CINAHL, PsycINFO, Web of Science, Scopus, AMED, Global Health, Psychological and Behavioural Sciences Collection and BNI). Full search strategies are available in online supplemental material 1 . No restrictions were applied to the searches. All databases were searched from inception to September 2019, and updated in November 2020. NHS England, Hospice UK, National Audit Office and OpenGrey were searched for ‘gypsy, gipsy, traveller, roma and rroma’. Citation and author searching was undertaken for all relevant full-text articles.

Supplemental material

Study selection.

Studies, including reports and PhD theses, fitted the criteria if they reported original research on the palliative and end of life care experiences, views and needs of adult Traveller, Gypsy or Roma people, whether from the perspective of members of these communities or healthcare professionals. Book chapters, studies focusing on children (under 18 years of age) or articles where the full text was not available in English were excluded.

After exclusion of duplicates using EndNote, two reviewers (KCD and RF) independently screened titles and abstracts and then full-texts, with discrepancy between reviewers resolved by discussion to reach consensus. Title and abstract screening was facilitated by the use of the web app Rayyan. 16 One reviewer (KCD) conducted the grey literature search, citation and author searching and articles chosen for inclusion were agreed by the second reviewer (RF).

The study identification process is summarised in figure 1 . Database and grey literature searches identified 1296 records after removal of duplicates. Seventeen full-text articles were assessed for eligibility with seven of these being eligible for inclusion. Each of these seven articles underwent citation and author searching, identifying a further three papers, one PhD thesis and two reports. Citation and author searching was then conducted for these records. One further unpublished study of relevance was identified but the authors did not respond to requests for access to the article. 17 Of the thirteen final articles selected for inclusion, five research papers reported on the same set of interviews and were therefore treated as one study. In addition, one report and one research paper reported on the same results and were also treated as one study. A total of thirteen papers relating to eight studies were therefore included in the qualitative synthesis.

• Download figure
• Open in new tab
• Download powerpoint

PRISMA Flow.

Quality appraisal

Two reviewers (KCD and RF) independently appraised the quality and relevance of the included studies using Gough’s ‘Weight of Evidence’ (WoE) framework. 18 Disagreements in quality assessment decisions were discussed and consensus achieved. The WoE framework provides an overall judgement on the quality and relevance of a study in answering the review question (WoE D). The adaptation of Gough’s WoE for this review is shown in table 1 .

• View inline

Review-specific Gough’s ‘Weight of Evidence’ high-quality criteria (adapted from Gough 2007) 18

Data extraction and synthesis

Information regarding publication details, study aims, participants, recruitment and research methods were extracted on to a review-specific data extraction form by KCD and checked by RF. The form was piloted on three studies before continuing with its use. Results data were extracted line by line in to an Excel spreadsheet by KCD prior to coding (see below). RF checked 10% of data extracted.

Data synthesis used a thematic analysis approach, adapted from that suggested by Thomas and Harden, 19 involving three main stages after data extraction:

Coding of the data: KCD coded all individual data points in Excel, developing a coding framework whereby different data points shared the same code. By using an inductive framework rather than developing a priori codes, potential for bias was reduced and significance of original data was not lost. RF checked a representative proportion of codes from each study to ensure consistency in code assigning across studies.

Generation of descriptive themes: KCD grouped the codes into descriptive themes on paper, which were agreed by discussion with RF. Codes from studies assessed to be of low quality under WoE D were only used in generation of descriptive themes if they supported codes from a study of medium or high quality.

Generation of analytical themes: KCD and RF independently, and then by discussion, organised the findings into overarching themes.

