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What is Research: Definition, Methods, Types & Examples

The search for knowledge is closely linked to the object of study; that is, to the reconstruction of the facts that will provide an explanation to an observed event and that at first sight can be considered as a problem. It is very human to seek answers and satisfy our curiosity. Let’s talk about research.

Content Index

What is Research?

What are the characteristics of research.

• Comparative analysis chart

Qualitative methods

Quantitative methods, 8 tips for conducting accurate research.

Research is the careful consideration of study regarding a particular concern or research problem using scientific methods. According to the American sociologist Earl Robert Babbie, “research is a systematic inquiry to describe, explain, predict, and control the observed phenomenon. It involves inductive and deductive methods.”

Inductive methods analyze an observed event, while deductive methods verify the observed event. Inductive approaches are associated with qualitative research , and deductive methods are more commonly associated with quantitative analysis .

Research is conducted with a purpose to:

• Identify potential and new customers
• Understand existing customers
• Set pragmatic goals
• Develop productive market strategies
• Address business challenges
• Put together a business expansion plan
• Identify new business opportunities
• Good research follows a systematic approach to capture accurate data. Researchers need to practice ethics and a code of conduct while making observations or drawing conclusions.
• The analysis is based on logical reasoning and involves both inductive and deductive methods.
• Real-time data and knowledge is derived from actual observations in natural settings.
• There is an in-depth analysis of all data collected so that there are no anomalies associated with it.
• It creates a path for generating new questions. Existing data helps create more research opportunities.
• It is analytical and uses all the available data so that there is no ambiguity in inference.
• Accuracy is one of the most critical aspects of research. The information must be accurate and correct. For example, laboratories provide a controlled environment to collect data. Accuracy is measured in the instruments used, the calibrations of instruments or tools, and the experiment’s final result.

What is the purpose of research?

There are three main purposes:

• Exploratory: As the name suggests, researchers conduct exploratory studies to explore a group of questions. The answers and analytics may not offer a conclusion to the perceived problem. It is undertaken to handle new problem areas that haven’t been explored before. This exploratory data analysis process lays the foundation for more conclusive data collection and analysis.

LEARN ABOUT: Descriptive Analysis

• Descriptive: It focuses on expanding knowledge on current issues through a process of data collection. Descriptive research describe the behavior of a sample population. Only one variable is required to conduct the study. The three primary purposes of descriptive studies are describing, explaining, and validating the findings. For example, a study conducted to know if top-level management leaders in the 21st century possess the moral right to receive a considerable sum of money from the company profit.

LEARN ABOUT: Best Data Collection Tools

• Explanatory: Causal research or explanatory research is conducted to understand the impact of specific changes in existing standard procedures. Running experiments is the most popular form. For example, a study that is conducted to understand the effect of rebranding on customer loyalty.

Here is a comparative analysis chart for a better understanding:

It begins by asking the right questions and choosing an appropriate method to investigate the problem. After collecting answers to your questions, you can analyze the findings or observations to draw reasonable conclusions.

When it comes to customers and market studies, the more thorough your questions, the better the analysis. You get essential insights into brand perception and product needs by thoroughly collecting customer data through surveys and questionnaires . You can use this data to make smart decisions about your marketing strategies to position your business effectively.

To make sense of your study and get insights faster, it helps to use a research repository as a single source of truth in your organization and manage your research data in one centralized data repository .

Types of research methods and Examples

Research methods are broadly classified as Qualitative and Quantitative .

Both methods have distinctive properties and data collection methods .

Qualitative research is a method that collects data using conversational methods, usually open-ended questions . The responses collected are essentially non-numerical. This method helps a researcher understand what participants think and why they think in a particular way.

Types of qualitative methods include:

• One-to-one Interview
• Focus Groups
• Ethnographic studies
• Text Analysis

Quantitative methods deal with numbers and measurable forms . It uses a systematic way of investigating events or data. It answers questions to justify relationships with measurable variables to either explain, predict, or control a phenomenon.

Types of quantitative methods include:

• Survey research
• Descriptive research
• Correlational research

LEARN MORE: Descriptive Research vs Correlational Research

Remember, it is only valuable and useful when it is valid, accurate, and reliable. Incorrect results can lead to customer churn and a decrease in sales.

It is essential to ensure that your data is:

• Valid – founded, logical, rigorous, and impartial.
• Accurate – free of errors and including required details.
• Reliable – other people who investigate in the same way can produce similar results.
• Timely – current and collected within an appropriate time frame.
• Complete – includes all the data you need to support your business decisions.

Gather insights

• Identify the main trends and issues, opportunities, and problems you observe. Write a sentence describing each one.
• Keep track of the frequency with which each of the main findings appears.
• Make a list of your findings from the most common to the least common.
• Evaluate a list of the strengths, weaknesses, opportunities, and threats identified in a SWOT analysis .
• Prepare conclusions and recommendations about your study.
• Act on your strategies
• Look for gaps in the information, and consider doing additional inquiry if necessary
• Plan to review the results and consider efficient methods to analyze and interpret results.

Review your goals before making any conclusions about your study. Remember how the process you have completed and the data you have gathered help answer your questions. Ask yourself if what your analysis revealed facilitates the identification of your conclusions and recommendations.

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Definition of research

 (Entry 1 of 2)

Definition of research  (Entry 2 of 2)

transitive verb

intransitive verb

• disquisition
• examination
• exploration
• inquisition
• investigation
• delve (into)
• inquire (into)
• investigate
• look (into)

Examples of research in a Sentence

These examples are programmatically compiled from various online sources to illustrate current usage of the word 'research.' Any opinions expressed in the examples do not represent those of Merriam-Webster or its editors. Send us feedback about these examples.

Word History

Middle French recerche , from recercher to go about seeking, from Old French recerchier , from re- + cerchier, sercher to search — more at search

1577, in the meaning defined at sense 3

1588, in the meaning defined at transitive sense 1

Phrases Containing research

• marketing research
• market research
• operations research
• oppo research

research and development

• research park
• translational research

Dictionary Entries Near research

Cite this entry.

“Research.” Merriam-Webster.com Dictionary , Merriam-Webster, https://www.merriam-webster.com/dictionary/research. Accessed 10 May. 2024.

Kids Definition

Kids definition of research.

Kids Definition of research  (Entry 2 of 2)

More from Merriam-Webster on research

Nglish: Translation of research for Spanish Speakers

Britannica English: Translation of research for Arabic Speakers

Britannica.com: Encyclopedia article about research

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Example sentences research study

One research study found that the chances of being adopted reduced by 'nearly a half for every year of delay'.

According to a doubtless authoritative research study , the average value of data stored in e-mail on a laptop exceeds 500,000.

This large-scale research study was designed to test the validity of such memories by using outside sources to corroborate the memories.

A small group of students was tested using mobiles during an initial research study .

Research study after research study shows the strong positive correlation between the level of an individual's education and his or her longevity.

Definition of 'research' research

Definition of 'study' study

COBUILD Collocations research study

Browse alphabetically research study

• research scientist
• research shows
• research student
• research study
• research subject
• research suggests
• research the effect of
• All ENGLISH words that begin with 'R'

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What Is Research, and Why Do People Do It?

• Open Access
• First Online: 03 December 2022

Cite this chapter

You have full access to this open access chapter

• James Hiebert 6 ,
• Jinfa Cai 7 ,
• Stephen Hwang 7 ,
• Anne K Morris 6 &
• Charles Hohensee 6  

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

17k Accesses

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.

You have full access to this open access chapter,  Download chapter PDF

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.

Agnes, M., & Guralnik, D. B. (Eds.). (2008). Hypothesis. In Webster’s new world college dictionary (4th ed.). Wiley.

Google Scholar  

Britannica. (n.d.). Scientific method. In Encyclopaedia Britannica . Retrieved July 15, 2022 from https://www.britannica.com/science/scientific-method

Brownell, W. A., & Moser, H. E. (1949). Meaningful vs. mechanical learning: A study in grade III subtraction . Duke University Press..

Cai, J., Morris, A., Hohensee, C., Hwang, S., Robison, V., Cirillo, M., Kramer, S. L., & Hiebert, J. (2019b). Posing significant research questions. Journal for Research in Mathematics Education, 50 (2), 114–120. https://doi.org/10.5951/jresematheduc.50.2.0114

Article   Google Scholar  

Cambridge University Press. (n.d.). Hypothesis. In Cambridge dictionary . Retrieved July 15, 2022 from https://dictionary.cambridge.org/us/dictionary/english/hypothesis

Cronbach, J. L. (1957). The two disciplines of scientific psychology. American Psychologist, 12 , 671–684.

Cronbach, L. J. (1975). Beyond the two disciplines of scientific psychology. American Psychologist, 30 , 116–127.

Cronbach, L. J. (1986). Social inquiry by and for earthlings. In D. W. Fiske & R. A. Shweder (Eds.), Metatheory in social science: Pluralisms and subjectivities (pp. 83–107). University of Chicago Press.

Hay, C. M. (Ed.). (2016). Methods that matter: Integrating mixed methods for more effective social science research . University of Chicago Press.

Merriam-Webster. (n.d.). Explain. In Merriam-Webster.com dictionary . Retrieved July 15, 2022, from https://www.merriam-webster.com/dictionary/explain

National Research Council. (2002). Scientific research in education . National Academy Press.

Weis, L., Eisenhart, M., Duncan, G. J., Albro, E., Bueschel, A. C., Cobb, P., Eccles, J., Mendenhall, R., Moss, P., Penuel, W., Ream, R. K., Rumbaut, R. G., Sloane, F., Weisner, T. S., & Wilson, J. (2019a). Mixed methods for studies that address broad and enduring issues in education research. Teachers College Record, 121 , 100307.

Weisner, T. S. (Ed.). (2005). Discovering successful pathways in children’s development: Mixed methods in the study of childhood and family life . University of Chicago Press.

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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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• He has dedicated his life to scientific research.
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• I'd like to see the research that these recommendations are founded on.
• It took months of painstaking research to write the book .
• absorptive capacity
• dream something up
• modularization
• nanotechnology
• non-imitative
• operations research
• think outside the box idiom
• think something up
• uninventive
• study What do you plan on studying in college?
• major US She majored in philosophy at Harvard.
• cram She's cramming for her history exam.
• revise UK I'm revising for tomorrow's test.
• review US We're going to review for the test tomorrow night.
• research Scientists are researching possible new treatments for cancer.
• The amount of time and money being spent on researching this disease is pitiful .
• We are researching the reproduction of elephants .
• She researched a wide variety of jobs before deciding on law .
• He researches heart disease .
• The internet has reduced the amount of time it takes to research these subjects .
• adjudication
• analytically
• interpretable
• interpretive
• interpretively
• investigate
• reinvestigate
• reinvestigation
• risk assessment
• run over/through something
• run through something

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What Is Research Methodology? A Plain-Language Explanation & Definition (With Examples)

By Derek Jansen (MBA)  and Kerryn Warren (PhD) | June 2020 (Last updated April 2023)

If you’re new to formal academic research, it’s quite likely that you’re feeling a little overwhelmed by all the technical lingo that gets thrown around. And who could blame you – “research methodology”, “research methods”, “sampling strategies”… it all seems never-ending!

In this post, we’ll demystify the landscape with plain-language explanations and loads of examples (including easy-to-follow videos), so that you can approach your dissertation, thesis or research project with confidence. Let’s get started.

Research Methodology 101

• What exactly research methodology means
• What qualitative , quantitative and mixed methods are
• What sampling strategy is
• What data collection methods are
• What data analysis methods are
• How to choose your research methodology
• Example of a research methodology

What is research methodology?

Research methodology simply refers to the practical “how” of a research study. More specifically, it’s about how  a researcher  systematically designs a study  to ensure valid and reliable results that address the research aims, objectives and research questions . Specifically, how the researcher went about deciding:

• What type of data to collect (e.g., qualitative or quantitative data )
• Who  to collect it from (i.e., the sampling strategy )
• How to  collect  it (i.e., the data collection method )
• How to  analyse  it (i.e., the data analysis methods )

Within any formal piece of academic research (be it a dissertation, thesis or journal article), you’ll find a research methodology chapter or section which covers the aspects mentioned above. Importantly, a good methodology chapter explains not just   what methodological choices were made, but also explains  why they were made. In other words, the methodology chapter should justify  the design choices, by showing that the chosen methods and techniques are the best fit for the research aims, objectives and research questions. 

So, it’s the same as research design?

Not quite. As we mentioned, research methodology refers to the collection of practical decisions regarding what data you’ll collect, from who, how you’ll collect it and how you’ll analyse it. Research design, on the other hand, is more about the overall strategy you’ll adopt in your study. For example, whether you’ll use an experimental design in which you manipulate one variable while controlling others. You can learn more about research design and the various design types here .

Need a helping hand?

What are qualitative, quantitative and mixed-methods?

Qualitative, quantitative and mixed-methods are different types of methodological approaches, distinguished by their focus on words , numbers or both . This is a bit of an oversimplification, but its a good starting point for understanding.

Let’s take a closer look.

Qualitative research refers to research which focuses on collecting and analysing words (written or spoken) and textual or visual data, whereas quantitative research focuses on measurement and testing using numerical data . Qualitative analysis can also focus on other “softer” data points, such as body language or visual elements.

It’s quite common for a qualitative methodology to be used when the research aims and research questions are exploratory  in nature. For example, a qualitative methodology might be used to understand peoples’ perceptions about an event that took place, or a political candidate running for president. 

Contrasted to this, a quantitative methodology is typically used when the research aims and research questions are confirmatory  in nature. For example, a quantitative methodology might be used to measure the relationship between two variables (e.g. personality type and likelihood to commit a crime) or to test a set of hypotheses .

As you’ve probably guessed, the mixed-method methodology attempts to combine the best of both qualitative and quantitative methodologies to integrate perspectives and create a rich picture. If you’d like to learn more about these three methodological approaches, be sure to watch our explainer video below.

What is sampling strategy?

Simply put, sampling is about deciding who (or where) you’re going to collect your data from . Why does this matter? Well, generally it’s not possible to collect data from every single person in your group of interest (this is called the “population”), so you’ll need to engage a smaller portion of that group that’s accessible and manageable (this is called the “sample”).

How you go about selecting the sample (i.e., your sampling strategy) will have a major impact on your study.  There are many different sampling methods  you can choose from, but the two overarching categories are probability   sampling and  non-probability   sampling .

Probability sampling  involves using a completely random sample from the group of people you’re interested in. This is comparable to throwing the names all potential participants into a hat, shaking it up, and picking out the “winners”. By using a completely random sample, you’ll minimise the risk of selection bias and the results of your study will be more generalisable  to the entire population. 

Non-probability sampling , on the other hand,  doesn’t use a random sample . For example, it might involve using a convenience sample, which means you’d only interview or survey people that you have access to (perhaps your friends, family or work colleagues), rather than a truly random sample. With non-probability sampling, the results are typically not generalisable .

To learn more about sampling methods, be sure to check out the video below.

What are data collection methods?

As the name suggests, data collection methods simply refers to the way in which you go about collecting the data for your study. Some of the most common data collection methods include:

• Interviews (which can be unstructured, semi-structured or structured)
• Focus groups and group interviews
• Surveys (online or physical surveys)
• Observations (watching and recording activities)
• Biophysical measurements (e.g., blood pressure, heart rate, etc.)
• Documents and records (e.g., financial reports, court records, etc.)

The choice of which data collection method to use depends on your overall research aims and research questions , as well as practicalities and resource constraints. For example, if your research is exploratory in nature, qualitative methods such as interviews and focus groups would likely be a good fit. Conversely, if your research aims to measure specific variables or test hypotheses, large-scale surveys that produce large volumes of numerical data would likely be a better fit.

What are data analysis methods?

Data analysis methods refer to the methods and techniques that you’ll use to make sense of your data. These can be grouped according to whether the research is qualitative  (words-based) or quantitative (numbers-based).

Popular data analysis methods in qualitative research include:

• Qualitative content analysis
• Thematic analysis
• Discourse analysis
• Narrative analysis
• Interpretative phenomenological analysis (IPA)
• Visual analysis (of photographs, videos, art, etc.)

Qualitative data analysis all begins with data coding , after which an analysis method is applied. In some cases, more than one analysis method is used, depending on the research aims and research questions . In the video below, we explore some  common qualitative analysis methods, along with practical examples.  

Moving on to the quantitative side of things, popular data analysis methods in this type of research include:

• Descriptive statistics (e.g. means, medians, modes )
• Inferential statistics (e.g. correlation, regression, structural equation modelling)

Again, the choice of which data collection method to use depends on your overall research aims and objectives , as well as practicalities and resource constraints. In the video below, we explain some core concepts central to quantitative analysis.

How do I choose a research methodology?

As you’ve probably picked up by now, your research aims and objectives have a major influence on the research methodology . So, the starting point for developing your research methodology is to take a step back and look at the big picture of your research, before you make methodology decisions. The first question you need to ask yourself is whether your research is exploratory or confirmatory in nature.

If your research aims and objectives are primarily exploratory in nature, your research will likely be qualitative and therefore you might consider qualitative data collection methods (e.g. interviews) and analysis methods (e.g. qualitative content analysis). 

Conversely, if your research aims and objective are looking to measure or test something (i.e. they’re confirmatory), then your research will quite likely be quantitative in nature, and you might consider quantitative data collection methods (e.g. surveys) and analyses (e.g. statistical analysis).

Designing your research and working out your methodology is a large topic, which we cover extensively on the blog . For now, however, the key takeaway is that you should always start with your research aims, objectives and research questions (the golden thread). Every methodological choice you make needs align with those three components. 

Example of a research methodology chapter

In the video below, we provide a detailed walkthrough of a research methodology from an actual dissertation, as well as an overview of our free methodology template .

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

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199 Comments

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Thanks for your comment.

We can’t write your methodology for you. If you’re looking for samples, you should be able to find some sample methodologies on Google. Alternatively, you can download some previous dissertations from a dissertation directory and have a look at the methodology chapters therein.

All the best with your research.

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Sure. You’re welcome to book an initial consultation with one of our Research Coaches to discuss how we can assist – https://gradcoach.com/book/new/ .

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MLA Jansen, Derek, and Kerryn Warren. “What (Exactly) Is Research Methodology?” Grad Coach, June 2021, gradcoach.com/what-is-research-methodology/.

APA Jansen, D., & Warren, K. (2021, June). What (Exactly) Is Research Methodology? Grad Coach. https://gradcoach.com/what-is-research-methodology/

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• Clinical Trials

About Clinical Studies

Research: it's all about patients.

Mayo's mission is about the patient, the patient comes first. So the mission and research here, is to advance how we can best help the patient, how to make sure the patient comes first in care. So in many ways, it's a cycle. It can start with as simple as an idea, worked on in a laboratory, brought to the patient bedside, and if everything goes right, and let's say it's helpful or beneficial, then brought on as a standard approach. And I think that is one of the unique characteristics of Mayo's approach to research, that patient-centeredness. That really helps to put it in its own spotlight.

At Mayo Clinic, the needs of the patient come first. Part of this commitment involves conducting medical research with the goal of helping patients live longer, healthier lives.

Through clinical studies, which involve people who volunteer to participate in them, researchers can better understand how to diagnose, treat and prevent diseases or conditions.

Types of clinical studies

• Observational study. A type of study in which people are observed or certain outcomes are measured. No attempt is made by the researcher to affect the outcome — for example, no treatment is given by the researcher.
• Clinical trial (interventional study). During clinical trials, researchers learn if a new test or treatment works and is safe. Treatments studied in clinical trials might be new drugs or new combinations of drugs, new surgical procedures or devices, or new ways to use existing treatments. Find out more about the five phases of non-cancer clinical trials on ClinicalTrials.gov or the National Cancer Institute phases of cancer trials .
• Medical records research. Medical records research involves the use of information collected from medical records. By studying the medical records of large groups of people over long periods of time, researchers can see how diseases progress and which treatments and surgeries work best. Find out more about Minnesota research authorization .

Clinical studies may differ from standard medical care

A health care provider diagnoses and treats existing illnesses or conditions based on current clinical practice guidelines and available, approved treatments.

But researchers are constantly looking for new and better ways to prevent and treat disease. In their laboratories, they explore ideas and test hypotheses through discovery science. Some of these ideas move into formal clinical trials.

During clinical studies, researchers formally and scientifically gather new knowledge and possibly translate these findings into improved patient care.

Before clinical trials begin

This video demonstrates how discovery science works, what happens in the research lab before clinical studies begin, and how a discovery is transformed into a potential therapy ready to be tested in trials with human participants:

How clinical trials work

Trace the clinical trial journey from a discovery research idea to a viable translatable treatment for patients:

See a glossary of terms related to clinical studies, clinical trials and medical research on ClinicalTrials.gov.

Watch a video about clinical studies to help you prepare to participate.

Let's Talk About Clinical Research

Narrator: This presentation is a brief introduction to the terms, purposes, benefits and risks of clinical research.

If you have questions about the content of this program, talk with your health care provider.

What is clinical research?

Clinical research is a process to find new and better ways to understand, detect, control and treat health conditions. The scientific method is used to find answers to difficult health-related questions.

Ways to participate

There are many ways to participate in clinical research at Mayo Clinic. Three common ways are by volunteering to be in a study, by giving permission to have your medical record reviewed for research purposes, and by allowing your blood or tissue samples to be studied.

Types of clinical research

There are many types of clinical research:

• Prevention studies look at ways to stop diseases from occurring or from recurring after successful treatment.
• Screening studies compare detection methods for common conditions.
• Diagnostic studies test methods for early identification of disease in those with symptoms.
• Treatment studies test new combinations of drugs and new approaches to surgery, radiation therapy and complementary medicine.
• The role of inheritance or genetic studies may be independent or part of other research.
• Quality of life studies explore ways to manage symptoms of chronic illness or side effects of treatment.
• Medical records studies review information from large groups of people.

Clinical research volunteers

Participants in clinical research volunteer to take part. Participants may be healthy, at high risk for developing a disease, or already diagnosed with a disease or illness. When a study is offered, individuals may choose whether or not to participate. If they choose to participate, they may leave the study at any time.

Research terms

You will hear many terms describing clinical research. These include research study, experiment, medical research and clinical trial.

Clinical trial

A clinical trial is research to answer specific questions about new therapies or new ways of using known treatments. Clinical trials take place in phases. For a treatment to become standard, it usually goes through two or three clinical trial phases. The early phases look at treatment safety. Later phases continue to look at safety and also determine the effectiveness of the treatment.

Phase I clinical trial

A small number of people participate in a phase I clinical trial. The goals are to determine safe dosages and methods of treatment delivery. This may be the first time the drug or intervention is used with people.

Phase II clinical trial

Phase II clinical trials have more participants. The goals are to evaluate the effectiveness of the treatment and to monitor side effects. Side effects are monitored in all the phases, but this is a special focus of phase II.

Phase III clinical trial

Phase III clinical trials have the largest number of participants and may take place in multiple health care centers. The goal of a phase III clinical trial is to compare the new treatment to the standard treatment. Sometimes the standard treatment is no treatment.

Phase IV clinical trial

A phase IV clinical trial may be conducted after U.S. Food and Drug Administration approval. The goal is to further assess the long-term safety and effectiveness of a therapy. Smaller numbers of participants may be enrolled if the disease is rare. Larger numbers will be enrolled for common diseases, such as diabetes or heart disease.

Clinical research sponsors

Mayo Clinic funds clinical research at facilities in Rochester, Minnesota; Jacksonville, Florida; and Arizona, and in the Mayo Clinic Health System. Clinical research is conducted in partnership with other medical centers throughout the world. Other sponsors of research at Mayo Clinic include the National Institutes of Health, device or pharmaceutical companies, foundations and organizations.

Clinical research at Mayo Clinic

Dr. Hugh Smith, former chair of Mayo Clinic Board of Governors, stated, "Our commitment to research is based on our knowledge that medicine must be constantly moving forward, that we need to continue our efforts to better understand disease and bring the latest medical knowledge to our practice and to our patients."

This fits with the term "translational research," meaning what is learned in the laboratory goes quickly to the patient's bedside and what is learned at the bedside is taken back to the laboratory.

Ethics and safety of clinical research

All clinical research conducted at Mayo Clinic is reviewed and approved by Mayo's Institutional Review Board. Multiple specialized committees and colleagues may also provide review of the research. Federal rules help ensure that clinical research is conducted in a safe and ethical manner.

Institutional review board

An institutional review board (IRB) reviews all clinical research proposals. The goal is to protect the welfare and safety of human subjects. The IRB continues its review as research is conducted.

Consent process

Participants sign a consent form to ensure that they understand key facts about a study. Such facts include that participation is voluntary and they may withdraw at any time. The consent form is an informational document, not a contract.

Study activities

Staff from the study team describe the research activities during the consent process. The research may include X-rays, blood tests, counseling or medications.

Study design

During the consent process, you may hear different phrases related to study design. Randomized means you will be assigned to a group by chance, much like a flip of a coin. In a single-blinded study, participants do not know which treatment they are receiving. In a double-blinded study, neither the participant nor the research team knows which treatment is being administered.

Some studies use an inactive substance called a placebo.

Multisite studies allow individuals from many different locations or health care centers to participate.

Remuneration

If the consent form states remuneration is provided, you will be paid for your time and participation in the study.

Some studies may involve additional cost. To address costs in a study, carefully review the consent form and discuss questions with the research team and your insurance company. Medicare may cover routine care costs that are part of clinical trials. Medicaid programs in some states may also provide routine care cost coverage, as well.

When considering participation in a research study, carefully look at the benefits and risks. Benefits may include earlier access to new clinical approaches and regular attention from a research team. Research participation often helps others in the future.

Risks/inconveniences

Risks may include side effects. The research treatment may be no better than the standard treatment. More visits, if required in the study, may be inconvenient.

Weigh your risks and benefits

Consider your situation as you weigh the risks and benefits of participation prior to enrolling and during the study. You may stop participation in the study at any time.

Ask questions

Stay informed while participating in research:

• Write down questions you want answered.
• If you do not understand, say so.
• If you have concerns, speak up.

Website resources are available. The first website lists clinical research at Mayo Clinic. The second website, provided by the National Institutes of Health, lists studies occurring in the United States and throughout the world.

Additional information about clinical research may be found at the Mayo Clinic Barbara Woodward Lips Patient Education Center and the Stephen and Barbara Slaggie Family Cancer Education Center.

Clinical studies questions

• Phone: 800-664-4542 (toll-free)
• Contact form

Cancer-related clinical studies questions

• Phone: 855-776-0015 (toll-free)

International patient clinical studies questions

• Phone: 507-284-8884
• Email: [email protected]

Clinical Studies in Depth

Learning all you can about clinical studies helps you prepare to participate.

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Understanding Clinical Trials

Clinical research: what is it.

Your doctor may have said that you are eligible for a clinical trial, or you may have seen an ad for a clinical research study. What is clinical research, and is it right for you?

Clinical research is the comprehensive study of the safety and effectiveness of the most promising advances in patient care. Clinical research is different than laboratory research. It involves people who volunteer to help us better understand medicine and health. Lab research generally does not involve people — although it helps us learn which new ideas may help people.

Every drug, device, tool, diagnostic test, technique and technology used in medicine today was once tested in volunteers who took part in clinical research studies.

At Johns Hopkins Medicine, we believe that clinical research is key to improve care for people in our community and around the world. Once you understand more about clinical research, you may appreciate why it’s important to participate — for yourself and the community.

What Are the Types of Clinical Research?

There are two main kinds of clinical research:

Observational Studies

Observational studies are studies that aim to identify and analyze patterns in medical data or in biological samples, such as tissue or blood provided by study participants.

Clinical Trials

Clinical trials, which are also called interventional studies, test the safety and effectiveness of medical interventions — such as medications, procedures and tools — in living people.

Clinical research studies need people of every age, health status, race, gender, ethnicity and cultural background to participate. This will increase the chances that scientists and clinicians will develop treatments and procedures that are likely to be safe and work well in all people. Potential volunteers are carefully screened to ensure that they meet all of the requirements for any study before they begin. Most of the reasons people are not included in studies is because of concerns about safety.

Both healthy people and those with diagnosed medical conditions can take part in clinical research. Participation is always completely voluntary, and participants can leave a study at any time for any reason.

“The only way medical advancements can be made is if people volunteer to participate in clinical research. The research participant is just as necessary as the researcher in this partnership to advance health care.” Liz Martinez, Johns Hopkins Medicine Research Participant Advocate

Types of Research Studies

Within the two main kinds of clinical research, there are many types of studies. They vary based on the study goals, participants and other factors.

Biospecimen studies

Healthy volunteer studies.

Clinical trials study the safety and effectiveness of interventions and procedures on people’s health. Interventions may include medications, radiation, foods or behaviors, such as exercise. Usually, the treatments in clinical trials are studied in a laboratory and sometimes in animals before they are studied in humans. The goal of clinical trials is to find new and better ways of preventing, diagnosing and treating disease. They are used to test:

Drugs or medicines

New types of surgery

Medical devices

New ways of using current treatments

New ways of changing health behaviors

New ways to improve quality of life for sick patients

 Goals of Clinical Trials

Because every clinical trial is designed to answer one or more medical questions, different trials have different goals. Those goals include:

Treatment trials

Prevention trials, screening trials, phases of a clinical trial.

In general, a new drug needs to go through a series of four types of clinical trials. This helps researchers show that the medication is safe and effective. As a study moves through each phase, researchers learn more about a medication, including its risks and benefits.

Is the medication safe and what is the right dose?   Phase one trials involve small numbers of participants, often normal volunteers.

Does the new medication work and what are the side effects?   Phase two trials test the treatment or procedure on a larger number of participants. These participants usually have the condition or disease that the treatment is intended to remedy.

Is the new medication more effective than existing treatments?  Phase three trials have even more people enrolled. Some may get a placebo (a substance that has no medical effect) or an already approved treatment, so that the new medication can be compared to that treatment.

Is the new medication effective and safe over the long term?   Phase four happens after the treatment or procedure has been approved. Information about patients who are receiving the treatment is gathered and studied to see if any new information is seen when given to a large number of patients.

“Johns Hopkins has a comprehensive system overseeing research that is audited by the FDA and the Association for Accreditation of Human Research Protection Programs to make certain all research participants voluntarily agreed to join a study and their safety was maximized.” Gail Daumit, M.D., M.H.S., Vice Dean for Clinical Investigation, Johns Hopkins University School of Medicine

Is It Safe to Participate in Clinical Research?

There are several steps in place to protect volunteers who take part in clinical research studies. Clinical Research is regulated by the federal government. In addition, the institutional review board (IRB) and Human Subjects Research Protection Program at each study location have many safeguards built in to each study to protect the safety and privacy of participants.

Clinical researchers are required by law to follow the safety rules outlined by each study's protocol. A protocol is a detailed plan of what researchers will do in during the study.

In the U.S., every study site's IRB — which is made up of both medical experts and members of the general public — must approve all clinical research. IRB members also review plans for all clinical studies. And, they make sure that research participants are protected from as much risk as possible.

Earning Your Trust

This was not always the case. Many people of color are wary of joining clinical research because of previous poor treatment of underrepresented minorities throughout the U.S. This includes medical research performed on enslaved people without their consent, or not giving treatment to Black men who participated in the Tuskegee Study of Untreated Syphilis in the Negro Male. Since the 1970s, numerous regulations have been in place to protect the rights of study participants.

Many clinical research studies are also supervised by a data and safety monitoring committee. This is a group made up of experts in the area being studied. These biomedical professionals regularly monitor clinical studies as they progress. If they discover or suspect any problems with a study, they immediately stop the trial. In addition, Johns Hopkins Medicine’s Research Participant Advocacy Group focuses on improving the experience of people who participate in clinical research.

Clinical research participants with concerns about anything related to the study they are taking part in should contact Johns Hopkins Medicine’s IRB or our Research Participant Advocacy Group .

Learn More About Clinical Research at Johns Hopkins Medicine

For information about clinical trial opportunities at Johns Hopkins Medicine, visit our trials site.

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Qualitative study.

Steven Tenny ; Janelle M. Brannan ; Grace D. Brannan .

Affiliations

Last Update: September 18, 2022 .

• Introduction

Qualitative research is a type of research that explores and provides deeper insights into real-world problems. [1] Instead of collecting numerical data points or intervene or introduce treatments just like in quantitative research, qualitative research helps generate hypotheses as well as further investigate and understand quantitative data. Qualitative research gathers participants' experiences, perceptions, and behavior. It answers the hows and whys instead of how many or how much. It could be structured as a stand-alone study, purely relying on qualitative data or it could be part of mixed-methods research that combines qualitative and quantitative data. This review introduces the readers to some basic concepts, definitions, terminology, and application of qualitative research.

Qualitative research at its core, ask open-ended questions whose answers are not easily put into numbers such as ‘how’ and ‘why’. [2] Due to the open-ended nature of the research questions at hand, qualitative research design is often not linear in the same way quantitative design is. [2] One of the strengths of qualitative research is its ability to explain processes and patterns of human behavior that can be difficult to quantify. [3] Phenomena such as experiences, attitudes, and behaviors can be difficult to accurately capture quantitatively, whereas a qualitative approach allows participants themselves to explain how, why, or what they were thinking, feeling, and experiencing at a certain time or during an event of interest. Quantifying qualitative data certainly is possible, but at its core, qualitative data is looking for themes and patterns that can be difficult to quantify and it is important to ensure that the context and narrative of qualitative work are not lost by trying to quantify something that is not meant to be quantified.

However, while qualitative research is sometimes placed in opposition to quantitative research, where they are necessarily opposites and therefore ‘compete’ against each other and the philosophical paradigms associated with each, qualitative and quantitative work are not necessarily opposites nor are they incompatible. [4] While qualitative and quantitative approaches are different, they are not necessarily opposites, and they are certainly not mutually exclusive. For instance, qualitative research can help expand and deepen understanding of data or results obtained from quantitative analysis. For example, say a quantitative analysis has determined that there is a correlation between length of stay and level of patient satisfaction, but why does this correlation exist? This dual-focus scenario shows one way in which qualitative and quantitative research could be integrated together.

Examples of Qualitative Research Approaches

Ethnography

Ethnography as a research design has its origins in social and cultural anthropology, and involves the researcher being directly immersed in the participant’s environment. [2] Through this immersion, the ethnographer can use a variety of data collection techniques with the aim of being able to produce a comprehensive account of the social phenomena that occurred during the research period. [2] That is to say, the researcher’s aim with ethnography is to immerse themselves into the research population and come out of it with accounts of actions, behaviors, events, etc. through the eyes of someone involved in the population. Direct involvement of the researcher with the target population is one benefit of ethnographic research because it can then be possible to find data that is otherwise very difficult to extract and record.

Grounded Theory

Grounded Theory is the “generation of a theoretical model through the experience of observing a study population and developing a comparative analysis of their speech and behavior.” [5] As opposed to quantitative research which is deductive and tests or verifies an existing theory, grounded theory research is inductive and therefore lends itself to research that is aiming to study social interactions or experiences. [3] [2] In essence, Grounded Theory’s goal is to explain for example how and why an event occurs or how and why people might behave a certain way. Through observing the population, a researcher using the Grounded Theory approach can then develop a theory to explain the phenomena of interest.

Phenomenology

Phenomenology is defined as the “study of the meaning of phenomena or the study of the particular”. [5] At first glance, it might seem that Grounded Theory and Phenomenology are quite similar, but upon careful examination, the differences can be seen. At its core, phenomenology looks to investigate experiences from the perspective of the individual. [2] Phenomenology is essentially looking into the ‘lived experiences’ of the participants and aims to examine how and why participants behaved a certain way, from their perspective . Herein lies one of the main differences between Grounded Theory and Phenomenology. Grounded Theory aims to develop a theory for social phenomena through an examination of various data sources whereas Phenomenology focuses on describing and explaining an event or phenomena from the perspective of those who have experienced it.

Narrative Research

One of qualitative research’s strengths lies in its ability to tell a story, often from the perspective of those directly involved in it. Reporting on qualitative research involves including details and descriptions of the setting involved and quotes from participants. This detail is called ‘thick’ or ‘rich’ description and is a strength of qualitative research. Narrative research is rife with the possibilities of ‘thick’ description as this approach weaves together a sequence of events, usually from just one or two individuals, in the hopes of creating a cohesive story, or narrative. [2] While it might seem like a waste of time to focus on such a specific, individual level, understanding one or two people’s narratives for an event or phenomenon can help to inform researchers about the influences that helped shape that narrative. The tension or conflict of differing narratives can be “opportunities for innovation”. [2]

Research Paradigm

Research paradigms are the assumptions, norms, and standards that underpin different approaches to research. Essentially, research paradigms are the ‘worldview’ that inform research. [4] It is valuable for researchers, both qualitative and quantitative, to understand what paradigm they are working within because understanding the theoretical basis of research paradigms allows researchers to understand the strengths and weaknesses of the approach being used and adjust accordingly. Different paradigms have different ontology and epistemologies . Ontology is defined as the "assumptions about the nature of reality” whereas epistemology is defined as the “assumptions about the nature of knowledge” that inform the work researchers do. [2] It is important to understand the ontological and epistemological foundations of the research paradigm researchers are working within to allow for a full understanding of the approach being used and the assumptions that underpin the approach as a whole. Further, it is crucial that researchers understand their own ontological and epistemological assumptions about the world in general because their assumptions about the world will necessarily impact how they interact with research. A discussion of the research paradigm is not complete without describing positivist, postpositivist, and constructivist philosophies.

Positivist vs Postpositivist

To further understand qualitative research, we need to discuss positivist and postpositivist frameworks. Positivism is a philosophy that the scientific method can and should be applied to social as well as natural sciences. [4] Essentially, positivist thinking insists that the social sciences should use natural science methods in its research which stems from positivist ontology that there is an objective reality that exists that is fully independent of our perception of the world as individuals. Quantitative research is rooted in positivist philosophy, which can be seen in the value it places on concepts such as causality, generalizability, and replicability.

Conversely, postpositivists argue that social reality can never be one hundred percent explained but it could be approximated. [4] Indeed, qualitative researchers have been insisting that there are “fundamental limits to the extent to which the methods and procedures of the natural sciences could be applied to the social world” and therefore postpositivist philosophy is often associated with qualitative research. [4] An example of positivist versus postpositivist values in research might be that positivist philosophies value hypothesis-testing, whereas postpositivist philosophies value the ability to formulate a substantive theory.

Constructivist

Constructivism is a subcategory of postpositivism. Most researchers invested in postpositivist research are constructivist as well, meaning they think there is no objective external reality that exists but rather that reality is constructed. Constructivism is a theoretical lens that emphasizes the dynamic nature of our world. “Constructivism contends that individuals’ views are directly influenced by their experiences, and it is these individual experiences and views that shape their perspective of reality”. [6] Essentially, Constructivist thought focuses on how ‘reality’ is not a fixed certainty and experiences, interactions, and backgrounds give people a unique view of the world. Constructivism contends, unlike in positivist views, that there is not necessarily an ‘objective’ reality we all experience. This is the ‘relativist’ ontological view that reality and the world we live in are dynamic and socially constructed. Therefore, qualitative scientific knowledge can be inductive as well as deductive.” [4]

So why is it important to understand the differences in assumptions that different philosophies and approaches to research have? Fundamentally, the assumptions underpinning the research tools a researcher selects provide an overall base for the assumptions the rest of the research will have and can even change the role of the researcher themselves. [2] For example, is the researcher an ‘objective’ observer such as in positivist quantitative work? Or is the researcher an active participant in the research itself, as in postpositivist qualitative work? Understanding the philosophical base of the research undertaken allows researchers to fully understand the implications of their work and their role within the research, as well as reflect on their own positionality and bias as it pertains to the research they are conducting.

Data Sampling 

The better the sample represents the intended study population, the more likely the researcher is to encompass the varying factors at play. The following are examples of participant sampling and selection: [7]

• Purposive sampling- selection based on the researcher’s rationale in terms of being the most informative.
• Criterion sampling-selection based on pre-identified factors.
• Convenience sampling- selection based on availability.
• Snowball sampling- the selection is by referral from other participants or people who know potential participants.
• Extreme case sampling- targeted selection of rare cases.
• Typical case sampling-selection based on regular or average participants. 

Data Collection and Analysis

Qualitative research uses several techniques including interviews, focus groups, and observation. [1] [2] [3] Interviews may be unstructured, with open-ended questions on a topic and the interviewer adapts to the responses. Structured interviews have a predetermined number of questions that every participant is asked. It is usually one on one and is appropriate for sensitive topics or topics needing an in-depth exploration. Focus groups are often held with 8-12 target participants and are used when group dynamics and collective views on a topic are desired. Researchers can be a participant-observer to share the experiences of the subject or a non-participant or detached observer.

While quantitative research design prescribes a controlled environment for data collection, qualitative data collection may be in a central location or in the environment of the participants, depending on the study goals and design. Qualitative research could amount to a large amount of data. Data is transcribed which may then be coded manually or with the use of Computer Assisted Qualitative Data Analysis Software or CAQDAS such as ATLAS.ti or NVivo. [8] [9] [10]

After the coding process, qualitative research results could be in various formats. It could be a synthesis and interpretation presented with excerpts from the data. [11] Results also could be in the form of themes and theory or model development.

Dissemination

To standardize and facilitate the dissemination of qualitative research outcomes, the healthcare team can use two reporting standards. The Consolidated Criteria for Reporting Qualitative Research or COREQ is a 32-item checklist for interviews and focus groups. [12] The Standards for Reporting Qualitative Research (SRQR) is a checklist covering a wider range of qualitative research. [13]

Examples of Application

Many times a research question will start with qualitative research. The qualitative research will help generate the research hypothesis which can be tested with quantitative methods. After the data is collected and analyzed with quantitative methods, a set of qualitative methods can be used to dive deeper into the data for a better understanding of what the numbers truly mean and their implications. The qualitative methods can then help clarify the quantitative data and also help refine the hypothesis for future research. Furthermore, with qualitative research researchers can explore subjects that are poorly studied with quantitative methods. These include opinions, individual's actions, and social science research.

A good qualitative study design starts with a goal or objective. This should be clearly defined or stated. The target population needs to be specified. A method for obtaining information from the study population must be carefully detailed to ensure there are no omissions of part of the target population. A proper collection method should be selected which will help obtain the desired information without overly limiting the collected data because many times, the information sought is not well compartmentalized or obtained. Finally, the design should ensure adequate methods for analyzing the data. An example may help better clarify some of the various aspects of qualitative research.

A researcher wants to decrease the number of teenagers who smoke in their community. The researcher could begin by asking current teen smokers why they started smoking through structured or unstructured interviews (qualitative research). The researcher can also get together a group of current teenage smokers and conduct a focus group to help brainstorm factors that may have prevented them from starting to smoke (qualitative research).

In this example, the researcher has used qualitative research methods (interviews and focus groups) to generate a list of ideas of both why teens start to smoke as well as factors that may have prevented them from starting to smoke. Next, the researcher compiles this data. The research found that, hypothetically, peer pressure, health issues, cost, being considered “cool,” and rebellious behavior all might increase or decrease the likelihood of teens starting to smoke.

The researcher creates a survey asking teen participants to rank how important each of the above factors is in either starting smoking (for current smokers) or not smoking (for current non-smokers). This survey provides specific numbers (ranked importance of each factor) and is thus a quantitative research tool.

The researcher can use the results of the survey to focus efforts on the one or two highest-ranked factors. Let us say the researcher found that health was the major factor that keeps teens from starting to smoke, and peer pressure was the major factor that contributed to teens to start smoking. The researcher can go back to qualitative research methods to dive deeper into each of these for more information. The researcher wants to focus on how to keep teens from starting to smoke, so they focus on the peer pressure aspect.

The researcher can conduct interviews and/or focus groups (qualitative research) about what types and forms of peer pressure are commonly encountered, where the peer pressure comes from, and where smoking first starts. The researcher hypothetically finds that peer pressure often occurs after school at the local teen hangouts, mostly the local park. The researcher also hypothetically finds that peer pressure comes from older, current smokers who provide the cigarettes.

The researcher could further explore this observation made at the local teen hangouts (qualitative research) and take notes regarding who is smoking, who is not, and what observable factors are at play for peer pressure of smoking. The researcher finds a local park where many local teenagers hang out and see that a shady, overgrown area of the park is where the smokers tend to hang out. The researcher notes the smoking teenagers buy their cigarettes from a local convenience store adjacent to the park where the clerk does not check identification before selling cigarettes. These observations fall under qualitative research.

If the researcher returns to the park and counts how many individuals smoke in each region of the park, this numerical data would be quantitative research. Based on the researcher's efforts thus far, they conclude that local teen smoking and teenagers who start to smoke may decrease if there are fewer overgrown areas of the park and the local convenience store does not sell cigarettes to underage individuals.

The researcher could try to have the parks department reassess the shady areas to make them less conducive to the smokers or identify how to limit the sales of cigarettes to underage individuals by the convenience store. The researcher would then cycle back to qualitative methods of asking at-risk population their perceptions of the changes, what factors are still at play, as well as quantitative research that includes teen smoking rates in the community, the incidence of new teen smokers, among others. [14] [15]

Qualitative research functions as a standalone research design or in combination with quantitative research to enhance our understanding of the world. Qualitative research uses techniques including structured and unstructured interviews, focus groups, and participant observation to not only help generate hypotheses which can be more rigorously tested with quantitative research but also to help researchers delve deeper into the quantitative research numbers, understand what they mean, and understand what the implications are.  Qualitative research provides researchers with a way to understand what is going on, especially when things are not easily categorized. [16]

• Issues of Concern

As discussed in the sections above, quantitative and qualitative work differ in many different ways, including the criteria for evaluating them. There are four well-established criteria for evaluating quantitative data: internal validity, external validity, reliability, and objectivity. The correlating concepts in qualitative research are credibility, transferability, dependability, and confirmability. [4] [11] The corresponding quantitative and qualitative concepts can be seen below, with the quantitative concept is on the left, and the qualitative concept is on the right:

• Internal validity--- Credibility
• External validity---Transferability
• Reliability---Dependability
• Objectivity---Confirmability

In conducting qualitative research, ensuring these concepts are satisfied and well thought out can mitigate potential issues from arising. For example, just as a researcher will ensure that their quantitative study is internally valid so should qualitative researchers ensure that their work has credibility.  

Indicators such as triangulation and peer examination can help evaluate the credibility of qualitative work.

• Triangulation: Triangulation involves using multiple methods of data collection to increase the likelihood of getting a reliable and accurate result. In our above magic example, the result would be more reliable by also interviewing the magician, back-stage hand, and the person who "vanished." In qualitative research, triangulation can include using telephone surveys, in-person surveys, focus groups, and interviews as well as surveying an adequate cross-section of the target demographic.
• Peer examination: Results can be reviewed by a peer to ensure the data is consistent with the findings.

‘Thick’ or ‘rich’ description can be used to evaluate the transferability of qualitative research whereas using an indicator such as an audit trail might help with evaluating the dependability and confirmability.

• Thick or rich description is a detailed and thorough description of details, the setting, and quotes from participants in the research. [5] Thick descriptions will include a detailed explanation of how the study was carried out. Thick descriptions are detailed enough to allow readers to draw conclusions and interpret the data themselves, which can help with transferability and replicability.
• Audit trail: An audit trail provides a documented set of steps of how the participants were selected and the data was collected. The original records of information should also be kept (e.g., surveys, notes, recordings).

One issue of concern that qualitative researchers should take into consideration is observation bias. Here are a few examples:

• Hawthorne effect: The Hawthorne effect is the change in participant behavior when they know they are being observed. If a researcher was wanting to identify factors that contribute to employee theft and tells the employees they are going to watch them to see what factors affect employee theft, one would suspect employee behavior would change when they know they are being watched.
• Observer-expectancy effect: Some participants change their behavior or responses to satisfy the researcher's desired effect. This happens in an unconscious manner for the participant so it is important to eliminate or limit transmitting the researcher's views.
• Artificial scenario effect: Some qualitative research occurs in artificial scenarios and/or with preset goals. In such situations, the information may not be accurate because of the artificial nature of the scenario. The preset goals may limit the qualitative information obtained.
• Clinical Significance

Qualitative research by itself or combined with quantitative research helps healthcare providers understand patients and the impact and challenges of the care they deliver. Qualitative research provides an opportunity to generate and refine hypotheses and delve deeper into the data generated by quantitative research. Qualitative research does not exist as an island apart from quantitative research, but as an integral part of research methods to be used for the understanding of the world around us. [17]

• Enhancing Healthcare Team Outcomes

Qualitative research is important for all members of the health care team as all are affected by qualitative research. Qualitative research may help develop a theory or a model for health research that can be further explored by quantitative research.  Much of the qualitative research data acquisition is completed by numerous team members including social works, scientists, nurses, etc.  Within each area of the medical field, there is copious ongoing qualitative research including physician-patient interactions, nursing-patient interactions, patient-environment interactions, health care team function, patient information delivery, etc. 

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Disclosure: Steven Tenny declares no relevant financial relationships with ineligible companies.

Disclosure: Janelle Brannan declares no relevant financial relationships with ineligible companies.

Disclosure: Grace Brannan declares no relevant financial relationships with ineligible companies.

This book is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ), which permits others to distribute the work, provided that the article is not altered or used commercially. You are not required to obtain permission to distribute this article, provided that you credit the author and journal.

• Cite this Page Tenny S, Brannan JM, Brannan GD. Qualitative Study. [Updated 2022 Sep 18]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.

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What marijuana reclassification means for the United States

The U.S. Drug Enforcement Administration will move to reclassify marijuana as a less dangerous drug, a historic shift to generations of American drug policy that could have wide ripple effects across the country.

FILE - Marijuana plants are seen at a secured growing facility in Washington County, N.Y., May 12, 2023. The U.S. Drug Enforcement Administration will move to reclassify marijuana as a less dangerous drug, a historic shift to generations of American drug policy that could have wide ripple effects across the country. (AP Photo/Hans Pennink, File)

• Copy Link copied

Budtender Rey Cruz weighs cannabis for a customer at the Marijuana Paradise on Friday, April 19, 2024, in Portland, Ore. (AP Photo/Jenny Kane)

Cloud 9 Cannabis employee Beau McQueen, right, helps a customer, Saturday, April 13, 2024, in Arlington, Wash. The shop is one of the first dispensaries to open under the Washington Liquor and Cannabis Board’s social equity program, established in efforts to remedy some of the disproportionate effects marijuana prohibition had on communities of color. (AP Photo/Lindsey Wasson)

WASHINGTON (AP) — The U.S. Drug Enforcement Administration is moving toward reclassifying marijuana as a less dangerous drug. The Justice Department proposal would recognize the medical uses of cannabis , but wouldn’t legalize it for recreational use.

The proposal would move marijuana from the “Schedule I” group to the less tightly regulated “Schedule III.”

So what does that mean, and what are the implications?

WHAT HAS ACTUALLY CHANGED? WHAT HAPPENS NEXT?

Technically, nothing yet. The proposal must be reviewed by the White House Office of Management and Budget, and then undergo a public-comment period and review from an administrative judge, a potentially lengthy process.

Still, the switch is considered “paradigm-shifting, and it’s very exciting,” Vince Sliwoski, a Portland, Oregon-based cannabis and psychedelics attorney who runs well-known legal blogs on those topics, told The Associated Press when the federal Health and Human Services Department recommended the change.

“I can’t emphasize enough how big of news it is,” he said.

It came after President Joe Biden asked both HHS and the attorney general, who oversees the DEA, last year to review how marijuana was classified. Schedule I put it on par, legally, with heroin, LSD, quaaludes and ecstasy, among others.

Biden, a Democrat, supports legalizing medical marijuana for use “where appropriate, consistent with medical and scientific evidence,” White House press secretary Karine Jean-Pierre said Thursday. “That is why it is important for this independent review to go through.”

Cloud 9 Cannabis employee Beau McQueen, right, helps a customer, Saturday, April 13, 2024, in Arlington, Wash. (AP Photo/Lindsey Wasson)

IF MARIJUANA GETS RECLASSIFIED, WOULD IT LEGALIZE RECREATIONAL CANNABIS NATIONWIDE?

Ap audio: what marijuana reclassification means for the united states.

AP correspondent Haya Panjwani reports on a proposal for the federal government to reclassify marijuana in what would be a historic shift that could have wide ripple effects across the country.

No. Schedule III drugs — which include ketamine, anabolic steroids and some acetaminophen-codeine combinations — are still controlled substances.

They’re subject to various rules that allow for some medical uses, and for federal criminal prosecution of anyone who traffics in the drugs without permission.

No changes are expected to the medical marijuana programs now licensed in 38 states or the legal recreational cannabis markets in 23 states, but it’s unlikely they would meet the federal production, record-keeping, prescribing and other requirements for Schedule III drugs.

There haven’t been many federal prosecutions for simply possessing marijuana in recent years, even under marijuana’s current Schedule I status, but the reclassification wouldn’t have an immediate impact on people already in the criminal justice system.

“Put simple, this move from Schedule I to Schedule III is not getting people out of jail,” said David Culver, senior vice president of public affairs at the U.S. Cannabis Council.

But rescheduling in itself would have some impact, particularly on research and marijuana business taxes.

WHAT WOULD THIS MEAN FOR RESEARCH?

Because marijuana is on Schedule I, it’s been very difficult to conduct authorized clinical studies that involve administering the drug. That has created something of a Catch-22: calls for more research, but barriers to doing it. (Scientists sometimes rely instead on people’s own reports of their marijuana use.)

Marijuana plants are seen at a secured growing facility in Washington County, N.Y., May 12, 2023. (AP Photo/Hans Pennink, File)

Schedule III drugs are easier to study, though the reclassification wouldn’t immediately reverse all barriers to study.

“It’s going to be really confusing for a long time,” said Ziva Cooper, director of the University of California, Los Angeles Center for Cannabis and Cannabinoids. “When the dust has settled, I don’t know how many years from now, research will be easier.”

Among the unknowns: whether researchers will be able to study marijuana from state-licensed dispensaries and how the federal Food and Drug Administration might oversee that.

Some researchers are optimistic.

“Reducing the schedule to schedule 3 will open up the door for us to be able to conduct research with human subjects with cannabis,” said Susan Ferguson, director of University of Washington’s Addictions, Drug & Alcohol Institute in Seattle.

WHAT ABOUT TAXES (AND BANKING)?

Under the federal tax code, businesses involved in “trafficking” in marijuana or any other Schedule I or II drug can’t deduct rent, payroll or various other expenses that other businesses can write off. (Yes, at least some cannabis businesses, particularly state-licensed ones, do pay taxes to the federal government, despite its prohibition on marijuana.) Industry groups say the tax rate often ends up at 70% or more.

The deduction rule doesn’t apply to Schedule III drugs, so the proposed change would cut cannabis companies’ taxes substantially.

They say it would treat them like other industries and help them compete against illegal competitors that are frustrating licensees and officials in places such as New York .

“You’re going to make these state-legal programs stronger,” says Adam Goers, of The Cannabist Company, formerly Columbia Care. He co-chairs a coalition of corporate and other players that’s pushing for rescheduling.

It could also mean more cannabis promotion and advertising if those costs could be deducted, according to Beau Kilmer, co-director of the RAND Drug Policy Center.

Rescheduling wouldn’t directly affect another marijuana business problem: difficulty accessing banks, particularly for loans, because the federally regulated institutions are wary of the drug’s legal status. The industry has been looking instead to a measure called the SAFE Banking Act . It has repeatedly passed the House but stalled in the Senate.

ARE THERE CRITICS? WHAT DO THEY SAY?

Indeed, there are, including the national anti-legalization group Smart Approaches to Marijuana. President Kevin Sabet, a former Obama administration drug policy official, said the HHS recommendation “flies in the face of science, reeks of politics” and gives a regrettable nod to an industry “desperately looking for legitimacy.”

Some legalization advocates say rescheduling weed is too incremental. They want to keep the focus on removing it completely from the controlled substances list, which doesn’t include such items as alcohol or tobacco (they’re regulated, but that’s not the same).

Paul Armentano, the deputy director of the National Organization for the Reform of Marijuana Laws, said that simply reclassifying marijuana would be “perpetuating the existing divide between state and federal marijuana policies.” Kaliko Castille, a past president of the Minority Cannabis Business Association, said rescheduling just “re-brands prohibition,” rather than giving an all-clear to state licensees and putting a definitive close to decades of arrests that disproportionately pulled in people of color.

“Schedule III is going to leave it in this kind of amorphous, mucky middle where people are not going to understand the danger of it still being federally illegal,” he said.

This story has been corrected to show that Kaliko Castille is a past president, not president, of the Minority Cannabis Business Association and that Columbia Care is now The Cannabist Company.

___ Peltz reported from New York. Associated Press writers Colleen Long in Washington and Carla K. Johnson in Seattle contributed to this report.

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• Published: 06 May 2024

Venus water loss is dominated by HCO + dissociative recombination

• M. S. Chaffin   ORCID: orcid.org/0000-0002-1939-4797 1   na1 ,
• E. M. Cangi 1   na1 ,
• B. S. Gregory 1 ,
• R. V. Yelle 2 ,
• J. Deighan   ORCID: orcid.org/0000-0003-3667-902X 1 ,
• R. D. Elliott 1 &
• H. Gröller 2  

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• Atmospheric chemistry
• Inner planets

Despite its Earth-like size and source material 1 , 2 , Venus is extremely dry 3 , 4 , indicating near-total water loss to space by means of hydrogen outflow from an ancient, steam-dominated atmosphere 5 , 6 . Such hydrodynamic escape likely removed most of an initial Earth-like 3-km global equivalent layer (GEL) of water but cannot deplete the atmosphere to the observed 3-cm GEL because it shuts down below about 10–100 m GEL 5 , 7 . To complete Venus water loss, and to produce the observed bulk atmospheric enrichment in deuterium of about 120 times Earth 8 , 9 , nonthermal H escape mechanisms still operating today are required 10 , 11 . Early studies identified these as resonant charge exchange 12 , 13 , 14 , hot oxygen impact 15 , 16 and ion outflow 17 , 18 , establishing a consensus view of H escape 10 , 19 that has since received only minimal updates 20 . Here we show that this consensus omits the most important present-day H loss process, HCO + dissociative recombination. This process nearly doubles the Venus H escape rate and, consequently, doubles the amount of present-day volcanic water outgassing and/or impactor infall required to maintain a steady-state atmospheric water abundance. These higher loss rates resolve long-standing difficulties in simultaneously explaining the measured abundance and isotope ratio of Venusian water 21 , 22 and would enable faster desiccation in the wake of speculative late ocean scenarios 23 . Design limitations prevented past Venus missions from measuring both HCO + and the escaping hydrogen produced by its recombination; future spacecraft measurements are imperative.

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Oxygen production from dissociation of Europa’s water-ice surface

Isotopic fractionation of water and its photolytic products in the atmosphere of Mars

Dry late accretion inferred from Venus’s coupled atmosphere and internal evolution

Data availability.

Tables containing all reactions used in the model, including their adopted rate coefficients and computed column rates, are provided in a supplementary PDF file accessible on the journal website. These rates are also accessible in the archived code repository listed below, which also includes our adopted photo cross-sections and all other source data used in our model. Model densities for all species, computed rates for reactions shown in Fig. 2 , assumed temperature and escape probabilities and computed photo rates are provided in Excel format in the online version of the paper; this file also includes data for our illustrative water-inventory timelines.  Source data are provided with this paper.

Code availability

All model code is available at github.com/emcangi/VenusPhotochemistry . The version of the model used to prepare the manuscript is archived on Zenodo at https://doi.org/10.5281/zenodo.10460004 .

Izidoro, A. et al. Planetesimal rings as the cause of the Solar System’s planetary architecture. Nat. Astron. 6 , 357–366 (2022).

Article   ADS   Google Scholar  

Salvador, A. et al. Magma ocean, water, and the early atmosphere of Venus. Space Sci. Rev. 219 , 51 (2023).

Article   ADS   CAS   Google Scholar  

Moroz, V. I. et al. Spectrum of the Venus day sky. Nature 284 , 243–244 (1980).

Marcq, E., Mills, F. P., Parkinson, C. D. & Vandaele, A. C. Composition and chemistry of the neutral atmosphere of Venus. Space Sci. Rev. 214 , 10 (2018).

Kasting, J. F. & Pollack, J. B. Loss of water from Venus. I. Hydrodynamic escape of hydrogen. Icarus 53 , 479–508 (1983).

Turbet, M. et al. Day–night cloud asymmetry prevents early oceans on Venus but not on Earth. Nature 598 , 276–280 (2021).

Article   ADS   CAS   PubMed   Google Scholar  

Johnstone, C. P. Hydrodynamic escape of water vapor atmospheres near very active stars. Astrophys. J. 890 , 79 (2020).

Donahue, T. M., Hoffman, J. H., Hodges, R. R. & Watson, A. J. Venus was wet: a measurement of the ratio of deuterium to hydrogen. Science 216 , 630–633 (1982).

De Bergh, C. et al. Deuterium on Venus: observations from Earth. Science 251 , 547–549 (1991).

Article   ADS   PubMed   Google Scholar  

Kumar, S., Hunten, D. M. & Pollack, J. B. Nonthermal escape of hydrogen and deuterium from Venus and implications for loss of water. Icarus 55 , 369–389 (1983).

Donahue, T. M. New analysis of hydrogen and deuterium escape from Venus. Icarus 141 , 226–235 (1999).

Stewart, A. I. F. in Second Arizona Conference on Planetary Atmospheres (1968).

Hodges, R. R. An exospheric perspective of isotopic fractionation of hydrogen on Venus. J. Geophys. Res. Planets 104 , 8463–8471 (1999).

Chaufray, J.-Y., Bertaux, J.-L., Quémerais, E., Villard, E. & Leblanc, F. Hydrogen density in the dayside Venusian exosphere derived from Lyman-α observations by SPICAV on Venus Express. Icarus 217 , 767–778 (2012).

McElroy, M. B., Prather, M. J. & Rodriguez, J. M. Escape of hydrogen from Venus. Science 215 , 1614–1615 (1982).

Gu, H., Cui, J., Niu, D. & Yu, J. Hydrogen and helium escape on Venus via energy transfer from hot oxygen atoms. Mon. Not. R. Astron. Soc. 501 , 2394–2402 (2021).

Hartle, R. E. & Grebowsky, J. M. Light ion flow in the nightside ionosphere of Venus. J. Geophys. Res. Planets 98 , 7437–7445 (1993).

Persson, M. et al. H + /O + escape rate ratio in the Venus magnetotail and its dependence on the solar cycle. Geophys. Res. Lett. 45 , 10805–10811 (2018).

Lammer, H. et al. Loss of hydrogen and oxygen from the upper atmosphere of Venus. Planet. Space Sci. 54 , 1445–1456 (2006).

Gillmann, C. et al. The long-term evolution of the atmosphere of Venus: processes and feedback mechanisms. Space Sci. Rev. 218 , 56 (2022).

Grinspoon, D. H. Implications of the high D/H ratio for the sources of water in Venus’ atmosphere. Nature 363 , 428–431 (1993).

Avice, G. et al. Noble gases and stable isotopes track the origin and early evolution of the Venus atmosphere. Space Sci. Rev. 218 , 60 (2022).

Way, M. J. & Del Genio, A. D. Venusian habitable climate scenarios: modeling Venus through time and applications to slowly rotating Venus-like exoplanets. J. Geophys. Res. Planets 125 , e06276 (2020).

Article   Google Scholar  

Chaffin, M. S., Deighan, J., Schneider, N. M. & Stewart, A. I. F. Elevated atmospheric escape of atomic hydrogen from Mars induced by high-altitude water. Nat. Geosci. 10 , 174–178 (2017).

Cangi, E. M., Chaffin, M. S. & Deighan, J. Higher Martian atmospheric temperatures at all altitudes increase the D/H fractionation factor and water loss. J. Geophys. Res. Planets 125 , e06626 (2020).

Cangi, E., Chaffin, M., Yelle, R., Gregory, B. & Deighan, J. Fully coupled photochemistry of the deuterated ionosphere of Mars and its effects on escape of H and D. J. Geophys. Res. Planets 128 , e2022JE007713 (2023).

Yung, Y. L. & Demore, W. B. Photochemistry of the stratosphere of Venus: implications for atmospheric evolution. Icarus 51 , 199–247 (1982).

Fox, J. L. & Sung, K. Y. Solar activity variations of the Venus thermosphere/ionosphere. J. Geophys. Res. Space Phys. 106 , 21305–21335 (2001).

Krasnopolsky, V. A. A photochemical model for the Venus atmosphere at 47–112 km. Icarus 218 , 230–246 (2012).

Fedorova, A. et al. HDO and H 2 O vertical distributions and isotopic ratio in the Venus mesosphere by Solar Occultation at Infrared spectrometer on board Venus Express. J. Geophys. Res. Planets 113 , E00B22 (2008).

Paxton, L. J., Anderson Jr, D. E. & Stewart, A. I. F. Analysis of Pioneer Venus Orbiter ultraviolet spectrometer Lyman α data from near the subsolar region. J. Geophys. Res. Space Phys. 93 , 1766–1772 (1988).

Fox, J. L. The post-terminator ionosphere of Venus. Icarus 216 , 625–639 (2011).

Brinton, H. C. et al. Venus nighttime hydrogen bulge. Geophys. Res. Lett. 7 , 865–868 (1980).

Martinez, A. et al. Exploring the variability of the Venusian thermosphere with the IPSL Venus GCM. Icarus 389 , 115272 (2023).

Article   CAS   Google Scholar  

Navarro, T. et al. Venus’ upper atmosphere revealed by a GCM: I. Structure and variability of the circulation. Icarus 366 , 114400 (2021).

Fox, J. L. The chemistry of protonated species in the Martian ionosphere. Icarus 252 , 366–392 (2015).

Taylor, H. A., Brinton, H. C., Wagner, T. C. G., Blackwell, B. H. & Cordier, G. R. Bennett ion mass spectrometers on the Pioneer Venus Bus and Orbiter. IEEE Tran. Geosci. Remote Sens. 18 , 44–49 (1980).

Miller, K. L., Knudsen, W. C. & Spenner, K. The dayside Venus ionosphere: I. Pioneer-Venus retarding potential analyzer experimental observations. Icarus 57 , 386–409 (1984).

Barabash, S. et al. The Analyser of Space Plasmas and Energetic Atoms (ASPERA-4) for the Venus Express mission. Planet. Space Sci. 55 , 1772–1792 (2007).

Bertaux, J. L. & Clarke, J. T. Deuterium content of the Venus atmosphere. Nature 338 , 567–568 (1989).

Donahue, T. M. Deuterium on Venus. Nature 340 , 513–514 (1989).

Liang, M.-C. & Yung, Y. L. Modeling the distribution of H 2 O and HDO in the upper atmosphere of Venus. J. Geophys. Res. Planets 114 , E00B28 (2009).

Parkinson, C. D. et al. Photochemical control of the distribution of Venusian water. Planet. Space Sci. 113 , 226–236 (2015).

Widemann, T. et al. Venus evolution through time: key science questions, selected mission concepts and future investigations. Space Sci. Rev. 219 , 56 (2023).

McClintock, W. E. et al. The Imaging Ultraviolet Spectrograph (IUVS) for the MAVEN Mission. Space Sci. Rev. 195 , 75–124 (2015).

Bertaux, J. L., Goutail, F., Dimarellis, E., Kockarts, G. & van Ransbeeck, E. First optical detection of atomic deuterium in the upper atmosphere from Spacelab 1. Nature 309 , 771–773 (1984).

Gregory, B. S., Elliott, R. D., Deighan, J., Gröller, H. & Chaffin, M. S. HCO + dissociative recombination: a significant driver of nonthermal hydrogen loss at Mars. J. Geophys. Res. Planets 128 , e2022JE007576 (2023).

Barth, C. A., Pearce, J. B., Kelly, K. K., Wallace, L. & Fastie, W. G. Ultraviolet emissions observed near Venus from Mariner V. Science 158 , 1675–1678 (1967).

Anderson, D. E. The Mariner 5 ultraviolet photometer experiment: analysis of hydrogen Lyman alpha data. J. Geophys. Res. 81 , 1213–1216 (1976).

Takacs, P., Broadfoot, A., Smith, G. & Kumar, S. Mariner 10 observations of hydrogen Lyman alpha emission from the Venus exosphere: evidence of complex structure. Planet. Space Sci. 28 , 687–701 (1980).

von Zahn, U., Kumar, S., Niemann, H. & Prinn, R. in Venus (eds Hunten D. M., Colin, L., Donahue, T. M. & Moroz, V. I.) 299–430 (Univ. Arizona Press, 1983).

Hunten, D. M. The escape of light gases from planetary atmospheres. J. Atmos. Sci. 30 , 1481–1494 (1973).

Krissansen-Totton, J., Fortney, J. J. & Nimmo, F. Was Venus ever habitable? Constraints from a coupled interior–atmosphere–redox evolution model. Planet. Sci. J. 2 , 216 (2021).

Warren, A. O. & Kite, E. S. Narrow range of early habitable Venus scenarios permitted by modeling of oxygen loss and radiogenic argon degassing. Proc. Natl Acad. Sci. 120 , e2209751120 (2023).

Article   CAS   PubMed   PubMed Central   Google Scholar  

Chassefière, E. Hydrodynamic escape of hydrogen from a hot water-rich atmosphere: the case of Venus. J. Geophys. Res. 101 , 26039–26056 (1996).

Chassefière, E. Loss of water on the young Venus: the effect of a strong primitive solar wind. Icarus 126 , 229–232 (1997).

Way, M. J. et al. Was Venus the first habitable world of our solar system? Geophys. Res. Lett. 43 , 8376–8383 (2016).

Article   ADS   CAS   PubMed   PubMed Central   Google Scholar  

Gillmann, C. et al. Dry late accretion inferred from Venus’s coupled atmosphere and internal evolution. Nat. Geosci. 13 , 265–269 (2020).

Selsis, F., Leconte, J., Turbet, M., Chaverot, G. & Bolmont, É. A cool runaway greenhouse without surface magma ocean. Nature 620 , 287–291 (2023).

Fox, J. L. & Bougher, S. W. Structure, luminosity, and dynamics of the Venus thermosphere. Space Sci. Rev. 55 , 357–489 (1991).

Hodges Jr, R. R. Collision cross sections and diffusion parameters for H and D in atomic oxygen. J. Geophys. Res. 98 , 3799–3805 (1993).

Shizgal, B. D. Escape of H and D from Mars and Venus by energization with hot oxygen. J. Geophys. Res. 104 , 14833–14846 (1999).

Yang, J., Boué, G., Fabrycky, D. C. & Abbot, D. S. Strong dependence of the inner edge of the habitable zone on planetary rotation rate. Astrophys. J. 787 , L2 (2014).

Herrick, R. R. & Hensley, S. Surface changes observed on a Venusian volcano during the Magellan mission. Science 379 , 1205–1208 (2023).

Rolf, T. et al. Dynamics and evolution of Venus’ mantle through time. Space Sci. Rev. 218 , 70 (2022).

Hedin, A. E., Niemann, H. B., Kasprzak, W. T. & Seiff, A. Global empirical model of the Venus thermosphere. J. Geophys. Res. 88 , 73–84 (1983).

Bertaux, J.-L. et al. SPICAV on Venus Express: three spectrometers to study the global structure and composition of the Venus atmosphere. Planet. Space Sci. 55 , 1673–1700 (2007).

Hagemann, R., Nief, G. & Roth, E. Absolute isotopic scale for deuterium analysis of natural waters. Absolute D/H ratio for SMOW. Tellus 22 , 712–715 (1970).

ADS   CAS   Google Scholar  

Lillis, R. et al. Photochemical escape of oxygen from Mars: first results from MAVEN in situ data. J. Geophys. Res. Space Phys. 122 , 3815–3836 (2017).

Rosati, R. E., Skrzypkowski, M. P., Johnsen, R. & Golde, M. F. Yield of excited CO molecules from dissociative recombination of HCO + and HOC + ions with electrons. J. Chem. Phys. 126 , 154302–154302 (2007).

Miller, K. L., Knudsen, C. W., Spenner, K., Whitten, R. C. & Novak, V. Solar zenith angle dependence of ionospheric ion and electron temperatures and density on Venus. J. Geophys. Res. Space Phys. 85 , 7759–7764 (1980).

Brace, L. H. et al. The dynamic behavior of the Venus ionosphere in response to solar wind interactions. J. Geophys. Res. 85 , 7663–7678 (1980).

Kasprzak, W. T. et al. in Venus II: Geology, Geophysics, Atmosphere, and Solar Wind Environment (eds Bougher, S. W. et al.) 225–258 (Univ. Arizona Press, 1997).

Niemann, H. B., Kasprzak, W. T., Hedin, A. E., Hunten, D. M. & Spencer, N. W. Mass spectrometric measurements of the neutral gas composition of the thermosphere and exosphere of Venus. J. Geophys. Res. Space Res. 85 , 7817–7827 (1980).

Fox, J. L. & Kliore, A. J. in Venus II: Geology, Geophysics, Atmosphere, and Solar Wind Environment (eds Bougher, S. W. et al.) 161–188 (Univ. Arizona Press, 1997).

Grebowsky, J. M., Kasprzak, W. T., Hartle, R. E. & Donahue, T. M. A new look at Venus’ thermosphere H distribution. Adv. Space Res. 17 , 191–195 (1996).

Donahue, T. M., Grinspoon, D. H., Hartle, R. E. & Hodges, R. R. Jr. in Venus II: Geology, Geophysics, Atmosphere, and Solar Wind Environment (eds Bougher, S. W. et al.) 385–414 (Univ. Arizona Press, 1997).

Stolzenbach, A., Lefèvre, F., Lebonnois, S. & Määttänen, A. Three-dimensional modeling of Venus photochemistry and clouds. Icarus 395 , 115447 (2023).

Dickinson, R. E. & Ridley, E. C. Venus mesosphere and thermosphere temperature structure: II. Day-night variations. Icarus 30 , 163–178 (1977).

Seiff, A. Dynamical implications of the observed thermal contrasts in Venus’ upper atmosphere. Icarus 51 , 574–592 (1982).

Garvin, J. B. et al. Revealing the mysteries of Venus: the DAVINCI mission. Planet. Sci. J. 3 , 117 (2022).

Smrekar, S. E. et al. VERITAS (Venus Emissivity, Radio Science, InSAR, Topography, and Spectroscopy): a selected discovery mission in 53rd Lunar and Planetary Science Conference. LPI contribution no. 2678, id. 1122 (2022).

Helbert, J. et al. The VenSpec suite on the ESA Envision mission – a holistic investigation of the coupled surface atmosphere system of Venus in 16th Europlanet Science Congress, id. EPSC2022-374 (2022).

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Acknowledgements

M.S.C., E.M.C., B.S.G. and R.D.E. were supported by NASA Solar System Workings grant 80NSSC19K0164 and Planetary Science Early Career Award grant 80NSSC20K1081. E.M.C. was also supported by NASA FINESST award 80NSSC22K1326. M.S.C. and E.M.C. thank M. Landis for helpful discussions about water delivery.

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These authors contributed equally: M. S. Chaffin, E. M. Cangi

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Laboratory for Atmospheric and Space Physics, University of Colorado Boulder, Boulder, CO, USA

M. S. Chaffin, E. M. Cangi, B. S. Gregory, J. Deighan & R. D. Elliott

Lunar and Planetary Laboratory, University of Arizona, Tucson, AZ, USA

R. V. Yelle & H. Gröller

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M.S.C. oversaw the study, performed final model calculations and the photochemical equilibrium calculation and wrote the initial text of the paper. E.M.C. developed the H-bearing and D-bearing photochemical model and nonthermal escape calculation originally used at Mars with a reaction network provided by R.V.Y. and performed initial model calculations for Venus. B.S.G. developed and ran the Monte Carlo model to generate escape probability curves. R.D.E. initially developed the Monte Carlo escape model with support from J.D. and H.G. H.G. performed pilot studies of HCO + -driven loss in the Mars atmosphere. All authors contributed to the interpretation and presentation of model results.

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Extended data figures and tables

Extended data fig. 1 model densities for all species..

The six panels function only to separate species for clarity.

Extended Data Fig. 2 Key photochemical model inputs.

a , Temperature profiles for neutrals, ions and electrons adapted from the inputs in ref.  28 . b , Adopted eddy diffusion profile and molecular diffusion coefficients for H and O atoms.

Extended Data Fig. 3 Implications of HCO + -driven loss for Venus ocean scenarios.

a , Escaping H production rates for the two most important processes in our model. b , Schematic water loss history of Venus.

Supplementary information

Supplementary information.

This file contains Supplementary Methods and Supplementary Tables. Merged PDF containing tables of reactions used in the model, assumed reaction rate coefficients and computed equilibrium model column rates.

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Chaffin, M.S., Cangi, E.M., Gregory, B.S. et al. Venus water loss is dominated by HCO + dissociative recombination. Nature 629 , 307–310 (2024). https://doi.org/10.1038/s41586-024-07261-y

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