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How to Write the Methods Section of a Research Paper

Writing a research paper is both an art and a skill, and knowing how to write the methods section of a research paper is the first crucial step in mastering scientific writing. If, like the majority of early career researchers, you believe that the methods section is the simplest to write and needs little in the way of careful consideration or thought, this article will help you understand it is not 1 .

We have all probably asked our supervisors, coworkers, or search engines “ how to write a methods section of a research paper ” at some point in our scientific careers, so you are not alone if that’s how you ended up here.  Even for seasoned researchers, selecting what to include in the methods section from a wealth of experimental information can occasionally be a source of distress and perplexity.   

Additionally, journal specifications, in some cases, may make it more of a requirement rather than a choice to provide a selective yet descriptive account of the experimental procedure. Hence, knowing these nuances of how to write the methods section of a research paper is critical to its success. The methods section of the research paper is not supposed to be a detailed heavy, dull section that some researchers tend to write; rather, it should be the central component of the study that justifies the validity and reliability of the research.

Are you still unsure of how the methods section of a research paper forms the basis of every investigation? Consider the last article you read but ignore the methods section and concentrate on the other parts of the paper . Now think whether you could repeat the study and be sure of the credibility of the findings despite knowing the literature review and even having the data in front of you. You have the answer!   

Having established the importance of the methods section , the next question is how to write the methods section of a research paper that unifies the overall study. The purpose of the methods section , which was earlier called as Materials and Methods , is to describe how the authors went about answering the “research question” at hand. Here, the objective is to tell a coherent story that gives a detailed account of how the study was conducted, the rationale behind specific experimental procedures, the experimental setup, objects (variables) involved, the research protocol employed, tools utilized to measure, calculations and measurements, and the analysis of the collected data 2 .

In this article, we will take a deep dive into this topic and provide a detailed overview of how to write the methods section of a research paper . For the sake of clarity, we have separated the subject into various sections with corresponding subheadings.  

Table of Contents

What is the methods section of a research paper ?  

The methods section is a fundamental section of any paper since it typically discusses the ‘ what ’, ‘ how ’, ‘ which ’, and ‘ why ’ of the study, which is necessary to arrive at the final conclusions. In a research article, the introduction, which serves to set the foundation for comprehending the background and results is usually followed by the methods section, which precedes the result and discussion sections. The methods section must explicitly state what was done, how it was done, which equipment, tools and techniques were utilized, how were the measurements/calculations taken, and why specific research protocols, software, and analytical methods were employed.  

Why is the methods section important?  

The primary goal of the methods section is to provide pertinent details about the experimental approach so that the reader may put the results in perspective and, if necessary, replicate the findings 3 .  This section offers readers the chance to evaluate the reliability and validity of any study. In short, it also serves as the study’s blueprint, assisting researchers who might be unsure about any other portion in establishing the study’s context and validity. The methods plays a rather crucial role in determining the fate of the article; an incomplete and unreliable methods section can frequently result in early rejections and may lead to numerous rounds of modifications during the publication process. This means that the reviewers also often use methods section to assess the reliability and validity of the research protocol and the data analysis employed to address the research topic. In other words, the purpose of the methods section is to demonstrate the research acumen and subject-matter expertise of the author(s) in their field.  

Structure of methods section of a research paper  

Similar to the research paper, the methods section also follows a defined structure; this may be dictated by the guidelines of a specific journal or can be presented in a chronological or thematic manner based on the study type. When writing the methods section , authors should keep in mind that they are telling a story about how the research was conducted. They should only report relevant information to avoid confusing the reader and include details that would aid in connecting various aspects of the entire research activity together. It is generally advisable to present experiments in the order in which they were conducted. This facilitates the logical flow of the research and allows readers to follow the progression of the study design.   

It is also essential to clearly state the rationale behind each experiment and how the findings of earlier experiments informed the design or interpretation of later experiments. This allows the readers to understand the overall purpose of the study design and the significance of each experiment within that context. However, depending on the particular research question and method, it may make sense to present information in a different order; therefore, authors must select the best structure and strategy for their individual studies.   

In cases where there is a lot of information, divide the sections into subheadings to cover the pertinent details. If the journal guidelines pose restrictions on the word limit , additional important information can be supplied in the supplementary files. A simple rule of thumb for sectioning the method section is to begin by explaining the methodological approach ( what was done ), describing the data collection methods ( how it was done ), providing the analysis method ( how the data was analyzed ), and explaining the rationale for choosing the methodological strategy. This is described in detail in the upcoming sections.    

How to write the methods section of a research paper  

Contrary to widespread assumption, the methods section of a research paper should be prepared once the study is complete to prevent missing any key parameter. Hence, please make sure that all relevant experiments are done before you start writing a methods section . The next step for authors is to look up any applicable academic style manuals or journal-specific standards to ensure that the methods section is formatted correctly. The methods section of a research paper typically constitutes materials and methods; while writing this section, authors usually arrange the information under each category.

The materials category describes the samples, materials, treatments, and instruments, while experimental design, sample preparation, data collection, and data analysis are a part of the method category. According to the nature of the study, authors should include additional subsections within the methods section, such as ethical considerations like the declaration of Helsinki (for studies involving human subjects), demographic information of the participants, and any other crucial information that can affect the output of the study. Simply put, the methods section has two major components: content and format. Here is an easy checklist for you to consider if you are struggling with how to write the methods section of a research paper .   

• Explain the research design, subjects, and sample details  
• Include information on inclusion and exclusion criteria  
• Mention ethical or any other permission required for the study  
• Include information about materials, experimental setup, tools, and software  
• Add details of data collection and analysis methods  
• Incorporate how research biases were avoided or confounding variables were controlled  
• Evaluate and justify the experimental procedure selected to address the research question  
• Provide precise and clear details of each experiment  
• Flowcharts, infographics, or tables can be used to present complex information     
• Use past tense to show that the experiments have been done   
• Follow academic style guides (such as APA or MLA ) to structure the content  
• Citations should be included as per standard protocols in the field  

Now that you know how to write the methods section of a research paper , let’s address another challenge researchers face while writing the methods section —what to include in the methods section .  How much information is too much is not always obvious when it comes to trying to include data in the methods section of a paper. In the next section, we examine this issue and explore potential solutions.   

What to include in the methods section of a research paper  

The technical nature of the methods section occasionally makes it harder to present the information clearly and concisely while staying within the study context. Many young researchers tend to veer off subject significantly, and they frequently commit the sin of becoming bogged down in itty bitty details, making the text harder to read and impairing its overall flow. However, the best way to write the methods section is to start with crucial components of the experiments. If you have trouble deciding which elements are essential, think about leaving out those that would make it more challenging to comprehend the context or replicate the results. The top-down approach helps to ensure all relevant information is incorporated and vital information is not lost in technicalities. Next, remember to add details that are significant to assess the validity and reliability of the study. Here is a simple checklist for you to follow ( bonus tip: you can also make a checklist for your own study to avoid missing any critical information while writing the methods section ).  

• Structuring the methods section : Authors should diligently follow journal guidelines and adhere to the specific author instructions provided when writing the methods section . Journals typically have specific guidelines for formatting the methods section ; for example, Frontiers in Plant Sciences advises arranging the materials and methods section by subheading and citing relevant literature. There are several standardized checklists available for different study types in the biomedical field, including CONSORT (Consolidated Standards of Reporting Trials) for randomized clinical trials, PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analysis) for systematic reviews and meta-analysis, and STROBE (STrengthening the Reporting of OBservational studies in Epidemiology) for cohort, case-control, cross-sectional studies. Before starting the methods section , check the checklist available in your field that can function as a guide.     
• Organizing different sections to tell a story : Once you are sure of the format required for structuring the methods section , the next is to present the sections in a logical manner; as mentioned earlier, the sections can be organized according to the chronology or themes. In the chronological arrangement, you should discuss the methods in accordance with how the experiments were carried out. An example of the method section of a research paper of an animal study should first ideally include information about the species, weight, sex, strain, and age. Next, the number of animals, their initial conditions, and their living and housing conditions should also be mentioned. Second, how the groups are assigned and the intervention (drug treatment, stress, or other) given to each group, and finally, the details of tools and techniques used to measure, collect, and analyze the data. Experiments involving animal or human subjects should additionally state an ethics approval statement. It is best to arrange the section using the thematic approach when discussing distinct experiments not following a sequential order.  
• Define and explain the objects and procedure: Experimental procedure should clearly be stated in the methods section . Samples, necessary preparations (samples, treatment, and drug), and methods for manipulation need to be included. All variables (control, dependent, independent, and confounding) must be clearly defined, particularly if the confounding variables can affect the outcome of the study.  
• Match the order of the methods section with the order of results: Though not mandatory, organizing the manuscript in a logical and coherent manner can improve the readability and clarity of the paper. This can be done by following a consistent structure throughout the manuscript; readers can easily navigate through the different sections and understand the methods and results in relation to each other. Using experiment names as headings for both the methods and results sections can also make it simpler for readers to locate specific information and corroborate it if needed.   
• Relevant information must always be included: The methods section should have information on all experiments conducted and their details clearly mentioned. Ask the journal whether there is a way to offer more information in the supplemental files or external repositories if your target journal has strict word limitations. For example, Nature communications encourages authors to deposit their step-by-step protocols in an open-resource depository, Protocol Exchange which allows the protocols to be linked with the manuscript upon publication. Providing access to detailed protocols also helps to increase the transparency and reproducibility of the research.  
• It’s all in the details: The methods section should meticulously list all the materials, tools, instruments, and software used for different experiments. Specify the testing equipment on which data was obtained, together with its manufacturer’s information, location, city, and state or any other stimuli used to manipulate the variables. Provide specifics on the research process you employed; if it was a standard protocol, cite previous studies that also used the protocol.  Include any protocol modifications that were made, as well as any other factors that were taken into account when planning the study or gathering data. Any new or modified techniques should be explained by the authors. Typically, readers evaluate the reliability and validity of the procedures using the cited literature, and a widely accepted checklist helps to support the credibility of the methodology. Note: Authors should include a statement on sample size estimation (if applicable), which is often missed. It enables the reader to determine how many subjects will be required to detect the expected change in the outcome variables within a given confidence interval.  
• Write for the audience: While explaining the details in the methods section , authors should be mindful of their target audience, as some of the rationale or assumptions on which specific procedures are based might not always be obvious to the audience, particularly for a general audience. Therefore, when in doubt, the objective of a procedure should be specified either in relation to the research question or to the entire protocol.  
• Data interpretation and analysis : Information on data processing, statistical testing, levels of significance, and analysis tools and software should be added. Mention if the recommendations and expertise of an experienced statistician were followed. Also, evaluate and justify the preferred statistical method used in the study and its significance.  

What NOT to include in the methods section of a research paper  

To address “ how to write the methods section of a research paper ”, authors should not only pay careful attention to what to include but also what not to include in the methods section of a research paper . Here is a list of do not’s when writing the methods section :  

• Do not elaborate on specifics of standard methods/procedures: You should refrain from adding unnecessary details of experiments and practices that are well established and cited previously.  Instead, simply cite relevant literature or mention if the manufacturer’s protocol was followed.  
• Do not add unnecessary details : Do not include minute details of the experimental procedure and materials/instruments used that are not significant for the outcome of the experiment. For example, there is no need to mention the brand name of the water bath used for incubation.    
• Do not discuss the results: The methods section is not to discuss the results or refer to the tables and figures; save it for the results and discussion section. Also, focus on the methods selected to conduct the study and avoid diverting to other methods or commenting on their pros or cons.  
• Do not make the section bulky : For extensive methods and protocols, provide the essential details and share the rest of the information in the supplemental files. The writing should be clear yet concise to maintain the flow of the section.  

We hope that by this point, you understand how crucial it is to write a thoughtful and precise methods section and the ins and outs of how to write the methods section of a research paper . To restate, the entire purpose of the methods section is to enable others to reproduce the results or verify the research. We sincerely hope that this post has cleared up any confusion and given you a fresh perspective on the methods section .

As a parting gift, we’re leaving you with a handy checklist that will help you understand how to write the methods section of a research paper . Feel free to download this checklist and use or share this with those who you think may benefit from it.  

References  

• Bhattacharya, D. How to write the Methods section of a research paper. Editage Insights, 2018. https://www.editage.com/insights/how-to-write-the-methods-section-of-a-research-paper (2018).
• Kallet, R. H. How to Write the Methods Section of a Research Paper. Respiratory Care 49, 1229–1232 (2004). https://pubmed.ncbi.nlm.nih.gov/15447808/
• Grindstaff, T. L. & Saliba, S. A. AVOIDING MANUSCRIPT MISTAKES. Int J Sports Phys Ther 7, 518–524 (2012). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3474299/

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How to Write a Research Paper Introduction (with Examples)

Table of Contents

The research paper introduction section, along with the Title and Abstract, can be considered the face of any research paper. The following article is intended to guide you in organizing and writing the research paper introduction for a quality academic article or dissertation.

The research paper introduction aims to present the topic to the reader. A study will only be accepted for publishing if you can ascertain that the available literature cannot answer your research question. So it is important to ensure that you have read important studies on that particular topic, especially those within the last five to ten years, and that they are properly referenced in this section. 1

What should be included in the research paper introduction is decided by what you want to tell readers about the reason behind the research and how you plan to fill the knowledge gap. The best research paper introduction provides a systemic review of existing work and demonstrates additional work that needs to be done. It needs to be brief, captivating, and well-referenced; a well-drafted research paper introduction will help the researcher win half the battle.

The introduction for a research paper is where you set up your topic and approach for the reader. It has several key goals:

• Present your research topic
• Capture reader interest
• Summarize existing research
• Position your own approach
• Define your specific research problem and problem statement
• Highlight the novelty and contributions of the study
• Give an overview of the paper’s structure

The research paper introduction can vary in size and structure depending on whether your paper presents the results of original empirical research or is a review paper. Some research paper introduction examples are only half a page while others are a few pages long. In many cases, the introduction will be shorter than all of the other sections of your paper; its length depends on the size of your paper as a whole.

What is the introduction for a research paper?

The introduction in a research paper is placed at the beginning to guide the reader from a broad subject area to the specific topic that your research addresses. They present the following information to the reader

• Scope: The topic covered in the research paper
• Context: Background of your topic
• Importance: Why your research matters in that particular area of research and the industry problem that can be targeted

Why is the introduction important in a research paper?

The research paper introduction conveys a lot of information and can be considered an essential roadmap for the rest of your paper. A good introduction for a research paper is important for the following reasons:

• It stimulates your reader’s interest: A good introduction section can make your readers want to read your paper by capturing their interest. It informs the reader what they are going to learn and helps determine if the topic is of interest to them.
• It helps the reader understand the research background: Without a clear introduction, your readers may feel confused and even struggle when reading your paper. A good research paper introduction will prepare them for the in-depth research to come. It provides you the opportunity to engage with the readers and demonstrate your knowledge and authority on the specific topic.
• It explains why your research paper is worth reading: Your introduction can convey a lot of information to your readers. It introduces the topic, why the topic is important, and how you plan to proceed with your research.
• It helps guide the reader through the rest of the paper: The research paper introduction gives the reader a sense of the nature of the information that will support your arguments and the general organization of the paragraphs that will follow.

What are the parts of introduction in the research?

A good research paper introduction section should comprise three main elements: 2

• What is known: This sets the stage for your research. It informs the readers of what is known on the subject.
• What is lacking: This is aimed at justifying the reason for carrying out your research. This could involve investigating a new concept or method or building upon previous research.
• What you aim to do: This part briefly states the objectives of your research and its major contributions. Your detailed hypothesis will also form a part of this section.

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How to write a research paper introduction?

The first step in writing the research paper introduction is to inform the reader what your topic is and why it’s interesting or important. This is generally accomplished with a strong opening statement. The second step involves establishing the kinds of research that have been done and ending with limitations or gaps in the research that you intend to address.

Finally, the research paper introduction clarifies how your own research fits in and what problem it addresses. If your research involved testing hypotheses, these should be stated along with your research question. The hypothesis should be presented in the past tense since it will have been tested by the time you are writing the research paper introduction.

The following key points, with examples, can guide you when writing the research paper introduction section:

1. Introduce the research topic:

• Highlight the importance of the research field or topic
• Describe the background of the topic
• Present an overview of current research on the topic

Example: The inclusion of experiential and competency-based learning has benefitted electronics engineering education. Industry partnerships provide an excellent alternative for students wanting to engage in solving real-world challenges. Industry-academia participation has grown in recent years due to the need for skilled engineers with practical training and specialized expertise. However, from the educational perspective, many activities are needed to incorporate sustainable development goals into the university curricula and consolidate learning innovation in universities.

2. Determine a research niche:

• Reveal a gap in existing research or oppose an existing assumption
• Formulate the research question

Example: There have been plausible efforts to integrate educational activities in higher education electronics engineering programs. However, very few studies have considered using educational research methods for performance evaluation of competency-based higher engineering education, with a focus on technical and or transversal skills. To remedy the current need for evaluating competencies in STEM fields and providing sustainable development goals in engineering education, in this study, a comparison was drawn between study groups without and with industry partners.

3. Place your research within the research niche:

• State the purpose of your study
• Highlight the key characteristics of your study
• Describe important results
• Highlight the novelty of the study.
• Offer a brief overview of the structure of the paper.

Example: The study evaluates the main competency needed in the applied electronics course, which is a fundamental core subject for many electronics engineering undergraduate programs. We compared two groups, without and with an industrial partner, that offered real-world projects to solve during the semester. This comparison can help determine significant differences in both groups in terms of developing subject competency and achieving sustainable development goals.

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Frequently Asked Questions

What is the purpose of the introduction in research papers.

The purpose of the research paper introduction is to introduce the reader to the problem definition, justify the need for the study, and describe the main theme of the study. The aim is to gain the reader’s attention by providing them with necessary background information and establishing the main purpose and direction of the research.

How long should the research paper introduction be?

The length of the research paper introduction can vary across journals and disciplines. While there are no strict word limits for writing the research paper introduction, an ideal length would be one page, with a maximum of 400 words over 1-4 paragraphs. Generally, it is one of the shorter sections of the paper as the reader is assumed to have at least a reasonable knowledge about the topic. 2

For example, for a study evaluating the role of building design in ensuring fire safety, there is no need to discuss definitions and nature of fire in the introduction; you could start by commenting upon the existing practices for fire safety and how your study will add to the existing knowledge and practice.

What should be included in the research paper introduction?

When deciding what to include in the research paper introduction, the rest of the paper should also be considered. The aim is to introduce the reader smoothly to the topic and facilitate an easy read without much dependency on external sources. 3

Below is a list of elements you can include to prepare a research paper introduction outline and follow it when you are writing the research paper introduction.

• Topic introduction: This can include key definitions and a brief history of the topic.
• Research context and background: Offer the readers some general information and then narrow it down to specific aspects.
• Details of the research you conducted: A brief literature review can be included to support your arguments or line of thought.
• Rationale for the study: This establishes the relevance of your study and establishes its importance.
• Importance of your research: The main contributions are highlighted to help establish the novelty of your study
• Research hypothesis: Introduce your research question and propose an expected outcome. Organization of the paper: Include a short paragraph of 3-4 sentences that highlights your plan for the entire paper

Should I include citations in the introduction for a research paper?

Cite only works that are most relevant to your topic; as a general rule, you can include one to three. Note that readers want to see evidence of original thinking. So it is better to avoid using too many references as it does not leave much room for your personal standpoint to shine through.

Citations in your research paper introduction support the key points, and the number of citations depend on the subject matter and the point discussed. If the research paper introduction is too long or overflowing with citations, it is better to cite a few review articles rather than the individual articles summarized in the review.

A good point to remember when citing research papers in the introduction section is to include at least one-third of the references in the introduction.

Should I provide a literature review in the research paper introduction?

The literature review plays a significant role in the research paper introduction section. A good literature review accomplishes the following:

• Introduces the topic
• Establishes the study’s significance
• Provides an overview of the relevant literature
• Provides context for the study using literature
• Identifies knowledge gaps

However, remember to avoid making the following mistakes when writing a research paper introduction:

• Do not use studies from the literature review to aggressively support your research
• Avoid direct quoting
• Do not allow literature review to be the focus of this section. Instead, the literature review should only aid in setting a foundation for the manuscript. 

Key points to remember

Remember the following key points for writing a good research paper introduction: 4

• Avoid stuffing too much general information: Avoid including what an average reader would know and include only that information related to the problem being addressed in the research paper introduction. For example, when describing a comparative study of non-traditional methods for mechanical design optimization, information related to the traditional methods and differences between traditional and non-traditional methods would not be relevant. In this case, the introduction for the research paper should begin with the state-of-the-art non-traditional methods and methods to evaluate the efficiency of newly developed algorithms.
• Avoid packing too many references: Cite only the required works in your research paper introduction. The other works can be included in the discussion section to strengthen your findings.
• Avoid extensive criticism of previous studies: Avoid being overly critical of earlier studies while setting the rationale for your study. A better place for this would be the Discussion section, where you can highlight the advantages of your method.
• Avoid describing conclusions of the study: When writing a research paper introduction remember not to include the findings of your study. The aim is to let the readers know what question is being answered. The actual answer should only be given in the Results and Discussion section.

To summarize, the research paper introduction section should be brief yet informative. It should convince the reader the need to conduct the study and motivate him to read further. If you’re feeling stuck or unsure, choose trusted AI academic writing assistants like Paperpal to effortlessly craft your research paper introduction and other sections of your research article.

• Jawaid, S. A., & Jawaid, M. (2019). How to write introduction and discussion. Saudi Journal of Anaesthesia, 13(Suppl 1), S18.
• Dewan, P., & Gupta, P. (2016). Writing the title, abstract and introduction: Looks matter!. Indian pediatrics, 53, 235-241.
• Cetin, S., & Hackam, D. J. (2005). An approach to the writing of a scientific Manuscript1. Journal of Surgical Research, 128(2), 165-167.
• Bavdekar, S. B. (2015). Writing introduction: Laying the foundations of a research paper. Journal of the Association of Physicians of India, 63(7), 44-6.

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How to write an effective introduction for your research paper

Last updated

20 January 2024

Reviewed by

However, the introduction is a vital element of your research paper . It helps the reader decide whether your paper is worth their time. As such, it's worth taking your time to get it right.

In this article, we'll tell you everything you need to know about writing an effective introduction for your research paper.

• The importance of an introduction in research papers

The primary purpose of an introduction is to provide an overview of your paper. This lets readers gauge whether they want to continue reading or not. The introduction should provide a meaningful roadmap of your research to help them make this decision. It should let readers know whether the information they're interested in is likely to be found in the pages that follow.

Aside from providing readers with information about the content of your paper, the introduction also sets the tone. It shows readers the style of language they can expect, which can further help them to decide how far to read.

When you take into account both of these roles that an introduction plays, it becomes clear that crafting an engaging introduction is the best way to get your paper read more widely. First impressions count, and the introduction provides that impression to readers.

• The optimum length for a research paper introduction

While there's no magic formula to determine exactly how long a research paper introduction should be, there are a few guidelines. Some variables that impact the ideal introduction length include:

Field of study

Complexity of the topic

Specific requirements of the course or publication

A commonly recommended length of a research paper introduction is around 10% of the total paper’s length. So, a ten-page paper has a one-page introduction. If the topic is complex, it may require more background to craft a compelling intro. Humanities papers tend to have longer introductions than those of the hard sciences.

The best way to craft an introduction of the right length is to focus on clarity and conciseness. Tell the reader only what is necessary to set up your research. An introduction edited down with this goal in mind should end up at an acceptable length.

• Evaluating successful research paper introductions

A good way to gauge how to create a great introduction is by looking at examples from across your field. The most influential and well-regarded papers should provide some insights into what makes a good introduction.

Dissecting examples: what works and why

We can make some general assumptions by looking at common elements of a good introduction, regardless of the field of research.

A common structure is to start with a broad context, and then narrow that down to specific research questions or hypotheses. This creates a funnel that establishes the scope and relevance.

