what is background of the study in research paper

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What is the Background of the Study and How to Write It

What is the Background of the Study in Research? 

The background of the study is the first section of a research paper and gives context surrounding the research topic. The background explains to the reader where your research journey started, why you got interested in the topic, and how you developed the research question that you will later specify. That means that you first establish the context of the research you did with a general overview of the field or topic and then present the key issues that drove your decision to study the specific problem you chose.

Once the reader understands where you are coming from and why there was indeed a need for the research you are going to present in the following—because there was a gap in the current research, or because there is an obvious problem with a currently used process or technology—you can proceed with the formulation of your research question and summarize how you are going to address it in the rest of your manuscript.

Why is the Background of the Study Important?

No matter how surprising and important the findings of your study are, if you do not provide the reader with the necessary background information and context, they will not be able to understand your reasons for studying the specific problem you chose and why you think your study is relevant. And more importantly, an editor who does not share your enthusiasm for your work (because you did not fill them in on all the important details) will very probably not even consider your manuscript worthy of their and the reviewers’ time and will immediately send it back to you.

To avoid such desk rejections , you need to make sure you pique the reader’s interest and help them understand the contribution of your work to the specific field you study, the more general research community, or the public. Introducing the study background is crucial to setting the scene for your readers.

Table of Contents:

• What is “Background Information” in a Research Paper?
• What Should the Background of a Research Paper Include?
• Where Does the Background Section Go in Your Paper?

Background of the Study Structure

Before writing your study background, it is essential to understand what to include. The following elements should all be included in the background and are presented in greater detail in the next section:

• A general overview of the topic and why it is important (overlaps with establishing the “importance of the topic” in the Introduction)
• The current state of the research on the topic or on related topics in the field
• Controversies about current knowledge or specific past studies that undergird your research methodology
• Any claims or assumptions that have been made by researchers, institutions, or politicians that might need to be clarified
• Methods and techniques used in the study or from which your study deviated in some way

Presenting the Study Background

As you begin introducing your background, you first need to provide a general overview and include the main issues concerning the topic. Depending on whether you do “basic” (with the aim of providing further knowledge) or “applied” research (to establish new techniques, processes, or products), this is either a literature review that summarizes all relevant earlier studies in the field or a description of the process (e.g., vote counting) or practice (e.g., diagnosis of a specific disease) that you think is problematic or lacking and needs a solution.

Example s of a general overview

If you study the function of a Drosophila gene, for example, you can explain to the reader why and for whom the study of fly genetics is relevant, what is already known and established, and where you see gaps in the existing literature. If you investigated how the way universities have transitioned into online teaching since the beginning of the Covid-19 pandemic has affected students’ learning progress, then you need to present a summary of what changes have happened around the world, what the effects of those changes have been so far, and where you see problems that need to be addressed. Note that you need to provide sources for every statement and every claim you make here, to establish a solid foundation of knowledge for your own study. 

Describing the current state of knowledge

When the reader understands the main issue(s), you need to fill them in more specifically on the current state of the field (in basic research) or the process/practice/product use you describe (in practical/applied research). Cite all relevant studies that have already reported on the Drosophila gene you are interested in, have failed to reveal certain functions of it, or have suggested that it might be involved in more processes than we know so far. Or list the reports from the education ministries of the countries you are interested in and highlight the data that shows the need for research into the effects of the Corona-19 pandemic on teaching and learning.

Discussing controversies, claims, and assumptions

Are there controversies regarding your topic of interest that need to be mentioned and/or addressed? For example, if your research topic involves an issue that is politically hot, you can acknowledge this here. Have any earlier claims or assumptions been made, by other researchers, institutions, or politicians, that you think need to be clarified?

Mentioning methodologies and approaches

While putting together these details, you also need to mention methodologies : What methods/techniques have been used so far to study what you studied and why are you going to either use the same or a different approach? Are any of the methods included in the literature review flawed in such a way that your study takes specific measures to correct or update? While you shouldn’t spend too much time here justifying your methods (this can be summarized briefly in the rationale of the study at the end of the Introduction and later in the Discussion section), you can engage with the crucial methods applied in previous studies here first.

When you have established the background of the study of your research paper in such a logical way, then the reader should have had no problem following you from the more general information you introduced first to the specific details you added later. You can now easily lead over to the relevance of your research, explain how your work fits into the bigger picture, and specify the aims and objectives of your study. This latter part is usually considered the “ statement of the problem ” of your study. Without a solid research paper background, this statement will come out of nowhere for the reader and very probably raise more questions than you were planning to answer.   

Where does the study background section go in a paper?

Unless you write a research proposal or some kind of report that has a specific “Background” chapter, the background of your study is the first part of your introduction section . This is where you put your work in context and provide all the relevant information the reader needs to follow your rationale. Make sure your background has a logical structure and naturally leads into the statement of the problem at the very end of the introduction so that you bring everything together for the reader to judge the relevance of your work and the validity of your approach before they dig deeper into the details of your study in the methods section .

Consider Receiving Professional Editing Services

Now that you know how to write a background section for a research paper, you might be interested in our AI text editor at Wordvice AI. And be sure to receive professional editing services , including academic editing and proofreading , before submitting your manuscript to journals. On the Wordvice academic resources website, you can also find many more articles and other resources that can help you with writing the other parts of your research paper , with making a research paper outline before you put everything together, or with writing an effective cover letter once you are ready to submit.

• Manuscript Preparation

What is the Background of a Study and How Should it be Written?

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Table of Contents

The background of a study is one of the most important components of a research paper. The quality of the background determines whether the reader will be interested in the rest of the study. Thus, to ensure that the audience is invested in reading the entire research paper, it is important to write an appealing and effective background. So, what constitutes the background of a study, and how must it be written?

What is the background of a study?

The background of a study is the first section of the paper and establishes the context underlying the research. It contains the rationale, the key problem statement, and a brief overview of research questions that are addressed in the rest of the paper. The background forms the crux of the study because it introduces an unaware audience to the research and its importance in a clear and logical manner. At times, the background may even explore whether the study builds on or refutes findings from previous studies. Any relevant information that the readers need to know before delving into the paper should be made available to them in the background.

How is a background different from the introduction?

The introduction of your research paper is presented before the background. Let’s find out what factors differentiate the background from the introduction.

• The introduction only contains preliminary data about the research topic and does not state the purpose of the study. On the contrary, the background clarifies the importance of the study in detail.
• The introduction provides an overview of the research topic from a broader perspective, while the background provides a detailed understanding of the topic.
• The introduction should end with the mention of the research questions, aims, and objectives of the study. In contrast, the background follows no such format and only provides essential context to the study.

How should one write the background of a research paper?

The length and detail presented in the background varies for different research papers, depending on the complexity and novelty of the research topic. At times, a simple background suffices, even if the study is complex. Before writing and adding details in the background, take a note of these additional points:

• Start with a strong beginning: Begin the background by defining the research topic and then identify the target audience.
• Cover key components: Explain all theories, concepts, terms, and ideas that may feel unfamiliar to the target audience thoroughly.
• Take note of important prerequisites: Go through the relevant literature in detail. Take notes while reading and cite the sources.
• Maintain a balance: Make sure that the background is focused on important details, but also appeals to a broader audience.
• Include historical data: Current issues largely originate from historical events or findings. If the research borrows information from a historical context, add relevant data in the background.
• Explain novelty: If the research study or methodology is unique or novel, provide an explanation that helps to understand the research better.
• Increase engagement: To make the background engaging, build a story around the central theme of the research

Avoid these mistakes while writing the background:

• Ambiguity: Don’t be ambiguous. While writing, assume that the reader does not understand any intricate detail about your research.
• Unrelated themes: Steer clear from topics that are not related to the key aspects of your research topic.
• Poor organization: Do not place information without a structure. Make sure that the background reads in a chronological manner and organize the sub-sections so that it flows well.

Writing the background for a research paper should not be a daunting task. But directions to go about it can always help. At Elsevier Author Services we provide essential insights on how to write a high quality, appealing, and logically structured paper for publication, beginning with a robust background. For further queries, contact our experts now!

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What Is Background in a Research Paper?

So you have carefully written your research paper  and probably ran it through your colleagues ten to fifteen times. While there are many elements to a good research article, one of the most important elements for your readers is the background of your study.

What is Background of the Study in Research

The background of your study will provide context to the information discussed throughout the research paper . Background information may include both important and relevant studies. This is particularly important if a study either supports or refutes your thesis.

Why is Background of the Study Necessary in Research?

The background of the study discusses your problem statement, rationale, and research questions. It links  introduction to your research topic  and ensures a logical flow of ideas.  Thus, it helps readers understand your reasons for conducting the study.

Providing Background Information

The reader should be able to understand your topic and its importance. The length and detail of your background also depend on the degree to which you need to demonstrate your understanding of the topic. Paying close attention to the following questions will help you in writing background information:

• Are there any theories, concepts, terms, and ideas that may be unfamiliar to the target audience and will require you to provide any additional explanation?
• Any historical data that need to be shared in order to provide context on why the current issue emerged?
• Are there any concepts that may have been borrowed from other disciplines that may be unfamiliar to the reader and need an explanation?

Related: Ready with the background and searching for more information on journal ranking? Check this infographic on the SCImago Journal Rank today!

Is the research study unique for which additional explanation is needed? For instance, you may have used a completely new method

How to Write a Background of the Study

The structure of a background study in a research paper generally follows a logical sequence to provide context, justification, and an understanding of the research problem. It includes an introduction, general background, literature review , rationale , objectives, scope and limitations , significance of the study and the research hypothesis . Following the structure can provide a comprehensive and well-organized background for your research.

Here are the steps to effectively write a background of the study.

1. Identify Your Audience:

Determine the level of expertise of your target audience. Tailor the depth and complexity of your background information accordingly.

2. Understand the Research Problem:

Define the research problem or question your study aims to address. Identify the significance of the problem within the broader context of the field.

3. Review Existing Literature:

Conduct a thorough literature review to understand what is already known in the area. Summarize key findings, theories, and concepts relevant to your research.

4. Include Historical Data:

Integrate historical data if relevant to the research, as current issues often trace back to historical events.

5. Identify Controversies and Gaps:

Note any controversies or debates within the existing literature. Identify gaps , limitations, or unanswered questions that your research can address.

6. Select Key Components:

Choose the most critical elements to include in the background based on their relevance to your research problem. Prioritize information that helps build a strong foundation for your study.

7. Craft a Logical Flow:

Organize the background information in a logical sequence. Start with general context, move to specific theories and concepts, and then focus on the specific problem.

8. Highlight the Novelty of Your Research:

Clearly explain the unique aspects or contributions of your study. Emphasize why your research is different from or builds upon existing work.

Here are some extra tips to increase the quality of your research background:

Example of a Research Background

Here is an example of a research background to help you understand better.

The above hypothetical example provides a research background, addresses the gap and highlights the potential outcome of the study; thereby aiding a better understanding of the proposed research.

What Makes the Introduction Different from the Background?

Your introduction is different from your background in a number of ways.

• The introduction contains preliminary data about your topic that  the reader will most likely read , whereas the background clarifies the importance of the paper.
• The background of your study discusses in depth about the topic, whereas the introduction only gives an overview.
• The introduction should end with your research questions, aims, and objectives, whereas your background should not (except in some cases where your background is integrated into your introduction). For instance, the C.A.R.S. ( Creating a Research Space ) model, created by John Swales is based on his analysis of journal articles. This model attempts to explain and describe the organizational pattern of writing the introduction in social sciences.

Points to Note

Your background should begin with defining a topic and audience. It is important that you identify which topic you need to review and what your audience already knows about the topic. You should proceed by searching and researching the relevant literature. In this case, it is advisable to keep track of the search terms you used and the articles that you downloaded. It is helpful to use one of the research paper management systems such as Papers, Mendeley, Evernote, or Sente. Next, it is helpful to take notes while reading. Be careful when copying quotes verbatim and make sure to put them in quotation marks and cite the sources. In addition, you should keep your background focused but balanced enough so that it is relevant to a broader audience. Aside from these, your background should be critical, consistent, and logically structured.

Writing the background of your study should not be an overly daunting task. Many guides that can help you organize your thoughts as you write the background. The background of the study is the key to introduce your audience to your research topic and should be done with strong knowledge and thoughtful writing.

The background of a research paper typically ranges from one to two paragraphs, summarizing the relevant literature and context of the study. It should be concise, providing enough information to contextualize the research problem and justify the need for the study. Journal instructions about any word count limits should be kept in mind while deciding on the length of the final content.

The background of a research paper provides the context and relevant literature to understand the research problem, while the introduction also introduces the specific research topic, states the research objectives, and outlines the scope of the study. The background focuses on the broader context, whereas the introduction focuses on the specific research project and its objectives.

When writing the background for a study, start by providing a brief overview of the research topic and its significance in the field. Then, highlight the gaps in existing knowledge or unresolved issues that the study aims to address. Finally, summarize the key findings from relevant literature to establish the context and rationale for conducting the research, emphasizing the need and importance of the study within the broader academic landscape.

The background in a research paper is crucial as it sets the stage for the study by providing essential context and rationale. It helps readers understand the significance of the research problem and its relevance in the broader field. By presenting relevant literature and highlighting gaps, the background justifies the need for the study, building a strong foundation for the research and enhancing its credibility.

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How to Write the Background of a Study

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The background to a study sets the scene . It lays out the “state of the art”. It tells your reader about other research done on the topic in question, via useful review papers and other summaries of the literature.

Updated on May 5, 2023

The background to your study, sometimes called the ‘state of the art’ (especially in grant writing), sets the scene for a paper. This section shows readers why your research is important, relevant, and why they should continue reading. You must hook them in with a great background to your study, which is part of the overall introduction to your research paper.

In higher impact articles, such as those published in Nature or Science (which is what we are all aiming for, after all …), the study background is t he middle section of an essentially three-part introduction . This section is framed by a presentation of ‘the question’ (first part of the introduction) and a quick explanation of ‘what this paper will do’ (the third part of the introduction).

The introduction of a research paper should be “shaped” like an upside down triangle: 

Start broad. Set the scene with a large-scale general research area [e.g., why doing a PhD erases your writing skills (ha ha) or mental health in teenagers and why this is such a widespread global issue] and then focus down to the question your research addresses (e.g., how can writing skills be improved in PhD students, or brain scans and how these can be used in treatment).

Read on to learn more about framing your next research paper with a well-written and researched background section.

What is the background of a study?

The background to a study sets the scene . It lays out the “state of the art”. It tells your reader about other research done on the topic in question, via useful review papers and other summaries of the literature. 

A background is not a literature review: No one wants to read endless citations back-to-back in this section. You don’t need to list all the papers you’ve read, or all the work done in the past on this topic. 

Set the scene and frame your question in the context of the literature. Seek out review articles in particular. The aim of this section is to build on what has come before so your reader will be armed with all the information they need to understand the remainder of your article, and why - in context - the aims of your study are important.

How to write the background to your research paper

Cater to your audience.

It’s important to frame your background to the right audience.

