importance of defining key terms in research

Terminology, the importance of defining

Affiliations.

• 1 Van Mil Consultancy, Zuidlaren, The Netherlands. [email protected].
• 2 School of Pharmacy & Pharmaceutical Sciences, Faculty of Health Sciences, Trinity College Dublin, Dublin, Ireland.
• PMID: 27073076
• DOI: 10.1007/s11096-016-0294-5

Multiple terms and definitions exist to describe specific aspects of pharmacy practice and service provision. This commentary explores the reasons for different interpretations of words and concepts in pharmaceutical care and pharmacy practice research. Reasons for this variation can be found in language, culture, profession and may also depend on developments over time. A list of words is provided where the authors think that currently multiple interpretations are possible. To make sure that the reader understands the essence, it seems imperative that authors include a definition of the topics that they actually study in their papers, and that they clearly cite existing definitions or refer to collections of definitions such as existing glossaries. It is important that presenters, authors and reviewers of pharmacy practice papers pay more attention to this aspect of describing studies.

Keywords: Pharmacy practice; Research; Terminology; Translation.

• Community Pharmacy Services
• Pharmacy Research / standards*
• Terminology as Topic*

Getting Started: Library Research Strategy

• Choosing Your Topic
• Gathering Background Information
• Defining Key Terms
• Crafting a Research Question
• Gathering Relevant Information
• Evaluating Sources This link opens in a new window
• Formulating a Thesis Statement
• Avoiding Plagiarism This link opens in a new window
• Citation Styles This link opens in a new window

If you have chosen a topic, you may break the topic down into a few main concepts and then list and/or define key terms related to that concept. If you have performed some background searching, you can include some of the words that were used to describe your topic.

For example, if your topic deals with the relationship between teenage smoking and advertising in the United States, the following key terms may apply:

smoking -- tobacco -- nicotine -- cigarettes

teenage -- adolescents -- children -- teens -- youth

advertising -- marketing -- media -- commercials -- TV -- billboards

When listing the key terms or concepts of your topic, be sure to consider synonyms for these terms as well. Since research is an iterative process, you will also find additional key terms to utilize through the resources you encounter throughout your research process.

• << Previous: Gathering Background Information
• Next: Crafting a Research Question >>
• Last Updated: Mar 11, 2024 4:57 PM
• URL: https://libguides.chapman.edu/strategy

Chapter Twelve: Positing a Thesis Statement and Composing a Title / Defining Key Terms

Defining Key Terms

You are viewing the first edition of this textbook. a second edition is available – please visit the latest edition for updated information..

Earlier in this course, we discussed how to conduct a library search using key terms. Here we discuss how to present key terms. Place yourself in your audience’s position and try to anticipate their need for information. Is your audience composed mostly of novices or professionals? If they are novices, you will need to provide more definition and context for your key concepts and terms.

Because disciplinary knowledge is filled with specialized terms, an ordinary dictionary is of limited value. Disciplines like psychology, cultural studies, and history use terms in ways that are often different from the way we communicate in daily life. Some disciplines have their own dictionaries of key terms. Others may have terms scattered throughout glossaries in important primary texts and textbooks.

Key terms are the “means of exchange” in disciplines. You gain entry into the discussion by demonstrating how well you know and understand them. Some disciplinary keywords can be tricky because they mean one thing in ordinary speech but can mean something different in the discipline. For instance, in ordinary speech, we use the word  shadow  to refer to a darker area produced by an object or person between a light source and a surface. In Jungian psychology,  shadow  refers to the unconscious or unknown aspects of a personality. Sometimes there is debate within a discipline about what key terms mean or how they should be used.

To avoid confusion, define all key terms in your paper before you begin a discussion about them. Even if you think your audience knows the definition of key terms, readers want to see how  you  understand the terms before you move ahead. If a definition is contested—meaning different writers define the term in different ways—make sure you acknowledge these differences and explain why you favor one definition over the others. Cite your sources when presenting key terms and concepts.

Key Takeaways

Strategies for Conducting Literary Research Copyright © 2021 by Barry Mauer & John Venecek is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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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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Key research terms.

bias: any influence that may distort the results of a research study and lead to error; the loss of balance and accuracy in the use of research methods.

case study: presentation of data about selected settings, persons, groups or events. Data can have been gathered using variety of different research methods (e.g., questionnaire, observation, historical or literary analysis). Is chiefly descriptive and analytical, usually based on qualitative data, though statistics such as survey findings may be included.

causal relationship: relationship between variables where movements in one or more variable(s) are held to cause changes in the other (s).

coded data: data are put into groups or categories, such as age groups, and each category is given a code number. Data are usually coded for convenience, speed, and handling to enable statistical analysis. construct: a mental state that can’t be directly observed or manipulated, such as love, intelligence, hunger, feeling warm, and aggression; a concept developed (constructed) for describing relations among or between phenomena or for other research purposes.

construct validity: the degree to which the study actually measures and manipulates the elements that the researcher claims to be measuring and manipulating. If the operational definitions of the constructs are poor, the study will not have good construct validity. For example, a test claiming to measure “aggressiveness” would not have construct validity if it really measured assertiveness.

internal validity: the degree to which the study demonstrates that a particular factor caused a change in behavior. If a study lacks internal validity, the researcher may falsely believe that a factor causes an effect when it really doesn’t. Most studies involving humans do not have internal validity because they can’t rule out the possibility that some other factor may have been responsible for the effect.

controls: processes used to make uniform or constant the conditions for carrying out an investigation.

control group: in experimental research, the group or item which does not receive the treatment or intervention under investigation and is used to compare outcomes with the one that does. correlation: the extent to which two or more factors vary in relationship to one another; the extent of association between two or more variables. Correlation does not equal causation. For example, might suggest relationship between academic success and self-esteem, but cannot prove that a change in first variable causes a change in second variable. correlation coefficient: a measure of the degree of relationship between two variables. It usually lies between +1 (showing a perfect positive relationship), 0 (showing no relationship), to -1.0 (showing a perfect negative relationship). dependent variable: variable thought to be determined or influenced by others.

experiment: a special type of study (not all studies are experiments!) that allows researchers to determine the cause of an effect; usually involves randomly assigning participants to groups.

external validity: the degree to which the results of the study can be generalized to other places, people, or times.

hypothesis: a proposition which research sets out to prove or disprove: “experimental” where the hypothesis is a positive statement, or “null” where statement contains a negative.

independent variable: a variable that researcher believes precedes, influences or predicts the dependent variable.

informed consent: giving potential participants information about the study, especially in terms of factors that might lead them to refuse to be in the study, before they decide whether to participate. Institutional Review Board (IRB): a committee of at least five members--one of whom must be a nonscientist--that review proposed research and monitor approved research in an effort to protect human research participants.

literature review: often the first step in the research process, it is a review of the literature on and around the subject of inquiry. Its main purposes are to avoid duplication, to identify gaps in research and to place the researcher’s approach within the work and approaches of others.

primary/secondary sources: primary sources are original firsthand records or materials relating to an event or happening. They may include, for example, official minutes of meetings, diaries, verbatim transcripts of interviews, completed questionnaires or records of the results of experiments. Secondary sources are accounts bases upon these, which usually offer an interpretation, commentary, analysis, or restatement of the primary sources. They can include, for example, books, journal articles, and conference papers.

qualitative data: information gathered in narrative, non-numerical form (e.g., transcript of an interview). Qualitative research used for exploratory (hypothesis-generating) purposes or explaining puzzling quantitative results, while quantitative methods are used to test hypotheses.

quantitative data: information gathered in numerical form. reliability: extent to which the same result will be repeated/achieved by using the same measure.

statistical significance: tests used to estimate the likelihood that the finding in a sample is true of the population from which the sample is derived and not due to chance.

simple experiment: used to establish cause and effect, so this type often used to determine effect of treatment. Participants randomly assigned to either control group with no treatment, while the experimental group receives treatment.

validity: extent to which research findings can be said to be accurate and reliable; degree to which conclusions are justified. Internal validity is extent to which researchers can show that they have evidence for the statements they make; external validity refers to a study’s generalizability.

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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 1.1 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 1.1 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.

Figure 1.3: Shows the research paradigms and research process © JIBC 2019

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). Figure 1.2 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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• Published: 27 July 2021

Conceptualizing the elements of research impact: towards semantic standards

• Brian Belcher   ORCID: orcid.org/0000-0002-7356-745X 1 , 2 &
• Janet Halliwell   ORCID: orcid.org/0000-0002-4224-9379 3  

Humanities and Social Sciences Communications volume  8 , Article number:  183 ( 2021 ) Cite this article

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• Complex networks
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• Science, technology and society

Any effort to understand, evaluate, and improve the impact of research must begin with clear concepts and definitions. Currently, key terms to describe research results are used ambiguously, and the most common definitions for these terms are fundamentally flawed. This hinders research design, evaluation, learning, and accountability. Specifically, the terms outcome and impact are often defined and distinguished from one another using relative characteristics, such as the degree, directness, scale, or duration of change. It is proposed instead to define these terms by the kind of change rather than by the degree or temporal nature of change. Research contributions to a change process are modeled as a series of causally inter-related steps in a results chain or results web with three main kinds of results: (i) the direct products of research, referred to as outputs; (ii) changes in the agency and actions of system actors when they are informed/influenced by research outputs, referred to as outcomes; and (iii) tangible changes in the social, economic, environmental, or other physical condition, referred to as realized benefits. Complete definitions for these terms are provided, along with examples. This classification aims to help focus research evaluation appropriately and enhance appreciation of the multiple pathways and mechanisms by which scholarship contributes to change.

Introduction

There are high expectations from the public, research funding agencies, and researchers themselves to contribute to and document impact resulting from their research (Bornmann, 2012 ; Edler et al., 2012 ; Wilsdon et al., 2015 ). Any effort to understand, evaluate, and improve the impact of research must begin with clear concepts and definitions. Currently there is a debilitating lack of clarity and consistency in the use of key terms that describe the results of any intervention, including changes engendered by research. The terms output, outcome, and impact, which are terms used in a typical logic model, are used ambiguously and the most common definitions for these terms are fundamentally flawed (Belcher and Palenberg, 2018 ). This hinders evaluation, learning, and accountability in academic research as much or more than in any other field. This essay, based on the authors’ experience with conceptualizing and assessing research impact in the social sciences and humanities, applied research, and research-for-development contexts, takes a systems perspective on research impact and offers precise sub-categories of impact to improve clarity.

Established concepts used in research evaluation such as “impact factor” and “high impact research” refer to measures of publication and citations of research, but do not measure actual use or value beyond the academic realm (DORA, 2012 ; Hicks et al., 2015 ). There has been increasing attention to the non-academic impacts of research (Bornmann, 2012 ; Oancea, 2019 ; Williams, 2020 ). Alla et al. ( 2017 ) conducted a systematic review of definitions of research impact, finding 108 definitions in 83 publications. However, they noted a dominance of what they called bureaucratic definitions and a widespread failure to actually define the term explicitly. The most highly cited definitions were those of the Research Excellence Framework (“an effect on, change or benefit to the economy, society, culture, public policy or services, health, the environment or quality of life, beyond academia” (REF, 2011 , p. 26)), the Research Councils of the UK (“the demonstrable contribution that excellent research makes to society and the economy” (Economic and Social Research Council, 2021 , para.1)), and the Australian Engagement and Impact Assessment framework (“the contribution that research makes to the economy, society, environment or culture, beyond the contribution to academic research” (Australian Research Council, 2018 , p. 5)). While these broad, all-encompassing concepts give attention to societal benefits beyond academia, they all lack precision and require further classification to be useful analytically. They also fail to recognize that research typically contributes to change within complex social, economic, technical, and environmental systems, in conjunction with many other factors. Based on their review, Alla et al. ( 2017 ) re-emphasize the need for conceptual clarity, while offering their own definition specific to the mental health field: “Research impact is a direct or indirect contribution of research processes or outputs that have informed (or resulted in) development of new (mental) health policy/practices, or revisions of existing (mental) health policy/practices, at various levels of governance (international, national, state, local, organizational, health unit)” (p. 9).

Gow and Redwood ( 2020 ) also give considerable attention to the lack of clarity in interpretation of impact. They devote a chapter to discuss impact terminology and suggest a four-part impact typology: Instrumental; Conceptual; Capacity Building, and Procedural. They do not provide precise definitions for these sub-components of impact, and the authors themselves note that the categories are not mutually exclusive.

The term outcome is also widely used to refer to a step in a results chain. Like impact, outcome is also used ambiguously to refer to everything from the products of research to intermediate and shorter-duration changes stimulated by research, and it is often used as a synonym for impact. Most results chains conceptualize outcomes as resulting from outputs and as precursors to impact. The terms outcome and impact are typically distinguished from one another relatively, based on the degree, directness, scale, or duration of change. For example, the influential OECD ( 2010 ) glossary of evaluation terms defined outcomes as “The likely or achieved short-term and medium-term effects of an intervention’s outputs” (p. 28) and impacts as “Positive and negative, primary and secondary long-term effects produced by a development intervention, directly or indirectly, intended or unintended” (p. 24). As Belcher and Palenberg ( 2018 ) discuss in detail, these definitions do not support clear, unambiguous distinctions between the terms or the concepts they are intended to define. Of particular relevance is the fact that the temporal dimension of these definitions is not helpful for analytical purposes such as research design, evaluation, learning, and accountability.

All the above impact definitions refer to a ‘contribution’ made by research, but devote most of their attention to the locus of change (i.e., beyond academia). They offer little to help specify, understand, or analyze the nature of the contribution research makes, or to ascertain definitively what is included and what is excluded in the definition. To help clarify the concept and advance thinking about research impact, we therefore propose two more precise sub-categories of impact that are defined absolutely, by the kind of change, rather than relatively, by the degree or temporal nature of change. We recognize that change processes happen in complex systems. Research contributes to a change process within a system and can be modeled as a series of causally inter-related steps in a results chain or results web. There are three main kinds of results from research: (i) the products and services of research, produced directly by a research program, which we refer to as outputs; (ii) changes in the agency of other actors when they use and/or are influenced by research outputs, which we refer to as outcomes; and (iii) tangible changes in the social, economic, environmental, or other physical condition, which we refer to as realized benefits. Complete definitions for these terms are provided below, along with examples. This is a classification of the types of contributions of research and scholarship within a theory of change, not a hierarchy of value.

Societal demands for impact naturally focus on positive changes in social, economic, environmental, or other physical condition. Research is supported with the expectation that it will contribute in some way to improvements in human well-being and environmental conditions. In the development field, the term impact is often used to mean mission-level impact (i.e., changes in social, economic, environmental, and/or physical condition) (Belcher and Palenberg, 2018 ). However, the term impact is used commonly and ambiguously in standard English language, and in the academic realm it has both a particular meaning (often measured by citations) and a general meaning that includes what we have called outcomes as well as realized benefits (and costs), as exemplified by the definitions cited above. The term is so imprecise in its common usage, and so loaded with pre-existing definitions, that it would be difficult to re-define. We have therefore elected not to propose a new or restricted definition of the term impact. Rather, we are proposing a classification of sub-categories of impact, which are based on the nature of the change. We use “impact” as an overarching term to denote any change caused in whole or in part by an action or set of actions, including research actions.

Proposed definitions

Knowledge, including new insights, technical innovations, institutional models, and other direct products and services produced by a research program. Outputs are produced by actions within a program’s (including partners) sphere of control (see Fig. 1 ).

Examples of outputs include: new research methods, data sets, analyses, discoveries, histories, new theories, policy analyses or recommendations, and artistic performances. Outputs may also include processes such as discussion fora, networking, or capacity building done as part of a research process.

Outputs are the actual knowledge, innovations, and services produced by research as well as the media that communicate knowledge and innovation, such as books, journal publications, policy briefs, or patents.

A change in knowledge, attitudes, skills, and/or relationships (KASR), ideally manifest as a change in behavior (B), that results in whole or in part from the research process and its outputs. Outcomes may be at the individual, group, organizational, or higher scales.

Outcomes occur in actors beyond the research boundary; that is, outside the sphere of control and within the spheres of influence and interest.

By this definition, a change in an individual, group, or organization’s KASR is an outcome.

If a change in KASR leads to an action or set of actions (a change in behavior Footnote 1 ) by an actor in the system, that action may in turn contribute to changes in other actors’ KASR and behavior. Such downstream changes are also defined as outcomes. A change in KASR is an outcome by this definition, but it can only contribute to further change if it leads to some action.

In research evaluation, outcomes can be disaggregated into academic outcomes , which refers to influences and changes within the academic realm, and societal outcomes , which refers to changes outside the academic realm.

Examples of academic outcomes include adoption and use of new methods, replication of studies, use of data sets, or use of new theories by other researchers.

Examples of societal outcomes include changes Footnote 2 in understanding of risk or vulnerabilities; changes in public understanding, values, and attitudes; adoption of new technologies or organizational practices; licensing of patents; new partnerships with community groups; skills and capabilities inculcated through the research experience; shared knowledge and public discourse; new policy or regulations; or creation of a social enterprise.

Realized benefits

A change in economic, social, or environmental condition resulting in whole or in part from a chain of events to which research has contributed. This can manifest as a change in flow or change in state. Benefits/costs may be realized at individual, group, organizational, or higher scales.

Realizing tangible social, economic, and/or environmental benefits often Footnote 3 involves actors outside the program’s/researcher’s sphere of influence and is the ultimate stage of a complex pathway and change process to which the research has contributed.

Examples of realized benefits include: changes in income (flow) or wealth (state), changes in the level of press freedom (state), changes in carbon emissions (flow) or water quality (state), changes in levels of experienced racism, or changes in a person’s or a community’s mental health status.

Realized benefits may be positive or negative in the same way an investment can yield a negative return; that is, the change process to which research contributes may have negative or harmful social, economic, and/or environmental consequences for some or all stakeholders. Such negative consequences are sometimes termed “grimpacts” (Derrick et al., 2018 , p. 1199).

Research outputs, outcomes, and realized benefits in a theory of change

Figure 1 illustrates a research program Footnote 4 theory of change. The three spheres reflect the fact that the relative influence of any intervention declines as interactions with other actors and processes increase (Hearn, 2010 ; Montague, 2000 ). The program has a high level of control over program activities and outputs in the sphere of control. Beyond the program boundary, research outputs inform, influence, and support other actors and their actions (outcomes), alongside many other influences and processes, in the sphere of influence. Ideally, the actions of those other actors will then contribute to realized benefits in the sphere of interest.

Generic research theory of change.

In practical terms, the sphere of control includes actions and outputs that can be produced directly by the researcher or research team. This includes actions and outputs produced by collaborators as part of their commitments to a program. If an actor must be persuaded through the provision of knowledge, tools, or advocacy, this change occurs in the sphere of influence. The concept of the sphere of influence attempts to capture the idea that change happens when the KASR of other actors (i.e., not part of the research team) change. These kinds of changes are classified as outcomes of the research if they result in whole or, more likely, in part from the research process and/or output(s). If there are co-produced outputs, it implies that the research process has resulted in KASR and behavior in other actors that would not have happened in the absence of the research, and this change is an outcome. Individually or collectively, changes in behavior that result in part or in whole from the research can lead to realized benefits.

The research program itself is represented in Fig. 1 as a stylized sequence of activities, from top to bottom, within the sphere of control. Activities include developing partnerships with other researchers and/or societal actors and (co-)defining the problem the research will address and the specific questions it seeks to answer. The research then may apply established methods and/or develop new methods to collect and analyze data and (co)create new knowledge and innovations. This list is indicative; not all steps may be present and\or they may occur in different sequence, iteratively, and with or without external actors being involved.

The program’s interactions with and influence in society is represented horizontally, from the sphere of control (program implementation), through the sphere of influence (other actors informed and influenced by research outputs), to the sphere of interest (the tangible benefits to which the research may contribute). The figure tries to represent the dynamic interactions in a complex system. The downward arrows in the sphere of control indicate that each step in the research process contributes to other actions in the research process.

In traditional academic research, the primary aim has been to create new knowledge, search for meaning, and improve understanding. However, research can contribute to outcomes and realized benefits in many ways. Moving from the left to right in the diagram (as indicated by the rightward arrows), each of the individual steps in the research process can produce outputs that contribute independently as well as in combination. For example, the process of developing a partnership may build relationships among stakeholders that have value beyond the program; the research question and/or new methods could stimulate attention and additional research on an important topic; open data policies are increasing the likelihood that data sets will be made available for other uses beyond a program. Each of the steps can contribute to changes in KASR and changes in behavior (B) by other actors. The research process may also be informed and influenced by societal engagement, as represented by the leftward arrows moving from partners, stakeholders, and society back to the program.

The rightward arrow to the second step within the sphere of influence illustrates how changes in KASRB (outcomes) among partners, stakeholders, and society more generally can lead to changes in policy and practice (outcomes) and higher-level system transformations (outcomes), that ultimately lead to changes in social, economic, or environmental condition (realized benefits) in the sphere of interest. This highlights the important role of collaborations and partnerships in co-creating and advancing the use the research-based knowledge and reflects an important rationale for increased use of engaged transdisciplinary research approaches. The circular arrow at the bottom of the diagram represents ongoing stakeholder engagement throughout all stages.

Finally, the figure indicates that the focus of monitoring, evaluation, and learning (MEL) is different at each stage in the impact pathway. Within the sphere of control, the focus is on research quality, broadly defined to include considerations of relevance, credibility, legitimacy, and how research is positioned for use (Belcher et al., 2016 ; Ofir et al., 2016 ). Is the research focus, design, and implementation appropriate and sound? Within the sphere of influence, research evaluation needs to focus on whether and how research has contributed to outcomes. Is there evidence that the research has stimulated or contributed to changes in KASRB, and is it reasonable to expect further knock-on changes? In the sphere of interest, the focus is on the scale and scope of realized benefits and analysis of the relative contribution of research.

It is important to emphasize that this is a classification, not a hierarchy of value. It is intended to support research evaluation by distinguishing the kinds of changes that research can enable, catalyze, and contribute to. In order to assess what difference research makes, we need to know what kind of change we are looking for. Change happens in complex systems and, as illustrated in Fig. 1 , most change happens outside the control of a research program. The kind and degree of change to which any research program contributes and the timeframe over which that change happens will depend on many other factors, including the nature of the issue, the current state of knowledge, and the political climate. In some domains of research (e.g., many Engineering and Applied Sciences), external stakeholders often have close linkages with researchers, such that the pathway through the spheres of influence and interest to realized benefits can be relatively direct and rapid. In Health research, the interface of researchers with individuals with lived experience of a disease provides engagement and learning, and enables more effective translation of research outputs to practice and realized benefits of the affected communities. The outputs of scholarship in Social Sciences and the Humanities may profoundly influence understanding, appreciation, values, and indeed the actions of individuals, organizations, or society more generally (i.e., outcomes). These kinds of changes are often difficult to observe, difficult to measure, and difficult to attribute, and occur over long timeframes, but have value in and of themselves. They may also contribute to realized benefits, but in most cases the attribution challenges are insurmountable because there are so many other causal factors. This classification aims to help focus research evaluation appropriately and enhance appreciation of contributions that scholarship makes to change in more diffuse ways. In any research evaluation, we need to look at outcomes as the primary indicator of research effectiveness.

There has been a great deal of discussion in the literature about research impact, how to define it, and how to measure it, but current definitions and usage remain vague and ambiguous. This essay combines two main ideas to help achieve conceptual clarity. First, we explicitly recognize that research contributes to change within systems as sequential causal processes (with feedback and iteration), in combination with other processes and other actors. We have provided a generic model of a research-to-impact process that: illustrates the declining relative influence of an intervention in a system, shown as spheres of control, influence, and interest; indicates typical actions within a research process; appreciates that individual actions in the research process may make valuable contributions independently as well as in combination, especially in engaged co-produced research; and identifies that the focus of monitoring, evaluation, and learning is different at each stage in the process. Second, we propose that it is practical and useful to classify research results into different kinds. Outputs are the products and services produced directly by research. Outcomes are the changes in KASR experienced by other actors who have been influenced by the outputs of research. Those changes in KASR may also contribute to changes in behavior and, thereby, to subsequent outcomes. Realized benefits are tangible changes in the social, economic, environmental, or other physical conditions. In this framing, research impact includes both outcomes and realized benefits. This classification aims to help focus research evaluation appropriately and enhance appreciation of the multiple pathways and mechanisms by which scholarship contributes to change.

Change in behavior is understood broadly. It is any action that would not otherwise have taken place. It could be something as simple as one person telling another what they have learned, to transformative changes in individual, organizational, institutional, or societal policies or practices. We are asking “Who does what differently as a result of the research?”

Change is assessed against a (hypothetical) counterfactual; i.e., what would have happened in the absence of the intervention. Thus, the change may be a decision to maintain the status quo or to avoid implementing a program.

In some types of research, such as participatory action research, benefits may be realized by participants.

We use the term “program” to refer to a body of research work done by an individual researcher or a team of researchers. The discussion could equally refer to a “project”.

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Acknowledgements

For their sponsorship of a 2019 workshop by the Federation for the Humanities and Social Sciences and CASRAI, as well as their valuable comments and feedback at various stages in the development of this article, the authors would like to acknowledge Suzanne Board, Laura Beaupre, Yolande Chan, Kyle Demes, Heather Frost, Laura Hillier, Sandra Lapointe, Sharon Murphy, Nilgun Onder, Emile Paquin, David Phipps, Sally Rutherford, Lisa Shapiro, Karine Souffez, Louise Michelle Verrier, and David Watt. We are also indebted to Anna Hatch for her insightful comments on an earlier draft of this article. Brian Belcher’s work on this has been supported by the Canada Research Chairs Programme, the Social Sciences and Humanities Research Council (SSHRC), Ashoka Canada, and the Forests, Trees and Agroforestry Consortium Research Program.

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Belcher, B., Halliwell, J. Conceptualizing the elements of research impact: towards semantic standards. Humanit Soc Sci Commun 8 , 183 (2021). https://doi.org/10.1057/s41599-021-00854-2

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An annotated and critical glossary of the terminology of inclusion in healthcare and health research

Shahid islam.

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The importance of including members of the public has been accorded a significant position in health planning, service delivery and research. But this position masks a lack of clarity about terms that are used. This paper identifies terms that are in common use in the lexicon of community based involvement and engagement in health with the intention of clarifying meaning and thus reducing ambiguity. We define and distinguish between key terms related to inclusion, we consider the terminology attached to community processes and to the challenges of inclusion and we engage with the strengths and weaknesses of the commonly used metaphor of “a ladder of participation”. We wish to contribute to the clear communication of intentions, challenges and achievements in pursuing varied forms of inclusion in health.

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Interest in members of the public taking part in health research and service design has grown in recent decades. With this growth in interest there has been an increase in the number of terms used to describe how people can play an active role. For members of the public, researchers and practitioners there is a need to be able to understand what these terms mean and how one is different from another. It is not uncommon to find the same word used in different ways. For example, engagement, involvement and participation are sometimes used interchangeably. We argue that terms such as these have specific meanings. In this article we define key terms, highlight when there is a conflict in the ways different people and organisations have used them and offer a brief commentary on where such terms originate. In doing this our intention is to bring clarity to the words and ideas that appear in policies, research papers and conversations about including members of the public in health care and health research.

In recent decades we have witnessed a change in the role members of the public play in healthcare service delivery and research. At least rhetorically they have moved from being considered ‘passive recipients’, where they had minimal influence over services or research processes, towards a world where they are encouraged to be ‘active citizens’, where strap lines such as ‘nothing about us without us’ [ 1 ] and ‘big society’ [ 2 ] frequently appear in policy documents across a range of disciplines. The evidence for this change can be gauged from proxy measures including the number of papers published on patient and public involvement as they have increased ten-fold in the first 10 years of this century [ 3 ], and the number of grant funding bodies which have now mandated all applicants to demonstrate how they will include patients and members of the public in their research plans [ 4 ]. Patient and public involvement is now an embedded part of the health research eco-system, although the degree to which it is effectively pursued varies [ 3 ]. There are numerous rewards to be reaped through pursuing and implementing community inclusive approaches and these have been documented in a number of systematic reviews (see for example [ 5 – 7 ]. The motivations to pursue community inclusive approaches vary in their detail but a summary from Public Health England captures a commonly shared position:

Communities, both place-based and where people share a common identity or affinity, have a vital contribution to make to improve health and wellbeing. Community life, social connections, supportive relationships and having a voice in local decisions are all factors that underpin good health [ 8 ](p.4).

Given the increasingly positive zeitgeist for community inclusive approaches, and with a growing evidence base to support their impact on health and wellbeing [ 9 ], it is timely to note that participatory approaches have their origins in two very distinct agendas. The first is as an adjunct to the introduction of market principles into health policy, in the UK exemplified by “The Patients Charter” (1991) [ 10 ]. This agenda sought to promote the rights of patients as consumers – rights lodged in the belief that they should have “voice” and “choice” in relation to the health care they receive. This is an agenda that is based on an inherent individualism in making consumption choices, that is we make these choices for ourselves. The second agenda was to enhance inclusivity, in the UK the “Local Voices” initiative of 1992 is an example [ 11 ]. This agenda has been linked to a communitarian philosophy [ 2 ] which assumes – or at least hopes – that stronger, more civic-minded communities can contribute to making life better for local people whether the focus is on health, social care, the ageing population or people’s happiness and quality of life [ 2 ]. Etzioni’s [ 12 ] work, which is associated with this philosophy, similarly argued for policy choices that emphasised social solidarity in pursuit of the common good. Not surprisingly, given their different starting points, these distinct agendas do not always sit comfortably together, something Beresford [ 13 ] critically discusses, although he uses the slightly different terminology of ‘consumerist’ and ‘democratic approaches’.

Contrasting the different agendas in market based and communitarian approaches also underlines a danger in too simply conflating patient and public. These two constituencies for involvement are likely to have different priorities, for example the importance given to the provision of treatment against the allocation of resources to prevention.

However, despite these different motives and starting points, there is no doubt that public and user involvement is an approach that now occupies a position of discursive privilege; it is present in a plethora of policies [ 14 ], standards [ 15 ], guidelines [ 16 ], institutional protocols [ 17 ] and publications [ 9 , 18 ] and its impact on practice has been described in a recent systematic review as “ central to the reform of Western economies” [ 6 ] (p.2).

As the commitment to participatory approaches has grown, so too has the call for robust definitions which outline and differentiate processes that fall under this rubric. This is crucial given the World Health Organisation's (WHO) observation that, “the quantity of terms and the lack of precision with which they are employed can cause confusion” [ 19 ] (p.10). We offer a glossary of and critical commentary on salient terms found in discussions relating to inclusion of communities in health service planning, delivery and research. These terms include, amongst others, those that are ubiquitous in the discourse and literature including community development, empowerment, involvement, co-production and social exclusion.

The terminology of inclusion

The term ‘Community’ has been used to describe the bonds, identities, relationships and interests that join people together or give them a shared stake in a place, service, culture or activity [ 20 ]. It is a term that is seen to invoke a more significant relationship than that of, “the more formal, more abstract and more instrumental relationship of state, or of society” [ 21 ] (p.76) [ 22 ]. It has been linked with terms like “interests” or “politics” in a way that reinforces its use as a “warmly persuasive word to describe an existing set of relationships”, or to encapsulate an aspired for “alternative set of relationships” [ 21 ] (p.76). According to guidance from the UK’s National Institute for Health and Care Excellence (NICE), the range and scope of the word allows communities to be defined by: “geographical location, race, ethnicity, age, occupation, a shared interest or affinity (such as religion and faith) or other common bonds, such as health need or disadvantage” [ 23 ](p.6). A research study by MacQueen et al. [ 24 ] recruited an impressively diverse sample of respondents to try and answer the question “what does community mean to you” (p1929) and found consensus forming around the following description: “a group of people with diverse characteristics who are linked by social ties, share common perspectives, and engage in joint action in geographical locations or settings” (p1929).

Engagement, involvement and participation

There are important differences between engagement, involvement, and participation but these terms are often used interchangeably. This is noted by the WHO; “Although it is not surprising that different people understand the term community participation very differently, this diversity of understandings can cause difficulty (and) can sometimes imply that the meaning of community participation is self-evident” [ 19 ] (p.10). Marjanovic et al. [ 25 ] highlight that the distinction between key terms is particularly blurred in the fields of applied research and health services research, and as a consequence, “many systematic reviews of PPI (Patient and Public Involvement) activities note the challenges they faced finding relevant literature, in part because PPI lacks standard terminology” (p1).

Community engagement is defined as “a process of working collaboratively with groups of people who are affiliated by geographic proximity, special interests, or similar situations, with respect to issues affecting their well-being” [ 18 ](p.1). A similar definition is reached when this issue is explored by a Scientific Consortium as they describe community engagement as “the process of working collaboratively with and through groups of people affiliated by geographic proximity, special interest, or similar situations to address issues affecting the well-being of those people” [ 26 ] (p.3). There is nothing in either of these definitions which shows how much collaboration is required to warrant this being considered engagement. Moreover, it is not clear what defining characteristic sets engagement apart from involvement and participation. This perplexity was noted by INVOLVE, a UK government funded group which was established over 20 years ago to actively support input by members of the public in health and social care research. It is worth quoting how INVOLVE make efforts to resolve this problem:

“INVOLVE Advisory Group members met for a two-day symposium ( …) and one of the many discussions we had was about the confusion language can create, for example what we mean when we use the terms ‘public’ ‘involvement’, ‘engagement’ and ‘participation’ in research and how others may have a different understanding for the same words. This was also raised in our recent webinar on public involvement in social care research” [ 27 ].

These efforts produced a definition and examples on what constitutes engagement. As INVOLVE describe it, engagement is:

(W) here information and knowledge about research is provided and disseminated. Examples of engagement are:

• science festivals open to the public with debates and discussions on research
• open day at a research centre where members of the public are invited to find out about research
• raising awareness of research through media such as television programmes, newspapers and social media
• dissemination to research participants, colleagues or members of the public on the findings of a study [ 27 ].

In this way communities may be considered engaged when they are informed about a specific initiative, say, through attendance at an event or through social media without the community necessarily reciprocating or having to take an active role in the process.. Thus a defining characteristic of engagement is minimal input by the target group and no/low expectation of any reciprocity within the processes employed.

Community involvement . The term involvement “implies being included as a necessary part of something” [ 19 ](p.10). INVOLVE, defines involvement as being where people are actively involved in research projects and in research organisations [ 27 ]. The same criteria applies when considering involvement in service design and delivery. The essential difference between engagement and involvement, from the definition provided by INVOLVE [ 27 ], means that the former does not require members of the community to play an active role whereas with involvement it is a prerequisite.

Community participation is defined by the WHO as “a process by which people are enabled to become actively and genuinely involved in defining the issues of concern to them, in making decisions about factors that affect their lives, in formulating and implementing policies, in planning, developing and delivering services and in taking action to achieve change” [ 19 ](p.10). As such, participation requires involvement but involvement, by itself, is not enough to qualify as participation.

A different meaning is reached by INVOLVE [ 27 ] as they identify participation as being where people take part in a research study. But this use of “participation” narrows it to a scenario where members of the public are essentially subjects of research. Their influence over study design or delivery may be negligible. This ambiguity in how to define participation seems to exemplify that distinction we introduced earlier between a consumerist and a communitarian understanding, with, in this case, INVOLVE representing the former and the WHO the latter.

More generally it is clear that classification is fraught with difficulties. It is common to find research documentation (e.g. ethics application forms and grant applications) describing participation as involvement, or talking of activities in the section dedicated to Patient and Public Involvement in which people who simply participate in a study are described as being involved. The National Institute for Health Research has taken steps to ameliorate this confusion by offering the following advice in their guidance to people applying for their grants:

The term involvement refers to an active partnership between patients, members of the public and researchers in the research process. This can include, for example, involvement in the choice of research topics, assisting in the design, advising on the research project or in carrying out the research. In this section it is important that you describe in as much detail as possible how patients and the public have been involved in the development of the application as well as plans for involvement in the proposed research(...) Please note that this section does not refer to the recruitment of patients or members of the public as participants in the research [ 28 ](p.7)

Community development and empowerment

Community development and community empowerment are sometimes conflated which is why a review by Campbell et al. [ 29 ] found a “great deal of confusion and contention in the literature”(p.67).

The inherent difficulty with defining community development was noted by Biddle in 1966 in his paper titled ‘the fuzziness of definition of community development’ [ 30 ]. The problem, as Biddle puts it, is: “(t) wo enthusiasts for Community Development, in conversation, will often discover that they are talking about quite different experiences, even though they both lay claim to the admired title” [ 30 ] (p.5). Biddle’s paper discusses the varying ways in which this term has been applied and then reaches a working definition: “Community Development is a social process by which human beings can become more competent to live with and gain some control over local aspects of a frustrating and changing world” [ 30 ](p.12).

To fully appreciate community development it is crucial to understand both its functionality and it’s ethos. Ledwith [ 31 ] notes “community development is rooted in a vision of a more fair and just world” (p.5) which is why it is considered a value based process which aims to redress imbalances in power and seeks to bring change founded on social justice, equality and inclusion [ 32 ] Operationally, community members identify issues and determine joint actions with institutions or professionals to build healthy, sustainable and equitable communities [ 8 ]. This may be achieved, for example, by influencing budgets, strategies and policies that could achieve community level improvements.

Community empowerment differs from development in that when it is in place joint actions with institutions and professionals will not be necessary as power to make such decisions will ipso facto already belong to the community. Community empowerment can be described as, “the ‘ultimate’ form of engagement, as it requires the ceding of power and control to communities who have traditionally been denied such privileges” [ 9 ] ( p.46). Whilst this may be presented as desirable, it can prove burdensome and challenging for many communities. It requires a level of self-sufficiency and adequate governance that may be difficult to achieve or sustain, particularly when the empowered community does not have the support of an established institutional structure.

Metaphors of “participation”

We have argued that the difference between consumerist and communitarian (or, as Beresford argues consumerist and democratic [ 12 ]) approaches to participation creates challenges for practitioners in identifying the correct nomenclature to best communicate their intentions and actions. This, in turn, creates problems for research funders. But as well as the terminology difficulties we have discussed above, there may be some confusion that stems from a metaphor that has characterised the field of inclusion. That metaphor is the ladder, the most widely recognised is Arnstein’s ladder of participation [ 33 ] which was first published in 1969. Others followed Arnsteins lead and also used the ladder metaphor. Wilcox’s ladder of participation [ 34 ] and Hart’s ladder of participation [ 35 ] are two such examples (see Fig.  1 ). A ladder conveniently illustrates the steps that can be taken to graduate from low levels of input through to high levels of influence and control. Activities which fit higher rungs of the various participation ladders such as ‘deciding together’, ‘shared decisions’ and ‘partnership’ may fit within the WHO definition of participation but they also demonstrate “higher” degrees of influence consistent with what we have categorised as co-production,community development and empowerment which we have shown are distinctly different to participation. The metaphor of the ladder is useful in illustrating the climb from lower to higher forms of inclusion but describing them all as “ladders of participation” risks compromising conceptual precision and, in so doing, adds to a serious communication gap in the field.

Ladders of participation

It is not only the terminology of inclusion that is complex there are also challenges in arriving at a clear and shared understanding of community processes, characteristics and challenges .

A wider glossary of the contribution of “community” in health

Community processes.

Co-production, as a concept, emerged in the 1970’s during a study by Ostrom into the Chicago Police forces’ ambitions to improve social outcomes through working ‘with’ residents rather than ‘for’ them [ 36 ]. Ostrom was searching for a term which could encapsulate the “process through which inputs used to produce a good or service are contributed by individuals who are not ‘in’ the same organisation” [ 36 ] (p13). Significant hopes and aspirations are placed on this idea as one report states; “co-production looks set to create the most important revolution in public services since the Beveridge Report in 1942” [ 36 ](p.3).

A more recent definition, which has expanded the one offered above, describes co-production to mean “delivering public services in an equal and reciprocal relationship between professionals, people using services, their families and their neighbours. Where activities are co-produced in this way, both services and neighbourhoods become far more effective agents of change.” [ 37 ](p.9). Key words here are ‘equal’, ‘reciprocal’ and ‘agents of change’ which are necessary cogs of the machinery that comprise co-production; and, whilst the concept may appear straightforward to define, it has generated uncertainty and heated debate as one blogger for the Kings Fund testifies: “I regularly have to challenge very senior people and we often get stuck at some point during the process (of reaching agreement on meaning). This usually revolves around denial of one consistent and very inconvenient truth: patient involvement is not co-production” [ 38 ]. Perhaps what makes co-production particularly distinctive is the egalitarian value and philosophical underpinning it is deeply rooted in. The emphasis given to ‘equality’, ‘reciprocity’ and how people must be ‘agents of change’ means that if the above ladders were used to gauge level and depth of inclusivity then co-production would occupy a place amongst the higher rungs.

Participatory Research (PR) is an umbrella term that embraces a number of methodological approaches. A fundamental premise of PR is a recognition that marginalised groups are able to construct knowledge in meaningful ways, and that such knowledge is both valuable and significant [ 39 ]. The methodologies that fall under PR are unified by collective endeavour formulated through negotiation taking place between the researcher(s), the communities and the participants. The approaches include community based participatory research [ 18 ], participatory action research [ 40 ], cooperative inquiry [ 41 ], appreciative inquiry [ 42 ] and citizen science [ 43 ] . There are numerous examples of PR available in the literature. One example is where service users, health care providers and academics pursued participatory action research on a joint basis from conception of the idea through to dissemination of findings on the topic of how travel affects mental health in-patients when admitted to a hospital [ 44 ]. An important point noted in this study is the value gained through employing service users as researchers. This was considered to have achieved a two-fold benefit; one, service users as researchers were able to personally relate to and empathise with the experience they heard during interviews; and secondly, being interviewed by service users made it easier for respondents to discuss their experiences.

Community characteristics

Community Capital. The physical and financial resources of a community are considered components of capital and there are powerful recommendations for pressing such capital into service. Community capital can be “drawn upon to generate great social value” [ 2 ](p.4) which, in turn, can energise communities into taking positive steps for health improvement. The origins of the term community capital can be traced to the theory of social capital which, according to Robert Putnam, posits that communities contain reserves that bind people together into trusted relationships through organisations and institutions where people come together to meet and socialise [ 20 ]. Building trusted relationships, from Putnam’s perspective, gives rise to a greater inclination amongst members to do things for one another. Robert Bordieu’s theory of social capital [ 45 ] takes a different position, emphasising the power of networking, building bridges with people and institutions with the purpose of gaining ‘ a credential’. Bourdieu goes on to say: “The volume of the social capital possessed by a given agent thus depends on the size of the network of connections he can effectively mobilize and on the volume of the capital (economic, cultural and symbolic) possessed in his own right by each of those to whom he is connected” (sic) [ 45 ] (p.249). Community capital incorporates both of these principles and is defined by Parsfield et al. [ 2 ] in the following way: “(W) e use it to describe the sum of Putnam’s social reserves and Bourdieu’s instrumental advantage; it is the net of social assets and resources which, if managed through the socially productive means of supporting greater social connectivity, generates benefits for the members of a community. Like any capital, it consists of a stock of valuable goods (in this case, significantly, relationships), it can be accessed by people (the members of the community in which the relationships exist) and it can be used in the production of other goods or advantages” [ 2 ] (p.21).

One practical example of community capital at work can be found in the Asset Based Community Development (ABCD) approach pioneered by Kretzmann and McKnight [ 42 ] (see Table  1 ).

Asset Based Community Development (ABCD)

Community Readiness “ is the degree to which a community is prepared to take action on an issue” [ 48 ] (p.3). Launching any new programme requires alignment between implementation efforts and the level of readiness in a community to take part in the planned programme if it is to be successful. When these variables work in harmony the possibility of acceptance and uptake by the target community increases [ 49 ]. The community readiness model (CRM), developed by researchers from the Tri-ethnic Centre in Colorado USA, was originally designed to test acceptance of a drug and alcohol prevention programme and has since developed into a toolkit [ 48 ] which has been applied to a broad range of topics across the globe including obesity in the UK [ 50 ], domestic violence in South Korea [ 51 ] and HIV prevention in Bangladesh [ 52 ]. In the original paper describing CRM, the authors highlight their concern about improper use of the terminology when they say: “Community readiness is a term that is being used more and more by various authors and in many contexts. Although different terms and descriptions can be used to describe the stages of readiness and the dimensions of readiness, it should be noted that the specific terms and descriptions have been thoroughly tested. If other names or descriptors are used, it should be incumbent on those using such terms to provide data showing that they have been subjected to an equivalent process” [ 49 ] (p.298).

Community Wellbeing . If communities possess anthropomorphic characteristics such as owning capital and showing a state of readiness to address issues then, in much the same way, it might be possible to identify a community’s level of wellbeing. There are a wide variety of definitions in use to describe community wellbeing. South et al. [ 53 ] state that, “community wellbeing is a complex concept, with no agreed definition(s) and many related concepts”(p.4). For example in one paper community wellbeing is described as being “about strong networks of relationships and support between people in a community” [ 53 ] (p.4) whereas another study defines community wellbeing “as the satisfaction with the local place of residence taking into account the attachment to it, the social and physical environment, and the services and facilities” [ 54 ] (p734). Despite these differences, the common unifying point is the importance of measuring determinants of health and social wellbeing at a community level. There are now several toolkits that do this (see South et al) [ 53 ].

Social Exclusion. The terms poverty and social exclusion are often found together as there are some important overlaps between them. Most commentaries describe relative poverty as a lack of resources which then manifest in, “the absence or inadequacy of those diets, amenities, standards, services and activities which are common or customary in society” [ 55 ] (p649). Social exclusion , however, is a broader concept encompassing not only low material means but the inability to participate effectively in economic, social, political and cultural life which then leads to alienation and distancing from mainstream society [ 56 ] . Social exclusion can lead to the exacerbation of health inequalities, for example if groups who are privileged and have easy access to services make use of what is available, whilst those who are marginalised and disenfranchised remain absent. Equally, research samples which do not adequately consider and redress social exclusion run the risk of recruiting an unrepresentative and/or biased sample.

Hidden Populations is a term which appears in the context of recruitment to programmes or sampling for research purposes. It refers to disadvantaged and disenfranchised groups that are difficult for researchers or service providers to access in a cost-efficient way, in large enough numbers, to meet the needs of the study or the service provision [ 57 , 58 ]. There are many reasons for populations becoming hidden for example some groups of people such as drug users, illegal migrants, sex workers or ex-offenders may not wish to make themselves known to services; while other groups may have no intention to hide but find the same outcome for different reasons. For example, older people with minimal social contact, homeless people or young people excluded from school find that they are hidden from the view of providers for reasons related to the more general phenomenon of social exclusion.

Hard to Reach refers to community groups that are difficult to involve, engage or achieve adequate levels of participation in research or health delivery programmes. This is a contentious term as populations are described in ways that could suggest apathy and lead to stigma, especially since it is usually applied to describe those communities that are ‘under-served’, characteristically minority groups, those ‘slipping through the net’, and the ‘service resistant’ [ 59 ]. It is a term that “implies the problem as one within the group itself, instead of those trying to reach them” [ 58 ] (p.1). Critics have argued that no-one is hard to reach and the reality is more imaginative methods and more resources may be necessary in reaching groups who do not avail themselves of services offered. A one-size-fits-all approach to engagement which does not take account of impediments arising from social exclusion is both the cause and consequence of groups becoming hard to reach.

Concluding remarks

Terms appearing in this paper were selected on the basis of their frequent appearance in contemporary debates and policy guidance when describing initiatives which involve working with communities to improve health and wellbeing or to research these areas. When planning this paper we were faced with a lengthy list of concepts to choose from and decided to narrow this down to those terms which we have experienced to be ambiguous and those that risk meaning different things to different people within the lexicon of inclusive approaches. Collectively the terms underline the contradictions and complexity of this area. We began by suggesting two agendas, enhancing individuals capacity as consumers of health and pursuing a common good through social solidarity. The former leaves the individual locked into a consumerist ideology. It represents the incorporation of the individual into a prevailing discourse in a way that supports this discourse rather than enhancing their agency. The latter also engages the individual and the community in a prevailing form of governmentality that can appear to be in their interests but can be effectively split off from the mechanisms by which key resource decisions are made. Governmentality here is understood as the way governments try to produce those citizens best suited to fulfil their policies [ 60 ]. The different way the term “participation” has been used illustrates the two agendas and the dangers that an intention to pursue a structural change can shift from a communitarian into an individualist approach.

Researchers and health providers need to keep a critical vigilance about the terms we use. This is important even when the terms relate to superficially desirable “inclusion” and “community” activities. Key to maintaining this vigilance is a critical engagement with language. There is a danger in conflating terms that have a distinct difference. The erosion of this difference adversely impacts on the clear communication of intentions and of challenges and achievements in pursuing the varied forms of inclusion.

Acknowledgements

We are grateful to Better Start Bradford for their funding and support. We are grateful to members of the Community Research Advisory Group (CRAG) of Better Start Bradford. This is a group of local people who advise on research, with a particular remit to focus on its relevance and acceptability. Three members of the CRAG read the manuscript and offered feedback on clarity to help us make this paper useful to a broad range of audiences.

Abbreviations

Authors’ contributions.

Both authors contributed equally in writing this paper. The authors read and approved the final manuscript.

Better Start Bradford has funded the costs associated with preparing this article. Better Start Bradford receives funding from The National Lottery Community Fund. The funder has not influenced the content of the manuscript.

Availability of data and materials

Ethics approval and consent to participate.

Not applicable.

Consent for publication

Competing interests.

The authors declare that they have no competing interests.

Both authors are also members of Born in Bradford, Bradford Institute for Health Research, Bradford Teaching Hospitals Foundation Trust, Temple Bank House, Duckworth Lane, Bradford, BD9 6RJ.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Shahid Islam and Neil Small contributed equally to this work.

Contributor Information

Shahid Islam, Email: ku.ca.drofdarb@21malsis .

Neil Small, Email: [email protected] .

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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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Your Guide to Understanding Common Research Terms

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                              Demystifying Clinical Trials -- Part 2

The clinical research world can sometimes seem confusing. Research teams have many people in different roles, and they may use words that are unfamiliar to people outside of research work.

The guide below defines some commonly used words and phrases. Let us know in the comments below or on our Facebook , Twitter , or Instagram pages if you’d like definitions of other words or parts of the research process!

Accrual – the number of subjects who have completed or are actively in the process of completing a study. The accrual goal is how many subjects are needed to finish the study (2).

Adverse event (AE) – a negative symptom or experience encountered by an subject during the course of a clinical trial. Adverse events can be expected or unexpected.

Assent – a minor child’s affirmative agreement to participate in a clinical trial. Failure to object may not be taken as assent.

Clinical research coordinator – a study team member who manages the day-to-day study tasks as directed by the principal investigator. (3)

Consent form – a document explaining all relevant study information to assist the study subject in understanding the expectations and requirements of participating in the trial. This document is presented to and signed by the study subject.

Control arm/group – a comparison group of study subjects who are not treated with the investigational agent. The subjects in this group have the same disease or condition under study, but receive either a different treatment, no treatment, or a placebo.

Data – the objective information gathered during a research study that is used to determine the results of the study.

De-identification – the process of removing identifiers (personal names, dates, social security numbers, etc.) that directly or indirectly point to a person, and removing those identifiers from the data. De-identification of protected health information is essential for protecting patient privacy (4).

Enroll/Enrollment – the process of an eligible participant signing a consent form and voluntarily agreeing to participate in a research study (2).

Ethics committee – an independent group of both medical and non-medical professionals who are responsible for verifying the integrity of a study and ensuring the safety, integrity, and human rights of the study participants.

Food and Drug Administration (FDA) – the agency within the Department of Health and Human Services (DHHS) that enforces public health laws related to research conduct.

Greater than minimal risk – the research involves more than minimal risk to subjects (2).

Health Insurance Portability and Accountability Act of 1996 (HIPAA) – required the Department of Health & Human Services to develop regulations protecting the privacy and security of certain health information (5). The HIPAA Privacy Rule established the conditions under which health information may be used or disclosed by approved entities for research purposes (6).

Hypothesis – a specific, clear, and testable proposition or prediction about the possible outcome of a scientific research study (7).

Informed consent – the process of discussing a clinical trial that goes beyond signing the consent form. The discussion should provide sufficient information so that a subject can make an informed decision about whether or not to enroll in a study, or continue participation in a study. Informed consent is a voluntary agreement to participate in research, and should be an ongoing conversation throughout a subject’s entire time in the study (8).

Investigational New Drug Application (IND) – the process through which an investigator requests the FDA to allow human testing of a new drug.

Institutional Review Board (IRB) – an independent group of professionals designated to review and approve the clinical protocol, informed consent forms, study advertisements, and patient brochures to ensure that the study is safe for human participation. It is also the IRB’s responsibility to ensure that the study adheres to the FDA’s regulations.

Minimal risk – the probability that harm or discomfort anticipated in the research study are not greater than those encountered in daily life or during routine physical examinations (2).

National Institutes of Health (NIH) – agency within DHHS that provides funding for research, conducts studies, and funds multi-site national studies.

Protected Health Information (PHI) – individually identifiable health information. HIPAA provides federal protections for personal health information and gives patients more control over their health information. It also sets boundaries for how entities and institutions can use and release health records (9).

Placebo – an inactive substance designed to resemble the drug being tested. It is used as a control to rule out any psychological effects testing may present. Most advanced clinical trials include a control group that is unknowingly taking a placebo.

Principal Investigator – the primary individual responsible for conducting a clinical trial and adhering to federal regulations, institutional policies, and IRB regulations (2).

Protocol – a detailed plan that sets out the objectives, study design, and methodology for a clinical trial. A study protocol must be approved by an IRB before research may begin on human subjects.

Randomization – study participants are assigned to groups in such a way that each participant has an equal chance of being assigned to each treatment or control group. Since randomization ensures that no specific criteria are used to assign any patients to a particular group, all the groups will be equally comparable.

Research – systematic investigation designed to develop or contribute to generalizable knowledge.

Standard treatment/Standard of care – the currently accepted treatment or intervention considered to be effective in the treatment of a specific disease or condition.

Statistical significance – the probability that an event or difference was occurred by chance alone. In clinical trials, the level of statistical significance depends on the number or participants studied and the observations made, as well as the magnitude of differences observed.

Subject/Participant – a patient or healthy individual participating in a research study.

Treatment arm/group – a group of study subjects who are treated with the investigational agent.

Visit schedule/Test schedule – the number, frequency, and type of exams, tests, and procedures that research subjects will be expected to undergo during the study. Some visits may be the same as normal clinical care visits, while others may be required just for the purpose of collecting data for the research study.

Definitions taken from https://www.centerwatch.com/health-resources/glossary/ unless otherwise cited.

(2) https://www.mayo.edu/research/institutional-review-board/definition-terms

(3) https://acrpnet.org/2018/08/14/the-anatomy-of-a-great-clinical-research-coordinator/

(4) https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5977668/

(5) https://www.hhs.gov/hipaa/for-professionals/privacy/index.html

(6) https://www.hhs.gov/hipaa/for-professionals/special-topics/research/index.html

(7) https://methods.sagepub.com/Reference//encyclopedia-of-survey-research-methods/n472.xml

(8) https://oprs.usc.edu/files/2017/04/Informed-Consent-Booklet-4.4.13.pdf

(9) https://www.hhs.gov/hipaa/for-individuals/faq/187/what-does-the-hipaa-privacy-rule-do/index.html

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What is the importance of defining terms in research?  

Defining terms in research is important for several reasons. Firstly, it helps to avoid confusion and misinterpretation of concepts and ideas . Different interpretations of words and concepts can arise due to language, culture, and professional differences, so providing clear definitions ensures that the essence of the research is understood . Secondly, defining terms allows for consistency and comparability across studies. By citing existing definitions or referring to collections of definitions, researchers can establish a common understanding within their field . Thirdly, clear definitions help to establish the scope and focus of the research, ensuring that the study addresses the specific topics it intends to investigate . Overall, defining terms in research is essential for clarity, consistency, and ensuring that the research contributes effectively to the body of knowledge in a particular field .

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The Importance of Defining Terms

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by Guest | Oct 1, 2017 | Theology and Christian Apologetics | 0 comments

By Luke Nix

Introduction

A few years ago I listened to the podcast “ The Word Nerds “. This podcast helped me gain an appreciation for the power of the English language. In my conversations with people, I have noticed the power of the words themselves. Using the wrong word can cause needless arguments; using a less specific word can cause confusion, and many other effects (I just checked  Dictionary.com  to make sure I used the right one there) come from using the wrong word.

In righting using the wrong word can cause the affect of people thanking your just dumb. How many times did you have to reread that last sentence before you figured out what I was trying to say? This is probably just more of a lazy-spelling issue, but I had to put it out their.

Defining terms is extremely important in conversations. In normal language, certain words have an accepted definition that is assumed based on the context. If these words did not exist, then you wouldn’t be able to read this post and understand it. However, many words have slightly different meanings to different people. Let’s take the word “period”. I can think of three different definitions right off the top of my head. Most of us can figure that one out pretty quickly.

Words in Debates

Now, let’s take the word “science”. How many definitions for this are you aware of? I pick this one because I was at a debate between William Dembski and Michael Ruse in 2009. The topic was “Is Intelligent Design Science?” I was quite perturbed to see that they were each defining “Intelligent Design” the same, but they were  not  defining “Science” the same. In order for such a debate to have been fruitful, all the terms in the question up for debate needed to be agreed upon. For example, using his own definition of “science”, Michael Ruse made a compelling case that could not be refuted- as long as William Dembski accepted Ruse’s definition; however, since Dembski did not accept Ruse’s definition, and instead used his own then Ruse’s position could easily be undermined. The same happend when Dembski used  his  definition of “science” and Ruse refuted him.

Let us examine a more recent debate:  William Lane Craig vs. Sam Harris . One of the words that was not clearly defined and accepted by both participants was “objective”. Sam Harris clarified that he was only arguing for a “universal” morality (one that only exists as long as conscious minds exist- he’s referring to humans), while Craig was arguing for morality that exists regardless of whether or not conscious minds exist- he’s also referring to humans. The fact that they were each using different definitions of “objective” caused much confusion for those who did not pick up on the distinction or its significance for the debate (even though Craig pointed out both in his first rebuttal).

Since the purpose of debates is to convince based upon agreed upon information, neither debate accomplish what they had the potential to accomplish. The definitions of “science” (in the first example) and “objective” in the second needed to be debated and agreed upon before any questions containing the words could be debated.

This is quite important when one is discussing religious, political, and other worldview ideas with someone who is opposed. Words that some people take to be universally defined across all wordviews are in for a huge surprise. Many words are not. “God” means one thing to the Christian and means another to the Buddhist or Muslim (Craig mentioned this also in his debate with Harris, but the point was ignored). “Empirical” means one thing to the scientist and means another to the historian.

The Power of Words

Speech is one of the communication methods that God has endowed strictly upon the human race. Speech is performed through many languages which all have numerous words (English alone claims nearly one million words). The power of speech lies in its ability to portray the unseen and the unmeasurable, along with the seen and measurable. It is used to communicate our thoughts, visions, and emotions to other humans. Each word corresponds to something and everything has a corresponding word (for the most part). However, the relationship of words to “things” is not one-to-one. One word may have several definitions (take the word “set” in English;  according to Dictionary.com  it has 119 definitions), and one definition may correspond to several words (synonyms).

However, the real power of words comes not in just the basic definitions, but in:

• The  contexts  that they alone are used- such as “annihilate” vs “demolish”, synonyms of one another, but not usually used interchangeably. “Demolish” tends to refer to the destruction of a building, and “annihilation” tends to refer to the destruction of a foe or enemy (in philosophy and theology it has an even stronger implication of the cessation of existence).
• The level of  emotion – “dislike” vs “hate”, synonyms of one another, but “hate” is stronger than “dislike”3. The  precision  of the description- “break” vs “shatter”, synonyms of one another, but “shatter” paints a more accurate picture of how an object disassembled than “break”
• The level of  power – “mean” vs “ruthless”, synonyms of one another, but “ruthless” is stronger than “mean”
• Intentionality – “push” vs “shove”, synonyms of one another, but “shove” indicates a mischievous “push”6.  Size – “hill” vs “mountain”, synonyms, but mountains are larger than hills and on, and on…

Precision of Communication

When precisely defined words are cleverly combined into phrases, sentences, and paragraphs, they can communicate something so vividly, that reader or listener will have a precise understanding in their mind of the concept that was in the mind of the communicator.

Speech has been given to humans to communicate with each other. Different studies have been conducted that have concluded that talking with someone about thoughts in the mind help that person emotionally- which can lead to a more healthy and productive life. With the words of our language, we can precisely describe to people what is on our minds, and they can understand it. The larger vocabulary one utilizes, the more precisely they can describe their inner-most feelings.

There are many books on communication, and how intimately it is related to one’s relationships with friends, family, co-workers, etc. Precise and honest communication allows for fewer “unknowns” between the speaker and the listener. As the level of “unknowns” decreases, the personal connection between the two becomes stronger. Strong communication leads to strong and trusting relationships.

Many of you already are aware that many times a word may not exist in your vocabulary (or even in the language) that describes precisely what you want to communicate. We are all aware of adjectives and adverbs- those little words that describe (or add precision) other words. As the words mentioned above, adjectives and adverbs have many levels and nuances that will assist us in our description of a specific word (and thus, our thought).

Of course, overuse of these can be really, really, really, really bad and do more to confuse the listener (or reader). That last sentence is almost painful to hear (or read). As you have already figured out, “devastating” could easily replace “really, really, really, really, bad”. Depending on my intended meaning of “bad” I could also have used “frustrating” or “confusing”. Notice, though, that each of those words have their own nuances. One may be chosen over the other, depending on the context.

Other times, thoughts exist that can’t be quickly communicated with a word and some descriptors. We have to futher qualify them with complete sentences. When this is necessary, don’t take the easy way out by ignoring it, just do it. Most questions that someone asks about your point of view will be a “clarifying” question. This is a good time to use these descriptive words to further clarify what you are attempting to communicate.

More Clarification Is Sometimes Necessary

The more precisely we can communicate our thoughts, the more likely we will be to have our point of view understood. Now, “understood” is not synonymous with “accepted” (notice that I specifically stated what “understood” does  not  mean).

I recently came across a very good example of this advice being taken. A couple years ago, I was working my way through the book “ Thrilled to Death ” by Archibald Hart. Hart uses the term “anhedonia” a lot because that is the primary topic of the book. At the beginning of the book Hart clearly defines “anhedonia”. He starts by making it clear that there is a “clinical” definition, but he is not using it in that strict sense. He then goes on to describe what exactly he means. This was provided as an answer to his peers who would notice immediately if he were using the word incorrectly. By providing an exact definition of his term, Hart avoided much confusion and possible dismissal of his ideas. In both debates referred to above, if such a courtesy were provided by both parties (it can’t just be one-sided), confusion could have been avoided. Instead, both proceeded with different definitions of their respective words, and debates that were already difficult to follow for some people just increased in difficulty level.

A while back I read the book “ No Free Lunch ” by William Dembski (chapter 4.9). In it he provided a critique of one of his views from a peer. He went through the critique and responded. (I checked for the other scholar’s further responses and found them  here  if you are curious). I was quite annoyed by this exchange. The glaring fact that both of them were trying to more specifically define their terms, while the other person complained that they were doing such a thing was unmistakable! We can’t expect to be able to specifically define our terms yet not allow someone else to do the same, and on the flip-side, we can’t demand that the other specifically define their terms while we do not reciprocate said demand.

Another example of this is in the scientific community of biologists. “Evolution” is a broad term. Some want it split into two different terms: “microevolution” and “macro-evolution”. Each one clearly defines a level of evolution in the biological realm. I think that this is quite useful because the separate terms allow scholars (and laymen) to know exactly which type the other is discussing and can engage with less ambiguity. I addressed this issue in more detail  here . Sometimes it is necessary to create new words to communicate a newly discovered distinction.

To finally conclude this, words have objective meanings. The fact that they have multiple possible meanings indicates that defining terms is extremely important if we wish for our conversations and debates to be productive. If this is not allowed, then the risk of holding a “ strawman ” understanding of the other person’s view is increased. When “strawmen” are believed, frustration abounds for both sides. In the future, when someone asks us to clarify our terms, we should patiently oblige them. Most of the time, they are not trying to be devious, they are simply trying to understand. They also ask with the expectation that we are not being devious. We must not abuse language to the point of demanding a different term in the absence of a distinction in definitions, but on the other extreme, we must not demand the same term in the presence of a distinction in definitions.

Over the last several years, I have written many other posts on the importance of clear communication to help keep worldview discussions and debates productive. Here are some of the recommended ones:

Related Posts:

Is Theism Well-Defined Enough to be Scientifically Testable?

Atheism: A Lack of Belief in God

What Is Faith?

Is Faith Emotional or Logical?

Philosophy of Science, Circumstantial Evidence, and Creation

Deconstructionism, The Constitution, and Biblical Interpretation

The Difference Between What A View Asserts and Implies

Original Blog Source: http://bit.ly/2hB3RpP

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6 Common Leadership Styles — and How to Decide Which to Use When

• Rebecca Knight

Being a great leader means recognizing that different circumstances call for different approaches.

Research suggests that the most effective leaders adapt their style to different circumstances — be it a change in setting, a shift in organizational dynamics, or a turn in the business cycle. But what if you feel like you’re not equipped to take on a new and different leadership style — let alone more than one? In this article, the author outlines the six leadership styles Daniel Goleman first introduced in his 2000 HBR article, “Leadership That Gets Results,” and explains when to use each one. The good news is that personality is not destiny. Even if you’re naturally introverted or you tend to be driven by data and analysis rather than emotion, you can still learn how to adapt different leadership styles to organize, motivate, and direct your team.

Much has been written about common leadership styles and how to identify the right style for you, whether it’s transactional or transformational, bureaucratic or laissez-faire. But according to Daniel Goleman, a psychologist best known for his work on emotional intelligence, “Being a great leader means recognizing that different circumstances may call for different approaches.”

• RK Rebecca Knight is a journalist who writes about all things related to the changing nature of careers and the workplace. Her essays and reported stories have been featured in The Boston Globe, Business Insider, The New York Times, BBC, and The Christian Science Monitor. She was shortlisted as a Reuters Institute Fellow at Oxford University in 2023. Earlier in her career, she spent a decade as an editor and reporter at the Financial Times in New York, London, and Boston.

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