The most effective introductions are careful about the assumptions they make regarding reader knowledge. By clearly defining key terms and concepts instead of assuming the reader is familiar with them, these introductions set a more solid foundation for understanding.

To pull in the reader and make that all-important good first impression, excellent research paper introductions will often incorporate a compelling narrative or some striking fact that grabs the reader's attention.

Finally, good introductions provide clear citations from past research to back up the claims they're making. In the case of argumentative papers or essays (those that take a stance on a topic or issue), a strong thesis statement compels the reader to continue reading.

Common pitfalls to avoid in research paper introductions

You can also learn what not to do by looking at other research papers. Many authors have made mistakes you can learn from.

We've talked about the need to be clear and concise. Many introductions fail at this; they're verbose, vague, or otherwise fail to convey the research problem or hypothesis efficiently. This often comes in the form of an overemphasis on background information, which obscures the main research focus.

Ensure your introduction provides the proper emphasis and excitement around your research and its significance. Otherwise, fewer people will want to read more about it.

• Crafting a compelling introduction for a research paper

Let’s take a look at the steps required to craft an introduction that pulls readers in and compels them to learn more about your research.

Step 1: Capturing interest and setting the scene

To capture the reader's interest immediately, begin your introduction with a compelling question, a surprising fact, a provocative quote, or some other mechanism that will hook readers and pull them further into the paper.

As they continue reading, the introduction should contextualize your research within the current field, showing readers its relevance and importance. Clarify any essential terms that will help them better understand what you're saying. This keeps the fundamentals of your research accessible to all readers from all backgrounds.

Step 2: Building a solid foundation with background information

Including background information in your introduction serves two major purposes:

It helps to clarify the topic for the reader

It establishes the depth of your research

The approach you take when conveying this information depends on the type of paper.

For argumentative papers, you'll want to develop engaging background narratives. These should provide context for the argument you'll be presenting.

For empirical papers, highlighting past research is the key. Often, there will be some questions that weren't answered in those past papers. If your paper is focused on those areas, those papers make ideal candidates for you to discuss and critique in your introduction.

Step 3: Pinpointing the research challenge

To capture the attention of the reader, you need to explain what research challenges you'll be discussing.

For argumentative papers, this involves articulating why the argument you'll be making is important. What is its relevance to current discussions or problems? What is the potential impact of people accepting or rejecting your argument?

For empirical papers, explain how your research is addressing a gap in existing knowledge. What new insights or contributions will your research bring to your field?

Step 4: Clarifying your research aims and objectives

We mentioned earlier that the introduction to a research paper can serve as a roadmap for what's within. We've also frequently discussed the need for clarity. This step addresses both of these.

When writing an argumentative paper, craft a thesis statement with impact. Clearly articulate what your position is and the main points you intend to present. This will map out for the reader exactly what they'll get from reading the rest.

For empirical papers, focus on formulating precise research questions and hypotheses. Directly link them to the gaps or issues you've identified in existing research to show the reader the precise direction your research paper will take.

Step 5: Sketching the blueprint of your study

Continue building a roadmap for your readers by designing a structured outline for the paper. Guide the reader through your research journey, explaining what the different sections will contain and their relationship to one another.

This outline should flow seamlessly as you move from section to section. Creating this outline early can also help guide the creation of the paper itself, resulting in a final product that's better organized. In doing so, you'll craft a paper where each section flows intuitively from the next.

Step 6: Integrating your research question

To avoid letting your research question get lost in background information or clarifications, craft your introduction in such a way that the research question resonates throughout. The research question should clearly address a gap in existing knowledge or offer a new perspective on an existing problem.

Tell users your research question explicitly but also remember to frequently come back to it. When providing context or clarification, point out how it relates to the research question. This keeps your focus where it needs to be and prevents the topic of the paper from becoming under-emphasized.

Step 7: Establishing the scope and limitations

So far, we've talked mostly about what's in the paper and how to convey that information to readers. The opposite is also important. Information that's outside the scope of your paper should be made clear to the reader in the introduction so their expectations for what is to follow are set appropriately.

Similarly, be honest and upfront about the limitations of the study. Any constraints in methodology, data, or how far your findings can be generalized should be fully communicated in the introduction.

Step 8: Concluding the introduction with a promise

The final few lines of the introduction are your last chance to convince people to continue reading the rest of the paper. Here is where you should make it very clear what benefit they'll get from doing so. What topics will be covered? What questions will be answered? Make it clear what they will get for continuing.

By providing a quick recap of the key points contained in the introduction in its final lines and properly setting the stage for what follows in the rest of the paper, you refocus the reader's attention on the topic of your research and guide them to read more.

• Research paper introduction best practices

Following the steps above will give you a compelling introduction that hits on all the key points an introduction should have. Some more tips and tricks can make an introduction even more polished.

As you follow the steps above, keep the following tips in mind.

Set the right tone and style

Like every piece of writing, a research paper should be written for the audience. That is to say, it should match the tone and style that your academic discipline and target audience expect. This is typically a formal and academic tone, though the degree of formality varies by field.

Kno w the audience

The perfect introduction balances clarity with conciseness. The amount of clarification required for a given topic depends greatly on the target audience. Knowing who will be reading your paper will guide you in determining how much background information is required.

Adopt the CARS (create a research space) model

The CARS model is a helpful tool for structuring introductions. This structure has three parts. The beginning of the introduction establishes the general research area. Next, relevant literature is reviewed and critiqued. The final section outlines the purpose of your study as it relates to the previous parts.

Master the art of funneling

The CARS method is one example of a well-funneled introduction. These start broadly and then slowly narrow down to your specific research problem. It provides a nice narrative flow that provides the right information at the right time. If you stray from the CARS model, try to retain this same type of funneling.

Incorporate narrative element

People read research papers largely to be informed. But to inform the reader, you have to hold their attention. A narrative style, particularly in the introduction, is a great way to do that. This can be a compelling story, an intriguing question, or a description of a real-world problem.

Write the introduction last

By writing the introduction after the rest of the paper, you'll have a better idea of what your research entails and how the paper is structured. This prevents the common problem of writing something in the introduction and then forgetting to include it in the paper. It also means anything particularly exciting in the paper isn’t neglected in the intro.

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• USC Libraries
• Research Guides

Organizing Your Social Sciences Research Paper

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

The introduction leads the reader from a general subject area to a particular topic of inquiry. It establishes the scope, context, and significance of the research being conducted by summarizing current understanding and background information about the topic, stating the purpose of the work in the form of the research problem supported by a hypothesis or a set of questions, explaining briefly the methodological approach used to examine the research problem, highlighting the potential outcomes your study can reveal, and outlining the remaining structure and organization of the paper.

Key Elements of the Research Proposal. Prepared under the direction of the Superintendent and by the 2010 Curriculum Design and Writing Team. Baltimore County Public Schools.

Importance of a Good Introduction

Think of the introduction as a mental road map that must answer for the reader these four questions:

• What was I studying?
• Why was this topic important to investigate?
• What did we know about this topic before I did this study?
• How will this study advance new knowledge or new ways of understanding?

According to Reyes, there are three overarching goals of a good introduction: 1) ensure that you summarize prior studies about the topic in a manner that lays a foundation for understanding the research problem; 2) explain how your study specifically addresses gaps in the literature, insufficient consideration of the topic, or other deficiency in the literature; and, 3) note the broader theoretical, empirical, and/or policy contributions and implications of your research.

A well-written introduction is important because, quite simply, you never get a second chance to make a good first impression. The opening paragraphs of your paper will provide your readers with their initial impressions about the logic of your argument, your writing style, the overall quality of your research, and, ultimately, the validity of your findings and conclusions. A vague, disorganized, or error-filled introduction will create a negative impression, whereas, a concise, engaging, and well-written introduction will lead your readers to think highly of your analytical skills, your writing style, and your research approach. All introductions should conclude with a brief paragraph that describes the organization of the rest of the paper.

Hirano, Eliana. “Research Article Introductions in English for Specific Purposes: A Comparison between Brazilian, Portuguese, and English.” English for Specific Purposes 28 (October 2009): 240-250; Samraj, B. “Introductions in Research Articles: Variations Across Disciplines.” English for Specific Purposes 21 (2002): 1–17; Introductions. The Writing Center. University of North Carolina; “Writing Introductions.” In Good Essay Writing: A Social Sciences Guide. Peter Redman. 4th edition. (London: Sage, 2011), pp. 63-70; Reyes, Victoria. Demystifying the Journal Article. Inside Higher Education.

Structure and Writing Style

I.  Structure and Approach

The introduction is the broad beginning of the paper that answers three important questions for the reader:

• What is this?
• Why should I read it?
• What do you want me to think about / consider doing / react to?

Think of the structure of the introduction as an inverted triangle of information that lays a foundation for understanding the research problem. Organize the information so as to present the more general aspects of the topic early in the introduction, then narrow your analysis to more specific topical information that provides context, finally arriving at your research problem and the rationale for studying it [often written as a series of key questions to be addressed or framed as a hypothesis or set of assumptions to be tested] and, whenever possible, a description of the potential outcomes your study can reveal.

These are general phases associated with writing an introduction: 1.  Establish an area to research by:

• Highlighting the importance of the topic, and/or
• Making general statements about the topic, and/or
• Presenting an overview on current research on the subject.

2.  Identify a research niche by:

• Opposing an existing assumption, and/or
• Revealing a gap in existing research, and/or
• Formulating a research question or problem, and/or
• Continuing a disciplinary tradition.

3.  Place your research within the research niche by:

• Stating the intent of your study,
• Outlining the key characteristics of your study,
• Describing important results, and
• Giving a brief overview of the structure of the paper.

NOTE:   It is often useful to review the introduction late in the writing process. This is appropriate because outcomes are unknown until you've completed the study. After you complete writing the body of the paper, go back and review introductory descriptions of the structure of the paper, the method of data gathering, the reporting and analysis of results, and the conclusion. Reviewing and, if necessary, rewriting the introduction ensures that it correctly matches the overall structure of your final paper.

II.  Delimitations of the Study

Delimitations refer to those characteristics that limit the scope and define the conceptual boundaries of your research . This is determined by the conscious exclusionary and inclusionary decisions you make about how to investigate the research problem. In other words, not only should you tell the reader what it is you are studying and why, but you must also acknowledge why you rejected alternative approaches that could have been used to examine the topic.

Obviously, the first limiting step was the choice of research problem itself. However, implicit are other, related problems that could have been chosen but were rejected. These should be noted in the conclusion of your introduction. For example, a delimitating statement could read, "Although many factors can be understood to impact the likelihood young people will vote, this study will focus on socioeconomic factors related to the need to work full-time while in school." The point is not to document every possible delimiting factor, but to highlight why previously researched issues related to the topic were not addressed.

Examples of delimitating choices would be:

• The key aims and objectives of your study,
• The research questions that you address,
• The variables of interest [i.e., the various factors and features of the phenomenon being studied],
• The method(s) of investigation,
• The time period your study covers, and
• Any relevant alternative theoretical frameworks that could have been adopted.

Review each of these decisions. Not only do you clearly establish what you intend to accomplish in your research, but you should also include a declaration of what the study does not intend to cover. In the latter case, your exclusionary decisions should be based upon criteria understood as, "not interesting"; "not directly relevant"; “too problematic because..."; "not feasible," and the like. Make this reasoning explicit!

NOTE:   Delimitations refer to the initial choices made about the broader, overall design of your study and should not be confused with documenting the limitations of your study discovered after the research has been completed.

ANOTHER NOTE: Do not view delimitating statements as admitting to an inherent failing or shortcoming in your research. They are an accepted element of academic writing intended to keep the reader focused on the research problem by explicitly defining the conceptual boundaries and scope of your study. It addresses any critical questions in the reader's mind of, "Why the hell didn't the author examine this?"

III.  The Narrative Flow

Issues to keep in mind that will help the narrative flow in your introduction :

• Your introduction should clearly identify the subject area of interest . A simple strategy to follow is to use key words from your title in the first few sentences of the introduction. This will help focus the introduction on the topic at the appropriate level and ensures that you get to the subject matter quickly without losing focus, or discussing information that is too general.
• Establish context by providing a brief and balanced review of the pertinent published literature that is available on the subject. The key is to summarize for the reader what is known about the specific research problem before you did your analysis. This part of your introduction should not represent a comprehensive literature review--that comes next. It consists of a general review of the important, foundational research literature [with citations] that establishes a foundation for understanding key elements of the research problem. See the drop-down menu under this tab for " Background Information " regarding types of contexts.
• Clearly state the hypothesis that you investigated . When you are first learning to write in this format it is okay, and actually preferable, to use a past statement like, "The purpose of this study was to...." or "We investigated three possible mechanisms to explain the...."
• Why did you choose this kind of research study or design? Provide a clear statement of the rationale for your approach to the problem studied. This will usually follow your statement of purpose in the last paragraph of the introduction.

IV.  Engaging the Reader

A research problem in the social sciences can come across as dry and uninteresting to anyone unfamiliar with the topic . Therefore, one of the goals of your introduction is to make readers want to read your paper. Here are several strategies you can use to grab the reader's attention:

• Open with a compelling story . Almost all research problems in the social sciences, no matter how obscure or esoteric , are really about the lives of people. Telling a story that humanizes an issue can help illuminate the significance of the problem and help the reader empathize with those affected by the condition being studied.
• Include a strong quotation or a vivid, perhaps unexpected, anecdote . During your review of the literature, make note of any quotes or anecdotes that grab your attention because they can used in your introduction to highlight the research problem in a captivating way.
• Pose a provocative or thought-provoking question . Your research problem should be framed by a set of questions to be addressed or hypotheses to be tested. However, a provocative question can be presented in the beginning of your introduction that challenges an existing assumption or compels the reader to consider an alternative viewpoint that helps establish the significance of your study. 
• Describe a puzzling scenario or incongruity . This involves highlighting an interesting quandary concerning the research problem or describing contradictory findings from prior studies about a topic. Posing what is essentially an unresolved intellectual riddle about the problem can engage the reader's interest in the study.
• Cite a stirring example or case study that illustrates why the research problem is important . Draw upon the findings of others to demonstrate the significance of the problem and to describe how your study builds upon or offers alternatives ways of investigating this prior research.

NOTE:   It is important that you choose only one of the suggested strategies for engaging your readers. This avoids giving an impression that your paper is more flash than substance and does not distract from the substance of your study.

Freedman, Leora  and Jerry Plotnick. Introductions and Conclusions. University College Writing Centre. University of Toronto; Introduction. The Structure, Format, Content, and Style of a Journal-Style Scientific Paper. Department of Biology. Bates College; Introductions. The Writing Center. University of North Carolina; Introductions. The Writer’s Handbook. Writing Center. University of Wisconsin, Madison; Introductions, Body Paragraphs, and Conclusions for an Argument Paper. The Writing Lab and The OWL. Purdue University; “Writing Introductions.” In Good Essay Writing: A Social Sciences Guide . Peter Redman. 4th edition. (London: Sage, 2011), pp. 63-70; Resources for Writers: Introduction Strategies. Program in Writing and Humanistic Studies. Massachusetts Institute of Technology; Sharpling, Gerald. Writing an Introduction. Centre for Applied Linguistics, University of Warwick; Samraj, B. “Introductions in Research Articles: Variations Across Disciplines.” English for Specific Purposes 21 (2002): 1–17; Swales, John and Christine B. Feak. Academic Writing for Graduate Students: Essential Skills and Tasks . 2nd edition. Ann Arbor, MI: University of Michigan Press, 2004 ; Writing Your Introduction. Department of English Writing Guide. George Mason University.

Writing Tip

Avoid the "Dictionary" Introduction

Giving the dictionary definition of words related to the research problem may appear appropriate because it is important to define specific terminology that readers may be unfamiliar with. However, anyone can look a word up in the dictionary and a general dictionary is not a particularly authoritative source because it doesn't take into account the context of your topic and doesn't offer particularly detailed information. Also, placed in the context of a particular discipline, a term or concept may have a different meaning than what is found in a general dictionary. If you feel that you must seek out an authoritative definition, use a subject specific dictionary or encyclopedia [e.g., if you are a sociology student, search for dictionaries of sociology]. A good database for obtaining definitive definitions of concepts or terms is Credo Reference .

Saba, Robert. The College Research Paper. Florida International University; Introductions. The Writing Center. University of North Carolina.

Another Writing Tip

When Do I Begin?

A common question asked at the start of any paper is, "Where should I begin?" An equally important question to ask yourself is, "When do I begin?" Research problems in the social sciences rarely rest in isolation from history. Therefore, it is important to lay a foundation for understanding the historical context underpinning the research problem. However, this information should be brief and succinct and begin at a point in time that illustrates the study's overall importance. For example, a study that investigates coffee cultivation and export in West Africa as a key stimulus for local economic growth needs to describe the beginning of exporting coffee in the region and establishing why economic growth is important. You do not need to give a long historical explanation about coffee exports in Africa. If a research problem requires a substantial exploration of the historical context, do this in the literature review section. In your introduction, make note of this as part of the "roadmap" [see below] that you use to describe the organization of your paper.

Introductions. The Writing Center. University of North Carolina; “Writing Introductions.” In Good Essay Writing: A Social Sciences Guide . Peter Redman. 4th edition. (London: Sage, 2011), pp. 63-70.

Yet Another Writing Tip

Always End with a Roadmap

The final paragraph or sentences of your introduction should forecast your main arguments and conclusions and provide a brief description of the rest of the paper [the "roadmap"] that let's the reader know where you are going and what to expect. A roadmap is important because it helps the reader place the research problem within the context of their own perspectives about the topic. In addition, concluding your introduction with an explicit roadmap tells the reader that you have a clear understanding of the structural purpose of your paper. In this way, the roadmap acts as a type of promise to yourself and to your readers that you will follow a consistent and coherent approach to addressing the topic of inquiry. Refer to it often to help keep your writing focused and organized.

Cassuto, Leonard. “On the Dissertation: How to Write the Introduction.” The Chronicle of Higher Education , May 28, 2018; Radich, Michael. A Student's Guide to Writing in East Asian Studies . (Cambridge, MA: Harvard University Writing n. d.), pp. 35-37.

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• Academic Writing

How to Write a Research Paper Introduction in 4 Steps

Published on July 2, 2024 by Hannah Skaggs . Revised on September 11, 2024.

Having a hard time learning how to write a research paper introduction? Follow these four steps:

• Draw readers in.
• Zoom in on your topic and its importance.
• Explain how you’ll add new knowledge.
• Tell readers what they’ll find in your paper.

To understand why a great introduction matters, imagine a friend inviting you to lunch with another friend of hers. You show up at the restaurant and find them waiting for you at the table. You sit down, and her friend says, “So I wanna tell you about my major goal in life.”

Pretty awkward, right? You don’t even know this guy’s name yet, and he’s already diving into the heavy stuff. You’d probably prefer to have your friend introduce him, then spend some time learning about his background and personality before you get into deeper conversation.

Research paper readers need this kind of warmup, too. A good introduction, or intro, lives up to its name—it introduces readers to the topic. It prepares them to care about and understand your research, and it’s more convincing.

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Table of contents

Steps to write a research paper introduction, tips for writing a research paper introduction, tools for writing a research paper introduction, frequently asked questions about how to write a research paper.

By following the steps below, you can learn how to write an introduction for a research paper that helps readers “shake hands” with your topic. In each step, thinking about the answers to key questions can help you reach your readers.

1. Get your readers’ attention

To speak to your readers effectively, you need to know who they are. Consider who is likely to read the paper and the extent of their knowledge on the topic. Then begin your introduction with a sentence or two that will capture their interest.

For instance, you might begin with an interesting quote or an example of a situation that illustrates your argument (as we did above). Or you could start by simply stating a fact that most people aren’t aware of, which may be a better approach in scientific fields. Whichever method you choose, remember that this is academic writing —keep your phrasing formal and don’t sensationalize.

Key questions:

• Who is your audience?
• What will your paper talk about?
• What will grab your audience’s interest in the topic?

2. Explain why your topic matters

Just as you’d like to understand where a new acquaintance is coming from as you get to know them, your readers want to understand the background of your research. Once you’ve got their attention, explain why they should care.

You can give background for your research by discussing previous research on the topic. While this part should be shorter than a literature review , it can explore some of the same kinds of connections and themes. Make sure the sources you cite relate to the argument you’re making or the problem you want to solve. The information you provide here should lay a factual foundation for your research.

• Why should readers care about your topic?
• What do readers need to know to understand your research?
• What have other researchers said about the topic?
• What is the field’s overall view of the topic?

3. Lay out your argument and plan

After showing your reader the existing knowledge on the topic, you can turn to how your paper will contribute new knowledge. Tying your research to previous research is the most important aspect of this step.

Explain what knowledge is missing from the existing research and how you plan to uncover that knowledge. This is the most common place for the thesis statement, which succinctly tells readers the purpose and main idea of your paper (though it could also appear at the end of Step 4).

• How does your research relate to the studies you described in Step 2?
• What question are you aiming to answer , or what problem are you looking to solve?
• What methods will you use to answer that question or solve that problem?

4. Define your direction

Besides introducing your readers to the topic and your related findings or argument, you’re introducing them to your research process and the paper itself. This means you need to help them understand how the paper is organized and where it’s going. Add a sentence, or a few sentences, describing the sections of your paper in order or the main ideas it will cover.

While longer papers typically need to include this step, shorter ones, such as a five-paragraph essay , can usually skip it. In these cases, the thesis statement outlines the paper’s structure.

• What goal will each section of your paper accomplish?
• What should readers take away from your paper?

As you go through the steps above, keep in mind the principles of quality academic writing. Specifically, understanding how to organize and summarize will empower you to complete each step with excellence.

Keep it smooth

A good flow helps readers follow your logic. As you progress from Step 1 to Step 4, the information you give should grow more and more specific. It’s similar to how, when you meet a person, you learn basics like their name and appearance first. Then you learn about their background and more specific details, like their political views.

To make your introduction flow, start with an outline. The outline functions like a skeleton. It provides a structure for the details that make up your introduction like muscles and other tissues. It helps you make sure you don’t miss any important elements. Then, as you flesh out the details, use transition words and phrases between them to show how they relate to each other.

Keep it brief

How long should a research paper introduction be? It depends on the overall length of your paper, but the intro is typically one of the shortest sections. For example, in a short paper like an essay, you can complete each of the steps above in just a sentence or two. But in a longer one, such as a dissertation , each step may take a couple of paragraphs.

In a sense, the intro is a summary of the rest of the paper, and summarizing is all about prioritizing. As business guru Karen Martin said, “When everything is a priority, nothing is a priority.”

Martin was talking about deciding which tasks are more urgent in a business, but the same principle applies to summarizing. You must decide which ideas are the most fundamental and leave the rest out. Think about it: when you’re first meeting someone, they don’t give you an exhaustive list of all their traits. They introduce themselves with just a few of their most prominent ones.

Besides narrowing your focus, another way to keep your introduction short is to write concisely. Plain, direct language helps hold the reader’s attention, but wordy sentences will make them nod off and lose interest.

Since the introduction of a research paper is basically a summary, you may find it helpful to write it last, after you’ve finished the rest of your paper. If you write it first, there’s a good chance you’ll have to change some of its main points later. This can happen because the other sections of your paper, which your intro is based on, may evolve while you’re writing them.

Of course, you should always go back and take a second or even third look at every section of your research paper to check for errors and other necessary changes. But if you write your intro last, editing it is likely to take much less time.

Now that we’ve introduced you to the basics of writing a research paper introduction, we’d like to introduce you to QuillBot. At every step of writing your intro, it can help you upgrade your writing skills:

• Cite sources using the Citation Generator .
• Avoid plagiarism using the Plagiarism Checker .
• Reword statements from previous research (but still cite them) using the Paraphraser .
• Write spectacular and concise thesis statements (or even your whole introduction section!) using the Summarizer .

A research paper introduction starts by acquainting readers with the topic generally. Then it explores the background of the research. Finally, it explains the specific purpose of the research and its contribution.