The background of your study needs to be pitched differently depending on your target journal. A more subject-area specific journal (e.g. Journal of Brain Studies ) will be read by specialists in your field. Generally, less information to set up the paper in a wider context and less background information will be required. Your readers are already experts on the topic in question .

However, if you are aiming your paper at a more general audience (a journal like Nature or Science , for example) then you're going to need to explain more in your background. A reader of a specialized journal will know about the neocortex within the brain and where this is located, but a general reader will need you to set things up more.

Readers are always the most important people in research publishing, after all: If you want your work to be read, used, and cited (and therefore drive up your H-index as well as your institution’s ranking) you’ll need a well-pitched background of your study.

What is included in the background of a study?

Remember this section sits in the middle of the introduction. Here’s a handy template for what to include:

• Existing research on the area of study (not everything, but a broad overview. Aim to cite review papers if you can). Start this section with preliminary data and then build it out;
• Mention any controversies around your topic (either that you’ve identified, or that have been picked up by earlier work. Check the discussion sections of recent articles for pointers here);
• Any gaps in existing research?, and;
• How will your study fill these gaps? State your research methodologies. Any further research that needs to be done?

Aim for one paragraph , or a series of short paragraphs within one section. The last two of the topics outlined above can be short, just one or two sentences. These are there to hook the reader in and to frame your background so that the text leads into the final section of the introduction where you explain ‘What your paper is going to do’.

Simple really.

And finally…some thoughts

I used to get really bogged down with article writing, especially the shape of the introduction.

Here’s a trick to keep in mind: Remember that the average length of an academic research paper published in a peer reviewed journal is around 4,000 - 5,000 words - not too long. 

This means that you're likely going to be aiming for an article of about this length the next time you sit down to write: Not too many words for an effective and well-structured introduction. You’ve got about 1,500 - 2,000 words maximum. And aim to keep it short (this will be enforced by word count limits, especially in higher impact journals like Nature and Science ). Editors at these journals are trained to cut down your writing to make sure your research fits in.

Less is more, in other words.

Keeping tight word count limits in mind means you can’t write an expansive, flowing background to your study that goes off in all directions and covers a huge amount of ground. Keep an eye on our tips for what to include, cite review papers, and keep your readers interested in the question your paper seeks to address.

A well written background to your study will ensure your paper gets read all the way through to the end. Can’t ask for more than that!

The AJE Team

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Background information identifies and describes the history and nature of a well-defined research problem with reference to contextualizing existing literature. The background information should indicate the root of the problem being studied, appropriate context of the problem in relation to theory, research, and/or practice , its scope, and the extent to which previous studies have successfully investigated the problem, noting, in particular, where gaps exist that your study attempts to address. Background information does not replace the literature review section of a research paper; it is intended to place the research problem within a specific context and an established plan for its solution.

Fitterling, Lori. Researching and Writing an Effective Background Section of a Research Paper. Kansas City University of Medicine & Biosciences; Creating a Research Paper: How to Write the Background to a Study. DurousseauElectricalInstitute.com; Background Information: Definition of Background Information. Literary Devices Definition and Examples of Literary Terms.

Importance of Having Enough Background Information

Background information expands upon the key points stated in the beginning of your introduction but is not intended to be the main focus of the paper. It generally supports the question, what is the most important information the reader needs to understand before continuing to read the paper? Sufficient background information helps the reader determine if you have a basic understanding of the research problem being investigated and promotes confidence in the overall quality of your analysis and findings. This information provides the reader with the essential context needed to conceptualize the research problem and its significance before moving on to a more thorough analysis of prior research.

Forms of contextualization included in background information can include describing one or more of the following:

• Cultural -- placed within the learned behavior of a specific group or groups of people.
• Economic -- of or relating to systems of production and management of material wealth and/or business activities.
• Gender -- located within the behavioral, cultural, or psychological traits typically associated with being self-identified as male, female, or other form of  gender expression.
• Historical -- the time in which something takes place or was created and how the condition of time influences how you interpret it.
• Interdisciplinary -- explanation of theories, concepts, ideas, or methodologies borrowed from other disciplines applied to the research problem rooted in a discipline other than the discipline where your paper resides.
• Philosophical -- clarification of the essential nature of being or of phenomena as it relates to the research problem.
• Physical/Spatial -- reflects the meaning of space around something and how that influences how it is understood.
• Political -- concerns the environment in which something is produced indicating it's public purpose or agenda.
• Social -- the environment of people that surrounds something's creation or intended audience, reflecting how the people associated with something use and interpret it.
• Temporal -- reflects issues or events of, relating to, or limited by time. Concerns past, present, or future contextualization and not just a historical past.

Background information can also include summaries of important research studies . This can be a particularly important element of providing background information if an innovative or groundbreaking study about the research problem laid a foundation for further research or there was a key study that is essential to understanding your arguments. The priority is to summarize for the reader what is known about the research problem before you conduct the analysis of prior research. This is accomplished with a general summary of the foundational research literature [with citations] that document findings that inform your study's overall aims and objectives.

NOTE : Research studies cited as part of the background information of your introduction should not include very specific, lengthy explanations. This should be discussed in greater detail in your literature review section. If you find a study requiring lengthy explanation, consider moving it to the literature review section.

ANOTHER NOTE : In some cases, your paper's introduction only needs to introduce the research problem, explain its significance, and then describe a road map for how you are going to address the problem; the background information basically forms the introduction part of your literature review. That said, while providing background information is not required, including it in the introduction is a way to highlight important contextual information that could otherwise be hidden or overlooked by the reader if placed in the literature review section.

Background of the Problem Section: What do you Need to Consider? Anonymous. Harvard University; Hopkins, Will G. How to Write a Research Paper. SPORTSCIENCE, Perspectives/Research Resources. Department of Physiology and School of Physical Education, University of Otago, 1999; Green, L. H. How to Write the Background/Introduction Section. Physics 499 Powerpoint slides. University of Illinois; Pyrczak, Fred. Writing Empirical Research Reports: A Basic Guide for Students of the Social and Behavioral Sciences . 8th edition. Glendale, CA: Pyrczak Publishing, 2014; Stevens, Kathleen C. “Can We Improve Reading by Teaching Background Information?.” Journal of Reading 25 (January 1982): 326-329; Woodall, W. Gill. Writing the Background and Significance Section. Senior Research Scientist and Professor of Communication. Center on Alcoholism, Substance Abuse, and Addictions. University of New Mexico.

Structure and Writing Style

Providing background information in the introduction of a research paper serves as a bridge that links the reader to the research problem . Precisely how long and in-depth this bridge should be is largely dependent upon how much information you think the reader will need to know in order to fully understand the problem being discussed and to appreciate why the issues you are investigating are important.

From another perspective, the length and detail of background information also depends on the degree to which you need to demonstrate to your professor how much you understand the research problem. Keep this in mind because providing pertinent background information can be an effective way to demonstrate that you have a clear grasp of key issues, debates, and concepts related to your overall study.

The structure and writing style of your background information can vary depending upon the complexity of your research and/or the nature of the assignment. However, in most cases it should be limited to only one to two paragraphs in your introduction.

Given this, here are some questions to consider while writing this part of your introduction :

• Are there concepts, terms, theories, or ideas that may be unfamiliar to the reader and, thus, require additional explanation?
• Are there historical elements that need to be explored in order to provide needed context, to highlight specific people, issues, or events, or to lay a foundation for understanding the emergence of a current issue or event?
• Are there theories, concepts, or ideas borrowed from other disciplines or academic traditions that may be unfamiliar to the reader and therefore require further explanation?
• Is there a key study or small set of studies that set the stage for understanding the topic and frames why it is important to conduct further research on the topic?
• Y our study uses a method of analysis never applied before;
• Your study investigates a very esoteric or complex research problem;
• Your study introduces new or unique variables that need to be taken into account ; or,
• Your study relies upon analyzing unique texts or documents, such as, archival materials or primary documents like diaries or personal letters that do not represent the established body of source literature on the topic?

Almost all introductions to a research problem require some contextualizing, but the scope and breadth of background information varies depending on your assumption about the reader's level of prior knowledge . However, despite this assessment, background information should be brief and succinct and sets the stage for the elaboration of critical points or in-depth discussion of key issues in the literature review section of your paper.

Writing Tip

Background Information vs. the Literature Review

Incorporating background information into the introduction is intended to provide the reader with critical information about the topic being studied, such as, highlighting and expanding upon foundational studies conducted in the past, describing important historical events that inform why and in what ways the research problem exists, defining key components of your study [concepts, people, places, phenomena] and/or placing the research problem within a particular context. Although introductory background information can often blend into the literature review portion of the paper, essential background information should not be considered a substitute for a comprehensive review and synthesis of relevant research literature.

Hart, Cris. Doing a Literature Review: Releasing the Social Science Research Imagination . Thousand Oaks, CA: Sage, 1998; Pyrczak, Fred. Writing Empirical Research Reports: A Basic Guide for Students of the Social and Behavioral Sciences . 8th edition. Glendale, CA: Pyrczak Publishing, 2014.

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How to Write the Background of the Study in Research (Part 1)

Background of the Study in Research: Definition and the Core Elements it Contains

Before we embark on a detailed discussion on how to write the background of the study of your proposed research or thesis, it is important to first discuss its meaning and the core elements that it should contain. This is obviously because understanding the nature of the background of the study in research and knowing exactly what to include in it allow us to have both greater control and clear direction of the writing process.

So, what really is the background of the study and what are the core elements that it should contain?

The background of the study, which usually forms the first section of the introduction to a research paper or thesis, provides the overview of the study. In other words, it is that section of the research paper or thesis that establishes the context of the study. Its main function is to explain why the proposed research is important and essential to understanding the main aspects of the study.

The background of the study, therefore, is the section of the research paper or thesis that identifies the problem or gap of the study that needs to addressed and justifies the need for conducting the study. It also articulates the main goal of the study and the thesis statement, that is, the main claim or argument of the paper.

Given this brief understanding of the background of the study, we can anticipate what readers or thesis committee members expect from it. As we can see, the background of the study should contain the following major points:

1) brief discussion on what is known about the topic under investigation; 2) An articulation of the research gap or problem that needs to be addressed; 3) What the researcher would like to do or aim to achieve in the study ( research goal); 4) The thesis statement, that is, the main argument or contention of the paper (which also serves as the reason why the researcher would want to pursue the study); 5) The major significance or contribution of the study to a particular discipline; and 6) Depending on the nature of the study, an articulation of the hypothesis of the study.

Thus, when writing the background of the study, you should plan and structure it based on the major points just mentioned. With this, you will have a clear picture of the flow of the tasks that need to be completed in writing this section of your research or thesis proposal.

Now, how do you go about writing the background of the study in your proposed research or thesis?

The next lessons will address this question.

How to Write the Opening Paragraphs of the Background of the Study?

To begin with, let us assume that you already have conducted a preliminary research on your chosen topic, that is, you already have read a lot of literature and gathered relevant information for writing the background of your study. Let us also assume that you already have identified the gap of your proposed research and have already developed the research questions and thesis statement. If you have not yet identified the gap in your proposed research, you might as well go back to our lesson on how to identify a research gap.

So, we will just put together everything that you have researched into a background of the study (assuming, again, that you already have the necessary information). But in this lesson, let’s just focus on writing the opening paragraphs.

It is important to note at this point that there are different styles of writing the background of the study. Hence, what I will be sharing with you here is not just “the” only way of writing the background of the study. As a matter of fact, there is no “one-size-fits-all” style of writing this part of the research or thesis. At the end of the day, you are free to develop your own. However, whatever style it would be, it always starts with a plan which structures the writing process into stages or steps. The steps that I will share with below are just some of the most effective ways of writing the background of the study in research.

So, let’s begin.

It is always a good idea to begin the background of your study by giving an overview of your research topic. This may include providing a definition of the key concepts of your research or highlighting the main developments of the research topic.

Let us suppose that the topic of your study is the “lived experiences of students with mathematical anxiety”.

Here, you may start the background of your study with a discussion on the meaning, nature, and dynamics of the term “mathematical anxiety”. The reason for this is too obvious: “mathematical anxiety” is a highly technical term that is specific to mathematics. Hence, this term is not readily understandable to non-specialists in this field.

So, you may write the opening paragraph of your background of the study with this:

“Mathematical anxiety refers to the individual’s unpleasant emotional mood responses when confronted with a mathematical situation.”

Since you do not invent the definition of the term “mathematical anxiety”, then you need to provide a citation to the source of the material from which you are quoting. For example, you may now say:

“Mathematical anxiety refers to the individual’s unpleasant emotional mood responses when confronted with a mathematical situation (Eliot, 2020).”

And then you may proceed with the discussion on the nature and dynamics of the term “mathematical anxiety”. You may say:

“Lou (2019) specifically identifies some of the manifestations of this type of anxiety, which include, but not limited to, depression, helplessness, nervousness and fearfulness in doing mathematical and numerical tasks.”

After explaining to your readers the meaning, nature, and dynamics (as well as some historical development if you wish to) of the term “mathematical anxiety”, you may now proceed to showing the problem or gap of the study. As you may already know, the research gap is the problem that needs to be addressed in the study. This is important because no research activity is possible without the research gap.

Let us suppose that your research problem or gap is: “Mathematical anxiety can negatively affect not just the academic achievement of the students but also their future career plans and total well-being. Also, there are no known studies that deal with the mathematical anxiety of junior high school students in New Zealand.” With this, you may say:

“If left unchecked, as Shapiro (2019) claims, this problem will expand and create a total avoidance pattern on the part of the students, which can be expressed most visibly in the form of cutting classes and habitual absenteeism. As we can see, this will negatively affect the performance of students in mathematics. In fact, the study conducted by Luttenberger and Wimmer (2018) revealed that the outcomes of mathematical anxiety do not only negatively affect the students’ performance in math-related situations but also their future career as professionals. Without a doubt, therefore, mathematical anxiety is a recurring problem for many individuals which will negatively affect the academic success and future career of the student.”

Now that you already have both explained the meaning, nature, and dynamics of the term “mathematical anxiety” and articulated the gap of your proposed research, you may now state the main goal of your study. You may say:

“Hence, it is precisely in this context that the researcher aims to determine the lived experiences of those students with mathematical anxiety. In particular, this proposed thesis aims to determine the lived experiences of the junior high school students in New Zealand and identify the factors that caused them to become disinterested in mathematics.”

Please note that you should not end the first paragraph of your background of the study with the articulation of the research goal. You also need to articulate the “thesis statement”, which usually comes after the research goal. As is well known, the thesis statement is the statement of your argument or contention in the study. It is more of a personal argument or claim of the researcher, which specifically highlights the possible contribution of the study. For example, you may say:

“The researcher argues that there is a need to determine the lived experiences of these students with mathematical anxiety because knowing and understanding the difficulties and challenges that they have encountered will put the researcher in the best position to offer some alternatives to the problem. Indeed, it is only when we have performed some kind of a ‘diagnosis’ that we can offer practicable solutions to the problem. And in the case of the junior high school students in New Zealand who are having mathematical anxiety, determining their lived experiences as well as identifying the factors that caused them to become disinterested in mathematics are the very first steps in addressing the problem.”

