what is the purpose of study in research

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Purpose of the Study: Common Errors in Writing Your Purpose Statement

The Purpose of the Study is perhaps the single most important sentence in your dissertation. In conjunction with the Problem Statement, it guides the focus of your research. Your research questions, methodology, and data analysis are all guided by the purpose of the study.

The “Purpose of the Study” section consists of a few short paragraphs describing, aptly, the purpose of your study. Within this section is the “Purpose Statement,” which is a single sentence.

It’s the distillation of your study’s purpose, and that particular sentence will show up again and again in your paper. It generally includes (a) the research paradigm, (b) the intent of the study (such as describe, develop, explore, etc.), and (c) the phenomenon of interest.

It’s also a sentence that many students struggle with, and find themselves revising multiple times before it’s finally accepted. My goal here is to give you all the information you need to create a stellar purpose statement the first time around.

Purpose of the Study in a Single Sentence

Your purpose statement distills the purpose of your study into a single sentence. It indicates the study’s method and overarching goal. This sentence is contained in the “Purpose of the Study” section. It should be a logical, explicit research response to the stated problem (more on that later). 

Elements of the Purpose Statement: 

Include the following elements in your purpose statement:

• Identify the research method (qualitative, quantitative, or mixed-method. Usually this is as simple as saying, “the purpose of this qualitative study is…”).
• The stated purpose reflects the research questions (make sure to identify variables/constructs and the central phenomenon/concept/idea).
• Clearly state the research design.
• Ensure the purpose (as well as the method/design) is aligned with the problem statement.  
• Identify participants or other data sources. 
• Identify the geographic location of study (when relevant).

Purpose of the Study Template

For Qualitative Studies

The purpose of this quantitative study is to ___[describe, compare, explore, or develop] ____ [describe the study goal that directly reflects and encompasses the research questions] in [describe the population or data source and geographic location]. [Brief overview of how, with what instruments/data, with whom, and where]

For Quantitative Studies:

The purpose of this quantitative study is to ___[describe, compare, correlate, explore, or develop] ____ [describe the study goal that directly reflects and encompasses the research questions] in [describe the population or data source and geographic location]. [State the independent, dependent, and covariate variables]. [Brief overview of how, with what instruments/data, with whom, and where]

How Long Should the Purpose of the Study Section Be?

Speaking with a Dissertation Chair about the Purpose of the Study section, he said simply, “Don’t make it too long. State the purpose and go onto something else.” That’s good advice. 

Treat dissertation sections like testifying in court (anything you say can and will be used against you by your committee). If you’re asked, “Do you know what time it is?” the correct answer is “yes” or “no,” not “Oh yes, it’s 11:30 and I have a meeting with Charlie in half an hour.” 

Similarly, in the Statement of the Purpose section, just give the purpose, whatever is required by your university’s template, and not much else. This can be accomplished within a few pages at most.

Aligning the Purpose of the Study With the Rest of Your Paper

Keeping your paper in alignment is an extraordinarily important part of writing your dissertation. What this means is that your Problem Statement, Purpose Statement, and Research Questions all say essentially the same thing (just with different wording).

Aligning the Purpose Statement with the Problem Statement

Your problem statement should have two parts–a General Problem and a Specific Problem. The general problem is an overarching view of the problem you’re looking to address–this is what you would tell a curious person asking what you’re studying. The Specific Problem is always a gap in research. “The specific problem is that ___ is not known.”

The language that you use to fill in the blank is the same language you should use for the purpose statement. 

Problem : “The problem is that x isn’t known”

Purpose : “The purpose is to find x out”

• The problem is that we don’t know what factors influence parent involvement in schools.
• The purpose is to determine the factors that determine parent involvement in schools.
• The problem is that we don’t know the impact of Covid-19 unemployment on stock prices.
• The purpose is to determine the impact of Covid-19 unemployment on stock prices.

The professor I interviewed said, “Your committee wants to see you being consistent. ‘My problem is x. My purpose is to explore the problem.’ Period. Don’t have more than one purpose, and don’t stray from your problem statement.”

Aligning the Purpose Statement with the Research Questions

The research questions should arise directly from the purpose statement. For example:

What factors do parents report impact their involvement in schools?

To what degree is there a significant relationship between Covid-19 unemployment and stock prices?

There could be additional research questions for each of these studies, but you get the idea: ensure that your research question arises from the purpose statement and the purpose statement arises from the problem statement.  These steps create the foundation of your study, and doing it this way will ensure there is alignment.

Mistakes People Make When Writing Their Purpose Statement

• Writing the purpose statement apart from their problem statement, so the purpose doesn’t directly relate to the problem.
• Trying to take on too much in one study — too big a problem to study while you’re paying tuition. (Save those larger studies for when you’re being paid.)
• Trying to be creative with wording and thereby veering away from the problem statement.
• Creating multiple purpose statements. 

In short, you’re trying to find information that will help your field better understand a problem that’s important to you. Your job in your dissertation is to address the problem, and your purpose statement will tell us that.

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Nicholas Tippins

Nicholas Tippins is the Founder & Executive Director of My Dissertation Editor. He has edited more dissertations than he can count. When not managing his business, he can be found playing the guitar or wandering around in the woods.

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11.1 The Purpose of Research Writing

Learning objectives.

• Identify reasons to research writing projects.
• Outline the steps of the research writing process.

Why was the Great Wall of China built? What have scientists learned about the possibility of life on Mars? What roles did women play in the American Revolution? How does the human brain create, store, and retrieve memories? Who invented the game of football, and how has it changed over the years?

You may know the answers to these questions off the top of your head. If you are like most people, however, you find answers to tough questions like these by searching the Internet, visiting the library, or asking others for information. To put it simply, you perform research.

Whether you are a scientist, an artist, a paralegal, or a parent, you probably perform research in your everyday life. When your boss, your instructor, or a family member asks you a question that you do not know the answer to, you locate relevant information, analyze your findings, and share your results. Locating, analyzing, and sharing information are key steps in the research process, and in this chapter, you will learn more about each step. By developing your research writing skills, you will prepare yourself to answer any question no matter how challenging.

Reasons for Research

When you perform research, you are essentially trying to solve a mystery—you want to know how something works or why something happened. In other words, you want to answer a question that you (and other people) have about the world. This is one of the most basic reasons for performing research.

But the research process does not end when you have solved your mystery. Imagine what would happen if a detective collected enough evidence to solve a criminal case, but she never shared her solution with the authorities. Presenting what you have learned from research can be just as important as performing the research. Research results can be presented in a variety of ways, but one of the most popular—and effective—presentation forms is the research paper . A research paper presents an original thesis, or purpose statement, about a topic and develops that thesis with information gathered from a variety of sources.

If you are curious about the possibility of life on Mars, for example, you might choose to research the topic. What will you do, though, when your research is complete? You will need a way to put your thoughts together in a logical, coherent manner. You may want to use the facts you have learned to create a narrative or to support an argument. And you may want to show the results of your research to your friends, your teachers, or even the editors of magazines and journals. Writing a research paper is an ideal way to organize thoughts, craft narratives or make arguments based on research, and share your newfound knowledge with the world.

Write a paragraph about a time when you used research in your everyday life. Did you look for the cheapest way to travel from Houston to Denver? Did you search for a way to remove gum from the bottom of your shoe? In your paragraph, explain what you wanted to research, how you performed the research, and what you learned as a result.

Research Writing and the Academic Paper

No matter what field of study you are interested in, you will most likely be asked to write a research paper during your academic career. For example, a student in an art history course might write a research paper about an artist’s work. Similarly, a student in a psychology course might write a research paper about current findings in childhood development.

Having to write a research paper may feel intimidating at first. After all, researching and writing a long paper requires a lot of time, effort, and organization. However, writing a research paper can also be a great opportunity to explore a topic that is particularly interesting to you. The research process allows you to gain expertise on a topic of your choice, and the writing process helps you remember what you have learned and understand it on a deeper level.

Research Writing at Work

Knowing how to write a good research paper is a valuable skill that will serve you well throughout your career. Whether you are developing a new product, studying the best way to perform a procedure, or learning about challenges and opportunities in your field of employment, you will use research techniques to guide your exploration. You may even need to create a written report of your findings. And because effective communication is essential to any company, employers seek to hire people who can write clearly and professionally.

Writing at Work

Take a few minutes to think about each of the following careers. How might each of these professionals use researching and research writing skills on the job?

• Medical laboratory technician
• Small business owner
• Information technology professional
• Freelance magazine writer

A medical laboratory technician or information technology professional might do research to learn about the latest technological developments in either of these fields. A small business owner might conduct research to learn about the latest trends in his or her industry. A freelance magazine writer may need to research a given topic to write an informed, up-to-date article.

Think about the job of your dreams. How might you use research writing skills to perform that job? Create a list of ways in which strong researching, organizing, writing, and critical thinking skills could help you succeed at your dream job. How might these skills help you obtain that job?

Steps of the Research Writing Process

How does a research paper grow from a folder of brainstormed notes to a polished final draft? No two projects are identical, but most projects follow a series of six basic steps.

These are the steps in the research writing process:

• Choose a topic.
• Plan and schedule time to research and write.
• Conduct research.
• Organize research and ideas.
• Draft your paper.
• Revise and edit your paper.

Each of these steps will be discussed in more detail later in this chapter. For now, though, we will take a brief look at what each step involves.

Step 1: Choosing a Topic

As you may recall from Chapter 8 “The Writing Process: How Do I Begin?” , to narrow the focus of your topic, you may try freewriting exercises, such as brainstorming. You may also need to ask a specific research question —a broad, open-ended question that will guide your research—as well as propose a possible answer, or a working thesis . You may use your research question and your working thesis to create a research proposal . In a research proposal, you present your main research question, any related subquestions you plan to explore, and your working thesis.

Step 2: Planning and Scheduling

Before you start researching your topic, take time to plan your researching and writing schedule. Research projects can take days, weeks, or even months to complete. Creating a schedule is a good way to ensure that you do not end up being overwhelmed by all the work you have to do as the deadline approaches.

During this step of the process, it is also a good idea to plan the resources and organizational tools you will use to keep yourself on track throughout the project. Flowcharts, calendars, and checklists can all help you stick to your schedule. See Chapter 11 “Writing from Research: What Will I Learn?” , Section 11.2 “Steps in Developing a Research Proposal” for an example of a research schedule.

Step 3: Conducting Research

When going about your research, you will likely use a variety of sources—anything from books and periodicals to video presentations and in-person interviews.

Your sources will include both primary sources and secondary sources . Primary sources provide firsthand information or raw data. For example, surveys, in-person interviews, and historical documents are primary sources. Secondary sources, such as biographies, literary reviews, or magazine articles, include some analysis or interpretation of the information presented. As you conduct research, you will take detailed, careful notes about your discoveries. You will also evaluate the reliability of each source you find.

Step 4: Organizing Research and the Writer’s Ideas

When your research is complete, you will organize your findings and decide which sources to cite in your paper. You will also have an opportunity to evaluate the evidence you have collected and determine whether it supports your thesis, or the focus of your paper. You may decide to adjust your thesis or conduct additional research to ensure that your thesis is well supported.

Remember, your working thesis is not set in stone. You can and should change your working thesis throughout the research writing process if the evidence you find does not support your original thesis. Never try to force evidence to fit your argument. For example, your working thesis is “Mars cannot support life-forms.” Yet, a week into researching your topic, you find an article in the New York Times detailing new findings of bacteria under the Martian surface. Instead of trying to argue that bacteria are not life forms, you might instead alter your thesis to “Mars cannot support complex life-forms.”

Step 5: Drafting Your Paper

Now you are ready to combine your research findings with your critical analysis of the results in a rough draft. You will incorporate source materials into your paper and discuss each source thoughtfully in relation to your thesis or purpose statement.

When you cite your reference sources, it is important to pay close attention to standard conventions for citing sources in order to avoid plagiarism , or the practice of using someone else’s words without acknowledging the source. Later in this chapter, you will learn how to incorporate sources in your paper and avoid some of the most common pitfalls of attributing information.

Step 6: Revising and Editing Your Paper

In the final step of the research writing process, you will revise and polish your paper. You might reorganize your paper’s structure or revise for unity and cohesion, ensuring that each element in your paper flows into the next logically and naturally. You will also make sure that your paper uses an appropriate and consistent tone.

Once you feel confident in the strength of your writing, you will edit your paper for proper spelling, grammar, punctuation, mechanics, and formatting. When you complete this final step, you will have transformed a simple idea or question into a thoroughly researched and well-written paper you can be proud of!

Review the steps of the research writing process. Then answer the questions on your own sheet of paper.

• In which steps of the research writing process are you allowed to change your thesis?
• In step 2, which types of information should you include in your project schedule?
• What might happen if you eliminated step 4 from the research writing process?

Key Takeaways

• People undertake research projects throughout their academic and professional careers in order to answer specific questions, share their findings with others, increase their understanding of challenging topics, and strengthen their researching, writing, and analytical skills.
• The research writing process generally comprises six steps: choosing a topic, scheduling and planning time for research and writing, conducting research, organizing research and ideas, drafting a paper, and revising and editing the paper.

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Home » Significance of the Study – Examples and Writing Guide

Significance of the Study – Examples and Writing Guide

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Significance of the Study

Definition:

Significance of the study in research refers to the potential importance, relevance, or impact of the research findings. It outlines how the research contributes to the existing body of knowledge, what gaps it fills, or what new understanding it brings to a particular field of study.

In general, the significance of a study can be assessed based on several factors, including:

• Originality : The extent to which the study advances existing knowledge or introduces new ideas and perspectives.
• Practical relevance: The potential implications of the study for real-world situations, such as improving policy or practice.
• Theoretical contribution: The extent to which the study provides new insights or perspectives on theoretical concepts or frameworks.
• Methodological rigor : The extent to which the study employs appropriate and robust methods and techniques to generate reliable and valid data.
• Social or cultural impact : The potential impact of the study on society, culture, or public perception of a particular issue.

Types of Significance of the Study

The significance of the Study can be divided into the following types:

Theoretical Significance

Theoretical significance refers to the contribution that a study makes to the existing body of theories in a specific field. This could be by confirming, refuting, or adding nuance to a currently accepted theory, or by proposing an entirely new theory.

Practical Significance

Practical significance refers to the direct applicability and usefulness of the research findings in real-world contexts. Studies with practical significance often address real-life problems and offer potential solutions or strategies. For example, a study in the field of public health might identify a new intervention that significantly reduces the spread of a certain disease.

Significance for Future Research

This pertains to the potential of a study to inspire further research. A study might open up new areas of investigation, provide new research methodologies, or propose new hypotheses that need to be tested.

How to Write Significance of the Study

Here’s a guide to writing an effective “Significance of the Study” section in research paper, thesis, or dissertation:

• Background : Begin by giving some context about your study. This could include a brief introduction to your subject area, the current state of research in the field, and the specific problem or question your study addresses.
• Identify the Gap : Demonstrate that there’s a gap in the existing literature or knowledge that needs to be filled, which is where your study comes in. The gap could be a lack of research on a particular topic, differing results in existing studies, or a new problem that has arisen and hasn’t yet been studied.
• State the Purpose of Your Study : Clearly state the main objective of your research. You may want to state the purpose as a solution to the problem or gap you’ve previously identified.
• Contributes to the existing body of knowledge.
• Addresses a significant research gap.
• Offers a new or better solution to a problem.
• Impacts policy or practice.
• Leads to improvements in a particular field or sector.
• Identify Beneficiaries : Identify who will benefit from your study. This could include other researchers, practitioners in your field, policy-makers, communities, businesses, or others. Explain how your findings could be used and by whom.
• Future Implications : Discuss the implications of your study for future research. This could involve questions that are left open, new questions that have been raised, or potential future methodologies suggested by your study.

Significance of the Study in Research Paper

The Significance of the Study in a research paper refers to the importance or relevance of the research topic being investigated. It answers the question “Why is this research important?” and highlights the potential contributions and impacts of the study.

The significance of the study can be presented in the introduction or background section of a research paper. It typically includes the following components:

• Importance of the research problem: This describes why the research problem is worth investigating and how it relates to existing knowledge and theories.
• Potential benefits and implications: This explains the potential contributions and impacts of the research on theory, practice, policy, or society.
• Originality and novelty: This highlights how the research adds new insights, approaches, or methods to the existing body of knowledge.
• Scope and limitations: This outlines the boundaries and constraints of the research and clarifies what the study will and will not address.

Suppose a researcher is conducting a study on the “Effects of social media use on the mental health of adolescents”.

The significance of the study may be:

“The present study is significant because it addresses a pressing public health issue of the negative impact of social media use on adolescent mental health. Given the widespread use of social media among this age group, understanding the effects of social media on mental health is critical for developing effective prevention and intervention strategies. This study will contribute to the existing literature by examining the moderating factors that may affect the relationship between social media use and mental health outcomes. It will also shed light on the potential benefits and risks of social media use for adolescents and inform the development of evidence-based guidelines for promoting healthy social media use among this population. The limitations of this study include the use of self-reported measures and the cross-sectional design, which precludes causal inference.”

Significance of the Study In Thesis

The significance of the study in a thesis refers to the importance or relevance of the research topic and the potential impact of the study on the field of study or society as a whole. It explains why the research is worth doing and what contribution it will make to existing knowledge.