Quotes , anecdotes, and interesting facts are all effective hooks to begin the introduction of a research paper. Which one you choose depends on the subject of your paper and your field of study.

Is this article helpful?

Hannah Skaggs

Research Blog

How to write a research paper introduction (with examples).

I hope you enjoy reading this blog post.

If you would like to learn more about research, check out this  Research Course .

Welcome to our comprehensive guide on crafting the perfect introduction for your research paper. In this blog, we’ll explore the crucial elements of a strong introduction, highlight common pitfalls to avoid, and provide practical tips to effectively set the stage for your study’s objectives and significance. 

Table of Contents

Lack of a clear thesis statement, lack of clear objectives and scope, failure to establish the research significance, insufficient background information, inadequate literature review, ignoring the research gap, overly technical language, poor organization and flow, neglecting the audience, the importance of a good introduction.

A strong introduction sets the tone for the entire paper, guiding the reader through the research journey. It provides context, establishes relevance, and ensures the reader understands the importance of the study.

Starting a research project is exciting, but getting the introduction right is key. It’s like opening the door to your study and inviting readers in. However, there are some common missteps that can trip you up along the way.

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Common mistakes to avoid.

A thesis statement is the central argument or claim that guides the entire research paper. It is a concise summary of the main point or claim of the paper and is typically found at the end of the introduction. A clear thesis statement helps to focus the research, provide direction, and inform the reader of the paper’s purpose. Expert reviewers may even skip the rest of the introduction (as they are well versed in the topic) and focus only on your thesis statement, so it’s vital to make sure it is perfect!

When a research introduction lacks a clear thesis statement, several issues can arise:

• Ambiguity : Without a clear thesis, the reader may be confused about the paper’s purpose and the main argument. Do not talk in vague terms. Whenever possible, use terminology established in recent literature. Narrow down the key aspects of the association that you are investigating (the study sample, the outcome and predictor measures) as much as possible.
• Lack of Focus : The paper can become unfocused and meander through unrelated topics, making it difficult for the reader to follow the argument. Do not try to have more than 1-2 main aims in a paper. Even if you have done supplementary analysis, it is better to say so in the discussion. As a rule of thumb, try to answer one major question only!
• Weak Argumentation : A well-defined thesis provides a strong foundation for building arguments. Without it, the arguments may appear weak and unsupported.

Let's be more practical:

1- In this paper, I will discuss climate change.

• Problem: This statement is too broad and vague. It does not provide a clear direction or specific argument.

2- This paper argues that climate change, measured by global average temperature change, is primarily driven by human activities, such as deforestation and the burning of fossil fuels, and proposes policy measures to mitigate its impact.(1)

• Strengths: – Specificity : It clearly states that the paper will focus on human activities as the main drivers of climate change. – Argument : It presents a specific claim that the paper will argue. – Direction : It hints at the structure of the paper by mentioning policy measures.

If you would like to learn more about introductions and other aspects of clinical research, check out the Medical Research Course from the Match Guy here .

Powerful Tips:

• Be Specific : Clearly define the main argument or claim. Avoid vague or broad statements.
• Be Concise : Keep the thesis statement concise, ideally one to two sentences.
• Provide Direction : Indicate the structure of the paper by hinting at the main points that will be discussed.
• Revise as Needed : Be prepared to revise the thesis statement as your research progresses and your understanding deepens.

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A clear statement of objectives and scope is crucial in a research paper introduction because it outlines what the study aims to achieve and defines the boundaries within which the research will be conducted.

Example of Lacking Clear Objectives and Scope: This paper examines the impacts of climate change on agriculture.

• Problem : This statement is too broad and vague. It does not specify what aspects of climate change or agriculture will be studied, nor does it define the geographical or temporal scope.

Example with Clear Objectives and Scope: This study aims to investigate the effects of rising temperatures and changing precipitation patterns on crop yields in the Midwest United States from 2000 to 2010. The objectives are to (1) assess the impact of temperature changes on corn and soybean yields, (2) analyze how variations in precipitation affect crop growth, and (3) identify adaptive strategies employed by farmers in the region.(2)

Powerful tips:

• Be Specific : Clearly state what the study aims to achieve and avoid vague or broad statements.
• Identify Key Areas : Outline the main areas or aspects that the research will focus on.
• Set Boundaries : Define the geographical, temporal, and conceptual boundaries of the research.
• List Objectives : Clearly articulate specific research objectives or questions that the study will address.
• Stay Realistic : Ensure that the objectives and scope are achievable within the constraints of the research project.
• Make it flow : Make sure you are not repeating the same concepts as the thesis statement, as these two sections are often presented back-to-back in the final paragraph of the introduction! Remember: the thesis statement is your hypothesis or question, and your objectives are ‘how’ you are going to test your thesis.

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This mistake can result in the research appearing trivial or irrelevant, diminishing its potential impact. When the significance of the research is not well-established, readers may struggle to understand the value of the study and why they should care about it.

Example of Failure to Establish Research Significance: This study investigates the effects of social media usage on sleep patterns among teenagers.

• Problem : The significance of studying social media’s impact on sleep patterns is not explained. The reader may wonder why this research is important or what implications it has.

Example with Established Research Significance: This study investigates the effects of social media usage on sleep patterns among teenagers. Understanding this relationship is crucial because insufficient sleep is linked to numerous health issues, including decreased academic performance, heightened stress levels, and increased risk of mental health problems. With the pervasive use of social media among adolescents, identifying how it impacts sleep can inform strategies for promoting healthier habits and improving overall well-being in this vulnerable age group.(3)

• Link to Broader Issues : Connect the research topic to broader issues or trends that highlight its relevance and importance.
• Explain Practical Implications : Discuss the potential practical applications or benefits of the research findings.
• Address Gaps in Knowledge : Identify gaps in the existing literature that the research aims to fill.
• Highlight Potential Impact : Emphasize the potential impact of the research on the field, society, or specific populations.
• Use Concrete Examples : Provide concrete examples or scenarios to illustrate the significance of the research.

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Insufficient background information in the introduction of a research paper refers to failing to provide enough context for the reader to understand the research problem and its significance. Background information sets the stage for the research by offering necessary details about the topic, relevant theories, previous studies, and key terms.

This may lead to:

• Reader Confusion : Without adequate context, readers may struggle to understand the research question, its importance, and how it fits into the broader field of study.
• Weak Justification : Insufficient background can undermine the rationale for the research, making it difficult to justify why the study is necessary or valuable.
• Misinterpretation : Lack of context can lead to misinterpretation of the research objectives, methods, and findings.

Example of Insufficient Background Information: In recent years, many researchers have studied the effects of social media on teenagers. This paper explores the relationship between social media use and anxiety among teenagers.

• Problem : This introduction lacks specific details about the previous research, the theoretical framework, and key terms. It does not provide enough context for the reader to understand why the study is important.

Example of Adequate Background Information: Social media platforms have become an integral part of teenagers’ daily lives, with studies showing that 95% of teens have access to a smartphone and 45% are online almost constantly. Previous research has linked excessive social media use to various mental health issues, including anxiety and depression. However, the mechanisms underlying this relationship remain unclear. This paper explores the impact of social media use on anxiety levels among teenagers, focusing on the roles of social comparison and cyberbullying.(4)

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• Review Relevant Literature : Summarize key studies and theories related to your topic.
• Provide Context : Explain the broader context of your research problem.
• Define Key Terms : Ensure that any specialized terms or concepts are clearly defined.
• Identify the Research Gap : Highlight what is not yet known or understood about your topic.
• Be Concise : Provide enough information to set the stage without overwhelming the reader with details.

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This mistake can occur when the literature review is too brief, lacks depth, omits key studies, or fails to critically analyze previous work. An inadequate literature review can undermine the foundation of the research by failing to provide the necessary context and justification for the study.

Inadequate Literature Review: There has been some research on the relationship between exercise and mental health. This paper will investigate this relationship further.

• Problem : This review is too general and does not provide sufficient detail about the existing research or how it informs the current study.

Example with Adequate Literature Review: Research has consistently shown that regular physical activity has positive effects on mental health. For example, a study by Gujral et al. (2019) demonstrated that aerobic exercise can significantly reduce symptoms of depression and anxiety. Similarly, Smith and Lee (2020) found that strength training also contributes to improved mood and reduced stress levels. However, much of the existing research has focused on adult populations, with relatively few studies examining these effects in adolescents. Additionally, the specific types of exercise that are most beneficial for different mental health outcomes have not been thoroughly investigated. This study aims to explore the effects of various types of exercise on the mental health of high school students, thereby addressing these gaps in the literature.(5-6)

• Be Comprehensive : Review a broad range of studies related to the research topic to provide a thorough context.
• Be Specific : Cite specific studies, including their methodologies, findings, and relevance to the current research.
• Be Critical : Analyze and evaluate the existing research, identifying strengths, weaknesses, and gaps.
• Be Structured : Organize the literature review logically, grouping studies by themes or findings to create a coherent narrative.
• Be Relevant : Focus on the most relevant studies that directly relate to the research question and objectives.

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Ignoring the research gap in a research paper introduction means failing to identify and articulate what specific aspect of the topic has not been explored or adequately addressed in existing literature. The research gap is a critical component because it justifies the necessity and originality of the study. Without highlighting this gap, the research may appear redundant or lacking in significance.

How huge is this mistake?

• Lack of Justification : The study may not appear necessary or relevant, diminishing its perceived value.
• Redundancy : The research may seem to duplicate existing studies, offering no new insights or contributions to the field. Even if you are using methodology similar to previous studies, it is important to note why you are doing so e.g., few studies have used that specific methodology, and you would like to validate it in your sample population!
• Reader Disinterest : Readers may lose interest if they do not see the unique contribution or purpose of the research.

Example of Ignoring the Research Gap: Many studies have examined the effects of exercise on mental health. This paper looks at the relationship between physical activity and depression.

• Problem : This introduction does not specify what aspect of the relationship between physical activity and depression has not been studied, failing to highlight the unique contribution of the research.

Example of Identifying the Research Gap: Numerous studies have demonstrated the general benefits of physical activity on mental health, particularly its role in alleviating symptoms of depression. However, there is limited research on how different types of exercise (e.g., aerobic vs. anaerobic) specifically impact depression levels among various age groups. This study investigates the differential effects of aerobic and anaerobic exercise on depression in young adults, aiming to fill this gap in the literature.(6)

• Conduct a Thorough Literature Review : Understand the current state of research in your field to identify what has been studied and where gaps exist.
• Be Specific : Clearly articulate what specific aspect has not been covered in existing studies.
• Link to Your Study : Explain how your research will address this gap and contribute to the field.
• Use Evidence : Support your identification of the gap with references to previous studies.
• Emphasize Significance : Highlight why filling this gap is important for advancing knowledge or practical applications.

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Overly technical language refers to the excessive use of jargon, complex terms, and highly specialized language that may be difficult for readers, especially those not familiar with the field, to understand. While technical language is sometimes necessary in academic writing, overusing it in the introduction can create several problems:

• Reader Alienation : Readers may find the text intimidating or inaccessible, leading to disengagement.
• Lack of Clarity : The main points and significance of the research can become obscured by complex terminology.
• Reduced Impact : The research may fail to communicate its importance effectively if readers struggle to understand the introduction.

Example of Overly Technical Language: The present study examines the metacognitive strategies employed by individuals in the domain of second language acquisition, specifically focusing on the interaction between declarative and procedural memory systems in the process of syntactic parsing.

• Problem : This sentence is loaded with jargon (“metacognitive strategies,” “second language acquisition,” “declarative and procedural memory systems,” “syntactic parsing”), which can be overwhelming and confusing for readers not familiar with these terms.

Example with Simplified Language: This study looks at the thinking strategies people use when learning a second language. It focuses on how different types of memory, such as the knowledge of facts and the skills for doing things, help in understanding sentence structures.(7)

• Know Your Audience : Tailor the language to the intended audience, ensuring it is accessible to both specialists and non-specialists.
• Define Term s: When technical terms are necessary, provide clear definitions or explanations.
• Use Analogies : Simplify complex concepts using analogies or examples that are easy to understand.
• Avoid Jargon : Limit the use of jargon and specialized terms, especially in the introduction.
• Seek Feedback : Ask peers or non-experts to read the introduction and provide feedback on clarity and accessibility.

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Poor organization and flow in a research paper introduction refer to a lack of logical structure and coherence that makes the introduction difficult to follow. This can occur when ideas are presented in a haphazard manner, transitions between sections are weak or non-existent, and the overall narrative is disjointed. A well-organized introduction should smoothly guide the reader from the general context to the specific objectives of the study.

Example of Poor Organization and Flow: “Climate change affects agriculture in various ways. Many studies have looked at the impact on crop yields. This paper will discuss the economic implications of these changes. Climate models predict increased variability in weather patterns, which will affect water availability. Researchers have found that higher temperatures reduce the growing season for many crops.”

• Problem : The ideas are presented in a scattered manner without clear connections. The mention of economic implications seems out of place, and there are abrupt shifts between topics.

Example with Good Organization and Flow: Climate change poses significant challenges to agriculture by altering weather patterns, impacting crop yields, and affecting water availability. Numerous studies have shown that increased temperatures can shorten the growing season for many crops, leading to reduced yields. Additionally, climate models predict increased variability in weather patterns, which complicates water management for farmers. These changes not only affect food production but also have substantial economic implications for agricultural communities. This paper will examine the economic impacts of climate-induced changes in agriculture, focusing on crop yield variability and water resource management.(1)

• Create an Outline : Before writing, outline the main points you want to cover in the introduction.
• Think in terms of an inverted triangle : Begin broadly to introduce basic concepts related to your topic. As you progress through the introduction, you can introduce more and more specific topics until you have enough information to justify your thesis statement
• Use Transitional Phrases : Employ transitional phrases and sentences to connect ideas and sections smoothly.
• Follow a Logical Sequence : Present information in a logical order, moving from general context to specific objectives.
• Maintain Focus : Stay focused on the main topic and avoid introducing unrelated ideas.
• Revise for Coherence : Review and revise the introduction to ensure that it flows well and that each part contributes to the overall narrative.

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Neglecting the audience refers to failing to consider the background, knowledge level, and interests of the intended readers when writing the introduction of a research paper. This mistake can manifest in several ways, such as using overly technical language for a general audience, providing insufficient background information for readers unfamiliar with the topic, or failing to engage the readers’ interest.

Example of Neglecting the Audience: For experts in genomic sequencing, this study explores the epigenetic modifications resulting from CRISPR-Cas9 interventions, focusing on the methylation patterns and histone modifications observed in gene-edited cells.

• Problem : This introduction assumes a high level of expertise in genomic sequencing and epigenetics, which may alienate readers without this background.

Example with Audience Consideration: CRISPR-Cas9 is a groundbreaking tool in genetic research that allows scientists to edit DNA with precision. However, altering genes can lead to unexpected changes in how genes are expressed, known as epigenetic modifications. This study investigates these changes by looking at specific markers on DNA, such as methylation patterns, and how they affect gene activity in cells that have been edited using CRISPR-Cas9. Our goal is to understand the broader implications of gene editing on cellular functions, which is crucial for advancing medical research and treatments.(8)

• Identify the Audience : Determine who the intended readers are (e.g., experts, students, general public) and tailor the language and content accordingly. Read papers from the journals you are considering for submission. Professional editors curate the language used in these papers and are a great starting point to identify the level of expertise of your audience!
• Simplify Language : Use clear and straightforward language, avoiding jargon and technical terms unless they are necessary and well-explained.
• Provide Background Information : Include sufficient background information to help readers understand the context and significance of the research.
• Engage the Reader : Start with an engaging introduction that highlights the relevance and importance of the research topic.
• Anticipate Questions : Consider what questions or concerns the audience might have and address them in the introduction

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By following these guidelines and avoiding common pitfalls, you can create an introduction that not only grabs the attention of your readers but also sets the stage for a compelling and impactful research paper.

Final Tips:

• Revise and refine your introduction multiple times to ensure clarity and coherence.
• Seek feedback from peers, mentors, or advisors to identify areas for improvement.
• Keep your audience in mind and tailor your language and content to their needs and interests.
• Stay focused on your research objectives and ensure that every part of your introduction contributes to achieving them.
• Be confident in the significance of your research and its potential impact on your field or community.

Let your introduction be more than just words on a page. It’s a doorway to understanding. To help you along, we’ve created a practical course on writing and publishing research projects. It’s 100% risk-free, with a money-back guarantee if you’re not satisfied. Try it out now by clicking here .

Wishing you success on your research journey!

Marina Ramzy Mourid, Hamza Ibad, MBBS

Dr. Ibad graduated from the Aga Khan University Medical College and completed a post-doctoral research fellowship at Johns Hopkins in the Department of Radiology (Musculoskeletal Division). Dr. Ibad’s research and clinical interests include deep-learning applications for automated image interpretation, osteoarthritis, and sarcopenia-related health outcomes.

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About thematchguy, become a researcher in the united states, interested in learning more about literature search with examples from published literature, the comprehensive research course, the systematic review course, the medical statistics course, how to find research positions in the us.

1. Abbass K, Qasim MZ, Song H, Murshed M, Mahmood H, Younis I. A review of the global climate change impacts, adaptation, and sustainable mitigation measures. Environ Sci Pollut Res. 2022;29(28):42539-42559. doi:10.1007/s11356-022-19718-6

2. Cai X, Wang D, Laurent R. Impact of climate change on crop yield: a case study of rainfed corn in central illinois. Journal of Applied Meteorology and Climatology. 2009;48(9):1868-1881. doi:10.1175/2009JAMC1880.1

3. Van Den Eijnden RJJM, Geurts SM, Ter Bogt TFM, Van Der Rijst VG, Koning IM. Social media use and adolescents’ sleep: a longitudinal study on the protective role of parental rules regarding internet use before sleep. IJERPH. 2021;18(3):1346. doi:10.3390/ijerph18031346

4. Schmitt, M. (2021). Effects of social media and technology on adolescents: What the evidence is showing and what we can do about it. Journal of Family and Consumer Sciences Education, 38(1), 51-59.

5. Gujral S, Aizenstein H, Reynolds CF, Butters MA, Erickson KI. Exercise effects on depression: Possible neural mechanisms. General Hospital Psychiatry. 2017;49:2-10. doi:10.1016/j.genhosppsych.2017.04.012

6. Smith PJ, Merwin RM. The role of exercise in management of mental health disorders: an integrative review. Annu Rev Med. 2021;72(1):45-62. doi:10.1146/annurev-med-060619-022943

7. Sun Q, Zhang LJ. Understanding learners’ metacognitive experiences in learning to write in English as a foreign language: A structural equation modeling approach. Front Psychol. 2022;13:986301. doi:10.3389/fpsyg.2022.986301

8. Kolanu ND. Crispr–cas9 gene editing: curing genetic diseases by inherited epigenetic modifications. Glob Med Genet. 2024;11(01):113-122. doi:10.1055/s-0044-1785234

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Writing a scientific paper.

• Writing a lab report

What is a "good" introduction?

Citing sources in the introduction, "introduction checklist" from: how to write a good scientific paper. chris a. mack. spie. 2018..

• LITERATURE CITED
• Bibliography of guides to scientific writing and presenting
• Peer Review
• Presentations
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This is where you describe briefly and clearly why you are writing the paper. The introduction supplies sufficient background information for the reader to understand and evaluate the experiment you did. It also supplies a rationale for the study.

• Present the problem and the proposed solution
• Presents nature and scope of the problem investigated
• Reviews the pertinent literature to orient the reader
• States the method of the experiment
• State the principle results of the experiment

It is important to cite sources in the introduction section of your paper as evidence of the claims you are making. There are ways of citing sources in the text so that the reader can find the full reference in the literature cited section at the end of the paper, yet the flow of the reading is not badly interrupted. Below are some example of how this can be done:     "Smith (1983) found that N-fixing plants could be infected by several different species of Rhizobium."     "Walnut trees are known to be allelopathic (Smith 1949,  Bond et al. 1955, Jones and Green 1963)."     "Although the presence of Rhizobium normally increases the growth of legumes (Nguyen 1987), the opposite effect has been observed (Washington 1999)." Note that articles by one or two authors are always cited in the text using their last names. However, if there are more than two authors, the last name of the 1st author is given followed by the abbreviation et al. which is Latin for "and others". 

From:  https://writingcenter.gmu.edu/guides/imrad-reports-introductions

• Indicate the field of the work, why this field is important, and what has already been done (with proper citations).
• Indicate a gap, raise a research question, or challenge prior work in this territory.
• Outline the purpose and announce the present research, clearly indicating what is novel and why it is significant.
• Avoid: repeating the abstract; providing unnecessary background information; exaggerating the importance of the work; claiming novelty without a proper literature search. 
• << Previous: ABSTRACT
• Next: METHODS >>
• Last Updated: Aug 4, 2023 9:33 AM
• URL: https://guides.lib.uci.edu/scientificwriting

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How to Write an APA Research Paper

Psychology/neuroscience 201, v iew in pdf format.

An APA-style paper includes the following sections: title page, abstract, introduction, method, results, discussion, and references. Your paper may also include one or more tables and/or figures. Different types of information about your study are addressed in each of the sections, as described below.

General formatting rules are as follows:

Do not put page breaks in between the introduction, method, results, and discussion sections.

The title page, abstract, references, table(s), and figure(s) should be on their own pages. The entire paper should be written in the past tense, in a 12-point font, double-spaced, and with one-inch margins all around.

(see sample on p. 41 of APA manual)

• Title should be between 10-12 words and should reflect content of paper (e.g., IV and DV).
• Title, your name, and Hamilton College are all double-spaced (no extra spaces)
• Create a page header using the “View header” function in MS Word. On the title page, the header should include the following: Flush left: Running head: THE RUNNING HEAD SHOULD BE IN ALL CAPITAL LETTERS. The running head is a short title that appears at the top of pages of published articles. It should not exceed 50 characters, including punctuation and spacing. (Note: on the title page, you actually write the words “Running head,” but these words do not appear on subsequent pages; just the actual running head does. If you make a section break between the title page and the rest of the paper you can make the header different for those two parts of the manuscript). Flush right, on same line: page number. Use the toolbox to insert a page number, so it will automatically number each page.

Abstract (labeled, centered, not bold)

No more than 120 words, one paragraph, block format (i.e., don’t indent), double-spaced.

• State topic, preferably in one sentence. Provide overview of method, results, and discussion.

Introduction

(Do not label as “Introduction.” Title of paper goes at the top of the page—not bold)

The introduction of an APA-style paper is the most difficult to write. A good introduction will summarize, integrate, and critically evaluate the empirical knowledge in the relevant area(s) in a way that sets the stage for your study and why you conducted it. The introduction starts out broad (but not too broad!) and gets more focused toward the end. Here are some guidelines for constructing a good introduction:

• Don’t put your readers to sleep by beginning your paper with the time-worn sentence, “Past research has shown (blah blah blah)” They’ll be snoring within a paragraph!  Try to draw your reader in by saying something interesting or thought-provoking right off the bat.  Take a look at articles you’ve read. Which ones captured your attention right away? How did the authors accomplish this task? Which ones didn’t?  Why not?  See if you can use articles you liked as a model. One way to begin (but not the only way) is to provide an example or anecdote illustrative of your topic area.
• Although you won’t go into the details of your study and hypotheses until the end of the intro, you should foreshadow your study a bit at the end of the first paragraph by stating your purpose briefly, to give your reader a schema for all the information you will present next.
• Your intro should be a logical flow of ideas that leads up to your hypothesis. Try to organize it in terms of the ideas rather than who did what when. In other words, your intro shouldn’t read like a story of “Schmirdley did such-and-such in 1991. Then Gurglehoff did something-or-other in 1993.  Then....(etc.)” First, brainstorm all of the ideas you think are necessary to include in your paper. Next, decide which ideas make sense to present first, second, third, and so forth, and think about how you want to transition between ideas. When an idea is complex, don’t be afraid to use a real-life example to clarify it for your reader. The introduction will end with a brief overview of your study and, finally, your specific hypotheses. The hypotheses should flow logically out of everything that’s been presented, so that the reader has the sense of, “Of course. This hypothesis makes complete sense, given all the other research that was presented.”
• When incorporating references into your intro, you do not necessarily need to describe every single study in complete detail, particularly if different studies use similar methodologies. Certainly you want to summarize briefly key articles, though, and point out differences in methods or findings of relevant studies when necessary. Don’t make one mistake typical of a novice APA-paper writer by stating overtly why you’re including a particular article (e.g., “This article is relevant to my study because…”). It should be obvious to the reader why you’re including a reference without your explicitly saying so.  DO NOT quote from the articles, instead paraphrase by putting the information in your own words.
• Be careful about citing your sources (see APA manual). Make sure there is a one-to-one correspondence between the articles you’ve cited in your intro and the articles listed in your reference section.
• Remember that your audience is the broader scientific community, not the other students in your class or your professor.  Therefore, you should assume they have a basic understanding of psychology, but you need to provide them with the complete information necessary for them to understand the research you are presenting.