If we combine the bits and pieces that we have written above, we can now come up with the opening paragraphs of your background of the study, which reads:

As we can see, we can find in the first paragraph 5 essential elements that must be articulated in the background of the study, namely:

1) A brief discussion on what is known about the topic under investigation; 2) An articulation of the research gap or problem that needs to be addressed; 3) What the researcher would like to do or aim to achieve in the study (research goal); 4) The thesis statement , that is, the main argument or claim of the paper; and 5) The major significance or contribution of the study to a particular discipline. So, that’s how you write the opening paragraphs of your background of the study. The next lesson will talk about writing the body of the background of the study.

How to Write the Body of the Background of the Study?

If we liken the background of the study to a sitting cat, then the opening paragraphs that we have completed in the previous lesson would just represent the head of the cat.

This means we still have to write the body (body of the cat) and the conclusion (tail). But how do we write the body of the background of the study? What should be its content?

Truly, this is one of the most difficult challenges that fledgling scholars faced. Because they are inexperienced researchers and didn’t know what to do next, they just wrote whatever they wished to write. Fortunately, this is relatively easy if they know the technique.

One of the best ways to write the body of the background of the study is to attack it from the vantage point of the research gap. If you recall, when we articulated the research gap in the opening paragraphs, we made a bold claim there, that is, there are junior high school students in New Zealand who are experiencing mathematical anxiety. Now, you have to remember that a “statement” remains an assumption until you can provide concrete proofs to it. This is what we call the “epistemological” aspect of research. As we may already know, epistemology is a specific branch of philosophy that deals with the validity of knowledge. And to validate knowledge is to provide concrete proofs to our statements. Hence, the reason why we need to provide proofs to our claim that there are indeed junior high school students in New Zealand who are experiencing mathematical anxiety is the obvious fact that if there are none, then we cannot proceed with our study. We have no one to interview with in the first. In short, we don’t have respondents.

The body of the background of the study, therefore, should be a presentation and articulation of the proofs to our claim that indeed there are junior high school students in New Zealand who are experiencing mathematical anxiety. Please note, however, that this idea is true only if you follow the style of writing the background of the study that I introduced in this course.

So, how do we do this?

One of the best ways to do this is to look for literature on mathematical anxiety among junior high school students in New Zealand and cite them here. However, if there are not enough literature on this topic in New Zealand, then we need to conduct initial interviews with these students or make actual classroom observations and record instances of mathematical anxiety among these students. But it is always a good idea if we combine literature review with interviews and actual observations.

Assuming you already have the data, then you may now proceed with the writing of the body of your background of the study. For example, you may say:

“According to records and based on the researcher’s firsthand experience with students in some junior high schools in New Zealand, indeed, there are students who lost interest in mathematics. For one, while checking the daily attendance and monitoring of the students, it was observed that some of them are not always attending classes in mathematics but are regularly attending the rest of the required subjects.”

After this sentence, you may insert some literature that will support this position. For example, you may say:

“As a matter of fact, this phenomenon is also observed in the work of Estonanto. In his study titled ‘Impact of Math Anxiety on Academic Performance in Pre-Calculus of Senior High School’, Estonanto (2019) found out that, inter alia, students with mathematical anxiety have the tendency to intentionally prioritize other subjects and commit habitual tardiness and absences.”

Then you may proceed saying:

“With this initial knowledge in mind, the researcher conducted initial interviews with some of these students. The researcher learned that one student did not regularly attend his math subject because he believed that he is not good in math and no matter how he listens to the topic he will not learn.”

Then you may say:

“Another student also mentioned that she was influenced by her friends’ perception that mathematics is hard; hence, she avoids the subject. Indeed, these are concrete proofs that there are some junior high school students in New Zealand who have mathematical anxiety. As already hinted, “disinterest” or the loss of interest in mathematics is one of the manifestations of a mathematical anxiety.”

If we combine what we have just written above, then we can have the first two paragraphs of the body of our background of the study. It reads:

“According to records and based on the researcher’s firsthand experience with students in some junior high schools in New Zealand, indeed there are students who lost interest in mathematics. For one, while checking the daily attendance and monitoring of the students, it was observed that some of them are not always attending classes in mathematics but are regularly attending the rest of the required subjects. As a matter of fact, this phenomenon is also observed in the work of Estonanto. In his study titled ‘Impact of Math Anxiety on Academic Performance in Pre-Calculus of Senior High School’, Estonanto (2019) found out that, inter alia, students with mathematical anxiety have the tendency to intentionally prioritize other subjects and commit habitual tardiness and absences.

With this initial knowledge in mind, the researcher conducted initial interviews with some of these students. The researcher learned that one student did not regularly attend his math subject because he believed that he is not good in math and no matter how he listens to the topic he will not learn. Another student also mentioned that she was influenced by her friends’ perception that mathematics is hard; hence, she avoids the subject. Indeed, these are concrete proofs that there are some junior high school students in New Zealand who have mathematical anxiety. As already hinted, “disinterest” or the loss of interest in mathematics is one of the manifestations of a mathematical anxiety.”

And then you need validate this observation by conducting another round of interview and observation in other schools. So, you may continue writing the body of the background of the study with this:

“To validate the information gathered from the initial interviews and observations, the researcher conducted another round of interview and observation with other junior high school students in New Zealand.”

“On the one hand, the researcher found out that during mathematics time some students felt uneasy; in fact, they showed a feeling of being tensed or anxious while working with numbers and mathematical problems. Some were even afraid to seat in front, while some students at the back were secretly playing with their mobile phones. These students also show remarkable apprehension during board works like trembling hands, nervous laughter, and the like.”

Then provide some literature that will support your position. You may say:

“As Finlayson (2017) corroborates, emotional symptoms of mathematical anxiety involve feeling of helplessness, lack of confidence, and being nervous for being put on the spot. It must be noted that these occasionally extreme emotional reactions are not triggered by provocative procedures. As a matter of fact, there are no personally sensitive questions or intentional manipulations of stress. The teacher simply asked a very simple question, like identifying the parts of a circle. Certainly, this observation also conforms with the study of Ashcraft (2016) when he mentions that students with mathematical anxiety show a negative attitude towards math and hold self-perceptions about their mathematical abilities.”

And then you proceed:

“On the other hand, when the class had their other subjects, the students show a feeling of excitement. They even hurried to seat in front and attentively participating in the class discussion without hesitation and without the feeling of being tensed or anxious. For sure, this is another concrete proof that there are junior high school students in New Zealand who have mathematical anxiety.”

To further prove the point that there indeed junior high school students in New Zealand who have mathematical anxiety, you may solicit observations from other math teachers. For instance, you may say:

“The researcher further verified if the problem is also happening in other sections and whether other mathematics teachers experienced the same observation that the researcher had. This validation or verification is important in establishing credibility of the claim (Buchbinder, 2016) and ensuring reliability and validity of the assertion (Morse et al., 2002). In this regard, the researcher attempted to open up the issue of math anxiety during the Departmentalized Learning Action Cell (LAC), a group discussion of educators per quarter, with the objective of ‘Teaching Strategies to Develop Critical Thinking of the Students’. During the session, one teacher corroborates the researcher’s observation that there are indeed junior high school students in New Zealand who have mathematical anxiety. The teacher pointed out that truly there were students who showed no extra effort in mathematics class in addition to the fact that some students really avoided the subject. In addition, another math teacher expressed her frustrations about these students who have mathematical anxiety. She quipped: “How can a teacher develop the critical thinking skills or ability of the students if in the first place these students show avoidance and disinterest in the subject?’.”

Again, if we combine what we have just written above, then we can now have the remaining parts of the body of the background of the study. It reads:

So, that’s how we write the body of the background of the study in research . Of course, you may add any relevant points which you think might amplify your content. What is important at this point is that you now have a clear idea of how to write the body of the background of the study.

How to Write the Concluding Part of the Background of the Study?

Since we have already completed the body of our background of the study in the previous lesson, we may now write the concluding paragraph (the tail of the cat). This is important because one of the rules of thumb in writing is that we always put a close to what we have started.

It is important to note that the conclusion of the background of the study is just a rehashing of the research gap and main goal of the study stated in the introductory paragraph, but framed differently. The purpose of this is just to emphasize, after presenting the justifications, what the study aims to attain and why it wants to do it. The conclusion, therefore, will look just like this:

“Given the above discussion, it is evident that there are indeed junior high school students in New Zealand who are experiencing mathematical anxiety. And as we can see, mathematical anxiety can negatively affect not just the academic achievement of the students but also their future career plans and total well-being. Again, it is for this reason that the researcher attempts to determine the lived experiences of those junior high school students in New Zealand who are experiencing a mathematical anxiety.”

If we combine all that we have written from the very beginning, the entire background of the study would now read:

If we analyze the background of the study that we have just completed, we can observe that in addition to the important elements that it should contain, it has also addressed other important elements that readers or thesis committee members expect from it.

On the one hand, it provides the researcher with a clear direction in the conduct of the study. As we can see, the background of the study that we have just completed enables us to move in the right direction with a strong focus as it has set clear goals and the reasons why we want to do it. Indeed, we now exactly know what to do next and how to write the rest of the research paper or thesis.

On the other hand, most researchers start their research with scattered ideas and usually get stuck with how to proceed further. But with a well-written background of the study, just as the one above, we have decluttered and organized our thoughts. We have also become aware of what have and have not been done in our area of study, as well as what we can significantly contribute in the already existing body of knowledge in this area of study.

Please note, however, as I already mentioned previously, that the model that I have just presented is only one of the many models available in textbooks and other sources. You are, of course, free to choose your own style of writing the background of the study. You may also consult your thesis supervisor for some guidance on how to attack the writing of your background of the study.

Lastly, and as you may already know, universities around the world have their own thesis formats. Hence, you should follow your university’s rules on the format and style in writing your research or thesis. What is important is that with the lessons that you learned in this course, you can now easily write the introductory part of your thesis, such as the background of the study.

Writing Research Background

Research background is a brief outline of the most important studies that have been conducted so far presented in a chronological order. Research background part in introduction chapter can be also headed ‘Background of the Study.” Research background should also include a brief discussion of major theories and models related to the research problem.

Specifically, when writing research background you can discuss major theories and models related to your research problem in a chronological order to outline historical developments in the research area.  When writing research background, you also need to demonstrate how your research relates to what has been done so far in the research area.

Research background is written after the literature review. Therefore, literature review has to be the first and the longest stage in the research process, even before the formulation of research aims and objectives, right after the selection of the research area. Once the research area is selected, the literature review is commenced in order to identify gaps in the research area.

Research aims and objectives need to be closely associated with the elimination of this gap in the literature. The main difference between background of the study and literature review is that the former only provides general information about what has been done so far in the research area, whereas the latter elaborates and critically reviews previous works.

John Dudovskiy

Organizing Academic Research Papers: Background Information

• Purpose of Guide
• Design Flaws to Avoid
• Glossary of Research Terms
• Narrowing a Topic Idea
• Broadening a Topic Idea
• Extending the Timeliness of a Topic Idea
• Academic Writing Style
• Choosing a Title
• Making an Outline
• Paragraph Development
• Executive Summary
• Background Information
• The Research Problem/Question
• Theoretical Framework
• Citation Tracking
• Content Alert Services
• Evaluating Sources
• Primary Sources
• Secondary Sources
• Tertiary Sources
• What Is Scholarly vs. Popular?
• Qualitative Methods
• Quantitative Methods
• Using Non-Textual Elements
• Limitations of the Study
• Common Grammar Mistakes
• Avoiding Plagiarism
• Footnotes or Endnotes?
• Further Readings
• Annotated Bibliography
• Dealing with Nervousness
• Using Visual Aids
• Grading Someone Else's Paper
• How to Manage Group Projects
• Multiple Book Review Essay
• Reviewing Collected Essays
• About Informed Consent
• Writing Field Notes
• Writing a Policy Memo
• Writing a Research Proposal
• Acknowledgements

Background information identifies and describes the history and nature of a well-defined research problem with reference to the existing literature. Background information in your Introduction should indicate the root of the problem being studied, its scope, and the extent to which previous studies have successfully investigated the problem, noting, in particular, where gaps exist that your study attempts to address.  Introductory background information differs from a literature review in that it places the research problem in proper context rather than thoroughly examining pertinent literature.

Importance of Having Enough Background Information

Background information expands upon the key points stated in your introduction but is not the main focus of the paper. Sufficient background information helps your reader determine if you have a basic understanding of the research problem being investigated and promotes confidence in the overall quality of your analysis and findings.

Background information provides the reader with the essential context needed to understand the research problem . Depending on the topic being studied, forms of contextualization may include:

• Cultural -- the issue placed within the learned behavior of specific groups of people.
• Economic -- of or relating to systems of production and management of material wealth and/or business activities.
• Historical -- the time in which something takes place or was created and how that influences how you interpret it.
• Philosophical -- clarification of the essential nature of being or of phenomena as it relates to the research problem.
• Physical/Spatial -- reflects the space around something and how that influences how you see it.
• Political -- concerns the environment in which something is produced indicating it's public purpose or agenda.
• Social -- the environment of people that surrounds something's creation or intended audience, reflecting how the people around something use and interpret it.
• Temporal -- reflects issues or events of, relating to, or limited by time.

Background information can also include summaries of important, relevant research studies . The key is to summarize for the reader what is known about the specific research problem before you conducted your analysis. This is accomplished with a general review of the foundational research literature (with citations) that report findings that inform your study's aims and objectives.

NOTE : Research studies cited as part of the background information of your introduction should not include very specific, lengthy explanations. This should be discussed in greater detail in your literature review section.

Background of the Problem Section: What do you Need to Consider? Anonymous. Harvard University; Hopkins, Will G. How to Write a Research Paper . SPORTSCIENCE, Perspectives/Research Resources. Department of Physiology and School of Physical Education, University of Otago, 1999; Green, L. H. How to Write the Background/Introduction Section. Physics 499 Powerpoint slides. University of Illinois; Woodall, W. Gill. Writing the Background and Significance Section. Senior Research Scientist and Professor of Communication. Center on Alcoholism, Substance Abuse, and Addictions. University of New Mexico.  

Structure and Writing Style

Providing background information in the Introduction of a research paper serves as a bridge that links the reader to the topic of your study . But precisely how long and in-depth this bridge should be is largely dependent upon how much information you think the reader will need in order to understand the research problem being discussed and to appreciate why the issues you are investigating are important.

From another perspective, the length and detail of background information also depends on the degree to which you need to demonstrate to your professor how much you understand the topic. Keep this in mind because providing succinct background information can be an effective way to show that you have a clear grasp of key issues and concepts underpinning your overall study. Don't try to show off, though!

Given that the structure and writing style of your background information can vary depending upon the complexity of your research and/or the nature of the assignment, here are some questions to consider while writing :

• Are there concepts, terms, theories, or ideas that may be unfamiliar to the reader and, thus, require additional explanation?
• Are there historical elements that need to be explored in order to add needed context, to highlight specific people, issues, or events, or to lay a foundation for understanding the emergence of a current issue or event?
• Is the research study unusual in some way that requires additional explanation, such as, a) your study uses a method never applied before to the research problem you are investigating; b) your study investigates a very esoteric or complex research problem; or, c) your study relies upon analyzing unique texts or documents, such as archival materials or primary documents like diaries or personal letters, that do not represent the established body of source literature on the topic.

Background of the Problem Section: What do you Need to Consider? Anonymous. Harvard University; Hopkins, Will G. How to Write a Research Paper . SPORTSCIENCE, Perspectives/Research Resources. Department of Physiology and School of Physical Education, University of Otago, 1999; Green, L. H. How to Write the Background/Introduction Section. Physics 499 Powerpoint slides. University of Illinois; Woodall, W. Gill. Writing the Background and Significance Section. Senior Research Scientist and Professor of Communication. Center on Alcoholism, Substance Abuse, and Addictions. University of New Mexico.

Writing Tip

Background Information vs. the Literature Review

Incorporating background information into the Introduction is intended to provide the reader with critical information about the topic being studied, such as highlighting and expanding upon foundational studies conducted in the past, important historical events that inform why and in what ways the research problem exists, or defining key components of your study [concepts, people, places, things]. Although in social sciences research introductory background information can often blend into the literature review portion of the paper, basic background information should not be considered a substitute for a comprehensive review and synthesis of relevant research literature.

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This paper is in the following e-collection/theme issue:

Published on 6.5.2024 in Vol 12 (2024)

Assessing the Efficacy of ChatGPT Versus Human Researchers in Identifying Relevant Studies on mHealth Interventions for Improving Medication Adherence in Patients With Ischemic Stroke When Conducting Systematic Reviews: Comparative Analysis

Authors of this article:

Original Paper

• Suebsarn Ruksakulpiwat 1 , RN, MMed, PhD   ; 
• Lalipat Phianhasin 1 , RN, MS, AGPCNP-BC   ; 
• Chitchanok Benjasirisan 1 , RN, MS   ; 
• Kedong Ding 2 , AM   ; 
• Anuoluwapo Ajibade 3 , BS   ; 
• Ayanesh Kumar 4 , MS   ; 
• Cassie Stewart 5  

1 Department of Medical Nursing, Faculty of Nursing, Mahidol University, Bangkok, Thailand

2 Jack, Joseph and Morton Mandel School of Applied Social Sciences, Case Western Reserve University, Cleveland, OH, United States

3 College of Art and Science, Department of Anthropology, Case Western Reserve University, Cleveland, OH, United States

4 School of Medicine, Case Western Reserve University, Cleveland, OH, United States

5 Frances Payne Bolton School of Nursing, Case Western Reserve University, Cleveland, OH, United States

Corresponding Author:

Suebsarn Ruksakulpiwat, RN, MMed, PhD

Department of Medical Nursing, Faculty of Nursing, Mahidol University

2 Wang Lang Road, Siriraj, Bangkok Noi

Bangkok, 10700

Phone: 66 984782692

Email: [email protected]

Background: ChatGPT by OpenAI emerged as a potential tool for researchers, aiding in various aspects of research. One such application was the identification of relevant studies in systematic reviews. However, a comprehensive comparison of the efficacy of relevant study identification between human researchers and ChatGPT has not been conducted.

Objective: This study aims to compare the efficacy of ChatGPT and human researchers in identifying relevant studies on medication adherence improvement using mobile health interventions in patients with ischemic stroke during systematic reviews.

Methods: This study used the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Four electronic databases, including CINAHL Plus with Full Text, Web of Science, PubMed, and MEDLINE, were searched to identify articles published from inception until 2023 using search terms based on MeSH (Medical Subject Headings) terms generated by human researchers versus ChatGPT. The authors independently screened the titles, abstracts, and full text of the studies identified through separate searches conducted by human researchers and ChatGPT. The comparison encompassed several aspects, including the ability to retrieve relevant studies, accuracy, efficiency, limitations, and challenges associated with each method.

Results: A total of 6 articles identified through search terms generated by human researchers were included in the final analysis, of which 4 (67%) reported improvements in medication adherence after the intervention. However, 33% (2/6) of the included studies did not clearly state whether medication adherence improved after the intervention. A total of 10 studies were included based on search terms generated by ChatGPT, of which 6 (60%) overlapped with studies identified by human researchers. Regarding the impact of mobile health interventions on medication adherence, most included studies (8/10, 80%) based on search terms generated by ChatGPT reported improvements in medication adherence after the intervention. However, 20% (2/10) of the studies did not clearly state whether medication adherence improved after the intervention. The precision in accurately identifying relevant studies was higher in human researchers (0.86) than in ChatGPT (0.77). This is consistent with the percentage of relevance, where human researchers (9.8%) demonstrated a higher percentage of relevance than ChatGPT (3%). However, when considering the time required for both humans and ChatGPT to identify relevant studies, ChatGPT substantially outperformed human researchers as it took less time to identify relevant studies.

Conclusions: Our comparative analysis highlighted the strengths and limitations of both approaches. Ultimately, the choice between human researchers and ChatGPT depends on the specific requirements and objectives of each review, but the collaborative synergy of both approaches holds the potential to advance evidence-based research and decision-making in the health care field.

Introduction

Artificial intelligence (AI) is the field of computer science that studies and develops systems that can perform tasks, typically requiring human intelligence, such as reasoning, learning, decision-making, natural language processing (NLP), computer vision, and speech recognition [ 1 ]. AI is a rapidly evolving field with applications in various domains, for example, health care, education, business, and entertainment [ 2 ]. One of the subfields of AI is NLP, which deals with analyzing and generating natural language texts [ 3 ]. Chatbots, a type of NLP system, can interact with humans using natural language, either through text or speech. Chatbots can be used for various purposes, including customer service, entertainment, education, and information retrieval [ 3 ]. However, developing chatbots that can engage in natural and coherent conversations with humans is a challenging task that requires advanced NLP techniques and large-scale data.

One of the recent advances in NLP is the development of GPT models, which are neural network models that can generate natural language texts based on a given input or context [ 4 ]. GPT models are trained on large corpora of text from various sources, such as books, websites, news articles, and social media posts [ 4 ]. GPT models have been used to create chatbots that can generate realistic and diverse responses to human queries or messages [ 4 ]. Although GPT models have been developed by various research groups and companies (ie, OpenAI, Google, Facebook, and Microsoft), the first one was introduced by OpenAI in 2019 [ 5 ]. Since then, ChatGPT has been improved and refined by researchers and developers, who have applied it to various tasks and scenarios, such as customer service, education, entertainment, and social media [ 5 ]. ChatGPT models aim to provide engaging, informative, and coherent dialogues with users across different domains and tasks [ 4 ].

ChatGPT has been applied in the medical field in various ways. For instance, in medical practice, it has the ability to help streamline the clinical workflow, enhance diagnostics, and predict disease risk and outcome [ 6 ]. For medical education, ChatGPT can be useful in tailoring education and enabling powerful self-learning [ 6 ]. In terms of medical research, a previous study reported that ChatGPT has the potential to advance understanding, identify new research questions, and improve data analysis and interpretation [ 7 ]. In addition, ChatGPT extends to involve in writing articles through improvement in language and communication of result findings [ 6 ]. In particular, in the literature review process, which is time and effort consuming, ChatGPT has a promising advantage because of its potential ability to analyze large amounts of data, particularly in scientific articles [ 8 ]. Furthermore, ChatGPT was reported to have the potential to generate effective Boolean queries for systematic review literature searches [ 9 ].

Although ChatGPT has several advantages in medical research, it has limitations that could impact the quality of research, particularly in the literature review and search strategies processes. Citation inaccuracies, insufficient references, and references to nonexistent sources were reported as current problems [ 6 ]. Moreover, ChatGPT has a limited knowledge period based on the data sets used in ChatGPT training, which limits the reliability of the updated source of the literature review [ 6 ]. In a previous study, researchers were advised to consider the potential for incorrect MeSH (Medical Subject Headings) terms and the varying effectiveness of search queries with multiple requests when devising search strategies for a systematic review [ 9 ]. However, ChatGPT has a high potential to be used in medical research in the future. Therefore, it is imperative to explore and develop to improve and use it effectively.

Despite the significant benefits and limitations of using ChatGPT, the evaluation of the quality and performance of ChatGPT models in the review process remains unclear. Therefore, this study aims to compare the efficacy of ChatGPT and human researchers in identifying relevant health-related studies, such as research on medication adherence improvement using mobile health (mHealth) interventions in patients with ischemic stroke. The review will use systematic methods to search, select, appraise, and synthesize to address the following questions: (1) How does ChatGPT’s performance compare to that of human researchers in terms of accuracy in identifying relevant studies? (2) What challenges and limitations arise from using ChatGPT versus human researchers for identifying relevant studies in systematic reviews? (3) What are the implications of using ChatGPT to enhance the efficiency of systematic reviews? The results of this review will provide crucial insights into the potential of ChatGPT as an innovative tool for conducting systematic reviews.

This study aims to compare the efficacy of using ChatGPT and human researchers in identifying relevant studies on medication adherence improvement using mHealth interventions in patients with ischemic stroke during systematic reviews.

Identify Relevant Studies

In this study, we used the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) [ 10 ] guidelines to identify the relevant studies. Overall, 4 electronic databases, including CINAHL Plus with Full Text, Web of Science, PubMed, and MEDLINE, were searched to identify articles published from inception until 2023 on using mHealth interventions for improving medication adherence in patients with ischemic stroke. We used search terms based on MeSH using Boolean phrases generated by human researchers and ChatGPT version 3.5 to identify relevant studies. The reference lists of the included studies, generated by human researchers and ChatGPT, were separately stored and screened in EndNote (EndNote X7 reference management software package). A PRISMA flow diagram was created to present the results of the search and screening process.

Study Selection

The authors independently screened the titles and abstracts of the studies identified through separate searches conducted by human researchers and ChatGPT to determine their relevance. Subsequently, the full text of the selected articles was also assessed to ensure they met the predetermined inclusion criteria. A consistent set of inclusion criteria was applied to ensure that only studies relevant to the review’s objective were included. In contrast, the same exclusion criteria were used to eliminate literature unrelated to the review ( Textbox 1 ).

Inclusion criteria

• Studies that aimed to use mobile health interventions for improving medication adherence
• Studies that primarily included adults with ischemic stroke or transient ischemic attack (TIA) aged ≥18 years (if the study included other stroke types, such as hemorrhagic stroke, it is acceptable, but the study population must include adults with ischemic stroke or TIA)
• Studies in English
• Studies that were published from inception until 2023

Exclusion criteria

• Studies that included children or adolescents aged <18 years
• Conference proceedings, abstracts, review articles, protocols, dissertations, letters to the editor, brief reports, or statement papers
• Studies that involved animal samples

Data Extraction

A separate summary table for data extraction is presented in Multimedia Appendix 1 [ 11 - 20 ], consisting of the following data for each study: reference, year, country, study design, sample size, target population, intervention and objective, and main findings. This table will be used to compare the included studies obtained through the Identify relevant studies phase conducted by human researchers versus ChatGPT. The primary outcome of interest is medication adherence among patients with ischemic stroke. Medication adherence can be measured using various methods, such as drug level measurement, pill count, electronic databases, self-report questionnaires, and electronic monitoring systems [ 21 ]. The findings from studies that aimed to use mHealth interventions for improving medication adherence but did not measure medical adherence directly will be evaluated based on how they operationalized medication adherence according to their study design.

Data Analysis

In this study, we will assess the accuracy of both human researchers and ChatGPT in identifying relevant studies from electronic databases by measuring precision. Precision is a performance metric that measures the accuracy of a model’s positive predictions. It focuses on the proportion of correctly identified positive instances (true positives) out of all the cases that the model predicted as positive (true positives+false positives) [ 22 ]. Precision is calculated using the following formula: precision=true positives/(true positives+false positives).

A high precision value close to 1 indicates that the model has a low rate of false positives. This means that when the model predicts an instance as positive, it will likely be correct. In contrast, a low precision value close to 0 indicates that the model has a high rate of false positives. This means that when the model predicts an instance as positive, it often needs to be corrected [ 22 ]. In the context of this study, precision will help evaluate the ability of both human researchers and ChatGPT to accurately identify relevant studies from electronic databases during the systematic review process. We will compare their precision scores to determine which approach yields a higher proportion of true positives and a lower rate of false positives.

In addition, as the human researcher will still need to conduct the screening, eligibility, and inclusion phases, we will also calculate the percentage of relevance using the formula ([true positives/total studies identified from the search]×100). This approach will be chosen to ensure a fair assessment, as relying solely on a formula based on true and false positives (precision) might only reflect human variability and accuracy during the screening, eligibility, and inclusion phases.

Ethical Considerations

This study considers nonhuman research according to the “Self-Assessment form whether an activity is human subject research which requires ethical approval” recommended by Mahidol University Central Institutional Review Board. Therefore, ethics approval from the research ethics committee was not required.

Search Term

Human researcher.

In the search phase, we used search terms based on MeSH using Boolean operators. The searched topic was related to using mHealth interventions for improving medication adherence in patients with ischemic stroke: (Ischemic Stroke* OR Cryptogenic Ischemic Stroke* OR Cryptogenic Stroke* OR Cryptogenic Embolism Stroke* OR Wake up Stroke* OR Acute Ischemic Stroke* OR Embolic Stroke* OR Cardioembolic Stroke* OR Cardioembolic Stroke* OR Thrombotic Stroke* OR Acute Thrombotic Stroke* OR Lacunar Stroke* OR Lacunar Syndrome* OR Lacunar Infarction* OR Lacunar Infarct*) AND (Medication Adherence OR Medication Nonadherence OR Medication Noncompliance OR Medication Persistence OR Medication Compliance OR Medication Non-Compliance) AND (Tele-Referral* OR Virtual Medicine OR Tele Intensive Care OR Tele ICU OR Mobile Health OR mHealth OR Telehealth OR eHealth OR Remote Consultation OR Teleconsultation* OR Telenursing OR Telepathology OR Teleradiology OR Telerehabilitation* OR Remote Rehabilitation* OR Virtual Rehabilitation*).

To compare with the search by human researchers, we asked ChatGPT [ 23 ] on June 23, 2023, at 1:30 PM EST to provide a search term for conducting a systematic review of the same topic as follows: “Hello ChatGPT, we are researchers and currently conduct a systematic review titled: Using m-health interventions for improving medication adherence in ischemic stroke patients. Can you provide Medical Subject Headings (MeSH) search terms and combine them using Boolean operators for a search process?” The following search terms resulted from ChatGPT, which we used in the search phase and then compared the results with those from human researchers: (Mobile Applications OR Cell Phone OR Smartphone OR Telemedicine OR Text Messaging OR Internet) AND (Medication Adherence OR Patient Compliance OR Medication Systems, Intelligent) AND (Stroke OR Ischemic Attack, Transient OR Cerebrovascular Disorders). The search term (generated by human researchers and ChatGPT) was adjusted according to the database searching requirement before searching, but the original keyword was not changed.

Search Results

We compared the ability of humans and ChatGPT to retrieve all relevant studies. A higher recall indicates a better ability to capture all the relevant literature. Figure 1 shows the flowchart diagram of the selection of included studies based on search terms generated by human researchers. An initial literature search yielded 61 articles, including 30 from PubMed and MEDLINE, 21 from Web of Science, and 10 from CINAHL Plus Full Text. No additional records were found through other sources. After deduplication (n=7 studies), the researchers screened 54 studies, of which 47 (87%) were excluded based on the inclusion and exclusion criteria following the title and abstract screening phase. This left 7 articles for full-text screening, during which 1 article was excluded as it did not include any mHealth-related intervention. Therefore, 6 articles were included in the final analysis. It should be noted that human researchers conducted the identification, screening, eligibility, and inclusion phases.

Figure 2 shows the flowchart diagram of the selection of included studies based on search terms generated by ChatGPT. An initial literature search yielded 334 articles, including 146 from PubMed and MEDLINE, 130 from Web of Science, and 58 from CINAHL Plus Full Text. No additional records were found through other sources. After deduplication (n=104 studies), the researchers screened 230 studies, of which 217 (94.3%) were excluded based on the inclusion and exclusion criteria following the title and abstract screening phase. Of the 13 articles that underwent full-text screening, 3 studies were excluded because the intervention was irrelevant (n=1, 33%), the publication was not in English (n=1, 33%), and it was a letter to the editor (n=1, 33%). Finally, 10 articles were included in the final analysis. It should be noted that ChatGPT has been used only in the identification phase. The human researcher conducted the screening, eligibility, and inclusion phases.

Description of the Included Studies

Studies included from human searches.

The analysis included 6 studies obtained from the human search ( Multimedia Appendix 1 ). Most of these studies (3/6, 50%) were published in 2020. Among the countries where the studies were conducted, 50% (3/6) were from China, whereas 17% (1/6) of the studies each originated from Belgium, the Republic of Korea, and Sweden. In terms of study design, of the 6 studies, 3 (50%) were cohort studies, 2 (33%) were randomized controlled trials (RCTs), and 1 (17%) was a non-RCT. The sample sizes varied, with 50% (3/6) of the studies having a sample size ranging from 1 to 300 and the other 50% (3/6) of the studies having a sample size of >300. Regarding the impact of mHealth interventions on medication adherence, most included studies (4/6, 67%) reported improvements in medication adherence after the intervention [ 11 - 14 ]. However, in 33% (2/6) of the included studies, it was not clearly stated whether medication adherence improved after the intervention [ 15 , 16 ].

Studies Included From ChatGPT Searches

A total of 10 studies were obtained from the ChatGPT search, of which 6 (60%) studies overlapped with the human searches ( Multimedia Appendix 1 ). Most of these studies (4/10, 40%) were published in 2020. Among the countries where the studies were conducted, 50% (5/10) of the studies were from China, whereas 10% (1/10) of the studies each originated from Belgium, the Republic of Korea, Sweden, the United States, and Pakistan. In terms of study design, most were RCTs (6/10, 60%), with 30% (3/10) of the studies being cohort studies, and 10% (1/10) of the studies being a non-RCT. The sample sizes varied, with 70% (7/10) of the studies having a sample size ranging from 1 to 300 (70%), and the other 30% (3/10) of the studies having a sample size of >300. Regarding the impact of mHealth interventions on medication adherence, most included studies (8/10, 80%) reported improvements in medication adherence after the intervention [ 11 - 14 , 17 - 20 ]. However, in 20% (2/10) of the included studies, it was not clearly stated whether medication adherence improved after the intervention [ 15 , 16 ].

In our study, we used precision as a metric to assess the accuracy of both human researchers and ChatGPT in identifying relevant studies from electronic databases during the systematic review process. By comparing their precision scores, we aimed to determine which approach yielded a higher proportion of true positives (correctly identified relevant studies) and a lower rate of false positives (incorrectly identified irrelevant studies). The precision calculation formula used was as follows: precision=true positives/(true positives+false positives).

Moreover, the human researcher conducted identification, screening, eligibility, and inclusion phases, as illustrated in Figure 1 . In contrast, ChatGPT was used only during the identification phase, and the human researcher conducted the screening, eligibility, and inclusion phases, as depicted in Figure 2 . Therefore, we also calculated the percentage of relevance using the formula ([true positives/total studies identified from the search]×100). This approach was chosen to ensure a fair assessment, as relying solely on a formula based on true and false positives might only reflect human variability and accuracy during the screening, eligibility, and inclusion phases.

For human researchers, the precision in accurately identifying relevant studies from electronic databases was calculated as 6/(6+1)=0.86, where 6 is the number of studies included in the review (true positive) and 1 (false positive) represents the study that was incorrectly identified as relevant for inclusion in the review (did not include any mHealth-related intervention; Figure 1 ). This means that out of the studies deemed relevant by human researchers, 86% (6/7) were indeed appropriate for inclusion in the review, whereas 14% (1/7) were falsely identified as relevant. The percentage of relevance for the human researcher was calculated as follows: (true positives/total studies identified from the search)×100=(6/61)×100=9.8%.

Regarding ChatGPT, its precision in accurately identifying relevant studies from electronic databases was calculated as 10/(10+3)=0.77, where 10 is the number of studies included in the review (true positive) and 3 (false positive) represents the studies that were incorrectly identified as relevant for inclusion in the review (irrelevant intervention, non-English publication, and a letter to the editor; Figure 2 ). This indicates that out of the studies identified by ChatGPT as potentially relevant, 77% (10/13) were indeed relevant and suitable for inclusion in the review, whereas 23% (3/13) were mistakenly identified as relevant. The percentage of relevance for ChatGPT was calculated as follows: (true positives/total studies identified from the search)×100=(10/334)×100=3%.

According to our findings, the precision of human researchers was higher (precision=0.86) compared to ChatGPT (precision=0.77). This is consistent with the percentage of relevance, where human researchers (9.8%) demonstrated a higher percentage of relevance than ChatGPT (3%). These results indicate that human researchers were more effective in identifying relevant studies during the systematic review process. However, it is noteworthy that despite the lower precision and percentage of relevance, ChatGPT’s initial search yielded a significantly larger number of studies (n=334) compared to human researchers (n=61), and ultimately resulted in more studies included in the final analysis (n=10 for ChatGPT vs n=6 for human researchers). This suggests that ChatGPT’s performance was more efficient in terms of study retrieval and inclusion, although there was a 60% overlap in the studies included between both approaches.

As reported in the Accuracy subsection, human researchers demonstrated higher precision in identifying relevant studies compared to ChatGPT. However, the efficiency and ability of ChatGPT to retrieve relevant studies could still hold value in the systematic review process. When considering the time required for both humans and ChatGPT to identify relevant studies, from the beginning (search term generation) to the outcome (identification of relevant studies before screening), our study found that ChatGPT substantially outperformed human researchers. ChatGPT took approximately 10 minutes, whereas human researchers spent an hour in the search term identification process using MeSH and Boolean operators before obtaining the relevant study.

In our study, we used ChatGPT to generate search terms for conducting the systematic review based on our research topic. This substantially reduced the time and effort required for initial study identification. However, it is important to note that ChatGPT’s current capabilities are limited to providing search terms, and human researchers are still required to conduct the screening of titles, abstracts, and full texts of the identified studies, using refined inclusion and exclusion criteria.

Principal Findings

According to our findings, the precision of human researchers was higher compared to ChatGPT, indicating that human researchers were more accurate in identifying relevant studies during the systematic review process. Our findings are congruent with a previous study [ 24 ], which reports inaccuracies of using ChatGPT in research that requires an in-depth understanding of the literature. Likewise, Zhao et al [ 25 ] reported that the factual accuracy of ChatGPT cannot be ensured, although it has massive resources such as Microsoft and Google. In addition, a case study of using ChatGPT to conduct literature searches indicated that ChatGPT does not provide an answer to the queries that researchers ask for [ 26 ].

Despite the lower precision of ChatGPT compared to human search, a previous study reported that ChatGPT has more accurate and comprehensive relevance judgments than all other types of NLP models or techniques [ 27 ]. Moreover, our findings show that ChatGPT’s initial search yielded a significantly larger number of studies compared to human researchers and ultimately resulted in more studies being included in the final analysis despite its lower precision. This suggests that ChatGPT’s performance was more efficient in terms of study retrieval and inclusion, although there was a 60% overlap in the studies included between both approaches. Similarly, a study of ChatGPT's insights on the future of scientific publishing reports it as a valuable resource for initiating discussions [ 28 ]. However, a previous study using ChatGPT for retrieval of clinical, radiological information reported that ChatGPT provided only two-thirds of correct responses to questions [ 29 ].

Regarding the efficiency issues of using ChatGPT in identifying relevant search terms, the results of this study suggest that ChatGPT can be a useful tool for generating search terms for systematic reviews, as it can save time and effort for human researchers and potentially retrieve more relevant studies. The previous study on the use of ChatGPT Boolean query construction and refinement for systematic review showed that ChatGPT can generate queries with high precision [ 9 ]. Therefore, ChatGPT could be a valuable tool, especially for rapid reviews where time is limited and high precision is preferred over high recall [ 9 ].

Some researchers may argue that as ChatGPT has lower precision and may generate irrelevant or inaccurate terms, human researchers still need to carefully screen the studies that ChatGPT identified and verify the quality and validity of the evidence [ 30 ]. ChatGPT should be used with caution and verification and supplemented with other methods and sources to ensure the validity and rigor of the literature search [ 9 ]. Furthermore, ChatGPT’s performance may vary depending on the research topic, data availability, and input quality. Thus, future studies are needed to evaluate ChatGPT’s generalizability and reliability across different domains and contexts.

Using ChatGPT to generate search terms for systematic reviews raises some ethical questions regarding the quality and validity of the research process. Although ChatGPT may offer some advantages in terms of efficiency and comprehensiveness, it may also introduce some biases and errors that could affect the reliability and reproducibility of the systematic reviews. For example, ChatGPT may generate search terms that are irrelevant to the research topic or too broad or narrow, resulting in either missing or including studies that do not meet the inclusion criteria [ 31 ]. Moreover, ChatGPT may generate search terms that are based on its own internal knowledge and information, which may not reflect the current state of the art or the best available evidence in the field [ 31 ]. Therefore, human researchers need to carefully evaluate and validate the search terms generated by ChatGPT and document their rationale and methods for using them. In addition, human researchers need to disclose the use of ChatGPT as a tool for generating search terms and report its strengths and limitations and any potential ethical implications in their systematic review reports [ 31 ]. This would ensure that the systematic review process is transparent, accountable, and trustworthy and that the results are credible and useful for informing decision-making.

As we embark on a comparative analysis between ChatGPT and human researchers in the pursuit of identifying relevant studies within systematic reviews, particularly focused on mHealth interventions for improving medication adherence in patients with ischemic stroke, it becomes evident that several challenges and limitations underscore the intricate nature of this exploration. These challenges offer insight into the complex interplay between cutting-edge technology and the established domain expertise of human researchers, shaping the landscape in which this study unfolds.

First and foremost, the outcomes of our study are intrinsically linked to the performance of ChatGPT, an AI-driven tool that relies on its current capabilities to generate search terms. As an entity in constant evolution, ChatGPT’s performance may undergo shifts over time, potentially influencing the accuracy and efficiency with which it generates relevant search terms. Moreover, replicating the search in subsequent studies is essential due to ChatGPT’s intrinsic unpredictability. The lack of such repetition presents challenges in determining whether the observed phenomenon reflects an inherent trait of the model or is simply a random incident.

This dynamic underscores the need to interpret our findings in the context of the tool’s state during the study period. Within the realm of medical research, the intricate and evolving nature of terminology poses a formidable challenge. Although ChatGPT exhibits language generation prowess, the intricate nuances of medical terminology—constantly adapting and expanding—could potentially pose challenges to its accurate formulation of search terms. The complexity inherent to medical concepts demands a level of contextual understanding that might be challenging for an AI system.

Another pivotal consideration revolves around the potential biases embedded within ChatGPT’s training data. Drawing insights from vast data sets, ChatGPT-generated search terms might inadvertently inherit biases present in the underlying data sources. This potential bias, albeit unintentional, introduces an element of caution when relying solely on AI-generated search terms for systematic reviews. A crucial aspect of our study’s execution pertains to refining search terms. Although ChatGPT serves as a catalyst for initial search term generation, human researchers play a pivotal role in the subsequent validation and fine-tuning of these terms. This collaborative process introduces an additional layer of complexity, as human intervention becomes essential to ensure the relevance and accuracy of the generated search terms. Moreover, the resources available and the access to ChatGPT’s capabilities could introduce variability in the study’s outcomes. Depending on factors such as subscription tiers or institutional resources, the extent of ChatGPT’s contributions and, subsequently, its comparative assessment against human researchers may exhibit nuances that warrant consideration. The study’s defined scope, focused on mHealth interventions for medication adherence improvement in patients with ischemic stroke, provides a specific lens through which insights are garnered. However, this specificity inherently limits the direct transposability of findings to other medical domains or broader systematic review topics. The nuances of different research contexts might yield distinct results. Language and geographic considerations further amplify the complexity. The study predominantly engaged with studies in English, potentially omitting valuable research published in other languages or regions. This limitation underscores the need for meticulous attention to language diversity and inclusion in systematic reviews. Human researcher variability introduces a layer of subjectivity into the study. With multiple researchers contributing to search term generation, variations in expertise and individual approaches could impact the study’s outcomes. The potential for differing interpretations and formulations of search terms necessitates careful management. Publication bias, a well-known challenge in research, extends its influence into our study’s design. Both ChatGPT and human researchers might inadvertently be swayed by publication bias, where certain types of studies are more likely to be published, potentially influencing the pool of studies considered in this review.

External factors beyond the purview of our study could exert unanticipated influence. Variables such as changes in database availability, updates to search algorithms, or shifts in the research landscape might subtly shape the study’s design and outcomes, introducing an element of unpredictability. The study’s designated time frame for data collection and inclusion introduces potential time constraints and selection bias. Studies published after the search period might be inadvertently omitted, potentially impacting the completeness of the review. Although the study provides valuable insights within its specific scope, the generalizability of findings to other systematic review topics or research questions requires cautious interpretation. The intricate interplay between technology and human expertise forms the cornerstone of our study, emphasizing the necessity for a balanced and nuanced approach when leveraging ChatGPT for systematic reviews.

The Implications of Using ChatGPT to Improve the Efficiency of Systematic Reviews

The integration of ChatGPT into the systematic review process for identifying relevant studies on mHealth interventions holds several noteworthy implications for research methodology, efficiency, and the advancement of evidence-based practices. This section explores the key implications that arise from incorporating ChatGPT as a tool to expedite and enhance the systematic review process.

One of the most immediate and impactful implications of using ChatGPT is its ability to significantly expedite the systematic review process. Traditionally, the generation of search terms for identifying relevant articles is a time-intensive task that requires meticulous crafting and refinement by human researchers. ChatGPT’s capacity to swiftly generate search terms offers an innovative solution to this bottleneck, reducing the time invested in this preliminary phase. This acceleration holds the potential to expedite the overall timeline of systematic reviews, enabling researchers to allocate more time to critical appraisal, synthesis, and analysis of selected studies.

The inherent nature of ChatGPT’s language generation capabilities allows a more diverse and expansive range of search terms. By tapping into its capacity to comprehend and generate natural language, researchers can explore a broader spectrum of keyword variations and synonyms. This expanded search scope can lead to the inclusion of studies that might have been overlooked using traditional search methods. As a result, the systematic review process becomes more comprehensive, encompassing a wider array of relevant literature.

ChatGPT’s ability to generate novel and contextually relevant search terms introduces a valuable avenue for exploratory research and hypothesis generation. Researchers can leverage ChatGPT to identify emerging trends, novel terminologies, or unconventional associations that may inform the direction of their systematic reviews. This capacity to extract insights from the vast expanse of existing literature can potentially lead to the formulation of innovative research questions and avenues for investigation.

Although ChatGPT demonstrates remarkable efficiency in generating search terms, its use necessitates a collaborative approach with human researchers. The synergy between ChatGPT’s speed and human researchers’ expertise in refining and validating search terms ensures a balanced and accurate outcome. Human researchers play a pivotal role in critically evaluating the generated search terms, refining them to align with the specific objectives of the review, and subsequently verifying the relevance of the identified articles. This collaborative interplay mitigates the risk of introducing erroneous or irrelevant studies into the review process.

In research environments with limited resources, such as time and personnel, ChatGPT offers a solution to address scalability challenges. Its ability to rapidly generate search terms can prove invaluable in scenarios where timely completion of systematic reviews is imperative. Researchers operating within resource-constrained contexts can leverage ChatGPT to conduct preliminary searches efficiently, thus optimizing the allocation of limited resources to subsequent stages of the review.

In summary, the integration of ChatGPT into the systematic review process introduces a transformative approach to enhancing efficiency and enriching the scope of literature exploration. Although its speed and breadth of search terms hold the promise of expediting the review timeline and uncovering hidden associations, the collaborative involvement of human researchers remains pivotal for ensuring accuracy, relevance, and the meticulous execution of subsequent review stages. The strategic use of ChatGPT in conjunction with traditional research practices paves the way for a new era of evidence synthesis and knowledge advancement in the field of health care interventions.

Conclusions

Our study compares the accuracy and efficacy of human researchers and ChatGPT in providing search terms to identify articles during a systematic review on mHealth interventions for improving medication adherence in patients with ischemic stroke. Although human researchers achieved greater precision, ChatGPT’s search results exhibited lower accuracy. However, ChatGPT excelled in efficacy, taking less time to generate search terms compared to human researchers, who required more time to identify appropriate search terms. In addition, ChatGPT’s search yielded a higher number of articles compared to human researchers. Following exclusions, human researchers were left with 6 articles, and ChatGPT resulted in 10 articles after screening, 6 (60%) of which overlapped with the findings of human researchers. The use of ChatGPT in creating search terms can significantly accelerate the systematic review process, although human researchers are still essential to carry out the selection process and ensure accuracy.

Acknowledgments

The authors would like to express their gratitude to Mahidol University, Thailand, for covering the article publishing charge. During the preparation of this work, the authors used ChatGPT (version 3.5, 2024; OpenAI [ 23 ]) to improve language and readability, which the study group further reviewed and revised.

Conflicts of Interest

None declared.

Summary table.

• Chassignol M, Khoroshavin A, Klimova A, Bilyatdinova A. Artificial Intelligence trends in education: a narrative overview. Procedia Comput Sci. 2018;136:16-24. [ CrossRef ]
• Bohr A, Memarzadeh K. The rise of artificial intelligence in healthcare applications. In: Bohr A, Memarzadeh K, editors. Artificial Intelligence in healthcarelsevier. Washington, DC. Academic Press; 2020;25-60.
• Hapke H, Howard C, Lane H. Natural Language Processing in Action: Understanding, Analyzing, and Generating Text With Python. New York, NY. Manning Publications; 2019.
• Lund BD, Wang T, Mannuru NR, Nie B, Shimray S, Wang Z. ChatGPT and a new academic reality: artificial intelligence-written research papers and the ethics of the large language models in scholarly publishing. J Assoc Inf Sci Technol. Mar 10, 2023;74(5):570-581. [ FREE Full text ] [ CrossRef ]
• Why tech insiders are so excited about ChatGPT, a chatbot that answers questions and writes essays. CNBC. 2022. URL: https:/​/www.​cnbc.com/​2022/​12/​13/​chatgpt-is-a-new-ai-chatbot-that-can-answer-questions-and-write-essays.​html [accessed 2024-04-12]
• Sallam M. ChatGPT utility in healthcare education, research, and practice: systematic review on the promising perspectives and valid concerns. Healthcare (Basel). Mar 19, 2023;11(6):887. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Ruksakulpiwat S, Kumar A, Ajibade A. Using ChatGPT in medical research: current status and future directions. J Multidiscip Healthc. 2023;16:1513-1520. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Dahmen J, Kayaalp ME, Ollivier M, Pareek A, Hirschmann MT, Karlsson J, et al. Artificial intelligence bot ChatGPT in medical research: the potential game changer as a double-edged sword. Knee Surg Sports Traumatol Arthrosc. Apr 21, 2023;31(4):1187-1189. [ CrossRef ] [ Medline ]
• Wang S, Scells H, Koopman B, Zuccon G. Can chatgpt write a good boolean query for systematic review literature search? arXiv preprint arXiv. arXiv. Preprint posted online February 3, 2023. 2023. [ CrossRef ]
• Moher D, Liberati A, Tetzlaff J, Altman DG, PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. Jul 21, 2009;6(7):e1000097. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Kim DY, Kwon H, Nam KW, Lee Y, Kwon HM, Chung YS. Remote management of poststroke patients with a smartphone-based management system integrated in clinical care: prospective, nonrandomized, interventional study. J Med Internet Res. Feb 27, 2020;22(2):e15377. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Li DM, Lu XY, Yang PF, Zheng J, Hu HH, Zhou Y, et al. Coordinated patient care via mobile phone-based telemedicine in secondary stroke prevention: a propensity score-matched cohort study. J Nurs Care Qual. 2023;38(3):E42-E49. [ CrossRef ] [ Medline ]
• Yan LL, Gong E, Gu W, Turner EL, Gallis JA, Zhou Y, et al. Effectiveness of a primary care-based integrated mobile health intervention for stroke management in rural China (SINEMA): a cluster-randomized controlled trial. PLoS Med. Apr 28, 2021;18(4):e1003582. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Zhang Y, Fan D, Ji H, Qiao S, Li X. Treatment adherence and secondary prevention of ischemic stroke among discharged patients using mobile phone- and WeChat-based improvement services: cohort study. JMIR Mhealth Uhealth. Apr 15, 2020;8(4):e16496. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Kamoen O, Maqueda V, Yperzeele L, Pottel H, Cras P, Vanhooren G, et al. Stroke coach: a pilot study of a personal digital coaching program for patients after ischemic stroke. Acta Neurol Belg. Feb 07, 2020;120(1):91-97. [ CrossRef ] [ Medline ]
• Ögren J, Irewall A, Söderström L, Mooe T. Long-term, telephone-based follow-up after stroke and TIA improves risk factors: 36-month results from the randomized controlled NAILED stroke risk factor trial. BMC Neurol. Sep 21, 2018;18(1):153. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Labovitz DL, Shafner L, Reyes Gil M, Virmani D, Hanina A. Using artificial intelligence to reduce the risk of nonadherence in patients on anticoagulation therapy. Stroke. May 2017;48(5):1416-1419. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Kamal AK, Shaikh Q, Pasha O, Azam I, Islam M, Memon AA, et al. A randomized controlled behavioral intervention trial to improve medication adherence in adult stroke patients with prescription tailored short messaging service (SMS)-SMS4Stroke study. BMC Neurol. Oct 21, 2015;15:212. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Wang MY, Shen MJ, Wan LH, Mo MM, Wu Z, Li LL, et al. Effects of a comprehensive reminder system based on the health belief model for patients who have had a stroke on health behaviors, blood pressure, disability, and recurrence from baseline to 6 months: a randomized controlled trial. J Cardiovasc Nurs. 2020;35(2):156-164. [ CrossRef ] [ Medline ]
• Wan L, Zhang X, You L, Ruan H, Chen S. The efficacy of a comprehensive reminder system to improve health behaviors and blood pressure control in hypertensive Ischemic stroke patients: a randomized controlled trial. J Cardiovasc Nurs. 2018;33(6):509-517. [ CrossRef ] [ Medline ]
• Anghel LA, Farcas AM, Oprean RN. An overview of the common methods used to measure treatment adherence. Med Pharm Rep. Apr 22, 2019;92(2):117-122. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Powers DM. Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation. arXiv. Preprint posted online October 11, 2020. 2020. [ FREE Full text ]
• ChatGPT (3.5). OpenAI. URL: https://chat.openai.com [accessed 2024-04-05]
• van Dis EA, Bollen J, Zuidema W, van Rooij R, Bockting CL. ChatGPT: five priorities for research. Nature. Feb 03, 2023;614(7947):224-226. [ CrossRef ] [ Medline ]
• Zhao R, Li X, Chia YK, Ding B, Bing L. Can ChatGPT-like generative models guarantee factual accuracy? On the mistakes of new generation search engines. arXiv. Preprint posted online March 3, 2023. 2023. [ FREE Full text ]
• McGee RW. Using ChatGPT to conduct literature searches: a case study. J Bus Ethics. 2023;95(2):165-178. [ CrossRef ]
• Sun W, Yan L, Ma X, Ren P, Yin D, Ren Z. Is ChatGPT good at search? Investigating large language models as re-ranking agents. arXiv. Preprint posted online April 19, 2023. 2023. [ FREE Full text ] [ CrossRef ]
• Hill-Yardin EL, Hutchinson MR, Laycock R, Spencer SJ. A Chat(GPT) about the future of scientific publishing. Brain Behav Immun. May 2023;110:152-154. [ CrossRef ] [ Medline ]
• Wagner MW, Ertl-Wagner BB. Accuracy of information and references using ChatGPT-3 for retrieval of clinical radiological information. Can Assoc Radiol J. Feb 20, 2024;75(1):69-73. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Bozkurt A, Karadeniz A, Baneres D, Guerrero-Roldán AE, Rodríguez ME. Artificial intelligence and reflections from educational landscape: a review of ai studies in half a century. Sustainability. Jan 15, 2021;13(2):800. [ CrossRef ]
• Khlaif ZN. Ethical concerns about using AI-generated text in scientific research. SSRN Journal. Preprint posted online March 20, 2023. 2023. [ FREE Full text ] [ CrossRef ]

Abbreviations

Edited by L Buis; submitted 17.08.23; peer-reviewed by S Tran, L Zhu; comments to author 10.02.24; revised version received 11.02.24; accepted 27.03.24; published 06.05.24.

©Suebsarn Ruksakulpiwat, Lalipat Phianhasin, Chitchanok Benjasirisan, Kedong Ding, Anuoluwapo Ajibade, Ayanesh Kumar, Cassie Stewart. Originally published in JMIR mHealth and uHealth (https://mhealth.jmir.org), 06.05.2024.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mHealth and uHealth, is properly cited. The complete bibliographic information, a link to the original publication on https://mhealth.jmir.org/, as well as this copyright and license information must be included.

This paper is in the following e-collection/theme issue:

Published on 8.5.2024 in Vol 26 (2024)

Emerging Trends in Information-Seeking Behavior for Alpha-Gal Syndrome: Infodemiology Study Using Time Series and Content Analysis

Authors of this article:

Original Paper

• Jamie L Romeiser, PhD, MPH   ; 
• Nicole Jusko, MPH   ; 
• Augusta A Williams, SCD, MPH  

Department of Public Health and Preventive Medicine, Upstate Medical University, Syracuse, NY, United States

Corresponding Author:

Jamie L Romeiser, PhD, MPH

Department of Public Health and Preventive Medicine

Upstate Medical University

766 Irving Ave

Syracuse, NY, 13210

United States

Phone: 1 315 464 6897

Email: [email protected]

Background: Alpha-gal syndrome is an emerging allergy characterized by an immune reaction to the carbohydrate molecule alpha-gal found in red meat. This unique food allergy is likely triggered by a tick bite. Cases of the allergy are on the rise, but prevalence estimates do not currently exist. Furthermore, varying symptoms and limited awareness of the allergy among health care providers contribute to delayed diagnosis, leading individuals to seek out their own information and potentially self-diagnose.

Objective: The study aimed to (1) describe the volume and patterns of information-seeking related to alpha-gal, (2) explore correlations between alpha-gal and lone star ticks, and (3) identify specific areas of interest that individuals are searching for in relation to alpha-gal.

Methods: Google Trends Supercharged-Glimpse, a new extension of Google Trends, provides estimates of the absolute volume of searches and related search queries. This extension was used to assess trends in searches for alpha-gal and lone star ticks ( lone star tick , alpha gal , and meat allergy , as well as food allergy for comparison) in the United States. Time series analyses were used to examine search volume trends over time, and Spearman correlation matrices and choropleth maps were used to explore geographic and temporal correlations between alpha-gal and lone star tick searches. Content analysis was performed on related search queries to identify themes and subcategories that are of interest to information seekers.

Results: Time series analysis revealed a rapidly increasing trend in search volumes for alpha-gal beginning in 2015. After adjusting for long-term trends, seasonal trends, and media coverage, from 2015 to 2022, the predicted adjusted average annual percent change in search volume for alpha-gal was 33.78%. The estimated overall change in average search volume was 627%. In comparison, the average annual percent change was 9.23% for lone star tick, 7.34% for meat allergy, and 2.45% for food allergy during this time. Geographic analysis showed strong significant correlations between alpha-gal and lone star tick searches especially in recent years (ρ=0.80; P <.001), with primary overlap and highest search rates found in the southeastern region of the United States. Content analysis identified 10 themes of primary interest: diet, diagnosis or testing, treatment, medications or contraindications of medications, symptoms, tick related, specific sources of information and locations, general education information, alternative words for alpha-gal, and unrelated or other.

Conclusions: The study provides insights into the changing information-seeking patterns for alpha-gal, indicating growing awareness and interest. Alpha-gal search volume is increasing at a rapid rate. Understanding specific questions and concerns can help health care providers and public health educators to tailor communication strategies. The Google Trends Supercharged-Glimpse tool offers enhanced features for analyzing information-seeking behavior and can be valuable for infodemiology research. Further research is needed to explore the evolving prevalence and impact of alpha-gal syndrome.

Introduction

Food allergy is a growing public health concern. The global burden of food allergy is increasing, with 220 million individuals worldwide estimated to be affected by at least 1 food allergy [ 1 - 3 ]. In the United States, it is estimated that 26 million, or about 6.2%, of US adults and children have a food allergy [ 4 ]. Food allergies can induce a hefty economic burden on individuals and families due to lost labor, productivity, out-of-pocket costs, and opportunity costs [ 5 ] and can decrease the quality of life of patients in impacted physical health and mental health [ 6 , 7 ].

One somewhat unconventional food allergy on the rise is the alpha-gal allergy, also known as alpha-gal syndrome, red meat allergy, or tick bite meat allergy [ 8 ]. Alpha-gal syndrome is a type of allergy that is characterized by an immune reaction to the carbohydrate molecule galactose-alpha-1,3-galactose (alpha-gal), which is found in most mammalian or “red meat” [ 9 ]. This immune reaction can result in a variety of symptoms including hives, swelling of the face or facial features, shortness of breath, abdominal pain, gastrointestinal issues, anaphylaxis, or even fatality [ 10 ]. Whereas conventional food allergies usually involve an immediate immune response, alpha-gal allergy is characterized by the delayed onset of symptoms (ie, 3-8 hours following exposure) [ 8 , 9 , 11 , 12 ]. This delayed response, compounded with the varying clinical presentation, can make the diagnosis of the allergy challenging.

The alpha-gal allergy stands out not only due to its delayed nature but also because of the unconventional way most individuals develop the allergy. In most cases, it is thought that transmission occurs through the bite of a tick, which injects alpha-gal into the bloodstream. This sensitizes individuals to the molecule and can lead to an immune response when consuming mammalian meat [ 13 ]. Alpha-gal cases have been reported worldwide and are associated with various tick species. In the United States, however, growing evidence suggests that alpha-gal allergy is primarily linked to lone star ticks [ 14 ]. The connection between alpha-gal allergy and lone star ticks was initially described in 2011 [ 15 ] and has since been supported by subsequent studies [ 12 , 13 , 16 - 18 ]. Recent evidence from a case-control study further strengthens this association, revealing significantly higher odds of tick exposures among individuals with alpha-gal syndrome compared to controls [ 16 ].

Lone star ticks are traditionally found in the Southeastern region of the United States. However, the geographic range of lone star ticks has expanded to the Northeast [ 19 ] and Midwest in part due to climate change and sensitivity to microclimate conditions [ 18 ]. Indeed, exposure to and cases of alpha-gal allergy are also expanding beyond the Southeastern United States [ 20 ]. Recognition and general awareness of alpha-gal allergy are growing [ 21 ], but health care providers’ knowledge of the connection between lone star ticks and alpha-gal allergy may be lagging. A recent survey conducted among clinicians in Illinois revealed a lack of awareness regarding the link between lone star tick bites and alpha-gal allergy, as well as limited familiarity with diagnostic testing for the condition [ 22 ].

Because there remains considerable variation in health care providers’ knowledge of the condition [ 23 ], patients often play a critical role in driving their own diagnoses [ 24 ]. As 1 study reported, there is often a lengthy amount of time between symptom onset and diagnosis, with patients visiting multiple health care settings and receiving numerous referrals before obtaining the correct diagnosis [ 23 ]. In general, it is likely that many patients rely on finding their own sources of information to learn about the allergy and potentially self-diagnose it before receiving an official diagnosis.

The alpha-gal syndrome is not a reportable or notifiable condition and was only granted a separate International Classification of Diseases  10th Revision ( ICD-10 ) code for diagnostic identification in 2022. Therefore, little data exist on the prevalence of the allergy [ 8 ]. In the absence of incidence or prevalence data, infoveillence and infodemiology techniques can be used to help describe the overall population interest in the topic of alpha-gal [ 25 ], as well as correlations with potentially related search terms. Many studies over the past decade have used Google Trends as a tool to explore patterns in health information–seeking behavior [ 26 , 27 ]. In fact, 1 prior study using Google Trends found a high correlation between alpha-gal and lone star tick, including a general upward trend in relative search volume (RSV) [ 21 ]. Data were examined from 2004 to 2019, but it is likely that both awareness and diagnosis of the allergy have grown in the past 3 years [ 20 ].

Further, new tools have emerged that offer enhanced features for analyzing various aspects of information-seeking behavior. One such tool is Glimpse, which is an extension app of Google Trends [ 28 ]. Google Trends has been both praised and criticized for reporting all searches as RSVs [ 29 ]. RSV is a query share of a search term within a specific geography and time range, which is then normalized to the highest point of popularity within that time period [ 26 ]. A notable drawback of this approach is that the absolute volume is not provided; therefore, there is no way to track an estimated number of queries for a particular topic [ 30 ]. Because the RSV is indexed to the highest point of popularity for a term within a time period, reproducibility of research results can be challenging [ 26 , 29 ]. To address this issue, the Supercharged-Glimpse extension offers an estimate of the absolute search volume, as well as a dashboard of additional information such as related search terms. The absolute volume numbers are overlayed on the traditional RSV index graph. This tool could be useful for understanding the specific content topics and themes that people search for health information.

Additional quantification of the changing volume of information seeking for alpha-gal can provide valuable evidence regarding shifts in awareness levels and potential changes in alpha-gal prevalence. Moreover, analyzing the evolving information-seeking patterns for both alpha-gal and lone star ticks can offer insights into the changing public interest across different geographic areas. Finally, health care providers and public health officials could benefit from understanding the topics that are most relevant to their patients and the public and adjust their communication strategies for alpha-gal accordingly. Therefore, using the Google Trends Supercharged-Glimpse extension, our objectives were to (1) describe the basic volume and patterns of information seeking related to alpha-gal; (2) explore further correlations between alpha-gal and lone star ticks; and (3) understand and identify specific questions, concerns, and areas of interest that individuals are searching for in relation to alpha-gal.

Google Trends Supercharged-Glimpse

Google Trends Supercharged-Glimpse is a new web-based tool available as an extension of Google Trends [ 28 ]. Glimpse functions in parallel with Google Trends and uses a similar random sampling approach to produce reports containing multiple components of trends in web-based information–seeking behavior. Searches are conducted on the Google Trends platform, with options to specify a particular geographic location and time period (spanning from 2004 to the present day). With the Glimpse extension, estimated search trends over time are provided as an absolute volume, rather than RSV. This allows for direct comparisons of volume from separate terms conducted in separate searches. The extension also produces a list of the highest volume of keywords and questions related to the search term, which is akin to a listing of terms that information seekers use in addition to the main keyword. Reports also contain the RSV for geographic areas from Google Trends.

Search Strategy

To begin our search, we implemented a methodological framework based upon previous strategies aimed to establish a consistent approach to conducting Google Trends research [ 31 , 32 ] and adhered to a suggested checklist for documenting and reporting our search strategy [ 26 ]. We report keywords in italics and the classification of the keyword in parentheses.

Google Trends Supercharged-Glimpse was used to determine search trends for 2 alpha-gal keywords: alpha gal (search term) and meat allergy (search term). Additional keywords related to alpha-gal were explored ( alpha-gal , alpha-gal syndrome , and alpha gal syndrome ), but these terms were visibly unstable, indicating a low search volume (with most months returning less than 1000 searches) and lower likelihood of using these terms when seeking information. Because these spelling variations produced very low volumes of searches and because the Supercharged tool does not allow modifiers (eg, “+” to add the terms together), we proceeded with the analysis without aggregating these data [ 31 ] but recognized these as potential limitations. We selected lone star tick (animal) as a keyword to explore objective 2 and food allergy (search term) as a broad comparison term. All keyword searches were compared with and without the use of quotations and produced similar results in terms of volume. Data were limited to the United States due to the context of the alpha-gal and lone star tick exploration, and the time frame ranged to include all available data (from January 1, 2004, to March 1, 2023). All keyword searches were conducted separately, without combining keywords. Similar to Google Trends, the Glimpse extension performs a sampling approach to estimate the absolute search volume. As with all sampling approaches, there is a degree of variability each time the data are queried. Further, there is a degree of caching that occurs; therefore, the same search conducted in a short time period (eg, within 10 minutes) may have identical numerical results. To produce a better estimate of the absolute volume of searches for our selected search terms, data were collected at 2 PM daily for a period of 10 days (March 2-12, 2023). Data for each term were compiled and averaged for search volume over time (absolute volume), related search queries (qualitative lists), and geographic interest (RSV). To demonstrate the overlap and correlation between the traditional RSV index values from Google Trends and the absolute volume estimates from the Supercharged-Glimpse extension, the averaged absolute volume and the averaged RSV index values for alpha gal (search term) are plotted in Figure S1 in Multimedia Appendix 1 . Absolute volume over time for all terms is presented in the Results section.

Statistical Analysis

Objective 1: trends over time.

Time series analyses were used to assess the trends in all 4 keywords over the study period. A quasi-Poisson regression was fit to account for the overdispersion of the count outcome variables. The regression used a penalized spline on year to account for long-term trends in these various allergies and related searches over time. We opted to use a penalized spline because the data appeared to be nonlinear in the raw data plots. Using penalized splines on the year allowed for the flexibility to account for the complex patterns seen in the raw data plots while not overfitting the model. The seasonality of web-based searches is likely to mirror the seasonality of cases of disease [ 31 ]. Therefore, we expected to see seasonal variation in search patterns for all 4 search terms, and indeed, this is what was revealed in graphing the monthly search volumes. There are seasonal variations in tick behaviors and tick-host encounters, which both peak during the warm season [ 33 , 34 ]. Additionally, food-related anaphylaxis has been found to increase during the warm season due to oral allergies (eg, pollen-food allergy syndrome) [ 35 ]. Therefore, a binary variable was created to indicate the warm season (May-September), which was then controlled via a linear term to account for seasonal trends. Google trends data for rare diseases can be influenced by the media [ 29 ]; therefore, the dates of national media stories on alpha-gal were identified from 2012 through 2023, and this (binary variable for the months that contained national media coverage) was controlled using a linear term. The predicted absolute search volume values are shown in the Results section. The average annual percent change (AAPC) in search volume was calculated based on this adjusted model for all 4 terms [ 36 ].

Objective 2: Alpha-Gal and Lone Star Tick

While our original intent was to describe how information-seeking behavior for both alpha gal and lone star tick changed geographically and temporally from 2004 to 2022, initial data extraction efforts revealed that the RSV geographic metrics were unstable and unreliable from 2004 to 2013. This is likely due to a lower volume of searches conducted during this time period, which would increase sampling variability. To produce more stable and reproducible results for the geographic analysis, the geographic interest index values were queried and exported in 3-year time period increments (2014-2016, 2017-2019, and 2020-2022) for the alpha gal (search term) and lone star tick ( animal ) keywords. Choropleth maps were produced. The distribution of the data was found to be nonnormally distributed (Shapiro-Wilk test P values <.05 for all variables); therefore, a Spearman correlation matrix was generated to examine geographic and temporal correlations for alpha gal and lone star tick using the RSV index values for the 3 time periods (2014-2016, 2017-2019, and 2020-2022).

Objective 3: Content Analysis

A conceptual content analysis was performed on the related search query data for alpha-gal. Lists from the 10 separate days were examined and found to be nearly identical. Lists were then combined and duplicates were removed, leaving a total of 371 related searches. All 371 related search queries contained the words “alpha gal” either before or after the additional keywords (eg, alpha gal hives ). For the qualitative content analysis, an inductive coding strategy was first implemented to identify overarching themes based on the content of the data itself. We identified 10 main themes: diet, diagnosis or testing, treatment, medications or contraindications of medications, symptoms, tick related, specific sources of information and locations, general education information, alternative words for alpha-gal, and unrelated or other. Two authors (JR and NJ) independently coded the list of 371 words based on the main concept themes. The results from the coders were compared, and discrepancies were resolved for a final theme designation. This process was repeated within each theme to further identify theme-based subcategories of interest. The total number of subthemes identified was 41. The frequency of keywords in each search theme and theme-based subcategories was compiled and described. All analyses were performed using SAS (version 9.4; SAS Institute) and R Studio (R Foundation for Statistical Computing).

Ethical Considerations

All data were publicly available and unidentifiable search engine metadata. Data are not used at the individual level and do not involve human subjects; therefore, institutional review board approval was not required for this study.

Time Series Analyses

The average absolute search volumes from 2004 to March 2023 were plotted for alpha gal , meat allergy , lone star tick , and food allergy ( Figure 1 ). The comparison of the traditional RSV index values and the absolute volume estimates demonstrated near-perfect overlap, with a Spearman correlation coefficient of ρ=0.99 ( P <.001; Figure S1 in Multimedia Appendix 1 ). In the time series analysis, the estimated absolute search volume values over time were nonlinear for all 4 search terms ( Figure 2 ). The binary indicator for the warm season was a significant predictor for all 4 search terms. While all 4 search terms demonstrated this significant seasonal trend, the magnitude of the warm season term was greatest for lone star tick and lowest for food allergy. Media coverage was only a significant predictor for alpha gal , lone star tick , and meat allergy . National media coverage of alpha-gal did not significantly impact food allergy searches. Based on the expected search volumes after adjusting for seasonality and media events in the time series analysis, the AAPC from 2004 to 2022 was 18.76%, 10.87%, 7.52%, and 1.09% for alpha gal , meat allergy , lone star tick , and food allergy , respectively. Interestingly, search trend volume began to noticeably increase starting around 2015 for alpha gal. From January 2015 to January 2022, the AAPC was 33.78%, 9.23%, 7.34%, and 2.45% for alpha gal , meat allergy , lone star tick , and food allergy , respectively. The estimated total increase during this time period was 627%, 81%, 61%, and 25% for alpha gal , meat allergy , lone star tick , and food allergy searches.

Alpha-Gal and Lone Star Tick

Choropleth maps of the RSV indices for alpha gal and lone star tick , as well as the Spearman correlation coefficient for each time period, are presented in Figure 3 . All correlations were significant at P <.001. State RSV indices for alpha gal and lone star tick were moderately correlated in 2014-2016 (ρ=0.59) but became more strongly correlated in the latter 2 time periods (ρ=0.82; ρ=0.80). These correlations can be visualized by the noticeable geographic overlap observed over time between states with a high information-seeking interest in alpha gal and lone star ticks .

Content Analysis

The content analysis revealed 10 overarching themes ( Figure 4 ). Of the 10 overarching themes, 7 were further divided into subcategories.

The most diverse search theme was diet (96/371, 25.9%), which could be further divided into 6 subthemes. The most popular subtheme was composed of general inquiries (eg, what foods to avoid with alpha gal? and what foods are safe with alpha gal? ), followed by food additives (eg, gelatin , glycerin , and magnesium stearate ), red meat (ie, specific mammal inquiries ), nonmammalian food options (eg, ostrich , eggs , and turkey ), dairy products (eg, butter , milk , and cheese ), and searches for recipes.

Symptom-related searchers accounted for 11.9% (44/371) of the total related search queries. General symptom–related questions or inquiries (eg, what are the symptoms? ) were most prominent, followed by symptom onset or triggers (eg, reaction time , onset , and exercise ). The other 5 specific subtheme symptoms that emerged were skin or rash (7/44, 15.9%), neurological (4/44, 9.1%), joint pain (3/44, 6.8%), gastrointestinal (3/44, 6.8%), and cardiovascular (2/44, 4.5%) symptoms.

Diagnosis-related searchers accounted for 10.8% (40/371) of the total related searches, including 4 subthemes of general searches for testing (eg, blood test and test results ), specific searches for IgE (eg, IgE numbers and levels ), specific laboratories that perform testing, and searches for ICD-10 codes.

General Education

General education and information seeking accounted for 10.5% (39/371) of the related searches. This theme was further broken down into causes (eg, what is the cause of alpha gal? , is alpha gal genetic? , is alpha gal contagious? ), duration (eg, is alpha gal permanent? , does alpha gal go away? ), general questions (eg, what is alpha gal? ), products, information seeking on the knockout pig, and other (eg, alpha gal and COVID-19 , alpha-gal while pregnant , and prevalence ).

Specific Sources

Specific sources of information or location accounted for 10.2% (38/371) of searches. Around 24% (9/38) of these were media-specific searches (eg, alpha-gal radiolab and nytimes ), 24% (9/38) were evidence-based sources (eg, NIH , UpToDate , CDC , and Mayo Clinic ), and 21% (8/38) were location or place specific (eg, Kentucky , Lynchburg VA , and UVA ). Other subgroups included nonevidence-based sources, specific clinician or health care provider searches, and others.

Treatment-related searches accounted for 9.4% (35/371). Most searches were general (eg. how to treat alpha gal and is it curable? ), while others were specifically related to acupuncture, antihistamines, and home remedies (eg, natural remedies and essential oils ).

Medication or contraindication-related searches accounted for 7.8% (27/371) of related searches. Roughly 25% (7/27) of these searches were vaccine related (eg, flu shot and COVID-19 vaccine ). About 25% (7/27) were inquiries about medications known to contain alpha-gal (eg, heparin), while the majority (37%, 16/27) were general inquiries on what medications were necessary to avoid (eg, alpha gal in medications , drugs to avoid , alpha gal medication list , and alpha gal and anesthesia ).

Principal Findings

To our knowledge, we believe this is one of the first studies to investigate absolute search volume trends over time using the Google Supercharged-Glimpse extension app. Our analysis revealed several important trends and patterns regarding public interest and information seeking for alpha-gal allergy.

First, over the past several years, the volume of searches for the alpha-gal allergy is significantly increasing at a rapid rate. After adjusting for seasonality and national media stories, the overall increase for alpha gal searches over time was at least 6 times that of the other search terms. Interestingly, alpha gal search term volume surpassed that of meat allergy in 2019, which likely indicates an increase in the awareness of the correct terminology for the allergy. Further, while lone star tick and meat allergy search term volumes seemed to level off from 2020 to 2022, alpha gal search term interest continued to grow. National media stories were found to have a significant impact on the search volume for alpha gal , meat allergy , and lone star tick terms, highlighting the role that media can play in engaging public interest and awareness of these topics.

Geographic popularity information-seeking for the term alpha gal did not vary greatly over time and remained concentrated in the southeast regions of the United States. While this finding was similar to a study using 2019 data [ 21 ], it was somewhat unexpected. Diagnoses of alpha-gal syndrome have occurred in other geographic regions including the Northeast and Midwest [ 20 ], and cases are increasing in those areas [ 8 ]. It is possible that this finding might be reflective of how the RSV index is generated. States with larger populations could have a greater absolute volume of interest, but this might not be reflected in the RSV index. There were no states throughout time with an RSV index of 0, which indicates that people are seeking information for the alpha-gal allergy in all 50 states. This finding is similar to laboratory-based studies that show documented cases in most states [ 20 ].

Geographic searches for the terms alpha gal and lone star tick strongly overlap. States have similarly ranked RSV indices for both alpha gal and lone star tick terms, and these have strengthened over time. Of note, geographic search interest in lone star ticks appears to be expanding. Search interest maps from 2014 to 2016 and 2017 to 2019 strongly overlap with a 2016 study that documented expansions of the lone star tick range [ 19 ]. Furthermore, search interest maps from 2020 to 2022 show a similar overlap with predicted lone star tick habitat expansion models developed in 2021 [ 37 ]. It is possible, therefore, that future interest and prevalence maps for alpha-gal may expand in similar ways. This serves as a forewarning, highlighting the urgent need to expand education efforts for both the general public and health care providers.

Finally, people are seeking a broad array of topics related to alpha-gal. The largest subgroup of content searched for in conjunction with alpha-gal was tick related. Encouragingly, national media stories and evidence-based sources comprised almost 50% of the specific sources that people were searching for. Unsurprisingly, diet was the largest theme, and interest in concealed sources of exposure and food additives remains a large concern [ 11 ]. The ubiquitous presence of animal products in food, medications, and other products can make it extremely difficult for individuals to know if what they ingest is safe [ 8 ]. Given the challenges of identifying safe foods and products, there is a clear need for improved food and product labeling. Additionally, information seeking for specific symptoms highlighted the broad array of ways that alpha-gal can manifest within an individual. Symptom variety remains one of the major reasons alpha-gal remains underdiagnosed. Health care professionals should not only be familiar with the most commonly identifiable symptoms of alpha-gal such as urticaria or anaphylaxis [ 18 ] but also be knowledgeable about symptom manifestations like joint pain [ 8 ], gastrointestinal symptoms [ 12 , 18 , 38 ], dizziness, or heart palpitations [ 10 ].

Limitations

There are several limitations to this study. First, we were only able to capture information seeking on 1 search engine platform. Second, absolute search volume estimates were not available geographically, and the RSV geographic data were unstable when examined yearly. We chose to sacrifice the granularity of a year-by-year analysis in favor of more reliable results. Third, the absolute volume was also not provided for each of the related searches. Therefore, the proportional composition of the content analysis themes represents the diversity within the theme, not necessarily the popularity of the theme. It is possible that tick-related searches encompassed the majority of the volume of the related alpha-gal searches, but we cannot identify this based on the data. Finally, at the time of the initial data analysis and submission of this study, alpha-gal syndrome was only available as a search term and not a disease. Since that time, the term has become searchable on the Google Trends platform as a designated syndrome. Absolute search volume trends over time for both alpha gal (search term) and alpha-gal syndrome (syndrome) are remarkably similar, indicating there is likely direct overlap between these 2 searches. It is unknown to what degree the addition of this condition as a designated syndrome may affect the volume reported for the alpha gal (search term) in the future.

Conclusions

Information seeking for alpha-gal syndrome is rapidly increasing. Geographic overlap with lone star tick searches might suggest future expansions in alpha-gal interest and prevalence, thereby emphasizing the urgency for increased education efforts. The diverse range of topics and symptoms searched for highlights the ongoing challenges faced by individuals affected by alpha-gal. However, the content and subthemes identified can serve as a valuable guide to facilitate public health outreach and effective patient-physician communication.

Acknowledgments

We would like to thank Adam Starke for assistance in generating the choropleth maps.

Data Availability

The data sets generated and analyzed during this study are available from the corresponding author on reasonable request.

Conflicts of Interest

None declared.

Comparison of absolute search volume and relative search volume (RSV) index over time for alpha gal (search term).

• Dunlop JH, Keet CA. Epidemiology of food allergy. Immunol Allergy Clin North Am. 2018;38(1):13-25. [ CrossRef ] [ Medline ]
• De Martinis M, Sirufo MM, Suppa M, Ginaldi L. New perspectives in food allergy. Int J Mol Sci. 2020;21(4):1474. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Fiocchi A, Risso D, DunnGalvin A, Díaz SNG, Monaci L, Fierro V, et al. Food labeling issues for severe food allergic patients. World Allergy Organ J. 2021;14(10):100598. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Ng AE, Boersma P. Diagnosed allergic conditions in adults: United States, 2021. NCHS Data Brief. 2023;(460):1-8. [ FREE Full text ] [ Medline ]
• Gupta R, Holdford D, Bilaver L, Dyer A, Holl JL, Meltzer D. The economic impact of childhood food allergy in the United States. JAMA Pediatr. 2013;167(11):1026-1031. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Blok BMJF, Dubois AEJ, Vlieg-Boerstra BJ, Elberink JNGO, Raat H, DunnGalvin A, et al. Health-related quality of life of food allergic patients: comparison with the general population and other diseases. Allergy. 2010;65(2):238-244. [ FREE Full text ] [ CrossRef ] [ Medline ]
• DunnGalvin A, Dubois AEJ, Blok BMJF, Hourihane JOB. The effects of food allergy on quality of life. Chem Immunol Allergy. 2015;101:235-252. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Commins SP. Diagnosis and management of alpha-gal syndrome: lessons from 2,500 patients. Expert Rev Clin Immunol. 2020;16(7):667-677. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Carson AS, Gardner A, Iweala OI. Where's the Beef? Understanding allergic responses to red meat in alpha-gal syndrome. J Immunol. 2022;208(2):267-277. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Alpha-gal syndrome. Centers for Disease Control and Prevention. 2023. URL: https://www.cdc.gov/ticks/alpha-gal/index.html [accessed 2023-06-07]
• Macdougall JD, Thomas KO, Iweala OI. The meat of the matter: understanding and managing alpha-gal syndrome. Immunotargets Ther. 2022;11:37-54. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Wilson JM, Schuyler AJ, Workman L, Gupta M, James HR, Posthumus J, et al. Investigation into the α-gal syndrome: characteristics of 261 children and adults reporting red meat allergy. J Allergy Clin Immunol Pract. 2019;7(7):2348-2358.e4. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Crispell G, Commins SP, Archer-Hartman SA, Choudhary S, Dharmarajan G, Azadi P, et al. Discovery of alpha-gal-containing antigens in North American tick species believed to induce red meat allergy. Front Immunol. 2019;10:1056. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Mitchell CL, Lin FC, Vaughn M, Apperson CS, Meshnick SR, Commins SP. Association between lone star tick bites and increased alpha-gal sensitization: evidence from a prospective cohort of outdoor workers. Parasit Vectors. 2020;13(1):470. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Commins SP, James HR, Kelly LA, Pochan SL, Workman LJ, Perzanowski MS, et al. The relevance of tick bites to the production of IgE antibodies to the mammalian oligosaccharide galactose-α-1,3-galactose. J Allergy Clin Immunol. 2011;127(5):1286-1293.e6. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Kersh GJ, Salzer J, Jones ES, Binder AM, Armstrong PA, Choudhary SK, et al. Tick bite as a risk factor for alpha-gal-specific immunoglobulin E antibodies and development of alpha-gal syndrome. Ann Allergy Asthma Immunol. 2023;130(4):472-478. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Sharma SR, Karim S. Tick saliva and the alpha-gal syndrome: finding a needle in a haystack. Front Cell Infect Microbiol. 2021;11:680264. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Young I, Prematunge C, Pussegoda K, Corrin T, Waddell L. Tick exposures and alpha-gal syndrome: a systematic review of the evidence. Ticks Tick Borne Dis. 2021;12(3):101674. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Molaei G, Little EAH, Williams SC, Stafford KC. Bracing for the worst - range expansion of the lone star tick in the Northeastern United States. N Engl J Med. 2019;381(23):2189-2192. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Binder AM, Commins SP, Altrich ML, Wachs T, Biggerstaff BJ, Beard CB, et al. Diagnostic testing for galactose-alpha-1,3-galactose, United States, 2010 to 2018. Ann Allergy Asthma Immunol. 2021;126(4):411-416.e1. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Iglesia EGA, Stone CA, Flaherty MG, Commins SP. Regional and temporal awareness of alpha-gal allergy: an infodemiological analysis using Google Trends. J Allergy Clin Immunol Pract. 2020;8(5):1725-1727.e1. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Carson DA, Kopsco H, Gronemeyer P, Mateus-Pinilla N, Smith GS, Sandstrom EN, et al. Knowledge, attitudes, and practices of illinois medical professionals related to ticks and tick-borne disease. One Health. 2022;15:100424. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Flaherty MG, Kaplan SJ, Jerath MR. Diagnosis of life-threatening alpha-gal food allergy appears to be patient driven. J Prim Care Community Health. 2017;8(4):345-348. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Flaherty MG, Threats M, Kaplan SJ. Patients' health information practices and perceptions of provider knowledge in the case of the newly discovered alpha-gal food allergy. J Patient Exp. 2020;7(1):132-139. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Eysenbach G. Infodemiology and infoveillance: framework for an emerging set of public health informatics methods to analyze search, communication and publication behavior on the internet. J Med Internet Res. 2009;11(1):e11. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Nuti SV, Wayda B, Ranasinghe I, Wang S, Dreyer RP, Chen SI, et al. The use of Google Trends in health care research: a systematic review. PLoS One. 2014;9(10):e109583. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Barros JM, Duggan J, Rebholz-Schuhmann D. The application of internet-based sources for public health surveillance (infoveillance): systematic review. J Med Internet Res. 2020;22(3):e13680. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Glimpse home page. Glimpse. 2023. URL: https://meetglimpse.com/extension/ [accessed 2023-03-02]
• Cervellin G, Comelli I, Lippi G. Is Google Trends a reliable tool for digital epidemiology? Insights from different clinical settings. J Epidemiol Glob Health. 2017;7(3):185-189. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Alibudbud R. Google Trends for health research: its advantages, application, methodological considerations, and limitations in psychiatric and mental health infodemiology. Front Big Data. 2023;6:1132764. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Mavragani A, Ochoa G, Tsagarakis KP. Assessing the methods, tools, and statistical approaches in Google Trends research: systematic review. J Med Internet Res. 2018;20(11):e270. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Neumann K, Mason SM, Farkas K, Santaularia NJ, Ahern J, Riddell CA. Harnessing google health trends data for epidemiologic research. Am J Epidemiol. 2023;192(3):430-437. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Jordan RA, Egizi A. The growing importance of lone star ticks in a lyme disease endemic county: passive tick surveillance in Monmouth County, NJ, 2006 - 2016. PLoS One. 2019;14(2):e0211778. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Preventing tick bites. Centers for Disease Control and Prevention. 2020. URL: https://www.cdc.gov/ticks/avoid/on_people.html#:~:text=Tick [accessed 2024-02-22]
• Lam HCY, Turner PJ, Hemming D, Jarvis DL. Seasonality of food-related anaphylaxis admissions and associations with temperature and pollen levels. J Allergy Clin Immunol Pract. 2021;9(1):518-520.e2. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Clegg LX, Hankey BF, Tiwari R, Feuer EJ, Edwards BK. Estimating average annual per cent change in trend analysis. Stat Med. 2009;28(29):3670-3682. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Alkishe A, Raghavan RK, Peterson AT. Likely geographic distributional shifts among medically important tick species and tick-associated diseases under climate change in North America: a review. Insects. 2021;12(3):225. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Richards NE, Richards RD. Alpha-gal allergy as a cause of intestinal symptoms in a gastroenterology community practice. South Med J. 2021;114(3):169-173. [ FREE Full text ] [ CrossRef ] [ Medline ]

Abbreviations

Edited by A Mavragani; submitted 14.06.23; peer-reviewed by JR Medina, A Allam, S Wei; comments to author 08.02.24; revised version received 28.02.24; accepted 23.03.24; published 08.05.24.

©Jamie L Romeiser, Nicole Jusko, Augusta A Williams. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 08.05.2024.

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