what is definition of terms in research study

Confusion to Clarity: Definition of Terms in a Research Paper

Explore the definition of terms in research paper to enhance your understanding of crucial scientific terminology and grow your knowledge.

Have you ever come across a research paper and found yourself scratching your head over complex synonyms and unfamiliar terms? It’s a hassle as you have to fetch a dictionary and then ruffle through it to find the meaning of the terms.

To avoid that, an exclusive section called ‘ Definition of Terms in a Research Paper ’ is introduced which contains the definitions of terms used in the paper. Let us learn more about it in this article.

What Is The “Definition Of Terms” In A Research Paper?

The definition of terms section in a research paper provides a clear and concise explanation of key concepts, variables, and terminology used throughout the study. 

In the definition of terms section, researchers typically provide precise definitions for specific technical terms, acronyms, jargon, and any other domain-specific vocabulary used in their work. This section enhances the overall quality and rigor of the research by establishing a solid foundation for communication and understanding.

Purpose Of Definition Of Terms In A Research Paper

This section aims to ensure that readers have a common understanding of the terminology employed in the research, eliminating confusion and promoting clarity. The definitions provided serve as a reference point for readers, enabling them to comprehend the context and scope of the study. It serves several important purposes:

• Enhancing clarity
• Establishing a shared language
• Providing a reference point
• Setting the scope and context
• Ensuring consistency

Benefits Of Having A Definition Of Terms In A Research Paper

Having a definition of terms section in a research paper offers several benefits that contribute to the overall quality and effectiveness of the study. These benefits include:

Clarity And Comprehension

Clear definitions enable readers to understand the specific meanings of key terms, concepts, and variables used in the research. This promotes clarity and enhances comprehension, ensuring that readers can follow the study’s arguments, methods, and findings more easily.

Consistency And Precision

Definitions provide a consistent framework for the use of terminology throughout the research paper. By clearly defining terms, researchers establish a standard vocabulary, reducing ambiguity and potential misunderstandings. This precision enhances the accuracy and reliability of the study’s findings.

Common Understanding

The definition of terms section helps establish a shared understanding among readers, including those from different disciplines or with varying levels of familiarity with the subject matter. It ensures that readers approach the research with a common knowledge base, facilitating effective communication and interpretation of the results.

Avoiding Misinterpretation

Without clear definitions, readers may interpret terms and concepts differently, leading to misinterpretation of the research findings. By providing explicit definitions, researchers minimize the risk of misunderstandings and ensure that readers grasp the intended meaning of the terminology used in the study.

Accessibility For Diverse Audiences

Research papers are often read by a wide range of individuals, including researchers, students, policymakers, and professionals. Having a definition of terms in a research paper helps the diverse audience understand the concepts better and make appropriate decisions. 

Types Of Definitions

There are several types of definitions that researchers can employ in a research paper, depending on the context and nature of the study. Here are some common types of definitions:

Lexical Definitions

Lexical definitions provide the dictionary or commonly accepted meaning of a term. They offer a concise and widely recognized explanation of a word or concept. Lexical definitions are useful for establishing a baseline understanding of a term, especially when dealing with everyday language or non-technical terms.

Operational Definitions

Operational definitions define a term or concept about how it is measured or observed in the study. These definitions specify the procedures, instruments, or criteria used to operationalize an abstract or theoretical concept. Operational definitions help ensure clarity and consistency in data collection and measurement.

Conceptual Definitions

Conceptual definitions provide an abstract or theoretical understanding of a term or concept within a specific research context. They often involve a more detailed and nuanced explanation, exploring the underlying principles, theories, or models that inform the concept. Conceptual definitions are useful for establishing a theoretical framework and promoting deeper understanding.

Descriptive Definitions

Descriptive definitions describe a term or concept by providing characteristics, features, or attributes associated with it. These definitions focus on outlining the essential qualities or elements that define the term. Descriptive definitions help readers grasp the nature and scope of a concept by painting a detailed picture.

Theoretical Definitions

Theoretical definitions explain a term or concept based on established theories or conceptual frameworks. They situate the concept within a broader theoretical context, connecting it to relevant literature and existing knowledge. Theoretical definitions help researchers establish the theoretical underpinnings of their study and provide a foundation for further analysis.

Also read: Understanding What is Theoretical Framework

Types Of Terms

In research papers, various types of terms can be identified based on their nature and usage. Here are some common types of terms:

A key term is a term that holds significant importance or plays a crucial role within the context of a research paper. It is a term that encapsulates a core concept, idea, or variable that is central to the study. Key terms are often essential for understanding the research objectives, methodology, findings, and conclusions.

Technical Term

Technical terms refer to specialized vocabulary or terminology used within a specific field of study. These terms are often precise and have specific meanings within their respective disciplines. Examples include “allele,” “hypothesis testing,” or “algorithm.”

Legal Terms

Legal terms are specific vocabulary used within the legal field to describe concepts, principles, and regulations. These terms have particular meanings within the legal context. Examples include “defendant,” “plaintiff,” “due process,” or “jurisdiction.”

Definitional Term

A definitional term refers to a word or phrase that requires an explicit definition to ensure clarity and understanding within a particular context. These terms may be technical, abstract, or have multiple interpretations.

Career Privacy Term

Career privacy term refers to a concept or idea related to the privacy of individuals in the context of their professional or occupational activities. It encompasses the protection of personal information, and confidential data, and the right to control the disclosure of sensitive career-related details. 

A broad term is a term that encompasses a wide range of related concepts, ideas, or objects. It has a broader scope and may encompass multiple subcategories or specific examples.

Also read: Keywords In A Research Paper: The Importance Of The Right Choice

Steps To Writing Definitions Of Terms

When writing the definition of terms section for a research paper, you can follow these steps to ensure clarity and accuracy:

Step 1: Identify Key Terms

Review your research paper and identify the key terms that require definition. These terms are typically central to your study, specific to your field or topic, or may have different interpretations.

Step 2: Conduct Research

Conduct thorough research on each key term to understand its commonly accepted definition, usage, and any variations or nuances within your specific research context. Consult authoritative sources such as academic journals, books, or reputable online resources.

Step 3: Craft Concise Definitions

Based on your research, craft concise definitions for each key term. Aim for clarity, precision, and relevance. Define the term in a manner that reflects its significance within your research and ensures reader comprehension.

Step 4: Use Your Own Words

Paraphrase the definitions in your own words to avoid plagiarism and maintain academic integrity. While you can draw inspiration from existing definitions, rephrase them to reflect your understanding and writing style. Avoid directly copying from sources.

Step 5: Provide Examples Or Explanations

Consider providing examples, explanations, or context for the defined terms to enhance reader understanding. This can help illustrate how the term is applied within your research or clarify its practical implications.

Step 6: Order And Format

Decide on the order in which you present the definitions. You can follow alphabetical order or arrange them based on their importance or relevance to your research. Use consistent formatting, such as bold or italics, to distinguish the defined terms from the rest of the text.

Step 7: Revise And Refine

Review the definitions for clarity, coherence, and accuracy. Ensure that they align with your research objectives and are tailored to your specific study. Seek feedback from peers, mentors, or experts in your field to further refine and improve the definitions.

Step 8: Include Proper Citations

If you have drawn ideas or information from external sources, remember to provide proper citations for those sources. This demonstrates academic integrity and acknowledges the original authors.

Step 9: Incorporate The Section Into Your Paper

Integrate the definition of terms section into your research paper, typically as an early section following the introduction. Make sure it flows smoothly with the rest of the paper and provides a solid foundation for understanding the subsequent content.

By following these steps, you can create a well-crafted and informative definition of terms section that enhances the clarity and comprehension of your research paper.

In conclusion, the definition of terms in a research paper plays a critical role by providing clarity, establishing a common understanding, and enhancing communication among readers. The definition of terms section is an essential component that contributes to the overall quality, rigor, and effectiveness of a research paper.

Also read: Beyond The Main Text: The Value Of A Research Paper Appendix

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About Sowjanya Pedada

Sowjanya is a passionate writer and an avid reader. She holds MBA in Agribusiness Management and now is working as a content writer. She loves to play with words and hopes to make a difference in the world through her writings. Apart from writing, she is interested in reading fiction novels and doing craftwork. She also loves to travel and explore different cuisines and spend time with her family and friends.

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In Need of Definition: How to Select Terms to Define in your Dissertation

One section that is often required in a dissertation is the “Definitions of Terms.” This gives your readers an understanding of the concepts or factors that will be discussed throughout your study, as well as contextual information as to how you will be using those concepts in your study. The “Definitions of Terms” ensures that your readers will understand the components of your study in the way that you will be presenting them, because often your readers may have their own understanding of the terms, or not be familiar with them at all. In this section, you provide a list of terms that will be used throughout the dissertation and definitions of each of them. Seems simple enough, right? But how do you know which terms to define and which ones to leave out?

The rule of thumb is to include and define terms that are important to your study or are used frequently throughout the dissertation but are not common knowledge. You also want to include terms that have a unique meaning within the scope of your study. You do not need to include terms that most, if not all, of your readers will understand without having definitions provided. For example, something like leadership probably does not need to be included in your “Definitions of Terms,” but laissez-faire leadership would be a good choice to include. However, if your study is about leadership, then it may be beneficial to the understanding of your readers to define leadership based on how you are using it within your study. Things like success or achievement may need definition as well, if you are using them within your study, as the readers will need to know what measures or markers of success or achievement that you will focus on within your study.

For more information on “Definitions of Terms,” including what information to include within the definitions, check out our other blog: How to Write Your Definitions.

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Methodology

• Operationalization | A Guide with Examples, Pros & Cons

Operationalization | A Guide with Examples, Pros & Cons

Published on May 6, 2022 by Pritha Bhandari . Revised on June 22, 2023.

Operationalization means turning abstract concepts into measurable observations. Although some concepts, like height or age, are easily measured, others, like spirituality or anxiety, are not.