Eight studies, described in thirteen articles, were synthesised in this review. Studies reported on practice in the UK (n=4), 20–23 Ireland (n=1), 24 25 Romania (n=1) 26–30 and Spain (n=2). 31 32 Studies focused on members of different travelling communities: Roma (n=3), 26–32 Irish Travellers (n=1) 24 25 and English Gypsies (n=1). 20 Two studies did not identify participants beyond ‘Gypsy and Traveller’, 22 23 and one study involved both Irish Travellers and English Gypsies. 21 The majority of participants were female with only two studies incorporating male participants. 26–30 32 Three studies reported the views of healthcare professionals: one in detail via interviews and questionnaires, 24 25 one via the involvement of two participants 32 and one via focus groups with 30 health mediators (although there was limited analysis of this in the article). 30 Methods included focus group discussion (n=4), 21 23–25 31 qualitative interviews with members of travelling communities (n=3), 20 22 26–30 qualitative interviews with healthcare professionals (n=1), 24 25 questionnaire (n=2), 21 24 25 observational fieldwork (n=1) 20 and communicative daily life stories (n=1). 32 The details of each study and their weighting on the WoE framework are summarised in table 2 . One study was weighted as high quality, 21 five as medium 20 22–25 31 and two had a low weighting. 26–30 32 One study was mainly focused on grief and bereavement after the loss of a child and therefore only information relevant to the review question was extracted. 21

Summary of included studies

Three overarching analytical themes were found: (1) strong family and community values, (2) distinct health beliefs and (3) practical barriers to non-community healthcare provision.

Strong family and community values

The importance of family and community was echoed by all studies. Family are considered to have a duty to care for a dying relative and there is a reciprocal desire by the dying person to be cared for by their family. 22–25 28 29 31 Consistent throughout all studies was the overriding desire to die at home, surrounded by family and the community. Attending the bedside of a dying community member is seen as a marker of respect for that person and their family. 20 21 26 32 Large groups gather around the bedside with as many as 50–200 people paying their respects at and around the time of death. 20–25 27–29 32 Financial, as well as emotional, community support is expected. 28 31 32

A consistent theme was that healthcare from within the community is preferred to external care. Although respectful of healthcare staff, it was considered that family members are most informed and best placed to judge a patient’s needs. 24 25 31 Decision-making around death and dying extended beyond the individual patient, with multiple family members requesting personal updates from doctors 24 25 and some families expressing the wish to withhold diagnoses from patients. 20 27

Despite the overwhelming message of the significance of family and the wider community for patients with terminal conditions, three studies described the concept of shame in being terminally ill or seeking support, with a need to hide the illness from the wider community due to the fear of social isolation. 23 27 31 In one study, participants were ashamed to accept care from a non-Traveller or non-Roma person. 32

Distinct health beliefs

Distinct health beliefs were described in relation to general health and hygiene, and specific beliefs around cancer and death. Hygiene rituals, including beliefs about impurity were described by three studies, 20 27 30 with the suggestion that care in a hospital or hospice environment could cause distress if normal hygiene practices could not be followed. 20

Superstitions were described around cancer. This included fear of discussing or saying the word ‘cancer’ with a perception that this could lead to disease progression or bring misfortune on family members. 24 25 27 There was also a fear that non-contagious conditions could spread and that cancer treatments might actually cause disease growth. 20 29 Similarly, death and dying were seen as taboo topics, socially unacceptable to discuss; 21 23–25 27 there were descriptions of research participants blessing themselves during focus groups and interviews in one study. 24 25 Connected to this was a wish not to know the exact details of an illness 24 25 and a belief that a patient knowing their own diagnosis could cause further harm. 20 26 27 Several studies highlighted the importance of ‘hope’ with loss of hope itself causing harm or hastening death. 21 24 25 27 31 Due to this belief, hospice care was described as a last resort by two studies as hospices were seen as places to die. 24 25 31

Grief is considered a private matter and several studies raised the issue that grief is not discussed or shared within these communities, which can lead to prolonged grief or unresolved bereavement. 20–22 24 25 Gender roles were presented in that women may be expected to grieve openly whereas men can cry only at the graveside. 21 The duty to care for unwell relatives resided with women rather than men. 31 In addition, when accessing healthcare or obtaining health-related advice, women only speak to women and men to men. 20