Method (labeled, centered, bold)

The Method section of an APA-style paper is the most straightforward to write, but requires precision. Your goal is to describe the details of your study in such a way that another researcher could duplicate your methods exactly.

The Method section typically includes Participants, Materials and/or Apparatus, and Procedure sections. If the design is particularly complicated (multiple IVs in a factorial experiment, for example), you might also include a separate Design subsection or have a “Design and Procedure” section.

Note that in some studies (e.g., questionnaire studies in which there are many measures to describe but the procedure is brief), it may be more useful to present the Procedure section prior to the Materials section rather than after it.

Participants (labeled, flush left, bold)

Total number of participants (# women, # men), age range, mean and SD for age, racial/ethnic composition (if applicable), population type (e.g., college students). Remember to write numbers out when they begin a sentence.

• How were the participants recruited? (Don’t say “randomly” if it wasn’t random!) Were they compensated for their time in any way? (e.g., money, extra credit points)
• Write for a broad audience. Thus, do not write, “Students in Psych. 280...” Rather, write (for instance), “Students in a psychological statistics and research methods course at a small liberal arts college….”
• Try to avoid short, choppy sentences. Combine information into a longer sentence when possible.

Materials (labeled, flush left, bold)

Carefully describe any stimuli, questionnaires, and so forth. It is unnecessary to mention things such as the paper and pencil used to record the responses, the data recording sheet, the computer that ran the data analysis, the color of the computer, and so forth.

• If you included a questionnaire, you should describe it in detail. For instance, note how many items were on the questionnaire, what the response format was (e.g., a 5-point Likert-type scale ranging from 1 (strongly disagree) to 5 (strongly agree)), how many items were reverse-scored, whether the measure had subscales, and so forth. Provide a sample item or two for your reader.
• If you have created a new instrument, you should attach it as an Appendix.
• If you presented participants with various word lists to remember or stimuli to judge, you should describe those in detail here. Use subheadings to separate different types of stimuli if needed.  If you are only describing questionnaires, you may call this section “Measures.”

Apparatus (labeled, flush left, bold)

Include an apparatus section if you used specialized equipment for your study (e.g., the eye tracking machine) and need to describe it in detail.

Procedure (labeled, flush left, bold)

What did participants do, and in what order? When you list a control variable (e.g., “Participants all sat two feet from the experimenter.”), explain WHY you did what you did.  In other words, what nuisance variable were you controlling for? Your procedure should be as brief and concise as possible. Read through it. Did you repeat yourself anywhere? If so, how can you rearrange things to avoid redundancy? You may either write the instructions to the participants verbatim or paraphrase, whichever you deem more appropriate. Don’t forget to include brief statements about informed consent and debriefing.

Results (labeled, centered, bold)

In this section, describe how you analyzed the data and what you found. If your data analyses were complex, feel free to break this section down into labeled subsections, perhaps one section for each hypothesis.

• Include a section for descriptive statistics
• List what type of analysis or test you conducted to test each hypothesis.
• Refer to your Statistics textbook for the proper way to report results in APA style. A t-test, for example, is reported in the following format: t (18) = 3.57, p < .001, where 18 is the number of degrees of freedom (N – 2 for an independent-groups t test). For a correlation: r (32) = -.52, p < .001, where 32 is the number of degrees of freedom (N – 2 for a correlation). For a one-way ANOVA: F (2, 18) = 7.00, p < .001, where 2 represents the between and 18 represents df within Remember that if a finding has a p value greater than .05, it is “nonsignificant,” not “insignificant.” For nonsignificant findings, still provide the exact p values. For correlations, be sure to report the r 2 value as an assessment of the strength of the finding, to show what proportion of variability is shared by the two variables you’re correlating. For t- tests and ANOVAs, report eta 2 .
• Report exact p values to two or three decimal places (e.g., p = .042; see p. 114 of APA manual).  However, for p-values less than .001, simply put p < .001.
• Following the presentation of all the statistics and numbers, be sure to state the nature of your finding(s) in words and whether or not they support your hypothesis (e.g., “As predicted …”). This information can typically be presented in a sentence or two following the numbers (within the same paragraph). Also, be sure to include the relevant means and SDs.
• It may be useful to include a table or figure to represent your results visually. Be sure to refer to these in your paper (e.g., “As illustrated in Figure 1…”). Remember that you may present a set of findings either as a table or as a figure, but not as both. Make sure that your text is not redundant with your tables/figures. For instance, if you present a table of means and standard deviations, you do not need to also report these in the text. However, if you use a figure to represent your results, you may wish to report means and standard deviations in the text, as these may not always be precisely ascertained by examining the figure. Do describe the trends shown in the figure.
• Do not spend any time interpreting or explaining the results; save that for the Discussion section.

Discussion (labeled, centered, bold)

The goal of the discussion section is to interpret your findings and place them in the broader context of the literature in the area. A discussion section is like the reverse of the introduction, in that you begin with the specifics and work toward the more general (funnel out). Some points to consider:

• Begin with a brief restatement of your main findings (using words, not numbers). Did they support the hypothesis or not? If not, why not, do you think? Were there any surprising or interesting findings? How do your findings tie into the existing literature on the topic, or extend previous research? What do the results say about the broader behavior under investigation? Bring back some of the literature you discussed in the Introduction, and show how your results fit in (or don’t fit in, as the case may be). If you have surprising findings, you might discuss other theories that can help to explain the findings. Begin with the assumption that your results are valid, and explain why they might differ from others in the literature.
• What are the limitations of the study? If your findings differ from those of other researchers, or if you did not get statistically significant results, don’t spend pages and pages detailing what might have gone wrong with your study, but do provide one or two suggestions. Perhaps these could be incorporated into the future research section, below.
• What additional questions were generated from this study? What further research should be conducted on the topic? What gaps are there in the current body of research? Whenever you present an idea for a future research study, be sure to explain why you think that particular study should be conducted. What new knowledge would be gained from it?  Don’t just say, “I think it would be interesting to re-run the study on a different college campus” or “It would be better to run the study again with more participants.” Really put some thought into what extensions of the research might be interesting/informative, and why.
• What are the theoretical and/or practical implications of your findings? How do these results relate to larger issues of human thoughts, feelings, and behavior? Give your readers “the big picture.” Try to answer the question, “So what?

Final paragraph: Be sure to sum up your paper with a final concluding statement. Don’t just trail off with an idea for a future study. End on a positive note by reminding your reader why your study was important and what it added to the literature.

References (labeled, centered, not bold)

Provide an alphabetical listing of the references (alphabetize by last name of first author). Double-space all, with no extra spaces between references. The second line of each reference should be indented (this is called a hanging indent and is easily accomplished using the ruler in Microsoft Word). See the APA manual for how to format references correctly.

Examples of references to journal articles start on p. 198 of the manual, and examples of references to books and book chapters start on pp. 202. Digital object identifiers (DOIs) are now included for electronic sources (see pp. 187-192 of APA manual to learn more).

Journal article example: [Note that only the first letter of the first word of the article title is capitalized; the journal name and volume are italicized. If the journal name had multiple words, each of the major words would be capitalized.] 

Ebner-Priemer, U. W., & Trull, T. J. (2009). Ecological momentary assessment of mood disorders and mood dysregulation. Psychological Assessment, 21, 463-475. doi:10.1037/a0017075

Book chapter example: [Note that only the first letter of the first word of both the chapter title and book title are capitalized.]

Stephan, W. G. (1985). Intergroup relations. In G. Lindzey & E. Aronson (Eds.), The handbook of social psychology (3 rd ed., Vol. 2, pp. 599-658). New York: Random House.

Book example: Gray, P. (2010). Psychology (6 th ed.). New York: Worth

Table There are various formats for tables, depending upon the information you wish to include. See the APA manual. Be sure to provide a table number and table title (the latter is italicized). Tables can be single or double-spaced.

Figure If you have more than one figure, each one gets its own page. Use a sans serif font, such as Helvetica, for any text within your figure. Be sure to label your x- and y-axes clearly, and make sure you’ve noted the units of measurement of the DV. Underneath the figure provide a label and brief caption (e.g., “Figure 1. Mean evaluation of job applicant qualifications as a function of applicant attractiveness level”). The figure caption typically includes the IVs/predictor variables and the DV. Include error bars in your bar graphs, and note what the bars represent in the figure caption: Error bars represent one standard error above and below the mean.

In-Text Citations: (see pp. 174-179 of APA manual) When citing sources in your paper, you need to include the authors’ names and publication date.

You should use the following formats:

• When including the citation as part of the sentence, use AND: “According to Jones and Smith (2003), the…”
• When the citation appears in parentheses, use “&”: “Studies have shown that priming can affect actual motor behavior (Jones & Smith, 2003; Klein, Bailey, & Hammer, 1999).” The studies appearing in parentheses should be ordered alphabetically by the first author’s last name, and should be separated by semicolons.
• If you are quoting directly (which you should avoid), you also need to include the page number.
• For sources with three or more authors, once you have listed all the authors’ names, you may write “et al.” on subsequent mentions. For example: “Klein et al. (1999) found that….” For sources with two authors, both authors must be included every time the source is cited. When a source has six or more authors, the first author’s last name and “et al.” are used every time the source is cited (including the first time). 

Secondary Sources

“Secondary source” is the term used to describe material that is cited in another source. If in his article entitled “Behavioral Study of Obedience” (1963), Stanley Milgram makes reference to the ideas of Snow (presented above), Snow (1961) is the primary source, and Milgram (1963) is the secondary source.

Try to avoid using secondary sources in your papers; in other words, try to find the primary source and read it before citing it in your own work. If you must use a secondary source, however, you should cite it in the following way:

Snow (as cited in Milgram, 1963) argued that, historically, the cause of most criminal acts... The reference for the Milgram article (but not the Snow reference) should then appear in the reference list at the end of your paper.

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Home » Research Methodology – Types, Examples and writing Guide

Research Methodology – Types, Examples and writing Guide

Table of Contents

Research Methodology

Definition:

Research Methodology refers to the systematic and scientific approach used to conduct research, investigate problems, and gather data and information for a specific purpose. It involves the techniques and procedures used to identify, collect , analyze , and interpret data to answer research questions or solve research problems . Moreover, They are philosophical and theoretical frameworks that guide the research process.

Structure of Research Methodology

Research methodology formats can vary depending on the specific requirements of the research project, but the following is a basic example of a structure for a research methodology section:

I. Introduction

• Provide an overview of the research problem and the need for a research methodology section
• Outline the main research questions and objectives

II. Research Design

• Explain the research design chosen and why it is appropriate for the research question(s) and objectives
• Discuss any alternative research designs considered and why they were not chosen
• Describe the research setting and participants (if applicable)

III. Data Collection Methods

• Describe the methods used to collect data (e.g., surveys, interviews, observations)
• Explain how the data collection methods were chosen and why they are appropriate for the research question(s) and objectives
• Detail any procedures or instruments used for data collection

IV. Data Analysis Methods

• Describe the methods used to analyze the data (e.g., statistical analysis, content analysis )
• Explain how the data analysis methods were chosen and why they are appropriate for the research question(s) and objectives
• Detail any procedures or software used for data analysis

V. Ethical Considerations

• Discuss any ethical issues that may arise from the research and how they were addressed
• Explain how informed consent was obtained (if applicable)
• Detail any measures taken to ensure confidentiality and anonymity

VI. Limitations

• Identify any potential limitations of the research methodology and how they may impact the results and conclusions

VII. Conclusion

• Summarize the key aspects of the research methodology section
• Explain how the research methodology addresses the research question(s) and objectives

Research Methodology Types

Types of Research Methodology are as follows:

Quantitative Research Methodology

This is a research methodology that involves the collection and analysis of numerical data using statistical methods. This type of research is often used to study cause-and-effect relationships and to make predictions.

Qualitative Research Methodology

This is a research methodology that involves the collection and analysis of non-numerical data such as words, images, and observations. This type of research is often used to explore complex phenomena, to gain an in-depth understanding of a particular topic, and to generate hypotheses.

Mixed-Methods Research Methodology

This is a research methodology that combines elements of both quantitative and qualitative research. This approach can be particularly useful for studies that aim to explore complex phenomena and to provide a more comprehensive understanding of a particular topic.

Case Study Research Methodology

This is a research methodology that involves in-depth examination of a single case or a small number of cases. Case studies are often used in psychology, sociology, and anthropology to gain a detailed understanding of a particular individual or group.

Action Research Methodology

This is a research methodology that involves a collaborative process between researchers and practitioners to identify and solve real-world problems. Action research is often used in education, healthcare, and social work.

Experimental Research Methodology

This is a research methodology that involves the manipulation of one or more independent variables to observe their effects on a dependent variable. Experimental research is often used to study cause-and-effect relationships and to make predictions.

Survey Research Methodology

This is a research methodology that involves the collection of data from a sample of individuals using questionnaires or interviews. Survey research is often used to study attitudes, opinions, and behaviors.

Grounded Theory Research Methodology

This is a research methodology that involves the development of theories based on the data collected during the research process. Grounded theory is often used in sociology and anthropology to generate theories about social phenomena.

Research Methodology Example

An Example of Research Methodology could be the following:

Research Methodology for Investigating the Effectiveness of Cognitive Behavioral Therapy in Reducing Symptoms of Depression in Adults

Introduction:

The aim of this research is to investigate the effectiveness of cognitive-behavioral therapy (CBT) in reducing symptoms of depression in adults. To achieve this objective, a randomized controlled trial (RCT) will be conducted using a mixed-methods approach.

Research Design:

The study will follow a pre-test and post-test design with two groups: an experimental group receiving CBT and a control group receiving no intervention. The study will also include a qualitative component, in which semi-structured interviews will be conducted with a subset of participants to explore their experiences of receiving CBT.

Participants:

Participants will be recruited from community mental health clinics in the local area. The sample will consist of 100 adults aged 18-65 years old who meet the diagnostic criteria for major depressive disorder. Participants will be randomly assigned to either the experimental group or the control group.

Intervention :

The experimental group will receive 12 weekly sessions of CBT, each lasting 60 minutes. The intervention will be delivered by licensed mental health professionals who have been trained in CBT. The control group will receive no intervention during the study period.

Data Collection:

Quantitative data will be collected through the use of standardized measures such as the Beck Depression Inventory-II (BDI-II) and the Generalized Anxiety Disorder-7 (GAD-7). Data will be collected at baseline, immediately after the intervention, and at a 3-month follow-up. Qualitative data will be collected through semi-structured interviews with a subset of participants from the experimental group. The interviews will be conducted at the end of the intervention period, and will explore participants’ experiences of receiving CBT.

Data Analysis:

Quantitative data will be analyzed using descriptive statistics, t-tests, and mixed-model analyses of variance (ANOVA) to assess the effectiveness of the intervention. Qualitative data will be analyzed using thematic analysis to identify common themes and patterns in participants’ experiences of receiving CBT.

Ethical Considerations:

This study will comply with ethical guidelines for research involving human subjects. Participants will provide informed consent before participating in the study, and their privacy and confidentiality will be protected throughout the study. Any adverse events or reactions will be reported and managed appropriately.

Data Management:

All data collected will be kept confidential and stored securely using password-protected databases. Identifying information will be removed from qualitative data transcripts to ensure participants’ anonymity.

Limitations:

One potential limitation of this study is that it only focuses on one type of psychotherapy, CBT, and may not generalize to other types of therapy or interventions. Another limitation is that the study will only include participants from community mental health clinics, which may not be representative of the general population.

Conclusion:

This research aims to investigate the effectiveness of CBT in reducing symptoms of depression in adults. By using a randomized controlled trial and a mixed-methods approach, the study will provide valuable insights into the mechanisms underlying the relationship between CBT and depression. The results of this study will have important implications for the development of effective treatments for depression in clinical settings.

How to Write Research Methodology

Writing a research methodology involves explaining the methods and techniques you used to conduct research, collect data, and analyze results. It’s an essential section of any research paper or thesis, as it helps readers understand the validity and reliability of your findings. Here are the steps to write a research methodology:

• Start by explaining your research question: Begin the methodology section by restating your research question and explaining why it’s important. This helps readers understand the purpose of your research and the rationale behind your methods.
• Describe your research design: Explain the overall approach you used to conduct research. This could be a qualitative or quantitative research design, experimental or non-experimental, case study or survey, etc. Discuss the advantages and limitations of the chosen design.
• Discuss your sample: Describe the participants or subjects you included in your study. Include details such as their demographics, sampling method, sample size, and any exclusion criteria used.
• Describe your data collection methods : Explain how you collected data from your participants. This could include surveys, interviews, observations, questionnaires, or experiments. Include details on how you obtained informed consent, how you administered the tools, and how you minimized the risk of bias.
• Explain your data analysis techniques: Describe the methods you used to analyze the data you collected. This could include statistical analysis, content analysis, thematic analysis, or discourse analysis. Explain how you dealt with missing data, outliers, and any other issues that arose during the analysis.
• Discuss the validity and reliability of your research : Explain how you ensured the validity and reliability of your study. This could include measures such as triangulation, member checking, peer review, or inter-coder reliability.
• Acknowledge any limitations of your research: Discuss any limitations of your study, including any potential threats to validity or generalizability. This helps readers understand the scope of your findings and how they might apply to other contexts.
• Provide a summary: End the methodology section by summarizing the methods and techniques you used to conduct your research. This provides a clear overview of your research methodology and helps readers understand the process you followed to arrive at your findings.

When to Write Research Methodology

Research methodology is typically written after the research proposal has been approved and before the actual research is conducted. It should be written prior to data collection and analysis, as it provides a clear roadmap for the research project.

The research methodology is an important section of any research paper or thesis, as it describes the methods and procedures that will be used to conduct the research. It should include details about the research design, data collection methods, data analysis techniques, and any ethical considerations.

The methodology should be written in a clear and concise manner, and it should be based on established research practices and standards. It is important to provide enough detail so that the reader can understand how the research was conducted and evaluate the validity of the results.

Applications of Research Methodology

Here are some of the applications of research methodology:

• To identify the research problem: Research methodology is used to identify the research problem, which is the first step in conducting any research.
• To design the research: Research methodology helps in designing the research by selecting the appropriate research method, research design, and sampling technique.
• To collect data: Research methodology provides a systematic approach to collect data from primary and secondary sources.
• To analyze data: Research methodology helps in analyzing the collected data using various statistical and non-statistical techniques.
• To test hypotheses: Research methodology provides a framework for testing hypotheses and drawing conclusions based on the analysis of data.
• To generalize findings: Research methodology helps in generalizing the findings of the research to the target population.
• To develop theories : Research methodology is used to develop new theories and modify existing theories based on the findings of the research.
• To evaluate programs and policies : Research methodology is used to evaluate the effectiveness of programs and policies by collecting data and analyzing it.
• To improve decision-making: Research methodology helps in making informed decisions by providing reliable and valid data.

Purpose of Research Methodology

Research methodology serves several important purposes, including:

• To guide the research process: Research methodology provides a systematic framework for conducting research. It helps researchers to plan their research, define their research questions, and select appropriate methods and techniques for collecting and analyzing data.
• To ensure research quality: Research methodology helps researchers to ensure that their research is rigorous, reliable, and valid. It provides guidelines for minimizing bias and error in data collection and analysis, and for ensuring that research findings are accurate and trustworthy.
• To replicate research: Research methodology provides a clear and detailed account of the research process, making it possible for other researchers to replicate the study and verify its findings.
• To advance knowledge: Research methodology enables researchers to generate new knowledge and to contribute to the body of knowledge in their field. It provides a means for testing hypotheses, exploring new ideas, and discovering new insights.
• To inform decision-making: Research methodology provides evidence-based information that can inform policy and decision-making in a variety of fields, including medicine, public health, education, and business.

Advantages of Research Methodology

Research methodology has several advantages that make it a valuable tool for conducting research in various fields. Here are some of the key advantages of research methodology:

• Systematic and structured approach : Research methodology provides a systematic and structured approach to conducting research, which ensures that the research is conducted in a rigorous and comprehensive manner.
• Objectivity : Research methodology aims to ensure objectivity in the research process, which means that the research findings are based on evidence and not influenced by personal bias or subjective opinions.
• Replicability : Research methodology ensures that research can be replicated by other researchers, which is essential for validating research findings and ensuring their accuracy.
• Reliability : Research methodology aims to ensure that the research findings are reliable, which means that they are consistent and can be depended upon.
• Validity : Research methodology ensures that the research findings are valid, which means that they accurately reflect the research question or hypothesis being tested.
• Efficiency : Research methodology provides a structured and efficient way of conducting research, which helps to save time and resources.
• Flexibility : Research methodology allows researchers to choose the most appropriate research methods and techniques based on the research question, data availability, and other relevant factors.
• Scope for innovation: Research methodology provides scope for innovation and creativity in designing research studies and developing new research techniques.

Research Methodology Vs Research Methods

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Research Methods

Chapter 2 introduction.

Maybe you have already gained some experience in doing research, for example in your bachelor studies, or as part of your work.

The challenge in conducting academic research at masters level, is that it is multi-faceted.

The types of activities are:

• Finding and reviewing literature on your research topic;
• Designing a research project that will answer your research questions;
• Collecting relevant data from one or more sources;
• Analyzing the data, statistically or otherwise, and
• Writing up and presenting your findings.

Some researchers are strong on some parts but weak on others.

We do not require perfection. But we do require high quality.

Going through all stages of the research project, with the guidance of your supervisor, is a learning process.

The journey is hard at times, but in the end your thesis is considered an academic publication, and we want you to be proud of what you have achieved!

Probably the biggest challenge is, where to begin?

• What will be your topic?
• And once you have selected a topic, what are the questions that you want to answer, and how?

In the first chapter of the book, you will find several views on the nature and scope of business research.

Since a study in business administration derives its relevance from its application to real-life situations, an MBA typically falls in the grey area between applied research and basic research.

The focus of applied research is on finding solutions to problems, and on improving (y)our understanding of existing theories of management.

Applied research that makes use of existing theories, often leads to amendments or refinements of these theories. That is, the applied research feeds back to basic research.

In the early stages of your research, you will feel like you are running around in circles.

You start with an idea for a research topic. Then, after reading literature on the topic, you will revise or refine your idea. And start reading again with a clearer focus ...

A thesis research/project typically consists of two main stages.

The first stage is the research proposal .

Once the research proposal has been approved, you can start with the data collection, analysis and write-up (including conclusions and recommendations).

Stage 1, the research proposal consists of he first three chapters of the commonly used five-chapter structure :

• Chapter 1: Introduction
• An introduction to the topic.
• The research questions that you want to answer (and/or hypotheses that you want to test).
• A note on why the research is of academic and/or professional relevance.
• Chapter 2: Literature
• A review of relevant literature on the topic.
• Chapter 3: Methodology

The methodology is at the core of your research. Here, you define how you are going to do the research. What data will be collected, and how?