For example, the significance of a thesis on “Artificial Intelligence in Healthcare” could be:

• With the increasing availability of healthcare data and the development of advanced machine learning algorithms, AI has the potential to revolutionize the healthcare industry by improving diagnosis, treatment, and patient outcomes. Therefore, this thesis can contribute to the understanding of how AI can be applied in healthcare and how it can benefit patients and healthcare providers.
• AI in healthcare also raises ethical and social issues, such as privacy concerns, bias in algorithms, and the impact on healthcare jobs. By exploring these issues in the thesis, it can provide insights into the potential risks and benefits of AI in healthcare and inform policy decisions.
• Finally, the thesis can also advance the field of computer science by developing new AI algorithms or techniques that can be applied to healthcare data, which can have broader applications in other industries or fields of research.

Significance of the Study in Research Proposal

The significance of a study in a research proposal refers to the importance or relevance of the research question, problem, or objective that the study aims to address. It explains why the research is valuable, relevant, and important to the academic or scientific community, policymakers, or society at large. A strong statement of significance can help to persuade the reviewers or funders of the research proposal that the study is worth funding and conducting.

Here is an example of a significance statement in a research proposal:

Title : The Effects of Gamification on Learning Programming: A Comparative Study

Significance Statement:

This proposed study aims to investigate the effects of gamification on learning programming. With the increasing demand for computer science professionals, programming has become a fundamental skill in the computer field. However, learning programming can be challenging, and students may struggle with motivation and engagement. Gamification has emerged as a promising approach to improve students’ engagement and motivation in learning, but its effects on programming education are not yet fully understood. This study is significant because it can provide valuable insights into the potential benefits of gamification in programming education and inform the development of effective teaching strategies to enhance students’ learning outcomes and interest in programming.

Examples of Significance of the Study

Here are some examples of the significance of a study that indicates how you can write this into your research paper according to your research topic:

Research on an Improved Water Filtration System : This study has the potential to impact millions of people living in water-scarce regions or those with limited access to clean water. A more efficient and affordable water filtration system can reduce water-borne diseases and improve the overall health of communities, enabling them to lead healthier, more productive lives.

Study on the Impact of Remote Work on Employee Productivity : Given the shift towards remote work due to recent events such as the COVID-19 pandemic, this study is of considerable significance. Findings could help organizations better structure their remote work policies and offer insights on how to maximize employee productivity, wellbeing, and job satisfaction.

Investigation into the Use of Solar Power in Developing Countries : With the world increasingly moving towards renewable energy, this study could provide important data on the feasibility and benefits of implementing solar power solutions in developing countries. This could potentially stimulate economic growth, reduce reliance on non-renewable resources, and contribute to global efforts to combat climate change.

Research on New Learning Strategies in Special Education : This study has the potential to greatly impact the field of special education. By understanding the effectiveness of new learning strategies, educators can improve their curriculum to provide better support for students with learning disabilities, fostering their academic growth and social development.

Examination of Mental Health Support in the Workplace : This study could highlight the impact of mental health initiatives on employee wellbeing and productivity. It could influence organizational policies across industries, promoting the implementation of mental health programs in the workplace, ultimately leading to healthier work environments.

Evaluation of a New Cancer Treatment Method : The significance of this study could be lifesaving. The research could lead to the development of more effective cancer treatments, increasing the survival rate and quality of life for patients worldwide.

When to Write Significance of the Study

The Significance of the Study section is an integral part of a research proposal or a thesis. This section is typically written after the introduction and the literature review. In the research process, the structure typically follows this order:

• Title – The name of your research.
• Abstract – A brief summary of the entire research.
• Introduction – A presentation of the problem your research aims to solve.
• Literature Review – A review of existing research on the topic to establish what is already known and where gaps exist.
• Significance of the Study – An explanation of why the research matters and its potential impact.

In the Significance of the Study section, you will discuss why your study is important, who it benefits, and how it adds to existing knowledge or practice in your field. This section is your opportunity to convince readers, and potentially funders or supervisors, that your research is valuable and worth undertaking.

Advantages of Significance of the Study

The Significance of the Study section in a research paper has multiple advantages:

• Establishes Relevance: This section helps to articulate the importance of your research to your field of study, as well as the wider society, by explicitly stating its relevance. This makes it easier for other researchers, funders, and policymakers to understand why your work is necessary and worth supporting.
• Guides the Research: Writing the significance can help you refine your research questions and objectives. This happens as you critically think about why your research is important and how it contributes to your field.
• Attracts Funding: If you are seeking funding or support for your research, having a well-written significance of the study section can be key. It helps to convince potential funders of the value of your work.
• Opens up Further Research: By stating the significance of the study, you’re also indicating what further research could be carried out in the future, based on your work. This helps to pave the way for future studies and demonstrates that your research is a valuable addition to the field.
• Provides Practical Applications: The significance of the study section often outlines how the research can be applied in real-world situations. This can be particularly important in applied sciences, where the practical implications of research are crucial.
• Enhances Understanding: This section can help readers understand how your study fits into the broader context of your field, adding value to the existing literature and contributing new knowledge or insights.

Limitations of Significance of the Study

The Significance of the Study section plays an essential role in any research. However, it is not without potential limitations. Here are some that you should be aware of:

• Subjectivity: The importance and implications of a study can be subjective and may vary from person to person. What one researcher considers significant might be seen as less critical by others. The assessment of significance often depends on personal judgement, biases, and perspectives.
• Predictability of Impact: While you can outline the potential implications of your research in the Significance of the Study section, the actual impact can be unpredictable. Research doesn’t always yield the expected results or have the predicted impact on the field or society.
• Difficulty in Measuring: The significance of a study is often qualitative and can be challenging to measure or quantify. You can explain how you think your research will contribute to your field or society, but measuring these outcomes can be complex.
• Possibility of Overstatement: Researchers may feel pressured to amplify the potential significance of their study to attract funding or interest. This can lead to overstating the potential benefits or implications, which can harm the credibility of the study if these results are not achieved.
• Overshadowing of Limitations: Sometimes, the significance of the study may overshadow the limitations of the research. It is important to balance the potential significance with a thorough discussion of the study’s limitations.
• Dependence on Successful Implementation: The significance of the study relies on the successful implementation of the research. If the research process has flaws or unexpected issues arise, the anticipated significance might not be realized.

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What Is Research, and Why Do People Do It?

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• First Online: 03 December 2022

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Part of the book series: Research in Mathematics Education ((RME))

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Abstractspiepr Abs1

Every day people do research as they gather information to learn about something of interest. In the scientific world, however, research means something different than simply gathering information. Scientific research is characterized by its careful planning and observing, by its relentless efforts to understand and explain, and by its commitment to learn from everyone else seriously engaged in research. We call this kind of research scientific inquiry and define it as “formulating, testing, and revising hypotheses.” By “hypotheses” we do not mean the hypotheses you encounter in statistics courses. We mean predictions about what you expect to find and rationales for why you made these predictions. Throughout this and the remaining chapters we make clear that the process of scientific inquiry applies to all kinds of research studies and data, both qualitative and quantitative.

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Part I. What Is Research?

Have you ever studied something carefully because you wanted to know more about it? Maybe you wanted to know more about your grandmother’s life when she was younger so you asked her to tell you stories from her childhood, or maybe you wanted to know more about a fertilizer you were about to use in your garden so you read the ingredients on the package and looked them up online. According to the dictionary definition, you were doing research.

Recall your high school assignments asking you to “research” a topic. The assignment likely included consulting a variety of sources that discussed the topic, perhaps including some “original” sources. Often, the teacher referred to your product as a “research paper.”

Were you conducting research when you interviewed your grandmother or wrote high school papers reviewing a particular topic? Our view is that you were engaged in part of the research process, but only a small part. In this book, we reserve the word “research” for what it means in the scientific world, that is, for scientific research or, more pointedly, for scientific inquiry .

Exercise 1.1

Before you read any further, write a definition of what you think scientific inquiry is. Keep it short—Two to three sentences. You will periodically update this definition as you read this chapter and the remainder of the book.

This book is about scientific inquiry—what it is and how to do it. For starters, scientific inquiry is a process, a particular way of finding out about something that involves a number of phases. Each phase of the process constitutes one aspect of scientific inquiry. You are doing scientific inquiry as you engage in each phase, but you have not done scientific inquiry until you complete the full process. Each phase is necessary but not sufficient.

In this chapter, we set the stage by defining scientific inquiry—describing what it is and what it is not—and by discussing what it is good for and why people do it. The remaining chapters build directly on the ideas presented in this chapter.

A first thing to know is that scientific inquiry is not all or nothing. “Scientificness” is a continuum. Inquiries can be more scientific or less scientific. What makes an inquiry more scientific? You might be surprised there is no universally agreed upon answer to this question. None of the descriptors we know of are sufficient by themselves to define scientific inquiry. But all of them give you a way of thinking about some aspects of the process of scientific inquiry. Each one gives you different insights.

Exercise 1.2

As you read about each descriptor below, think about what would make an inquiry more or less scientific. If you think a descriptor is important, use it to revise your definition of scientific inquiry.

Creating an Image of Scientific Inquiry

We will present three descriptors of scientific inquiry. Each provides a different perspective and emphasizes a different aspect of scientific inquiry. We will draw on all three descriptors to compose our definition of scientific inquiry.

Descriptor 1. Experience Carefully Planned in Advance

Sir Ronald Fisher, often called the father of modern statistical design, once referred to research as “experience carefully planned in advance” (1935, p. 8). He said that humans are always learning from experience, from interacting with the world around them. Usually, this learning is haphazard rather than the result of a deliberate process carried out over an extended period of time. Research, Fisher said, was learning from experience, but experience carefully planned in advance.

This phrase can be fully appreciated by looking at each word. The fact that scientific inquiry is based on experience means that it is based on interacting with the world. These interactions could be thought of as the stuff of scientific inquiry. In addition, it is not just any experience that counts. The experience must be carefully planned . The interactions with the world must be conducted with an explicit, describable purpose, and steps must be taken to make the intended learning as likely as possible. This planning is an integral part of scientific inquiry; it is not just a preparation phase. It is one of the things that distinguishes scientific inquiry from many everyday learning experiences. Finally, these steps must be taken beforehand and the purpose of the inquiry must be articulated in advance of the experience. Clearly, scientific inquiry does not happen by accident, by just stumbling into something. Stumbling into something unexpected and interesting can happen while engaged in scientific inquiry, but learning does not depend on it and serendipity does not make the inquiry scientific.

Descriptor 2. Observing Something and Trying to Explain Why It Is the Way It Is

When we were writing this chapter and googled “scientific inquiry,” the first entry was: “Scientific inquiry refers to the diverse ways in which scientists study the natural world and propose explanations based on the evidence derived from their work.” The emphasis is on studying, or observing, and then explaining . This descriptor takes the image of scientific inquiry beyond carefully planned experience and includes explaining what was experienced.

According to the Merriam-Webster dictionary, “explain” means “(a) to make known, (b) to make plain or understandable, (c) to give the reason or cause of, and (d) to show the logical development or relations of” (Merriam-Webster, n.d. ). We will use all these definitions. Taken together, they suggest that to explain an observation means to understand it by finding reasons (or causes) for why it is as it is. In this sense of scientific inquiry, the following are synonyms: explaining why, understanding why, and reasoning about causes and effects. Our image of scientific inquiry now includes planning, observing, and explaining why.

We need to add a final note about this descriptor. We have phrased it in a way that suggests “observing something” means you are observing something in real time—observing the way things are or the way things are changing. This is often true. But, observing could mean observing data that already have been collected, maybe by someone else making the original observations (e.g., secondary analysis of NAEP data or analysis of existing video recordings of classroom instruction). We will address secondary analyses more fully in Chap. 4 . For now, what is important is that the process requires explaining why the data look like they do.

We must note that for us, the term “data” is not limited to numerical or quantitative data such as test scores. Data can also take many nonquantitative forms, including written survey responses, interview transcripts, journal entries, video recordings of students, teachers, and classrooms, text messages, and so forth.

Exercise 1.3

What are the implications of the statement that just “observing” is not enough to count as scientific inquiry? Does this mean that a detailed description of a phenomenon is not scientific inquiry?

Find sources that define research in education that differ with our position, that say description alone, without explanation, counts as scientific research. Identify the precise points where the opinions differ. What are the best arguments for each of the positions? Which do you prefer? Why?

Descriptor 3. Updating Everyone’s Thinking in Response to More and Better Information

This descriptor focuses on a third aspect of scientific inquiry: updating and advancing the field’s understanding of phenomena that are investigated. This descriptor foregrounds a powerful characteristic of scientific inquiry: the reliability (or trustworthiness) of what is learned and the ultimate inevitability of this learning to advance human understanding of phenomena. Humans might choose not to learn from scientific inquiry, but history suggests that scientific inquiry always has the potential to advance understanding and that, eventually, humans take advantage of these new understandings.

Before exploring these bold claims a bit further, note that this descriptor uses “information” in the same way the previous two descriptors used “experience” and “observations.” These are the stuff of scientific inquiry and we will use them often, sometimes interchangeably. Frequently, we will use the term “data” to stand for all these terms.

An overriding goal of scientific inquiry is for everyone to learn from what one scientist does. Much of this book is about the methods you need to use so others have faith in what you report and can learn the same things you learned. This aspect of scientific inquiry has many implications.

One implication is that scientific inquiry is not a private practice. It is a public practice available for others to see and learn from. Notice how different this is from everyday learning. When you happen to learn something from your everyday experience, often only you gain from the experience. The fact that research is a public practice means it is also a social one. It is best conducted by interacting with others along the way: soliciting feedback at each phase, taking opportunities to present work-in-progress, and benefitting from the advice of others.

A second implication is that you, as the researcher, must be committed to sharing what you are doing and what you are learning in an open and transparent way. This allows all phases of your work to be scrutinized and critiqued. This is what gives your work credibility. The reliability or trustworthiness of your findings depends on your colleagues recognizing that you have used all appropriate methods to maximize the chances that your claims are justified by the data.

A third implication of viewing scientific inquiry as a collective enterprise is the reverse of the second—you must be committed to receiving comments from others. You must treat your colleagues as fair and honest critics even though it might sometimes feel otherwise. You must appreciate their job, which is to remain skeptical while scrutinizing what you have done in considerable detail. To provide the best help to you, they must remain skeptical about your conclusions (when, for example, the data are difficult for them to interpret) until you offer a convincing logical argument based on the information you share. A rather harsh but good-to-remember statement of the role of your friendly critics was voiced by Karl Popper, a well-known twentieth century philosopher of science: “. . . if you are interested in the problem which I tried to solve by my tentative assertion, you may help me by criticizing it as severely as you can” (Popper, 1968, p. 27).

A final implication of this third descriptor is that, as someone engaged in scientific inquiry, you have no choice but to update your thinking when the data support a different conclusion. This applies to your own data as well as to those of others. When data clearly point to a specific claim, even one that is quite different than you expected, you must reconsider your position. If the outcome is replicated multiple times, you need to adjust your thinking accordingly. Scientific inquiry does not let you pick and choose which data to believe; it mandates that everyone update their thinking when the data warrant an update.

Doing Scientific Inquiry

We define scientific inquiry in an operational sense—what does it mean to do scientific inquiry? What kind of process would satisfy all three descriptors: carefully planning an experience in advance; observing and trying to explain what you see; and, contributing to updating everyone’s thinking about an important phenomenon?

We define scientific inquiry as formulating , testing , and revising hypotheses about phenomena of interest.

Of course, we are not the only ones who define it in this way. The definition for the scientific method posted by the editors of Britannica is: “a researcher develops a hypothesis, tests it through various means, and then modifies the hypothesis on the basis of the outcome of the tests and experiments” (Britannica, n.d. ).

Notice how defining scientific inquiry this way satisfies each of the descriptors. “Carefully planning an experience in advance” is exactly what happens when formulating a hypothesis about a phenomenon of interest and thinking about how to test it. “ Observing a phenomenon” occurs when testing a hypothesis, and “ explaining ” what is found is required when revising a hypothesis based on the data. Finally, “updating everyone’s thinking” comes from comparing publicly the original with the revised hypothesis.

Doing scientific inquiry, as we have defined it, underscores the value of accumulating knowledge rather than generating random bits of knowledge. Formulating, testing, and revising hypotheses is an ongoing process, with each revised hypothesis begging for another test, whether by the same researcher or by new researchers. The editors of Britannica signaled this cyclic process by adding the following phrase to their definition of the scientific method: “The modified hypothesis is then retested, further modified, and tested again.” Scientific inquiry creates a process that encourages each study to build on the studies that have gone before. Through collective engagement in this process of building study on top of study, the scientific community works together to update its thinking.

Before exploring more fully the meaning of “formulating, testing, and revising hypotheses,” we need to acknowledge that this is not the only way researchers define research. Some researchers prefer a less formal definition, one that includes more serendipity, less planning, less explanation. You might have come across more open definitions such as “research is finding out about something.” We prefer the tighter hypothesis formulation, testing, and revision definition because we believe it provides a single, coherent map for conducting research that addresses many of the thorny problems educational researchers encounter. We believe it is the most useful orientation toward research and the most helpful to learn as a beginning researcher.