Death rituals were important 23–25 27 30 and although in some cases linked to religion, cultural traditions tended to supersede religious practice. 21 24 25 32 Examples include a ‘rite of light’ (the lighting of a candle near the time of death to enable passage of the soul to ‘the other world’), 24 25 27 30 the need for large numbers of family and community to say goodbye personally and immediately after death, 23–25 29 32 often via a vigil 32 and the need for appropriate respect of a person by dressing them ‘properly’ before death. 30 Death rituals and traditions were described as changing over time, with associated intergenerational differences. 21 24 25 For example, one tradition involves burning the place of death, yet many participants remarked on the change in this belief over time, given the expense and move away from wooden trailers; families report preferring to have the trailer cleaned and blessed by a priest, or selling it. 21 24 25

Some studies evaluated views on life-sustaining treatment and advanced decisions about care. 24 25 27 31 Generally, written documents were not thought useful. Although in part due to variable literacy, this appeared mainly to be due to a perception that the family already know how to care appropriately for the patient, without need for written plans. 24 25 31

Practical barriers to non-community healthcare provision

Barriers to non-community healthcare in general and palliative care specifically were identified. Illiteracy and a misunderstanding of medical terminology were cited as common initial barriers to all non-community healthcare. 20 23–26 32 Three studies raised concerns regarding reduced access to a General Practitioner. 20 22 24 25 Late presentation of disease was then attributed to either fear of the diagnosis, 24 25 lack of registration with a General Practitioner 20 22 or reluctance to see a doctor. 20 24 25 Participants reported experiences of staff basing their ideas on stereotypes or showing a lack of respect for patients and their families from travelling communities. 20 22–25 30 32 Several studies raised the idea of ‘conflict’ between staff and patients with patients feeling that staff did not understand their culture and had limited experience in looking after them. 22–25 30 32 Likewise, healthcare professionals agreed that they had limited knowledge in caring for these patients and would appreciate training, which was felt to not be available. 21 24 25

There were mutual concerns from both the community and healthcare professionals regarding factors leading to reduced access to palliative care specifically. Travellers reported limited knowledge of what palliative care is and what services are available 20 23–25 but also raised concerns that the services available may not be appropriate or targeted towards people from their community. 21 22 Similarly, staff expressed views that the service may not be appropriate for travellers and lack of knowledge as to whether external non-community healthcare was acceptable. 24 25 Healthcare professionals suggested that the living situation and lifestyle for their travelling patients would impact the provision of appropriate care and follow-up. 24–26 They also raised concerns about the safety of other staff when attending to patients alone on a caravan site. 24 25

Solutions were suggested by both parties; travellers raised the issue of a lack of targeted support being available and the idea of trained travellers providing bereavement care or advice to patients and families or acting as a liaison between the community and healthcare professionals. 20–25 32 There were examples where allowances for cultural needs had enabled positive experiences, such as catering for large groups to attend the bedside. 21–23

Theme integration

There were commonalities, but also findings of significant diversity between communities in relation to all three themes. It was also clearly acknowledged across several studies by Irish travellers, English Romany Gypsies and Roma that views differed within and between communities with not all travelling communities sharing the same values or practices. 20 24–28

The three themes do not exist in isolation, nor are they static entities. This relationship is conceptualised in figure 2 . Each pair of the three themes connect, for example the wish to die at home could be seen as a barrier to non-community healthcare if there is limited awareness of services that can help facilitate this, such as hospice at home. Health beliefs and family values cannot exist without the other; the importance of caring for or being with a dying relative is inherently linked to a cultural belief system of right and wrong behaviours. Death rituals and the community view of a hospice as a last resort could prevent a patient and their family from accessing hospice support. The encompassing square of the wider society represents the influence of external factors on the community culture, such as the change in tradition of ritualistic burning over time, or the influence that the healthcare setting or professional has on future engagement of a travelling community with non-community healthcare.

Theme Integration.

This review identified three interconnected themes underpinning palliative and end of life care within travelling communities. Travelling communities have strong family and community values, often preferring to die at home, with care being provided by extended family. Distinct health beliefs include not discussing cancer or death and dying and the importance placed on hope. Illiteracy, lack of knowledge of medical terminology and communication issues also present barriers to non-community healthcare. Healthcare professionals’ knowledge of, or inappropriate professional attitude towards travellers, can be a further barrier. These beliefs, values and barriers were dynamic entities, influenced by varied and distinct community cultures.