Through operationalization, you can systematically collect data on processes and phenomena that aren’t directly observable.

• self-rating scores on a social anxiety scale
• number of recent behavioral incidents of avoidance of crowded places
• intensity of physical anxiety symptoms in social situations

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Table of contents

Why operationalization matters, how to operationalize concepts, strengths of operationalization, limitations of operationalization, other interesting articles, frequently asked questions about operationalization.

In quantitative research , it’s important to precisely define the types of variables that you want to study.

Without transparent and specific operational definitions, researchers may measure irrelevant concepts or inconsistently apply methods. Operationalization reduces subjectivity, minimizes the potential for research bias , and increases the reliability  of your study.

Your choice of operational definition can sometimes affect your results. For example, an experimental intervention for social anxiety may reduce self-rating anxiety scores but not behavioral avoidance of crowded places. This means that your results are context-specific, and may not generalize to different real-life settings.

Generally, abstract concepts can be operationalized in many different ways. These differences mean that you may actually measure slightly different aspects of a concept, so it’s important to be specific about what you are measuring.

If you test a hypothesis using multiple operationalizations of a concept, you can check whether your results depend on the type of measure that you use. If your results don’t vary when you use different measures, then they are said to be “robust.”

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There are 3 main steps for operationalization:

• Identify the main concepts you are interested in studying.
• Choose a variable to represent each of the concepts.
• Select indicators for each of your variables.

1. Identify the main concepts you are interested in studying.

Based on your research interests and goals, define your topic and come up with an initial research question .

There are two main concepts in your research question:

• Social media behavior

2. Choose a variable to represent each of the concepts.

Your main concepts may each have many variables , or properties, that you can measure.

For instance, are you going to measure the  amount of sleep or the  quality of sleep? And are you going to measure  how often teenagers use social media,  which social media they use, or when they use it?

• Alternate hypothesis (H a or H 1 ): Lower quality of sleep is related to higher night-time social media use in teenagers.
• Null hypothesis (H 0 ): There is no relation between quality of sleep and night-time social media use in teenagers.

3. Select indicators for each of your variables.

To measure your variables, decide on indicators that can represent them numerically.

Sometimes these indicators will be obvious: for example, the amount of sleep is represented by the number of hours per night. But a variable like sleep quality is harder to measure.

You can come up with practical ideas for how to measure variables based on previously published studies. These may include established scales (e.g., Likert scales ) or questionnaires that you can distribute to your participants. If none are available that are appropriate for your sample, you can develop your own scales or questionnaires.

• To measure sleep quality, you give participants wristbands that track sleep phases.
• To measure night-time social media use, you create a questionnaire that asks participants to track how much time they spend using social media in bed.

After operationalizing your concepts, it’s important to report your study variables and indicators when writing up your methodology section . You can evaluate how your choice of operationalization may have affected your results or interpretations in the discussion section .

Operationalization makes it possible to consistently measure variables across different contexts.

Scientific research is based on observable and measurable findings. Operational definitions break down intangible concepts into recordable characteristics.

Objectivity

A standardized approach for collecting data leaves little room for subjective or biased personal interpretations of observations .

Reliability

A good operationalization can be used consistently by other researchers (high replicability ). If other people measure the same thing using your operational definition, they should all get the same results.

Operational definitions of concepts can sometimes be problematic.

Underdetermination

Many concepts vary across different time periods and social settings.

For example, poverty is a worldwide phenomenon, but the exact income-level that determines poverty can differ significantly across countries.

Reductiveness

Operational definitions can easily miss meaningful and subjective perceptions of concepts by trying to reduce complex concepts to numbers.

For example, asking consumers to rate their satisfaction with a service on a 5-point scale will tell you nothing about why they felt that way.

Lack of universality

Context-specific operationalizations help preserve real-life experiences, but make it hard to compare studies if the measures differ significantly.

For example, corruption can be operationalized in a wide range of ways (e.g., perceptions of corrupt business practices, or frequency of bribe requests from public officials), but the measures may not consistently reflect the same concept.

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

• Normal distribution
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Ecological validity

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

Operationalization means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioral avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalize the variables that you want to measure.

In scientific research, concepts are the abstract ideas or phenomena that are being studied (e.g., educational achievement). Variables are properties or characteristics of the concept (e.g., performance at school), while indicators are ways of measuring or quantifying variables (e.g., yearly grade reports).

The process of turning abstract concepts into measurable variables and indicators is called operationalization .

Reliability and validity are both about how well a method measures something:

• Reliability refers to the  consistency of a measure (whether the results can be reproduced under the same conditions).
• Validity   refers to the  accuracy of a measure (whether the results really do represent what they are supposed to measure).

If you are doing experimental research, you also have to consider the internal and external validity of your experiment.

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Chapter 1: Introduction to Research Methods

1.4 Understanding Key Research Concepts and Terms

In this textbook you will be exposed to many terms and concepts associated with research methods, particularly as they relate to the research planning decisions you must make along the way. Figure 1.3 will help you contextualize many of these terms and understand the research process. This general chart begins with two key concepts: ontology and epistemology, advances through other concepts, and concludes with three research methodological approaches: qualitative, quantitative and mixed methods.

Research does not end with making decisions about the type of methods you will use; we could argue that the work is just beginning at this point. Figure 1.3 does not represent an all-encompassing list of concepts and terms related to research methods. Keep in mind that each strategy has its own data collection and analysis approaches associated with the various methodological approaches you choose. Figure 1.3 is intentioned to provide a general overview of the research concept. You may want to keep this figure handy as you read through the various chapters.

Ontology & Epistemology

Thinking about what you know and how you know what you know involves questions of ontology and epistemology. Perhaps you have heard these concepts before in a philosophy class? These concepts are relevant to the work of sociologists as well. As sociologists (those who undertake socially-focused research), we want to understand some aspect of our social world. Usually, we are not starting with zero knowledge. In fact, we usually start with some understanding of three concepts: 1) what is; 2) what can be known about what is; and, 3) what the best mechanism happens to be for learning about what is (Saylor Academy, 2012). In the following sections, we will define these concepts and provide an example of the terms, ontology and epistemology.

Ontology is a Greek word that means the study, theory, or science of being. Ontology is concerned with the what is or the nature of reality (Saunders, Lewis, & Thornhill, 2009). It can involve some very large and difficult to answer questions, such as:

• What is the purpose of life?
• What, if anything, exists beyond our universe?
• What categories does it belong to?
• Is there such a thing as objective reality?
• What does the verb “to be” mean?

Ontology is comprised of two aspects: objectivism and subjectivism. Objectivism means that social entities exist externally to the social actors who are concerned with their existence. Subjectivism means that social phenomena are created from the perceptions and actions of the social actors who are concerned with their existence (Saunders, et al., 2009). The table below provides an example of a similar research project to be undertaken by two different students. While the projects being proposed by the students are similar, they each have different research questions. Read the scenario and then answer the questions that follow.

Subjectivist and objectivist approaches (adapted from Saunders et al., 2009)

Ana is an Emergency & Security Management Studies (ESMS) student at a local college. She is just beginning her capstone research project and she plans to do research at the City of Vancouver. Her research question is: What is the role of City of Vancouver managers in the Emergency Management Department (EMD) in enabling positive community relationships? She will be collecting data related to the roles and duties of managers in enabling positive community relationships.

Robert is also an ESMS student at the same college. He, too, will be undertaking his research at the City of Vancouver. His research question is: What is the effect of the City of Vancouver’s corporate culture in enabling EMD managers to develop a positive relationship with the local community? He will be collecting data related to perceptions of corporate culture and its effect on enabling positive community-emergency management department relationships.

Before the students begin collecting data, they learn that six months ago, the long-time emergency department manager and assistance manager both retired. They have been replaced by two senior staff managers who have Bachelor’s degrees in Emergency Services Management. These new managers are considered more up-to-date and knowledgeable on emergency services management, given their specialized academic training and practical on-the-job work experience in this department. The new managers have essentially the same job duties and operate under the same procedures as the managers they replaced. When Ana and Robert approach the managers to ask them to participate in their separate studies, the new managers state that they are just new on the job and probably cannot answer the research questions; they decline to participate. Ana and Robert are worried that they will need to start all over again with a new research project. They return to their supervisors to get their opinions on what they should do.

Before reading about their supervisors’ responses, answer the following questions:

• Is Ana’s research question indicative of an objectivist or a subjectivist approach?
• Is Robert’s research question indicative of an objectivist or a subjectivist approach?
• Given your answer in question 1, which managers could Ana interview (new, old, or both) for her research study? Why?
• Given your answer in question 2, which managers could Robert interview (new, old, or both) for his research study? Why?

Ana’s supervisor tells her that her research question is set up for an objectivist approach. Her supervisor tells her that in her study the social entity (the City) exists in reality external to the social actors (the managers), i.e., there is a formal management structure at the City that has largely remained unchanged since the old managers left and the new ones started. The procedures remain the same regardless of whoever occupies those positions. As such, Ana, using an objectivist approach, could state that the new managers have job descriptions which describe their duties and that they are a part of a formal structure with a hierarchy of people reporting to them and to whom they report. She could further state that this hierarchy, which is unique to this organization, also resembles hierarchies found in other similar organizations. As such, she can argue that the new managers will be able to speak about the role they play in enabling positive community relationships. Their answers would likely be no different than those of the old managers, because the management structure and the procedures remain the same. Therefore, she could go back to the new managers and ask them to participate in her research study.

Robert’s supervisor tells him that his research is set up for a subjectivist approach. In his study, the social phenomena (the effect of corporate culture on the relationship with the community) is created from the perceptions and consequent actions of the social actors (the managers); i.e., the corporate culture at the City continually influences the process of social interaction, and these interactions influence perceptions of the relationship with the community. The relationship is in a constant state of revision. As such, Robert, using a subjectivist approach, could state that the new managers may have had few interactions with the community members to date and therefore may not be fully cognizant of how the corporate culture affects the department’s relationship with the community. While it would be important to get the new managers’ perceptions, he would also need to speak with the previous managers to get their perceptions from the time they were employed in their positions. This is because the community-department relationship is in a state of constant revision, which is influenced by the various managers’ perceptions of the corporate culture and its effect on their ability to form positive community relationships. Therefore, he could go back to the current managers and ask them to participate in his study, and also ask that the department please contact the previous managers to see if they would be willing to participate in his study.

As you can see the research question of each study guides the decision as to whether the researcher should take a subjective or an objective ontological approach. This decision, in turn, guides their approach to the research study, including whom they should interview.

Epistemology

Epistemology has to do with knowledge. Rather than dealing with questions about what is, epistemology deals with questions of how we know what is.  In sociology, there are many ways to uncover knowledge. We might interview people to understand public opinion about a topic, or perhaps observe them in their natural environment. We could avoid face-to-face interaction altogether by mailing people surveys to complete on their own or by reading people’s opinions in newspaper editorials. Each method of data collection comes with its own set of epistemological assumptions about how to find things out (Saylor Academy, 2012). There are two main subsections of epistemology: positivist and interpretivist philosophies. We will examine these philosophies or paradigms in the following sections.

Research Methods for the Social Sciences: An Introduction Copyright © 2020 by Valerie Sheppard is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Academic Phrasebank

Defining terms.

• GENERAL LANGUAGE FUNCTIONS
• Being cautious
• Being critical
• Classifying and listing
• Compare and contrast
• Describing trends
• Describing quantities
• Explaining causality
• Giving examples
• Signalling transition
• Writing about the past

In academic work students are often expected to give definitions of key words and phrases in order to demonstrate to their tutors that they understand these terms clearly. More generally, however, academic writers define terms so that their readers understand exactly what is meant when certain key terms are used. When important words are not clearly understood misinterpretation may result. In fact, many disagreements (academic, legal, diplomatic, personal) arise as a result of different interpretations of the same term. In academic writing, teachers and their students often have to explore these differing interpretations before moving on to study a topic.

Introductory phrases

The term ‘X’ was first used by … The term ‘X’ can be traced back to … Previous studies mostly defined X as … The term ‘X’ was introduced by Smith in her … Historically, the term ‘X’ has been used to describe … It is necessary here to clarify exactly what is meant by … This shows a need to be explicit about exactly what is meant by the word ‘X’.

Simple three-part definitions

General meanings or application of meanings

X can broadly be defined as … X can be loosely described as … X can be defined as … It encompasses … In the literature, the term tends to be used to refer to … In broad terms, X can be defined as any stimulus that is … Whereas X refers to the operations of …, Y refers to the … The broad use of the term ‘X’ is sometimes equated with … The term ‘disease’ refers to a biological event characterised by … Defined as …, X is now considered a worldwide problem and is associated with …

Indicating varying definitions

The definition of X has evolved. There are multiple definitions of X. Several definitions of X have been proposed. In the field of X, various definitions of X are found. The term ‘X’ embodies a multitude of concepts which … This term has two overlapping, even slightly confusing meanings. Widely varying definitions of X have emerged (Smith and Jones, 1999). Despite its common usage, X is used in different disciplines to mean different things. Since the definition of X varies among researchers, it is important to clarify how the term is …

Indicating difficulties in defining a term

X is a contested term. X is a rather nebulous term … X is challenging to define because … A precise definition of X has proved elusive. A generally accepted definition of X is lacking. Unfortunately, X remains a poorly defined term. There is no agreed definition on what constitutes … There is little consensus about what X actually means. There is a degree of uncertainty around the terminology in … These terms are often used interchangeably and without precision. Numerous terms are used to describe X, the most common of which are …. The definition of X varies in the literature and there is terminological confusion. Smith (2001) identified four abilities that might be subsumed under the term ‘X’: a) … ‘X’ is a term frequently used in the literature, but to date there is no consensus about … X is a commonly-used notion in psychology and yet it is a concept difficult to define precisely. Although differences of opinion still exist, there appears to be some agreement that X refers to …

Specifying terms that are used in an essay or thesis

The term ‘X’ is used here to refer to … In the present study, X is defined as … The term ‘X’ will be used solely when referring to … In this essay, the term ‘X’ will be used in its broadest sense to refer to all … In this paper, the term that will be used to describe this phenomenon is ‘X’. In this dissertation, the terms ‘X’ and ‘Y’ are used interchangeably to mean … Throughout this thesis, the term ‘X’ is used to refer to informal systems as well as … While a variety of definitions of the term ‘X’ have been suggested, this paper will use the definition first suggested by Smith (1968) who saw it as …

Referring to people’s definitions: author prominent

For Smith (2001), X means … Smith (2001) uses the term ‘X’ to refer to … Smith (1954) was apparently the first to use the term … In 1987, psychologist John Smith popularized the term ‘X’ to describe … According to a definition provided by Smith (2001:23), X is ‘the maximally … This definition is close to those of Smith (2012) and Jones (2013) who define X as … Smith, has shown that, as late as 1920, Jones was using the term ‘X’ to refer to particular … One of the first people to define nursing was Florence Nightingale (1860), who wrote: ‘… …’ Chomsky writes that a grammar is a ‘device of some sort for producing the ….’ (1957, p.11). Aristotle defines the imagination as ‘the movement which results upon an actual sensation.’ Smith  et al . (2002) have provided a new definition of health: ‘health is a state of being with …

Referring to people’s definitions: author non-prominent

X is defined by Smith (2003: 119) as ‘… …’ The term ‘X’ is used by Smith (2001) to refer to … X is, for Smith (2012), the situation which occurs when … A further definition of X is given by Smith (1982) who describes … The term ‘X’ is used by Aristotle in four overlapping senses. First, it is the underlying … X is the degree to which an assessment process or device measures … (Smith  et al ., 1986).

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Lesson 21: Definition of Terms

A word or phrase used to describe a thing or to express concept, especially In a particular kind of language or branch of study.

Guidelines in defining terms:

1.     Definition of terms works like a glossary but have a different twist. It is placed on the beginning of the research paper to tell the meaning of the terms used in the said paper.

2.     Only terms, words, or phrases which have special or unique meanings in the study are defined.

3.     There are two types of definition of terms. Conceptual and Operational Terms.

Theoretical Definition are based be taken from encyclopedias, books, magazines and newspaper article, dictionaries, and other publications but the researcher must acknowledge his/her sources.

Conceptual Definition are based on how the researcher may develop his own definition from the characteristics of the term define.

4.     The term should be arranged alphabetically .

5.     When the definition are taken from encyclopedias, books, magazine and newspaper articles, dictionaries and other publications, the researcher must acknowledge his sources .

Definition of terms

Theoretical Definition

Knowledge - the fact or condition of knowing something with familiarity gained through experience or association.

Conceptual Definition

Knowledge - it is a condition of being aware to a certain problem-cyberbullying.

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How to Write the Definition of Terms in Chapter 1 of a Thesis

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Meta: Journal des traducteurs, 2000

The study is intended to describe the methods of defining terms found in the theses of the English Foreign Language (EFL) students of IAIN Palangka Raya. The method to be used is a mixed method, qualitative and quantitative. Quantitative approach was used to identify, describe the frequencies, and classify the methods of defining terms. In interpreting and explaining the types of method to be used, the writer used qualitative approach. In qualitative approach, data were described in the form of words and explanation. The findings show that there were two methods of defining terms, dictionary approach and athoritative reference.

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Terminology is the field of lexicology (or the study of lexicon) that deals with specialized vocabularies and sets of terms related to particular fields (aviation terminology, medical terminology, stylistics, agriculture, etc.). Terminology as a new academic field is located at the boundary among linguistics, logic, theory of existence, information science and specialized areas of science and technology, and in the interdisciplinary area.

During the past several decades, the theory of terminology has been a subject of debates in various circles. The views on terminology as a scientific discipline vary considerably. Currently, there are a number of treatments of this field and a number of debatable questions involved. Is terminology a science, or just a practice? does terminology have a status of separate scholarly discipline with its own theory or does it owe its theoretical assumptions to more consolidated disciplines?

Chapter 1.1 of my book A Model for an English-Polish Systematic Dictionary of Chemical Terminology

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This glossary is intended to assist you in understanding commonly used terms and concepts when reading, interpreting, and evaluating scholarly research. Also included are common words and phrases defined within the context of how they apply to research in the social and behavioral sciences.

• Acculturation -- refers to the process of adapting to another culture, particularly in reference to blending in with the majority population [e.g., an immigrant adopting American customs]. However, acculturation also implies that both cultures add something to one another, but still remain distinct groups unto themselves.
• Accuracy -- a term used in survey research to refer to the match between the target population and the sample.
• Affective Measures -- procedures or devices used to obtain quantified descriptions of an individual's feelings, emotional states, or dispositions.
• Aggregate -- a total created from smaller units. For instance, the population of a county is an aggregate of the populations of the cities, rural areas, etc. that comprise the county. As a verb, it refers to total data from smaller units into a large unit.
• Anonymity -- a research condition in which no one, including the researcher, knows the identities of research participants.
• Baseline -- a control measurement carried out before an experimental treatment.
• Behaviorism -- school of psychological thought concerned with the observable, tangible, objective facts of behavior, rather than with subjective phenomena such as thoughts, emotions, or impulses. Contemporary behaviorism also emphasizes the study of mental states such as feelings and fantasies to the extent that they can be directly observed and measured.
• Beliefs -- ideas, doctrines, tenets, etc. that are accepted as true on grounds which are not immediately susceptible to rigorous proof.
• Benchmarking -- systematically measuring and comparing the operations and outcomes of organizations, systems, processes, etc., against agreed upon "best-in-class" frames of reference.
• Bias -- a loss of balance and accuracy in the use of research methods. It can appear in research via the sampling frame, random sampling, or non-response. It can also occur at other stages in research, such as while interviewing, in the design of questions, or in the way data are analyzed and presented. Bias means that the research findings will not be representative of, or generalizable to, a wider population.
• Case Study -- the collection and presentation of detailed information about a particular participant or small group, frequently including data derived from the subjects themselves.
• Causal Hypothesis -- a statement hypothesizing that the independent variable affects the dependent variable in some way.
• Causal Relationship -- the relationship established that shows that an independent variable, and nothing else, causes a change in a dependent variable. It also establishes how much of a change is shown in the dependent variable.
• Causality -- the relation between cause and effect.
• Central Tendency -- any way of describing or characterizing typical, average, or common values in some distribution.
• Chi-square Analysis -- a common non-parametric statistical test which compares an expected proportion or ratio to an actual proportion or ratio.
• Claim -- a statement, similar to a hypothesis, which is made in response to the research question and that is affirmed with evidence based on research.
• Classification -- ordering of related phenomena into categories, groups, or systems according to characteristics or attributes.
• Cluster Analysis -- a method of statistical analysis where data that share a common trait are grouped together. The data is collected in a way that allows the data collector to group data according to certain characteristics.
• Cohort Analysis -- group by group analytic treatment of individuals having a statistical factor in common to each group. Group members share a particular characteristic [e.g., born in a given year] or a common experience [e.g., entering a college at a given time].
• Confidentiality -- a research condition in which no one except the researcher(s) knows the identities of the participants in a study. It refers to the treatment of information that a participant has disclosed to the researcher in a relationship of trust and with the expectation that it will not be revealed to others in ways that violate the original consent agreement, unless permission is granted by the participant.
• Confirmability Objectivity -- the findings of the study could be confirmed by another person conducting the same study.
• Construct -- refers to any of the following: something that exists theoretically but is not directly observable; a concept developed [constructed] for describing relations among phenomena or for other research purposes; or, a theoretical definition in which concepts are defined in terms of other concepts. For example, intelligence cannot be directly observed or measured; it is a construct.
• Construct Validity -- seeks an agreement between a theoretical concept and a specific measuring device, such as observation.
• Constructivism -- the idea that reality is socially constructed. It is the view that reality cannot be understood outside of the way humans interact and that the idea that knowledge is constructed, not discovered. Constructivists believe that learning is more active and self-directed than either behaviorism or cognitive theory would postulate.
• Content Analysis -- the systematic, objective, and quantitative description of the manifest or latent content of print or nonprint communications.
• Context Sensitivity -- awareness by a qualitative researcher of factors such as values and beliefs that influence cultural behaviors.
• Control Group -- the group in an experimental design that receives either no treatment or a different treatment from the experimental group. This group can thus be compared to the experimental group.
• Controlled Experiment -- an experimental design with two or more randomly selected groups [an experimental group and control group] in which the researcher controls or introduces the independent variable and measures the dependent variable at least two times [pre- and post-test measurements].
• Correlation -- a common statistical analysis, usually abbreviated as r, that measures the degree of relationship between pairs of interval variables in a sample. The range of correlation is from -1.00 to zero to +1.00. Also, a non-cause and effect relationship between two variables.
• Covariate -- a product of the correlation of two related variables times their standard deviations. Used in true experiments to measure the difference of treatment between them.
• Credibility -- a researcher's ability to demonstrate that the object of a study is accurately identified and described based on the way in which the study was conducted.
• Critical Theory -- an evaluative approach to social science research, associated with Germany's neo-Marxist “Frankfurt School,” that aims to criticize as well as analyze society, opposing the political orthodoxy of modern communism. Its goal is to promote human emancipatory forces and to expose ideas and systems that impede them.
• Data -- factual information [as measurements or statistics] used as a basis for reasoning, discussion, or calculation.
• Data Mining -- the process of analyzing data from different perspectives and summarizing it into useful information, often to discover patterns and/or systematic relationships among variables.
• Data Quality -- this is the degree to which the collected data [results of measurement or observation] meet the standards of quality to be considered valid [trustworthy] and  reliable [dependable].
• Deductive -- a form of reasoning in which conclusions are formulated about particulars from general or universal premises.
• Dependability -- being able to account for changes in the design of the study and the changing conditions surrounding what was studied.
• Dependent Variable -- a variable that varies due, at least in part, to the impact of the independent variable. In other words, its value “depends” on the value of the independent variable. For example, in the variables “gender” and “academic major,” academic major is the dependent variable, meaning that your major cannot determine whether you are male or female, but your gender might indirectly lead you to favor one major over another.
• Deviation -- the distance between the mean and a particular data point in a given distribution.
• Discourse Community -- a community of scholars and researchers in a given field who respond to and communicate to each other through published articles in the community's journals and presentations at conventions. All members of the discourse community adhere to certain conventions for the presentation of their theories and research.
• Discrete Variable -- a variable that is measured solely in whole units, such as, gender and number of siblings.
• Distribution -- the range of values of a particular variable.
• Effect Size -- the amount of change in a dependent variable that can be attributed to manipulations of the independent variable. A large effect size exists when the value of the dependent variable is strongly influenced by the independent variable. It is the mean difference on a variable between experimental and control groups divided by the standard deviation on that variable of the pooled groups or of the control group alone.
• Emancipatory Research -- research is conducted on and with people from marginalized groups or communities. It is led by a researcher or research team who is either an indigenous or external insider; is interpreted within intellectual frameworks of that group; and, is conducted largely for the purpose of empowering members of that community and improving services for them. It also engages members of the community as co-constructors or validators of knowledge.
• Empirical Research -- the process of developing systematized knowledge gained from observations that are formulated to support insights and generalizations about the phenomena being researched.
• Epistemology -- concerns knowledge construction; asks what constitutes knowledge and how knowledge is validated.
• Ethnography -- method to study groups and/or cultures over a period of time. The goal of this type of research is to comprehend the particular group/culture through immersion into the culture or group. Research is completed through various methods but, since the researcher is immersed within the group for an extended period of time, more detailed information is usually collected during the research.
• Expectancy Effect -- any unconscious or conscious cues that convey to the participant in a study how the researcher wants them to respond. Expecting someone to behave in a particular way has been shown to promote the expected behavior. Expectancy effects can be minimized by using standardized interactions with subjects, automated data-gathering methods, and double blind protocols.
• External Validity -- the extent to which the results of a study are generalizable or transferable.
• Factor Analysis -- a statistical test that explores relationships among data. The test explores which variables in a data set are most related to each other. In a carefully constructed survey, for example, factor analysis can yield information on patterns of responses, not simply data on a single response. Larger tendencies may then be interpreted, indicating behavior trends rather than simply responses to specific questions.
• Field Studies -- academic or other investigative studies undertaken in a natural setting, rather than in laboratories, classrooms, or other structured environments.
• Focus Groups -- small, roundtable discussion groups charged with examining specific topics or problems, including possible options or solutions. Focus groups usually consist of 4-12 participants, guided by moderators to keep the discussion flowing and to collect and report the results.
• Framework -- the structure and support that may be used as both the launching point and the on-going guidelines for investigating a research problem.
• Generalizability -- the extent to which research findings and conclusions conducted on a specific study to groups or situations can be applied to the population at large.
• Grey Literature -- research produced by organizations outside of commercial and academic publishing that publish materials, such as, working papers, research reports, and briefing papers.
• Grounded Theory -- practice of developing other theories that emerge from observing a group. Theories are grounded in the group's observable experiences, but researchers add their own insight into why those experiences exist.
• Group Behavior -- behaviors of a group as a whole, as well as the behavior of an individual as influenced by his or her membership in a group.
• Hypothesis -- a tentative explanation based on theory to predict a causal relationship between variables.
• Independent Variable -- the conditions of an experiment that are systematically manipulated by the researcher. A variable that is not impacted by the dependent variable, and that itself impacts the dependent variable. In the earlier example of "gender" and "academic major," (see Dependent Variable) gender is the independent variable.
• Individualism -- a theory or policy having primary regard for the liberty, rights, or independent actions of individuals.
• Inductive -- a form of reasoning in which a generalized conclusion is formulated from particular instances.
• Inductive Analysis -- a form of analysis based on inductive reasoning; a researcher using inductive analysis starts with answers, but formulates questions throughout the research process.
• Insiderness -- a concept in qualitative research that refers to the degree to which a researcher has access to and an understanding of persons, places, or things within a group or community based on being a member of that group or community.
• Internal Consistency -- the extent to which all questions or items assess the same characteristic, skill, or quality.
• Internal Validity -- the rigor with which the study was conducted [e.g., the study's design, the care taken to conduct measurements, and decisions concerning what was and was not measured]. It is also the extent to which the designers of a study have taken into account alternative explanations for any causal relationships they explore. In studies that do not explore causal relationships, only the first of these definitions should be considered when assessing internal validity.
• Life History -- a record of an event/events in a respondent's life told [written down, but increasingly audio or video recorded] by the respondent from his/her own perspective in his/her own words. A life history is different from a "research story" in that it covers a longer time span, perhaps a complete life, or a significant period in a life.
• Margin of Error -- the permittable or acceptable deviation from the target or a specific value. The allowance for slight error or miscalculation or changing circumstances in a study.
• Measurement -- process of obtaining a numerical description of the extent to which persons, organizations, or things possess specified characteristics.
• Meta-Analysis -- an analysis combining the results of several studies that address a set of related hypotheses.
• Methodology -- a theory or analysis of how research does and should proceed.
• Methods -- systematic approaches to the conduct of an operation or process. It includes steps of procedure, application of techniques, systems of reasoning or analysis, and the modes of inquiry employed by a discipline.
• Mixed-Methods -- a research approach that uses two or more methods from both the quantitative and qualitative research categories. It is also referred to as blended methods, combined methods, or methodological triangulation.
• Modeling -- the creation of a physical or computer analogy to understand a particular phenomenon. Modeling helps in estimating the relative magnitude of various factors involved in a phenomenon. A successful model can be shown to account for unexpected behavior that has been observed, to predict certain behaviors, which can then be tested experimentally, and to demonstrate that a given theory cannot account for certain phenomenon.
• Models -- representations of objects, principles, processes, or ideas often used for imitation or emulation.
• Naturalistic Observation -- observation of behaviors and events in natural settings without experimental manipulation or other forms of interference.
• Norm -- the norm in statistics is the average or usual performance. For example, students usually complete their high school graduation requirements when they are 18 years old. Even though some students graduate when they are younger or older, the norm is that any given student will graduate when he or she is 18 years old.
• Null Hypothesis -- the proposition, to be tested statistically, that the experimental intervention has "no effect," meaning that the treatment and control groups will not differ as a result of the intervention. Investigators usually hope that the data will demonstrate some effect from the intervention, thus allowing the investigator to reject the null hypothesis.
• Ontology -- a discipline of philosophy that explores the science of what is, the kinds and structures of objects, properties, events, processes, and relations in every area of reality.
• Panel Study -- a longitudinal study in which a group of individuals is interviewed at intervals over a period of time.
• Participant -- individuals whose physiological and/or behavioral characteristics and responses are the object of study in a research project.
• Peer-Review -- the process in which the author of a book, article, or other type of publication submits his or her work to experts in the field for critical evaluation, usually prior to publication. This is standard procedure in publishing scholarly research.
• Phenomenology -- a qualitative research approach concerned with understanding certain group behaviors from that group's point of view.
• Philosophy -- critical examination of the grounds for fundamental beliefs and analysis of the basic concepts, doctrines, or practices that express such beliefs.
• Phonology -- the study of the ways in which speech sounds form systems and patterns in language.
• Policy -- governing principles that serve as guidelines or rules for decision making and action in a given area.
• Policy Analysis -- systematic study of the nature, rationale, cost, impact, effectiveness, implications, etc., of existing or alternative policies, using the theories and methodologies of relevant social science disciplines.
• Population -- the target group under investigation. The population is the entire set under consideration. Samples are drawn from populations.
• Position Papers -- statements of official or organizational viewpoints, often recommending a particular course of action or response to a situation.
• Positivism -- a doctrine in the philosophy of science, positivism argues that science can only deal with observable entities known directly to experience. The positivist aims to construct general laws, or theories, which express relationships between phenomena. Observation and experiment is used to show whether the phenomena fit the theory.
• Predictive Measurement -- use of tests, inventories, or other measures to determine or estimate future events, conditions, outcomes, or trends.
• Principal Investigator -- the scientist or scholar with primary responsibility for the design and conduct of a research project.
• Probability -- the chance that a phenomenon will occur randomly. As a statistical measure, it is shown as p [the "p" factor].
• Questionnaire -- structured sets of questions on specified subjects that are used to gather information, attitudes, or opinions.
• Random Sampling -- a process used in research to draw a sample of a population strictly by chance, yielding no discernible pattern beyond chance. Random sampling can be accomplished by first numbering the population, then selecting the sample according to a table of random numbers or using a random-number computer generator. The sample is said to be random because there is no regular or discernible pattern or order. Random sample selection is used under the assumption that sufficiently large samples assigned randomly will exhibit a distribution comparable to that of the population from which the sample is drawn. The random assignment of participants increases the probability that differences observed between participant groups are the result of the experimental intervention.
• Reliability -- the degree to which a measure yields consistent results. If the measuring instrument [e.g., survey] is reliable, then administering it to similar groups would yield similar results. Reliability is a prerequisite for validity. An unreliable indicator cannot produce trustworthy results.
• Representative Sample -- sample in which the participants closely match the characteristics of the population, and thus, all segments of the population are represented in the sample. A representative sample allows results to be generalized from the sample to the population.
• Rigor -- degree to which research methods are scrupulously and meticulously carried out in order to recognize important influences occurring in an experimental study.
• Sample -- the population researched in a particular study. Usually, attempts are made to select a "sample population" that is considered representative of groups of people to whom results will be generalized or transferred. In studies that use inferential statistics to analyze results or which are designed to be generalizable, sample size is critical, generally the larger the number in the sample, the higher the likelihood of a representative distribution of the population.
• Sampling Error -- the degree to which the results from the sample deviate from those that would be obtained from the entire population, because of random error in the selection of respondent and the corresponding reduction in reliability.
• Saturation -- a situation in which data analysis begins to reveal repetition and redundancy and when new data tend to confirm existing findings rather than expand upon them.
• Semantics -- the relationship between symbols and meaning in a linguistic system. Also, the cuing system that connects what is written in the text to what is stored in the reader's prior knowledge.
• Social Theories -- theories about the structure, organization, and functioning of human societies.
• Sociolinguistics -- the study of language in society and, more specifically, the study of language varieties, their functions, and their speakers.
• Standard Deviation -- a measure of variation that indicates the typical distance between the scores of a distribution and the mean; it is determined by taking the square root of the average of the squared deviations in a given distribution. It can be used to indicate the proportion of data within certain ranges of scale values when the distribution conforms closely to the normal curve.
• Statistical Analysis -- application of statistical processes and theory to the compilation, presentation, discussion, and interpretation of numerical data.
• Statistical Bias -- characteristics of an experimental or sampling design, or the mathematical treatment of data, that systematically affects the results of a study so as to produce incorrect, unjustified, or inappropriate inferences or conclusions.
• Statistical Significance -- the probability that the difference between the outcomes of the control and experimental group are great enough that it is unlikely due solely to chance. The probability that the null hypothesis can be rejected at a predetermined significance level [0.05 or 0.01].
• Statistical Tests -- researchers use statistical tests to make quantitative decisions about whether a study's data indicate a significant effect from the intervention and allow the researcher to reject the null hypothesis. That is, statistical tests show whether the differences between the outcomes of the control and experimental groups are great enough to be statistically significant. If differences are found to be statistically significant, it means that the probability [likelihood] that these differences occurred solely due to chance is relatively low. Most researchers agree that a significance value of .05 or less [i.e., there is a 95% probability that the differences are real] sufficiently determines significance.
• Subcultures -- ethnic, regional, economic, or social groups exhibiting characteristic patterns of behavior sufficient to distinguish them from the larger society to which they belong.
• Testing -- the act of gathering and processing information about individuals' ability, skill, understanding, or knowledge under controlled conditions.
• Theory -- a general explanation about a specific behavior or set of events that is based on known principles and serves to organize related events in a meaningful way. A theory is not as specific as a hypothesis.
• Treatment -- the stimulus given to a dependent variable.
• Trend Samples -- method of sampling different groups of people at different points in time from the same population.
• Triangulation -- a multi-method or pluralistic approach, using different methods in order to focus on the research topic from different viewpoints and to produce a multi-faceted set of data. Also used to check the validity of findings from any one method.
• Unit of Analysis -- the basic observable entity or phenomenon being analyzed by a study and for which data are collected in the form of variables.
• Validity -- the degree to which a study accurately reflects or assesses the specific concept that the researcher is attempting to measure. A method can be reliable, consistently measuring the same thing, but not valid.
• Variable -- any characteristic or trait that can vary from one person to another [race, gender, academic major] or for one person over time [age, political beliefs].
• Weighted Scores -- scores in which the components are modified by different multipliers to reflect their relative importance.
• White Paper -- an authoritative report that often states the position or philosophy about a social, political, or other subject, or a general explanation of an architecture, framework, or product technology written by a group of researchers. A white paper seeks to contain unbiased information and analysis regarding a business or policy problem that the researchers may be facing.

Elliot, Mark, Fairweather, Ian, Olsen, Wendy Kay, and Pampaka, Maria. A Dictionary of Social Research Methods. Oxford, UK: Oxford University Press, 2016; Free Social Science Dictionary. Socialsciencedictionary.com [2008]. Glossary. Institutional Review Board. Colorado College; Glossary of Key Terms. Writing@CSU. Colorado State University; Glossary A-Z. Education.com; Glossary of Research Terms. Research Mindedness Virtual Learning Resource. Centre for Human Servive Technology. University of Southampton; Miller, Robert L. and Brewer, John D. The A-Z of Social Research: A Dictionary of Key Social Science Research Concepts London: SAGE, 2003; Jupp, Victor. The SAGE Dictionary of Social and Cultural Research Methods . London: Sage, 2006.

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Study designs: Part 1 – An overview and classification

Priya ranganathan.

Department of Anaesthesiology, Tata Memorial Centre, Mumbai, Maharashtra, India

Rakesh Aggarwal

1 Department of Gastroenterology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India

There are several types of research study designs, each with its inherent strengths and flaws. The study design used to answer a particular research question depends on the nature of the question and the availability of resources. In this article, which is the first part of a series on “study designs,” we provide an overview of research study designs and their classification. The subsequent articles will focus on individual designs.

INTRODUCTION

Research study design is a framework, or the set of methods and procedures used to collect and analyze data on variables specified in a particular research problem.

Research study designs are of many types, each with its advantages and limitations. The type of study design used to answer a particular research question is determined by the nature of question, the goal of research, and the availability of resources. Since the design of a study can affect the validity of its results, it is important to understand the different types of study designs and their strengths and limitations.

There are some terms that are used frequently while classifying study designs which are described in the following sections.

A variable represents a measurable attribute that varies across study units, for example, individual participants in a study, or at times even when measured in an individual person over time. Some examples of variables include age, sex, weight, height, health status, alive/dead, diseased/healthy, annual income, smoking yes/no, and treated/untreated.

Exposure (or intervention) and outcome variables

A large proportion of research studies assess the relationship between two variables. Here, the question is whether one variable is associated with or responsible for change in the value of the other variable. Exposure (or intervention) refers to the risk factor whose effect is being studied. It is also referred to as the independent or the predictor variable. The outcome (or predicted or dependent) variable develops as a consequence of the exposure (or intervention). Typically, the term “exposure” is used when the “causative” variable is naturally determined (as in observational studies – examples include age, sex, smoking, and educational status), and the term “intervention” is preferred where the researcher assigns some or all participants to receive a particular treatment for the purpose of the study (experimental studies – e.g., administration of a drug). If a drug had been started in some individuals but not in the others, before the study started, this counts as exposure, and not as intervention – since the drug was not started specifically for the study.

Observational versus interventional (or experimental) studies

Observational studies are those where the researcher is documenting a naturally occurring relationship between the exposure and the outcome that he/she is studying. The researcher does not do any active intervention in any individual, and the exposure has already been decided naturally or by some other factor. For example, looking at the incidence of lung cancer in smokers versus nonsmokers, or comparing the antenatal dietary habits of mothers with normal and low-birth babies. In these studies, the investigator did not play any role in determining the smoking or dietary habit in individuals.

For an exposure to determine the outcome, it must precede the latter. Any variable that occurs simultaneously with or following the outcome cannot be causative, and hence is not considered as an “exposure.”

Observational studies can be either descriptive (nonanalytical) or analytical (inferential) – this is discussed later in this article.

Interventional studies are experiments where the researcher actively performs an intervention in some or all members of a group of participants. This intervention could take many forms – for example, administration of a drug or vaccine, performance of a diagnostic or therapeutic procedure, and introduction of an educational tool. For example, a study could randomly assign persons to receive aspirin or placebo for a specific duration and assess the effect on the risk of developing cerebrovascular events.

Descriptive versus analytical studies

Descriptive (or nonanalytical) studies, as the name suggests, merely try to describe the data on one or more characteristics of a group of individuals. These do not try to answer questions or establish relationships between variables. Examples of descriptive studies include case reports, case series, and cross-sectional surveys (please note that cross-sectional surveys may be analytical studies as well – this will be discussed in the next article in this series). Examples of descriptive studies include a survey of dietary habits among pregnant women or a case series of patients with an unusual reaction to a drug.

Analytical studies attempt to test a hypothesis and establish causal relationships between variables. In these studies, the researcher assesses the effect of an exposure (or intervention) on an outcome. As described earlier, analytical studies can be observational (if the exposure is naturally determined) or interventional (if the researcher actively administers the intervention).

Directionality of study designs

Based on the direction of inquiry, study designs may be classified as forward-direction or backward-direction. In forward-direction studies, the researcher starts with determining the exposure to a risk factor and then assesses whether the outcome occurs at a future time point. This design is known as a cohort study. For example, a researcher can follow a group of smokers and a group of nonsmokers to determine the incidence of lung cancer in each. In backward-direction studies, the researcher begins by determining whether the outcome is present (cases vs. noncases [also called controls]) and then traces the presence of prior exposure to a risk factor. These are known as case–control studies. For example, a researcher identifies a group of normal-weight babies and a group of low-birth weight babies and then asks the mothers about their dietary habits during the index pregnancy.

Prospective versus retrospective study designs

The terms “prospective” and “retrospective” refer to the timing of the research in relation to the development of the outcome. In retrospective studies, the outcome of interest has already occurred (or not occurred – e.g., in controls) in each individual by the time s/he is enrolled, and the data are collected either from records or by asking participants to recall exposures. There is no follow-up of participants. By contrast, in prospective studies, the outcome (and sometimes even the exposure or intervention) has not occurred when the study starts and participants are followed up over a period of time to determine the occurrence of outcomes. Typically, most cohort studies are prospective studies (though there may be retrospective cohorts), whereas case–control studies are retrospective studies. An interventional study has to be, by definition, a prospective study since the investigator determines the exposure for each study participant and then follows them to observe outcomes.

The terms “prospective” versus “retrospective” studies can be confusing. Let us think of an investigator who starts a case–control study. To him/her, the process of enrolling cases and controls over a period of several months appears prospective. Hence, the use of these terms is best avoided. Or, at the very least, one must be clear that the terms relate to work flow for each individual study participant, and not to the study as a whole.

Classification of study designs

Figure 1 depicts a simple classification of research study designs. The Centre for Evidence-based Medicine has put forward a useful three-point algorithm which can help determine the design of a research study from its methods section:[ 1 ]

Classification of research study designs

• Does the study describe the characteristics of a sample or does it attempt to analyze (or draw inferences about) the relationship between two variables? – If no, then it is a descriptive study, and if yes, it is an analytical (inferential) study
• If analytical, did the investigator determine the exposure? – If no, it is an observational study, and if yes, it is an experimental study
• If observational, when was the outcome determined? – at the start of the study (case–control study), at the end of a period of follow-up (cohort study), or simultaneously (cross sectional).

In the next few pieces in the series, we will discuss various study designs in greater detail.

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Any untoward occurrence in a research participant. The occurrence need not have a clear causal relationship with the individual’s participation in the research; an AE can be any unfavorable and unintended sign, symptom, event, or occurrence affecting a participant’s physical, mental, social, financial, legal, or psychological well-being. An unanticipated AE should be reported to the committee as soon as possible after it is identified.

Agreement by an individual not competent to give legally valid informed consent (e.g., a child or cognitively impaired person) to participate in research. An assent is typically paired with permission from a parent or guardian, and together they comprise the informed consent to participate.

An officer of an institution with the authority to speak for and legally commit the institution to adherence to the requirements of the federal regulations regarding the involvement of human subjects in biomedical and behavioral research.

A statement of basic ethical principles governing research involving human subjects issued by the National Commission for the Protection of Human Subjects in 1979. View a summary of the Belmont Report . The Belmont Report principles permeate human subjects research to this day.

An ethical principle discussed in the Belmont Report that entails an obligation to protect persons from harm. The principle of beneficence can be expressed in two general rules: 1) do not harm; and 2) protect from harm by maximizing possible benefits and minimizing possible risks of harm.

A valued or desired outcome associated with a research project. Anticipated benefits may express the probability that subjects and society may benefit from the research procedures. Research may benefit the individual or society as a whole. If research will not benefit individuals, it is required to provide a reasonable likelihood of resulting in benefits to society. UNLV’s human research application requests information about the direct benefits accruing to the research participants and to society. Compensation and incentives given to participants are not considered benefit.

This is a certificate issued by the National Institutes of Health that protects identifiable research information of a sensitive nature from forced disclosure. It is typically requested when the researcher believes his/her research objectives could not be met without this form of protection. 

Persons who have not attained the legal age for consent to treatment or procedures involved in the research, as determined under the applicable law of the jurisdiction in which the research will be conducted [45 CFR 46 46.401(a)]. In Nevada, individuals younger than 18 years of age are considered children for most research situations, and informed consent then consists of the child’s assent and the parent’s permission.(See “Assent.”)

The act of forcing or compelling one to take action against one’s will. Coercion can be overt or perceived, and it can occur when the researcher is in a position of authority or power over the subject (for example, teachers over students or physicians over patients). It can also occur when incentives become so great that the participant will only participate to attain the incentive.

Having either a psychiatric disorder (e.g., psychosis, neurosis, personality or behavior disorders, or dementia) or a developmental disorder (e.g., mental retardation) that affects cognitive or emotional functions to the extent that capacity for judgment and reasoning is significantly diminished. Others, including persons under the influence of or dependent on drugs or alcohol, those suffering from degenerative diseases affecting the brain, terminally ill patients, and persons with severely disabling physical handicaps, may also be compromised in their ability to make decisions in their best interests.

Human subjects research projects conducted by more than one institution. Each institution is responsible for safeguarding the rights and welfare of human subjects. Arrangements for joint review, relying upon one qualified IRB, or similar arrangements are acceptable. (Please contact the ORI-HS staff if this situation occurs; they can assist with the arrangements.)

Payment for participation in research. Compensation should be appropriate for the amount of effort involved, and not excessive and thereby coercive. Compensation is NOT considered a benefit.

Technically, a legal term, used to denote capacity to act on one’s own behalf; the ability to understand information presented, to appreciate the consequences of acting (or not acting) on that information, and to make a choice. (See also: Incompetence, Incapacity)

Pertains to the treatment of information that an individual has disclosed in a relationship of trust and with the expectation that it will not be divulged to others without permission in ways that are inconsistent with the understanding of the original disclosure.

Defined as a set of conditions in which an investigator’s judgment concerning a primary interest (e.g., subject welfare, integrity of research) could be biased by a secondary interest (e.g., personal or financial gain). See information regarding UNLV’s Conflict of Interest/Compensated Outside Services Policy .

See “Informed Consent.”

Subject(s) used for comparison who are not given the treatment under study or who do not have a given condition, background, or risk factor that is the object of study. Control conditions may be concurrent (occurring more or less simultaneously with the condition under study) or historical (preceding the condition under study). When the present condition of subjects is compared with their own condition on a prior regimen or treatment, the study is considered historically controlled.

The other primary scholar or researcher involved in conducting the research. Co-PIs must also meet the UNLV PI eligibility requirements.

Giving subjects previously undisclosed information about the research project following completion of their participation in research.

A code of ethics for clinical research approved by the World Medical Association in 1964 and widely adopted by medical associations in various countries. It was revised most recently in 2008.

Any study that is not truly experimental (e.g., quasi-experimental studies, correlational studies, record reviews, case histories, and observational studies).

A legal status conferred upon persons who have not yet attained the age of legal competency as defined by state law (for such purposes as consenting to medical care), but who are entitled to treatment as if they had by virtue of assuming adult responsibilities such as marriage, procreation, or being self-supporting and not living at home. (See also “Mature Minor.”)

Fair or just; used in the context of selection of subjects to indicate that the benefits and burdens of research are fairly distributed.

The code of federal regulations (45 CFR 46.101(b)) identifies several categories of minimal risk research as exempt from the Federal Policy for the Protection of Research Subjects. This determination must not be made by the PI, but by the IRB or someone appointed by the IRB. For more information, see the U.S. Health and Human Services website, “ Exempt Research and Research That May Undergo Expedited Review .”

The code of federal regulations (45 CFR 46.110 and 21 CFR 56.110) identifies several categories of minimal risk research that may be reviewed through an expedited review process. For more information, see the U.S. Health and Human Services website on “ Guidance on Expedited Review Procedures .”

This act defines the rights of students and parents concerning reviewing, amending, and disclosing educational records and requires written permission to disclose personally identifiable information from a student’s education record, except under certain circumstances such as an order of subpoena. 1

The federal policy that provides regulations for the involvement of human subjects in research. The policy applies to all research involving human subjects conducted, supported, or otherwise subject to regulation by any federal department or agency that takes appropriate administrative action to make the policy applicable to such research. Currently, 16 federal agencies have adopted this policy, commonly referred to as “The Federal Policy,” but also known as the “Common Rule.”

A formal written, binding commitment that is submitted to the Department of Health and Human Services (DHHS) Office of Human Research Protections (OHRP) in which an institution agrees to comply with applicable regulations governing research with human subjects and stipulates the procedures through which compliance will be achieved. UNLV’s assurance number is FWA00002305.

Review of proposed research at a convened meeting at which a majority of the membership of the IRB are present, including at least one member whose primary concerns are in nonscientific areas. For the research to be approved, it must receive the approval of a majority of those members present at the meeting. Generally, studies that undergo full board review are studies involving greater than minimal risk, risky, or novel procedures or vulnerable populations.

An individual who is authorized under applicable state or local law to give permission on behalf of a child for general medical care. In Nevada, under NRS 159.0805, guardians may not give permission for a child to enter into a research study unless a court order has been obtained.

The rule which protects the privacy of individually identifiable health information. The privacy rule provides federal protections for personal health information held by covered entities and gives patients specific rights with respect to that information.

Individuals whose physiological or behavioral characteristics and responses are the object of study in a research project. Under the federal regulations, human subjects are defined as living individual(s) about whom an investigator conducting research obtains: (1) data through intervention or interaction with the individual; or (2) identifiable private information.

Federal regulations define identifiable to mean that the identity of the individual subject is or may readily be ascertained by the investigator or may be associated with the information.

This refers to a person’s mental status and means inability to understand information presented, to appreciate the consequences of acting (or not acting) on that information, and to make a choice. The term is often used as a synonym for incompetence.

A legal term meaning inability to manage one’s own affairs, and often used as a synonym for incapacity.

A person’s voluntary agreement, based upon adequate knowledge and understanding of relevant information, to participate in research or to undergo a diagnostic, therapeutic, or preventive procedure. In giving informed consent, subjects may not waive or appear to waive any of their legal rights, or release or appear to release the investigator, the sponsor, the institution, or agents thereof from liability for negligence.

Institutional research (also called internal research) is the gathering of data from or about UNLV students, faculty, and staff by university offices or organizations, with the sole intent of using the data for internal informational purposes or for required data-collection purposes. This data would not be made generalizable. Examples include surveys to improve university services or procedures; ascertain the opinions, experiences, or preferences of the university community; or to provide necessary information to characterize the university community. This kind of data gathering does not require IRB review unless respondents are queried about sensitive aspects of their own behavior. For debatable projects, investigators should submit an exclusion review form to the ORI-HS.

A specially constituted, federally mandated review body established or designated by an entity to protect the welfare of human subjects recruited to participate in biomedical or behavioral research. UNLV has two IRBs – Social/Behavioral and Biomedical.

The federal regulations define interaction as “communication or interpersonal contact between investigator and subject.”

The federal regulations define intervention as both physical procedures by which data are gathered (for example, venipuncture) and manipulations of the subject or the subject’s environment that are performed for research purposes.

This refers to a researcher conducting the project. Investigators can be principal investigators or co-principal investigators. Students are always listed as student investigators.

A formal agreement between UNLV and another FWA-holding institution that allows the one IRB to serve as the “IRB of Record” for protocols involving collaborative research between UNLV and the other institution.

A term utilized when an institution assumes the IRB responsibilities for a human subject research protocol conducted at another institution. An IRB authorization agreement signed by institutional officials at both institutions is required.

An ethical principle discussed in the Belmont Report requiring fairness in distribution of burdens and benefits; those that bear the burdens of research should also receive the benefits. There must be fair and equitable selection of subjects.

A person authorized either by statute or by court appointment to make decisions on behalf of another person. In human subjects research, an individual or judicial or other body authorized under applicable law to consent on behalf of a prospective subject to the subject’s participation in the procedure(s) involved in the research.

Someone who has not reached adulthood (as defined by state law) but who may be treated as an adult for certain purposes (e.g., consenting to medical care). Note that a mature minor is not necessarily an emancipated minor. (See also “Emancipated Minor.”)

A risk is minimal when the probability and magnitude of harm or discomfort anticipated in the proposed research are not greater, in and of themselves, than those ordinarily encountered in daily life or during the performance of routine physical or psychological examinations or tests. For example, the risk of drawing a small amount of blood from a healthy individual for research purposes is no greater than the risk of doing so as part of routine physical examination. Note: The definition of minimal risk for research involving prisoners differs somewhat from that given for non-institutionalized adults.

Any change to an IRB-approved study protocol, regardless of the level of review it receives initially.

A federally mandated member of an Institutional Review Board who has no ties to the parent institution, its staff, or faculty. This individual is usually from the local community (e.g., business person, attorney, or teacher).

A code of research ethics developed during the trials of Nazi war criminals following World War II and widely adopted as a standard during the 1950s and 1960s for protecting human subjects.

The office within the Department of Health and Human Services that is responsible for implementing DHHS regulations (45CFR46) governing research involving human subjects.

The UNLV office, formerly known as the Office for the Protection of Research Subjects (OPRS), that serves as an administrative hub for the UNLV IRB’s oversight of human subjects research.

The agreement of parent(s) to the participation of their child in research.

The scientist or scholar with primary responsibility for the design and conduct of a research project. See UNLV’s PI Eligibility Policy for those who are eligible for automatic PI status and how to apply for PI status.

An individual involuntarily confined in a penal institution, including persons: 1) sentenced under a criminal or civil statue; 2) detained pending arraignment, trial, or sentencing; and 3) detained in other facilities (e.g., for drug detoxification or treatment of alcoholism) under statutes or commitment procedures providing such alternatives to criminal prosecution or incarceration in a penal institution. Note that this includes adjudicated youth.

Control over the extent, timing, and circumstances of disclosing personal information (physical, behavioral, or intellectual) with others.

Defined by the federal regulations to include information about behavior that occurs in a context in which an individual can reasonably expect that no observation or recording is taking place. It also includes information that has been provided for specific purposes by an individual and which the individual can reasonably expect will not be made public (e.g., a medical record). Private information must be individually identifiable (i.e., the identity of the subject is or may readily be ascertained by the investigator or associated with the information) in order for the acquisition of the information to constitute research involving human subjects.

Studies designed to observe outcomes or events that occur subsequent to the identification of the group of subjects to be studied. Prospective studies need not involve manipulation or intervention but may be purely observational or involve only the collection of data.

Applies to survey research conducted in schools and states that parents have the right to inspect surveys and questionnaires distributed within schools. This amendment also specifies that parental permission must be obtained to have minors participate in surveys that disclose certain types of sensitive information. 1

The formal design or plan of an experiment or research study; specifically, the plan submitted to an IRB for review and to an agency for research support. The protocol includes a description of the research design or methodology to be employed, the eligibility requirements for prospective subjects and controls, the treatment regimen(s), and the proposed methods of analysis that will be performed on the collected data.

A systematic investigation (i.e., the gathering and analysis of information) designed to develop or contribute to generalizable knowledge.

An ethical principle discussed in the Belmont Report requiring that individual autonomy be respected and persons with diminished autonomy be protected.

Research conducted by reviewing records from the past (e.g., birth and death certificates, medical records, school records, or employment records) or by obtaining information about past events elicited through interviews or surveys. Case control studies are an example of this type of research. This requires IRB review, as long as it involves private information about humans.

The probability of harm or injury (physical, psychological, social, or economic) occurring as a result of participation in a research study. Both the probability and magnitude of possible harm may vary from minimal to significant. Risks include immediate risks of study participation as well as risks of long-term effects.

This involves two types of data: 1) data collected by someone other than the principal investigator for a research or non-research purpose, or 2) data that was collected by the principal investigator, but when collected was not intended to be used for human subjects research. For data to be considered secondary data, the data must exist prior to the initiation of the current research study or be “on the shelf” at the time of study initiation. Principal investigators must submit and receive approval for use of secondary human subjects data prior to initiation of the project.

A visit by agency officials, representatives, or consultants to the location of a research activity to assess the adequacy of IRB protection of human subjects or the capability of personnel to conduct the research.

“Participant” is the preferred term since it more correctly portrays the participatory aspects of research. Sometimes “subject” more accurately describes the role.

Free of coercion, duress, or undue inducement or influence. Used in the research context to refer to a subject’s decision to participate (or to continue to participate) in a research activity.

Glossary of Key Research Terms

This glossary provides definitions of many of the terms used in the guides to conducting qualitative and quantitative research. The definitions were developed by members of the research methods seminar (E600) taught by Mike Palmquist in the 1990s and 2000s.

Citation Information

Members of the Research Methods Seminar (E600) taught by Mike Palmquist in the 1990s and 2000s. (1994-2024). Glossary of Key Terms. The WAC Clearinghouse. Colorado State University. Available at https://wac.colostate.edu/repository/writing/guides/.

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Definition of human subjects research.

• Obtains information or biospecimens through intervention or interaction with the individual, and uses, studies, or analyzes the information or biospecimens; or
• Obtains, uses, studies, analyzes, or generates identifiable private information or identifiable biospecimens."

Are you planning on conducting human subjects research? Learn more about research that meets the definition human subjects research, Federal regulation requirements, and whether your project may be considered exempt. Also, learn about NIH specific considerations and become more familiar with NIH policies, and other regulations as it relates to human subjects research protections.

Decision Tool: Am I Doing Human Subjects Research?

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Human Subjects Research Infographic

This resource summarizes the definition of human subjects research and provides examples of human subjects research projects. It also describes what you will need when you are preparing your NIH application and what is required if you are funded.

Exempt Human Subjects Research Infographic

This resource is a guide to simplify the understanding of the exemptions from the federal regulations for the protection of human subjects research. It summarizes Exemptions 1, 2, 3, 4, 5, 6, 7 and 8, providing basic definitions, examples of studies that meet and do not meet the criteria of the exemption, and aspects one must consider when engaged in exempt or non-exempt human subjects research.

Research Involving Private Information or Biospecimens Flowchart

Studies involving the use of human specimens or data may or may not be considered to be research involving human subjects, depending on the details of the materials to be used. Use this flowchart to help determine if studies involving private information or biospecimens may meet the definition of human subjects research.

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Are you in the American middle class? Find out with our income calculator

About half of U.S. adults (52%) lived in middle-income households in 2022, according to a Pew Research Center analysis of the most recent available government data. Roughly three-in-ten (28%) were in lower-income households and 19% were in upper-income households.

Our calculator below, updated with 2022 data, lets you find out which group you are in, and compares you with:

• Other adults in your metropolitan area
• U.S. adults overall
• U.S. adults similar to you in education, age, race or ethnicity, and marital status

Find more research about the U.S. middle class on our topic page .

Our latest analysis shows that the estimated share of adults who live in middle-income households varies widely across the 254 metropolitan areas we examined, from 42% in San Jose-Sunnyvale-Santa Clara, California, to 66% in Olympia-Lacey-Tumwater, Washington. The share of adults who live in lower-income households ranges from 16% in Bismarck, North Dakota, to 46% in Laredo, Texas. The share living in upper-income households is smallest in Muskegon-Norton Shores, Michigan (8%), and greatest in San Jose-Sunnyvale-Santa Clara, California (41%).

How the income calculator works

The calculator takes your household income and adjusts it for the size of your household. The income is revised upward for households that are below average in size and downward for those of above-average size. This way, each household’s income is made equivalent to the income of a three-person household. (Three is the whole number nearest to the  average size of a U.S. household , which was 2.5 people in 2023.)

Pew Research Center does not store or share any of the information you enter.

We use your size-adjusted household income and the cost of living in your area to determine your income tier. Middle-income households – those with an income that is two-thirds to double the U.S. median household income – had incomes ranging from about $56,600 to $169,800 in 2022. Lower-income households had incomes less than $56,600, and upper-income households had incomes greater than $169,800. (All figures are computed for three-person households, adjusted for the cost of living in a metropolitan area, and expressed in 2022 dollars.)

The following example illustrates how cost-of-living adjustment for a given area was calculated: Jackson, Tennessee, is a relatively inexpensive area, with a  price level in 2022 that was 13.0% less than the national average. The San Francisco-Oakland-Berkeley metropolitan area in California is one of the most expensive, with a price level that was 17.9% higher than the national average. Thus, to step over the national middle-class threshold of $56,600, a household in Jackson needs an income of only about $49,200, or 13.0% less than the national threshold. But a household in the San Francisco area needs an income of about $66,700, or 17.9% more than the U.S. threshold, to be considered middle class.

The income calculator encompasses 254 of 387 metropolitan areas in the United States, as defined by the Office of Management and Budget  . If you live outside of one of these 254 areas, the calculator reports the estimates for your state.

The second part of our calculator asks about your education, age, race or ethnicity, and marital status. This allows you to see how other adults who are similar to you demographically are distributed across lower-, middle- and upper-income tiers in the U.S. overall. It does not recompute your economic tier.

Note: This post and interactive calculator were originally published Dec. 9, 2015, and have been updated to reflect the Center’s new analysis.   Former Senior Researcher Rakesh Kochhar and former Research Analyst Jesse Bennett also contributed to this analysis.

The Center recently published an analysis of the distribution of the  American population across income tiers . In that analysis, the estimates of the overall shares in each income tier are slightly different, because it relies on a separate government data source and includes children as well as adults.

Pew Research Center designed this calculator as a way for users to find out, based on our analysis, where they appear in the distribution of U.S. adults by income tier, as well as how they compare with others who match their demographic profile.

The data underlying the calculator come from the 2022 American Community Survey (ACS). The ACS contains approximately 3 million records, or about 1% of the U.S. population.

In our analysis, “middle-income” Americans are adults whose annual household income is two-thirds to double the national median, after incomes have been adjusted for household size. Lower-income households have incomes less than two-thirds of the median, and upper-income households have incomes more than double the median. American adults refers to those ages 18 and older who reside in a household (as opposed to group quarters).

In 2022, the  national  middle-income range was about $56,600 to $169,800 annually for a household of three. Lower-income households had incomes less than $56,600, and upper-income households had incomes greater than $169,800. (Incomes are calculated in 2022 dollars.) The median adjusted household income used to derive this middle-income range is based on household heads, regardless of their age.

These income ranges vary with the cost of living in metropolitan areas and with household size. A household in a metropolitan area with a higher-than-average cost of living, or one with more than three people, needs more than $56,600 to be included in the middle-income tier. Households in less expensive areas or with fewer than three people need less than $56,600 to be considered middle income. Additional details on the methodology are available in our  earlier analyses .

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Principal: UVA Mindfulness Research for Students Is a ‘Game-Changer’

• By Audrey Breen , [email protected]

(Illustration by John DiJulio, University Communications)

James Payne, an elementary school student, took in a deep breath and exhaled slowly.

“When you’re frustrated, when you’re having a bad day, just take some deep breaths and you’ll be good to go,” James said.

He learned that lesson as a student at Semple Elementary School in Louisville, Kentucky, as part of a University of Virginia research project billed as “the most comprehensive study ever undertaken of a 21st-century health and wellness curriculum in an elementary or secondary school setting.”

In the eight-year study published last month involving 45 elementary schools and nearly 10,000 students in Kentucky’s Jefferson County Public Schools, UVA researchers found a curriculum called “Flourish” had positive impacts on students, particularly in schools serving high-poverty communities.

Flourish “has been a game-changer for us,” Danielle Randle, Semple Elementary’s principal, said. 

Flourish is part of UVA’s   Compassionate Schools Project , a collaboration involving UVA’s School of Education and Human Development, its Youth-Nex Center, UVA’s Contemplative Sciences Center and the Jefferson County Public Schools. Flourish integrates mindfulness and movement into social and emotional learning to improve academic engagement, student well-being and behavior.

Students who participated in Flourish showed improvements in attention control, had a greater sense of support from their classmates and believed more strongly in their abilities to solve social problems. Researchers said the curriculum also helped prevent problem behaviors while increasing important developmental skills.

“I am always stressed that I am going to mess up,” said Maddie Pfannerstill, a Louisville elementary school student, “so I use mindfulness breathing to calm myself down.”

The students, teachers and administrators described their experiences with the project on a video   produced about halfway through the study.

The Compassionate Schools Project, or CSP, “has been great for our school,” said Candace McMahon, a former CSP teacher at Luhr Elementary School in Kentucky.

“We have found that our kids have a lot of issues from their home lives that sometimes come with them to school that cause them to have trouble regulating their emotions and their focus,” McMahon said. “CSP really gives them specific strategies that they can use to put in place when they are feeling strained or stressed. And it will be strategies that will help them not only in school, but throughout life.”

Tish Jennings, left, and Patrick Tolan, professors in UVA’s School of Education and Human Development, were part of an eight-year study of schoolchildren to understand if using mindfulness practices in the classroom made them better students. (Photos by Tom Daly)

Jefferson County Public Schools Superintendent Marty Pollio said the findings confirm what teachers and principals participating in the study have been telling him.

“This curriculum can help all of our students, but especially those in schools with the most need, in terms of being ready to learn day in and day out,” Pollio said. “And its lasting, preventive effect on disruptive behavior not only helps that student, but also peers, teachers, schools and the whole system.”

The effects were stronger in schools serving high-poverty communities, where students saw improvements in social problem-solving and positive behavior and reductions in problem behavior.

“The results show that through a class with this curriculum that is part of regular education, students can gain important resiliency skills that have well-proven linkages to better academic, mental health and behavioral functioning long term,” Patrick Tolan, a UVA education professor and principal investigator of the study, said. “It is exciting to see that the benefits were stronger where the need was greater.”

UVA researchers say the program’s focus on contemplation, integrating compassion and mindful awareness practices is uniquely innovative.

“While an increasing number of social and emotional learning programs are incorporating mindfulness into their curricula, few take such a comprehensive approach in designing a program that fosters students’ psychological well-being, social and emotional skills, physical health and attention,” said Tish Jennings, a professor at the UVA School of Education and coauthor of the Flourish curriculum.

With positive results from a prior pilot study and funding from a coalition of partners, the researchers launched the 8-year randomized control trial. The effects of the curriculum were measured over 2 years with follow-up to trace its impact over the long term. 

“The Flourish curriculum is still being implemented with integrity, and educators continue to benefit from the training and support,” said Alexis Harris, director of the Compassionate Schools Project and coauthor of Flourish.

“I have been amazed by the rigorous work of the researchers, educators, school administrators, funders, advisers, community partners and more, who all came together with us to fill an important void in knowledge,” Owsley Brown III, board member of the Contemplative Sciences Center at UVA, said. “Mindfulness practices are well known to be effective in many settings, and they are often used in schools, but there hasn’t been high-quality research on whether and how they support learning for young kids. Louisville has given a rich trove of answers, and this is just the beginning.”

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Audrey Breen

Senior Writer and Research Communications Strategist School of Education and Human Development

[email protected] 434-924-0809

Article Information

September 25, 2024

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