A final clarification of our definition is that it applies equally to qualitative and quantitative research. This is a familiar distinction in education that has generated much discussion. You might think our definition favors quantitative methods over qualitative methods because the language of hypothesis formulation and testing is often associated with quantitative methods. In fact, we do not favor one method over another. In Chap. 4 , we will illustrate how our definition fits research using a range of quantitative and qualitative methods.

Exercise 1.4

Look for ways to extend what the field knows in an area that has already received attention by other researchers. Specifically, you can search for a program of research carried out by more experienced researchers that has some revised hypotheses that remain untested. Identify a revised hypothesis that you might like to test.

Unpacking the Terms Formulating, Testing, and Revising Hypotheses

To get a full sense of the definition of scientific inquiry we will use throughout this book, it is helpful to spend a little time with each of the key terms.

We first want to make clear that we use the term “hypothesis” as it is defined in most dictionaries and as it used in many scientific fields rather than as it is usually defined in educational statistics courses. By “hypothesis,” we do not mean a null hypothesis that is accepted or rejected by statistical analysis. Rather, we use “hypothesis” in the sense conveyed by the following definitions: “An idea or explanation for something that is based on known facts but has not yet been proved” (Cambridge University Press, n.d. ), and “An unproved theory, proposition, or supposition, tentatively accepted to explain certain facts and to provide a basis for further investigation or argument” (Agnes & Guralnik, 2008 ).

We distinguish two parts to “hypotheses.” Hypotheses consist of predictions and rationales . Predictions are statements about what you expect to find when you inquire about something. Rationales are explanations for why you made the predictions you did, why you believe your predictions are correct. So, for us “formulating hypotheses” means making explicit predictions and developing rationales for the predictions.

“Testing hypotheses” means making observations that allow you to assess in what ways your predictions were correct and in what ways they were incorrect. In education research, it is rarely useful to think of your predictions as either right or wrong. Because of the complexity of most issues you will investigate, most predictions will be right in some ways and wrong in others.

By studying the observations you make (data you collect) to test your hypotheses, you can revise your hypotheses to better align with the observations. This means revising your predictions plus revising your rationales to justify your adjusted predictions. Even though you might not run another test, formulating revised hypotheses is an essential part of conducting a research study. Comparing your original and revised hypotheses informs everyone of what you learned by conducting your study. In addition, a revised hypothesis sets the stage for you or someone else to extend your study and accumulate more knowledge of the phenomenon.

We should note that not everyone makes a clear distinction between predictions and rationales as two aspects of hypotheses. In fact, common, non-scientific uses of the word “hypothesis” may limit it to only a prediction or only an explanation (or rationale). We choose to explicitly include both prediction and rationale in our definition of hypothesis, not because we assert this should be the universal definition, but because we want to foreground the importance of both parts acting in concert. Using “hypothesis” to represent both prediction and rationale could hide the two aspects, but we make them explicit because they provide different kinds of information. It is usually easier to make predictions than develop rationales because predictions can be guesses, hunches, or gut feelings about which you have little confidence. Developing a compelling rationale requires careful thought plus reading what other researchers have found plus talking with your colleagues. Often, while you are developing your rationale you will find good reasons to change your predictions. Developing good rationales is the engine that drives scientific inquiry. Rationales are essentially descriptions of how much you know about the phenomenon you are studying. Throughout this guide, we will elaborate on how developing good rationales drives scientific inquiry. For now, we simply note that it can sharpen your predictions and help you to interpret your data as you test your hypotheses.

Hypotheses in education research take a variety of forms or types. This is because there are a variety of phenomena that can be investigated. Investigating educational phenomena is sometimes best done using qualitative methods, sometimes using quantitative methods, and most often using mixed methods (e.g., Hay, 2016 ; Weis et al. 2019a ; Weisner, 2005 ). This means that, given our definition, hypotheses are equally applicable to qualitative and quantitative investigations.

Hypotheses take different forms when they are used to investigate different kinds of phenomena. Two very different activities in education could be labeled conducting experiments and descriptions. In an experiment, a hypothesis makes a prediction about anticipated changes, say the changes that occur when a treatment or intervention is applied. You might investigate how students’ thinking changes during a particular kind of instruction.

A second type of hypothesis, relevant for descriptive research, makes a prediction about what you will find when you investigate and describe the nature of a situation. The goal is to understand a situation as it exists rather than to understand a change from one situation to another. In this case, your prediction is what you expect to observe. Your rationale is the set of reasons for making this prediction; it is your current explanation for why the situation will look like it does.

You will probably read, if you have not already, that some researchers say you do not need a prediction to conduct a descriptive study. We will discuss this point of view in Chap. 2 . For now, we simply claim that scientific inquiry, as we have defined it, applies to all kinds of research studies. Descriptive studies, like others, not only benefit from formulating, testing, and revising hypotheses, but also need hypothesis formulating, testing, and revising.

One reason we define research as formulating, testing, and revising hypotheses is that if you think of research in this way you are less likely to go wrong. It is a useful guide for the entire process, as we will describe in detail in the chapters ahead. For example, as you build the rationale for your predictions, you are constructing the theoretical framework for your study (Chap. 3 ). As you work out the methods you will use to test your hypothesis, every decision you make will be based on asking, “Will this help me formulate or test or revise my hypothesis?” (Chap. 4 ). As you interpret the results of testing your predictions, you will compare them to what you predicted and examine the differences, focusing on how you must revise your hypotheses (Chap. 5 ). By anchoring the process to formulating, testing, and revising hypotheses, you will make smart decisions that yield a coherent and well-designed study.

Exercise 1.5

Compare the concept of formulating, testing, and revising hypotheses with the descriptions of scientific inquiry contained in Scientific Research in Education (NRC, 2002 ). How are they similar or different?

Exercise 1.6

Provide an example to illustrate and emphasize the differences between everyday learning/thinking and scientific inquiry.

Learning from Doing Scientific Inquiry

We noted earlier that a measure of what you have learned by conducting a research study is found in the differences between your original hypothesis and your revised hypothesis based on the data you collected to test your hypothesis. We will elaborate this statement in later chapters, but we preview our argument here.

Even before collecting data, scientific inquiry requires cycles of making a prediction, developing a rationale, refining your predictions, reading and studying more to strengthen your rationale, refining your predictions again, and so forth. And, even if you have run through several such cycles, you still will likely find that when you test your prediction you will be partly right and partly wrong. The results will support some parts of your predictions but not others, or the results will “kind of” support your predictions. A critical part of scientific inquiry is making sense of your results by interpreting them against your predictions. Carefully describing what aspects of your data supported your predictions, what aspects did not, and what data fell outside of any predictions is not an easy task, but you cannot learn from your study without doing this analysis.

Analyzing the matches and mismatches between your predictions and your data allows you to formulate different rationales that would have accounted for more of the data. The best revised rationale is the one that accounts for the most data. Once you have revised your rationales, you can think about the predictions they best justify or explain. It is by comparing your original rationales to your new rationales that you can sort out what you learned from your study.

Suppose your study was an experiment. Maybe you were investigating the effects of a new instructional intervention on students’ learning. Your original rationale was your explanation for why the intervention would change the learning outcomes in a particular way. Your revised rationale explained why the changes that you observed occurred like they did and why your revised predictions are better. Maybe your original rationale focused on the potential of the activities if they were implemented in ideal ways and your revised rationale included the factors that are likely to affect how teachers implement them. By comparing the before and after rationales, you are describing what you learned—what you can explain now that you could not before. Another way of saying this is that you are describing how much more you understand now than before you conducted your study.

Revised predictions based on carefully planned and collected data usually exhibit some of the following features compared with the originals: more precision, more completeness, and broader scope. Revised rationales have more explanatory power and become more complete, more aligned with the new predictions, sharper, and overall more convincing.

Part II. Why Do Educators Do Research?

Doing scientific inquiry is a lot of work. Each phase of the process takes time, and you will often cycle back to improve earlier phases as you engage in later phases. Because of the significant effort required, you should make sure your study is worth it. So, from the beginning, you should think about the purpose of your study. Why do you want to do it? And, because research is a social practice, you should also think about whether the results of your study are likely to be important and significant to the education community.

If you are doing research in the way we have described—as scientific inquiry—then one purpose of your study is to understand , not just to describe or evaluate or report. As we noted earlier, when you formulate hypotheses, you are developing rationales that explain why things might be like they are. In our view, trying to understand and explain is what separates research from other kinds of activities, like evaluating or describing.

One reason understanding is so important is that it allows researchers to see how or why something works like it does. When you see how something works, you are better able to predict how it might work in other contexts, under other conditions. And, because conditions, or contextual factors, matter a lot in education, gaining insights into applying your findings to other contexts increases the contributions of your work and its importance to the broader education community.

Consequently, the purposes of research studies in education often include the more specific aim of identifying and understanding the conditions under which the phenomena being studied work like the observations suggest. A classic example of this kind of study in mathematics education was reported by William Brownell and Harold Moser in 1949 . They were trying to establish which method of subtracting whole numbers could be taught most effectively—the regrouping method or the equal additions method. However, they realized that effectiveness might depend on the conditions under which the methods were taught—“meaningfully” versus “mechanically.” So, they designed a study that crossed the two instructional approaches with the two different methods (regrouping and equal additions). Among other results, they found that these conditions did matter. The regrouping method was more effective under the meaningful condition than the mechanical condition, but the same was not true for the equal additions algorithm.

What do education researchers want to understand? In our view, the ultimate goal of education is to offer all students the best possible learning opportunities. So, we believe the ultimate purpose of scientific inquiry in education is to develop understanding that supports the improvement of learning opportunities for all students. We say “ultimate” because there are lots of issues that must be understood to improve learning opportunities for all students. Hypotheses about many aspects of education are connected, ultimately, to students’ learning. For example, formulating and testing a hypothesis that preservice teachers need to engage in particular kinds of activities in their coursework in order to teach particular topics well is, ultimately, connected to improving students’ learning opportunities. So is hypothesizing that school districts often devote relatively few resources to instructional leadership training or hypothesizing that positioning mathematics as a tool students can use to combat social injustice can help students see the relevance of mathematics to their lives.

We do not exclude the importance of research on educational issues more removed from improving students’ learning opportunities, but we do think the argument for their importance will be more difficult to make. If there is no way to imagine a connection between your hypothesis and improving learning opportunities for students, even a distant connection, we recommend you reconsider whether it is an important hypothesis within the education community.

Notice that we said the ultimate goal of education is to offer all students the best possible learning opportunities. For too long, educators have been satisfied with a goal of offering rich learning opportunities for lots of students, sometimes even for just the majority of students, but not necessarily for all students. Evaluations of success often are based on outcomes that show high averages. In other words, if many students have learned something, or even a smaller number have learned a lot, educators may have been satisfied. The problem is that there is usually a pattern in the groups of students who receive lower quality opportunities—students of color and students who live in poor areas, urban and rural. This is not acceptable. Consequently, we emphasize the premise that the purpose of education research is to offer rich learning opportunities to all students.

One way to make sure you will be able to convince others of the importance of your study is to consider investigating some aspect of teachers’ shared instructional problems. Historically, researchers in education have set their own research agendas, regardless of the problems teachers are facing in schools. It is increasingly recognized that teachers have had trouble applying to their own classrooms what researchers find. To address this problem, a researcher could partner with a teacher—better yet, a small group of teachers—and talk with them about instructional problems they all share. These discussions can create a rich pool of problems researchers can consider. If researchers pursued one of these problems (preferably alongside teachers), the connection to improving learning opportunities for all students could be direct and immediate. “Grounding a research question in instructional problems that are experienced across multiple teachers’ classrooms helps to ensure that the answer to the question will be of sufficient scope to be relevant and significant beyond the local context” (Cai et al., 2019b , p. 115).

As a beginning researcher, determining the relevance and importance of a research problem is especially challenging. We recommend talking with advisors, other experienced researchers, and peers to test the educational importance of possible research problems and topics of study. You will also learn much more about the issue of research importance when you read Chap. 5 .

Exercise 1.7

Identify a problem in education that is closely connected to improving learning opportunities and a problem that has a less close connection. For each problem, write a brief argument (like a logical sequence of if-then statements) that connects the problem to all students’ learning opportunities.

Part III. Conducting Research as a Practice of Failing Productively

Scientific inquiry involves formulating hypotheses about phenomena that are not fully understood—by you or anyone else. Even if you are able to inform your hypotheses with lots of knowledge that has already been accumulated, you are likely to find that your prediction is not entirely accurate. This is normal. Remember, scientific inquiry is a process of constantly updating your thinking. More and better information means revising your thinking, again, and again, and again. Because you never fully understand a complicated phenomenon and your hypotheses never produce completely accurate predictions, it is easy to believe you are somehow failing.

The trick is to fail upward, to fail to predict accurately in ways that inform your next hypothesis so you can make a better prediction. Some of the best-known researchers in education have been open and honest about the many times their predictions were wrong and, based on the results of their studies and those of others, they continuously updated their thinking and changed their hypotheses.

A striking example of publicly revising (actually reversing) hypotheses due to incorrect predictions is found in the work of Lee J. Cronbach, one of the most distinguished educational psychologists of the twentieth century. In 1955, Cronbach delivered his presidential address to the American Psychological Association. Titling it “Two Disciplines of Scientific Psychology,” Cronbach proposed a rapprochement between two research approaches—correlational studies that focused on individual differences and experimental studies that focused on instructional treatments controlling for individual differences. (We will examine different research approaches in Chap. 4 ). If these approaches could be brought together, reasoned Cronbach ( 1957 ), researchers could find interactions between individual characteristics and treatments (aptitude-treatment interactions or ATIs), fitting the best treatments to different individuals.

In 1975, after years of research by many researchers looking for ATIs, Cronbach acknowledged the evidence for simple, useful ATIs had not been found. Even when trying to find interactions between a few variables that could provide instructional guidance, the analysis, said Cronbach, creates “a hall of mirrors that extends to infinity, tormenting even the boldest investigators and defeating even ambitious designs” (Cronbach, 1975 , p. 119).

As he was reflecting back on his work, Cronbach ( 1986 ) recommended moving away from documenting instructional effects through statistical inference (an approach he had championed for much of his career) and toward approaches that probe the reasons for these effects, approaches that provide a “full account of events in a time, place, and context” (Cronbach, 1986 , p. 104). This is a remarkable change in hypotheses, a change based on data and made fully transparent. Cronbach understood the value of failing productively.

Closer to home, in a less dramatic example, one of us began a line of scientific inquiry into how to prepare elementary preservice teachers to teach early algebra. Teaching early algebra meant engaging elementary students in early forms of algebraic reasoning. Such reasoning should help them transition from arithmetic to algebra. To begin this line of inquiry, a set of activities for preservice teachers were developed. Even though the activities were based on well-supported hypotheses, they largely failed to engage preservice teachers as predicted because of unanticipated challenges the preservice teachers faced. To capitalize on this failure, follow-up studies were conducted, first to better understand elementary preservice teachers’ challenges with preparing to teach early algebra, and then to better support preservice teachers in navigating these challenges. In this example, the initial failure was a necessary step in the researchers’ scientific inquiry and furthered the researchers’ understanding of this issue.

We present another example of failing productively in Chap. 2 . That example emerges from recounting the history of a well-known research program in mathematics education.

Making mistakes is an inherent part of doing scientific research. Conducting a study is rarely a smooth path from beginning to end. We recommend that you keep the following things in mind as you begin a career of conducting research in education.

First, do not get discouraged when you make mistakes; do not fall into the trap of feeling like you are not capable of doing research because you make too many errors.

Second, learn from your mistakes. Do not ignore your mistakes or treat them as errors that you simply need to forget and move past. Mistakes are rich sites for learning—in research just as in other fields of study.

Third, by reflecting on your mistakes, you can learn to make better mistakes, mistakes that inform you about a productive next step. You will not be able to eliminate your mistakes, but you can set a goal of making better and better mistakes.

Exercise 1.8

How does scientific inquiry differ from everyday learning in giving you the tools to fail upward? You may find helpful perspectives on this question in other resources on science and scientific inquiry (e.g., Failure: Why Science is So Successful by Firestein, 2015).

Exercise 1.9

Use what you have learned in this chapter to write a new definition of scientific inquiry. Compare this definition with the one you wrote before reading this chapter. If you are reading this book as part of a course, compare your definition with your colleagues’ definitions. Develop a consensus definition with everyone in the course.

Part IV. Preview of Chap. 2

Now that you have a good idea of what research is, at least of what we believe research is, the next step is to think about how to actually begin doing research. This means how to begin formulating, testing, and revising hypotheses. As for all phases of scientific inquiry, there are lots of things to think about. Because it is critical to start well, we devote Chap. 2 to getting started with formulating hypotheses.

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Hiebert, J., Cai, J., Hwang, S., Morris, A.K., Hohensee, C. (2023). What Is Research, and Why Do People Do It?. In: Doing Research: A New Researcher’s Guide. Research in Mathematics Education. Springer, Cham. https://doi.org/10.1007/978-3-031-19078-0_1

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Purpose Statement 

The purpose statement succinctly explains the objectives of the doctoral project or dissertation-in-practice. These objectives must directly address the problem. The purpose statement also identifies the project methodology and design.

A problem and a missing piece in combination can lead to different objectives, and hence, different purpose statements. 

The purpose of the applied doctoral project or dissertation-in-practice must not only align with the problem and address a missing piece; it must also align with the chosen project method. In fact, the template requires you to name the research method at the very beginning of the purpose statement. In general, quantitative studies involve “closed-ended” research verbs such as determine, measure, correlate, explain, compare, validate, identify, or examine; whereas qualitative studies involve “open-ended” research verbs such as explore, understand, narrate, articulate [meanings], discover, or develop.  

Qualitative Purpose Statement

A qualitative purpose statement following the color-coded problem statement (assumed here to be low well-being among financial sector employees) + missing piece (lack of research on followers of mid-level managers), might start like this: 

In response to declining levels of employee well-being, the purpose of the qualitative phenomenology was to explore and understand the lived experiences related to the well-being of the followers of novice mid-level managers in the financial services industry.  The levels of follower well-being have been shown to correlate to employee morale, turnover intention, and customer orientation (Eren et al., 2013).  A combined framework of Leader-Member Exchange (LMX) Theory and the employee well-being concept informed the research questions and supported the inquiry, analysis, and interpretation of the findings to be applied in the financial services industry.   

Quantitative Purpose Statement

A quantitative purpose statement for the same problem and gap might start like this: 

In response to declining levels of employee well-being, the purpose of the quantitative correlational study was to determine which leadership factors predict employee well-being of the followers of novice mid-level managers to be applied in the financial services industry. Leadership factors were measured by the Leader Member Exchange (LMX) assessment framework by Mantlekow (2015), and employee well-being was conceptualized as a compound variable consisting of self-reported turnover-intent and psychological test scores from the Mental Health Survey (MHS) developed by Johns Hopkins University researchers.  

Both of these purpose statements reflect viable research strategies and both align with the problem and gap so it’s up to the practitioner to design a doctoral project or dissertation-in-practice in a manner that reflects personal preferences and desired study outcomes. Note that the quantitative research purpose incorporates operationalized concepts, or variables; that reflect the way the practitioner intends to measure the key concepts under study; whereas the qualitative purpose statement isn’t about translating the concepts under study as variables but instead aim to explore and understand the core research phenomenon.

An important step in the successful completion of an Applied Doctoral Project/Dissertation in Practice is starting off with an accurate and precise purpose statement.  Read through the information below to get some general ideas or guidelines related to effective purpose statements and how to compose them.  All this information comes from faculty who want you to succeed in the process.

General Guidelines

Keep these in mind as you begin to compose your purpose statement

Good purpose statements:

• Flow from the problem statement and actually address the proposed problem
• Are concise and clear
• Answer the question ‘Why are you doing this project?’
• Match the methodology to your  questions
• Have a ‘hook’ to get the reader’s attention
• Set the stage by clearly stating, “The purpose of this (qualitative or quantitative) study is to ...”

Writing your Purpose Statement:

• The Problem Statement is why I am doing the project or dissertation-in-practice
• The Purpose Statement is what type of project or study I am doing to fit or address the problem

The Purpose Statement includes:

• Design and Method of Study
• Specific Population

Creswell (2002) suggested that purpose statements in qualitative projects or studies include deliberate phrasing to alert the reader to the purpose statement. Verbs are key to indicate what will take place in the project or study research and the use of non-directional language that does not suggest an outcome. A purpose statement should focus on a single idea or concept with a broad definition of that idea or concept. How the concept will be investigated should also be included, as well as participants in the study and study locations to give the reader a sense of with whom and where the project or study will occur.  

Creswell (2003) advised the following script for purpose statements in qualitative methodology:

“The purpose of this qualitative_________________ (strategy of inquiry, such as ethnography, case study, or other type) study is (was? will be?) to ________________ (understand? describe? develop? discover?) the _________________(central phenomenon being studied) for ______________ (the participants, such as the individual, groups, organization) at __________(site). At this stage in the project, the __________ (central phenomenon being studied) will be generally defined as ___________________ (provide a general definition)” (pg. 90).

Quantitative Purpose Statement

Creswell (2003) offers vast differences between the purpose statements written for qualitative methodology and those written for quantitative methodology, particularly with respect to language and the inclusion of variables. The comparison of variables is often a focus of quantitative methodology with the variables distinguishable by either the temporal order or how they are measured. As with qualitative purpose statements, Creswell (2003) recommends the use of deliberate language to alert the reader to the purpose of the project or study, though quantitative purpose statements also include the theory or conceptual framework guiding the project or study, the variables that are being studied, and how those variables are related.  

Creswell (2003) suggests the following script for drafting purpose statements in quantitative projects:

“The purpose of this _____________________ (experiment? survey?) project is (was? will be?) to test the theory of _________________that _________________ (compares? relates?) the ___________(independent variable) to _________________________(dependent variable), controlling for _______________________ (control variables) for ___________________ (participants) at _________________________ (site). The independent variable(s) _____________________ will be generally defined as _______________________ (provide a general definition). The dependent variable(s) will be generally defined as _____________________ (provide a general definition), and the control and intervening variables(s), _________________ (identify the control and intervening variables) will be statistically controlled in this project” (pg. 97).

Creswell, J. (2002). Educational research: Planning, conducting, and evaluating quantitative and qualitative research.  Merrill Prentice Hall. 7.  Creswell, J. (2003). Research design: Qualitative, quantitative and mixed methods approaches (2nd ed.).  SAGE Publications.

Always keep in mind that the process is iterative, and your writing, over time, will be refined as clarity is gradually achieved. Most of the time, greater clarity for the purpose statement and other components is the result of a growing understanding of the literature in the field. As you increasingly master the literature you will also increasingly clarify the purpose of your project or study. 

The purpose statement should flow directly from the problem statement. There should be clear and obvious alignment between the two, and that alignment will get tighter and more pronounced as your work progresses.

The purpose statement should specifically address the reason for conducting the project or study, with emphasis on the word specifically. There should not be any doubt in your readers’ minds as to the purpose of your project or study. To achieve this level of clarity, you will need to also ensure there is no doubt in your mind as to the purpose of your project or study. 

You may benefit from stopping your work during the process when insight strikes you in order to write about that insight while it is still fresh in your mind. This pause can help you clarify all aspects of the project or study, including clarifying its purpose. 

Your Chair and your committee members can help you to clarify the purpose of your project or dissertation-in-practice, so carefully attend to any feedback they offer.

The purpose statement should reflect the questions proposed and vice versa. The chain of alignment that began with the problem description and continues on to the purpose, questions, and methodology must be respected at all times during development. You are to succinctly describe the overarching goal of the project or dissertation-in-practice that reflects the questions. Each question narrows and focuses the purpose statement. Conversely, the purpose statement encompasses all of the questions. 

Identify in the purpose statement the methodology as quantitative, qualitative or mixed (i.e., “The purpose of this [qualitative/quantitative/mixed] study is to ...)

Follow the initial declaration of purpose with a brief overview of how the project or study will be conducted, including instruments, data, with whom (sample), and where (as applicable). Identify variables/constructs and/or phenomenon/concept/idea. Since this section is to be a concise paragraph, emphasis must be placed on the word brief. However, adding these details will give your readers a very clear picture of the purpose of your project or dissertation-in-practice.

Developing the purpose section is usually not achieved in a single flash of insight. The process involves a great deal of reading to find out what other practitioners have done to address the problem you have identified. The purpose section could well be the most important paragraph you write during your academic career, and every word should be carefully selected. Think of it as the DNA of your project or study. Everything else you write should emerge directly and clearly from your purpose statement. In turn, your purpose statement should emerge directly and clearly from your problem description. It is good practice to print out your problem statement and purpose statement and keep them in front of you as you work on each part of your project or dissertation-in-practice in order to ensure alignment.

It is helpful to collect several project or dissertation-in-practice reports or literature similar to the one you envision creating. Extract the problem descriptions and purpose statements of other authors and compare them in order to sharpen your thinking about your own work.  Comparing how other authors have handled the many challenges you are facing can be an invaluable exercise. Keep in mind that individual universities use their own tailored protocols for presenting key components, so your review of these purpose statements should focus on content rather than form.

Once your purpose statement is set, it must be consistently presented throughout the project or dissertation-in-practice. This consistency may require some recursive editing because the way you articulate your purpose may evolve as you work on various aspects of your project or dissertation-in-practice. Whenever you make an adjustment to your purpose statement, you should carefully follow up on the editing and conceptual ramifications throughout the entire document.

In establishing your purpose, you should NOT advocate for a particular outcome. Your review of the literature should be done to answer questions, not to prove a point. As a scholar-practitioner, you are to inquire with an open mind, and even when you come to the work with clear assumptions, your job is to support the validity of the conclusions reached. For example, you would not say the purpose of your project or study is to demonstrate that there is a relationship between two variables. Such a statement presupposes you know the answer before your review of the literature conducted and promotes or supports (advocates on behalf of) a particular outcome. A more appropriate purpose statement would be to examine or explore the relationship between two variables. 

Your purpose statement should not imply that you are going to prove something. You may be surprised to learn that we cannot prove anything in scholarly review of the literature for two reasons. First, in quantitative analyses, statistical tests calculate the probability that something is true rather than establishing it as true. Second, in qualitative methodology, the study can only purport to describe what is occurring from the perspective of the participants. Whether or not the phenomenon they are describing is true in a larger context is not knowable. We cannot observe the phenomenon in all settings and in all circumstances. 

Here are some example purpose statements for your consideration.

Purpose Statement 1

The purpose of this qualitative project was to determine how participation in service-learning in an alternative school impacted students academically, civically, and personally.  There is ample evidence demonstrating the failure of schools for students at-risk; however, there is still a need to demonstrate why these students are successful in non-traditional educational programs like the service-learning model used at TDS.  This study was unique in that it examined one alternative school’s approach to service-learning in a setting where students not only serve, but faculty serve as volunteer teachers.  The use of a constructivist approach in service-learning in an alternative school setting was examined in an effort to determine whether service-learning participation contributes positively to academic, personal, and civic gain for students, and to examine student and teacher views regarding the overall outcomes of service-learning.  This study was completed using an ethnographic approach that included observations, content analysis, and interviews with teachers at The David School.

Purpose Statement 2

The purpose of this quantitative, non-experimental, cross-sectional linear, multiple regression design study was to investigate the relationship among early childhood teachers’ self-reported assessment of multicultural awareness as measured by responses from the Teacher Multicultural Attitude Survey (TMAS) and supervisors’ observed assessment of teachers’ multicultural competency skills as measured by the Multicultural Teaching Competency Scale (MTCS) survey. Demographic data such as number of multicultural training hours, years teaching in Dubai, curriculum program at current school, and age were also examined and their relationship to multicultural teaching competency. The study took place in the emirate of Dubai where there were 14,333 expatriate teachers employed in private schools (KHDA, 2013b). 

Purpose Statement 3

The purpose of this quantitative, non-experimental project is to examine the degree to which stages of change, gender, acculturation level and trauma types predicts the reluctance of Arab refugees, aged 18 and over, in the Dearborn, MI area, to seek professional help for their mental health needs. This study will utilize four instruments to measure these variables: University of Rhode Island Change Assessment (URICA: DiClemente & Hughes, 1990); Cumulative Trauma Scale (Kira, 2012); Acculturation Rating Scale for Arabic Americans-II Arabic and English (ARSAA-IIA, ARSAA-IIE: Jadalla & Lee, 2013), and a demographic survey. This study will examine 1) the relationship between stages of change, gender, acculturation levels, and trauma types and Arab refugees’ help-seeking behavior, 2) the degree to which any of these variables can predict Arab refugee help-seeking behavior.  Additionally, the outcome of this study could provide researchers and clinicians with a stage-based model, TTM, for measuring Arab refugees’ help-seeking behavior and lay a foundation for how TTM can help target the clinical needs of Arab refugees. Lastly, this attempt to apply the TTM model to Arab refugees’ condition could lay the foundation for future research to investigate the application of TTM to clinical work among refugee populations.

Purpose Statement 4

The purpose of this qualitative, phenomenological project is to describe the lived experiences of LLM for 10 EFL learners in rural Guatemala and to utilize that data to determine how it conforms to, or possibly challenges, current theoretical conceptions of LLM. In accordance with Morse’s (1994) suggestion that a phenomenological study should utilize at least six participants, this study utilized semi-structured interviews with 10 EFL learners to explore why and how they have experienced the motivation to learn English throughout their lives. The methodology of horizontalization was used to break the interview protocols into individual units of meaning before analyzing these units to extract the overarching themes (Moustakas, 1994). These themes were then interpreted into a detailed description of LLM as experienced by EFL students in this context. Finally, the resulting description was analyzed to discover how these learners’ lived experiences with LLM conformed with and/or diverged from current theories of LLM.

Purpose Statement 5

The purpose of this qualitative, embedded, multiple case project was to examine how both parent-child attachment relationships are impacted by the quality of the paternal and maternal caregiver-child interactions that occur throughout a maternal deployment, within the context of dual-military couples. In order to examine this phenomenon, an embedded, multiple case study was conducted, utilizing an attachment systems metatheory perspective. The study included four dual-military couples who experienced a maternal deployment to Operation Iraqi Freedom (OIF) or Operation Enduring Freedom (OEF) when they had at least one child between 8 weeks-old to 5 years-old.  Each member of the couple participated in an individual, semi-structured interview with the researcher and completed the Parenting Relationship Questionnaire (PRQ). “The PRQ is designed to capture a parent’s perspective on the parent-child relationship” (Pearson, 2012, para. 1) and was used within the proposed study for this purpose. The PRQ was utilized to triangulate the data (Bekhet & Zauszniewski, 2012) as well as to provide some additional information on the parents’ perspective of the quality of the parent-child attachment relationship in regards to communication, discipline, parenting confidence, relationship satisfaction, and time spent together (Pearson, 2012). The researcher utilized the semi-structured interview to collect information regarding the parents' perspectives of the quality of their parental caregiver behaviors during the deployment cycle, the mother's parent-child interactions while deployed, the behavior of the child or children at time of reunification, and the strategies or behaviors the parents believe may have contributed to their child's behavior at the time of reunification. The results of this project may be utilized by the military, and by civilian providers, to develop proactive and preventive measures that both providers and parents can implement, to address any potential adverse effects on the parent-child attachment relationship, identified through the proposed study. The results of this project may also be utilized to further refine and understand the integration of attachment theory and systems theory, in both clinical and research settings, within the field of marriage and family therapy. 

Compiled by Dr. Darren Adamson, Department Chair, School of Social and Behavioral Sciences 

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What is Scientific Research and How Can it be Done?

Scientific researches are studies that should be systematically planned before performing them. In this review, classification and description of scientific studies, planning stage randomisation and bias are explained.

Research conducted for the purpose of contributing towards science by the systematic collection, interpretation and evaluation of data and that, too, in a planned manner is called scientific research: a researcher is the one who conducts this research. The results obtained from a small group through scientific studies are socialised, and new information is revealed with respect to diagnosis, treatment and reliability of applications. The purpose of this review is to provide information about the definition, classification and methodology of scientific research.

Before beginning the scientific research, the researcher should determine the subject, do planning and specify the methodology. In the Declaration of Helsinki, it is stated that ‘the primary purpose of medical researches on volunteers is to understand the reasons, development and effects of diseases and develop protective, diagnostic and therapeutic interventions (method, operation and therapies). Even the best proven interventions should be evaluated continuously by investigations with regard to reliability, effectiveness, efficiency, accessibility and quality’ ( 1 ).

The questions, methods of response to questions and difficulties in scientific research may vary, but the design and structure are generally the same ( 2 ).

Classification of Scientific Research

Scientific research can be classified in several ways. Classification can be made according to the data collection techniques based on causality, relationship with time and the medium through which they are applied.

• Observational
• Experimental
• Descriptive
• Retrospective
• Prospective
• Cross-sectional
• Social descriptive research ( 3 )

Another method is to classify the research according to its descriptive or analytical features. This review is written according to this classification method.

I. Descriptive research

• Case series
• Surveillance studies

II. Analytical research

• Observational studies: cohort, case control and cross- sectional research
• Interventional research: quasi-experimental and clinical research
• Case Report: it is the most common type of descriptive study. It is the examination of a single case having a different quality in the society, e.g. conducting general anaesthesia in a pregnant patient with mucopolysaccharidosis.
• Case Series: it is the description of repetitive cases having common features. For instance; case series involving interscapular pain related to neuraxial labour analgesia. Interestingly, malignant hyperthermia cases are not accepted as case series since they are rarely seen during historical development.
• Surveillance Studies: these are the results obtained from the databases that follow and record a health problem for a certain time, e.g. the surveillance of cross-infections during anaesthesia in the intensive care unit.

Moreover, some studies may be experimental. After the researcher intervenes, the researcher waits for the result, observes and obtains data. Experimental studies are, more often, in the form of clinical trials or laboratory animal trials ( 2 ).

Analytical observational research can be classified as cohort, case-control and cross-sectional studies.

Firstly, the participants are controlled with regard to the disease under investigation. Patients are excluded from the study. Healthy participants are evaluated with regard to the exposure to the effect. Then, the group (cohort) is followed-up for a sufficient period of time with respect to the occurrence of disease, and the progress of disease is studied. The risk of the healthy participants getting sick is considered an incident. In cohort studies, the risk of disease between the groups exposed and not exposed to the effect is calculated and rated. This rate is called relative risk. Relative risk indicates the strength of exposure to the effect on the disease.

Cohort research may be observational and experimental. The follow-up of patients prospectively is called a prospective cohort study . The results are obtained after the research starts. The researcher’s following-up of cohort subjects from a certain point towards the past is called a retrospective cohort study . Prospective cohort studies are more valuable than retrospective cohort studies: this is because in the former, the researcher observes and records the data. The researcher plans the study before the research and determines what data will be used. On the other hand, in retrospective studies, the research is made on recorded data: no new data can be added.

In fact, retrospective and prospective studies are not observational. They determine the relationship between the date on which the researcher has begun the study and the disease development period. The most critical disadvantage of this type of research is that if the follow-up period is long, participants may leave the study at their own behest or due to physical conditions. Cohort studies that begin after exposure and before disease development are called ambidirectional studies . Public healthcare studies generally fall within this group, e.g. lung cancer development in smokers.

• Case-Control Studies: these studies are retrospective cohort studies. They examine the cause and effect relationship from the effect to the cause. The detection or determination of data depends on the information recorded in the past. The researcher has no control over the data ( 2 ).

Cross-sectional studies are advantageous since they can be concluded relatively quickly. It may be difficult to obtain a reliable result from such studies for rare diseases ( 2 ).

Cross-sectional studies are characterised by timing. In such studies, the exposure and result are simultaneously evaluated. While cross-sectional studies are restrictedly used in studies involving anaesthesia (since the process of exposure is limited), they can be used in studies conducted in intensive care units.

• Quasi-Experimental Research: they are conducted in cases in which a quick result is requested and the participants or research areas cannot be randomised, e.g. giving hand-wash training and comparing the frequency of nosocomial infections before and after hand wash.
• Clinical Research: they are prospective studies carried out with a control group for the purpose of comparing the effect and value of an intervention in a clinical case. Clinical study and research have the same meaning. Drugs, invasive interventions, medical devices and operations, diets, physical therapy and diagnostic tools are relevant in this context ( 6 ).

Clinical studies are conducted by a responsible researcher, generally a physician. In the research team, there may be other healthcare staff besides physicians. Clinical studies may be financed by healthcare institutes, drug companies, academic medical centres, volunteer groups, physicians, healthcare service providers and other individuals. They may be conducted in several places including hospitals, universities, physicians’ offices and community clinics based on the researcher’s requirements. The participants are made aware of the duration of the study before their inclusion. Clinical studies should include the evaluation of recommendations (drug, device and surgical) for the treatment of a disease, syndrome or a comparison of one or more applications; finding different ways for recognition of a disease or case and prevention of their recurrence ( 7 ).

Clinical Research

In this review, clinical research is explained in more detail since it is the most valuable study in scientific research.

Clinical research starts with forming a hypothesis. A hypothesis can be defined as a claim put forward about the value of a population parameter based on sampling. There are two types of hypotheses in statistics.

• H 0 hypothesis is called a control or null hypothesis. It is the hypothesis put forward in research, which implies that there is no difference between the groups under consideration. If this hypothesis is rejected at the end of the study, it indicates that a difference exists between the two treatments under consideration.
• H 1 hypothesis is called an alternative hypothesis. It is hypothesised against a null hypothesis, which implies that a difference exists between the groups under consideration. For example, consider the following hypothesis: drug A has an analgesic effect. Control or null hypothesis (H 0 ): there is no difference between drug A and placebo with regard to the analgesic effect. The alternative hypothesis (H 1 ) is applicable if a difference exists between drug A and placebo with regard to the analgesic effect.

The planning phase comes after the determination of a hypothesis. A clinical research plan is called a protocol . In a protocol, the reasons for research, number and qualities of participants, tests to be applied, study duration and what information to be gathered from the participants should be found and conformity criteria should be developed.

The selection of participant groups to be included in the study is important. Inclusion and exclusion criteria of the study for the participants should be determined. Inclusion criteria should be defined in the form of demographic characteristics (age, gender, etc.) of the participant group and the exclusion criteria as the diseases that may influence the study, age ranges, cases involving pregnancy and lactation, continuously used drugs and participants’ cooperation.

The next stage is methodology. Methodology can be grouped under subheadings, namely, the calculation of number of subjects, blinding (masking), randomisation, selection of operation to be applied, use of placebo and criteria for stopping and changing the treatment.

I. Calculation of the Number of Subjects

The entire source from which the data are obtained is called a universe or population . A small group selected from a certain universe based on certain rules and which is accepted to highly represent the universe from which it is selected is called a sample and the characteristics of the population from which the data are collected are called variables. If data is collected from the entire population, such an instance is called a parameter . Conducting a study on the sample rather than the entire population is easier and less costly. Many factors influence the determination of the sample size. Firstly, the type of variable should be determined. Variables are classified as categorical (qualitative, non-numerical) or numerical (quantitative). Individuals in categorical variables are classified according to their characteristics. Categorical variables are indicated as nominal and ordinal (ordered). In nominal variables, the application of a category depends on the researcher’s preference. For instance, a female participant can be considered first and then the male participant, or vice versa. An ordinal (ordered) variable is ordered from small to large or vice versa (e.g. ordering obese patients based on their weights-from the lightest to the heaviest or vice versa). A categorical variable may have more than one characteristic: such variables are called binary or dichotomous (e.g. a participant may be both female and obese).

If the variable has numerical (quantitative) characteristics and these characteristics cannot be categorised, then it is called a numerical variable. Numerical variables are either discrete or continuous. For example, the number of operations with spinal anaesthesia represents a discrete variable. The haemoglobin value or height represents a continuous variable.

Statistical analyses that need to be employed depend on the type of variable. The determination of variables is necessary for selecting the statistical method as well as software in SPSS. While categorical variables are presented as numbers and percentages, numerical variables are represented using measures such as mean and standard deviation. It may be necessary to use mean in categorising some cases such as the following: even though the variable is categorical (qualitative, non-numerical) when Visual Analogue Scale (VAS) is used (since a numerical value is obtained), it is classified as a numerical variable: such variables are averaged.

Clinical research is carried out on the sample and generalised to the population. Accordingly, the number of samples should be correctly determined. Different sample size formulas are used on the basis of the statistical method to be used. When the sample size increases, error probability decreases. The sample size is calculated based on the primary hypothesis. The determination of a sample size before beginning the research specifies the power of the study. Power analysis enables the acquisition of realistic results in the research, and it is used for comparing two or more clinical research methods.

Because of the difference in the formulas used in calculating power analysis and number of samples for clinical research, it facilitates the use of computer programs for making calculations.

It is necessary to know certain parameters in order to calculate the number of samples by power analysis.

• Type-I (α) and type-II (β) error levels
• Difference between groups (d-difference) and effect size (ES)
• Distribution ratio of groups
• Direction of research hypothesis (H1)

a. Type-I (α) and Type-II (β) Error (β) Levels

Two types of errors can be made while accepting or rejecting H 0 hypothesis in a hypothesis test. Type-I error (α) level is the probability of finding a difference at the end of the research when there is no difference between the two applications. In other words, it is the rejection of the hypothesis when H 0 is actually correct and it is known as α error or p value. For instance, when the size is determined, type-I error level is accepted as 0.05 or 0.01.

Another error that can be made during a hypothesis test is a type-II error. It is the acceptance of a wrongly hypothesised H 0 hypothesis. In fact, it is the probability of failing to find a difference when there is a difference between the two applications. The power of a test is the ability of that test to find a difference that actually exists. Therefore, it is related to the type-II error level.

Since the type-II error risk is expressed as β, the power of the test is defined as 1–β. When a type-II error is 0.20, the power of the test is 0.80. Type-I (α) and type-II (β) errors can be intentional. The reason to intentionally make such an error is the necessity to look at the events from the opposite perspective.

b. Difference between Groups and ES

ES is defined as the state in which statistical difference also has clinically significance: ES≥0.5 is desirable. The difference between groups is the absolute difference between the groups compared in clinical research.

c. Allocation Ratio of Groups

The allocation ratio of groups is effective in determining the number of samples. If the number of samples is desired to be determined at the lowest level, the rate should be kept as 1/1.

d. Direction of Hypothesis (H1)

The direction of hypothesis in clinical research may be one-sided or two-sided. While one-sided hypotheses hypothesis test differences in the direction of size, two-sided hypotheses hypothesis test differences without direction. The power of the test in two-sided hypotheses is lower than one-sided hypotheses.

After these four variables are determined, they are entered in the appropriate computer program and the number of samples is calculated. Statistical packaged software programs such as Statistica, NCSS and G-Power may be used for power analysis and calculating the number of samples. When the samples size is calculated, if there is a decrease in α, difference between groups, ES and number of samples, then the standard deviation increases and power decreases. The power in two-sided hypothesis is lower. It is ethically appropriate to consider the determination of sample size, particularly in animal experiments, at the beginning of the study. The phase of the study is also important in the determination of number of subjects to be included in drug studies. Usually, phase-I studies are used to determine the safety profile of a drug or product, and they are generally conducted on a few healthy volunteers. If no unacceptable toxicity is detected during phase-I studies, phase-II studies may be carried out. Phase-II studies are proof-of-concept studies conducted on a larger number (100–500) of volunteer patients. When the effectiveness of the drug or product is evident in phase-II studies, phase-III studies can be initiated. These are randomised, double-blinded, placebo or standard treatment-controlled studies. Volunteer patients are periodically followed-up with respect to the effectiveness and side effects of the drug. It can generally last 1–4 years and is valuable during licensing and releasing the drug to the general market. Then, phase-IV studies begin in which long-term safety is investigated (indication, dose, mode of application, safety, effectiveness, etc.) on thousands of volunteer patients.

II. Blinding (Masking) and Randomisation Methods

When the methodology of clinical research is prepared, precautions should be taken to prevent taking sides. For this reason, techniques such as randomisation and blinding (masking) are used. Comparative studies are the most ideal ones in clinical research.

Blinding Method

A case in which the treatments applied to participants of clinical research should be kept unknown is called the blinding method . If the participant does not know what it receives, it is called a single-blind study; if even the researcher does not know, it is called a double-blind study. When there is a probability of knowing which drug is given in the order of application, when uninformed staff administers the drug, it is called in-house blinding. In case the study drug is known in its pharmaceutical form, a double-dummy blinding test is conducted. Intravenous drug is given to one group and a placebo tablet is given to the comparison group; then, the placebo tablet is given to the group that received the intravenous drug and intravenous drug in addition to placebo tablet is given to the comparison group. In this manner, each group receives both the intravenous and tablet forms of the drug. In case a third party interested in the study is involved and it also does not know about the drug (along with the statistician), it is called third-party blinding.

Randomisation Method

The selection of patients for the study groups should be random. Randomisation methods are used for such selection, which prevent conscious or unconscious manipulations in the selection of patients ( 8 ).

No factor pertaining to the patient should provide preference of one treatment to the other during randomisation. This characteristic is the most important difference separating randomised clinical studies from prospective and synchronous studies with experimental groups. Randomisation strengthens the study design and enables the determination of reliable scientific knowledge ( 2 ).

The easiest method is simple randomisation, e.g. determination of the type of anaesthesia to be administered to a patient by tossing a coin. In this method, when the number of samples is kept high, a balanced distribution is created. When the number of samples is low, there will be an imbalance between the groups. In this case, stratification and blocking have to be added to randomisation. Stratification is the classification of patients one or more times according to prognostic features determined by the researcher and blocking is the selection of a certain number of patients for each stratification process. The number of stratification processes should be determined at the beginning of the study.

As the number of stratification processes increases, performing the study and balancing the groups become difficult. For this reason, stratification characteristics and limitations should be effectively determined at the beginning of the study. It is not mandatory for the stratifications to have equal intervals. Despite all the precautions, an imbalance might occur between the groups before beginning the research. In such circumstances, post-stratification or restandardisation may be conducted according to the prognostic factors.

The main characteristic of applying blinding (masking) and randomisation is the prevention of bias. Therefore, it is worthwhile to comprehensively examine bias at this stage.

Bias and Chicanery

While conducting clinical research, errors can be introduced voluntarily or involuntarily at a number of stages, such as design, population selection, calculating the number of samples, non-compliance with study protocol, data entry and selection of statistical method. Bias is taking sides of individuals in line with their own decisions, views and ideological preferences ( 9 ). In order for an error to lead to bias, it has to be a systematic error. Systematic errors in controlled studies generally cause the results of one group to move in a different direction as compared to the other. It has to be understood that scientific research is generally prone to errors. However, random errors (or, in other words, ‘the luck factor’-in which bias is unintended-do not lead to bias ( 10 ).

Another issue, which is different from bias, is chicanery. It is defined as voluntarily changing the interventions, results and data of patients in an unethical manner or copying data from other studies. Comparatively, bias may not be done consciously.

In case unexpected results or outliers are found while the study is analysed, if possible, such data should be re-included into the study since the complete exclusion of data from a study endangers its reliability. In such a case, evaluation needs to be made with and without outliers. It is insignificant if no difference is found. However, if there is a difference, the results with outliers are re-evaluated. If there is no error, then the outlier is included in the study (as the outlier may be a result). It should be noted that re-evaluation of data in anaesthesiology is not possible.

Statistical evaluation methods should be determined at the design stage so as not to encounter unexpected results in clinical research. The data should be evaluated before the end of the study and without entering into details in research that are time-consuming and involve several samples. This is called an interim analysis . The date of interim analysis should be determined at the beginning of the study. The purpose of making interim analysis is to prevent unnecessary cost and effort since it may be necessary to conclude the research after the interim analysis, e.g. studies in which there is no possibility to validate the hypothesis at the end or the occurrence of different side effects of the drug to be used. The accuracy of the hypothesis and number of samples are compared. Statistical significance levels in interim analysis are very important. If the data level is significant, the hypothesis is validated even if the result turns out to be insignificant after the date of the analysis.

Another important point to be considered is the necessity to conclude the participants’ treatment within the period specified in the study protocol. When the result of the study is achieved earlier and unexpected situations develop, the treatment is concluded earlier. Moreover, the participant may quit the study at its own behest, may die or unpredictable situations (e.g. pregnancy) may develop. The participant can also quit the study whenever it wants, even if the study has not ended ( 7 ).

In case the results of a study are contrary to already known or expected results, the expected quality level of the study suggesting the contradiction may be higher than the studies supporting what is known in that subject. This type of bias is called confirmation bias. The presence of well-known mechanisms and logical inference from them may create problems in the evaluation of data. This is called plausibility bias.

Another type of bias is expectation bias. If a result different from the known results has been achieved and it is against the editor’s will, it can be challenged. Bias may be introduced during the publication of studies, such as publishing only positive results, selection of study results in a way to support a view or prevention of their publication. Some editors may only publish research that extols only the positive results or results that they desire.

Bias may be introduced for advertisement or economic reasons. Economic pressure may be applied on the editor, particularly in the cases of studies involving drugs and new medical devices. This is called commercial bias.

In recent years, before beginning a study, it has been recommended to record it on the Web site www.clinicaltrials.gov for the purpose of facilitating systematic interpretation and analysis in scientific research, informing other researchers, preventing bias, provision of writing in a standard format, enhancing contribution of research results to the general literature and enabling early intervention of an institution for support. This Web site is a service of the US National Institutes of Health.

The last stage in the methodology of clinical studies is the selection of intervention to be conducted. Placebo use assumes an important place in interventions. In Latin, placebo means ‘I will be fine’. In medical literature, it refers to substances that are not curative, do not have active ingredients and have various pharmaceutical forms. Although placebos do not have active drug characteristic, they have shown effective analgesic characteristics, particularly in algology applications; further, its use prevents bias in comparative studies. If a placebo has a positive impact on a participant, it is called the placebo effect ; on the contrary, if it has a negative impact, it is called the nocebo effect . Another type of therapy that can be used in clinical research is sham application. Although a researcher does not cure the patient, the researcher may compare those who receive therapy and undergo sham. It has been seen that sham therapies also exhibit a placebo effect. In particular, sham therapies are used in acupuncture applications ( 11 ). While placebo is a substance, sham is a type of clinical application.

Ethically, the patient has to receive appropriate therapy. For this reason, if its use prevents effective treatment, it causes great problem with regard to patient health and legalities.

Before medical research is conducted with human subjects, predictable risks, drawbacks and benefits must be evaluated for individuals or groups participating in the study. Precautions must be taken for reducing the risk to a minimum level. The risks during the study should be followed, evaluated and recorded by the researcher ( 1 ).

After the methodology for a clinical study is determined, dealing with the ‘Ethics Committee’ forms the next stage. The purpose of the ethics committee is to protect the rights, safety and well-being of volunteers taking part in the clinical research, considering the scientific method and concerns of society. The ethics committee examines the studies presented in time, comprehensively and independently, with regard to ethics and science; in line with the Declaration of Helsinki and following national and international standards concerning ‘Good Clinical Practice’. The method to be followed in the formation of the ethics committee should be developed without any kind of prejudice and to examine the applications with regard to ethics and science within the framework of the ethics committee, Regulation on Clinical Trials and Good Clinical Practice ( www.iku.com ). The necessary documents to be presented to the ethics committee are research protocol, volunteer consent form, budget contract, Declaration of Helsinki, curriculum vitae of researchers, similar or explanatory literature samples, supporting institution approval certificate and patient follow-up form.

Only one sister/brother, mother, father, son/daughter and wife/husband can take charge in the same ethics committee. A rector, vice rector, dean, deputy dean, provincial healthcare director and chief physician cannot be members of the ethics committee.

Members of the ethics committee can work as researchers or coordinators in clinical research. However, during research meetings in which members of the ethics committee are researchers or coordinators, they must leave the session and they cannot sign-off on decisions. If the number of members in the ethics committee for a particular research is so high that it is impossible to take a decision, the clinical research is presented to another ethics committee in the same province. If there is no ethics committee in the same province, an ethics committee in the closest settlement is found.

Thereafter, researchers need to inform the participants using an informed consent form. This form should explain the content of clinical study, potential benefits of the study, alternatives and risks (if any). It should be easy, comprehensible, conforming to spelling rules and written in plain language understandable by the participant.

This form assists the participants in taking a decision regarding participation in the study. It should aim to protect the participants. The participant should be included in the study only after it signs the informed consent form; the participant can quit the study whenever required, even when the study has not ended ( 7 ).

Peer-review: Externally peer-reviewed.

Author Contributions: Concept - C.Ö.Ç., A.D.; Design - C.Ö.Ç.; Supervision - A.D.; Resource - C.Ö.Ç., A.D.; Materials - C.Ö.Ç., A.D.; Analysis and/or Interpretation - C.Ö.Ç., A.D.; Literature Search - C.Ö.Ç.; Writing Manuscript - C.Ö.Ç.; Critical Review - A.D.; Other - C.Ö.Ç., A.D.

Conflict of Interest: No conflict of interest was declared by the authors.

Financial Disclosure: The authors declared that this study has received no financial support.

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How to Write the Rationale of the Study in Research (Examples)

What is the Rationale of the Study?

The rationale of the study is the justification for taking on a given study. It explains the reason the study was conducted or should be conducted. This means the study rationale should explain to the reader or examiner why the study is/was necessary. It is also sometimes called the “purpose” or “justification” of a study. While this is not difficult to grasp in itself, you might wonder how the rationale of the study is different from your research question or from the statement of the problem of your study, and how it fits into the rest of your thesis or research paper. 

The rationale of the study links the background of the study to your specific research question and justifies the need for the latter on the basis of the former. In brief, you first provide and discuss existing data on the topic, and then you tell the reader, based on the background evidence you just presented, where you identified gaps or issues and why you think it is important to address those. The problem statement, lastly, is the formulation of the specific research question you choose to investigate, following logically from your rationale, and the approach you are planning to use to do that.

Table of Contents:

How to write a rationale for a research paper , how do you justify the need for a research study.

• Study Rationale Example: Where Does It Go In Your Paper?

The basis for writing a research rationale is preliminary data or a clear description of an observation. If you are doing basic/theoretical research, then a literature review will help you identify gaps in current knowledge. In applied/practical research, you base your rationale on an existing issue with a certain process (e.g., vaccine proof registration) or practice (e.g., patient treatment) that is well documented and needs to be addressed. By presenting the reader with earlier evidence or observations, you can (and have to) convince them that you are not just repeating what other people have already done or said and that your ideas are not coming out of thin air. 

Once you have explained where you are coming from, you should justify the need for doing additional research–this is essentially the rationale of your study. Finally, when you have convinced the reader of the purpose of your work, you can end your introduction section with the statement of the problem of your research that contains clear aims and objectives and also briefly describes (and justifies) your methodological approach. 

When is the Rationale for Research Written?

The author can present the study rationale both before and after the research is conducted. 

• Before conducting research : The study rationale is a central component of the research proposal . It represents the plan of your work, constructed before the study is actually executed.
• Once research has been conducted : After the study is completed, the rationale is presented in a research article or  PhD dissertation  to explain why you focused on this specific research question. When writing the study rationale for this purpose, the author should link the rationale of the research to the aims and outcomes of the study.

What to Include in the Study Rationale

Although every study rationale is different and discusses different specific elements of a study’s method or approach, there are some elements that should be included to write a good rationale. Make sure to touch on the following:

• A summary of conclusions from your review of the relevant literature
• What is currently unknown (gaps in knowledge)
• Inconclusive or contested results  from previous studies on the same or similar topic
• The necessity to improve or build on previous research, such as to improve methodology or utilize newer techniques and/or technologies

There are different types of limitations that you can use to justify the need for your study. In applied/practical research, the justification for investigating something is always that an existing process/practice has a problem or is not satisfactory. Let’s say, for example, that people in a certain country/city/community commonly complain about hospital care on weekends (not enough staff, not enough attention, no decisions being made), but you looked into it and realized that nobody ever investigated whether these perceived problems are actually based on objective shortages/non-availabilities of care or whether the lower numbers of patients who are treated during weekends are commensurate with the provided services.

In this case, “lack of data” is your justification for digging deeper into the problem. Or, if it is obvious that there is a shortage of staff and provided services on weekends, you could decide to investigate which of the usual procedures are skipped during weekends as a result and what the negative consequences are. 

In basic/theoretical research, lack of knowledge is of course a common and accepted justification for additional research—but make sure that it is not your only motivation. “Nobody has ever done this” is only a convincing reason for a study if you explain to the reader why you think we should know more about this specific phenomenon. If there is earlier research but you think it has limitations, then those can usually be classified into “methodological”, “contextual”, and “conceptual” limitations. To identify such limitations, you can ask specific questions and let those questions guide you when you explain to the reader why your study was necessary:

Methodological limitations

• Did earlier studies try but failed to measure/identify a specific phenomenon?
• Was earlier research based on incorrect conceptualizations of variables?
• Were earlier studies based on questionable operationalizations of key concepts?
• Did earlier studies use questionable or inappropriate research designs?

Contextual limitations

• Have recent changes in the studied problem made previous studies irrelevant?
• Are you studying a new/particular context that previous findings do not apply to?

Conceptual limitations

• Do previous findings only make sense within a specific framework or ideology?

Study Rationale Examples

Let’s look at an example from one of our earlier articles on the statement of the problem to clarify how your rationale fits into your introduction section. This is a very short introduction for a practical research study on the challenges of online learning. Your introduction might be much longer (especially the context/background section), and this example does not contain any sources (which you will have to provide for all claims you make and all earlier studies you cite)—but please pay attention to how the background presentation , rationale, and problem statement blend into each other in a logical way so that the reader can follow and has no reason to question your motivation or the foundation of your research.

Background presentation

Since the beginning of the Covid pandemic, most educational institutions around the world have transitioned to a fully online study model, at least during peak times of infections and social distancing measures. This transition has not been easy and even two years into the pandemic, problems with online teaching and studying persist (reference needed) . 

While the increasing gap between those with access to technology and equipment and those without access has been determined to be one of the main challenges (reference needed) , others claim that online learning offers more opportunities for many students by breaking down barriers of location and distance (reference needed) .  

Rationale of the study

Since teachers and students cannot wait for circumstances to go back to normal, the measures that schools and universities have implemented during the last two years, their advantages and disadvantages, and the impact of those measures on students’ progress, satisfaction, and well-being need to be understood so that improvements can be made and demographics that have been left behind can receive the support they need as soon as possible.

Statement of the problem

To identify what changes in the learning environment were considered the most challenging and how those changes relate to a variety of student outcome measures, we conducted surveys and interviews among teachers and students at ten institutions of higher education in four different major cities, two in the US (New York and Chicago), one in South Korea (Seoul), and one in the UK (London). Responses were analyzed with a focus on different student demographics and how they might have been affected differently by the current situation.

How long is a study rationale?

In a research article bound for journal publication, your rationale should not be longer than a few sentences (no longer than one brief paragraph). A  dissertation or thesis  usually allows for a longer description; depending on the length and nature of your document, this could be up to a couple of paragraphs in length. A completely novel or unconventional approach might warrant a longer and more detailed justification than an approach that slightly deviates from well-established methods and approaches.

Consider Using Professional Academic Editing Services

Now that you know how to write the rationale of the study for a research proposal or paper, you should make use of our free AI grammar checker , Wordvice AI, or receive professional academic proofreading services from Wordvice, including research paper editing services and manuscript editing services to polish your submitted research documents.

You can also find many more articles, for example on writing the other parts of your research paper , on choosing a title , or on making sure you understand and adhere to the author instructions before you submit to a journal, on the Wordvice academic resources pages.

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The Purpose of the Study should b e a clear and accurate statement of the scientific purpose/objectives of the research.  

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Purpose of the Study

The Purpose of the Study statement helps the subject assess the importance of the study relative to individual values.   The statement should include not only the immediate purpose of the study, but also any larger, eventual purpose.     

The Purpose of the Study portion of the Consent Form should not reflect a potential benefit to the subject or be directed toward the subject in any way.   For example, “the purpose of this study is to compare the effectiveness of exercise A to exercise B as a method that can be used to increase quadriceps muscle” is acceptable.   However, a statement, “the purpose of this study is to compare the effectiveness of exercise A to exercise B as a method that can be used to increase your quadriceps muscle” is unacceptable.  

If the study involves deception or the withholding of information as a necessary and justifiable research strategy, the Purpose of the Study statement should be written in such a way whereby the least possible deception and/or withholding of information occurs.    

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• Open access
• Published: 31 March 2024

Association between sociodemographic factors and health beliefs related to breast cancer screening behavior among Northern Thai women: a hospital-based study

• Surin Jiraniramai 1 , 2 ,
• Kanokporn Pinyopornpanish 1 , 2 ,
• Nahathai Wongpakaran 3 ,
• Chaisiri Angkurawaranon 1 , 2 ,
• Victoria L. Champion 4 , 5 ,
• Imjai Chitapanarux 6 ,
• Wichuda Jiraporncharoen 1 , 2 &
• Tinakon Wongpakaran 3  

Scientific Reports volume  14 , Article number:  7596 ( 2024 ) Cite this article

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• Health services
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Early diagnosis of breast cancer is crucial for reducing mortality rates. The purpose of this study is to determine the impact of demographics/social determinants of health on beliefs about the practice of self-breast examination, using mammogram and ultrasound in the context of breast cancer screening among Thai women in a hospital-based setting for implying program planning and future research. A cross-sectional study was conducted in two health centers in Chiang Mai Province from August 2021 to December 2021, involving 130 Thai women ages 40 to 70 years. Data were collected by a survey using a questionnaire to gather sociodemographic information, and health beliefs about breast cancer and screening behavior utilizing the modified Thai version of Champion's Health Belief Model Scale (MT-CHBMS). Descriptive statistics, t-tests, ANOVA, and linear regression models were employed for examining association between sociodemographic factors and health beliefs about the practice of self-breast examination (BSE), using mammogram (MG) and ultrasound (UTS). Health insurance schemes were associated with Benefit-MG, Barrier-BSE, Barrier-MG and Barrier-UTS subscales. Additionally, monthly income was associated with Barrier-MG and Barrier-UTS subscales. The most common barriers reported were “embarrassment”, “worry”, and “takes too much time”. To enhance breast cancer screening in Thailand, program planning and future research should focus on health insurance schemes, especially women with social security schemes, as they may be the most appropriate target group for intervention.

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Introduction

Female breast cancer is the most commonly diagnosed cancer, with approximately 2.3 million new cases and 685,000 deaths reported in 2020 1 . It is the leading or second leading cause of female cancer-related deaths in 95% of countries worldwide 2 . In 2022, breast cancer in Thailand accounted for 38,559 cases 3 , making it the most prevalent female cancer, and accounting for 32.64% of the top five cancers in the northern region of Thailand 4 . This region has been predicted to have the highest age-standardized incidence rate (ASR) and proportion of female cancer cases by 2025 5 . However, early diagnosis and treatment can significantly reduce breast cancer mortality rates and improve women's overall health 6 .

Globally, high-income countries have adopted mammography as the standard screening method for early diagnosis of breast cancer, which helps reduce rates of advanced and fatal breast cancer 7 . In contrast, low to moderate-income countries, including Thailand 8 , 9 , 10 , often rely on breast self-examination (BSE) due to its insufficient mammography resources, although it is considered less reliable 11 , 12 , 13 . Therefore, it is recommended that women regularly and accurately perform BSE and consult with their physicians, who might recommend mammography and/or ultrasound if a lump is found 9 . It's important to note that BSE alone is not an effective method for reducing breast cancer mortality 14 . However, a recent population-based study of 1,906,697 women participating in a breast cancer awareness program in Thailand reported that women who regularly practiced BSE had better survival rates compared to non-practicing women. Additionally, a significantly higher proportion of smaller tumor sizes and earlier stages of breast cancer were observed in the group that regularly performed BSE. This positive outcome was attributed to the strong collaboration between village health volunteers and the use of BSE record booklets. Village health volunteers played a vital role in reminding women to perform BSE consistently, while the BSE record booklets helped women accurately follow the instructions and document their BSE practices 15 . Many countries of low to moderate-income countries have BSE practice as the first line screening because it is easy, convenient, private safe and no specific equipment requirement. Its purpose is to make women familiar with both the appearance and feel of their breasts as early as possible, so that they will be able to easily detect changes in their breast 13 , 16 . The more practice of BSE, the more empower women health 8 , 13 , 17 Based on these evidence, initial BSE is deemed appropriate for Thailand as a low to moderate-income country. The practice of BSE among women is influenced by their knowledge and beliefs about breast cancer and screening methods 17 .

In Thailand, the current guidelines for breast cancer screening 18 include breast cancer screening according to age. For ages 20–39 years old, it is recommended that breast self-examination should be performed once a month. Women between 40 and 69 years should be examined by a doctor annually. If abnormalities are identified, a mammogram will be scheduled. For the age of 70 years old and over, mammography for breast cancer screening should be weighed in terms of benefits and risks based on individual’s life expectancy and preference. However, in the voluntary case of populations who wish to have breast cancer screening by mammogram in the first place, recommendations for screening have been added that are similar to those recommended by the American Cancer Society. This recommendation was caused by public health policy and public finance management in Thailand.

In some resource-limited areas, breast ultrasound has been proposed as a possible alternative for mammography in breast cancer screening because it is portable, less expensive than mammography, and versatile across a wider range of clinical applications. The use of ultrasound as an effective primary detection tool for breast cancer may be beneficial in low-resource settings where mammography is unavailable 19 . Furthermore, according to the findings of a multi-center randomized trial comparing ultrasound vs. mammography for screening breast cancer in high-risk Chinese women, ultrasound was superior to mammography for screening breast cancer in this group 19 . In Thailand, mammography is not available in most rural areas. Similarly, Thai women, like Chinese women, have smaller and denser breasts than Western women 20 . Additionally, ultrasound yields less pain or discomfort than a mammogram, which is one of the main problems preventing women from breast cancer screening. 21 .

In real-world practice, BSE is not widely adopted among most Thai women. From secondary data of the 2007 Health and Welfare Survey that comprised 18,474 women aged 20 years and older and the 2009 Reproductive Health Survey that comprised 26,951 women aged 30 to 59 years show that only 18.4% of women practice monthly BSE 21 , indicating a low level of knowledge and awareness about breast cancer and the importance of BSE, mammography, and ultrasound screening that are the steps for increasing diagnosis of breast cancer. Before planning effective interventions to motivate the use of these screening methods, it is important to understand Thai women's knowledge and beliefs about breast cancer screening. Previous studies have shown that the Health Belief Model is a reliable and valid tool for measuring individuals' knowledge and beliefs about breast cancer and screening methods 22 . This model predicts the behaviors of people who take action to prevent, screen for, or control illness conditions based on their personal beliefs or perceptions about a disease 23 . Champion's Health Belief Model Scale (CHBMS) is the first and most widely used tool in the literature across continents, countries, cultures, and ethnicities to measure women's beliefs about breast cancer screening 8 , 24 , 25 , 26 , 27 , 28 , 29 .

The CHBMS comprises six main constructs: susceptibility, seriousness, benefits, barriers, health motivation, and confidence (self-efficacy). This scale has also been developed to assess perceived benefits and barriers of BSE and mammogram screening 25 , 26 , 27 , 29 , 30 , 31 . Recently, a modified Thai version of Champion's Health Belief Model Scale (MT-CHBMS) 32 incorporated ultrasound items for breast cancer screening. The primary reason for this addition is that ultrasound can effectively detect small and dense tissue tumors, particularly in younger Asian women who tend to have denser breast tissue compared to Western women 19 . In terms of advanced technology, techniques such as artificial intelligence (e.g., deep-learning-enabled clinical decision support systems) and classification of ultrasound images have demonstrated superior accuracy in detecting breast cancers compared to various screening tools currently available 33 , 34 . The MT-CHBMS has been found to be valid and reliable among Thai women 32 . This scale can be comparing perceived benefits and barriers of BSE, mammogram and ultrasound screening from associate predictors of sociodemographic factors. These predictors could be implying the program design for increasing breast cancer screening.

Numerous studies have demonstrated the significant impact of sociodemographic factors on women's breast cancer screening behaviors, with results varying across cultures and values. For instance, research conducted in Middle Eastern countries revealed notable associations between age, title, giving birth, BC screening in the last 6 months, BSE training, chronic disease, mental illness, and BSE practice 35 . Conversely, a study in a similar cultural context showed that BSE and mammography practices among women were influenced by the only level of their knowledge about breast cancer 36 . In an African country, a study found significant associations between income status, marital status, age of first childbirth in the family, and perceived susceptibility, health motivation, convenience, perceived benefits, and self-efficacy for BSE 37 .

Despite these findings, there is currently a lack of information regarding the health perception of Thai women, the scope of their health beliefs, and how demographics/social determinants impact these beliefs. Additionally, these results have been integrated to plan for detecting and managing for breast cancer in primary care of hospital that is the one of strategic in Thailand’s sustainable development goals 38 , 39 . Therefore, the objective of this study is to determine the impact of demographics/social determinants of health on beliefs about the practice of self-breast examination, using mammogram and ultrasound in the context of breast cancer screening among Thai women in a hospital-based setting for implying program planning and future research.

Study design and participants

A cross-sectional study was conducted in Chiang Mai province, Kingdom of Thailand, from August 2021 to December 2021. One hundred and thirty participants recruited with convenience sampling method for the study, consisting of women from two health centers: Maharaj Nakorn Chiang Mai Hospital, located in an urban area, and San Pa Tong Hospital, situated in a rural area. A comprehensive description of the development of the MT-CHBMS has been previously published 32 .

Inclusion and exclusion criteria

The inclusion criteria for the study were as follows: individuals between the ages of 40 and 70 years (the recommended age for mammograms), no prior history of breast cancer or any other types of cancer, and not currently pregnant or breastfeeding. The exclusion criteria included individuals who were unable to communicate effectively due to language barriers and those who expressed unwillingness to complete the questionnaires.

Sample size

Sample size is calculated based on the following criteria.

Anticipated effect size ( f 2 ) was 0.15 (small). The desired statistical power level was 0.8

The number of predictors was 5. Therefore, the minimum required sample was 91. We recruited 130 participants for this study, indicating that it was sufficient.

The data collection tools

To collect data at the outpatient clinic, the researchers gathered socio-economic information by structured interviewing. The questions included items such as age, religion, marital status, education level, healthcare insurance schemes (including the three main public health insurance schemes: government or state enterprise officer, social security scheme, and universal coverage scheme), income, and residential area. Then paper questionnaires were provided to all participants. Prior to completing the questionnaires, all participants provided written informed consent.

The questionnaire addressing beliefs was the MT-CHBMS. The CHBMS was translated into Thai, validated by a panel of experts, back translated, modified by adding content about ultrasound for screening breast cancer, and pretested. Confirmatory factor analysis was used with a sample of 130 Thai women aged 40 to 70 years old. The scales were measured with an ordinal scale using a five-point Likert type 1: “Strongly disagree”, to 5: “Strongly agree”. Each subscale can be used independently. In the case of overall assessment of the awareness of breast cancer and screening methods, the total score can be adopted but the questions concerning barriers must be reversed before summing up.

The MT-CHBMS’s Cronbach’s alphas values were acceptable, ranging from 0.74 to 0.93 for the scales)and valid(Content validity using the CVI index from 3 experts showed that the average Item-CVI was 1.00, all factor loading coefficients in the confirmatory factor analysis were significant(p < 0.001) and ranged from 0.413 to 1.029) tool for measuring the Health Belief Model related to the practice of breast self-examination (BSE), as well as investigating attitudes towards mammograms and ultrasounds 32 . The confirmatory factor analysis results of the CHBMS and MT-CHBMS. Each item had sufficient factor loadings (estimated coefficients) on the designated factor. All factor loading coefficients were significant ( p  < 0.001) and ranged from 0.413 to 1.029. The fit statistics were assessed to demonstrate how well the CFA model fitted the data. For the model MT-CHBM: chi-square = 2488.868, df = 1879, chi-square/df = 1.324, TLI = 0.961, CFI = 0.964, and RMSEA (90% CI) = 0.050(0.045–0.055). Except for the motivation subscale, 21 pairs of error terms in each subscale of T-CHBMS and 23 pairs of error terms of MT-CHBMS were correlated. All these error terms suggested a high correlation between items and became the potential sources of the model misfit.

The questionnaire consisted of 64 items distributed among 10 subscales: susceptibility (5 items), seriousness (7 items), benefits of BSE (6 items), barriers to BSE (6 items), benefits of mammogram (6 items), barriers to mammogram (5 items), benefits of ultrasound (6 items), barriers to ultrasound (5 items), confidence (11 items), and health motivation (7 items). All items were formatted using an ordinal scale with a 5-point Likert scale response: 1 = "Strongly disagree," 2 = "Disagree," 3 = "Neutral," 4 = "Agree," and 5 = "Strongly agree" for positive statements. Each subscale can be utilized independently. However, when conducting an overall assessment of awareness regarding breast cancer and screening methods, the total score may be used. It's important to note that questions pertaining to barriers must be reversed before summing up the scores.

Statistical analysis

The data were analysed using Stata version 15.0. Descriptive statistics, including mean, standard deviation (SD), frequency, and percentages, were used to describe the data. Internal consistency of the items within the health belief subscales was assessed using Cronbach's alpha. The association and comparison of items within the health belief subscales and across other variables were analysed using t-tests, analysis of variance (ANOVA), and linear regression models.

Ethical approval and consent to participate

This study was conducted in accordance with the Declaration of Helsinki and under the review and approval of the Institutional Research Ethics Committee of the Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand (No. FAM 2564-08138) and Sanpatong Hospital Ethics Committee (No. SPT/REC 012/2564). All procedures were conducted following the relevant institutional guidelines and regulations.

Distribution of sociodemographic factors of women (n = 130)

The sociodemographic characteristics of the 130 participants are presented in Table 1 . The average age of the participants was 52.33 years (SD = 7.28). The majority of participants were single (61.54%). About 37.69% of the participants had attained a college-level education, while 51.54% had a monthly income exceeding 10,000 Baht (270 US dollars). Additionally, 41.54% of the participants had health insurance schemes through government or state enterprise officers.

Distribution statistical data and Cronbach’s alphas for MT-CHBMS

Table 2 presents the mean ranged from 2.46 to 4.35 and SD ranged from 3.56 to 8.00. The overall Cronbach's alphas for the health belief model subscales were found to be within an acceptable range (0.70 or higher), indicating good internal consistency 40 .

Comparison of sociodemographic factors with MT-CHBMS

Table 3 presents the results of the statistical analyses conducted on various sociodemographic factors and their associations with the Health Belief Model subscales.

Participants with education less than secondary school exhibited higher scores in the Seriousness subscale compared to other education level groups ( F  = 3.44, p  = 0.035). Participants with a college educational level had higher scores in the Barrier-BSE subscale compared to other education level groups ( F  = 5.32, p  = 0.006).

In terms of monthly income, participants in the lower 10,000 Baht income group demonstrated higher scores in the Seriousness subscale compared to the more than 10,000 Baht income group ( t  = 2.43, p  = 0.017). Conversely, the more than 10,000 Baht income group had higher scores in the Barrier-BSE and Barrier-UTS subscales compared to the lower 10,000 Baht income group ( t  =  − 2.71, p  = 0.008 and t  =  − 2.64, p  = 0.009).

Participants with health insurance schemes through government or state enterprise officer schemes exhibited higher scores in the Barrier-BSE and Barrier-UTS subscales compared to other groups ( F  = 8.50, p  = 0.001 and F  = 6.85, p  = 0.002). Additionally, participants with health insurance schemes through government or state enterprise officer schemes and those covered under the universal coverage scheme had higher scores in the Barrier-MG subscale compared to the social security scheme group ( F  = 5.94, p  = 0.003).

Multiple linear regression model of MT-CHBMS

Table 4 presents the results of multiple linear regression analysis. None of the factors were found to be significant associated with of Seriousness subscale. However, health insurance schemes were found to be a significant associated with of the Benefit-MG and Barrier-BSE (β m  =  − 2.48, P = 0.023 and β m  =  − 3.38, P = 0.008, respectively). Both monthly income and health insurance schemes were significant associated with of the Barrier-MG and Barrier-UTS (β m  = 2.65, P = 0.008, β h  =  − 3.11, P = 0.002 and β m  = 2.49, P = 0.013, β h  =  − 3.40, P = 0.001, respectively).

BM= item from benefit to mammogram, BARB = item from barrier to breast self-examination, BARM = item from barrier to mammogram, BAU = item from barrier of ultrasound.

Comparison of monthly income and health insurance schemes with the significant subscales of MT-CHBMS

To delve deeper into the specifics, each subscale item, including those related to the benefits and barriers of mammograms, breast self-examination, and ultrasound, was compared among different monthly income groups and health insurance schemes using t-tests and ANOVA analyses (Table 5 ). For the Barrier-BSE subscale, the group with an income of 10,000 Baht or more demonstrated higher scores in Barrier-BSE compared to the less than 10,000 Baht income group across the BARB1 (funny), BARB3 (embarrassing), and BARB5 (unpleasant) items. Additionally, participants with health insurance schemes through government or state enterprise officer schemes exhibited higher scores in Barrier-BSE compared to other groups across all BARB (1–6) items.

Regarding the Barrier-MG subscale, participants with health insurance schemes through government or state enterprise officer schemes had higher scores in Barrier-MG compared to other groups across the BARM1 (worry), BARM2 (embarrassing), and BARM3 (take too much time) items.

In terms of the Barrier-UTS subscale, the group with an income of 10,000 Baht or more demonstrated higher scores in barrier-UTS compared to the less than 10,000 Baht income group across the BAU1 (worry), BAU2 (embarrassing), and BAU5 (cost too much money) items. Additionally, participants with health insurance schemes through government or state enterprise officer schemes had higher scores in Barrier-UTS compared to other groups across the BAU2 (embarrassing), BAU3 (take too much time), and BAU4 (painful) items.

The objective of the study was to investigate differences in beliefs related to breast examination among various sociodemographic variables in Thai women, and the results have confirmed their presence.

Using multiple linear regression analysis with the MT-CHBMS, the results indicated several findings. Health insurance schemes were associated with Benefit-MG, Barrier-BSE, Barrier-MG and Barrier-UTS subscales. Additionally, monthly income showed associations with the Barrier-MG and Barrier-UTS subscales. The most common barriers reported by participants were feeling “embarrassed”, “worry”, and feeling that it “takes too much time”.

Unlike population-based studies, the current study reveals a distinct finding: health beliefs were not associated with age, marital status, and education. This contrasts with findings from other related studies, such as those involving Turkish and Iranian women, where age, marital status, and education were significantly correlated with health beliefs scales. 41 , 42 .

Interestingly, our study observed that distinct income groups were associated with varying outcomes in the Barriers-MG and Barriers-UTS subscales. Notably, there is a dearth of similar literature available for direct comparison. However, Kirag and Kizilkaya et al. 35 reported correlations between income levels and Benefit-BSE, Barriers-BSE, Self-efficacy, and Benefit MG, while Altunkurek and Hassan Mohamed 37 also identified a relationship between income status and the Susceptibility and Health Motivation subscales. The connection between lower income and barriers to BSE is not easily explained. It is possible that there are intermediary variables requiring further investigation.

According to the Health Belief Model, perceived barriers have consistently been identified as the most influential predictor in various studies for practicing BSE and mammography 43 . Recent studies have also shown that perceiving more benefits, having higher confidence, and experiencing fewer barriers are positively associated with BSE practice 16 , 44 , 45 . Similarly, perceiving more benefits and fewer barriers is positively associated with mammography 44 . In this study, it was found that the social security scheme associated with Barrier-BSE, Barrier-MG and Barrier-UTS. In addition, the social security scheme had lower scores than the government or state enterprise officer and universal coverage scheme in the barrier to BSE, barrier to mammogram, and barrier to ultrasound subscales. It is to note that the government or state enterprise officer scheme beneficiaries benefit from a higher level of healthcare coverage compared to the other two schemes. It offers a high level of coverage and includes access to government hospitals and medical facilities. This scheme beneficiaries typically have access to a comprehensive range of medical services, often with little or no out-of-pocket expenses. The scheme provides coverage for both routine healthcare and specialized treatments, including access to government-run healthcare facilities. The social security scheme members often enjoy relatively comprehensive healthcare benefits, and the quality of care is generally good. However, it is limited to formal sector employees and their dependents, which means that informal sector workers and those not covered by formal employment arrangements are not eligible. The universal coverage scheme aims to provide equitable access to healthcare for all, emphasizing the principle of social justice. The scheme may have limitations on specialized or high-cost medical treatments, and there may be variations in the quality of care among different facilities.

The impact of the healthcare scheme type on barriers to BSE, MG, or UTS may be influenced by numerous factors. Nevertheless, the results suggests that women who have health coverage through the social security scheme may benefit from targeted interventions to improve detection. Evidence for program planning should be implement in health insurance schemes groups such as health education, skill training and confidence in performing for BSE, reminders to perform BSE, regular use of BSE record booklets 15 , 46 .

One of the general barriers observed in this study is the lack of knowledge and awareness of breast cancer among the participants, as evidenced by their low scores in the Susceptibility, Seriousness, and Confidence scales. Knowledge is identified as the most influential barrier affecting the engagement of participants in BSE, particularly in low to middle-income countries and rural areas where resources are limited 47 . Participants in this study perceived their ability to perform the BSE technique as low, indicating a lack of knowledge or a lack of regular practice. Susceptibility refers to participants' perception of their chances of being at risk for a disease. In this study, participants perceived their chances of having a risk or disease as low, indicating a potential lack of knowledge regarding the risk factors of breast cancer, such as young age, no family history of cancer, and the absence of breast lumps. Seriousness pertains to participants' perception of the severity of the consequences associated with the disease. In this study, participants may perceive breast cancer as not causing pain, exhibiting no symptoms or signs, and not posing a significant threat. This suggests a lack of knowledge or the use of defence mechanisms such as denial or rationalization, similar to behaviours observed in smokers and alcohol drinkers 48 , 49 . Consistent with many Thai studies, interventions focusing on health education and skill training for BSE are recommended to address these knowledge gaps 17 , 21 , 46 .

One of the most common barriers to early screening detection identified in this study is the feeling of “embarrassment” and “worry”. Similar to Amin MN et al. 50 , this study conducted a hospital survey. The feeling of embarrassment can be considered a cultural barrier, where women may feel too embarrassed to have their breasts examined by a male doctor. This cultural aspect can hinder their willingness to seek medical attention for abnormalities. Worry, on the other hand, is associated with feelings of anxiety. Women may experience worry related to breast lumps, the potential consequences of breast cancer, and concerns about health professionals and healthcare facilities. Additionally, the perception that screening “takes too much time” can be a deterrent. Women may feel that they are too busy, have limited time, or believe that they lack sufficient time to perform BSE and undergo screening procedures 47 . Interventions should focus on problem-solving approaches and aim to improve healthcare services in order to overcome barriers faced by the participants. By addressing these barriers and concerns, healthcare providers can create a more supportive and comfortable environment for women to engage in early screening and detection practices. Apart from the issue of “embarrassment”, “worry”, and “takes too much time”, which should be considered as one of the barriers to BSE, mammograms, and ultrasounds, there could be other contributing factors. Future research should incorporate qualitative studies to explore additional causal factors influencing the practice or non-practice of BSE, as well as the utilization or non-utilization of mammograms and ultrasounds. Additionally, it is recommended to compare interventions using a before-and-after study design involving the three main public health insurance schemes: government or state enterprise officer, social security scheme, and universal coverage scheme. This examination is necessary to identify effective interventions for women within each health insurance scheme who may face different barriers.

Participants in this study are to be more empowering their health. They have the highest score of Health Motivation and comparing Benefit-MG and Benefit-UTS more than Benefit-BSE. Conversely, Barrier-BSE when comparing Barrier-MG and Barrier-UTS is inverse. This is show that they would like to take investigate accuracy screening tools more than their manual. As health practitioners’ perspective of Thai study would like to drive a policy of national cancer act to enable women’s rights for accessing standardized screening tools 10 .

Evidence for planning and future research

There is associated between a monthly income and perceived Barriers-MG and Barriers-UTS. This predictor may be sensitive and difficult to approach regarding their monthly income when implementing intervention strategies targeting MG and UTS promotion. However, there is health insurance schemes which associated with Benefit-MG, Barrier-BSE, Barrier-MG and Barrier-UTS subscale. Also, health insurance schemes in the social security scheme is the predictor of perceived Barrier-BSE, Barrier-MG and Barrier-UTS. Specifically, the perceived barriers subscale can help identify the problems of implementation. Furthermore, attitudes toward BSE, mammograms, and ultrasounds can be compared in terms of their benefits and barriers. Such comparisons can yield valuable insights for the development of targeted interventions and approaches aimed at increasing breast cancer screening among Northern Thai women in a hospital-based setting. The design of programs and future research should take this evidence into account during implementation. Future research could employ a before-and-after study design, integrating health education and skill training for BSE, and incorporating qualitative studies to explore the additional causal factors influencing the practice or non-practice of BSE, using or non-using mammogram/ultrasound. Moreover, investigating how to improve healthcare services to ensure women's satisfaction would be beneficial.

Strength and limitations

This study is the first research project known to utilize the MT-CHBMS to study the association between sociodemographic factors and health beliefs of breast cancer and screening behaviors. Additionally, the inclusion of new items related to ultrasound in the MT-CHBMS holds promise for the assessment of breast cancer beliefs among Thai women with dense breast masses and the potential integration of advanced technologies such as artificial intelligence in the future.

However, it is important to acknowledge the limitations of this study. Firstly, the cross-sectional design employed cannot establish causal relationships between beliefs and screening practices. Secondly, the results may not be generalizable to the entire population due to the selection of participants from a single geographic area and hospital setting in Northern Thailand. Thirdly, convenience sampling may cause these study results to only generalize to this research's sampling group. Fourthly, small sample size may cause low statistical power, increased error rate, and less precise information. Fifthly, structured interviews may be subject to interviewer or social desirability bias. Sixthly, no external validation, e.g., concurrent validity, was conducted along with the construct validity. Test–retest reliability and predictive validity were not examined and should be included in future research. Lastly, certain factors such as family history of breast cancer and other breast masses were not specifically excluded from the study, which could potentially influence participants' beliefs regarding breast cancer and their practices related to screening methods.

This study marked the first use of the MT-CHBMS to investigate the association between sociodemographic factors and health beliefs related to breast cancer screening. The findings provide evidence for program design and future research aimed at increasing breast cancer screening among women in Northern Thailand in a hospital-based setting. By successfully implementing the interventions, the ssocial security scheme represents the most targeted interventions can serve as role models for other health insurance schemes and contribute to enhancing the effectiveness of screening among women.

Data availability

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

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Department of Family Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand

Surin Jiraniramai, Kanokporn Pinyopornpanish, Chaisiri Angkurawaranon & Wichuda Jiraporncharoen

Global Health and Chronic Conditions Research Group, Chiang Mai University, Chiang Mai, 50200, Thailand

Department of Psychiatry, Faculty of Medicine, Chiang Mai University, 110 Inthawarorot Rd., Sriphum, Muang, Chiang Mai, 50200, Thailand

Nahathai Wongpakaran & Tinakon Wongpakaran

School of Nursing, Indiana University, Indianapolis, IN, 46202, USA

Victoria L. Champion

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All authors contributed to this study’s conceptualization and methodology. Validation, S.J., K.P.,V.L.C., N.W. and T.W.; Formal analysis,S.J.,K.P.,T.W.,N.W.and C.A.; investigation, all.; data curation, S.J., C.A.;The original draft was written by Surin Jiraniramai and reviewed and edited by all authors. Resources, S.J.,K.P.,C.A.,W.J.,and T.W.; supervision, T.W. and N.W.

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Jiraniramai, S., Pinyopornpanish, K., Wongpakaran, N. et al. Association between sociodemographic factors and health beliefs related to breast cancer screening behavior among Northern Thai women: a hospital-based study. Sci Rep 14 , 7596 (2024). https://doi.org/10.1038/s41598-024-58155-y

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The 4 Types of Organizational Culture and Their Benefits

Organizational culture influences the success of your company, directly affecting the sort of candidates you attract and the employees you hold onto. There are several different types of organizational culture too; so you have to find the one that works best for you.

What Is Organizational Culture?

Organizational culture, or company culture, is the shared values, attitudes and practices that make up the identity of an organization. It largely shapes employee behavior and interactions within a company. 

Organizational culture, also known as  company culture , is defined as the shared values, attitudes and practices that characterize an organization. It’s the personality of your company, and it plays a large part in your employees’ overall satisfaction.

Having a strong organizational culture is important because it helps attract the right candidates and it keeps them engaged as employees. According to a 2019 Glassdoor study , 77 percent of adults would evaluate a company’s culture before applying to an open position, with more than half ranking an organization’s organizational culture as more important than compensation. And an SHRM study from 2021 revealed that 94 percent of people managers believe a positive workplace culture helps retain employees.

Creating a winning organizational culture takes a lot of time and effort — your culture must accurately reflect your values and align with your overall mission. It’s a big to-do, but don’t get discouraged: your efforts will pay off in the long run.

While any given organizational culture will evolve with time — especially as the team grows and onboards more people — you can take steps to tailor your culture to better fit your organization’s values and mission. But first, you need to understand the type of organizational culture your company has.

Related Types of Diversity in the Workplace You Need to Know

4 Types of Organizational Culture

There are four main types of organizational culture, which come from Robert E. Quinn and Kim S. Cameron of the University of Michigan, who investigated the qualities that make businesses effective. From a list of 39 attributes, the researchers identified two key polarities: (1) internal focus and integration vs. external focus and differentiation, and (2) flexibility and discretion vs. stability and control.

Types of Organizational Culture

• Clan Culture: emphasizes collaboration across teams and a horizontal structure. 
• Adhocracy Culture: allows individuals to share ideas and encourages the company to take risks. 
• Market Culture: focuses on financial success and how each employee contributes to revenue. 
• Hierarchy Culture: emphasizes career paths and provides clear managerial processes.  

These qualities are visually represented within the Competing Values Framework, which is part of the validated and widely-used Organizational Cultural Assessment Instrument . Although there are several types of organizational culture, Quinn and Cameron’s four types are generally accepted and appear to influence any variations. These four types of organizational culture are neither good nor bad, but they do provide frameworks that company leadership can lean on. 

Understanding what type of organizational culture your company has can help you identify what makes your company stand out to candidates. When you know why your organization’s culture is unique, you can highlight these attributes in your recruitment marketing materials. Recognizing the type of company culture you have can also help you write your core values and mission statement . 

Related 21 Company Culture Examples to Get You Inspired

Type 1: Clan Culture

Primary Focus: Mentorship and teamwork.

Motto: “We’re all in this together.”

About Clan Culture: A clan culture is people-focused in the sense that the company feels family-like. This is a highly collaborative work environment where every individual is valued and communication is a top priority. Clan culture is often paired with a horizontal structure, which helps to break down barriers between the C-suite and employees, and it encourages mentorship opportunities . These companies are action-oriented and embrace change, a testament to their highly flexible nature.

Clan Culture Definition

• Clan culture is a collaborative model usually paired with horizontal company structure.
• Communication is key to this type of culture. 
• Companies can implement clan culture by asking for direct feedback for employees and taking action based on their suggestions.

Advantages of Clan Culture:  Clan cultures boast high rates of employee engagement , and happy employees make for happy customers. Because of its highly adaptable environment, there’s a great possibility for market growth within a clan culture.

Disadvantages of Clan Culture:  A family-style corporate culture is difficult to maintain as the company grows. Plus, with a horizontal leadership structure, day-to-day operations can seem cluttered and lacking direction.

Where You’ll Find Clan Culture: It’s no surprise that clan cultures are often seen in startups and smaller companies. Young organizations that are just starting out put a heavy emphasis on collaboration and communication, leadership looks to employees for feedback and ideas and companies prioritize team-building. 

For companies with a large percentage of employees working remotely like HR tech provider Hireology , creating an empathetic and communicative organizational culture is key to success. “When you have a blended team, your local staff can help bridge gaps and build empathy,” Joel Schlundt, vice president of engineering at Hireology, said. The team coordinated job swaps to help employees better understand and appreciate their peers’ roles.

How to Create Clan Culture Within Your Organization: To cultivate a clan culture within your company, your first step is to turn to your employees. Communication is vital to a successful clan culture, so let your team know that you’re open to feedback. Find out what they value, what they’d like to see change, what ideas they have to help push the company further. Step two: take their thoughts into account and put them into action.

Type 2: Adhocracy Culture

Primary Focus: Risk-taking and innovation.

Motto: “Risk it to get the biscuit.”

About Adhocracy Culture: Adhocracy cultures are rooted in innovation and adaptability. These are the companies that are on the cutting-edge of their industry — they’re looking to develop the next big thing before anyone else has even started asking the right questions. To do so, they need to take risks. Adhocracy cultures value individuality in the sense that employees are encouraged to think creatively and bring their ideas to the table. Because this type of organizational culture falls within the external focus and differentiation category, new ideas need to be tied to market growth and company success.

Adhocracy Culture Definition

• Adhocracy culture puts a focus on employees adapting and innovating. 
• This culture helps companies take risks and invites individuals to share their ideas. 
• Companies can implement adhocracy culture by hosting strategy and brainstorming sessions.   

Advantages of Adhocracy Culture: An adhocracy culture contributes to high profit margins and notoriety. Employees stay motivated with the goal of breaking the mold. Plus, with a focus on creativity and new ideas, professional development opportunities are easy to justify.

Disadvantages of Adhocracy Culture: Risk is risk, so there’s always a chance that a new venture won’t pan out and may even hurt your business. Adhocracy cultures can also foster competition between employees as the pressure to come up with new ideas mounts.

Where You’ll Find Adhocracy Culture: Think of Google or Apple — these are companies that embody the external focus and risk-taking nature of adhocracy culture. They run on creative energy and doing what hasn’t been done before. Adhocracy cultures are commonplace within the ever-changing tech industry where new products are being developed and released on a regular basis.

How to Create Adhocracy Culture Within Your Organization: Depending on your industry, it may be hard to develop an authentic adhocracy culture that includes a high-risk business strategy. However, implementing strategy and brainstorming sessions provides employees with the opportunity to share big ideas that can help to propel the company further. Rewarding successful ideas encourages teams to think outside of the box, too.

Related Culture Fit: More Harm Than Good? 12 Experts Share Their Take.

Type 3: Market Culture 

Primary Focus: Competition and growth.

Motto: “We’re in it to win it.”

About Market Culture: Market culture prioritizes profitability. Everything is evaluated with the bottom line in mind; each position has an objective that aligns with the company’s larger goal, and there are often several degrees of separation between employees and leadership roles. These are results-oriented organizations that focus on external success rather than internal satisfaction. A market culture stresses the importance of meeting quotas , reaching targets and getting results. 

Market Culture Definition

• Companies with a market culture are focused on financial success and meeting goals and targets. 
• Each employee working within market culture plays a distinct part in reaching the company’s larger goals. 
• Companies can implement market culture by analyzing each role within the company and determining the ROI of each role. Rewarding top performers will motivate employees.

Advantages of Market Culture: Companies that boast market cultures are profitable and successful. Because the entire organization is externally focused, there’s a key objective employees can get behind and work toward.

Disadvantages of Market Culture: On the other hand, because there’s a number tied to every decision, project and position within the company, it can be difficult for employees to meaningfully engage with their work and live out their professional purpose. There is also risk for burnout in this aggressive and fast-paced environment.

Where You’ll Find Market Culture: The goal of a market culture company is to be the best in its industry. Because of that, these are often larger companies that are already leaders of the pack. They’re looking to compete and beat out anyone else that may compare.

For an industry leader like Bluecore , a retail marketing platform that utilizes AI technology , providing employees with clear objectives helps the team provide all-star customer service. “Our team is clear on its goals, and we are incentivized through compensation structure and recognition,” Kim Surko, vice president of customer success, said. “With that foundation, we can apply our personality and values to define how we will accomplish those goals.” 

How to Create Market Culture Within Your Organization: Because every aspect of a market culture is tied to the company’s bottom line, start by evaluating each position within your organization. Calculate the ROI of every role and ascribe reasonable benchmarks for production. Consider rewarding top performers to encourage similar work.

Type 4: Hierarchy Culture

Primary Focus: Structure and stability.

Motto: “Get it done right. ”

About Hierarchy Culture: Companies with hierarchy cultures adhere to the traditional corporate structure. These are companies focused on internal organization by way of a clear chain of command and multiple management tiers that separate employees and leadership. In addition to a rigid structure, there’s often a dress code for employees to follow. Hierarchy cultures have a set way of doing things, which makes them stable and risk-averse.

Hierarchy Culture Definition

• Companies with hierarchy culture have a clear chain of command and detailed career paths within the organization. 
• These companies tend to avoid risk and focus on internal organization. 
• Companies can implement hierarchy culture by ensuring each department and team has clear and concise processes and managerial structure.   

Advantages of Hierarchy Culture: With internal organization as a priority, hierarchy cultures have clear direction. There are well-defined processes that cater to the company’s main objectives.

Disadvantages of Hierarchy Culture: The rigidity of hierarchy cultures leaves little room for creativity, making these companies relatively slow to adapt to the changing marketplace. The company takes precedence over the individual, which doesn’t necessarily encourage employee feedback.

Where You’ll Find Hierarchy Culture: Hierarchy cultures can be found at both ends of the corporate spectrum, from old-school organizations to those of the customer service industry, such as fast food restaurants. These are companies that are hyper-focused on how day-to-day operations are carried out and aren’t interested in changing things up anytime soon.

How to Create Hierarchy Culture Within Your Organization: The first step to establishing a hierarchy culture is to button up your processes. If the chain of command has some gaps, fill them. Consider every team and department to ensure they have clear long- and short-term goals.

Learn About Recruiting 12 Recruitment Strategies and Examples to Hire Top Talent

Other Types of Organizational Culture

Outside of these four main categories of organizational culture, there are a few more worth noting. 

Purpose Culture

Purpose culture focuses on a company’s mission and core values. These aspects drive the culture. Often companies with this culture will have a mission of changing an industry or community for the better. One example of this can be seen in Patagonia ’s mission statement : “We’re in business to save our home planet.” 

Coaching Culture

In a company with a coaching culture senior leadership is responsible for mentoring their employees and ensuring that individuals advance in their careers. Various coaching techniques, such as providing assessments on specific projects or one-on-one meetings where expectations and personal goals are discussed, typically drive this style of culture. 

Related 5 Companies With Interesting Organizational Cultures

Accountability Culture

Accountability culture means that everyone within the organization, including the CEO and senior leadership, are responsible and held accountable for their own actions and performance. This can look like employees taking ownership of their mistakes and openly questioning how they can learn from them as well as recognizing colleagues when they have excelled in their role.

Learning Culture 

Companies with a learning culture put a special emphasis on learning and development opportunities . These organizations often have company-wide workshops and encourage employees to learn skills outside of what is immediately required for their role, providing stipends for various educational opportunities . 

Go Deeper 7 Leadership Lessons From Netflix CEO Reed Hastings

How to Identify Your Organizational Culture

Your organizational culture says a lot about your team and what you value, and job seekers can pick up on that almost immediately. If you’re not sure where your organization lands on this list, you’re not alone. Cameron and Quinn developed an assessment tool that helps companies identify their organizational culture. 

Once you evaluate your existing organizational culture, take stock of what truly matters to your organization: Where are you aligned? What are your areas for improvement? 

If you think a different kind of organizational culture would work better for your company and employees, take steps to shift it . While that looks different from company to company, you’ll generally want to start by defining and assessing the current culture, financial goals, company structure, mission and core values. Then continually evaluate your culture and the progress you’ve made toward your organizational culture goals.

Strategies to decode, maintain and improve company culture.

Frequently Asked Questions

What is organizational culture.

Organizational culture, or company culture, is the shared values, practices and attitudes that characterize an organization. It defines the overall personality and working environment of a company, and has a significant impact on employee behavior and satisfaction.

What are the 4 types of organizational culture?

The four main types of organizational culture include:

• Clan culture 
• Adhocracy culture
• Market culture
• Hierarchy culture

What does a good organizational culture look like?

A good or positive organizational culture is often one that fosters mutual respect, growth opportunities and shared goals amongst employees. This kind of organizational culture also reflects a company's core values and aligns with the company's overarching mission.

What are the 7 characteristics of organizational culture?

The seven characteristics of organizational culture include:

• Attention to detail 
• Emphasis on outcome and results 
• Emphasis on people and relationships
• Aggressiveness or competitive nature

Organizational cultures are comprised of all of these characteristics to some degree. However, the prioritization and value put to each characteristic will vary depending on the company and its type of culture.

Great Companies Need Great People. That's Where We Come In.

Study of Sausage Products Prepared Using Biologically Active Additives from Sprouted Wheat and Cattle by Products

• 1 Laboratory of Technology for Processing and Storage of Animal Products, Kazakh Research Institute of Processing and Food Industry, Almaty, Kazakhstan
• 2 Laboratory of Technology for Processing and Storage of Animal Products, Kazakh Research Institute of Processing and Food Industry, Almaty, Kazakhstan

The production of meat and meat products is closely related to the development of livestock farming and the processing industry. A promising direction for the development of the meat industry could be an increase in the depth of processing of meat raw materials, including an increase in the production of meat products from by-products that are in high demand among the population. The main problem in this industry is the lack of raw materials. This problem can be solved by optimizing meat production through the use of by-products, in particular, such as fat. Despite the fact that the use of fat in meat production is not something new, no research has been conducted on the use of fat in combination with vegetable raw materials in the Republic of Kazakhstan. At the same time, the practical significance of combining fat with vegetable raw materials is due to the properties of high-quality plant raw materials, which are valuable for the food industry, providing the opportunity to produce products with a high content of useful substances. The article analyzes the possibility of using a dietary supplement using fat obtained from animal fat and vegetable raw materials in the production of sausages. The purpose of the study is to increase the range of sausage products by increasing the volume of useful, easily digestible, low-cost raw materials. Chemical indicators according to GOST 9959-2015 and microbiological indicators according to GOST R 54354-2011 of control and test samples of sausage products were studied. The possibility of using a biologically active fat additive in sausages has also been considered. It has been proven that the use of dietary supplements allows saving raw meat up to 20-25% and in combination with beef it makes sausages a high-calorie food product with increased digestibility. The use of the proposed method makes it possible to increase the possibility of replacing raw meat by up to 20-25%, increase the biological and energy value, and improve the organoleptic properties of the final product. Ready-made sausages have a good presentation, and juicy consistency and have a pronounced specific smell and taste.

How to Cite: Kenenbay, G., Chomanov, U., Tultabayeva, T., Shoman, A. & Tultabayev, N. (2024). Study of Sausage Products Prepared Using Biologically Active Additives from Sprouted Wheat and Cattle by Products. American Journal of Animal and Veterinary Sciences , 19 (2), 133-141. https://doi.org/10.3844/ajavsp.2024.133.141

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