There is known inequity in the provision of palliative care in the UK with barriers to accessing palliative care frequently identified. 33 The findings of this review echo those found by Evans et al 15 in black and minority ethnic groups in the UK, with common themes including families preferring to care for their relative at home and community negativity if this does not occur, hospital care being associated with hope, reduced awareness of palliative care services, communication problems, conflicts regarding diagnosis disclosure and healthcare professional concern regarding a need for training. 15 Evans et al acknowledge that their review did not identify any articles regarding white minority ethnic groups in the UK and suggested that this echoes a genuine lack of research in the field.

Other than the studies analysed in this review, there is little evidence available regarding the palliative and end of life care experiences, views and needs of travelling communities. Okely’s book ‘The Traveller-Gypsies’ published in 1983 and based on an ethnographic study, presented a chapter on end of life in the Gypsy community. 34 As inclusion criteria for this review did not include books, this was not included in thematic analysis. There are some similarities between Okely’s book and the findings of this review, but also some key differences such as the preferred place of death, which Okely stated was not at home. This could represent the change in values and practices overtime, with the fieldwork for Okely’s study carried out in the 1970s, compared with 2003 onwards for studies included in this review.

All three themes point to reduced access to palliative care services in travelling communities. This finding is consistent with the candidacy framework which describes access to healthcare by vulnerable groups. 35 Candidacy is a construct which describes how a vulnerable person’s eligibility for healthcare is negotiated between individuals and health services; it is subject to influences from the individual’s social context and from broader factors such as allocation of resources, policy and the healthcare setting. In the context of palliative care in travelling communities, the development of local resources to address the needs of travellers and the building of trusted relationships with primary care professionals, such as General Practitioners, is likely to be vital in facilitating appropriate awareness of and access to specialist services.

Strengths and limitations of the review

The main strength of this review is that it is broad and comprehensive, including extensive evaluation of grey literature, given the limited publication of relevant literature in the conventional electronic databases. Data extraction and analysis were systematic, with an inductive coding framework and second author checking at each stage, reducing author bias in assignment of codes and themes. Thematic analysis allowed for trends across all studies to be identified and only using codes from studies with a low WoE D grade where they supported findings from other studies, further improved the validity of the findings. Although the search strategy was not restricted by language, studies were excluded if an English full text was unavailable. One Spanish study was excluded for this reason. 36

Generalisability of the findings was limited by study heterogeneity. Only two studies involved male participants, both providing only a low weight of evidence on Gough’s scale. 26–30 32 The lack of male participants was stated as being due to either failure to recruit male participants where their involvement had been planned or due to local advisory groups suggesting that male participants would be unlikely to engage in conversation with female researchers. 20 21 24 25

Implications for clinical practice and policy

Although this review identified similarities in palliative and end of life care experiences, views and needs within Gypsy, Traveller and Roma communities, it also identified key differences between and within them. Policies must therefore avoid blanket statements about healthcare for Gypsy, Traveller and Roma communities, given the disparate needs of each community. Healthcare professionals reported inadequate training in how to look after patients from travelling communities. 24 25 However, it is not practical to give training to healthcare professionals for every minority ethnic group, culture or religion. Instead, the most important aspect is that healthcare professionals recognise that there are a multitude of factors affecting patient preferences for palliative and end of life care and only individual discussion with the patient and their family can lead to patient-centred, personalised care.

The need for there to be a good relationship between the community and professionals and the importance of the involvement of a known and trusted, respectful professional to enable a positive experience of non-community healthcare was clear. 21–25 30 Travellers and healthcare professionals need to work together to design culturally sensitive health services. Simple steps may be highly valued, for example providing an external door to a hospice room for extended family members to use. 22 Specific liaison roles could facilitate suitable healthcare provision. It has been suggested that travellers may find it more appropriate to discuss concerns such as bereavement, with another traveller who has been given appropriate training. 21 24 25 Local advocates for travelling communities, whether travellers themselves or healthcare professionals with a specialist interest, could provide significant benefit by acting as a liaison between patients and healthcare professionals. Roma Health Mediators, who are members of the Romani community, in countries such as Romania, Bulgaria and Slovakia have, for example, contributed to improving access to healthcare services by facilitating interaction between Romani patients and medical professionals. 37