Your data should allow you to answer your research questions. In the research proposal, you will also provide answers to the questions when and how much . Is it feasible to conduct the research within the given time-frame (say, 3-6 months for a typical master thesis)? And do you have the resources to collect and analyze the data?

In stage 2 you collect and analyze the data, and write the conclusions.

• Chapter 4: Data Analysis and Findings
• Chapter 5: Summary, Conclusions and Recommendations

This video gives a nice overview of the elements of writing a thesis.

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• Knowledge Base

Methodology

Research Methods | Definitions, Types, Examples

Research methods are specific procedures for collecting and analyzing data. Developing your research methods is an integral part of your research design . When planning your methods, there are two key decisions you will make.

First, decide how you will collect data . Your methods depend on what type of data you need to answer your research question :

• Qualitative vs. quantitative : Will your data take the form of words or numbers?
• Primary vs. secondary : Will you collect original data yourself, or will you use data that has already been collected by someone else?
• Descriptive vs. experimental : Will you take measurements of something as it is, or will you perform an experiment?

Second, decide how you will analyze the data .

• For quantitative data, you can use statistical analysis methods to test relationships between variables.
• For qualitative data, you can use methods such as thematic analysis to interpret patterns and meanings in the data.

Table of contents

Methods for collecting data, examples of data collection methods, methods for analyzing data, examples of data analysis methods, other interesting articles, frequently asked questions about research methods.

Data is the information that you collect for the purposes of answering your research question . The type of data you need depends on the aims of your research.

Qualitative vs. quantitative data

Your choice of qualitative or quantitative data collection depends on the type of knowledge you want to develop.

For questions about ideas, experiences and meanings, or to study something that can’t be described numerically, collect qualitative data .

If you want to develop a more mechanistic understanding of a topic, or your research involves hypothesis testing , collect quantitative data .

You can also take a mixed methods approach , where you use both qualitative and quantitative research methods.

Primary vs. secondary research

Primary research is any original data that you collect yourself for the purposes of answering your research question (e.g. through surveys , observations and experiments ). Secondary research is data that has already been collected by other researchers (e.g. in a government census or previous scientific studies).

If you are exploring a novel research question, you’ll probably need to collect primary data . But if you want to synthesize existing knowledge, analyze historical trends, or identify patterns on a large scale, secondary data might be a better choice.

Descriptive vs. experimental data

In descriptive research , you collect data about your study subject without intervening. The validity of your research will depend on your sampling method .

In experimental research , you systematically intervene in a process and measure the outcome. The validity of your research will depend on your experimental design .

To conduct an experiment, you need to be able to vary your independent variable , precisely measure your dependent variable, and control for confounding variables . If it’s practically and ethically possible, this method is the best choice for answering questions about cause and effect.

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Your data analysis methods will depend on the type of data you collect and how you prepare it for analysis.

Data can often be analyzed both quantitatively and qualitatively. For example, survey responses could be analyzed qualitatively by studying the meanings of responses or quantitatively by studying the frequencies of responses.

Qualitative analysis methods

Qualitative analysis is used to understand words, ideas, and experiences. You can use it to interpret data that was collected:

• From open-ended surveys and interviews , literature reviews , case studies , ethnographies , and other sources that use text rather than numbers.
• Using non-probability sampling methods .

Qualitative analysis tends to be quite flexible and relies on the researcher’s judgement, so you have to reflect carefully on your choices and assumptions and be careful to avoid research bias .

Quantitative analysis methods

Quantitative analysis uses numbers and statistics to understand frequencies, averages and correlations (in descriptive studies) or cause-and-effect relationships (in experiments).

You can use quantitative analysis to interpret data that was collected either:

• During an experiment .
• Using probability sampling methods .

Because the data is collected and analyzed in a statistically valid way, the results of quantitative analysis can be easily standardized and shared among researchers.

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

• Chi square test of independence
• Statistical power
• Descriptive statistics
• Degrees of freedom
• Pearson correlation
• Null hypothesis
• Double-blind study
• Case-control study
• Research ethics
• Data collection
• Hypothesis testing
• Structured interviews

Research bias

• Hawthorne effect
• Unconscious bias
• Recall bias
• Halo effect
• Self-serving bias
• Information bias

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
• If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

Methodology refers to the overarching strategy and rationale of your research project . It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives.

Methods are the specific tools and procedures you use to collect and analyze data (for example, experiments, surveys , and statistical tests ).

In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section .

In a longer or more complex research project, such as a thesis or dissertation , you will probably include a methodology section , where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods.

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• Published: 18 September 2024

An adaptive operation planning and EBO-BPNN optimization method for decision support systems

• Yunxiao Liu 1 ,
• Yiming Wang 1 ,
• Guangyao Wang 2 &
• Jianliang Ai 1  

Scientific Reports volume  14 , Article number:  21838 ( 2024 ) Cite this article

Metrics details

• Aerospace engineering
• Electrical and electronic engineering

Formulating a course of action (COA) before a combat is crucial for operational command. Research in command and control (C2) artificial intelligence is currently focused on using intelligent auxiliary decision-making methods to implement COA. This paper proposes a COA planning method based on line of operation (LOO) and uses planning domain definition language (PDDL) to describe combat scenarios and COA. Following the effect-based optimization (EBO) principle, an effect evaluation model for COA was constructed, and dynamic bayesian networks (DBNs) was used to determine the reasoning and calculate the results of the effect evaluation network. To further improve the execution efficiency of the effect evaluation model in practical applications, the network was optimized through a back propagation neural network (BPNN). Relevant experiments based on the coordinated distributed air defense and anti-missile scenario were carried out using the LOO model to complete the planning of COA. A BPNN evaluation model based on the DBNs evaluation model was built. After training and fine-tuning, it achieved similar evaluation results, with a mean absolute percentage error (MAPE) of less than 0.02%. Compared with the DBNs model, the BPNN model achieved an efficiency improvement of no less than 65%, effectively reducing the consumption of computing resources. This research is the first time to realize the modeled description of COA planning, automatic evaluation, and calculation optimization of COA effects. It can support the development of decision support systems (DSS) and has the potential for practical application.

Introduction

Automatic planning of COA is a typical application of DSS. DSS is widely used in various industrial scenarios that require fast and efficient decision-making 1 , 2 , 3 . The development of DSS capable of tactical-level COA planning represents a current research focus within the C2 domain. Tactical commanders’ command and decision-making process often face highly complex and contentious battlefield situations. Giving full play to the advantages of COA intelligent planning in tactical planning will play an essential role in promoting cross-domain joint combat operation command.

The COA approach converts the commander’s intention into a specific combat action plan. In recent years, with the increasing use of artificial intelligence technology in combat decision-making, developing combat DSS with intelligent COA planning and optimization has become a crucial focus in C2 intelligence. COA optimization is the optimization process of feasible combat action plans. In tactical planning, COA optimization aims to find the most effective and workable action plan to achieve mission objectives to the greatest extent and ultimately achieve the best combat effect under limited resources. Using machine learning algorithms to solve optimization problems in combat action planning can achieve scene adaptation, data-driven intelligent decision-making and computing resource optimization, thereby improving the decision-making speed and tactical flexibility of the combat auxiliary DSS. Using machine learning algorithms to achieve COA optimization is a critical technology that urgently needs breakthroughs in intelligent combat decision-making 4 .

In recent years, relevant COA planning and optimization research has focused on modelling process research based on rules 5 , probabilistic networks, or classic planning-solving algorithms. Wang et al. 6 proposed an intelligent planning method for combat missions based on probability graphs. This method determines the causal relationship between tasks through statistical analysis, uses Graph Neural Networks (GNN) to extract critical events in the task to construct a probability map, and then calculates the mission planning solution or the probability of success. He et al. 7 proposed a model based on heterogeneous networks to represent the relationships among various elements and to generate COA by decomposing combat tasks. It provides auxiliary control and offers network-based information to the commander. This method provides conditional support for command and decision-making. Marques et al. 8 proposed an ontology-based COA planning method. The core of this work is to solve and generate combat actions based on hierarchical network planning technology. Bayesian networks can convert dynamic decision-making problems into probabilistic inference problems, and many recent studies have been carried out on this. Pang et al 9 . proposed a Role-based Bayesian decision framework for autonomous unmanned systems. This framework can realize situation awareness based on multi-entity Bayesian networks to describe action scenarios and uncertainties semantically. It was verified through virtual mission scenarios, and the application of Bayesian networks in situation awareness was explored. Kim et al. 10 proposed a situational awareness model based on DBN, which can quantify the uncertainty in the battlefield and then predict the enemy’s intentions. They also further studied the interaction between the predicted enemy intentions and COA. Several COA effect evaluation methods based on Wargaming have been proposed regarding COA optimization. Yuksek et al. 11 implemented a high-precision intelligent wargaming method to implement COA analysis, which was verified by the simulation. The simulation environment includes a grid-world representation of the operation area, performance models of military units and combat models. DeBerry et al. 12 proposed a wargaming commodity COA automated method under uncertainty, which models a wargame scenario as a stochastic multi-commodity flow problem and produces an optimal COA that minimizes risk when the enemy force amounts are unknown. This method can help commanders observe the Correlation between COA success rate and risk to help evaluate COA. The above research content provides a theoretical and practical basis for COA intelligent planning. However, traditional COA planning methods based on rules or probabilistic networks may bring specific challenges in developing and applying intelligent combat auxiliary DSS. It is difficult to adapt to highly dynamic saturation attack combat scenarios. The main reason is that in the execution process of reasoning methods based on rules or probabilistic networks, there may be a surge in computational complexity caused by the rapid expansion of the network, which significantly affects the optimization efficiency of COA development.

In 2021, the Rand Corporation report on machine learning assisted command and control decision-making 13 . The report summarized representative classic and modern artificial intelligence algorithms. It divides intelligent auxiliary decision-making tasks into planning, classification and reaction. The applicability of various typical artificial intelligence algorithms for different decision-making tasks is analyzed. In 2023, the Causal Adaptive Combat Decision Assistance System (CADA) research report proposed the causal concept of using machine learning algorithms to carry out intelligent generation and recommendation of COA. A combat auxiliary decision-making method was explored based on causal feature learning and domain expertise display. Therefore, in the defence industry, DSS that can realize the intelligent generation of COA has application requirements. The research proposed in this paper is precisely to solve the critical issues in the application process.

The paper makes the following main contributions:

We propose an adaptive COA planning method based on the LOO model. To define the inputs of the model, decision areas, decision points, and specific elements related to the combat operation, PDDL was used according to the execution logic and constraints of the combat operation. This method accurately enables the adaptive description of the COA planning process and its necessary elements.

Based on the LOO model, a DBNs effect evaluation network was created using the EBO theory, and a systematic evaluation method for COA was established. This method constructs an interpretable and inferential effect evaluation model, which represents the action and effect nodes and the influence relationships between nodes in the evaluation networks.

Based on the DBNs evaluation method, the EBO-BPNN evaluation model was proposed. A BPNN evaluation model was established to optimize the calculation efficiency of the COA optimization process.

As described above, a coordinated distributed air defense and the anti-missile scenario were created to test the method’s effectiveness. The scenario modelling and COA planning process were completed, and optional COAs were effectively generated. Subsequently, the EBO-BPNN evaluation method for COAs proposed in this paper was experimentally verified.

LOO-based COA generation method

The process of planning a COA is typically divided into three categories based on the driving factors of the generation process: Threat-Based Planning (TBP), Capability-Based Planning (CBP) and Scenario-Based Planning (SBP). There have been many research results in this field. Planning a COA can provide a feasible sequence of actions for the current battlefield situation. COA optimization extends the COA planning link in the intelligent tactical planning auxiliary decision-making process. The core content of COA optimization is to analyze and select the optimal COA from this set.

Modeling of COA planning and optimization

After analysis, it was found that at the tactical level COA planning level, the TBP planning method 14 is usually used to drive the generation of our COA by clarifying the centre of gravity (COG), the enemy’s combat capabilities, and our feasible methods to deal with the enemy’s combat capabilities 7 , 15 . The premise of COA planning is to realize the intelligent generation of COA reasonably and accurately. The JP 5-0 outline comprehensively analyzes the relevant elements that may be involved in the COA planning and optimization process. It describes the action planning process with COA generation and optimization as the main content. This paper references the action planning process in JP 5-0. It fully considers the interface and input and output issues involved in the design and development process of the intelligent tactical auxiliary decision-making system. The implementation process is shown in Fig. 1 .

The process of intelligent tactical auxiliary decision-making implementation.

Among them, this paper divides the implementation of intelligent tactical decision-making into six steps: (a) threat assessment, (b) intent analysis, (c) COG analysis, (d) mission analysis, (e) COA planning, (f) COA optimization. By running the functions (a) to (d), the necessary elements required for COA planning can be obtained. That is the enemy target group and threat assessment results, the enemy target group intention, our combat focus and our combat missions. The preorder process in implementing intelligent tactical auxiliary decision-making can output the necessary input required for the COA planning process.

Modeling and implementation of LOO method

As shown in Fig. 2 , this paper proposes a COA planning framework based on the LOO model, which explains the COA planning logical operation process and core elements.

COA generation framework driven by the LOO model.

This framework implements the COA planning method based on TBP, and our combat focus serves as an essential input to the framework. It also clarified the enemy targets that must be attacked or intercepted under the current battlefield. Our operational COG is based on the analytic hierarchy process, which fully integrates the results of the enemy’s threat ranking and intentions. This framework constructs a COA planning method based on our combat resources and combat areas for our combat COG. The LOO model is the critical driving means for COA planning, which can realize dynamic and feasible kill chain and assessment chain. The reconstruction under the guidance of the theoretical framework of F2T2EA (Find, Fix, Track, Target, Engage, Assess), a coordinated, integrated kill-web 16 , 17 can be constructed, giving full play to the advantages of tactical flexibility in coordinated combat scenarios.

To build a coordinated, integrated kill net based on LOO, it is first necessary to clearly define the COG, decision-making area, combat resources, mission, decisive condition (DC), DC points, effects, actions and other elements and application processes in the process of building the operation line. Considering the diverse characteristics of the tactical decision-making process in different combat scenarios and the general need for generated models, the use of PDDL can define the key elements and relationships required in building combat lines 18 . Thus, PDDL has been widely used in intelligent planning to form an updateable domain knowledge file 19 .

Phase 1: clarify and get external input

Construct the external input entity after obtaining the COG, decision area, combat resources, and tasks processed by the external module.

Phase 2: decision area and decision point generation

The entire battlefield area is divided into different decision-making areas. Decision points define the boundaries of the decision area. Each combat unit or formation can perform corresponding actions by tactical rules in different areas.

Definition of phase 1 and 2

External input elements are defined as “objects”, the object type is clarified with “types”, and the relationship, attributes, or conditions between objects are represented with the predicate “predicates”. The initial state is defined with “init”.

Phase3 determination of DC and DC point

DC is a combination of combat action effects that, when achieved, will give the commander a significant advantage over an opponent or contribute significantly to achieving combat objectives. The DC point corresponds to the critical point for completing a tactical action goal. In applying the LOO model for intelligent tactical planning, it is first necessary to determine the goals and objectives of combat operations based on the COG. Moreover, based on this, the corresponding decisive conditions and the DC point at which the DCs are completed and established.

Phase 4: generation of actions, effects and feasible actions

The effect is an identifiable change in an operational process or physical state caused by one or more actionable actions. The operational line connects the DCs to achieving operational objectives and the effects impact the completion of the DCs. The key to implementing the LOO model is determining the sequence and influence relationship of feasible actions, effects and DCs.

Definition of phase 3 and 4

The key points and object processing logic flow when applying the LOO model are described through predicates composed of “ achieves, drives, composes, has, and action-end ”. When using PDDL to represent a tactical planning instance, it can be described as a two-tuple:

Among them, “ planning _ input ” is the external input domain knowledge description file, and “ line _ of _ operation ” is the planning process description file under the current combat mission. Combat scenarios and planning models can be modularized by simply predefining different description files.

Phase 5: obtain a feasible COA that complies with tactical rules

After completing phases 1 to 4, the COAs based on combat formations and divided into time segments can be obtained according to the constraints of the tactical planning process. These optional COAs need to be further optimized. Figure 3 shows the standard style of a COA.

Tactical level COA standard format for combat formations.

Effect-based optimization of COA

In most cases, the COA planning method based on the LOO model can obtain several alternative COAs that comply with tactical rules based on the battlefield situation and available combat resources. Each optional COA has different advantages and disadvantages, and COA optimization helps to comprehensively understand each COA and determine the best COA 20 . At the level of COA optimization implementation based on EBO 8 , there are mainly methods such as DBNs 21 , 22 , genetic algorithm 23 , and probability graphs 6 . The above methods have advantages in the interpretability of combat operations and their effects. Combined with the assessment of impact probability by C2 experts, a more accurate prior probability of inference can be obtained, which lays a good foundation for achieving highly robust combat auxiliary decision-making. However, it also has the disadvantages of high computational complexity and slow convergence speed, so optimizing this problem is crucial.

This paper fully uses the advantages of DBNs in the interpretability of reasoning logic to model the effect chain of the LOO model. Combined with the action-effect conditional probability evaluated by experts, the effect inference results of a single COA are generated, and a training sample data set necessary for the machine learning optimization algorithm is established.

Construction of COA effect evaluation model

A complete optional COA can be obtained based on the LOO model. At the same time, the effect evaluation chain of each operation line can be obtained. Multiple effect evaluation chains can be aggregated to form an effect evaluation network 24 . The effect evaluation network’s construction process is divided into three steps: network node identification, impact relationship analysis, and determining impact intensity.

Phase 1: effect evaluation network node identification

The construction of the effect evaluation network requires first clarifying which nodes it consists of. According to the LOO model designed in this paper, actions, direct effects produced by actions, intermediate effects, DC point effects, and COA evaluation results are used as five types of nodes in the effect evaluation network. Therefore, type 5 nodes can be described as the following five-tuple:

where, \({\varvec{N}}_{a}\) is the action node-set, which represents several actions that the combat node may perform; \({\varvec{N}}_{e}\) represents the action-effect node-set, which expresses the direct effects produced by the combat node after executing the combat action; \({\varvec{N}}_{me}\) represents the intermediate effect set, which cannot be directly observed The indirect effect; \({\varvec{N}}_{dc}\) represents the DC point effect-set, which is the final effect-set of the execution of a series of combat operations in a critical area or time segment. \({\varvec{N}}_{coa}\) represents the effect evaluation node set of the complete COA.

Phase 2: effect evaluation network relationship analysis

After determining the nodes in the effect evaluation network through the above steps, further determining the influence relationship between the nodes is necessary. The connection relationship between the five types of nodes can be described as the following five-tuple:

where, \({\varvec{R}}_{ae}\) defines the set of connecting relationships from action nodes to action-effect nodes. For any \({{n}_{b}}\in {\varvec{N}}_{b}\) , there exists \({{n}_{a}}\in {{\varvec{N}}_{a}}\) that satisfies \(\left\langle {{n}_{a}},{{n}_{b}} \right\rangle \in {{\varvec{R}}_{ae}}\) :

\({\varvec{R}}_{eme}\) is a collection of connecting relationships between action-effect and intermediate effect nodes. It describes the influence of action effects on intermediate effects. The intermediate effect may be affected by multiple action-effect nodes simultaneously, satisfying:

\({\varvec{R}}_{medc}\) is the set of relationships connecting intermediate effect nodes and DC points. It describes the impact of intermediate effects on DC point effects and satisfies:

\({\varvec{R}}_{dcdc}\) is the set of connecting relationships between different DC points. It describes the impact of the DC point effects and satisfies:

\({\varvec{R}}_{coa}\) represents the connecting relationships between DC points and COA effect evaluation nodes. It describes the influence relationship of multiple DC points on the final effect evaluation of COA and satisfies the following:

Phase 3: determine the intensity of the impact

Impact intensity refers to the degree of influence of the intensity change of the parent node on the child nodes. The prior and baseline probability are used as the impact intensity parameters. The prior probability refers to the execution probability of the combat operation at the initial moment. The base probability is the probability that an effect node achieves the expected effect when taking action. The impact intensity is described as follows:

\({S}_{a}\) represents the intensity of the direct effect produced by the implementation of combat operations on the combat target, and \({S}_{e}\) represents the intensity of the intermediate effect on the DC point. They can usually be calculated based on the preset values of C2 command experts.

COA effect calculation based on DBNs

DBNs is developed based on bayesian network (BN) and belongs to the category of probability graphical model. DBNs add event sequence data or variables that evolve to BN, allowing the modelling of relationships that change over time. The COA effect evaluation network can be modelled and implemented through DBNs, and the DBNs can infer the evaluation results for COA. BN is a directed acyclic graph, represented by \(G=(V,E)\) , where V and E are the node set and the relationship set connecting the nodes. DBNs can be decomposed into a static BN and a time transfer network, defined as \(({{B}_{0}},{{B}_{2d}})\) . \({B}_{0}\) represents the static BN at the initial moment, and \({B}_{2d}\) represents the BN, including two adjacent time slices. The joint probability of the static BN at the initial moment is defined as \(P({{x}_{0}})\) , and the dynamic variable set of the DBNs is defined as \(X=\{{{X}^{1}},{{X}^{2}},...{{X}^{n}}\}\) . Among them, \(X_{t}^{i}\) represents the state of the corresponding variable \({{X}^{i}}\) at time t , and \(\pi \left( X_{t}^{i} \right) =\text \!\!\{\!\!\text X_{t-1}^{i},\ P{{a}^{j}}(X_{t}^{i})\text \!\!\}\!\!\text ,\ \left( j=1,2,\cdots ,N-1 \right)\) is the set of parent nodes of \(X_{t}^{i}\) . \(P(\left. {{X}_{t}} \right| {{X}_{t-1}})\) is used to describe the transition probability of a node from \(t - 1\) to t , which can be obtained:

The joint probability calculation of DBNs can be realized by tracking the time series 24 . Assuming that T represents the length of the time series, the joint probability at time T can be obtained:

The structure of DBNs.

Figure 4 shows the DBNs structure expanded by time slices. The solid lines connect the directed dependencies in the static BN, and the dotted lines connect the probability transfer relationships of nodes between time slices. The joint probability of DBNs can be obtained from ( 11 ) distributed.

COA effect evaluation network based on DBNs.

Based on the joint probability evaluation and comparison of DBNs, the combat effectiveness assessment of different COAs can be realized. As shown in Fig. 5 , the COAs effect evaluation model based on DBNs is driven by the LOO model. The effect evaluation network covers action nodes, action-effect nodes, intermediate effect nodes, DC point effect nodes and COA evaluation result nodes, represented by \(a_{t}^{i},e_{t}^{i},me_{t}^{i},dc_{t}^{i}\) and \(coa_{n}\) respectively. Among them, the action-effect node may be composed of two parts in the actual application process: the direct effect of our actions and the impact of the enemy’s actions and changes on our actions to achieve a more comprehensive COA adversarial assessment. The probability calculation process of each node can be expressed as:

In applying DBNs to realize COA evaluation, the inference calculation of the joint probability of COA evaluation can be realized by dynamically adjusting the node structure and related node probability values according to the preset expert rules or conditional probabilities for each node.

COA optimization method based on EBO-BPNN

Coa optimization process based on ebo-bpnn.

Applying DBNs can realize the effect evaluation of COA. However, in the actual application process, the computing performance requirements are high when the number of DBNs nodes is enormous. By applying machine learning algorithms combined with model pretraining based on DBNs inference, the performance improvement of the COA optimization model can be better achieved. Some scholars have carried out relevant research on the application of machine learning algorithms in the field of intelligent decision-making. BPNN is a typical supervised learning algorithm in machine learning 25 . It uses the back-propagation algorithm to train the network and establish the mapping relationship between input data and output. BPNN can learn complex nonlinear relationships and is suitable for processing such as DBNs data migration and optimization calculations in the COA optimization process. It has good fitting ability and flexibility and can be applied to COA effect evaluation. The COA optimization process based on BPNN is divided into three phases, as shown in Fig. 6 .

COA optimization implementation process based on BPNN.

Phase 1: construction of the training dataset

Before constructing the EBO-BPNN model, it is necessary first to construct a training dataset through the COA effect evaluation model based on DBNs. First, determine the enemy’s target in the current combat scenario, the upper limit of our available resources, and the possible enemy actions. Then, we will use the LOO model to create feasible COAs for our formation and use DBNs for evaluation. As a result, a sufficient training dataset is obtained. The input of the training dataset is our COA and the enemy’s action, and the output is the evaluation result of COA using DBNs.

Phase 2: development of the EBO-BPNN model

Create an EBO-BPNN model. The input of the model is the combat actions of our side and the enemy, and the output is the evaluation result of the effectiveness of our actions. The training dataset generated in phase 1 is used as the learning process input and output of the neural network model, and the network parameters are continuously adjusted to achieve model tuning that can meet accuracy requirements.

Phase 3: application of the EBO-BPNN model

After training and tuning the EBO-BPNN model, the model is deployed and used. The LOO model creates COAs during the application stage based on the current combat situation. The actions of the own and the enemy are then input into the EBO-BPNN model, which allows for the quick determination of the impact of COAs, thus aiding in making efficient decisions.

Application of EBO-BPNN in COA optimization process

Basic principles of bpnn.

BPNN is a neural network algorithm with signal feedforward propagation and error back-propagation. In the signal feedforward propagation stage, the input signal is transmitted from the first hidden layer to the output layer, and the output signal is generated at the output layer. If the actual output is inconsistent with the expected output, the algorithm enters the error back-propagation stage. The error is propagated back from the output layer to the first hidden layer and distributed to all units in each layer. The network learning process is realized through continuous forward propagation and reverse adjustment, and the weights between neurons are continuously revised until the network output error meets the accuracy requirements 26 . This paper uses a BPNN with two hidden layers to analyze its principle. The network structure is shown in Fig. 7 .

Among them, let the number of signals contained in the input layer be h , and use o as the symbol of any neuron. The first hidden layer contains l neurons, and p represents any neuron. The output layer has n output neurons, and r represents any neuron. \(v_{qp}(p=1,2,...,l|q=1,2,...,m)\) represents the weight between the input and first hidden layers, and \(w_{rq}(q=1,2,...,m|r=1,2,...,n)\) represents the weight between the second and output layers. The input and output of the first hidden layer are represented by \(layer_{1}in_{p}(p=1,2,...,l)\) and \(x_p(p=1,2,...,l)\) , respectively, and the activation function is represented by \(f(\cdot )\) . \(layer_2in_q(q=1,2,...,m)\) and \(y_{q}(q=1,2,...,m)\) represent the input and output of the second hidden layer, and the activation function is represented by \(g(\cdot )\) . The input and output of the output layer are represented by \(layer_3in_r(r=1,2,...,n)\) and \(z_{r}(r=1,2,...,n)\) , respectively, and the activation function is represented by \(h(\cdot )\) . The training data set is represented by \(\varvec{T}=[T_{1},T_{2},...,T_{a},...,T_{z}]\) , and any sample can be represented by \(\varvec{T_{a}}=[t_{1a},t_{1a},t_{2a},...,t_{la}]^{\textrm{T}}(a=1,2,...,Z)\) .

BPNN structure.

The actual output and expected output during the neural network operation are represented by \(\varvec{z_{a}}=[z_{1a},z_{2a},...,z_{na}]^{\textrm{T}}\) and \(\varvec{d_{a}}=[d_{1a},d_{2a},...,d_{na}]^{\textrm{T}}\) , respectively. The network weight and output are num functions when num is the number of iterations. According to the feedforward propagation process of the input signal, assuming that the input training sample is \(\varvec{T_{a}}\) , then have

The matrix form of the above formulas is expressed as follows:

The r -th neuron of the output layer neuron it satisfies the following:

\(err_{ra}^2(num)/2\) is defined as the error energy of the r -th neuron, and the sum of the error energy of all neurons in the output layer is defined as \(E_a(num)\) , then:

The error signal is the difference between the network output and the desired output. This error signal will be passed from the output to the first hidden layer. This process is called the feedforward propagation stage of the error signal. The network’s weights and biases are adjusted at this stage through error feedback. The actual network output gradually approaches the expected output by repeatedly modifying the weights and biases. The calculation process of the error feedforward propagation stage is as follows:

The matrix form of the above process is as follows:

Where \(\eta\) is the learning rate that exists as a given constant, BPNN has completed the feedforward propagation and reverse adjustment process. This process is an iteration. BPNN needs to go through multiple iterations to converge the learning error to the preset accuracy.

Construction of EBO-BPNN in COA optimization

To optimize and evaluate COA using BPNN, it is necessary to first identify the input and output parameters of the network. When using DBNs to evaluate COA, the focus is primarily on the impact of combat formation actions on DC. Therefore, the input for the EBO-BPNN model consists of COA for all combat formations in the combat area, with the probability of DC impact on a specific COG being used as the network output. Based on the current battlefield situation, we have developed a comprehensive EBO-BPNN evaluation model for each COG to assess its potential impact. The final outcome of the EBO-BPNN is determined by the collective evaluation of all targets. Our objective is to select the most effective COA through optimization.

Application case analysis

Application and combat scenario design.

To test the LOO planning model and EBO-BPNN evaluation method, we propose and verify a coordinated distributed air defense and anti-missile scenario 27 , 28 , 29 . In Fig. 8 , the battlefield is divided into four decision areas, with the Vessel positioned at the center of areas. Red icons represent our combat formations, while blue icons represent the enemy’s formations. When an enemy target enters one of these areas and is detected by our formations, we assess the battlefield situation, the capabilities of each combat formations, and the status of available combat resources. Then, we will select the appropriate combat formations and complete COA planning based on above information.

Coordinated distributed air defense and anti-missile scenarios.

LOO based COA planning

The LOO model is used to plan COA for each decision area. Based on the missions assigned by the commander, the chosen COG, and the available resources of the combat formations, COA planning can be carried out for a single combat formation, or multiple formations can be combined. Combat formations carry out coordinated operations planning. Figure 9 illustrates the complete establishment process of the LOO model in the current coordinated air defense and anti-missile scenario. In the LOO model, to simplify the description, the names of the own formations are simplified and replaced with early warning UAV - E1, communication UAV - C, fighter UAV 1 - A1, fighter UAV 2 - A2, and vessel - V.

Coordinated distributed air defense and antimissile scenarios.

Then, we use PDDL language to complete an interception of missile 1 in area 2.

Definition of interception to missile 1

The LOOs for other COG targets are also created using the PDDL language. Once the LOO model for all enemy targets in the current situation is completed, the COA for each combat formation can be determined. Figure 10 displays one of the potential combinations of COAs, with Missile1 being the target for this set of COAs.

COA sample for target missile 1.

DBNs evaluation model establishment

According to the LOO model, we can obtain each decision area’s effect evaluation chain and effect evaluation network. Figure 11 displays the effect evaluation network of the four decision areas.

EBO effect evaluation networks based on DBNs.

An evaluation network is created according to the combat areas divided in the LOO model. The LOO model determines the type and number of nodes. In the evaluation network of each stage, the parent node represents the direct effect of the action. When the action occurs, its value changes. The middle layer shows the action’s intermediate effect, and each area’s bottom node represents the DC point effect of each COG. The connecting lines in each area depict the relationship of influence between nodes.

Each stage’s intermediate and DC effects will affect the effects of other stages. A static BN represents the network effect of each decision area. In the current scenario, since the combat stage is divided into four in the LOO model, the number and definition of BNs are determined accordingly. The dotted connecting line shows the probability transfer relationship of nodes between time slices. The intermediate and DC effects of the current decision area will influence the intermediate and DC effects of the following area. The last area’s DC evaluation result is the current COA’s evaluation result. To clearly illustrate the transfer relationship between Stage 2 and Stage 3, a schematic diagram of the connection between the two has been added in the lower left corner of Fig. 11 .

Construction of EBO-BPNN optimization model

This section outlines the construction of the EBO-BPNN optimization evaluation model under current combat scenarios. It includes the conversion from the DBNs model, the determination of input and output parameters, and the collection of datasets.

Collection of the datasets

We utilized Visual Studio to construct a DBN network that encompasses the current combat scenario. Randomly generated data will be used as input for the EBO-BPNN evaluation network dataset for each decision area, and the DBNs evaluation network will calculate the intermediate and DC effects of each decision area as the output of the dataset. For each evaluation network, 10,000 samples are generated, with 70% randomly selected as the training set, 15% as the validation set, and 15% as the test set. Figure 12 displays the input and output formats of some datasets of the BPNN-Combat network.

Sample datasets of BPNN-Combat.

Determination of parameters

Based on the current combat scenario and the evaluation network for the DBNs effect, it is necessary to construct four networks for each enemy target. These networks will be used to evaluate and predict the COAs in decision areas. The EBO-BPN in four decision areas are defined as BPNN-Warning, BPNN-Combat, BPNN-Cooperate, and BPNN-Vessel. They will be used to evaluate the impact of coordinated actions in decision areas to complete DC successfully.

The inputs of EBO-BPNN include our actions and the potential actions that the enemy may take. The intermediate and DC effects of different time segments are additional inputs.

In the BPNN-Cooperate example, the network’s input layer consists of 13 nodes. Nodes 1 to 8 represent the actions of multiple combat formations in the current decision area, while the ninth node represents the potential actions taken by the enemy target. The values of these nine nodes representing actions are 1.0 or 0.0, with 1.0 indicating the execution of the action. The 10th to 12th nodes represent the intermediate effect of the previous regional stage, and the 13th node represents the DC effect of the previous decision area on a specific COG target. The network’s output layer consists of four nodes, Node 1 representing the DC effect of the combat formation’s action on a specific COG target in the current regional stage. Nodes 2 to 4 represent the intermediate effect of the current area.

The network’s hidden layer determines the robustness and accuracy of the network evaluation. This study utilizes a single hidden layer network structure. Typically, a single hidden layer can solve most problems 30 , and the effectiveness of a single hidden layer was also confirmed during subsequent experiments.

In order to obtain more accurate evaluation results, it is essential to reasonably determine the number of neurons in the hidden layer when building a network. A reasonable number of neurons can ensure sufficient fitting and local optimal solutions. In this study, the initial setting for the number of neurons in the hidden layer is 2/3 of the number of input nodes plus the number of output nodes. The number of neurons is adjusted during subsequent training and testing to achieve optimal prediction results. Specifically, the number of neurons is at most twice the number of input nodes.

The learning rate is a critical parameter that affects the training speed and stability. A more significant learning rate may lead to an unstable model training process, while a smaller learning rate will slow down the training speed 31 . Our study selected a lower learning rate for a more stable training result. Table 1 shows the the hyperparameter settings.

Model training and tuning

After collecting and processing the datasets, it is essential to build a neural network and tune the training parameters to improve the accuracy of evaluating the effect of the COA. We will use MATLAB code to construct the EBO-BPNN model, and randomly divide and import the datasets. Various measures are available to compare the accuracy of a network’s evaluation of the effects of COAs. However, no universal standard method exists, so using multiple metrics to evaluate the network is essential 32 . This study utilizes three indicators: mean absolute error (MAE), mean squared error (MSE) and mean absolute percentage error (MAPE) 33 , 34 .

Where \(y_{n}\) is the actual evaluation result calculated using the DBN network, \(\hat{y}_{n}\) is the action sequence evaluation result predicted by the EBO-BPNN network, and N is the total number of data used to test the network.

Performance analysis

This section introduces the experimental results of four networks for evaluating the effect of COAs. All networks have been tuned multiple times, and the appropriate number of hidden layer neurons has been selected to achieve the required training accuracy. Fig. 13 illustrates the training process of the four networks.

The training processes of EBO-BPNNs.

The training environment is configured with Core i7-11800H, 16GB RAM, and GeForce RTX3060 6GB GPU. All four networks can reach the required training accuracy before reaching the maximum number of iterations. Specifically, BPNN-Warning converges in 173 epochs, BPNN-Combat in 140 epochs, BPNN-Cooperate in 243 epochs, and BPNN-Vessel in 131 epochs. To assess the predictive capability of the network, we randomly created 50 extra sets of data for testing purposes and employed the trained network for testing.

Comparison of observed and predicted data.

Figure 14 compares the test and predicted data of DC effects, it shows the regression of the model data. The X-axis represents the actual value of the dataset, and the Y-axis represents the model’s predicted value. The higher the overlap between the actual and predicted values, the better the model’s performance. The results show that the model can obtain good prediction results within the value range of the data set. The model’s performance meets the use requirements and can accurately evaluate COA. Figure 15 illustrates the absolute errors of DC effects in four networks. The absolute errors of the selected test data are all less than \(2.5\times 10^{4}\) .

In addition, Table 2 contains additional evaluation indicators for the models, all results are for DC effect. These indicators are derived from the test set used during training. The results indicate that BPNN-Combat has the lowest MAPE at 0.006733%, and the MAPE of the other three networks is also less than 0.02%, which meets the requirements and demonstrates the ability to effectively evaluate the COAs.

Absolute errors of the test data.

More importantly, using the BPNN-EBO method can effectively reduce the consumption of computing resources. Table 3 compares the COA evaluation results obtained using the BPNN-EBO and the DBNs methods. It is important to note that the outcomes presented for both models reflect the performance of a singular target. The five selected sets of data are randomly generated. It can be seen that using the BPNN-EBO method can obtain evaluation results similar to DBNs, and its MAPE is 0.0143798%. At the same time, using the same computing resources, the average time consumed is reduced by, resulting in a 69.83% improvement in efficiency, which can effectively improve the efficiency of COA evaluation for airborne scenarios where computing resources are constrained. Model training took less than 10 hours during our experiments, allowing for quick retraining and adjustment to new scenarios.

Conclusions

This paper proposes the LOO-based COA planning and EBO-BPNN evaluation methods. The COAs were determined using the LOO model, and prediction experiments were carried out on the EBO-BPNN model. The effectiveness of developing tactical-level COA was verified. The main conclusions are as follows:

The LOO model, established in this paper using PDDL language, accurately defines the input of combat elements, including decision areas, decision points, and other characteristic information related to COA generation. The model can adapt to battlefield environments and rapidly generate optional COAs.

This paper established a DBNs evaluation model to evaluate and optimize COA and modeled each node in the DBNs evaluation network to make it interpretable and scalable.

Based on the DBNs evaluation network, we constructed the EBO-BPNN evaluation model, which can further optimize and improve the computational efficiency of the COA optimization process. After testing and verification, the EBO-BPNN model can achieve similar evaluation results to the DBNs model, with MAPE of less than 0.02%. Compared with the DBNs model, the EBO-BPNN model can achieve an efficiency improvement of no less than 65%, effectively reducing the consumption of computing resources. Experts have verified the process and results.

In summery, the methods proposed in this paper achieve the modeled description and generation of COA development, automatic evaluation, and calculation optimization of COA effects. It is worth noting that this method can be adapted to different combat scenarios during application. We can quickly model new scenarios by redefining and expanding relevant elements in the LOO model, updating and expanding nodes in the evaluation network, and completing the training and tuning of the EBO-BPNN model, which allows us to complete the compliance COA planning and optimization with different scene constraints. It can effectively support the development and application of intelligent auxiliary DSS.

Data availability

The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.

Qureshi, S. G. & Shandilya, S. K. Nature-inspired adaptive decision support system for secured clustering in cyber networks. Multimed. Tools Appl. 83 , 3153–3187 (2024).

Article   Google Scholar  

Kwon, Y. & Lee, Z. A hybrid decision support system for adaptive trading strategies: Combining a rule-based expert system with a deep reinforcement learning strategy. Decis. Support Syst. 177 , 114100 (2024).

Sadeghi, K., Ojha, D., Kaur, P., Mahto, R. V. & Dhir, A. Explainable artificial intelligence and agile decision-making in supply chain cyber resilience. Decis. Support Syst. 180 , 114194 (2024).

McDowell, K., Novoseller, E., Madison, A., Goecks, V. G. & Kelshaw, C. Re-envisioning command and control. In 2024 International Conference on Military Communication and Information Systems (ICMCIS) , 1–7 (IEEE, 2024).

Chen, C., Feng Kong, D., Du Jun, Z. & Li, R. Modeling and solution of coa development based on timed influence net and game theory. Appl. Math. Model. 38 , 5269–5278. https://doi.org/10.1016/j.apm.2014.04.019 (2014).

Article   MathSciNet   Google Scholar  

Wang, B. et al. Intelligent planning method of combat mission based on probability graph(in chinese). Syst. Eng. Electron. 42 , 2795–2801 (2020).

Google Scholar  

He, H., Wang, W., Zhu, Y., Li, X. & Wang, T. An operation planning generation and optimization method for the new intelligent combat sos. IEEE Access 7 , 156834–156847 (2019).

Marques, H. C., de Oliveira, J. & da Costa, P. Representing coa with probabilistic ontologies. In 16th International Command and Control Research and Technology Symposium (2011).

Pang, W., Ma, X., Liang, X., Liu, X. & Dong, E. Role-based bayesian decision framework for autonomous unmanned systems. J. Syst. Eng. Electron. 34 , 1397–1408 (2023).

Kim, A. & Lee, D. Dynamic bayesian network-based situational awareness and course of action decision-making support model. Expert Syst. Appl. 252 , 124093 (2024).

Yuksek, B., Guner, G., Karali, H., Candan, B. & Inalhan, G. Intelligent wargaming approach to increase course of action effectiveness in military operations. AIAA SCITECH 2023 Forum [SPACE] https://doi.org/10.2514/6.2023-2531 (2023).

DeBerry, W. T., Dill, R., Hopkinson, K., Hodson, D. D. & Grimaila, M. The wargame commodity course of action automated analysis method. J. Def. Model. Simul. 21 , 17–29 (2024).

Walsh, M. et al. Exploring the feasibility and utility of machine learning-assisted command and control. Supporting Technical Analysis 2 (2021).

Mazarr, M. et al. The U.S. Department of Defense’s Planning Process: Components and Challenges . G - Reference,Information and Interdisciplinary Subjects Series (RAND Corporation, 2019).

Clark, B., Patt, D., Schramm, H., for Strategic, C. & Budgetary Assessments (Washington, D. Mosaic Warfare: Exploiting Artificial Intelligence and Autonomous Systems to Implement Decision-centric Operations (Center for Strategic and Budgetary Assessments, 2020).

Yang, K., Xia, B., Chen, G., Yang, Z. & Li, M. Multi-objective optimization of operation loop recommendation for kill web. J. Syst. Eng. Electron. 33 , 969–985 (2022).

Jiang, J., Li, J., Xia, B. & Yang, K. Modeling and resilience analysis of combat systems-of-systems based on kill web. In 2022 17th Annual System of Systems Engineering Conference (SOSE) , 28–35 (IEEE, 2022).

Arora, A., Fiorino, H., Pellier, D., Métivier, M. & Pesty, S. A review of learning planning action models. Knowl. Eng. Rev. 33 , e20 (2018).

Lindsay, A. On using action inheritance and modularity in pddl domain modelling. In Proceedings of the International Conference on Automated Planning and Scheduling 33 , 259–267 (2023).

Wu, Z. & Cao, Y. Advances in research on joint operational design methods. In 2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC) , vol. 9, 207–212 (IEEE, 2020).

Kelleher, C. T., Hill, R. R., Bauer, K. W. & Miller, J. O. Using dynamic bayesian networks as simulation metamodels based on bootstrapping. Comput. Indus. Eng. 115 , 595–602 (2018).

Wan, L., Zhong, Y. & Li, W. Coa optimized selection method of aviation swarm based on dins and dabc. IEEE Access 8 , 65116–65126. https://doi.org/10.1109/ACCESS.2020.2982784 (2020).

Zhou, Y., Zhao, H., Chen, J. & Jia, Y. A novel mission planning method for uavs’ course of action. Comput. Commun. 152 , 345–356 (2020).

Benhamou, E., Atif, J. & Laraki, R. A new approach to learning in dynamic bayesian networks (dbns). arXiv preprint [SPACE] arXiv:1812.09027 (2018).

Buscema, M. Back propagation neural networks. Subst. Use Misuse 33 , 233–270 (1998).

Article   CAS   PubMed   Google Scholar  

Zhang, L., Wang, F., Sun, T. & Xu, B. A constrained optimization method based on bp neural network. Neural Comput. Appl. 29 , 413–421 (2018).

Article   CAS   Google Scholar  

Ji, J. et al. Ontology Construction and Reasoning of Air Defense and Anti-missile Assistant Decision Based on Distributed Operation. In 2021 7th International Conference on Big Data and Information Analytics (BigDIA) , 157–165 (IEEE, Chongqing, China, 2021).

Li, H., Zhao, Q., Sun, J., Xia, B. & Ding, J. Modeling and Parameter Optimization of Anti-Missile System Combat Network. In 2021 7th International Conference on Computing and Artificial Intelligence , 314–320 (ACM, Tianjin China, 2021).

Ding, J., Zhao, Q., Li, J. & Xu, J. Temporal constraint modeling and conflict resolving based on the combat process of air and missile defense system. In 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC) , 2684–2689 (IEEE, 2019).

Gaurang, P., Ganatra, A., Kosta, Y. & Panchal, D. Behaviour analysis of multilayer perceptronswith multiple hidden neurons and hidden layers. Int. J. Comput. Theory Eng. 3 , 332–337. https://doi.org/10.7763/IJCTE.2011.V3.328 (2011).

Wilson, D. R. & Martinez, T. R. The need for small learning rates on large problems. In IJCNN’01. International Joint Conference on Neural Networks. Proceedings (Cat. No. 01CH37222) , vol. 1, 115–119 (IEEE, 2001).

Ren, C. et al. Optimal parameters selection for bp neural network based on particle swarm optimization: A case study of wind speed forecasting. Knowl. Based Syst. 56 , 226–239 (2014).

Article   ADS   Google Scholar  

De Myttenaere, A., Golden, B., Le Grand, B. & Rossi, F. Mean absolute percentage error for regression models. Neurocomputing 192 , 38–48 (2016).

Willmott, C. J. & Matsuura, K. Advantages of the mean absolute error (mae) over the root mean square error (rmse) in assessing average model performance. Climate Res. 30 , 79–82 (2005).

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All authors contributed to the study conception and design. Y.L. was involved with software, methodology, data collection and preparation, and drafting. Y.W. contributed to programming, visualization. H.L. contributed to writing and editing. G.W. contributed to methodology. J.A. contributed to supervision, reviewing, and validation.

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Liu, Y., Wang, Y., Li, H. et al. An adaptive operation planning and EBO-BPNN optimization method for decision support systems. Sci Rep 14 , 21838 (2024). https://doi.org/10.1038/s41598-024-72808-y

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Impact of concrete durability improvement on building life cycle carbon emissions: a case study of residential buildings in Northwest China

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• Xiangchen Zhu 1 ,
• Zhiyong Liu 2 ,
• Yunsheng Zhang 1 ,
• Hongxia Qiao 1 &
• Qiming Zhou 1  

Building carbon emissions (CE) have become the focus of the current topic, but there is still no mature typical building life cycle theory method from the perspective of building materials, and the research on the relationship between building durability and building life cycle is still insufficient. To this end, this study established a detailed calculation method for building carbon emissions (CE) and divided the building life cycle (BLC) into three stages: manufacturing, use, and demolition according to the result analysis. In addition, a durability improvement and carbon reduction scheme of “partition, resistance, and repair” is proposed, and the carbon emission reduction index of effectiveness index is proposed. The proposed method is applied to the case of residential buildings in Northwest China. The main conclusions are as follows: the CE of residential buildings are more dependent on the use stage. If the centralized heating system is adopted, the CE in the operation stage account for 80–90%. If the air conditioning refrigeration and heating system is adopted, the CE in the operation stage account for about 50%. Using the method of improving the durability of buildings to extend the service life of buildings is very significant for building carbon reduction (RC); the effectiveness index proposed in this paper includes key indicators such as total CE, service life, and building area. Compared with the traditional index, the effectiveness index is more accurate and comprehensive. CR is the focus of green building, but the impact of economy needs to be considered in practical engineering. In the future research, durability, CE, and economy need to be considered comprehensively for careful study.

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Adem A, Nihat A (2015) Life cycle energy (LCEA) and carbon dioxide emissions (LCCO 2 A) assessment of two residential buildings in Gaziantep, Turkey. Energy and Buildings 102:417–431

Article   Google Scholar  

Basheer L, Cleland D (2005) Freeze-thaw resistance of concretes treated with pore liners. Constr Build Mater 20(10):990–998

Bhatia, Pankaj, Cynthia E et al (2011) Greenhouse gas protocol product life cycle accounting and reporting standard

Brühwiler E (2009) Improving safety and durability of civil structures. In: Ibrahimbegovic A, Zlatar M (eds) Damage Assessment and Reconstruction after War or Natural Disaster. Springer Netherlands, p 63–93

Bryan H, FAIA F, Grimm M (2009) Creating a building carbon emission performance standard. In 38th ASES National Solar Conference 2009, SOLAR 2009, pp 1656–1685

Chau C, Leung T, Ng W (2015) A review on life cycle assessment, life cycle energy assessment and life cycle carbon emissions assessment on buildings. Appl Energy 143:395–413

Chen C, Hu D, Wen Q et al (2007) Resource depletion and environmental discharge of cement production in China. J Anhui Agric Sci 28:8986–8989

Google Scholar  

Cuce E, Cuce PM, Wood C et al (2024) Experimental investigation of internal aerogel insulation towards low/zero carbon buildings: a comprehensive thermal analysis for a UK building. Sustain Clean Build 1(1):1–22. https://ojs.wiserpub.com/index.php/scb/article/view/4072 . Accessed 25 Dec 2023

Cui X, Liao C, Li M (2011) Investigation and research on heat collection area of solar water heating system of highrise residential building. Build Technol 42(01):38–42

Dang Y, Xie N, Kessel A et al (2014) Accelerated laboratory evaluation of surface treatments for protecting concrete bridge decks from salt scaling. Constr Build Mater 55:128–135

DIN EN 1504–1–2005 (2005) Products and systems for the protection and repair of concrete structures — definitions, requirements, quality control and evaluation of conformity—part 1: definitions

DIN EN 1504 (2009) Products and systems for the protection and repair of concrete structures. Definitions, requirements, quality control and evaluation of conformity. Structural and non-structural repair. European Standard.

DOE (2021) Emission factors for greenhouse gas inventories, DOE/EIA

Erdem C, Mert C, Emre A et al (2023) Experimental performance assessment of a novel insulation plaster as an energy-efficient retrofit solution for external walls: a key building material towards low/zero carbon buildings. Case Stud Therm Eng 49:103350

Fieldson R, Rai D, Sodagar B (2009) Towards a framework for early estimation of lifecycle carbon footprinting of buildings in the UK. Constr Inf Q 11(2):66–75

Freitag S, Bruce S (2010) The influence of surface treatments on the service lives of concrete bridges. Engineering, Materials Science

GB/T 30559.2–2017 (2017) Energy performance of elevators, escalators and moving walkways - part 2: energy calculation and classification of elevators

GHG Protocol (2011) Product life cycle accounting and reporting standard. An Accounting and Reporting Standard for Cities Version 1.1

GjØrv OE (2015) Durability design of concrete structures in server environments, 2nd edn. CRC Press, China Building Materials Industry Press

Gong Z (2004) A quantitative method to the assessment of the life cycle embodied environmental profile of building materials. Tsinghua University

Gong X, Nie Z, Wang Z et al (2012) Life cycle energy consumption and carbon dioxide emission of residential building designs in Beijing. J Ind Ecol 16(4):576–587

Article   CAS   Google Scholar  

Guggemos A, Horvath A (2005) Comparison of environmental effects of steel- and concrete-framed buildings. J Infrastruct Syst 11(2):93–101

Han J, Zhao C, Wang M et al (2010) CO 2 emission status and emission reduction analysis of China’s cement industry. J Hainan Univ (Nat Sci Ed) 28(03):252–256

Hooton D, Bickley A (2014) Design for durability: the key to improving concrete sustainability. Constr Build Mater 67:422–430

Hu Q (2009) Key indicators of design theory on engineering structures in the whole life-cycle. Zhejiang University

Hung L, FlorinConstantin M, Anna B et al (2023) Life cycle assessment of river sand and aggregates alternatives in concrete. Materials 16(5):2064–2064

Hungerbühler K, Boucher J, Pereira C et al (2021) Life cycle assessment of chemical products and processes. In: Chemical Products and Processes. Springer, Cham. https://doi.org/10.1007/978-3-030-62422-4_5 .

IPCC (1990) Climate change: the IPCC scientific assessment.In: Houghton JT, Jenkins GJ, Ephraunms JJ (eds) Cambridge: Cambridge University Press, pp 67–105

IPCC (2006) 2006 IPCC guidelines for national greenhouse gas inventories, Japan: the Institute for Global Environmental Strategies (IGES)

IPCC (2019) The 2019 Refinement to the 2006 IPCC guidelines for national greenhouse gas inventories. Tokyo, Japan

Jiang Y, Qin Y, Zhu Y (2004) Research on evaluation system of Green Olympic buildings. China Hous Facil 05:9–14

Jin W, Zhao Y (2014) Durability of concrete structures, 2nd edn. Science Press, Beijing

Kargol A, Müller U, Gardei A (2013) Properties and performance of silane: blended cement systems. Mater Struct 46(9):1429–1439

Kikuchi R (2001) Recycling of municipal solid waste for cement production: pilot-scale test for transforming incineration ash of solid waste into cement clinker. Resour Conserv Recycl 31(2):137–147

Levine M, Ürge-Vorsatz D, Blok K et al (2007) Residential and commercial buildings. In: Metz B, Davidson OR, Bosch PR, Dave R and Meyer LA (eds) Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK

Li Y (2022) Green and low-carbon manufacturing technology for cement and concrete. China Building and Construction Press

Li L, Guo S, Zhang Y (2010) The quantitative relationship between cement product varieties, energy consumption and CO 2 emission. Build Mater Dev Orientation 8(01):29–35

Li D, Chen H, Hui C et al (2013) A methodology for estimating the life-cycle carbon efficiency of a residential building. Build Environ 59:448–455

Liu N (2014) Research on carbon emission calculation and emission reduction strategies of building based on life cycle assessment. Shijiazhuang Railway University

Liu J (2023) Research on durability and life prediction of waterborne epoxy coated reinforced concrete underharsh environment. Yantai university

Luo Z (2016) Study on calculation method of building life cycle CO 2 emission and emission reduction strategies. Xi’an University of Architecture and Technology

Luo Z, Yang L, Liu J et al (2011) Research on CO 2 emission calculation method and co 2 reduction strategies of building materials. Build Sci 27(04):1–8. https://doi.org/10.13614/j.cnki.11-1962/tu.2011.04.001

McGettigan E (1990) Application mechanism of silane weatherproofers. Concr Int 12(10):66–68

CAS   Google Scholar  

Mert C, Ayşe P, Erdem C et al (2024) Internal or external thermal superinsulation towards low/zero carbon buildings? A Critical Report. Gazi J Eng Sci: N Pag. https://doi.org/10.30855/gmbd.07050777

National Bureau of Statistics of China (2013) National economy and society developed statistical bulletin 2013. http://www.stats.gov.cn/tjsj/zxfb/201402/t20140224_514970 . Accessed 5 Jan 2024

National Bureau of Statistics of China (2023) China Statistical Yearbook

Ng T (2012) Carbon dioxide reduction in the building life cycle: a critical review. Proc Inst Civ Eng - Eng Sustain 165(ES4):281–292

Ng A, Geoff B (2006) Techniques to combat corrosion of steel in concrete.

Norbert D (2009) 6-Methods of crack repair in concrete structures. Failure, distress and repair of concrete structures. Woodhead Publishing, pp 169–193

Nosouhian F, Mostofinejad D, Hasheminejad H (2016) Concrete durability improvement in a sulfate environment using bacteria. J Mater Civ Eng 28(1):04015064–04015064

Peng C (2016) Calculation of a building’s life cycle carbon emissions based on ecotect and building information modeling. J Clean Prod 112:453–465

Petrova T, Chistyakov E, Makarov Y (2018) Methods of road surface durability improvement. Transp Res Procedia 36:586–590

Radhi H, Sharples S (2013) Global warming implications of facade parameters: a life cycle assessment of residential buildings in Bahrain. Environ Impact Assess Rev 38:99–108

Ramesh T, Prakash R, Shukla K (2010) Life cycle energy analysis of buildings: an overview. Energy Build 42(10):1592–1600

Research Group on China’s Energy Development Strategy and Policy (2004) Research on China’s energy development strategy and policy. Economic Science Press, Beijing, pp 63–66

Rzezniczak A (2010) Durability of repair techniques of fine cracks in concrete. McMaster University

Sandeford P, Bendell G, Mansoor A (2009) Corrosion management strategy for reinforced concrete wharf infrastructure located at the mouth of the Brisbane River. Corros Mater 34:32–37

Serres N, Braymand S, Feugeas F (2006) Environmental evaluation of concrete made from recycled concrete aggregate implementing life cycle assessment. J Build Eng 5:24–33

Su X, Zhang X, Sun Y (2011) A new algorithm for life cycle inventory analysis of reproducible materials. J Tongji Univ (Nat Sci) 39(10):1528–1530+1547

Tait MW, Cheung WM (2016) A comparative cradle-to-gate life cycle assessment of three concrete mix designs. Int J Life Cycle Assess 21:847–860

Tittarelli F, Moriconi G (2008) The effect of silane-based hydrophobic admixture on corrosion of reinforcing steel in concrete. Cem Concr Res 38(11):1354–1357

Ty01–31–2015 (2015) Consumption quota of housing construction and decoration works, Beijing

Wang L (2009) Calculation of CO 2 emissions of cement production enterprises. China Cem 11:21–22

Wang Z, Fan L, Mark H (2011) Life-cycle assessment of CO 2 emissions of buildings. International Conference on Remote Sensing, Environment and Transportation Engineering, pp 438–441

Wu H, Cui S, Wang Z (2006) LCA for cement production in China. China Build Mater Sci Technol 03:50–54

Xu Y (2002) Migrating corrosion inhibitor - a new development of corrosion inhibitors for steel bar in concrete. Kuei Suan Jen Hsueh Pao/ J Chin Ceram Soc 30:94–101

Xu Z, Wu Y, Zhang Z et al (2023) A review on the research progress of LDHs as corrosion inhibitors for reinforced concrete. J Build Eng 70:106303

Yan Y (2011) Research of energy consumption and CO 2 emission of buildings in Zhejiang Province Based on Life Cycle Assessment. Zhejiang University

Yan H, Shen Q, Fan L et al (2010) Greenhouse gas emissions in building construction: a case study of One Peking in Hong Kong. Build Environ 45(4):949–955

Yang P, Li W, Zhao T (2012) Protective effect of surface coatings on concrete. J Silic 40(11):1613–1617

You F, Hu D, Zhang H et al (2011) Carbon emissions in the life cycle of urban building system in China—a case study of residential buildings. Ecol Complex 8(2):201–212

Yu H (2004) Study on high performance concrete in salt lake: durability, mechanism and service life prediction. Southeast University

Zhang T (2018) System based on total life cycle research of low-carbon bridge evaluation. China University of Mining and Technology

Zhang X, Wang F (2015) Life-cycle assessment and control measures for carbon emissions of typical buildings in China. Build Environ 86:89–87

Zhang C, Li W, Fan J et al (2019) Study on durability of concrete structures strengthened by different protective coatings. Concrete 12:165–168

Zhang XC, Liu KH, Zhang ZH (2020) Life cycle carbon emissions of two residential buildings in China: comparison and uncertainty analysis of different assessment methods. J Clean Prod 266:122037

Zhao P, Tong J, Ma J (2004) The research on the system of the building material environment load index and evaluate. Chin Build Mater Sci Technol 13(6):1

Zhu X, Zhang Y, Liu Z et al (2023) Research on carbon emission reduction of manufactured sand concrete based on compressive strength. Constr Build Mater 403. https://doi.org/10.1016/j.conbuildmat.2023.133101 .

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This paper is supported by the National Natural Science Foundation of China (U21A20150, 52178216, 52008196) and the Science and Technology Program of Gansu Province (23JRRA799).

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Zhu, X., Liu, Z., Zhang, Y. et al. Impact of concrete durability improvement on building life cycle carbon emissions: a case study of residential buildings in Northwest China. Environ Sci Pollut Res (2024). https://doi.org/10.1007/s11356-024-34883-6

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Volume 30, Number 10—October 2024

Early Introductions of Candida auris Detected by Wastewater Surveillance, Utah, USA, 2022–2023

Suggested citation for this article

Candida auris is considered a nosocomial pathogen of high concern and is currently spreading across the United States. Infection control measures for C. auris focus mainly on healthcare facilities, yet transmission levels may already be significant in the community before outbreaks are detected in healthcare settings. Wastewater-based epidemiology (culture, quantitative PCR, and whole-genome sequencing) can potentially gauge pathogen transmission in the general population and lead to early detection of C. auris before it is detected in clinical cases. To learn more about the sensitivity and limitations of wastewater-based surveillance, we used wastewater-based methods to detect C. auris in a southern Utah jurisdiction with no known clinical cases before and after the documented transfer of colonized patients from bordering Nevada. Our study illustrates the potential of wastewater-based surveillance for being sufficiently sensitive to detect C. auris transmission during the early stages of introduction into a community.

Candida auris is an antifungal-resistant yeast that leads to high mortality rates among patients with underlying conditions and displays a formidable persistence in healthcare settings because of its biofilm-forming potential and resistance to some commonly used disinfectants ( 1 – 3 ). Circulating strains are classified into 5 genomic clades linked to their geographic area of origin: clade I (southern Asia), clade II (eastern Asia), clade III (Africa), clade IV (South America), and clade V (Iran) ( 4 , 5 ). Since C. auris introduction into the United States was documented in 2013 ( 6 ), prevalence has increased rapidly and the organism has become endemic to many jurisdictions ( 7 ). The strain exerted by the COVID-19 pandemic on infection control practices and public health resources in general is thought to have contributed to C. auris expansion ( 8 ).

Despite the widespread prevalence of C. auris in the United States, its effect on healthcare facilities should be limited, and jurisdictions that have not yet experienced sustained transmission should be protected. In addition to classic infection prevention strategies focused on admission screenings, point prevalence surveys (PPSs), and interfacility communication ( 9 , 10 ), wastewater-based surveillance could help control the spread of emerging pathogens by providing opportunities for early detection and management of outbreak responses ( 11 – 13 ).

We and others have previously shown the feasibility of community-scale wastewater surveillance for C. auris in high disease prevalence settings, specifically Nevada and Florida ( 14 – 16 ). We monitored the influent of the only wastewater treatment plant (WWTP) in St. George, Utah, before and after the transfer of a C. auris –positive patient into that community. On the basis of available epidemiologic information and modeling, we propose that wastewater surveillance could be a sufficiently sensitive strategy for early detection of C. auris , before it is detected in clinical surveillance efforts. In addition, we report improvements to the culture method that we originally used to recover C. auris isolates from wastewater and demonstrate the utility of organism isolation in providing high-quality genomic data for investigations. Our study was performed under Utah Department of Health and Human Services (DHHS) Institutional Review Board protocol no. 651 (“Community and facility level surveillance for multidrug resistant organisms using wastewater samples”).

Materials and Methods

Wastewater sample collection and transport.

Figure 1 . Transfer of Candida auris cases from Nevada to St. George, Utah, USA, and quantitative PCR monitoring of C. auris concentrations at the St. George wastewater treatment plant....

During November 2022–June 2023, we collected 24-hour composite influent wastewater samples from 3 WWTPs in southwestern Utah, near the border with Nevada: St. George (population ≈92,000), Ash Creek (≈25,000), and Cedar City (≈32,000) ( Table 1 ; Figure 1 , panel A). The St. George WWTP served as the primary experimental site, and the Ash Creek and Cedar City WWTPs served as presumptive negative control sites ( Table 1 ). The average flow rate for the St. George WWTP during this study was 12.73 million gallons per day (mgd), which corresponds to 138 gallons per capita per day (gpcd). The per capita wastewater generation rate is similar to the national average of 132 gpcd ( 17 ). Each sample consisted of 250 mL of influent wastewater collected in polypropylene bottles and transported on ice (≈24 hours) to the Utah Public Health Laboratory (UPHL). Subsequently, 150-mL aliquots of each sample were shipped on ice with an overnight priority service (≈24 hours) to the Southern Nevada Water Authority laboratory.

Quantitative Real-Time PCR Monitoring and Performance Characteristics

To perform wastewater surveillance of C. auris , the Southern Nevada Water Authority used quantitative PCR (qPCR) as previously described ( 15 ). In the earlier study, the statistical limit of quantification was determined to be a quantification cycle (Cq) of 33.03 ( 15 ), which equated to an average of 7 gene copies (gc) across all study-specific standard curves, and the theoretical limit of detection was assumed to correspond to 1 gc. Across 18 samples in our study, the average equivalent sample volume (ESV) for each qPCR reaction was 1.07 ± 0.81 mL of influent wastewater, yielding an average limit of detection of 2.97 log 10 gc/L. Limits of quantification ranged from 3.95 to 4.47 log 10 gc/L based on variability in run-specific standard curves and an assumed average ESV of 1.07 mL ( Appendix ).

C. auris Isolation by Culture of Filter-Based Concentration

We vacuum filtered < 50 mL of influent wastewater through 0.45-μm cellulose nitrate analytical filters (ThermoFisher Scientific, https://www.thermofisher.com ). We removed the filters from the vacuum unit by using forceps, placed the filters in a 50-mL conical tube, and submerged them in 12 ml of Salt Sabouraud Dulcitol Broth ( 2 ) (Thomas Scientific, https://www.thomassci.com ) supplemented with 32 μg/mL fluconazole ( 14 ). The submerged filters were incubated at 42°C for up to 5 days with vigorous agitation at 250 rpm. We performed plating of the broth after incubation on chromogenic media and species identification of presumptive colonies as previously described ( 14 ).

Whole-Genome Sequencing and Bioinformatics

We sequenced C. auris genomes by using a NextSeq platform (Illumina, https://www.illumina.com ). We performed single-nucleotide polymorphism (SNP) distance analyses by using the MycoSNP pipeline ( 18 ), as previously described ( 14 ).

Monte Carlo Modeling

We created a model to assess the theoretical sensitivity of the wastewater qPCR method for detecting C. auris from 1 shedding person in the sewershed. The model predicts the concentration of C. auris in wastewater (in gc/L) from 1 shedder ( Table 2 ). We performed a Monte Carlo simulation by using 10,000 random samplings of the parameter distributions to characterize the distribution of possible C. auris concentrations with 1 C. auris shedder contributing urine and feces to the wastewater ( Appendix ).

Epidemiology Data and Infection Control Practices

C. auris reporting and submission of isolates or residual primary specimens is regulated by the Utah Communicable Disease Rule R386-702. The Utah DHHS uses EpiTrax as the centralized reportable disease database ( 25 ). Reports are filed electronically or via manual entry after notification to Utah DHHS by fax. Federal regulations recommend transfer notifications of patients colonized or infected with C. auris ; however, compliance is seldom enforced, and effective interfacility communication relies on good infection prevention stewardship.

PPSs were conducted via composite axilla/groin swabbing ( 26 ) with nylon swabs, and samples were transported in liquid Amies (Eswab system; Copan, https://www.copanusa.com ). We processed 200 μL of Amies media by using the on-board extraction PCR system BDMax (Becton, Dickinson and Company, https://www.bd.com ) ( 27 ).

Introduction of C. auris into St. George

In November 2022, the Utah DHHS was notified about the upcoming transfer of a patient with an active C. auris infection from Nevada to St. George, Utah (patient 1). Before patient 1 was transferred, no C. auris case or colonized person had been recorded in Utah. On November 10, 2022, patient 1 was transferred from an acute-care hospital (ACH A) in Nevada to a skilled nursing facility (SNF A) in St. George ( Figure 1 , panels B, C). Patient 1 was highly debilitated and while in St. George had a C. auris –positive urine culture (>10 5 CFU/mL); the patient died after the transfer (December 2022) ( Figure 1 , panel C). No additional colonized persons were discovered at SNF A through a PPS evaluating 40 persons.

In March 2023, Utah DHHS was notified about the transfer of a second C. auris –colonized person from Nevada (patient 2). Patient 2 had been hospitalized in a different acute-care hospital in Nevada (ACH B) and was admitted to SNF A in St. George on March 23, 2023; the patient remained there for the duration of our wastewater surveillance study ( Figure 1 , panels B, C).

We discovered a third patient from Nevada (patient 3) retrospectively. Patient 3 previously resided at ACH B in Nevada (similar to patient 2) but was not found to be colonized with C. auris before being transferred to St. George in December 2022 ( Figure 1 , panels B, C). Because of the risk factor associated with patient 3 being transferred from a healthcare facility with an ongoing outbreak (i.e., ACH B in Nevada), the acute-care hospital in St. George (ACH C) ordered an admission screening, which led to confirmation of C. auris colonization on December 28, 2022 ( Figure 1 , panels B, C). The colonization status of patient 3 was communicated via fax to the Utah DHHS according to Utah communicable diseases rules; however, the alert was overlooked because of human error. After 2 days at ACH C, patient 3 was discharged and continued to receive dialysis in an outpatient setting in St. George until June 2023, albeit by commuting between his residence in Nevada and St. George ( Figure 1 , panel C).

Collectively, the 3 patient transfers potentially resulted in nearly continuous shedding of C. auris into St. George wastewater during November 2022–June 2023, which coincided with the duration of our wastewater surveillance study. Moreover, patients 2 and 3 simultaneously resided or spent a substantial amount of time in St. George during March–June 2023 ( Figure 1 , panel C), potentially increasing C. auris loading in local wastewater.

Detection of C. auris in St. George Wastewater

After being notified of the pending transfer of patient 1 to St. George, we identified a unique opportunity to assess the sensitivity of wastewater surveillance for the early detection of C. auris . On November 8, 2022 (2 days before the transfer), we initiated qPCR-based wastewater surveillance at the St. George WWTP ( Figure 1 , panel C), which continued at irregular intervals until June 13, 2023 ( Table 1 ; Figure 1 , panel C). C. auris was not detected (i.e., below the limit of detection) in the first 2 samples collected for the study (November 8 and 15), which straddled the transfer date of patient 1 ( Table 1 ; Figure 1 , panel C). However, C. auris was detected, albeit below the limit of quantification, in a sample collected on November 29 and was detected in every sample thereafter ( Table 1 ; Figure 1 , panel C). Before March 2023, only 2 of 7 samples were above the limit of quantification, but starting in April 2023, when patients 2 and 3 were potentially contributing to the St. George WWTP, all samples were above the limit of quantification ( Table 1 ; Figure 1 , panel C).

To assess potential transmission in areas near St. George, we also analyzed 4 influent wastewater samples from WWTPs in Ash Creek and Cedar City ( Figure 1 , panel A). C. auris was not detected in those presumptive negative control samples ( Table 1 ).

Modeled Sensitivity of qPCR-based, Community-Scale Wastewater Surveillance

Given the available epidemiologic data and the fact that C. auris was not detected in the sample collected before the initial transfer of patient 1, the subsequent C. auris –positive wastewater could represent detection of its initial introduction in St. George. If true, that finding indicates that qPCR-based wastewater surveillance may be sufficiently sensitive to detect a single C. auris shedder in a sewershed serving ≈100,000 inhabitants.

To gauge the plausibility of that statement, we used a Monte Carlo simulation model previously used for SARS-CoV-2 but adapted to C. auris ( 28 ). The model considers the following parameters: C. auris concentration ranges for urine and feces (based on a neutropenic mouse model and quantitative analyses of urine clinical cultures [ 19 , 22 ]); urine and feces production rates in healthy humans ( 20 , 21 , 23 ); variable gc numbers of the qPCR target (internal transcribed spacer 2) across C. auris strains (based on a nucleotide BLAST analysis in which the sequence of the qPCR probe was searched in various C. auris genomes, as well as the number of rRNA genes reported in C. albicans as an upper hypothetical value [ 24 , 29 , 30 ]); and average daily wastewater flow rate ( Table 2 ).

The primary site of C. auris colonization is skin ( 31 ), and routine hygiene practices (e.g., handwashing, showering, laundering) should also represent a major route for release of organisms into the sewer system. However, we did not incorporate that shedding mode in our model because it would entail assumptions with considerable uncertainty (e.g., affected water volumes, affected skin surface area, skin mobilization rate, frequency of handwashing/showering/laundering).

• Figure 2 . Monte Carlo simulation model forecasting Candida auris concentrations as a function of variable shedding levels in urine and feces, organism gene copy numbers, and wastewater treatment plant flow rate...

Our model indicates that 97% of the predicted C. auris wastewater concentrations resulting from 1 person shedding the pathogen in urine and feces were above the average limit of detection for our study (2.97 log 10 gc/L; assumes a limit of 1 gc and the average of all sample-specific ESVs for our study) ( Figure 2 , panels A, B). The median predicted concentration from the Monte Carlo simulation was 3.90 log 10 gc/L, a value greater than the upper limit of observed limits of detection (i.e., 3.60 log 10 gc/L; assumes a limit of 1 gc and the average of all sample-specific ESVs for our study) ( Figure 2 , panel A). The upper-bound probability of detection increases to 99.9% when the lowest limit of detection is considered ( Figure 2 , panel B). If shedding is modeled through either urine or feces alone, the probability of detection decreases to ≈85% when the average limit of detection is considered ( Figure 2 , panel B).

To determine the effect of each stochastic parameter on the final predicted wastewater concentrations, we used the Spearman correlation coefficient to perform a sensitivity analysis on the Monte Carlo model ( 28 ) ( Figure 2 , panel C). The parameter with the strongest correlation was the number of genome copies per CFU, followed by the rate of C. auris shedding in urine (and to a slightly lesser extent, feces). The flow rate had a moderate negative correlation, indicating that an increased flow rate results in a decreased probability of detection in wastewater from 1 shedder. To better illustrate this effect, we generated probability plots for 3 hypothetical WWTP flow rates: 1, 10, and 100 mgd. Assuming the St. George per capita wastewater generation rate of 138 gpcd, those flow rates represent C. auris infection prevalences of 1 in 7,200 (flow rate 1 mgd), 1 in 72,000 (flow rate 2 mgd), and 1 in 720,000 (flow rate 100 mgd) persons. At the average limit of detection, the detection probability relative to a single shedder was almost 100% at a flow rate of 1 mgd, ≈97.5% at 10 mgd, and 50% at 100 mgd ( Figure 2 , panel D). Altogether, our modeled and observed results support the hypothesis that use of qPCR-based wastewater surveillance for C. auris can achieve sensitivity on the order of 1 in 100,000.

Isolation of C. auris from the St. George Sewershed and Genetic Relatedness to Clinical Isolates

• Figure 3 . Neighbor-joining phylogenetic tree including clade III Candida auris isolates recovered from the St. George, Utah, USA, wastewater treatment plant on 2 collection dates (March 28 and April 4, 2023)...

We complemented qPCR-based wastewater surveillance with culturing and subsequent whole-gene sequencing of recovered isolates. Initial attempts with the centrifugation-based method previously used for southern Nevada wastewater ( 14 ) were unsuccessful ( Table 1 ). As such, we explored a filtration-based alternative that was observed to be superior to our original method across 2 split samples from Nevada ( Appendix Figure 1). Using that improved method, we were able to recover 15 C. auris isolates from 2 samples consecutively collected on March 28, 2023, and April 4, 2023 ( Table 1 ). All wastewater isolates belonged to clade III and segregated topologically into 2 individual subgroups distinctly separated by collection date ( Figure 3 ). Isolates within the subgroup linked to the March 28 wastewater sample were highly related to the clinical isolate available for patient 2 (0–6 SNPs), who was transferred to St. George on March 23. The isolates within the subgroup linked to the April 4 sample displayed ≈12 SNP differences from the patient 2 isolate ( Figure 3 ). Unfortunately, no clinical whole-genome sequencing (WGS) data were available for patient 3 because the patient’s colonization status was not determined in Nevada and the positive clinical sample collected in Utah was not submitted to UPHL. Patient 1 was infected with a clade I strain, but we were unable to culture C. auris in any wastewater samples collected during the time of the patient’s stay at SNF A or before March 28, 2023 ( Table 1 ). As such, we were unable to study the contribution of clade I isolates to the overall C. auris signal in the St. George sewershed.

The recent history of C. auris in the United States highlighted the challenges in controlling the pathogen after it becomes established in an area ( 7 ). Early detection strategies coupled with aggressive infection control measures could reduce its effect on healthcare facilities and the general population. In that respect, wastewater-based surveillance is a promising tool for detecting pathogens that are circulating in the population at very low prevalence and have not been overtly manifested at the clinical level ( 12 ).

The application of wastewater-based surveillance to the C. auris problem is in its infancy ( 14 – 16 ), so fundamental parameters that will guide its use have not yet been studied in detail. For example, levels of C. auris shedding in human excreta and body site densities during colonization have not yet been adequately characterized. C. auris effectively colonizes skin and nares ( 26 , 31 ) but is not typically recovered from the buccal mucosa ( 31 , 32 ). A regular nylon swab can usually recover 10 2 –10 10 CFU of C. auris from various skin sites (e.g., palms/fingertips, toe web, perianal skin, axilla, inguinal crease, neck) and nares ( 31 ). As such, it is conceivable that the organism could be released in great numbers into the sewershed via skin shedding during routine hygiene practices or even when laundering items that have been in contact with a colonized person. Because skin is the primary C. auris colonization site, clinical studies aimed at determining the actual bioburden released through hygiene practices ( 33 ) will be essential for assessing quantitative measurements in wastewater. C. auris is also commonly recovered from urine ( 4 , 26 ) of patients with candiduria ( 34 ), as well as from asymptomatic persons ( 35 ). C. auris is less frequently recovered from fecal samples but has been recovered via rectal swabbing ( 26 , 32 , 36 ). Of note, a correlation between gut colonization and urinary tract infections has been observed in cohorts of patients affected by C. auris ( 36 ).

As has been accomplished for wastewater-based surveillance of SARS-CoV-2, additional modeling and parameterization are needed to fully characterize relationships between incidence/prevalence and expected wastewater concentrations ( 28 , 37 ). Early attempts to establish those correlations for C. auris have been extremely challenging ( 16 ). Nevertheless, the qPCR data and the excreta-only model used in our study fit very well with the clinical course of patient 1 (the putative introduction event in St. George) and indicate that detecting 1 C. auris shedder to a community-scale wastewater system of moderate size is plausible ( Figure 2 ). Although our study focused on early detection of pathogen introduction, future studies should consider monitoring wastewater C. auris loads after the population presumably returns to a zero-infection status.

Recovery of C. auris in culture has been instrumental in obtaining isolates for molecular epidemiology analyses by WGS ( 14 ). The incorporation of WGS into wastewater-based surveillance systems for C. auris should be universally adopted to understand the origin of introduction events as well as the evolving diversity of contributions to sewersheds. Motivated by the initial inability to recover C. auris isolates in St. George ( Table 1 ), we worked at improving our original culture method by changing the sample concentration step from centrifugation to membrane filtration ( Appendix Figure 1), an approach also recently used by Babler et al. ( 16 ). Yet, culture from wastewater samples remains a highly variable endeavor, possibly because of variable competition from other species of fungi or fluctuations in environmental factors within the sewer environment affecting the growth of C. auris , such as dissolved oxygen concentration ( 38 , 39 ). In addition, our broth enrichment approach remains unsuitable for isolating fluconazole-susceptible isolates ( 14 ).

WGS analysis indicated a close relationship between C. auris wastewater isolates and 1 isolate from patient 2 ( Figure 3 ). When those wastewater samples were collected, both patients 2 and 3 were potentially contributing C. auris to the St. George WWTP ( Figure 1 , panel C). With the data available, we cannot discriminate whether the genetic diversity of the wastewater isolates collected on 2 separate dates encompasses shedding from patient 3 or other unidentified colonized persons. Moreover, mixed colonization consisting of clones separated by SNP distances greater than those displayed in Figure 3 is not unusual ( 40 , 41 ) and represents another layer of complexity in the interpretation of molecular epidemiology analyses for C. auris ( 42 ). However, incorporating WGS analyses into C. auris wastewater surveillance would still be invaluable for detecting contributions from strains belonging to different clades or displaying very large SNP distances. In addition, if C. auris strains can persist in sewer pipes as biofilm (a phenomenon not yet investigated for this organism) ( 38 ), WGS could potentially distinguish persistent signals from a new shedding event.

In conclusion, we used a holistic approach to C. auris wastewater-based surveillance that entailed using qPCR as the main testing method as well as culture and WGS to better characterize the source of the molecular signals. After being proven effective, metagenomic approaches could potentially bypass the need for culture ( 43 ). We believe that our case study illustrates the potential of wastewater-based surveillance to be a sufficiently sensitive method for discovering C. auris transmission at early stages of introduction into a community.

Mr. Chavez is an ORISE (Oak Ridge Institute for Science and Education) Fellow at CDC. His research expertise encompasses environmental microbiology, wastewater surveillance, and mycotic diseases.

Acknowledgments

We thank Andrew Gorzalski for sharing clinical isolates sequences. We are grateful for the support and contributions of many groups: the Healthcare-associated Infections and Antimicrobial Resistance team at Utah DHHS and the Antimicrobial Resistance Laboratory Network, NGS, and wastewater testing teams at UPHL.

J.C. was supported by an Association of Public Health Laboratories Fellowship in Antibiotic Resistance (Cooperative Agreement no. NU60OE000104, funded by the Centers for Disease Control and Prevention [CDC] through the Association of Public Health Laboratories). Southern Nevada wastewater sample collection was supported by CDC grant NH75OT000057-01-00.

• Lone  SA , Ahmad  A . Candida auris -the growing menace to global health. Mycoses . 2019 ; 62 : 620 – 37 . DOI PubMed Google Scholar
• Welsh  RM , Bentz  ML , Shams  A , Houston  H , Lyons  A , Rose  LJ , et al. Survival, persistence, and isolation of the emerging multidrug-resistant pathogenic yeast Candida auris on a plastic health care surface. J Clin Microbiol . 2017 ; 55 : 2996 – 3005 . DOI PubMed Google Scholar
• Ku  TSN , Walraven  CJ , Lee  SA . Candida auris : disinfectants and implications for infection control. Front Microbiol . 2018 ; 9 : 726 . DOI PubMed Google Scholar
• Lockhart  SR , Etienne  KA , Vallabhaneni  S , Farooqi  J , Chowdhary  A , Govender  NP , et al. Simultaneous emergence of multidrug-resistant Candida auris on 3 continents confirmed by whole-genome sequencing and epidemiological analyses. Clin Infect Dis . 2017 ; 64 : 134 – 40 . DOI PubMed Google Scholar
• Chow  NA , de Groot  T , Badali  H , Abastabar  M , Chiller  TM , Meis  JF . Potential fifth clade of Candida auris , Iran, 2018. Emerg Infect Dis . 2019 ; 25 : 1780 – 1 . DOI PubMed Google Scholar
• Vallabhaneni  S , Kallen  A , Tsay  S , Chow  N , Welsh  R , Kerins  J , et al. ; MSD . MSD. Investigation of the first seven reported cases of Candida auris , a globally emerging invasive, multidrug-resistant fungus—United States, May 2013–August 2016. MMWR Morb Mortal Wkly Rep . 2016 ; 65 : 1234 – 7 . DOI PubMed Google Scholar
• Lyman  M , Forsberg  K , Sexton  DJ , Chow  NA , Lockhart  SR , Jackson  BR , et al. Worsening spread of Candida auris in the United States, 2019 to 2021. Ann Intern Med . 2023 ; 176 : 489 – 95 . DOI PubMed Google Scholar
• Thoma  R , Seneghini  M , Seiffert  SN , Vuichard Gysin  D , Scanferla  G , Haller  S , et al. The challenge of preventing and containing outbreaks of multidrug-resistant organisms and Candida auris during the coronavirus disease 2019 pandemic: report of a carbapenem-resistant Acinetobacter baumannii outbreak and a systematic review of the literature. Antimicrob Resist Infect Control . 2022 ; 11 : 12 . DOI PubMed Google Scholar
• Saleem  Z , Godman  B , Hassali  MA , Hashmi  FK , Azhar  F , Rehman  IU . Point prevalence surveys of health-care-associated infections: a systematic review. Pathog Glob Health . 2019 ; 113 : 191 – 205 . DOI PubMed Google Scholar
• Wang  TZ , White  KN , Scarr  JV , Simon  MS , Calfee  DP . Preparing your healthcare facility for the new fungus among us: An infection preventionist’s guide to Candida auris. Am J Infect Control . 2020 ; 48 : 825 – 7 . DOI PubMed Google Scholar
• Vo  V , Tillett  RL , Papp  K , Shen  S , Gu  R , Gorzalski  A , et al. Use of wastewater surveillance for early detection of Alpha and Epsilon SARS-CoV-2 variants of concern and estimation of overall COVID-19 infection burden. Sci Total Environ . 2022 ; 835 : 155410 . DOI PubMed Google Scholar
• Gupta  P , Liao  S , Ezekiel  M , Novak  N , Rossi  A , LaCross  N , et al. Wastewater genomic surveillance captures early detection of omicron in Utah. Microbiol Spectr . 2023 ; 11 : e0039123 . DOI PubMed Google Scholar
• Ryerson  AB , Lang  D , Alazawi  MA , Neyra  M , Hill  DT , St George  K , et al. ; 2022 U.S. Poliovirus Response Team . 2022 U.S. Poliovirus Response Team. Wastewater testing and detection of poliovirus type 2 genetically linked to virus isolated from a paralytic polio case—New York, March 9–October 11, 2022. MMWR Morb Mortal Wkly Rep . 2022 ; 71 : 1418 – 24 . DOI PubMed Google Scholar
• Rossi  A , Chavez  J , Iverson  T , Hergert  J , Oakeson  K , LaCross  N , et al. Candida auris discovery through community wastewater surveillance during healthcare outbreak, Nevada, USA, 2022. Emerg Infect Dis . 2023 ; 29 : 422 – 5 . DOI PubMed Google Scholar
• Barber  C , Crank  K , Papp  K , Innes  GK , Schmitz  BW , Chavez  J , et al. Community-scale wastewater surveillance of Candida auris during an ongoing outbreak in southern Nevada. Environ Sci Technol . 2023 ; 57 : 1755 – 63 . DOI PubMed Google Scholar
• Babler  K , Sharkey  M , Arenas  S , Amirali  A , Beaver  C , Comerford  S , et al. Detection of the clinically persistent, pathogenic yeast spp. Candida auris from hospital and municipal wastewater in Miami-Dade County, Florida. Sci Total Environ . 2023 ; 898 : 165459 . DOI PubMed Google Scholar
• Chini  CMS , Stillwell  AS . The state of U.S. urban water: data and the energy-water nexus. Water Resour Res . 2018 ; 54 : 1796 – 811 . DOI Google Scholar
• Bagal  UR , Phan  J , Welsh  RM , Misas  E , Wagner  D , Gade  L , et al. MycoSNP: A portable workflow for performing whole-genome sequencing analysis of Candida auris. Methods Mol Biol . 2022 ; 2517 : 215 – 28 . DOI PubMed Google Scholar
• Torres  SR , Pichowicz  A , Torres-Velez  F , Song  R , Singh  N , Lasek-Nesselquist  E , et al. Impact of Candida auris infection in a neutropenic murine model. Antimicrob Agents Chemother . 2020 ; 64 : e01625 – 19 . DOI PubMed Google Scholar
• Rose  C , Parker  A , Jefferson  B , Cartmell  E . The characterization of feces and urine: a review of the literature to inform advanced treatment technology. Crit Rev Environ Sci Technol . 2015 ; 45 : 1827 – 79 . DOI PubMed Google Scholar
• Penn  R , Ward  BJ , Strande  L , Maurer  M . Review of synthetic human faeces and faecal sludge for sanitation and wastewater research. Water Res . 2018 ; 132 : 222 – 40 . DOI PubMed Google Scholar
• Croxatto  A , Dijkstra  K , Prod’hom  G , Greub  G . Comparison of inoculation with the InoqulA and WASP automated systems with manual inoculation. J Clin Microbiol . 2015 ; 53 : 2298 – 307 . DOI PubMed Google Scholar
• Rauch  W , Brockmann  D , Peters  I , Larsen  TA , Gujer  W . Combining urine separation with waste design: an analysis using a stochastic model for urine production. Water Res . 2003 ; 37 : 681 – 9 . DOI PubMed Google Scholar
• Jones  T , Federspiel  NA , Chibana  H , Dungan  J , Kalman  S , Magee  BB , et al. The diploid genome sequence of Candida albicans. Proc Natl Acad Sci U S A . 2004 ; 101 : 7329 – 34 . DOI PubMed Google Scholar
• Whipple  A , Jackson  J , Ridderhoff  J , Nakashima  AK . Piloting electronic case reporting for improved surveillance of sexually transmitted diseases in Utah. Online J Public Health Inform . 2019 ; 11 : e7 . DOI PubMed Google Scholar
• Zhu  Y , O’Brien  B , Leach  L , Clarke  A , Bates  M , Adams  E , et al. Laboratory analysis of an outbreak of Candida auris in New York from 2016 to 2018: impact and lessons learned. J Clin Microbiol . 2020 ; 58 : e01503 – 19 . DOI PubMed Google Scholar
• Leach  L , Russell  A , Zhu  Y , Chaturvedi  S , Chaturvedi  V . A rapid and automated sample-to-result Candida auris real-time PCR assay for high-throughput testing of surveillance samples with the BD Max Open System. J Clin Microbiol . 2019 ; 57 : e00630 – 19 . DOI PubMed Google Scholar
• Crank  K , Chen  W , Bivins  A , Lowry  S , Bibby  K . Contribution of SARS-CoV-2 RNA shedding routes to RNA loads in wastewater. Sci Total Environ . 2022 ; 806 : 150376 . DOI PubMed Google Scholar
• Altschul  SF , Gish  W , Miller  W , Myers  EW , Lipman  DJ . Basic local alignment search tool. J Mol Biol . 1990 ; 215 : 403 – 10 . DOI PubMed Google Scholar
• Leach  L , Zhu  Y , Chaturvedi  S . Development and validation of a real-time PCR assay for rapid detection of Candida auris from surveillance samples. J Clin Microbiol . 2018 ; 56 : e01223 – 17 . DOI PubMed Google Scholar
• Proctor  DM , Dangana  T , Sexton  DJ , Fukuda  C , Yelin  RD , Stanley  M , et al. ; NISC Comparative Sequencing Program . Integrated genomic, epidemiologic investigation of Candida auris skin colonization in a skilled nursing facility. Nat Med . 2021 ; 27 : 1401 – 9 . DOI PubMed Google Scholar
• Du  H , Bing  J , Hu  T , Ennis  CL , Nobile  CJ , Huang  G . Candida auris : Epidemiology, biology, antifungal resistance, and virulence. PLoS Pathog . 2020 ; 16 : e1008921 . DOI PubMed Google Scholar
• Plano  LR , Garza  AC , Shibata  T , Elmir  SM , Kish  J , Sinigalliano  CD , et al. Shedding of Staphylococcus aureus and methicillin-resistant Staphylococcus aureus from adult and pediatric bathers in marine waters. BMC Microbiol . 2011 ; 11 : 5 . DOI PubMed Google Scholar
• Griffith  N , Danziger  L . Candida auris urinary tract infections and possible treatment. Antibiotics (Basel) . 2020 ; 9 : 898 . DOI PubMed Google Scholar
• Sayeed  MA , Farooqi  J , Jabeen  K , Awan  S , Mahmood  SF . Clinical spectrum and factors impacting outcome of Candida auris : a single center study from Pakistan. BMC Infect Dis . 2019 ; 19 : 384 . DOI PubMed Google Scholar
• Piatti  G , Sartini  M , Cusato  C , Schito  AM . Colonization by Candida auris in critically ill patients: role of cutaneous and rectal localization during an outbreak. J Hosp Infect . 2022 ; 120 : 85 – 9 . DOI PubMed Google Scholar
• Gerrity  D , Papp  K , Stoker  M , Sims  A , Frehner  W . Early-pandemic wastewater surveillance of SARS-CoV-2 in Southern Nevada: Methodology, occurrence, and incidence/prevalence considerations. Water Res X . 2021 ; 10 : 100086 . DOI PubMed Google Scholar
• McLellan  SL , Roguet  A . The unexpected habitat in sewer pipes for the propagation of microbial communities and their imprint on urban waters. Curr Opin Biotechnol . 2019 ; 57 : 34 – 41 . DOI PubMed Google Scholar
• Day  AM , McNiff  MM , da Silva Dantas  A , Gow  NAR , Quinn  J . Hog1 regulates stress tolerance and virulence in the emerging fungal pathogen Candida auris. mSphere . 2018 ; 3 : e00506 – 18 . DOI PubMed Google Scholar
• Eyre  DW , Sheppard  AE , Madder  H , Moir  I , Moroney  R , Quan  TP , et al. A Candida auris outbreak and its control in an intensive care setting. N Engl J Med . 2018 ; 379 : 1322 – 31 . DOI PubMed Google Scholar
• Roberts  SC , Zembower  TR , Ozer  EA , Qi  C . Genetic evaluation of nosocomial Candida auris transmission. J Clin Microbiol . 2021 ; 59 : e02252 – 20 . DOI PubMed Google Scholar
• Chow  NA , Gade  L , Tsay  SV , Forsberg  K , Greenko  JA , Southwick  KL , et al. ; US Candida auris Investigation Team . Multiple introductions and subsequent transmission of multidrug-resistant Candida auris in the USA: a molecular epidemiological survey. Lancet Infect Dis . 2018 ; 18 : 1377 – 84 . DOI PubMed Google Scholar
• Huang  X , Welsh  RM , Deming  C , Proctor  DM , Thomas  PJ , Gussin  GM , et al. ; NISC Comparative Sequencing Program . Skin metagenomic sequence analysis of early Candida auris outbreaks in U.S. nursing homes. mSphere . 2021 ; 6 : e0028721 . DOI PubMed Google Scholar
• Figure 1 . Transfer of Candida auris cases from Nevada to St. George, Utah, USA, and quantitative PCR monitoring of C. auris concentrations at the St. George wastewater treatment plant. A) Utah...
• Table 1 . Candida auris qPCR and culture results from St. George, Ash Creek, and Cedar City, Utah, USA, 2022–2023
• Table 2 . Candida auris shedding model parameters and distributions

Suggested citation for this article : Chavez J, Crank K, Barber C, Gerrity D, Iverson T, Mongillo J, et al. Early introductions of Candida auris detected by wastewater surveillance, Utah, USA, 2022–2023. Emerg Infect Dis. 2024 Oct [ date cited ]. https://doi.org/10.3201/eid3010.240173

DOI: 10.3201/eid3010.240173

Original Publication Date: September 17, 2024

1 These first authors contributed equally to this article.

2 Current affiliation: Center for Disease Control and Prevention, Atlanta, Georgia, USA.

3 Current affiliation: North Carolina Department of Health and Human Services, Wilmington, North Carolina, USA.

Table of Contents – Volume 30, Number 10—October 2024

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Alessandro Rossi, Utah Public Health Laboratory, 4431 S 2700 West, Taylorsville, UT 84129, USA

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