Involvement of primary care services is likely to be valuable because of existing trusted relationships. Generalist palliative care may preclude the need for specialist services. A trusted primary care professional, already known to the community and able to provide continuity of care is likely to be invaluable in supporting patients from travelling communities at the end of life. This is in keeping with WHO recommendations that, as many patients prefer to remain at home for end of life care, community palliative care should be integrated into primary care services worldwide. 38

Implications for research

A series of qualitative studies are needed to gain insight into the exact and varied health needs of each travelling community. Research involving cocreation of acceptable services, with key stakeholders within these communities, will be vital. Such services could then be evaluated using outcomes of relevance to each community. Caution would be needed to avoid inappropriate extrapolation of results across different communities. Service design research could include investigating how to optimise selection and training of people in liaison roles. Understanding healthcare professionals’ experiences of caring for people from travelling communities could also provide insights into where service changes could be made.

Given the propensity of female participants, it is vital to determine the experiences, views and needs of men. Considering the cultural sensitivities, carefully designed research with extensive stakeholder consultation will be a prerequisite. Only studies from the UK, Ireland, Spain and Romania were identified. Further investigation of palliative and end of life care within itinerant groups outside of Europe is warranted.

This review has identified a number of shared palliative and end of life care experiences, views and needs across Gypsy, Traveller and Roma communities. Many values, healthcare beliefs and practical factors act to hinder access to palliative care that meets the needs of these communities. Furthermore, the communities are diverse, requiring highly personalised care that addresses individuals’ specific cultural needs.

Successful engagement between health services and patients from these communities requires respectful relationships and trust between the two groups, which can be facilitated by individuals providing mutual liaison. Primary care staff, who are able to build a rapport with their local travelling community, may be ideally placed to coordinate and deliver culturally appropriate palliative care that meets the unique needs of these communities.

Ethics statements

Patient consent for publication.

Not required.

• European Commission
• Council of Europe
• Friends Families and Travellers
• Gilbert E ,
• Ennis S , et al
• European Union Agency for Fundamental Rights
• Spencer S ,
• Greenfield M ,
• Burnett S , et al
• Aspinall PJ
• NHS England
• McFadden A ,
• Siebelt L ,
• Gavine A , et al
• World Health Organization
• Farmer PE ,
• Krakauer EL , et al
• Care Quality Commission
• Andrew EVW , et al
• Ouzzani M ,
• Hammady H ,
• Fedorowicz Z , et al
• McDonagh C ,
• McCormack M
• Griffiths F ,
• McQuillan R ,
• Van Doorslaer O
• Van Doorslaer O ,
• McQuillan R
• Pârvu A , et al
• Enache A , et al
• Peinado-Gorlat P ,
• Castro-Martínez FJ ,
• Arriba-Marcos B , et al
• Garcia-Espinel T ,
• Redondo-Sama G , et al
• Matosevic T ,
• Dixon-Woods M ,
• Agarwal S , et al
• Valera MAB ,
• Lezcano CM ,
• Aguarrón MJ
• Naydenova V

Supplementary materials

Supplementary data.

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

• Data supplement 1
• Data supplement 2

Correction notice This article has been updated since it was first published. The article type has been changed to Systematic review.

Contributors Search strategy was developed by KCD and IK. KCD and RF independently screened titles and abstracts and appraised the quality of included studies. KCD coded the data and developed descriptive themes. Coding was checked by RF and themes agreed by discussion with RF and AS. KCD wrote the final manuscript with supervision, comments and review from AS and SB.

Funding KCD is an Academic Clinical Fellow funded by Health Education East of England. SB is supported by the National Institute for Health Research (NIHR) Applied Research Collaboration East of England (ARC EoE) programme. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care.

Competing interests None declared.

Provenance and peer review Not commissioned; externally peer reviewed.

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

Read the full text or download the PDF: