theoretical framework in scientific research

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What is a Theoretical Framework? How to Write It (with Examples) 

Theoretical framework 1,2 is the structure that supports and describes a theory. A theory is a set of interrelated concepts and definitions that present a systematic view of phenomena by describing the relationship among the variables for explaining these phenomena. A theory is developed after a long research process and explains the existence of a research problem in a study. A theoretical framework guides the research process like a roadmap for the research study and helps researchers clearly interpret their findings by providing a structure for organizing data and developing conclusions.   

A theoretical framework in research is an important part of a manuscript and should be presented in the first section. It shows an understanding of the theories and concepts relevant to the research and helps limit the scope of the research.  

Table of Contents

What is a theoretical framework ?  

A theoretical framework in research can be defined as a set of concepts, theories, ideas, and assumptions that help you understand a specific phenomenon or problem. It can be considered a blueprint that is borrowed by researchers to develop their own research inquiry. A theoretical framework in research helps researchers design and conduct their research and analyze and interpret their findings. It explains the relationship between variables, identifies gaps in existing knowledge, and guides the development of research questions, hypotheses, and methodologies to address that gap.  

Now that you know the answer to ‘ What is a theoretical framework? ’, check the following table that lists the different types of theoretical frameworks in research: 3

Developing a theoretical framework in research can help in the following situations: 4

• When conducting research on complex phenomena because a theoretical framework helps organize the research questions, hypotheses, and findings  
• When the research problem requires a deeper understanding of the underlying concepts  
• When conducting research that seeks to address a specific gap in knowledge  
• When conducting research that involves the analysis of existing theories  

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Importance of a theoretical framework  

The purpose of theoretical framework s is to support you in the following ways during the research process: 2  

• Provide a structure for the complete research process  
• Assist researchers in incorporating formal theories into their study as a guide  
• Provide a broad guideline to maintain the research focus  
• Guide the selection of research methods, data collection, and data analysis  
• Help understand the relationships between different concepts and develop hypotheses and research questions  
• Address gaps in existing literature  
• Analyze the data collected and draw meaningful conclusions and make the findings more generalizable  

Theoretical vs. Conceptual framework  

While a theoretical framework covers the theoretical aspect of your study, that is, the various theories that can guide your research, a conceptual framework defines the variables for your study and presents how they relate to each other. The conceptual framework is developed before collecting the data. However, both frameworks help in understanding the research problem and guide the development, collection, and analysis of the research.  

The following table lists some differences between conceptual and theoretical frameworks . 5

How to write a theoretical framework  

The following general steps can help those wondering how to write a theoretical framework: 2

• Identify and define the key concepts clearly and organize them into a suitable structure.  
• Use appropriate terminology and define all key terms to ensure consistency.  
• Identify the relationships between concepts and provide a logical and coherent structure.  
• Develop hypotheses that can be tested through data collection and analysis.  
• Keep it concise and focused with clear and specific aims.  

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Examples of a theoretical framework  

Here are two examples of a theoretical framework. 6,7

Example 1 .   

An insurance company is facing a challenge cross-selling its products. The sales department indicates that most customers have just one policy, although the company offers over 10 unique policies. The company would want its customers to purchase more than one policy since most customers are purchasing policies from other companies.  

Objective : To sell more insurance products to existing customers.  

Problem : Many customers are purchasing additional policies from other companies.  

Research question : How can customer product awareness be improved to increase cross-selling of insurance products?  

Sub-questions: What is the relationship between product awareness and sales? Which factors determine product awareness?  

Since “product awareness” is the main focus in this study, the theoretical framework should analyze this concept and study previous literature on this subject and propose theories that discuss the relationship between product awareness and its improvement in sales of other products.  

Example 2 .

A company is facing a continued decline in its sales and profitability. The main reason for the decline in the profitability is poor services, which have resulted in a high level of dissatisfaction among customers and consequently a decline in customer loyalty. The management is planning to concentrate on clients’ satisfaction and customer loyalty.  

Objective: To provide better service to customers and increase customer loyalty and satisfaction.  

Problem: Continued decrease in sales and profitability.  

Research question: How can customer satisfaction help in increasing sales and profitability?  

Sub-questions: What is the relationship between customer loyalty and sales? Which factors influence the level of satisfaction gained by customers?  

Since customer satisfaction, loyalty, profitability, and sales are the important topics in this example, the theoretical framework should focus on these concepts.  

Benefits of a theoretical framework  

There are several benefits of a theoretical framework in research: 2  

• Provides a structured approach allowing researchers to organize their thoughts in a coherent way.  
• Helps to identify gaps in knowledge highlighting areas where further research is needed.  
• Increases research efficiency by providing a clear direction for research and focusing efforts on relevant data.  
• Improves the quality of research by providing a rigorous and systematic approach to research, which can increase the likelihood of producing valid and reliable results.  
• Provides a basis for comparison by providing a common language and conceptual framework for researchers to compare their findings with other research in the field, facilitating the exchange of ideas and the development of new knowledge.  

Frequently Asked Questions 

Q1. How do I develop a theoretical framework ? 7

A1. The following steps can be used for developing a theoretical framework :  

• Identify the research problem and research questions by clearly defining the problem that the research aims to address and identifying the specific questions that the research aims to answer.
• Review the existing literature to identify the key concepts that have been studied previously. These concepts should be clearly defined and organized into a structure.
• Develop propositions that describe the relationships between the concepts. These propositions should be based on the existing literature and should be testable.
• Develop hypotheses that can be tested through data collection and analysis.
• Test the theoretical framework through data collection and analysis to determine whether the framework is valid and reliable.

Q2. How do I know if I have developed a good theoretical framework or not? 8

A2. The following checklist could help you answer this question:  

• Is my theoretical framework clearly seen as emerging from my literature review?  
• Is it the result of my analysis of the main theories previously studied in my same research field?  
• Does it represent or is it relevant to the most current state of theoretical knowledge on my topic?  
• Does the theoretical framework in research present a logical, coherent, and analytical structure that will support my data analysis?  
• Do the different parts of the theory help analyze the relationships among the variables in my research?  
• Does the theoretical framework target how I will answer my research questions or test the hypotheses?  
• Have I documented every source I have used in developing this theoretical framework ?  
• Is my theoretical framework a model, a table, a figure, or a description?  
• Have I explained why this is the appropriate theoretical framework for my data analysis?  

Q3. Can I use multiple theoretical frameworks in a single study?  

A3. Using multiple theoretical frameworks in a single study is acceptable as long as each theory is clearly defined and related to the study. Each theory should also be discussed individually. This approach may, however, be tedious and effort intensive. Therefore, multiple theoretical frameworks should be used only if absolutely necessary for the study.  

Q4. Is it necessary to include a theoretical framework in every research study?  

A4. The theoretical framework connects researchers to existing knowledge. So, including a theoretical framework would help researchers get a clear idea about the research process and help structure their study effectively by clearly defining an objective, a research problem, and a research question.  

Q5. Can a theoretical framework be developed for qualitative research?  

A5. Yes, a theoretical framework can be developed for qualitative research. However, qualitative research methods may or may not involve a theory developed beforehand. In these studies, a theoretical framework can guide the study and help develop a theory during the data analysis phase. This resulting framework uses inductive reasoning. The outcome of this inductive approach can be referred to as an emergent theoretical framework . This method helps researchers develop a theory inductively, which explains a phenomenon without a guiding framework at the outset.  

Q6. What is the main difference between a literature review and a theoretical framework ?  

A6. A literature review explores already existing studies about a specific topic in order to highlight a gap, which becomes the focus of the current research study. A theoretical framework can be considered the next step in the process, in which the researcher plans a specific conceptual and analytical approach to address the identified gap in the research.  

Theoretical frameworks are thus important components of the research process and researchers should therefore devote ample amount of time to develop a solid theoretical framework so that it can effectively guide their research in a suitable direction. We hope this article has provided a good insight into the concept of theoretical frameworks in research and their benefits.  

References  

• Organizing academic research papers: Theoretical framework. Sacred Heart University library. Accessed August 4, 2023. https://library.sacredheart.edu/c.php?g=29803&p=185919#:~:text=The%20theoretical%20framework%20is%20the,research%20problem%20under%20study%20exists .  
• Salomao A. Understanding what is theoretical framework. Mind the Graph website. Accessed August 5, 2023. https://mindthegraph.com/blog/what-is-theoretical-framework/  
• Theoretical framework—Types, examples, and writing guide. Research Method website. Accessed August 6, 2023. https://researchmethod.net/theoretical-framework/  
• Grant C., Osanloo A. Understanding, selecting, and integrating a theoretical framework in dissertation research: Creating the blueprint for your “house.” Administrative Issues Journal : Connecting Education, Practice, and Research; 4(2):12-26. 2014. Accessed August 7, 2023. https://files.eric.ed.gov/fulltext/EJ1058505.pdf  
• Difference between conceptual framework and theoretical framework. MIM Learnovate website. Accessed August 7, 2023. https://mimlearnovate.com/difference-between-conceptual-framework-and-theoretical-framework/  
• Example of a theoretical framework—Thesis & dissertation. BacherlorPrint website. Accessed August 6, 2023. https://www.bachelorprint.com/dissertation/example-of-a-theoretical-framework/  
• Sample theoretical framework in dissertation and thesis—Overview and example. Students assignment help website. Accessed August 6, 2023. https://www.studentsassignmenthelp.co.uk/blogs/sample-dissertation-theoretical-framework/#Example_of_the_theoretical_framework  
• Kivunja C. Distinguishing between theory, theoretical framework, and conceptual framework: A systematic review of lessons from the field. Accessed August 8, 2023. https://files.eric.ed.gov/fulltext/EJ1198682.pdf  

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Home » Theoretical Framework – Types, Examples and Writing Guide

Theoretical Framework – Types, Examples and Writing Guide

Table of Contents

Theoretical Framework

Definition:

Theoretical framework refers to a set of concepts, theories, ideas , and assumptions that serve as a foundation for understanding a particular phenomenon or problem. It provides a conceptual framework that helps researchers to design and conduct their research, as well as to analyze and interpret their findings.

In research, a theoretical framework explains the relationship between various variables, identifies gaps in existing knowledge, and guides the development of research questions, hypotheses, and methodologies. It also helps to contextualize the research within a broader theoretical perspective, and can be used to guide the interpretation of results and the formulation of recommendations.

Types of Theoretical Framework

Types of Types of Theoretical Framework are as follows:

Conceptual Framework

This type of framework defines the key concepts and relationships between them. It helps to provide a theoretical foundation for a study or research project .

Deductive Framework

This type of framework starts with a general theory or hypothesis and then uses data to test and refine it. It is often used in quantitative research .

Inductive Framework

This type of framework starts with data and then develops a theory or hypothesis based on the patterns and themes that emerge from the data. It is often used in qualitative research .

Empirical Framework

This type of framework focuses on the collection and analysis of empirical data, such as surveys or experiments. It is often used in scientific research .

Normative Framework

This type of framework defines a set of norms or values that guide behavior or decision-making. It is often used in ethics and social sciences.

Explanatory Framework

This type of framework seeks to explain the underlying mechanisms or causes of a particular phenomenon or behavior. It is often used in psychology and social sciences.

Components of Theoretical Framework

The components of a theoretical framework include:

• Concepts : The basic building blocks of a theoretical framework. Concepts are abstract ideas or generalizations that represent objects, events, or phenomena.
• Variables : These are measurable and observable aspects of a concept. In a research context, variables can be manipulated or measured to test hypotheses.
• Assumptions : These are beliefs or statements that are taken for granted and are not tested in a study. They provide a starting point for developing hypotheses.
• Propositions : These are statements that explain the relationships between concepts and variables in a theoretical framework.
• Hypotheses : These are testable predictions that are derived from the theoretical framework. Hypotheses are used to guide data collection and analysis.
• Constructs : These are abstract concepts that cannot be directly measured but are inferred from observable variables. Constructs provide a way to understand complex phenomena.
• Models : These are simplified representations of reality that are used to explain, predict, or control a phenomenon.

How to Write Theoretical Framework

A theoretical framework is an essential part of any research study or paper, as it helps to provide a theoretical basis for the research and guide the analysis and interpretation of the data. Here are some steps to help you write a theoretical framework:

• Identify the key concepts and variables : Start by identifying the main concepts and variables that your research is exploring. These could include things like motivation, behavior, attitudes, or any other relevant concepts.
• Review relevant literature: Conduct a thorough review of the existing literature in your field to identify key theories and ideas that relate to your research. This will help you to understand the existing knowledge and theories that are relevant to your research and provide a basis for your theoretical framework.
• Develop a conceptual framework : Based on your literature review, develop a conceptual framework that outlines the key concepts and their relationships. This framework should provide a clear and concise overview of the theoretical perspective that underpins your research.
• Identify hypotheses and research questions: Based on your conceptual framework, identify the hypotheses and research questions that you want to test or explore in your research.
• Test your theoretical framework: Once you have developed your theoretical framework, test it by applying it to your research data. This will help you to identify any gaps or weaknesses in your framework and refine it as necessary.
• Write up your theoretical framework: Finally, write up your theoretical framework in a clear and concise manner, using appropriate terminology and referencing the relevant literature to support your arguments.

Theoretical Framework Examples

Here are some examples of theoretical frameworks:

• Social Learning Theory : This framework, developed by Albert Bandura, suggests that people learn from their environment, including the behaviors of others, and that behavior is influenced by both external and internal factors.
• Maslow’s Hierarchy of Needs : Abraham Maslow proposed that human needs are arranged in a hierarchy, with basic physiological needs at the bottom, followed by safety, love and belonging, esteem, and self-actualization at the top. This framework has been used in various fields, including psychology and education.
• Ecological Systems Theory : This framework, developed by Urie Bronfenbrenner, suggests that a person’s development is influenced by the interaction between the individual and the various environments in which they live, such as family, school, and community.
• Feminist Theory: This framework examines how gender and power intersect to influence social, cultural, and political issues. It emphasizes the importance of understanding and challenging systems of oppression.
• Cognitive Behavioral Theory: This framework suggests that our thoughts, beliefs, and attitudes influence our behavior, and that changing our thought patterns can lead to changes in behavior and emotional responses.
• Attachment Theory: This framework examines the ways in which early relationships with caregivers shape our later relationships and attachment styles.
• Critical Race Theory : This framework examines how race intersects with other forms of social stratification and oppression to perpetuate inequality and discrimination.

When to Have A Theoretical Framework

Following are some situations When to Have A Theoretical Framework:

• A theoretical framework should be developed when conducting research in any discipline, as it provides a foundation for understanding the research problem and guiding the research process.
• A theoretical framework is essential when conducting research on complex phenomena, as it helps to organize and structure the research questions, hypotheses, and findings.
• A theoretical framework should be developed when the research problem requires a deeper understanding of the underlying concepts and principles that govern the phenomenon being studied.
• A theoretical framework is particularly important when conducting research in social sciences, as it helps to explain the relationships between variables and provides a framework for testing hypotheses.
• A theoretical framework should be developed when conducting research in applied fields, such as engineering or medicine, as it helps to provide a theoretical basis for the development of new technologies or treatments.
• A theoretical framework should be developed when conducting research that seeks to address a specific gap in knowledge, as it helps to define the problem and identify potential solutions.
• A theoretical framework is also important when conducting research that involves the analysis of existing theories or concepts, as it helps to provide a framework for comparing and contrasting different theories and concepts.
• A theoretical framework should be developed when conducting research that seeks to make predictions or develop generalizations about a particular phenomenon, as it helps to provide a basis for evaluating the accuracy of these predictions or generalizations.
• Finally, a theoretical framework should be developed when conducting research that seeks to make a contribution to the field, as it helps to situate the research within the broader context of the discipline and identify its significance.

Purpose of Theoretical Framework

The purposes of a theoretical framework include:

• Providing a conceptual framework for the study: A theoretical framework helps researchers to define and clarify the concepts and variables of interest in their research. It enables researchers to develop a clear and concise definition of the problem, which in turn helps to guide the research process.
• Guiding the research design: A theoretical framework can guide the selection of research methods, data collection techniques, and data analysis procedures. By outlining the key concepts and assumptions underlying the research questions, the theoretical framework can help researchers to identify the most appropriate research design for their study.
• Supporting the interpretation of research findings: A theoretical framework provides a framework for interpreting the research findings by helping researchers to make connections between their findings and existing theory. It enables researchers to identify the implications of their findings for theory development and to assess the generalizability of their findings.
• Enhancing the credibility of the research: A well-developed theoretical framework can enhance the credibility of the research by providing a strong theoretical foundation for the study. It demonstrates that the research is based on a solid understanding of the relevant theory and that the research questions are grounded in a clear conceptual framework.
• Facilitating communication and collaboration: A theoretical framework provides a common language and conceptual framework for researchers, enabling them to communicate and collaborate more effectively. It helps to ensure that everyone involved in the research is working towards the same goals and is using the same concepts and definitions.

Characteristics of Theoretical Framework

Some of the characteristics of a theoretical framework include:

• Conceptual clarity: The concepts used in the theoretical framework should be clearly defined and understood by all stakeholders.
• Logical coherence : The framework should be internally consistent, with each concept and assumption logically connected to the others.
• Empirical relevance: The framework should be based on empirical evidence and research findings.
• Parsimony : The framework should be as simple as possible, without sacrificing its ability to explain the phenomenon in question.
• Flexibility : The framework should be adaptable to new findings and insights.
• Testability : The framework should be testable through research, with clear hypotheses that can be falsified or supported by data.
• Applicability : The framework should be useful for practical applications, such as designing interventions or policies.

Advantages of Theoretical Framework

Here are some of the advantages of having a theoretical framework:

• Provides a clear direction : A theoretical framework helps researchers to identify the key concepts and variables they need to study and the relationships between them. This provides a clear direction for the research and helps researchers to focus their efforts and resources.
• Increases the validity of the research: A theoretical framework helps to ensure that the research is based on sound theoretical principles and concepts. This increases the validity of the research by ensuring that it is grounded in established knowledge and is not based on arbitrary assumptions.
• Enables comparisons between studies : A theoretical framework provides a common language and set of concepts that researchers can use to compare and contrast their findings. This helps to build a cumulative body of knowledge and allows researchers to identify patterns and trends across different studies.
• Helps to generate hypotheses: A theoretical framework provides a basis for generating hypotheses about the relationships between different concepts and variables. This can help to guide the research process and identify areas that require further investigation.
• Facilitates communication: A theoretical framework provides a common language and set of concepts that researchers can use to communicate their findings to other researchers and to the wider community. This makes it easier for others to understand the research and its implications.

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• v.21(3); Fall 2022

Literature Reviews, Theoretical Frameworks, and Conceptual Frameworks: An Introduction for New Biology Education Researchers

Julie a. luft.

† Department of Mathematics, Social Studies, and Science Education, Mary Frances Early College of Education, University of Georgia, Athens, GA 30602-7124

Sophia Jeong

‡ Department of Teaching & Learning, College of Education & Human Ecology, Ohio State University, Columbus, OH 43210

Robert Idsardi

§ Department of Biology, Eastern Washington University, Cheney, WA 99004

Grant Gardner

∥ Department of Biology, Middle Tennessee State University, Murfreesboro, TN 37132

Associated Data

To frame their work, biology education researchers need to consider the role of literature reviews, theoretical frameworks, and conceptual frameworks as critical elements of the research and writing process. However, these elements can be confusing for scholars new to education research. This Research Methods article is designed to provide an overview of each of these elements and delineate the purpose of each in the educational research process. We describe what biology education researchers should consider as they conduct literature reviews, identify theoretical frameworks, and construct conceptual frameworks. Clarifying these different components of educational research studies can be helpful to new biology education researchers and the biology education research community at large in situating their work in the broader scholarly literature.

INTRODUCTION

Discipline-based education research (DBER) involves the purposeful and situated study of teaching and learning in specific disciplinary areas ( Singer et al. , 2012 ). Studies in DBER are guided by research questions that reflect disciplines’ priorities and worldviews. Researchers can use quantitative data, qualitative data, or both to answer these research questions through a variety of methodological traditions. Across all methodologies, there are different methods associated with planning and conducting educational research studies that include the use of surveys, interviews, observations, artifacts, or instruments. Ensuring the coherence of these elements to the discipline’s perspective also involves situating the work in the broader scholarly literature. The tools for doing this include literature reviews, theoretical frameworks, and conceptual frameworks. However, the purpose and function of each of these elements is often confusing to new education researchers. The goal of this article is to introduce new biology education researchers to these three important elements important in DBER scholarship and the broader educational literature.

The first element we discuss is a review of research (literature reviews), which highlights the need for a specific research question, study problem, or topic of investigation. Literature reviews situate the relevance of the study within a topic and a field. The process may seem familiar to science researchers entering DBER fields, but new researchers may still struggle in conducting the review. Booth et al. (2016b) highlight some of the challenges novice education researchers face when conducting a review of literature. They point out that novice researchers struggle in deciding how to focus the review, determining the scope of articles needed in the review, and knowing how to be critical of the articles in the review. Overcoming these challenges (and others) can help novice researchers construct a sound literature review that can inform the design of the study and help ensure the work makes a contribution to the field.

The second and third highlighted elements are theoretical and conceptual frameworks. These guide biology education research (BER) studies, and may be less familiar to science researchers. These elements are important in shaping the construction of new knowledge. Theoretical frameworks offer a way to explain and interpret the studied phenomenon, while conceptual frameworks clarify assumptions about the studied phenomenon. Despite the importance of these constructs in educational research, biology educational researchers have noted the limited use of theoretical or conceptual frameworks in published work ( DeHaan, 2011 ; Dirks, 2011 ; Lo et al. , 2019 ). In reviewing articles published in CBE—Life Sciences Education ( LSE ) between 2015 and 2019, we found that fewer than 25% of the research articles had a theoretical or conceptual framework (see the Supplemental Information), and at times there was an inconsistent use of theoretical and conceptual frameworks. Clearly, these frameworks are challenging for published biology education researchers, which suggests the importance of providing some initial guidance to new biology education researchers.

Fortunately, educational researchers have increased their explicit use of these frameworks over time, and this is influencing educational research in science, technology, engineering, and mathematics (STEM) fields. For instance, a quick search for theoretical or conceptual frameworks in the abstracts of articles in Educational Research Complete (a common database for educational research) in STEM fields demonstrates a dramatic change over the last 20 years: from only 778 articles published between 2000 and 2010 to 5703 articles published between 2010 and 2020, a more than sevenfold increase. Greater recognition of the importance of these frameworks is contributing to DBER authors being more explicit about such frameworks in their studies.

Collectively, literature reviews, theoretical frameworks, and conceptual frameworks work to guide methodological decisions and the elucidation of important findings. Each offers a different perspective on the problem of study and is an essential element in all forms of educational research. As new researchers seek to learn about these elements, they will find different resources, a variety of perspectives, and many suggestions about the construction and use of these elements. The wide range of available information can overwhelm the new researcher who just wants to learn the distinction between these elements or how to craft them adequately.

Our goal in writing this paper is not to offer specific advice about how to write these sections in scholarly work. Instead, we wanted to introduce these elements to those who are new to BER and who are interested in better distinguishing one from the other. In this paper, we share the purpose of each element in BER scholarship, along with important points on its construction. We also provide references for additional resources that may be beneficial to better understanding each element. Table 1 summarizes the key distinctions among these elements.

Comparison of literature reviews, theoretical frameworks, and conceptual reviews

This article is written for the new biology education researcher who is just learning about these different elements or for scientists looking to become more involved in BER. It is a result of our own work as science education and biology education researchers, whether as graduate students and postdoctoral scholars or newly hired and established faculty members. This is the article we wish had been available as we started to learn about these elements or discussed them with new educational researchers in biology.

LITERATURE REVIEWS

Purpose of a literature review.

A literature review is foundational to any research study in education or science. In education, a well-conceptualized and well-executed review provides a summary of the research that has already been done on a specific topic and identifies questions that remain to be answered, thus illustrating the current research project’s potential contribution to the field and the reasoning behind the methodological approach selected for the study ( Maxwell, 2012 ). BER is an evolving disciplinary area that is redefining areas of conceptual emphasis as well as orientations toward teaching and learning (e.g., Labov et al. , 2010 ; American Association for the Advancement of Science, 2011 ; Nehm, 2019 ). As a result, building comprehensive, critical, purposeful, and concise literature reviews can be a challenge for new biology education researchers.

Building Literature Reviews

There are different ways to approach and construct a literature review. Booth et al. (2016a) provide an overview that includes, for example, scoping reviews, which are focused only on notable studies and use a basic method of analysis, and integrative reviews, which are the result of exhaustive literature searches across different genres. Underlying each of these different review processes are attention to the s earch process, a ppraisa l of articles, s ynthesis of the literature, and a nalysis: SALSA ( Booth et al. , 2016a ). This useful acronym can help the researcher focus on the process while building a specific type of review.

However, new educational researchers often have questions about literature reviews that are foundational to SALSA or other approaches. Common questions concern determining which literature pertains to the topic of study or the role of the literature review in the design of the study. This section addresses such questions broadly while providing general guidance for writing a narrative literature review that evaluates the most pertinent studies.

The literature review process should begin before the research is conducted. As Boote and Beile (2005 , p. 3) suggested, researchers should be “scholars before researchers.” They point out that having a good working knowledge of the proposed topic helps illuminate avenues of study. Some subject areas have a deep body of work to read and reflect upon, providing a strong foundation for developing the research question(s). For instance, the teaching and learning of evolution is an area of long-standing interest in the BER community, generating many studies (e.g., Perry et al. , 2008 ; Barnes and Brownell, 2016 ) and reviews of research (e.g., Sickel and Friedrichsen, 2013 ; Ziadie and Andrews, 2018 ). Emerging areas of BER include the affective domain, issues of transfer, and metacognition ( Singer et al. , 2012 ). Many studies in these areas are transdisciplinary and not always specific to biology education (e.g., Rodrigo-Peiris et al. , 2018 ; Kolpikova et al. , 2019 ). These newer areas may require reading outside BER; fortunately, summaries of some of these topics can be found in the Current Insights section of the LSE website.

In focusing on a specific problem within a broader research strand, a new researcher will likely need to examine research outside BER. Depending upon the area of study, the expanded reading list might involve a mix of BER, DBER, and educational research studies. Determining the scope of the reading is not always straightforward. A simple way to focus one’s reading is to create a “summary phrase” or “research nugget,” which is a very brief descriptive statement about the study. It should focus on the essence of the study, for example, “first-year nonmajor students’ understanding of evolution,” “metacognitive prompts to enhance learning during biochemistry,” or “instructors’ inquiry-based instructional practices after professional development programming.” This type of phrase should help a new researcher identify two or more areas to review that pertain to the study. Focusing on recent research in the last 5 years is a good first step. Additional studies can be identified by reading relevant works referenced in those articles. It is also important to read seminal studies that are more than 5 years old. Reading a range of studies should give the researcher the necessary command of the subject in order to suggest a research question.

Given that the research question(s) arise from the literature review, the review should also substantiate the selected methodological approach. The review and research question(s) guide the researcher in determining how to collect and analyze data. Often the methodological approach used in a study is selected to contribute knowledge that expands upon what has been published previously about the topic (see Institute of Education Sciences and National Science Foundation, 2013 ). An emerging topic of study may need an exploratory approach that allows for a description of the phenomenon and development of a potential theory. This could, but not necessarily, require a methodological approach that uses interviews, observations, surveys, or other instruments. An extensively studied topic may call for the additional understanding of specific factors or variables; this type of study would be well suited to a verification or a causal research design. These could entail a methodological approach that uses valid and reliable instruments, observations, or interviews to determine an effect in the studied event. In either of these examples, the researcher(s) may use a qualitative, quantitative, or mixed methods methodological approach.

Even with a good research question, there is still more reading to be done. The complexity and focus of the research question dictates the depth and breadth of the literature to be examined. Questions that connect multiple topics can require broad literature reviews. For instance, a study that explores the impact of a biology faculty learning community on the inquiry instruction of faculty could have the following review areas: learning communities among biology faculty, inquiry instruction among biology faculty, and inquiry instruction among biology faculty as a result of professional learning. Biology education researchers need to consider whether their literature review requires studies from different disciplines within or outside DBER. For the example given, it would be fruitful to look at research focused on learning communities with faculty in STEM fields or in general education fields that result in instructional change. It is important not to be too narrow or too broad when reading. When the conclusions of articles start to sound similar or no new insights are gained, the researcher likely has a good foundation for a literature review. This level of reading should allow the researcher to demonstrate a mastery in understanding the researched topic, explain the suitability of the proposed research approach, and point to the need for the refined research question(s).

The literature review should include the researcher’s evaluation and critique of the selected studies. A researcher may have a large collection of studies, but not all of the studies will follow standards important in the reporting of empirical work in the social sciences. The American Educational Research Association ( Duran et al. , 2006 ), for example, offers a general discussion about standards for such work: an adequate review of research informing the study, the existence of sound and appropriate data collection and analysis methods, and appropriate conclusions that do not overstep or underexplore the analyzed data. The Institute of Education Sciences and National Science Foundation (2013) also offer Common Guidelines for Education Research and Development that can be used to evaluate collected studies.

Because not all journals adhere to such standards, it is important that a researcher review each study to determine the quality of published research, per the guidelines suggested earlier. In some instances, the research may be fatally flawed. Examples of such flaws include data that do not pertain to the question, a lack of discussion about the data collection, poorly constructed instruments, or an inadequate analysis. These types of errors result in studies that are incomplete, error-laden, or inaccurate and should be excluded from the review. Most studies have limitations, and the author(s) often make them explicit. For instance, there may be an instructor effect, recognized bias in the analysis, or issues with the sample population. Limitations are usually addressed by the research team in some way to ensure a sound and acceptable research process. Occasionally, the limitations associated with the study can be significant and not addressed adequately, which leaves a consequential decision in the hands of the researcher. Providing critiques of studies in the literature review process gives the reader confidence that the researcher has carefully examined relevant work in preparation for the study and, ultimately, the manuscript.

A solid literature review clearly anchors the proposed study in the field and connects the research question(s), the methodological approach, and the discussion. Reviewing extant research leads to research questions that will contribute to what is known in the field. By summarizing what is known, the literature review points to what needs to be known, which in turn guides decisions about methodology. Finally, notable findings of the new study are discussed in reference to those described in the literature review.

Within published BER studies, literature reviews can be placed in different locations in an article. When included in the introductory section of the study, the first few paragraphs of the manuscript set the stage, with the literature review following the opening paragraphs. Cooper et al. (2019) illustrate this approach in their study of course-based undergraduate research experiences (CUREs). An introduction discussing the potential of CURES is followed by an analysis of the existing literature relevant to the design of CUREs that allows for novel student discoveries. Within this review, the authors point out contradictory findings among research on novel student discoveries. This clarifies the need for their study, which is described and highlighted through specific research aims.

A literature reviews can also make up a separate section in a paper. For example, the introduction to Todd et al. (2019) illustrates the need for their research topic by highlighting the potential of learning progressions (LPs) and suggesting that LPs may help mitigate learning loss in genetics. At the end of the introduction, the authors state their specific research questions. The review of literature following this opening section comprises two subsections. One focuses on learning loss in general and examines a variety of studies and meta-analyses from the disciplines of medical education, mathematics, and reading. The second section focuses specifically on LPs in genetics and highlights student learning in the midst of LPs. These separate reviews provide insights into the stated research question.

Suggestions and Advice

A well-conceptualized, comprehensive, and critical literature review reveals the understanding of the topic that the researcher brings to the study. Literature reviews should not be so big that there is no clear area of focus; nor should they be so narrow that no real research question arises. The task for a researcher is to craft an efficient literature review that offers a critical analysis of published work, articulates the need for the study, guides the methodological approach to the topic of study, and provides an adequate foundation for the discussion of the findings.

In our own writing of literature reviews, there are often many drafts. An early draft may seem well suited to the study because the need for and approach to the study are well described. However, as the results of the study are analyzed and findings begin to emerge, the existing literature review may be inadequate and need revision. The need for an expanded discussion about the research area can result in the inclusion of new studies that support the explanation of a potential finding. The literature review may also prove to be too broad. Refocusing on a specific area allows for more contemplation of a finding.

It should be noted that there are different types of literature reviews, and many books and articles have been written about the different ways to embark on these types of reviews. Among these different resources, the following may be helpful in considering how to refine the review process for scholarly journals:

• Booth, A., Sutton, A., & Papaioannou, D. (2016a). Systemic approaches to a successful literature review (2nd ed.). Los Angeles, CA: Sage. This book addresses different types of literature reviews and offers important suggestions pertaining to defining the scope of the literature review and assessing extant studies.
• Booth, W. C., Colomb, G. G., Williams, J. M., Bizup, J., & Fitzgerald, W. T. (2016b). The craft of research (4th ed.). Chicago: University of Chicago Press. This book can help the novice consider how to make the case for an area of study. While this book is not specifically about literature reviews, it offers suggestions about making the case for your study.
• Galvan, J. L., & Galvan, M. C. (2017). Writing literature reviews: A guide for students of the social and behavioral sciences (7th ed.). Routledge. This book offers guidance on writing different types of literature reviews. For the novice researcher, there are useful suggestions for creating coherent literature reviews.

THEORETICAL FRAMEWORKS

Purpose of theoretical frameworks.

As new education researchers may be less familiar with theoretical frameworks than with literature reviews, this discussion begins with an analogy. Envision a biologist, chemist, and physicist examining together the dramatic effect of a fog tsunami over the ocean. A biologist gazing at this phenomenon may be concerned with the effect of fog on various species. A chemist may be interested in the chemical composition of the fog as water vapor condenses around bits of salt. A physicist may be focused on the refraction of light to make fog appear to be “sitting” above the ocean. While observing the same “objective event,” the scientists are operating under different theoretical frameworks that provide a particular perspective or “lens” for the interpretation of the phenomenon. Each of these scientists brings specialized knowledge, experiences, and values to this phenomenon, and these influence the interpretation of the phenomenon. The scientists’ theoretical frameworks influence how they design and carry out their studies and interpret their data.

Within an educational study, a theoretical framework helps to explain a phenomenon through a particular lens and challenges and extends existing knowledge within the limitations of that lens. Theoretical frameworks are explicitly stated by an educational researcher in the paper’s framework, theory, or relevant literature section. The framework shapes the types of questions asked, guides the method by which data are collected and analyzed, and informs the discussion of the results of the study. It also reveals the researcher’s subjectivities, for example, values, social experience, and viewpoint ( Allen, 2017 ). It is essential that a novice researcher learn to explicitly state a theoretical framework, because all research questions are being asked from the researcher’s implicit or explicit assumptions of a phenomenon of interest ( Schwandt, 2000 ).

Selecting Theoretical Frameworks

Theoretical frameworks are one of the most contemplated elements in our work in educational research. In this section, we share three important considerations for new scholars selecting a theoretical framework.

The first step in identifying a theoretical framework involves reflecting on the phenomenon within the study and the assumptions aligned with the phenomenon. The phenomenon involves the studied event. There are many possibilities, for example, student learning, instructional approach, or group organization. A researcher holds assumptions about how the phenomenon will be effected, influenced, changed, or portrayed. It is ultimately the researcher’s assumption(s) about the phenomenon that aligns with a theoretical framework. An example can help illustrate how a researcher’s reflection on the phenomenon and acknowledgment of assumptions can result in the identification of a theoretical framework.

In our example, a biology education researcher may be interested in exploring how students’ learning of difficult biological concepts can be supported by the interactions of group members. The phenomenon of interest is the interactions among the peers, and the researcher assumes that more knowledgeable students are important in supporting the learning of the group. As a result, the researcher may draw on Vygotsky’s (1978) sociocultural theory of learning and development that is focused on the phenomenon of student learning in a social setting. This theory posits the critical nature of interactions among students and between students and teachers in the process of building knowledge. A researcher drawing upon this framework holds the assumption that learning is a dynamic social process involving questions and explanations among students in the classroom and that more knowledgeable peers play an important part in the process of building conceptual knowledge.

It is important to state at this point that there are many different theoretical frameworks. Some frameworks focus on learning and knowing, while other theoretical frameworks focus on equity, empowerment, or discourse. Some frameworks are well articulated, and others are still being refined. For a new researcher, it can be challenging to find a theoretical framework. Two of the best ways to look for theoretical frameworks is through published works that highlight different frameworks.

When a theoretical framework is selected, it should clearly connect to all parts of the study. The framework should augment the study by adding a perspective that provides greater insights into the phenomenon. It should clearly align with the studies described in the literature review. For instance, a framework focused on learning would correspond to research that reported different learning outcomes for similar studies. The methods for data collection and analysis should also correspond to the framework. For instance, a study about instructional interventions could use a theoretical framework concerned with learning and could collect data about the effect of the intervention on what is learned. When the data are analyzed, the theoretical framework should provide added meaning to the findings, and the findings should align with the theoretical framework.

A study by Jensen and Lawson (2011) provides an example of how a theoretical framework connects different parts of the study. They compared undergraduate biology students in heterogeneous and homogeneous groups over the course of a semester. Jensen and Lawson (2011) assumed that learning involved collaboration and more knowledgeable peers, which made Vygotsky’s (1978) theory a good fit for their study. They predicted that students in heterogeneous groups would experience greater improvement in their reasoning abilities and science achievements with much of the learning guided by the more knowledgeable peers.

In the enactment of the study, they collected data about the instruction in traditional and inquiry-oriented classes, while the students worked in homogeneous or heterogeneous groups. To determine the effect of working in groups, the authors also measured students’ reasoning abilities and achievement. Each data-collection and analysis decision connected to understanding the influence of collaborative work.

Their findings highlighted aspects of Vygotsky’s (1978) theory of learning. One finding, for instance, posited that inquiry instruction, as a whole, resulted in reasoning and achievement gains. This links to Vygotsky (1978) , because inquiry instruction involves interactions among group members. A more nuanced finding was that group composition had a conditional effect. Heterogeneous groups performed better with more traditional and didactic instruction, regardless of the reasoning ability of the group members. Homogeneous groups worked better during interaction-rich activities for students with low reasoning ability. The authors attributed the variation to the different types of helping behaviors of students. High-performing students provided the answers, while students with low reasoning ability had to work collectively through the material. In terms of Vygotsky (1978) , this finding provided new insights into the learning context in which productive interactions can occur for students.

Another consideration in the selection and use of a theoretical framework pertains to its orientation to the study. This can result in the theoretical framework prioritizing individuals, institutions, and/or policies ( Anfara and Mertz, 2014 ). Frameworks that connect to individuals, for instance, could contribute to understanding their actions, learning, or knowledge. Institutional frameworks, on the other hand, offer insights into how institutions, organizations, or groups can influence individuals or materials. Policy theories provide ways to understand how national or local policies can dictate an emphasis on outcomes or instructional design. These different types of frameworks highlight different aspects in an educational setting, which influences the design of the study and the collection of data. In addition, these different frameworks offer a way to make sense of the data. Aligning the data collection and analysis with the framework ensures that a study is coherent and can contribute to the field.

New understandings emerge when different theoretical frameworks are used. For instance, Ebert-May et al. (2015) prioritized the individual level within conceptual change theory (see Posner et al. , 1982 ). In this theory, an individual’s knowledge changes when it no longer fits the phenomenon. Ebert-May et al. (2015) designed a professional development program challenging biology postdoctoral scholars’ existing conceptions of teaching. The authors reported that the biology postdoctoral scholars’ teaching practices became more student-centered as they were challenged to explain their instructional decision making. According to the theory, the biology postdoctoral scholars’ dissatisfaction in their descriptions of teaching and learning initiated change in their knowledge and instruction. These results reveal how conceptual change theory can explain the learning of participants and guide the design of professional development programming.

The communities of practice (CoP) theoretical framework ( Lave, 1988 ; Wenger, 1998 ) prioritizes the institutional level , suggesting that learning occurs when individuals learn from and contribute to the communities in which they reside. Grounded in the assumption of community learning, the literature on CoP suggests that, as individuals interact regularly with the other members of their group, they learn about the rules, roles, and goals of the community ( Allee, 2000 ). A study conducted by Gehrke and Kezar (2017) used the CoP framework to understand organizational change by examining the involvement of individual faculty engaged in a cross-institutional CoP focused on changing the instructional practice of faculty at each institution. In the CoP, faculty members were involved in enhancing instructional materials within their department, which aligned with an overarching goal of instituting instruction that embraced active learning. Not surprisingly, Gehrke and Kezar (2017) revealed that faculty who perceived the community culture as important in their work cultivated institutional change. Furthermore, they found that institutional change was sustained when key leaders served as mentors and provided support for faculty, and as faculty themselves developed into leaders. This study reveals the complexity of individual roles in a COP in order to support institutional instructional change.

It is important to explicitly state the theoretical framework used in a study, but elucidating a theoretical framework can be challenging for a new educational researcher. The literature review can help to identify an applicable theoretical framework. Focal areas of the review or central terms often connect to assumptions and assertions associated with the framework that pertain to the phenomenon of interest. Another way to identify a theoretical framework is self-reflection by the researcher on personal beliefs and understandings about the nature of knowledge the researcher brings to the study ( Lysaght, 2011 ). In stating one’s beliefs and understandings related to the study (e.g., students construct their knowledge, instructional materials support learning), an orientation becomes evident that will suggest a particular theoretical framework. Theoretical frameworks are not arbitrary , but purposefully selected.

With experience, a researcher may find expanded roles for theoretical frameworks. Researchers may revise an existing framework that has limited explanatory power, or they may decide there is a need to develop a new theoretical framework. These frameworks can emerge from a current study or the need to explain a phenomenon in a new way. Researchers may also find that multiple theoretical frameworks are necessary to frame and explore a problem, as different frameworks can provide different insights into a problem.

Finally, it is important to recognize that choosing “x” theoretical framework does not necessarily mean a researcher chooses “y” methodology and so on, nor is there a clear-cut, linear process in selecting a theoretical framework for one’s study. In part, the nonlinear process of identifying a theoretical framework is what makes understanding and using theoretical frameworks challenging. For the novice scholar, contemplating and understanding theoretical frameworks is essential. Fortunately, there are articles and books that can help:

• Creswell, J. W. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). Los Angeles, CA: Sage. This book provides an overview of theoretical frameworks in general educational research.
• Ding, L. (2019). Theoretical perspectives of quantitative physics education research. Physical Review Physics Education Research , 15 (2), 020101-1–020101-13. This paper illustrates how a DBER field can use theoretical frameworks.
• Nehm, R. (2019). Biology education research: Building integrative frameworks for teaching and learning about living systems. Disciplinary and Interdisciplinary Science Education Research , 1 , ar15. https://doi.org/10.1186/s43031-019-0017-6 . This paper articulates the need for studies in BER to explicitly state theoretical frameworks and provides examples of potential studies.
• Patton, M. Q. (2015). Qualitative research & evaluation methods: Integrating theory and practice . Sage. This book also provides an overview of theoretical frameworks, but for both research and evaluation.

CONCEPTUAL FRAMEWORKS

Purpose of a conceptual framework.

A conceptual framework is a description of the way a researcher understands the factors and/or variables that are involved in the study and their relationships to one another. The purpose of a conceptual framework is to articulate the concepts under study using relevant literature ( Rocco and Plakhotnik, 2009 ) and to clarify the presumed relationships among those concepts ( Rocco and Plakhotnik, 2009 ; Anfara and Mertz, 2014 ). Conceptual frameworks are different from theoretical frameworks in both their breadth and grounding in established findings. Whereas a theoretical framework articulates the lens through which a researcher views the work, the conceptual framework is often more mechanistic and malleable.

Conceptual frameworks are broader, encompassing both established theories (i.e., theoretical frameworks) and the researchers’ own emergent ideas. Emergent ideas, for example, may be rooted in informal and/or unpublished observations from experience. These emergent ideas would not be considered a “theory” if they are not yet tested, supported by systematically collected evidence, and peer reviewed. However, they do still play an important role in the way researchers approach their studies. The conceptual framework allows authors to clearly describe their emergent ideas so that connections among ideas in the study and the significance of the study are apparent to readers.

Constructing Conceptual Frameworks

Including a conceptual framework in a research study is important, but researchers often opt to include either a conceptual or a theoretical framework. Either may be adequate, but both provide greater insight into the research approach. For instance, a research team plans to test a novel component of an existing theory. In their study, they describe the existing theoretical framework that informs their work and then present their own conceptual framework. Within this conceptual framework, specific topics portray emergent ideas that are related to the theory. Describing both frameworks allows readers to better understand the researchers’ assumptions, orientations, and understanding of concepts being investigated. For example, Connolly et al. (2018) included a conceptual framework that described how they applied a theoretical framework of social cognitive career theory (SCCT) to their study on teaching programs for doctoral students. In their conceptual framework, the authors described SCCT, explained how it applied to the investigation, and drew upon results from previous studies to justify the proposed connections between the theory and their emergent ideas.

In some cases, authors may be able to sufficiently describe their conceptualization of the phenomenon under study in an introduction alone, without a separate conceptual framework section. However, incomplete descriptions of how the researchers conceptualize the components of the study may limit the significance of the study by making the research less intelligible to readers. This is especially problematic when studying topics in which researchers use the same terms for different constructs or different terms for similar and overlapping constructs (e.g., inquiry, teacher beliefs, pedagogical content knowledge, or active learning). Authors must describe their conceptualization of a construct if the research is to be understandable and useful.

There are some key areas to consider regarding the inclusion of a conceptual framework in a study. To begin with, it is important to recognize that conceptual frameworks are constructed by the researchers conducting the study ( Rocco and Plakhotnik, 2009 ; Maxwell, 2012 ). This is different from theoretical frameworks that are often taken from established literature. Researchers should bring together ideas from the literature, but they may be influenced by their own experiences as a student and/or instructor, the shared experiences of others, or thought experiments as they construct a description, model, or representation of their understanding of the phenomenon under study. This is an exercise in intellectual organization and clarity that often considers what is learned, known, and experienced. The conceptual framework makes these constructs explicitly visible to readers, who may have different understandings of the phenomenon based on their prior knowledge and experience. There is no single method to go about this intellectual work.

Reeves et al. (2016) is an example of an article that proposed a conceptual framework about graduate teaching assistant professional development evaluation and research. The authors used existing literature to create a novel framework that filled a gap in current research and practice related to the training of graduate teaching assistants. This conceptual framework can guide the systematic collection of data by other researchers because the framework describes the relationships among various factors that influence teaching and learning. The Reeves et al. (2016) conceptual framework may be modified as additional data are collected and analyzed by other researchers. This is not uncommon, as conceptual frameworks can serve as catalysts for concerted research efforts that systematically explore a phenomenon (e.g., Reynolds et al. , 2012 ; Brownell and Kloser, 2015 ).

Sabel et al. (2017) used a conceptual framework in their exploration of how scaffolds, an external factor, interact with internal factors to support student learning. Their conceptual framework integrated principles from two theoretical frameworks, self-regulated learning and metacognition, to illustrate how the research team conceptualized students’ use of scaffolds in their learning ( Figure 1 ). Sabel et al. (2017) created this model using their interpretations of these two frameworks in the context of their teaching.

Conceptual framework from Sabel et al. (2017) .

A conceptual framework should describe the relationship among components of the investigation ( Anfara and Mertz, 2014 ). These relationships should guide the researcher’s methods of approaching the study ( Miles et al. , 2014 ) and inform both the data to be collected and how those data should be analyzed. Explicitly describing the connections among the ideas allows the researcher to justify the importance of the study and the rigor of the research design. Just as importantly, these frameworks help readers understand why certain components of a system were not explored in the study. This is a challenge in education research, which is rooted in complex environments with many variables that are difficult to control.

For example, Sabel et al. (2017) stated: “Scaffolds, such as enhanced answer keys and reflection questions, can help students and instructors bridge the external and internal factors and support learning” (p. 3). They connected the scaffolds in the study to the three dimensions of metacognition and the eventual transformation of existing ideas into new or revised ideas. Their framework provides a rationale for focusing on how students use two different scaffolds, and not on other factors that may influence a student’s success (self-efficacy, use of active learning, exam format, etc.).

In constructing conceptual frameworks, researchers should address needed areas of study and/or contradictions discovered in literature reviews. By attending to these areas, researchers can strengthen their arguments for the importance of a study. For instance, conceptual frameworks can address how the current study will fill gaps in the research, resolve contradictions in existing literature, or suggest a new area of study. While a literature review describes what is known and not known about the phenomenon, the conceptual framework leverages these gaps in describing the current study ( Maxwell, 2012 ). In the example of Sabel et al. (2017) , the authors indicated there was a gap in the literature regarding how scaffolds engage students in metacognition to promote learning in large classes. Their study helps fill that gap by describing how scaffolds can support students in the three dimensions of metacognition: intelligibility, plausibility, and wide applicability. In another example, Lane (2016) integrated research from science identity, the ethic of care, the sense of belonging, and an expertise model of student success to form a conceptual framework that addressed the critiques of other frameworks. In a more recent example, Sbeglia et al. (2021) illustrated how a conceptual framework influences the methodological choices and inferences in studies by educational researchers.

Sometimes researchers draw upon the conceptual frameworks of other researchers. When a researcher’s conceptual framework closely aligns with an existing framework, the discussion may be brief. For example, Ghee et al. (2016) referred to portions of SCCT as their conceptual framework to explain the significance of their work on students’ self-efficacy and career interests. Because the authors’ conceptualization of this phenomenon aligned with a previously described framework, they briefly mentioned the conceptual framework and provided additional citations that provided more detail for the readers.

Within both the BER and the broader DBER communities, conceptual frameworks have been used to describe different constructs. For example, some researchers have used the term “conceptual framework” to describe students’ conceptual understandings of a biological phenomenon. This is distinct from a researcher’s conceptual framework of the educational phenomenon under investigation, which may also need to be explicitly described in the article. Other studies have presented a research logic model or flowchart of the research design as a conceptual framework. These constructions can be quite valuable in helping readers understand the data-collection and analysis process. However, a model depicting the study design does not serve the same role as a conceptual framework. Researchers need to avoid conflating these constructs by differentiating the researchers’ conceptual framework that guides the study from the research design, when applicable.

Explicitly describing conceptual frameworks is essential in depicting the focus of the study. We have found that being explicit in a conceptual framework means using accepted terminology, referencing prior work, and clearly noting connections between terms. This description can also highlight gaps in the literature or suggest potential contributions to the field of study. A well-elucidated conceptual framework can suggest additional studies that may be warranted. This can also spur other researchers to consider how they would approach the examination of a phenomenon and could result in a revised conceptual framework.

It can be challenging to create conceptual frameworks, but they are important. Below are two resources that could be helpful in constructing and presenting conceptual frameworks in educational research:

• Maxwell, J. A. (2012). Qualitative research design: An interactive approach (3rd ed.). Los Angeles, CA: Sage. Chapter 3 in this book describes how to construct conceptual frameworks.
• Ravitch, S. M., & Riggan, M. (2016). Reason & rigor: How conceptual frameworks guide research . Los Angeles, CA: Sage. This book explains how conceptual frameworks guide the research questions, data collection, data analyses, and interpretation of results.

CONCLUDING THOUGHTS

Literature reviews, theoretical frameworks, and conceptual frameworks are all important in DBER and BER. Robust literature reviews reinforce the importance of a study. Theoretical frameworks connect the study to the base of knowledge in educational theory and specify the researcher’s assumptions. Conceptual frameworks allow researchers to explicitly describe their conceptualization of the relationships among the components of the phenomenon under study. Table 1 provides a general overview of these components in order to assist biology education researchers in thinking about these elements.

It is important to emphasize that these different elements are intertwined. When these elements are aligned and complement one another, the study is coherent, and the study findings contribute to knowledge in the field. When literature reviews, theoretical frameworks, and conceptual frameworks are disconnected from one another, the study suffers. The point of the study is lost, suggested findings are unsupported, or important conclusions are invisible to the researcher. In addition, this misalignment may be costly in terms of time and money.

Conducting a literature review, selecting a theoretical framework, and building a conceptual framework are some of the most difficult elements of a research study. It takes time to understand the relevant research, identify a theoretical framework that provides important insights into the study, and formulate a conceptual framework that organizes the finding. In the research process, there is often a constant back and forth among these elements as the study evolves. With an ongoing refinement of the review of literature, clarification of the theoretical framework, and articulation of a conceptual framework, a sound study can emerge that makes a contribution to the field. This is the goal of BER and education research.

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Theories are formulated to explain, predict, and understand phenomena and, in many cases, to challenge and extend existing knowledge within the limits of critical bounded assumptions or predictions of behavior. The theoretical framework is the structure that can hold or support a theory of a research study. The theoretical framework encompasses not just the theory, but the narrative explanation about how the researcher engages in using the theory and its underlying assumptions to investigate the research problem. It is the structure of your paper that summarizes concepts, ideas, and theories derived from prior research studies and which was synthesized in order to form a conceptual basis for your analysis and interpretation of meaning found within your research.

Abend, Gabriel. "The Meaning of Theory." Sociological Theory 26 (June 2008): 173–199; Kivunja, Charles. "Distinguishing between Theory, Theoretical Framework, and Conceptual Framework: A Systematic Review of Lessons from the Field." International Journal of Higher Education 7 (December 2018): 44-53; Swanson, Richard A. Theory Building in Applied Disciplines . San Francisco, CA: Berrett-Koehler Publishers 2013; Varpio, Lara, Elise Paradis, Sebastian Uijtdehaage, and Meredith Young. "The Distinctions between Theory, Theoretical Framework, and Conceptual Framework." Academic Medicine 95 (July 2020): 989-994.

Importance of Theory and a Theoretical Framework

Theories can be unfamiliar to the beginning researcher because they are rarely applied in high school social studies curriculum and, as a result, can come across as unfamiliar and imprecise when first introduced as part of a writing assignment. However, in their most simplified form, a theory is simply a set of assumptions or predictions about something you think will happen based on existing evidence and that can be tested to see if those outcomes turn out to be true. Of course, it is slightly more deliberate than that, therefore, summarized from Kivunja (2018, p. 46), here are the essential characteristics of a theory.

• It is logical and coherent
• It has clear definitions of terms or variables, and has boundary conditions [i.e., it is not an open-ended statement]
• It has a domain where it applies
• It has clearly described relationships among variables
• It describes, explains, and makes specific predictions
• It comprises of concepts, themes, principles, and constructs
• It must have been based on empirical data [i.e., it is not a guess]
• It must have made claims that are subject to testing, been tested and verified
• It must be clear and concise
• Its assertions or predictions must be different and better than those in existing theories
• Its predictions must be general enough to be applicable to and understood within multiple contexts
• Its assertions or predictions are relevant, and if applied as predicted, will result in the predicted outcome
• The assertions and predictions are not immutable, but subject to revision and improvement as researchers use the theory to make sense of phenomena
• Its concepts and principles explain what is going on and why
• Its concepts and principles are substantive enough to enable us to predict a future

Given these characteristics, a theory can best be understood as the foundation from which you investigate assumptions or predictions derived from previous studies about the research problem, but in a way that leads to new knowledge and understanding as well as, in some cases, discovering how to improve the relevance of the theory itself or to argue that the theory is outdated and a new theory needs to be formulated based on new evidence.

A theoretical framework consists of concepts and, together with their definitions and reference to relevant scholarly literature, existing theory that is used for your particular study. The theoretical framework must demonstrate an understanding of theories and concepts that are relevant to the topic of your research paper and that relate to the broader areas of knowledge being considered.

The theoretical framework is most often not something readily found within the literature . You must review course readings and pertinent research studies for theories and analytic models that are relevant to the research problem you are investigating. The selection of a theory should depend on its appropriateness, ease of application, and explanatory power.

The theoretical framework strengthens the study in the following ways :

• An explicit statement of  theoretical assumptions permits the reader to evaluate them critically.
• The theoretical framework connects the researcher to existing knowledge. Guided by a relevant theory, you are given a basis for your hypotheses and choice of research methods.
• Articulating the theoretical assumptions of a research study forces you to address questions of why and how. It permits you to intellectually transition from simply describing a phenomenon you have observed to generalizing about various aspects of that phenomenon.
• Having a theory helps you identify the limits to those generalizations. A theoretical framework specifies which key variables influence a phenomenon of interest and highlights the need to examine how those key variables might differ and under what circumstances.
• The theoretical framework adds context around the theory itself based on how scholars had previously tested the theory in relation their overall research design [i.e., purpose of the study, methods of collecting data or information, methods of analysis, the time frame in which information is collected, study setting, and the methodological strategy used to conduct the research].

By virtue of its applicative nature, good theory in the social sciences is of value precisely because it fulfills one primary purpose: to explain the meaning, nature, and challenges associated with a phenomenon, often experienced but unexplained in the world in which we live, so that we may use that knowledge and understanding to act in more informed and effective ways.

The Conceptual Framework. College of Education. Alabama State University; Corvellec, Hervé, ed. What is Theory?: Answers from the Social and Cultural Sciences . Stockholm: Copenhagen Business School Press, 2013; Asher, Herbert B. Theory-Building and Data Analysis in the Social Sciences . Knoxville, TN: University of Tennessee Press, 1984; Drafting an Argument. Writing@CSU. Colorado State University; Kivunja, Charles. "Distinguishing between Theory, Theoretical Framework, and Conceptual Framework: A Systematic Review of Lessons from the Field." International Journal of Higher Education 7 (2018): 44-53; Omodan, Bunmi Isaiah. "A Model for Selecting Theoretical Framework through Epistemology of Research Paradigms." African Journal of Inter/Multidisciplinary Studies 4 (2022): 275-285; Ravitch, Sharon M. and Matthew Riggan. Reason and Rigor: How Conceptual Frameworks Guide Research . Second edition. Los Angeles, CA: SAGE, 2017; Trochim, William M.K. Philosophy of Research. Research Methods Knowledge Base. 2006; Jarvis, Peter. The Practitioner-Researcher. Developing Theory from Practice . San Francisco, CA: Jossey-Bass, 1999.

Strategies for Developing the Theoretical Framework

I.  Developing the Framework

Here are some strategies to develop of an effective theoretical framework:

• Examine your thesis title and research problem . The research problem anchors your entire study and forms the basis from which you construct your theoretical framework.
• Brainstorm about what you consider to be the key variables in your research . Answer the question, "What factors contribute to the presumed effect?"
• Review related literature to find how scholars have addressed your research problem. Identify the assumptions from which the author(s) addressed the problem.
• List  the constructs and variables that might be relevant to your study. Group these variables into independent and dependent categories.
• Review key social science theories that are introduced to you in your course readings and choose the theory that can best explain the relationships between the key variables in your study [note the Writing Tip on this page].
• Discuss the assumptions or propositions of this theory and point out their relevance to your research.

A theoretical framework is used to limit the scope of the relevant data by focusing on specific variables and defining the specific viewpoint [framework] that the researcher will take in analyzing and interpreting the data to be gathered. It also facilitates the understanding of concepts and variables according to given definitions and builds new knowledge by validating or challenging theoretical assumptions.

II.  Purpose

Think of theories as the conceptual basis for understanding, analyzing, and designing ways to investigate relationships within social systems. To that end, the following roles served by a theory can help guide the development of your framework.

• Means by which new research data can be interpreted and coded for future use,
• Response to new problems that have no previously identified solutions strategy,
• Means for identifying and defining research problems,
• Means for prescribing or evaluating solutions to research problems,
• Ways of discerning certain facts among the accumulated knowledge that are important and which facts are not,
• Means of giving old data new interpretations and new meaning,
• Means by which to identify important new issues and prescribe the most critical research questions that need to be answered to maximize understanding of the issue,
• Means of providing members of a professional discipline with a common language and a frame of reference for defining the boundaries of their profession, and
• Means to guide and inform research so that it can, in turn, guide research efforts and improve professional practice.

Adapted from: Torraco, R. J. “Theory-Building Research Methods.” In Swanson R. A. and E. F. Holton III , editors. Human Resource Development Handbook: Linking Research and Practice . (San Francisco, CA: Berrett-Koehler, 1997): pp. 114-137; Jacard, James and Jacob Jacoby. Theory Construction and Model-Building Skills: A Practical Guide for Social Scientists . New York: Guilford, 2010; Ravitch, Sharon M. and Matthew Riggan. Reason and Rigor: How Conceptual Frameworks Guide Research . Second edition. Los Angeles, CA: SAGE, 2017; Sutton, Robert I. and Barry M. Staw. “What Theory is Not.” Administrative Science Quarterly 40 (September 1995): 371-384.

Structure and Writing Style

The theoretical framework may be rooted in a specific theory , in which case, your work is expected to test the validity of that existing theory in relation to specific events, issues, or phenomena. Many social science research papers fit into this rubric. For example, Peripheral Realism Theory, which categorizes perceived differences among nation-states as those that give orders, those that obey, and those that rebel, could be used as a means for understanding conflicted relationships among countries in Africa. A test of this theory could be the following: Does Peripheral Realism Theory help explain intra-state actions, such as, the disputed split between southern and northern Sudan that led to the creation of two nations?

However, you may not always be asked by your professor to test a specific theory in your paper, but to develop your own framework from which your analysis of the research problem is derived . Based upon the above example, it is perhaps easiest to understand the nature and function of a theoretical framework if it is viewed as an answer to two basic questions:

• What is the research problem/question? [e.g., "How should the individual and the state relate during periods of conflict?"]
• Why is your approach a feasible solution? [i.e., justify the application of your choice of a particular theory and explain why alternative constructs were rejected. I could choose instead to test Instrumentalist or Circumstantialists models developed among ethnic conflict theorists that rely upon socio-economic-political factors to explain individual-state relations and to apply this theoretical model to periods of war between nations].

The answers to these questions come from a thorough review of the literature and your course readings [summarized and analyzed in the next section of your paper] and the gaps in the research that emerge from the review process. With this in mind, a complete theoretical framework will likely not emerge until after you have completed a thorough review of the literature .

Just as a research problem in your paper requires contextualization and background information, a theory requires a framework for understanding its application to the topic being investigated. When writing and revising this part of your research paper, keep in mind the following:

• Clearly describe the framework, concepts, models, or specific theories that underpin your study . This includes noting who the key theorists are in the field who have conducted research on the problem you are investigating and, when necessary, the historical context that supports the formulation of that theory. This latter element is particularly important if the theory is relatively unknown or it is borrowed from another discipline.
• Position your theoretical framework within a broader context of related frameworks, concepts, models, or theories . As noted in the example above, there will likely be several concepts, theories, or models that can be used to help develop a framework for understanding the research problem. Therefore, note why the theory you've chosen is the appropriate one.
• The present tense is used when writing about theory. Although the past tense can be used to describe the history of a theory or the role of key theorists, the construction of your theoretical framework is happening now.
• You should make your theoretical assumptions as explicit as possible . Later, your discussion of methodology should be linked back to this theoretical framework.
• Don’t just take what the theory says as a given! Reality is never accurately represented in such a simplistic way; if you imply that it can be, you fundamentally distort a reader's ability to understand the findings that emerge. Given this, always note the limitations of the theoretical framework you've chosen [i.e., what parts of the research problem require further investigation because the theory inadequately explains a certain phenomena].

The Conceptual Framework. College of Education. Alabama State University; Conceptual Framework: What Do You Think is Going On? College of Engineering. University of Michigan; Drafting an Argument. Writing@CSU. Colorado State University; Lynham, Susan A. “The General Method of Theory-Building Research in Applied Disciplines.” Advances in Developing Human Resources 4 (August 2002): 221-241; Tavallaei, Mehdi and Mansor Abu Talib. "A General Perspective on the Role of Theory in Qualitative Research." Journal of International Social Research 3 (Spring 2010); Ravitch, Sharon M. and Matthew Riggan. Reason and Rigor: How Conceptual Frameworks Guide Research . Second edition. Los Angeles, CA: SAGE, 2017; Reyes, Victoria. Demystifying the Journal Article. Inside Higher Education; Trochim, William M.K. Philosophy of Research. Research Methods Knowledge Base. 2006; Weick, Karl E. “The Work of Theorizing.” In Theorizing in Social Science: The Context of Discovery . Richard Swedberg, editor. (Stanford, CA: Stanford University Press, 2014), pp. 177-194.

Writing Tip

Borrowing Theoretical Constructs from Other Disciplines

An increasingly important trend in the social and behavioral sciences is to think about and attempt to understand research problems from an interdisciplinary perspective. One way to do this is to not rely exclusively on the theories developed within your particular discipline, but to think about how an issue might be informed by theories developed in other disciplines. For example, if you are a political science student studying the rhetorical strategies used by female incumbents in state legislature campaigns, theories about the use of language could be derived, not only from political science, but linguistics, communication studies, philosophy, psychology, and, in this particular case, feminist studies. Building theoretical frameworks based on the postulates and hypotheses developed in other disciplinary contexts can be both enlightening and an effective way to be more engaged in the research topic.

CohenMiller, A. S. and P. Elizabeth Pate. "A Model for Developing Interdisciplinary Research Theoretical Frameworks." The Qualitative Researcher 24 (2019): 1211-1226; Frodeman, Robert. The Oxford Handbook of Interdisciplinarity . New York: Oxford University Press, 2010.

Another Writing Tip

Don't Undertheorize!

Do not leave the theory hanging out there in the introduction never to be mentioned again. Undertheorizing weakens your paper. The theoretical framework you describe should guide your study throughout the paper. Be sure to always connect theory to the review of pertinent literature and to explain in the discussion part of your paper how the theoretical framework you chose supports analysis of the research problem or, if appropriate, how the theoretical framework was found to be inadequate in explaining the phenomenon you were investigating. In that case, don't be afraid to propose your own theory based on your findings.

Yet Another Writing Tip

What's a Theory? What's a Hypothesis?

The terms theory and hypothesis are often used interchangeably in newspapers and popular magazines and in non-academic settings. However, the difference between theory and hypothesis in scholarly research is important, particularly when using an experimental design. A theory is a well-established principle that has been developed to explain some aspect of the natural world. Theories arise from repeated observation and testing and incorporates facts, laws, predictions, and tested assumptions that are widely accepted [e.g., rational choice theory; grounded theory; critical race theory].

A hypothesis is a specific, testable prediction about what you expect to happen in your study. For example, an experiment designed to look at the relationship between study habits and test anxiety might have a hypothesis that states, "We predict that students with better study habits will suffer less test anxiety." Unless your study is exploratory in nature, your hypothesis should always explain what you expect to happen during the course of your research.

The key distinctions are:

• A theory predicts events in a broad, general context;  a hypothesis makes a specific prediction about a specified set of circumstances.
• A theory has been extensively tested and is generally accepted among a set of scholars; a hypothesis is a speculative guess that has yet to be tested.

Cherry, Kendra. Introduction to Research Methods: Theory and Hypothesis. About.com Psychology; Gezae, Michael et al. Welcome Presentation on Hypothesis. Slideshare presentation.

Still Yet Another Writing Tip

Be Prepared to Challenge the Validity of an Existing Theory

Theories are meant to be tested and their underlying assumptions challenged; they are not rigid or intransigent, but are meant to set forth general principles for explaining phenomena or predicting outcomes. Given this, testing theoretical assumptions is an important way that knowledge in any discipline develops and grows. If you're asked to apply an existing theory to a research problem, the analysis will likely include the expectation by your professor that you should offer modifications to the theory based on your research findings.

Indications that theoretical assumptions may need to be modified can include the following:

• Your findings suggest that the theory does not explain or account for current conditions or circumstances or the passage of time,
• The study reveals a finding that is incompatible with what the theory attempts to explain or predict, or
• Your analysis reveals that the theory overly generalizes behaviors or actions without taking into consideration specific factors revealed from your analysis [e.g., factors related to culture, nationality, history, gender, ethnicity, age, geographic location, legal norms or customs , religion, social class, socioeconomic status, etc.].

Philipsen, Kristian. "Theory Building: Using Abductive Search Strategies." In Collaborative Research Design: Working with Business for Meaningful Findings . Per Vagn Freytag and Louise Young, editors. (Singapore: Springer Nature, 2018), pp. 45-71; Shepherd, Dean A. and Roy Suddaby. "Theory Building: A Review and Integration." Journal of Management 43 (2017): 59-86.

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• Roberta Heale 1 ,
• Helen Noble 2
• 1 Laurentian University , School of Nursing , Sudbury , Ontario , Canada
• 2 Queens University Belfast , School of Nursing and Midwifery , Belfast , UK
• Correspondence to Dr Roberta Heale, School of Nursing, Laurentian University, Ramsey Lake Road, Sudbury, P3E2C6, Canada; rheale{at}laurentian.ca

https://doi.org/10.1136/ebnurs-2019-103077

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Often the most difficult part of a research study is preparing the proposal based around a theoretical or philosophical framework. Graduate students ‘…express confusion, a lack of knowledge, and frustration with the challenge of choosing a theoretical framework and understanding how to apply it’. 1 However, the importance in understanding and applying a theoretical framework in research cannot be overestimated.

The choice of a theoretical framework for a research study is often a reflection of the researcher’s ontological (nature of being) and epistemological (theory of knowledge) perspective. We will not delve into these concepts, or personal philosophy in this article. Rather we will focus on how a theoretical framework can be integrated into research.

The theoretical framework is a blueprint for your research project 1 and serves several purposes. It informs the problem you have identified, the purpose and significance of your research demonstrating how your research fits with what is already known (relationship to existing theory and research). This provides a basis for your research questions, the literature review and the methodology and analysis that you choose. 1 Evidence of your chosen theoretical framework should be visible in every aspect of your research and should demonstrate the contribution of this research to knowledge. 2

What is a theory?

A theory is an explanation of a concept or an abstract idea of a phenomenon. An example of a theory is Bandura’s middle range theory of self-efficacy, 3 or the level of confidence one has in achieving a goal. Self-efficacy determines the coping behaviours that a person will exhibit when facing obstacles. Those who have high self-efficacy are likely to apply adequate effort leading to successful outcomes, while those with low self-efficacy are more likely to give up earlier and ultimately fail. Any research that is exploring concepts related to self-efficacy or the ability to manage difficult life situations might apply Bandura’s theoretical framework to their study.

Using a theoretical framework in a research study

Example 1: the big five theoretical framework.

The first example includes research which integrates the ‘Big Five’, a theoretical framework that includes concepts related to teamwork. These include team leadership, mutual performance monitoring, backup behaviour, adaptability and team orientation. 4 In order to conduct research incorporating a theoretical framework, the concepts need to be defined according to a frame of reference. This provides a means to understand the theoretical framework as it relates to a specific context and provides a mechanism for measurement of the concepts.

In this example, the concepts of the Big Five were given a conceptual definition, that provided a broad meaning and then an operational definition, which was more concrete. 4 From here, a survey was developed that reflected the operational definitions related to teamwork in nursing: the Nursing Teamwork Survey (NTS). 5 In this case, the concepts used in the theoretical framework, the Big Five, were the used to develop a survey specific to teamwork in nursing.

The NTS was used in research of nurses at one hospital in northeastern Ontario. Survey questions were grouped into subscales for analysis, that reflected the concepts of the Big Five. 6 For example, one finding of this study was that the nurses from the surgical unit rated the items in the subscale of ’team leadership' (one of the concepts in the Big Five) significantly lower than in the other units. The researchers looked back to the definition of this concept in the Big Five in their interpretation of the findings. Since the definition included a person(s) who has the leadership skills to facilitate teamwork among the nurses on the unit, the conclusion in this study was that the surgical unit lacked a mentor, or facilitator for teamwork. In this way, the theory of teamwork was presented through a set of concepts in a theoretical framework. The Theoretical Framework (TF)was the foundation for development of a survey related to a specific context, used to measure each of the concepts within the TF. Then, the analysis and results circled back to the concepts within the TF and provided a guide for the discussion and conclusions arising from the research.

Example 2: the Health Decisions Model

In another study which explored adherence to intravenous chemotherapy in African-American and Caucasian Women with early stage breast cancer, an adapted version of the Health Decisions Model (HDM) was used as the theoretical basis for the study. 7 The HDM, a revised version of the Health Belief Model, incorporates some aspects of the Health Belief Model and factors relating to patient preferences. 8 The HDM consists of six interrelated constituents that might predict how well a person adheres to a health decision. These include sociodemographic, social interaction, experience, knowledge, general and specific health beliefs and patient preferences, and are clearly defined. The HDM model was used to explore factors which might influence adherence to chemotherapy in women with breast cancer. Sociodemographic, social interaction, knowledge, personal experience and specific health beliefs were used as predictors of adherence to chemotherapy.

The findings were reported using the theoretical framework to discuss results. The study found that delay to treatment, health insurance, depression and symptom severity were predictors to starting chemotherapy which could potentially be adapted with clinical interventions. The findings from the study contribute to the existing body of literature related to cancer nursing.

Example 3: the nursing role effectiveness model

In this final example, research was conducted to determine the nursing processes that were associated with unexpected intensive care unit admissions. 9 The framework was the Nursing Role Effectiveness Model. In this theoretical framework, the concepts within Donabedian’s Quality Framework of Structure, Process and Outcome were each defined according to nursing practice. 10 11  Processes defined in the Nursing Role Effectiveness Model were used to identify the nursing process variables that were measured in the study.

A theoretical framework should be logically presented and represent the concepts, variables and relationships related to your research study, in order to clearly identify what will be examined, described or measured. It involves reading the literature and identifying a research question(s) while clearly defining and identifying the existing relationship between concepts and theories (related to your research questions[s] in the literature). You must then identify what you will examine or explore in relation to the concepts of the theoretical framework. Once you present your findings using the theoretical framework you will be able to articulate how your study relates to and may potentially advance your chosen theory and add to knowledge.

• Kalisch BJ ,
• Parent M , et al
• Strickland OL ,
• Dalton JA , et al
• Eraker SA ,
• Kirscht JP ,
• Lightfoot N , et al
• Harrison MB ,
• Laschinger H , et al

Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

Competing interests None declared.

Provenance and peer review Not commissioned; internally peer reviewed.

Patient and public involvement Not required.

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What is a Theoretical Framework? | A Step-by-Step Guide

Published on 14 February 2020 by Shona McCombes . Revised on 10 October 2022.

A theoretical framework is a foundational review of existing theories that serves as a roadmap for developing the arguments you will use in your own work.

Theories are developed by researchers to explain phenomena, draw connections, and make predictions. In a theoretical framework, you explain the existing theories that support your research, showing that your work is grounded in established ideas.

In other words, your theoretical framework justifies and contextualises your later research, and it’s a crucial first step for your research paper , thesis, or dissertation . A well-rounded theoretical framework sets you up for success later on in your research and writing process.

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Table of contents

Why do you need a theoretical framework, how to write a theoretical framework, structuring your theoretical framework, example of a theoretical framework, frequently asked questions about theoretical frameworks.

Before you start your own research, it’s crucial to familiarise yourself with the theories and models that other researchers have already developed. Your theoretical framework is your opportunity to present and explain what you’ve learned, situated within your future research topic.

There’s a good chance that many different theories about your topic already exist, especially if the topic is broad. In your theoretical framework, you will evaluate, compare, and select the most relevant ones.

By “framing” your research within a clearly defined field, you make the reader aware of the assumptions that inform your approach, showing the rationale behind your choices for later sections, like methodology and discussion . This part of your dissertation lays the foundations that will support your analysis, helping you interpret your results and make broader generalisations .

• In literature , a scholar using postmodernist literary theory would analyse The Great Gatsby differently than a scholar using Marxist literary theory.
• In psychology , a behaviourist approach to depression would involve different research methods and assumptions than a psychoanalytic approach.
• In economics , wealth inequality would be explained and interpreted differently based on a classical economics approach than based on a Keynesian economics one.

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To create your own theoretical framework, you can follow these three steps:

• Identifying your key concepts
• Evaluating and explaining relevant theories
• Showing how your research fits into existing research

1. Identify your key concepts

The first step is to pick out the key terms from your problem statement and research questions . Concepts often have multiple definitions, so your theoretical framework should also clearly define what you mean by each term.

To investigate this problem, you have identified and plan to focus on the following problem statement, objective, and research questions:

Problem : Many online customers do not return to make subsequent purchases.

Objective : To increase the quantity of return customers.

Research question : How can the satisfaction of company X’s online customers be improved in order to increase the quantity of return customers?

2. Evaluate and explain relevant theories

By conducting a thorough literature review , you can determine how other researchers have defined these key concepts and drawn connections between them. As you write your theoretical framework, your aim is to compare and critically evaluate the approaches that different authors have taken.

After discussing different models and theories, you can establish the definitions that best fit your research and justify why. You can even combine theories from different fields to build your own unique framework if this better suits your topic.

Make sure to at least briefly mention each of the most important theories related to your key concepts. If there is a well-established theory that you don’t want to apply to your own research, explain why it isn’t suitable for your purposes.

3. Show how your research fits into existing research

Apart from summarising and discussing existing theories, your theoretical framework should show how your project will make use of these ideas and take them a step further.

You might aim to do one or more of the following:

• Test whether a theory holds in a specific, previously unexamined context
• Use an existing theory as a basis for interpreting your results
• Critique or challenge a theory
• Combine different theories in a new or unique way

A theoretical framework can sometimes be integrated into a literature review chapter , but it can also be included as its own chapter or section in your dissertation. As a rule of thumb, if your research involves dealing with a lot of complex theories, it’s a good idea to include a separate theoretical framework chapter.

There are no fixed rules for structuring your theoretical framework, but it’s best to double-check with your department or institution to make sure they don’t have any formatting guidelines. The most important thing is to create a clear, logical structure. There are a few ways to do this:

• Draw on your research questions, structuring each section around a question or key concept
• Organise by theory cluster
• Organise by date

As in all other parts of your research paper , thesis, or dissertation , make sure to properly cite your sources to avoid plagiarism .

To get a sense of what this part of your thesis or dissertation might look like, take a look at our full example .

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While a theoretical framework describes the theoretical underpinnings of your work based on existing research, a conceptual framework allows you to draw your own conclusions, mapping out the variables you may use in your study and the interplay between them.

A literature review and a theoretical framework are not the same thing and cannot be used interchangeably. While a theoretical framework describes the theoretical underpinnings of your work, a literature review critically evaluates existing research relating to your topic. You’ll likely need both in your dissertation .

A theoretical framework can sometimes be integrated into a  literature review chapter , but it can also be included as its own chapter or section in your dissertation . As a rule of thumb, if your research involves dealing with a lot of complex theories, it’s a good idea to include a separate theoretical framework chapter.

A literature review is a survey of scholarly sources (such as books, journal articles, and theses) related to a specific topic or research question .

It is often written as part of a dissertation , thesis, research paper , or proposal .

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Organizing Academic Research Papers: Theoretical Framework

• Purpose of Guide
• Design Flaws to Avoid
• Glossary of Research Terms
• Narrowing a Topic Idea
• Broadening a Topic Idea
• Extending the Timeliness of a Topic Idea
• Academic Writing Style
• Choosing a Title
• Making an Outline
• Paragraph Development
• Executive Summary
• Background Information
• The Research Problem/Question
• Theoretical Framework
• Citation Tracking
• Content Alert Services
• Evaluating Sources
• Primary Sources
• Secondary Sources
• Tertiary Sources
• What Is Scholarly vs. Popular?
• Qualitative Methods
• Quantitative Methods
• Using Non-Textual Elements
• Limitations of the Study
• Common Grammar Mistakes
• Avoiding Plagiarism
• Footnotes or Endnotes?
• Further Readings
• Annotated Bibliography
• Dealing with Nervousness
• Using Visual Aids
• Grading Someone Else's Paper
• How to Manage Group Projects
• Multiple Book Review Essay
• Reviewing Collected Essays
• About Informed Consent
• Writing Field Notes
• Writing a Policy Memo
• Writing a Research Proposal
• Acknowledgements

Theories are formulated to explain, predict, and understand phenomena and, in many cases, to challenge and extend existing knowledge, within the limits of the critical bounding assumptions. The theoretical framework is the structure that can hold or support a theory of a research study. The theoretical framework introduces and describes the theory which explains why the research problem under study exists.

Importance of Theory

A theoretical framework consists of concepts, together with their definitions, and existing theory/theories that are used for your particular study. The theoretical framework must demonstrate an understanding of theories and concepts that are relevant to the topic of your  research paper and that will relate it to the broader fields of knowledge in the class you are taking.

The theoretical framework is not something that is found readily available in the literature . You must review course readings and pertinent research literature for theories and analytic models that are relevant to the research problem you are investigating. The selection of a theory should depend on its appropriateness, ease of application, and explanatory power.

The theoretical framework strengthens the study in the following ways .

• An explicit statement of  theoretical assumptions permits the reader to evaluate them critically.
• The theoretical framework connects the researcher to existing knowledge. Guided by a relevant theory, you are given a basis for your hypotheses and choice of research methods.
• Articulating the theoretical assumptions of a research study forces you to address questions of why and how. It permits you to move from simply describing a phenomenon observed to generalizing about various aspects of that phenomenon.
• Having a theory helps you to identify the limits to those generalizations. A theoretical framework specifies which key variables influence a phenomenon of interest. It alerts you to examine how those key variables might differ and under what circumstances.

By virtue of its application nature, good theory in the social sciences is of value precisely because it fulfills one primary purpose: to explain the meaning, nature, and challenges of a phenomenon, often experienced but unexplained in the world in which we live, so that we may use that knowledge and understanding to act in more informed and effective ways.

The Conceptual Framework. College of Education. Alabama State University; Drafting an Argument . Writing@CSU. Colorado State University; Trochim, William M.K. Philosophy of Research. Research Methods Knowledge Base. 2006.

Strategies for Developing the Theoretical Framework

I.  Developing the Framework

Here are some strategies to develop of an effective theoretical framework:

• Examine your thesis title and research problem . The research problem anchors your entire study and forms the basis from which you construct your theoretical framework.
• Brainstorm on what you consider to be the key variables in your research . Answer the question, what factors contribute to the presumed effect?
• Review related literature to find answers to your research question.
• List  the constructs and variables that might be relevant to your study. Group these variables into independent and dependent categories.
• Review the key social science theories that are introduced to you in your course readings and choose the theory or theories that can best explain the relationships between the key variables in your study [note the Writing Tip on this page].
• Discuss the assumptions or propositions of this theory and point out their relevance to your research.

A theoretical framework is used to limit the scope of the relevant data by focusing on specific variables and defining the specific viewpoint (framework) that the researcher will take in analyzing and interpreting the data to be gathered, understanding concepts and variables according to the given definitions, and building knowledge by validating or challenging theoretical assumptions.

II.  Purpose

Think of theories as the conceptual basis for understanding, analyzing, and designing ways to investigate relationships within social systems. To the end, the following roles served by a theory can help guide the development of your framework.*

• Means by which new research data can be interpreted and coded for future use,
• Response to new problems that have no previously identified solutions strategy,
• Means for identifying and defining research problems,
• Means for prescribing or evaluating solutions to research problems,
• Way of telling us that certain facts among the accumulated knowledge are important and which facts are not,
• Means of giving old data new interpretations and new meaning,
• Means by which to identify important new issues and prescribe the most critical research questions that need to be answered to maximize understanding of the issue,
• Means of providing members of a professional discipline with a common language and a frame of reference for defining boundaries of their profession, and
• Means to guide and inform research so that it can, in turn, guide research efforts and improve professional practice.

*Adapted from: Torraco, R. J. “Theory-Building Research Methods.” In Swanson R. A. and E. F. Holton III , editors. Human Resource Development Handbook: Linking Research and Practice . (San Francisco, CA: Berrett-Koehler, 1997): pp. 114-137; Sutton, Robert I. and Barry M. Staw. “What Theory is Not.” Administrative Science Quarterly 40 (September 1995): 371-384.

Structure and Writing Style

The theoretical framework may be rooted in a specific theory , in which case, you are expected to test the validity of an existing theory in relation to specific events, issues, or phenomena. Many social science research papers fit into this rubric. For example, Peripheral Realism theory, which categorizes perceived differences between nation-states as those that give orders, those that obey, and those that rebel, could be used as a means for understanding conflicted relationships among countries in Africa. A test of this theory could be the following: Does Peripheral Realism theory help explain intra-state actions, such as, the growing split between southern and northern Sudan that may likely lead to the creation of two nations?

However, you may not always be asked by your professor to test a specific theory in your paper, but to develop your own framework from which your analysis of the research problem is derived . Given this, it is perhaps easiest to understand the nature and function of a theoretical framework if it is viewed as the answer to two basic questions:

• What is the research problem/question? [e.g., "How should the individual and the state relate during periods of conflict?"]
• Why is your approach a feasible solution? [I could choose to test Instrumentalist or Circumstantialists models developed among Ethnic Conflict Theorists that rely upon socio-economic-political factors to explain individual-state relations and to apply this theoretical model to periods of war between nations].

The answers to these questions come from a thorough review of the literature and your course readings [summarized and analyzed in the next section of your paper] and the gaps in the research that emerge from the review process. With this in mind, a complete theoretical framework will likely not emerge until after you have completed a thorough review of the literature .

In writing this part of your research paper, keep in mind the following:

• Clearly describe the framework, concepts, models, or specific theories that underpin your study . This includes noting who the key theorists are in the field who have conducted research on the problem you are investigating and, when necessary, the historical context that supports the formulation of that theory. This latter element is particularly important if the theory is relatively unknown or it is borrowed from another discipline.
• Position your theoretical framework within a broader context of related frameworks , concepts, models, or theories . There will likely be several concepts, theories, or models that can be used to help develop a framework for understanding the research problem. Therefore, note why the framework you've chosen is the appropriate one.
• The present tense is used when writing about theory.
• You should make your theoretical assumptions as explicit as possible . Later, your discussion of methodology should be linked back to this theoretical framework.
• Don’t just take what the theory says as a given! Reality is never accurately represented in such a simplistic way; if you imply that it can be, you fundamentally distort a reader's ability to understand the findings that emerge. Given this, always note the limitiations of the theoretical framework you've chosen [i.e., what parts of the research problem require further investigation because the theory does not explain a certain phenomena].

The Conceptual Framework. College of Education. Alabama State University; Conceptual Framework: What Do You Think is Going On? College of Engineering. University of Michigan; Drafting an Argument . Writing@CSU. Colorado State University; Lynham, Susan A. “The General Method of Theory-Building Research in Applied Disciplines.” Advances in Developing Human Resources 4 (August 2002): 221-241; Tavallaei, Mehdi and Mansor Abu Talib. A General Perspective on the Role of Theory in Qualitative Research. Journal of International Social Research 3 (Spring 2010); Trochim, William M.K. Philosophy of Research. Research Methods Knowledge Base. 2006.

Writing Tip

Borrowing Theoretical Constructs from Elsewhere

A growing and increasingly important trend in the social sciences is to think about and attempt to understand specific research problems from an interdisciplinary perspective. One way to do this is to not rely exclusively on the theories you've read about in a particular class, but to think about how an issue might be informed by theories developed in other disciplines. For example, if you are a political science student studying the rhetorical strategies used by female incumbants in state legislature campaigns, theories about the use of language could be derived, not only from political science, but linguistics, communication studies, philosophy, psychology, and, in this particular case, feminist studies. Building theoretical frameworks based on the postulates and hypotheses developed in other disciplinary contexts can be both enlightening and an effective way to be fully engaged in the research topic.

Another Writing Tip

Don't Undertheorize!

Never leave the theory hanging out there in the Introduction never to be mentioned again. Undertheorizing weakens your paper. The theoretical framework you introduce should guide your study throughout the paper. Be sure to always connect theory to the analysis and to explain in the discussion part of your paper how the theoretical framework you chose fit the research problem, or if appropriate, was inadequate in explaining the phenomenon you were investigating. In that case, don't be afraid to propose your own theory based on your findings.

Still Another Writing Tip

What's a Theory? What's a Hypothesis?

The terms theory and hypothesis are often used interchangeably in everyday use. However, the difference between them in scholarly research is important, particularly when using an experimental design. A theory is a well-established principle that has been developed to explain some aspect of the natural world. Theories arise from repeated observation and testing and incorporates facts, laws, predictions, and tested hypotheses that are widely accepted [e.g., rational choice theory; grounded theory].

A hypothesis is a specific, testable prediction about what you expect to happen in your study. For example, an experiment designed to look at the relationship between study habits and test anxiety might have a hypothesis that states, "We predict that students with better study habits will suffer less test anxiety." Unless your study is exploratory in nature, your hypothesis should always explain what you expect to happen during the course of your research.

The key distinctions are:

• A theory predicts events in a broad, general context;  a hypothesis makes a specific prediction about a specified set of circumstances.
• A theory has been extensively tested and is generally accepted among scholars; a hypothesis is a speculative guess that has yet to be tested.

Cherry, Kendra. Introduction to Research Methods: Theory and Hypothesis . About.com Psychology; Gezae, Michael et al. Welcome Presentation on Hypothesis . Slideshare presentation.

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Theoretical Framework Example for a Thesis or Dissertation

Published on October 14, 2015 by Sarah Vinz . Revised on July 18, 2023 by Tegan George.

Your theoretical framework defines the key concepts in your research, suggests relationships between them, and discusses relevant theories based on your literature review .

A strong theoretical framework gives your research direction. It allows you to convincingly interpret, explain, and generalize from your findings and show the relevance of your thesis or dissertation topic in your field.

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Table of contents

Sample problem statement and research questions, sample theoretical framework, your theoretical framework, other interesting articles.

Your theoretical framework is based on:

• Your problem statement
• Your research questions
• Your literature review

A new boutique downtown is struggling with the fact that many of their online customers do not return to make subsequent purchases. This is a big issue for the otherwise fast-growing store.Management wants to increase customer loyalty. They believe that improved customer satisfaction will play a major role in achieving their goal of increased return customers.

To investigate this problem, you have zeroed in on the following problem statement, objective, and research questions:

• Problem : Many online customers do not return to make subsequent purchases.
• Objective : To increase the quantity of return customers.
• Research question : How can the satisfaction of the boutique’s online customers be improved in order to increase the quantity of return customers?

The concepts of “customer loyalty” and “customer satisfaction” are clearly central to this study, along with their relationship to the likelihood that a customer will return. Your theoretical framework should define these concepts and discuss theories about the relationship between these variables.

Some sub-questions could include:

• What is the relationship between customer loyalty and customer satisfaction?
• How satisfied and loyal are the boutique’s online customers currently?
• What factors affect the satisfaction and loyalty of the boutique’s online customers?

As the concepts of “loyalty” and “customer satisfaction” play a major role in the investigation and will later be measured, they are essential concepts to define within your theoretical framework .

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Below is a simplified example showing how you can describe and compare theories in your thesis or dissertation . In this example, we focus on the concept of customer satisfaction introduced above.

Customer satisfaction

Thomassen (2003, p. 69) defines customer satisfaction as “the perception of the customer as a result of consciously or unconsciously comparing their experiences with their expectations.” Kotler & Keller (2008, p. 80) build on this definition, stating that customer satisfaction is determined by “the degree to which someone is happy or disappointed with the observed performance of a product in relation to his or her expectations.”

Performance that is below expectations leads to a dissatisfied customer, while performance that satisfies expectations produces satisfied customers (Kotler & Keller, 2003, p. 80).

The definition of Zeithaml and Bitner (2003, p. 86) is slightly different from that of Thomassen. They posit that “satisfaction is the consumer fulfillment response. It is a judgement that a product or service feature, or the product of service itself, provides a pleasurable level of consumption-related fulfillment.” Zeithaml and Bitner’s emphasis is thus on obtaining a certain satisfaction in relation to purchasing.

Thomassen’s definition is the most relevant to the aims of this study, given the emphasis it places on unconscious perception. Although Zeithaml and Bitner, like Thomassen, say that customer satisfaction is a reaction to the experience gained, there is no distinction between conscious and unconscious comparisons in their definition.

The boutique claims in its mission statement that it wants to sell not only a product, but also a feeling. As a result, unconscious comparison will play an important role in the satisfaction of its customers. Thomassen’s definition is therefore more relevant.

Thomassen’s Customer Satisfaction Model

According to Thomassen, both the so-called “value proposition” and other influences have an impact on final customer satisfaction. In his satisfaction model (Fig. 1), Thomassen shows that word-of-mouth, personal needs, past experiences, and marketing and public relations determine customers’ needs and expectations.

These factors are compared to their experiences, with the interplay between expectations and experiences determining a customer’s satisfaction level. Thomassen’s model is important for this study as it allows us to determine both the extent to which the boutique’s customers are satisfied, as well as where improvements can be made.

Figure 1 Customer satisfaction creation 

Of course, you could analyze the concepts more thoroughly and compare additional definitions to each other. You could also discuss the theories and ideas of key authors in greater detail and provide several models to illustrate different concepts.

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Guide for Thesis Research

• Introduction to the Thesis Process
• Project Planning
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Some Articles About Theory

The following are articles that may help you understand the importance of theory as a fundamental aspect of academic research.

• It's Just a Theory
• Literature Reviews, Conceptual Frameworks, and Theoretical Frameworks: Terms, Functions, and Distinctions
• Use of Theoretical Frameworks in Research

Why is theory important?

Theories reflect previous study and analysis that has been conducted in your field.  They propose explanations for phenomena that occur in an area of study. Over time, theories are reexamined, refined, and sometimes discarded in favor of new ones, always with the purpose of providing ever more accurate explanations for the dynamics that operate in our world.

The following quote, taken from John Kuada's book Research Methodology: A Project Guide for University Students , helps to explain the importance of theory when developing a research project:

“Theory provides the language, the concepts, and assumptions that help researchers to make sense of the phenomenon that they seek to investigate. It enables researchers to connect the issues they are investigating to the existing body of knowledge in the area” (Kuada, 2012, p. 64).

A theory can help researchers make predictions about the phenomena they are setting out to study. They can be informative in terms of determining what variables should be observed, as well as how data should be collected, analyzed, and interpreted on the way to presenting and justifying conclusions. 

As a researcher working on a project, it is essential that you be aware of theories that have gained prominence in your field. Think of scholarship as an ongoing conversation. As people publish ideas and develop theories, they help shape that conversation. When you do research and present your findings and ideas, you are joining in on those discussions. You become a contributor. Therefore, it is good to have a sense of what has been said before.

Identify major theories in your field. Be conscious of the fundamental concepts that have guided scholars in your area, and be aware of emerging perspectives and trends. Try to identify a theoretical base from which you can develop your arguments. This will greatly strengthen your positions when the time comes to present your thesis.

Resources About Theory and Theoretical Frameworks

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The Ultimate Guide to Qualitative Research - Part 1: The Basics

• Introduction and overview
• What is qualitative research?
• What is qualitative data?
• Examples of qualitative data
• Qualitative vs. quantitative research
• Mixed methods
• Qualitative research preparation
• Theoretical perspective
• Introduction

Strategies for developing the theoretical framework

• Literature reviews
• Research question
• Conceptual framework
• Conceptual vs. theoretical framework
• Data collection
• Qualitative research methods
• Focus groups
• Observational research
• Case studies
• Ethnographical research
• Ethical considerations
• Confidentiality and privacy
• Power dynamics
• Reflexivity

Theoretical framework

The theoretical perspective provides the broader lens or orientation through which the researcher views the research topic and guides their overall understanding and approach. The theoretical framework, on the other hand, is a more specific and focused framework that connects the theoretical perspective to the data analysis strategy through pre-established theory.

A useful theoretical framework provides a structure for organizing and interpreting the data collected during the research study. Theoretical frameworks provide a specific lens through which the data is examined, allowing the researcher to identify recurring patterns, themes, and categories related to your research inquiry based on relevant theory.

Let's explore the idea of the theoretical framework in greater detail by exploring its place in qualitative research, particularly how it is generated and how it contributes to and guides your research study.

Theoretical framework vs. theoretical perspective

While these two terms may sound similar, they play very distinct roles in qualitative research . A theoretical perspective refers to the philosophical stance informing the methodology and thus provides a context for the research process. These perspectives could be rooted in various schools of thought like postmodernism, constructivism, or positivism, which fundamentally shape how researchers perceive reality and construct knowledge.

On the other hand, the theoretical framework represents the structure that can hold or support a theory of a research study. It presents a logical structure of connected concepts that help the researcher understand, explain, and predict how phenomena are interrelated. The theoretical framework can pull together various theories or ideas from different perspectives to provide a comprehensive approach to addressing the research problem.

Moreover, theoretical frameworks provide useful guidance as to which research methods are appropriate for your research project. If the theoretical framework you employ is relevant to individual perspectives and beliefs, then interviews may be more suitable for your research. On the other hand, if you are utilizing an existing theory about a certain social behavior, then ethnographic observations can help you more ably capture data from social interactions.

Later in this guide, we will also discuss conceptual frameworks , which help you visualize the essential concepts and data points in the context you are studying. For now, it is important to emphasize that these are all related but ultimately different ideas.

Example of a theoretical framework

Let's look at a simple example of a theoretical framework used to address a social science research problem. Consider a study examining the impact of social media on body image among adolescents. The theoretical perspective might be rooted in social constructivism, based on the assumption that our understanding of reality is shaped by social interactions and cultural context.

The theoretical framework, then, could draw on one or several theories to provide a comprehensive structure for examining this issue. For instance, it might combine elements of "social comparison theory" (which suggests that individuals determine their own social and personal worth based on how they stack up against others), "self-perception theory" (which posits that individuals develop their attitudes by observing their own behavior and concluding what attitudes must have caused it), and "cultivation theory" (which suggests that long-term immersion in a media environment leads to "cultivation", or adopting the attitudes and beliefs portrayed in the media).

This framework would provide the structure to understand how social media exposure influences adolescents' perceptions of their bodies, how they compare themselves to images seen on social media, and how these influences may shape their attitudes toward their own bodies.

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Other examples of theoretical frameworks

Let's briefly look at examples in other fields to put the idea of "theoretical framework" in greater context.

Political science

In a study investigating the influence of lobbying on legislative decisions, the theoretical framework could be rooted in the "pluralist theory" and "elite theory".

Pluralist theory views politics as a competition among groups, each one pressing for its preferred policies, while elite theory suggests that a small, cohesive elite group makes the most important decisions in society. The framework could combine these theories to examine the power dynamics in legislative decisions and the role of lobbying groups in influencing these outcomes.

Educational research

An educational research study aiming to understand the impact of parental involvement on children's academic success could employ a theoretical framework based on Bronfenbrenner's ecological systems theory and Epstein's theory of overlapping spheres of influence.

The ecological systems theory emphasizes the importance of multiple environmental systems on child development, while Epstein's theory focuses on the partnership between family, school, and community. The intersection of these theories allows for a comprehensive examination of parental involvement both in and outside of the school context.

Health services research

In a health services study exploring factors affecting patient adherence to medication regimes, the theoretical framework could draw from the health belief model and social cognitive theory.

The health belief model posits that people's beliefs about health problems, perceived benefits of action and barriers to action, and self-efficacy explain engagement in health-promoting behavior.

The social cognitive theory emphasizes the role of observational learning, social experience, and reciprocal determinism in behavior change. The framework combining these theories provides a holistic understanding of both personal and social influences on patient medication adherence.

Developing a theoretical framework involves a multi-step process that begins with a thorough literature review . This allows you to understand the existing theories and research related to your topic and identify gaps or unresolved puzzles that your study can address.

1. Identify key concepts: These might be the phenomena you are studying, the attributes of these phenomena, or the relationships between them. Identifying these can help you define the relevant data points to analyze.

2. Find relevant theories: Conduct a literature review to search for existing theories in academic research papers that relate to your key concepts. These theories might explain the phenomena you are studying, provide context for it, or suggest how the phenomena might be related. You can build off of one theory or multiple theories, but what is most important is that the theory is aligned with the concepts and research problem you are studying.

3. Map relationships: Outline how the theories you have found relate to one another and to your key concepts. This might involve drawing a diagram or writing a narrative that explains these relationships.

4. Refine the framework: As you conduct your research, refine your theoretical framework. This might involve adding new concepts or theories, removing concepts or theories that do not fit your data, or changing how you conceptualize the relationships between theories.

Remember, the theoretical framework is not set in stone. At the same time, it may start with existing knowledge, it is important to develop your own framework as you gather more data and gain a deeper understanding of your research topic and context.

In the end, a good theoretical framework guides your research question and methods so that you can ultimately generate new knowledge and theory that meaningfully contributes to the existing conversation around a topic.

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5.5 Developing a theoretical framework

Social work researchers develop theoretical frameworks based on social science theories and empirical literature. A study’s theory describes the theoretical foundations of the research and consists of the big-T theory(ies) that guide the investigation. It provides overarching perspectives, explanations, and predictions about the social problem and research topic.

In deductive research (e.g., quantitative research), researchers create a theoretical framework to explain the thought process behind the study’s research questions and hypotheses. The theoretical framework includes the constructs of interest in the study and the associations the researchers expect to find. These constructs and their relations are based on the broader theory, but likely do not entail all the components of the theory.  The theoretical framework is specific to a particular study or analysis and provides the rationale for the research question(s). In inductive studies such as grounded theory, a theoretical framework can be the final result of the research.  In this case, the theoretical framework is also a combination of concepts and their associations, but it is derived from the data collected during the research. This contrasts to theoretical frameworks in deductive research, which are created before collecting data and derive from theories and other empirical findings.

In Chapter 8, we will develop your quantitative theoretical framework further, identifying associations or causal relations in a research question. Developing a quantitative theoretical framework is also instructive for revising and clarifying your working research question and identifying concepts that serve as keywords for additional literature searching. But first, we will consider identifying your theory. The greater clarity you have with your theoretical perspective, the easier each subsequent step in the research process will be. Getting acquainted with the important theoretical concepts in a new area can be challenging. While social work education provides a broad overview of social theory, you will find much greater fulfillment out of reading about the theories related to your topic area. We discussed some strategies for finding theoretical information in Chapter 3 as part of literature searching. To extend that conversation a bit, some strategies for searching for theories in the literature include:

• Consider searching for these keywords in the title or abstract, specifically
• Looking at the references and cited by links within theoretical articles and textbooks
• Looking at books, edited volumes, and textbooks that discuss theory
• Talking with a scholar on your topic, or asking a professor if they can help connect you to someone
• It is helpful when authors are clear about how they use theory to inform their research project, usually in the introduction and discussion section.
• For example, from the broad umbrella of systems theory, you might pick out family systems theory if you want to understand the effectiveness of a family counseling program.

It’s important to remember that knowledge arises within disciplines, and that disciplines have different theoretical frameworks for explaining the same topic. While it is certainly important for the social work perspective to be a part of your analysis, social workers benefit from searching across disciplines to come to a more comprehensive understanding of the topic. Reaching across disciplines can provide uncommon insights during conceptualization, and once the study is completed, a multidisciplinary researcher will be able to share results in a way that speaks to a variety of audiences. A study by An and colleagues (2015) [1] uses game theory from the discipline of economics to understand problems in the Temporary Assistance for Needy Families (TANF) program. In order to receive TANF benefits, mothers must cooperate with paternity and child support requirements unless they have “good cause,” as in cases of domestic violence, in which providing that information would put the mother at greater risk of violence. Game theory can help us understand how TANF recipients and caseworkers respond to the incentives in their environment, and highlight why the design of the “good cause” waiver program may not achieve its intended outcome of increasing access to benefits for survivors of family abuse.

Of course, there are natural limits on the depth with which student researchers can and should engage in a search for theory about their topic. At minimum, you should be able to draw connections across studies and be able to assess the relative importance of each theory within the literature. Just because you found one article applying your theory (like game theory, in our example above) does not mean it is important or often used in the domestic violence literature. Indeed, it would be much more common in the family violence literature to find psychological theories of trauma, feminist theories of power and control, and similar theoretical perspectives used to inform research projects rather than game theory, which is equally applicable to survivors of family violence as workers and bosses at a corporation. Consider using the Cited By feature to identify articles, books, and other sources of theoretical information that are seminal or well-cited in the literature. Similarly, by using the name of a theory in the keywords of a search query (along with keywords related to your topic), you can get a sense of how often the theory is used in your topic area. You should have a sense of what theories are commonly used to analyze your topic, even if you end up choosing a different one to inform your project.

Theories that are not cited or used as often are still immensely valuable. As we saw before with TANF and “good cause” waivers, using theories from other disciplines can produce uncommon insights and help you make a new contribution to the social work literature. Given the privileged position that the social work curriculum places on theories developed by white men, students may want to explore Afrocentricity as a social work practice theory (Pellebon, 2007) [2] or abolitionist social work (Jacobs et al., 2021) [3] when deciding on a theoretical framework for their research project that addresses concepts of racial justice. Start with your working question, and explain how each theory helps you answer your question. Some explanations are going to feel right, and some concepts will feel more salient to you than others. Keep in mind that this is an iterative process. Your theoretical framework will likely change as you continue to conceptualize your research project, revise your research question, and design your study.

By trying on many different theoretical explanations for your topic area, you can better clarify your own theoretical framework. Some of you may be fortunate enough to find theories that match perfectly with how you think about your topic, are used often in the literature, and are therefore relatively straightforward to apply. However, many of you may find that a combination of theoretical perspectives is most helpful for you to investigate your project. For example, maybe the group counseling program for which you are evaluating client outcomes draws from both motivational interviewing and cognitive behavioral therapy. In order to understand the change happening in the client population, you would need to know each theory separately as well as how they work in tandem with one another. Because theoretical explanations and even the definitions of concepts are debated by scientists, it may be helpful to find a specific social scientist or group of scientists whose perspective on the topic you find matches with your understanding of the topic. Of course, it is also perfectly acceptable to develop your own theoretical framework, though you should be able to articulate how your framework fills a gap within the literature.

Much like paradigm, theory plays a supporting role for the conceptualization of your research project. Recall the ice float from Figure 5.1. Theoretical explanations support the design and methods you use to answer your research question. In projects that lack a theoretical framework, you may see the biases and errors in reasoning that we discussed in Chapter 1 that get in the way of good social science. That’s because theories mark which concepts are important, provide a framework for understanding them, and measure their interrelationships. If research is missing this foundation, it may instead operate on informal observation, messages from authority, and other forms of unsystematic and unscientific thinking we reviewed in Chapter 1.

Theory-informed inquiry is incredibly helpful for identifying key concepts and how to measure them in your research project, but there is a risk in aligning research too closely with theory. The theory-ladenness of facts and observations produced by social science research means that we may be making our ideas real through research. This is a potential source of confirmation bias in social science. Moreover, as Tan (2016) [4] demonstrates, social science often proceeds by adopting as true the perspective of Western and Global North countries, and cross-cultural research is often when ethnocentric and biased ideas are most visible . In her example, a researcher from the West studying teacher-centric classrooms in China that rely partially on rote memorization may view them as less advanced than student-centered classrooms developed in a Western country simply because of Western philosophical assumptions about the importance of individualism and self-determination. Developing a clear theoretical framework is a way to guard against biased research, and it will establish a firm foundation on which you will develop the design and methods for your study.

Key Takeaways

• Just as empirical evidence is important for conceptualizing a research project, so too are the key concepts and relationships identified by social work theory.
• Using theory your theory textbook will provide you with a sense of the broad theoretical perspectives in social work that might be relevant to your project.
• Try to find small-t theories that are more specific to your topic area and relevant to your working question.

TRACK 1 (IF YOU ARE CREATING A RESEARCH PROPOSAL FOR THIS CLASS):

In Chapter 2, you developed a concept map for your proposal.

• Take a moment to revisit your concept map now as your theoretical framework is taking shape. Make any updates to the key concepts and relationships in your concept map.

If you need a refresher, we have embedded a short how-to video from the University of Guelph Library (CC-BY-NC-SA 4.0) that we also used in Chapter 2.

TRACK 2 (IF YOU AREN’T CREATING A RESEARCH PROPOSAL FOR THIS CLASS):

You are interested in researching bullying among school-aged children, and how this impacts students’ academic success.

• Find two theoretical frameworks that have been used in published articles on this topic. Identify similarities and differences between the frameworks.

5.6 Designing your project using theory and paradigm

Learning Objectives

Learners will be able to…

• Apply the assumptions of each paradigm to your project
• Summarize what aspects of your project stem from positivist, constructivist, or critical assumptions

In the previous sections, we reviewed the major paradigms and theories in social work research. In this section, we will provide an example of how to apply theory and paradigm in research. This process is depicted in Figure 5.2 below with some quick summary questions for each stage. Some questions in the figure below have example answers like designs (i.e., experimental, survey) and data analysis approaches (i.e., discourse analysis). These examples are arbitrary. There are a lot of options that are not listed. So, don’t feel like you have to memorize them or use them in your study.

This diagram (taken from an archived Open University (UK) course entitled E89 ​- Educational Inquiry ) ​ shows one way to visualize the research design process. While research is far from linear, in general, this is how research projects progress sequentially. Researchers begin with a working question, and through engaging with the literature, develop and refine those questions into research questions (a process we will finalize in Chapter 9). But in order to get to the part where you gather your sample, measure your participants, and analyze your data, you need to start with paradigm. Based on your work in section 5.3, you should have a sense of which paradigm or paradigms are best suited to answering your question. The approach taken will often reflect the nature of the research question; the kind of data it is possible to collect; and work previously done in the area under consideration. When evaluating paradigm and theory, it is important to look at what other authors have done previously and the framework used by studies that are similar to the one you are thinking of conducting.

Once you situate your project in a research paradigm, it becomes possible to start making concrete choices about methods. Depending on the project, this will involve choices about things like:

• What is my final research question?
• What are the key variables and concepts under investigation, and how will I measure them?
• How do I find a representative sample of people who experience the topic I’m studying?
• What design is most appropriate for my research question?
• How will I collect and analyze data?
• How do I determine whether my results describe real patterns in the world or are the result of bias or error?

The data collection phase can begin once these decisions are made. It can be very tempting to start collecting data as soon as possible in the research process as this gives a sense of progress. However, it is usually worth getting things exactly right before collecting data as an error found in your approach further down the line can be harder to correct or recalibrate around.

Designing a study using paradigm and theory: An example

Paradigm and theory have the potential to turn some people off since there is a lot of abstract terminology and thinking about real-world social work practice contexts. In this section, I’ll use an example from my own research, and I hope it will illustrate a few things. First, it will show that paradigms are really just philosophical statements about things you already understand and think about normally. It will also show that no project neatly sits in one paradigm and that a social work researcher should use whichever paradigm or combination of paradigms suit their question the best. Finally, I hope it is one example of how to be a pragmatist and strategically use the strengths of different theories and paradigms to answering a research question. We will pick up the discussion of mixed methods in the next chapter.

Thinking as an expert: Positivism

In my undergraduate research methods class, I used an open textbook much like this one and wanted to study whether it improved student learning. You can read a copy of the article we wrote on based on our study . We’ll learn more about the specifics of experiments and evaluation research in Chapter 13, but you know enough to understand what evaluating an intervention might look like. My first thought was to conduct an experiment, which placed me firmly within the positivist or “expert” paradigm.

Experiments focus on isolating the relationship between cause and effect. For my study, this meant studying an open textbook (the cause, or intervention) and final grades (the effect, or outcome). Notice that my position as “expert” lets me assume many things in this process. First, it assumes that I can distill the many dimensions of student learning into one number—the final grade. Second, as the “expert,” I’ve determined what the intervention is: indeed, I created the book I was studying, and applied a theory from experts in the field that explains how and why it should impact student learning.

Theory is part of applying all paradigms, but I’ll discuss its impact within positivism first. Theories grounded in positivism help explain why one thing causes another. More specifically, these theories isolate a causal relationship between two (or more) concepts while holding constant the effects of other variables that might confound the relationship between the key variables. That is why experimental design is so common in positivist research. The researcher isolates the environment from anything that might impact or bias the cause and effect relationship they want to investigate.

But in order for one thing to lead to change in something else, there must be some logical, rational reason why it would do so. In open education, there are a few hypotheses (though no full-fledged theories) on why students might perform better using open textbooks. The most common is the access hypothesis , which states that students who cannot afford expensive textbooks or wouldn’t buy them anyway can access open textbooks because they are free, which will improve their grades. It’s important to note that I held this theory prior to starting the experiment, as in positivist research you spell out your hypotheses in advance and design an experiment to support or refute that hypothesis.

Notice that the hypothesis here applies not only to the people in my experiment, but to any student in higher education. Positivism seeks generalizable truth, or what is true for everyone. The results of my study should provide evidence that  anyone  who uses an open textbook would achieve similar outcomes. Of course, there were a number of limitations as it was difficult to tightly control the study. I could not randomly assign students or prevent them from sharing resources with one another, for example. So, while this study had many positivist elements, it was far from a perfect positivist study because I was forced to adapt to the pragmatic limitations of my research context (e.g., I cannot randomly assign students to classes) that made it difficult to establish an objective, generalizable truth.

Thinking like an empathizer: constructivism

One of the things that did not sit right with me about the study was the reliance on final grades to signify everything that was going on with students. I added another quantitative measure that measured research knowledge, but this was still too simplistic. I wanted to understand how students used the book and what they thought about it. I could create survey questions that ask about these things, but to get at the subjective truths here, I thought it best to use focus groups in which students would talk to one another with a researcher moderating the discussion and guiding it using predetermined questions. You will learn more about focus groups in Chapter 18.

Researchers spoke with small groups of students during the last class of the semester. They prompted people to talk about aspects of the textbook they liked and didn’t like, compare it to textbooks from other classes, describe how they used it, and so forth. It was this focus on  understanding and subjective experience that brought us into the constructivist paradigm. Alongside other researchers, I created the focus group questions but encouraged researchers who moderated the focus groups to allow the conversation to flow organically.

We originally started out with the assumption, for which there is support in the literature, that students would be angry with the high-cost textbook that we used prior to the free one, and this cost shock might play a role in students’ negative attitudes about research. But unlike the hypotheses in positivism, these are merely a place to start and are open to revision throughout the research process. This is because the researchers are not the experts, the participants are! Just like your clients are the experts on their lives, so were the students in my study. Our job as researchers was to create a group in which they would reveal their informed thoughts about the issue, coming to consensus around a few key themes.

When we initially analyzed the focus groups, we uncovered themes that seemed to fit the data. But the overall picture was murky. How were themes related to each other? And how could we distill these themes and relationships into something meaningful? We went back to the data again. We could do this because there isn’t one truth, as in positivism, but multiple truths and multiple ways of interpreting the data. When we looked again, we focused on some of the effects of having a textbook customized to the course. It was that customization process that helped make the language more approachable, engaging, and relevant to social work practice.

Ultimately, our data revealed differences in how students perceived a free textbook versus a free textbook that is customized to the class. When we went to interpret this finding, the remix  hypothesis of open textbook was helpful in understanding that relationship. It states that the more faculty incorporate editing and creating into the course, the better student learning will be. Our study helped flesh out that theory by discussing the customization process and how students made sense of a customized resource.

In this way, theoretical analysis operates differently in constructivist research. While positivist research tests existing theories, constructivist research creates theories based on the stories of research participants. However, it is difficult to say if this theory was totally emergent in the dataset or if my prior knowledge of the remix hypothesis influenced my thinking about the data. Constructivist researchers are encouraged to put a box around their previous experiences and beliefs, acknowledging them, but trying to approach the data with fresh eyes. Constructivists know that this is never perfectly possible, though, as we are always influenced by our previous experiences when interpreting data and conducting scientific research projects.

Thinking like an activist: Critical

Although adding focus groups helped ease my concern about reducing student learning down to just final grades by providing a more rich set of conversations to analyze. However, my role as researcher and “expert” was still an important part of the analysis. As someone who has been out of school for a while, and indeed has taught this course for years, I have lost touch with what it is like to be a student taking research methods for the first time. How could I accurately interpret or understand what students were saying? Perhaps I would overlook things that reflected poorly on my teaching or my book. I brought other faculty researchers on board to help me analyze the data, but this still didn’t feel like enough.

By luck, an undergraduate student approached me about wanting to work together on a research project. I asked her if she would like to collaborate on evaluating the textbook with me. Over the next year, she assisted me with conceptualizing the project, creating research questions, as well as conducting and analyzing the focus groups. Not only would she provide an “insider” perspective on coding the data, steeped in her lived experience as a student, but she would serve as a check on my power through the process.

Including people from the group you are measuring as part of your research team is a common component of critical research. Ultimately, critical theorists would find my study to be inadequate in many ways. I still developed the research question, created the intervention, and wrote up the results for publication, which privileges my voice and role as “expert.” Instead, critical theorists would emphasize the role of students (community members) in identifying research questions, choosing the best intervention to used, and so forth. But collaborating with students as part of a research team did address some of the power imbalances in the research process.

Critical research projects also aim to have an impact on the people and systems involved in research. No students or researchers had profound personal realizations as a result of my study, nor did it lessen the impact of oppressive structures in society. I can claim some small victory that my department switched to using my textbook after the study was complete (changing a system), though this was likely the result of factors other than the study (my advocacy for open textbooks).

Social work research is almost always designed to create change for people or systems. To that end, every social work project is at least somewhat critical. However, the additional steps of conducting research with people rather than on people reveal a depth to the critical paradigm. By bringing students on board the research team, study had student perspectives represented in conceptualization, data collection, and analysis. That said, there was much to critique about this study from a critical perspective. I retained a lot of the power in the research process, and students did not have the ability to determine the research question or purpose of the project. For example, students might likely have said that textbook costs and the quality of their research methods textbook were less important than student debt, racism, or other potential issues experienced by students in my class. Instead of a ground-up research process based in community engagement, my research included some important participation by students on project created and led by faculty.

Designing research is an iterative process

I hope this conversation was useful in applying paradigms to a research project. While my example discusses education research, the same would apply for social work research about social welfare programs, clinical interventions, or other topics. Paradigm and theory are covered at the beginning of the project because these assumptions will structure the rest of the project. Each of the research steps that occur after this chapter (e.g., forming a question, choosing a design) rely upon philosophical and theoretical assumptions. As you continue designing a project, you may find yourself shifting between paradigms. That is normal, as conceptualization is not a linear process. As you move through the next steps of conceptualizing and designing a project, you’ll find philosophies and theories that best match how you want to study your topic.

Viewing theoretical and empirical arguments through this lens is one of the true gifts of the social work approach to research. The multi-paradigmatic perspective is a hallmark of social work research and one that helps us contribute something unique on research teams and in practice.

• Multi-paradigmatic research is a distinguishing hallmark of social work research. Understanding the limitations and strengths of each paradigm will help you justify your research approach and strategically choose elements from one or more paradigms to answer your question.
• Paradigmatic assumptions help you understand the “blind spots” in your research project and how to adjust and address these areas. Keep in mind, it is not necessary to address all of your blind spots, as all projects have limitations.

Post-awareness check (Emotion)

Of the introduced social science paradigms, which would you say aligns with your current perspective on your research topic?

• Sketch out which paradigm applies best to your project. Second, building on your answer to the exercise in section 6.3, identify how the theory you chose and the paradigm in which you find yourself are consistent or are in conflict with one another. For example, if you are using systems theory in a positivist framework, you might talk about how they both rely on a deterministic approach to human behavior with a focus on the status-quo and social order.
• Select one paradigm and one theoretical framework. How does your selected theoretical framework align with your paradigm? How could the theory and paradigm together inform the overall research design?
• An, S., Yoo, J., & Nackerud, L. G. (2015). Using game theory to understand screening for domestic violence under the TANF family violence option.  Advances in Social Work ,  16 (2), 338-357. ↵
• Pellebon, D. A. (2007). An analysis of Afrocentricity as theory for social work practice.  Advances in Social Work ,  8 (1), 169-183. ↵
• Jacobs, L. A., Kim, M. E., Whitfield, D. L., Gartner, R. E., Panichelli, M., Kattari, S. K., ... & Mountz, S. E. (2021). Defund the police: Moving towards an anti-carceral social work.  Journal of Progressive Human Services ,  32 (1), 37-62. ↵
• Tan, C. (2016). Investigator bias and theory-ladenness in cross-cultural research: Insights from Wittgenstein. Current Issues in Comparative Education ,  18 (1), 83-95. ↵

a network of linked concepts that together provide a rationale for a research project or analysis; theoretical frameworks are based in theory and empirical literature

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Network analyses of emotion components: an exploratory application to the component process model of emotion

• Open access
• Published: 14 September 2024

Cite this article

You have full access to this open access article

• Livia Sacchi   ORCID: orcid.org/0000-0002-6428-3789 1 &
• Elise Dan-Glauser 1  

Emotion is an episode involving changes in multiple components, specifically subjective feelings, physiological arousal, expressivity, and action tendencies, all these driven by appraisal processes. However, very few attempts have been made to comprehensively model emotion episodes from this full componential perspective, given the statistical and methodological complexity involved. Recently, network analyses have been proposed in the field of emotion and cognition as an innovative theoretical and statistical framework able to integrate several properties of emotions. We therefore addressed the call for more multi-componential evidence by modeling the network of a comprehensive list of emotion components drawn from the Component Process Model of Emotion. Five-hundred students were confronted with mildly ambiguous scenarios from everyday life, and reported on their situational appraisals and emotion responses. Network analyses were applied to the emotion components related to a positive and a negative scenario to explore 1) how the components organize themselves into networks and dimensions; 2) which components are the most central within networks and dimensions; and 3) the patterns of components relation between and within dimensions. A three-dimensional solution emerged in both scenarios. Additionally, some appraisals and responses appeared to be differentially relevant and related to each other in both scenarios, highlighting the importance of context in shaping the strength of emotion component relations. Overall, we enriched the field of affective science by exploring the connections between emotion components in three novel ways: by using network analyses, by integrating them into a multi-componential framework, and by providing context to our emotion components. Our results can also potentially inform applied research, where understanding the interconnections and the centrality of components could aid the personalization of interventions.

Avoid common mistakes on your manuscript.

In emotion research, it is generally accepted that an emotion has a componential nature: that is, what we call emotion is the byproduct of the interaction of several components, namely subjective evaluations, feelings, physiological arousal, expressivity, and action tendencies (Lange et al., 2020 ). Several emotion theories coexist, and differ in their conceptualizations of how and which of these components are most central. However, they converge on the necessity of an antecedent event for an emotion to occur – that is, a situation that will then be appraised (Scherer & Moors, 2019 ).

The Component Process Model (CPM) of emotion by Scherer ( 2009 ) has established itself as one of the most authoritative modern appraisal theories thanks to its dynamic and functional architecture. In the CPM, an emotion is a synchronized, multi-componential episode initiated by cognitive appraisal of an emotionally charged situation (e.g., an external event such as a friend not greeting back, or an internal event such as an upsetting memory). Compared to other emotion theories, the CPM assigns a special gate-keeper role to appraisal. Indeed, as a result of phylogenetic processes, appraisal is a highly sophisticated cognitive tool that allows us to navigate safely through complex and ambiguous situations. In other words, appraisals serve an evolutionary function, that the CPM has the merit of organizing into an increasingly differentiated, sequential architecture. For example, within a situational appraisal, early Stimulus Evaluation Checks (SECs) act as orienting responses to novelty, followed by evaluations of pleasantness, and of personal goal relevance. These first SECs fall under the functional category of Relevance detection, which is also found in non-human species and in simple organisms (Ellsworth & Scherer, 2003 ). It is theorized that if these basic checks are not present, an emotion episode cannot be elicited. Then, more “costly” cognitive checks are endorsed. The functional category of Implications regroups those checks that assess the personal consequences that might result from the situation, for example depending on who caused it, whether it is still conducive to personal goals, and what the probability of the desired outcome is. Then, the functional category of Coping Potential regroups those checks that determine the individual’s ability to cope with and/or adjust to the situation. Finally, the functional category of Normative Significance assesses the compatibility of the situation to personal and external norms. In the CPM, the result of this multilevel appraisal process causally leads to the differentiation and modification of emotion responses, i.e., the experiential (e.g., frustration), somatic (e.g., feeling hot), expressive (e.g., frowning), and motivational (e.g., repair instinct) components of an emotion episode. Finally, the event is represented centrally as nonverbal feelings, and the emergent emotion (e.g., sadness) is categorized and labeled (Fig. S1 ). Importantly, in the CPM, emotion components activation is theorized to have a recursive effect on the other components: that is, once an emotion episode is initiated, a dynamic update of the system takes place continuously, always with an adaptive function (Scherer, 2009 ).

Despite the agreement on the multi-componential nature of emotion episodes, virtually no attempts have been made to model them comprehensively under a full componential perspective, mainly for two reasons. The first concerns the overwhelming amount of research dedicated to the investigation of what is considered as the “real” outcome of an emotion episode, that is, a categorical emotion (e.g., guilt, pride). Early appraisal theory aimed to identify the fixed patterns of component activation that would lead to the experience of these prototypical emotions, usually by applying self-report measures in a deductive-semantic fashion (Gentsch et al., 2018 ). In such cases, participants are presented with an emotion term, followed by a list of emotion components to be matched to the emotion based on their beliefs and experience. This procedure has however been heavily criticized for eliciting culturally-based and/or stereotypical assumptions about emotions (Scherer & Moors, 2019 ). Modern appraisal theorists have also now acknowledged the pervasive “impurity” and complexity of the emotion experience, proving that the existence of pure emotions is the exception rather than the rule (Scherer & Meuleman, 2013 ; Scherer & Moors, 2019 ). This has led appraisal research to shift from the identification of categorical emotions as outcomes of the emotion chain to the study of the interconnections between the five components: however, paradigm shifts are slow to be implemented in practice. Indeed, the most prolific contemporary strand of appraisal research is known as bi-componential, that is, concerned with exploring relations between component pairs (Meuleman et al., 2019 ). Scherer and Moors ( 2019 ) recently provided a summary of such evidence: overall, novel and goal-relevant stimuli elicit pre-attentive appraisals, which are linked to automatic action tendencies such as approach or avoidance tendencies, depending on the stimuli valence. When a stimulus is negatively valenced and externally caused, or general control/power over the situation is high, action tendencies are more aggressive in nature. Regarding the relation between appraisal and physiological reactions, evidence suggests that novel and goal-relevant stimuli re-orient attention and induce physiological changes in parameters such as muscular tone, electrodermal and respiratory activity, as well as pupil dilation, with negative and positive valence inducing differential reactions. A higher vascular reactivity and sympathetic arousal have also been associated with low prospective control. Finally, fewer experimental evidence is available for the appraisal-expressivity relationship: the strongest results concern the intrinsic pleasantness appraisal affecting frowning (corrugator muscles activity) and smiling (zygomatic muscles activity), and the power and control appraisals affecting vocal expressivity (Scherer & Moors, 2019 ).

The second reason for the scarcity of multi-componential modeling is pragmatic: attempting to model a large number of components involves great statistical and methodological complexity (Meuleman et al., 2019 ). Examples of these multi-componential attempts are rare, but two are noteworthy for their innovation. Within the CPM framework, Meuleman et al. ( 2019 ) used machine learning algorithms to explore the relationships between 18 appraisals and the emotion responses factors. They found that factors within the same emotion component, as well as appraisals factors and response factors, were mostly uncorrelated. Only the appraisal of goal compatibility and of suddenness were strongly related to physiological and expressive responses, respectively. More recently, Lange et al. ( 2020 ) proposed the network approach to model emotion components, which postulates how, for instance, the emotion of anger actually emerges from the interaction of beliefs, motivations, expressive behaviors and bodily reactions. Inspired by the theoretical proposition of Lange et al. ( 2020 ), we believe that networks could similarly advance modern appraisal research by allowing a comprehensive exploration of multi-componential relations.

Applied to many scientific fields in the last decade, network modeling has also grown exponentially in psychology (Borsboom et al., 2021 ). Its widespread popularity across disciplines lies in its foundational assumption that phenomena between and within individuals– from human genes and mental health to relational or social media transactions– are dynamic, complex systems, and thus exhibit complex behavior (Barabási, 2012 ). Because systems entail a structural organization—a network– of their components, it is often fruitless to study their functioning in isolation (Barabási, 2012 ; Borsboom et al., 2021 ). This is especially true when components interact with each other to give life to a phenomenon, which in turn can influence the functioning of the same components through feedback loops – a property known as bi-directionality (Dalege et al., 2016 ; Lewis, 2005 ). The simplicity with which networks visually convey very complex relationships between system components is another reason why they have become so popular (Hevey, 2018 ). Components, called nodes, are connected via edges that convey the magnitude and direction of their association. For example, thicker and green (or blue) edges signal a strong and positive (excitatory) relation, while thinner and red edges a weak and negative (inhibitory) relation (Borsboom et al., 2021 ; Dalege et al., 2016 ). Moreover, nodes can a) be more important (central) to the network, by being more strongly connected to all the other nodes; b) cluster into communities– i.e., groups of more densely connected nodes; and c) bridge different communities (Borsboom et al., 2021 ).

In psychology, these network properties have led to important theoretical and empirical advances through the modeling of affects, cognitions, and behaviors. For instance, network approaches have allowed the subfield of clinical psychology to move away from the long-standing essentialist, biologically-based view of mental disorders, and to explore how syndromes may actually be the byproducts of causal and dynamic interconnections of symptoms, such as negative cognitive schemas (Bringmann et al., 2022 ; Robinaugh et al., 2020 ). For example, in a sample of American psychology college students, Collins et al. ( 2023 ) investigated the moderating influence of depressive symptoms on the network of negative self-schemas associated with fear of happiness. They found that more depressed students reported stronger and positive links between nodes representing avoidance and devaluation of positivity. Similarly, Tao et al. ( 2022 ) explored the association between anxiety, depression and sleep disturbance symptoms in a large convenience sample of Chinese university students. The authors found that the symptoms of guilt, irritability, restlessness, fear, and sleep disturbance bridged the three disorders, meaning that once these symptoms are activated, they would in turn activate the entire network. This knowledge opens the possibility of improving the whole mental health network by acting on a single symptom (Jones et al., 2021 ). In cognitive psychology, networks have allowed to easily visualize how and with what intensity nodes are connected (or not), as well as their centrality, across groups. For example, Neubeck et al. ( 2022b ) modelled cognitive performance components in young and old individuals and showed how the fluid intelligence component was more central, and the link between intelligence and working memory stronger, in the old group compared to the young one, while the accelerated attention component was most central in the latter. Similarly, Neubeck et al. ( 2022a ) found that self-regulation and executive control functions were more strongly interconnected in older than in younger individuals, possibly due to a stronger effect of cognitive decline on overall regulatory processes. In the field of emotion psychology, Mattsson et al. ( 2020 ) explored the interconnection of academic-related positive and negative emotions in a sample of 241 Finnish university students, highlighting how self-efficacy beliefs emerged as the most central node and therefore targetable. More recently, Lange and Zickfeld ( 2021 , 2023 ) confirmed the utility of the network approach by demonstrating that components are indeed shared between similarly valenced emotions, such as awe, admiration, and gratitude, guilt and shame, or awe and kama muta (“being moved”).

Strikingly, emotion episodes were already being discussed as complex systems of component interactions almost 20 years ago (Lewis, 2005 ; Sander et al., 2005 ). The CPM itself relies on dynamic system principles, in particular that of recursiveness (i.e., bi-directionality; Moors, 2022 ; Sander et al., 2005 ), according to which “the emotion process is considered as a continuously fluctuating pattern of change in several organismic subsystems that become integrated into coherence clusters and thus yields an extraordinarily large number of different emotional qualities” (Scherer, 2009 , p. 1320). The application of networks to the modeling of CPM emotion components is thus a natural step, if not the required step, to focus on the mechanisms underlying an emotion episode and move beyond standard emotion labels as outcomes (Scherer & Moors, 2019 ). Moreover, as suggested by Lange et al. ( 2020 ), the application of networks to emotion components and emotions has the potential to achieve the integration needed in emotion research, by serving as an alternative psychometric model to perhaps the most explicitly (and implicitly) applied one in the field: the reflective latent-variable model. Its theorization of what constitutes an emotion episode coincides with the lay notion of an unobserved (i.e., latent) construct, whose symptoms (i.e., indicators) are instead observable (Lange et al., 2020 ). These indicators are thus causally dependent on the latent variable and causally independent of each other, implying that: 1) an emotion episode is separable from its components; 2) these components have a fixed and universal pattern of activation that leads only to the experience of a particular emotion; and 3) they are correlated to the latent variable but not causally interacting between each other (Lange et al., 2020 ). However, empirical evidence contradicts the reflective latent-variable model of emotion: components are routinely manipulated to assess the target emotion (Mauss & Robinson, 2009 ); individuals vary in their situational appraisals, and in the intensity with which these appraisals affect emotion reactivity (Kuppens & Tong, 2010 ); appraisals exert a causal effect on other components of emotion (Meuleman et al., 2019 ), and some components are known to be more correlated than others (Lange et al., 2020 ; Scherer & Moors, 2019 ); and, finally, mixed emotions are the norm rather than the exception (Israel & Schönbrodt, 2021 ; Scherer & Meuleman, 2013 ).

Thus, inspired by the theoretical and methodological proposal by Lange et al. ( 2020 ), we aimed to explore the network of a comprehensive list of emotion components in slightly ambiguous, positive and negative daily life situations, without deductive prompt of emotion terms (Gentsch et al., 2018 ). This was done to explore what is referred to as an emotion episode in the CPM (Scherer & Moors, 2019 ). As noted in the findings reported above, bi-componential research points to few but stable relations between appraisal and emotion responses, while multi-componential evidence is so far sparse and heterogeneous. Therefore, we had several goals with this work.

Our first research question was to explore how the five emotion components organized themselves into a network and into dimensions. This would provide important information regarding the influence of context on component inter-connections and clustering. Emotion components in the CPM are theorized to be organized at a higher-order level, which comprises a four-factor structure of Valence, Arousal, Power, and Novelty (Fontaine et al., 2013 ). Recently, Fontaine et al. ( 2022 ) provided even more nuanced results concerning the relations between these four dimensions as negative and positive emotion terms turned out to be strongly distributed across a dimensional space consisting of the first two dimensions. The meaning of these terms was then further contextually refined by the dimensions of Power and Novelty. For example, the authors found a strong relation between Valence and Power dimensions in positive emotion terms, which did not hold for negative ones. The authors explained this finding by arguing that positive valence already captures substantial variance in power-related components (i.e., having power over a situation is generally perceived as positive). Based on this evidence, Fontaine et al. ( 2022 ) formulated specific predictions concerning the emergence of a distinct Power dimension, depending on the proportion of positive versus negative emotion terms. Translating their predictions to scenarios, we thus hypothesized that, in a positive one, appraisals belonging to the Coping Potential category would be more connected to or clustered with clearly valenced appraisals, such as the appraisal of pleasantness and of consequences, resulting in a blend of power and valence appraisals; and that, in a negative scenario, a Power dimension would emerge more clearly. Moreover, the authors show that when Novelty was higher, more Arousal and less Power were reported in emotion terms, respectively: we therefore hypothesized that the appraisals of suddenness, predictability, urgency, and immediateness, theoretically related to the higher-order Novelty dimension, would be more strongly associated to, or clustered with, either Arousal-related emotion components, or appraisals of Coping Potential, depending on the perceived situational novelty.

Our second research question concerned the assessment of components centrality: that is, we aimed at evaluating which component(s) appeared to be the most central (i.e., important) in the network and in the assigned dimensions. By estimating centrality indices, nodes that play a pivotal role in network activation and in their assigned dimensions can be identified. Given the strong evolutionary implication of the appraisals of pleasantness and of goal conduciveness in emotion emergence (Ellsworth & Scherer, 2003 ), we hypothesized that these will emerge as more central in the networks and in their assigned dimensions than other appraisals, regardless of the contextual valence. We further hypothesized that SECs related to the Coping Potential category will also emerge as central in the networks, given the theoretical and the empirical implications of these appraisals in valenced situations (Scherer, 2020 ; Scherer et al., 2022 ). Indeed, this hypothesis would also align with the finding by Mattsson et al. ( 2020 ) of self-efficacy beliefs emerging as the most central node in a network of positive and negative academic emotions.

Finally, our third research question concerned the formal testing of the between- and within-dimension component relations, following the recent contribution by Lange and Zickfeld ( 2023 ). This test permits to highlight the interrelation of components within the CPM. Given that previous research on emotion coherence has generally found stronger associations between elements within each component than across components (Lange et al., 2020 ; Mauss & Robinson, 2009 ), we hypothesized that emotion components within the same dimension would be more strongly connected to each other than across dimensions, an empirically proven property known as “small-world” (Borsboom et al., 2021 ; Dalege et al., 2016 ).

All in all, to the best of our knowledge, this is the first contextual application of network models within the CPM framework, aiming at providing complex modeling of specific emotion episodes.

Participants

We began by recruiting first-year psychology students at our host institution, who received compensation in the form of course credits. In a second round of recruitment via social media, we then extended the study to students at other Swiss educational institutions at the Bachelor, Master, and occasionally doctoral level, if deemed appropriate. These participants were rewarded with a voucher. Inclusion criteria were being between 18 and 45 years old, being in good health, and having sufficient proficiency in French. The former age inclusion criterion was dictated by the known physiological and hormonal changes occurring after the age of 45 (Crandall et al., 2023 ; McKinlay, 1996 ; Rymer & Morris, 2000 ). Exclusion criteria were medical treatment, regular use of drugs or medication, and diagnosis of a psychiatric disorder, as these factors are known to influence emotional and physiological processes at both the self-report and objective levels (Clark & Beck, 2010 ; Edgar et al., 2007 ; Kin et al., 2007 ; Wirth & Gaffey, 2013 ). Concerning sample size, guidelines for network models in psychology are still in their infancy (Hevey, 2018 ). However, a sample size of 250 for approximately 25 nodes is generally recommended based on simulations (Dalege et al., 2017 ). Given that several research questions were to be answered by this database, we aimed at the largest possible sample. The final sample consisted of 500 participants, of whom 212 (42.4%) were rewarded with vouchers and 288 (57.6%) with credits. In total, the sample included 412 females (83%) and had a mean age of 22.41 years (SD = 3.23), with 78% of the participants being native French speakers. The predominant educational level was bachelor’s degree (90% of the sample), with psychology being the most common subject (72% of the sample). The sample size obtained was considered adequate for network analyses.

As appraisals and emotion responses are specifically about situations, contextualization of our measures had to be performed. To explore emotion components, participants were thus administered four emotionally loaded scenarios (contexts) that were pre-tested in a pilot study. The first criterion for selecting the scenarios was that the scenario content had to be relevant to a student population. In the context of the CPM, emotionally charged autobiographical or written scenarios have been used extensively with student samples similar to ours (Gentsch et al., 2018 ; Pivetti et al., 2016 ; Scherer et al., 2022 ). The second selection criterion was that the scenario had to include some ambiguity in their formulation, as early pioneers in emotion research stated the important role of ambiguity in amplifying individual differences in appraisal processes (Lazarus & Folkman, 1984 ). Indeed, recent evidence shows that presenting stimuli with unambiguous valence increases the likelihood of obtaining floor or ceiling effects (Neta & Brock, 2021 ).

In the present work, analyses were conducted on the emotion components embedded in daily life situations. Specifically, out of the four scenarios, we employed the positive one, describing a birthday party - hereafter, Positive Scenario, adapted from Farrell et al. ( 2015 ) and Rohrbacher and Reinecke ( 2014 ) – and one of two negative scenarios, concerning social rejection. The scenario retained in the present work– hereafter, Social Rejection Scenario, adapted from Zimmer-Gembeck and Nesdale ( 2013 ) – reports an incident of ambiguous rejection around a group of close friends. Previous studies on emotion coherence have focused on situations that could activate the four emotion component systems, like anger or surprise situations (Evers et al., 2014 ; Reisenzein, 2000 ): we thus deemed this type of scenario appropriate to maximise a differentiated response in terms of valence and arousal, given the unexpectedness and negativity of the event. The Positive Scenario was tested for comparison purposes, as routinely done in affective science (e.g., Mauss & Robinson, 2009 ; Mauss et al., 2005 ). The other two scenarios, depicting an ambiguous, more active - overt - rejection incident and a neutral situation, are to be employed in a separate study on emotional processing and maladaptive personality, given the cognitive interpretation biases exhibited by individuals with pathological traits in these contexts (An et al., 2023 ; Grynberg et al., 2012 ; Priebe et al., 2022 ). Therefore, these two additional scenarios are not reported here. Nonetheless, the text of all scenarios, along with their corresponding French translations for the selected ones, are reported in supplementary Table S1 .

Within the CPM, the five emotion components (appraisal, physiological reaction, expressivity, experience, and action tendency) were operationalized using a psycholinguistic instrument called GRID (Fontaine et al., 2013 ). The GRID was originally designed to assess semantic profiles of emotions at a componential level with 142 features (i.e., items). Later, the GRID has been applied to emotionally charged situations, such as scenarios (Scherer, 2020 ; Schlegel & Scherer, 2018 ) and video-clips (Mohammadi & Vuilleumier, 2020 ). Due to its length, two shorter versions were derived from the GRID (Scherer et al., 2013 ): the CoreGRID (63 features) and the MiniGRID (14 features).

The GRID, and derivatively the CoreGRID and MiniGRID, are organized at a higher-order level, which comprises a four-factor structure, and a lower-order level (see Table  1 , “Higher Order Factor Assignment”, and “Lower Order Factor Assignment”; Fontaine et al., 2013 ). For the current project, as a trade-off between comprehensiveness and parsimony, we integrated the MiniGRID with the Appraisal component of the CoreGRID to have better coverage of appraisals categories and content.

Appraisal measures

As described in Scherer et al. ( 2013 ), 21 appraisals were derived from the French version of the Appraisal component of the CoreGRID instrument. Appraisals are categorized into the four main SEC functional categories of Relevance, Implications, Coping Potential, and Normative Significance (Fig. S1 ; Table  1 ). Participants rated each of the 21 items for each scenario on a 9-point scale ranging from 1 (not at all) to 9 (completely).

Emotion responses

Emotional reactivity was assessed using the French version of the MiniGRID instrument (Scherer et al., 2013 ), with two items tapping the feeling component, four tapping the physiological component, four tapping the expressive component, and two tapping the action tendency component (Table  1 ).

Other measures

For other projects, additional measures were administered which will not be discussed in depth as not part of the current study. Briefly, participants were asked to rate the intensity of nine categorical emotions experienced in the scenarios on a scale from 0 to 100, and to fill the following individual differences batteries: the Toronto Alexithymia Scale (TAS; Bagby et al., 1994 ), the Difficulties in Emotion Regulation Scale (DERS-F; Dan-Glauser & Scherer, 2013 ), the NEO Five-Factor Inventory (NEO-FFI; Costa & McCrae, 1992 ), the Personality Inventory for DSM-5 (PID-5; Maples et al., 2015 ), the 4-item Patient-Health Questionnaire (PHQ-4; Kroenke et al., 2009 ), the Berkeley Expressivity Questionnaire (BEQ; Gross & John, 1997 ); and the Positive and Negative Affective Schedule (PANAS; Watson et al., 1988 ).

The entire study was conducted on LimeSurvey ( https://www.limesurvey.org/fr ), an online survey platform accessible from smartphones and laptops. All data were anonymized. The study was approved by the Ethics Committee of the University of Lausanne (protocol number: C-SSP-042020-00001).

At the beginning of the online study, students were greeted and given general information about the content of the study. After signing the consent form, they answered general demographic questions. The study was divided in two parts, a scenario part, and a questionnaire part, which were randomized to avoid order effect. Before being confronted with the two scenarios, participants were given a brief instruction based on that of Smith and Lazarus ( 1993 ), encouraging them to imagine themselves in the scenario and to immerse themselves in the emotions, feelings, and thoughts they elicited. Each of the two scenarios started with a description of the scene over a few lines. For each scenario, participants had to answer the selected CoreGRID and MiniGRID items and complete the emotion category questions. At the end of the study, a detailed debriefing on the research questions was provided. The study lasted between 50 and 90 min.

Data processing

Analyses were performed in the R environment (R Development Core Team, 2020 ). For each of the two scenarios, we followed the same steps. Based on Cronbach's alpha calculations, the CoreGRID Appraisal component and MiniGRID items were reversed to obtain coherent response scores. We then transformed our data to ensure that the multivariate normality assumption was met (Epskamp et al., 2018 ). Deidentified data, R scripts for all analyses, and supplementary material - including code source and acknowledgments - can be found at our OSF link at https://osf.io/t9f43/.

Network and dimensionality estimation

To address our first research question, we endorsed the Exploratory Graph Analysis (EGA) framework (Golino & Christensen, 2024 ; Golino & Epskamp, 2017 ). Within this framework, we applied to our transformed data the standard psychometric network model - known as the Gaussian graphical model (GGM; Lauritzen, 1996 ) - in combination with a clustering algorithm– known as the Walktrap community detection algorithm (Pons & Latapy, 2005 ). The GGM estimates partial correlation coefficients that are plotted as edges connecting two nodes (Borsboom et al., 2021 ; Epskamp et al., 2018 ). Edge weights (connection strength) are depicted in the networks, along with their magnitude - thin or thick line - and direction - red for negative and green or blue for positive (Epskamp et al., 2018 ). GGM was used in conjunction with the extended Bayesian Information Criteria (EBIC; Chen & Chen, 2008 ) - graphic least absolute shrinkage and selection operator (lasso; Tibshirani, 1996 ) approach, which shrinks partial correlation coefficients to zero to retain only those truly different from zero (Epskamp et al., 2018 ). The Walktrap community detection algorithm allows the identification of dimensions – or communities – by grouping nodes that are more strongly interconnected in the network (Golino & Epskamp, 2017 ).

We then performed a variable redundancy check. Local dependence – i.e., strong correlations – among items can lead to network instability: we therefore applied Unique Variable Analysis (UVA; Christensen et al., 2023 ), an approach that detects highly correlated items. For the current work, UVA is particularly useful since the Appraisal component of the CoreGRID and the MiniGRID were designed as semantic emotion analysis tools, and high intercorrelations between the items are thus expected. UVA reports the extent to which nodes overlap and share nearly the same relationships with other nodes in terms of edge strength and positive/negative direction via a measure called weighted topological overlap (wTO; Christensen et al., 2023 ). Based on recent guidelines and implementations (Christensen et al., 2023 ; Maertens et al., 2023 ), we implemented a wTO threshold of 0.20, and for each pair of items flagged as redundant, we retained the one with the higher ratio of main network loadings to cross-loadings, to obtain higher dimension stability. Developed within the EGA framework, network loadings have been shown to be equivalent to factor analytic loadings, with values of 0.15, 0.25, and 0.35 indicating low, moderate, and high magnitude, respectively (Christensen & Golino, 2021b ). Indeed, as in factor analytic methods, items that cross-load heavily on dimensions other than the assigned one can lead to model misfit and instability (Christensen et al., 2023 ; Maertens et al., 2023 ).

After network structures and dimensions were retrieved in the empirical data, and redundant items removed, the stability and consistency of these dimensions was inspected with Bootstrapped EGA (bootEGA; Christensen & Golino, 2021a ). Briefly, it is important to inspect if the number of dimensions retrieved by bootEGA is a recurrent solution, or if other dimension solutions are also found. Notably, the more frequently a dimension solution is retrieved, the more stable it is. Perfect stability is reached when the dimension solution is found 100% of time in the bootstrapped replicated samples. An item stability plot is then run to visualize how items are loading on their respective dimensions, and to identify possibly unstable items. Item stability values below the threshold of 0.75 and with network loadings lower than 0.15 signal instability (Christensen et al., 2023 ; Maertens et al., 2023 ). It is recommended to remove such items. The dimensionality and structural consistency of the network is then reassessed in an iterative fashion, until an optimal and stable solution is found (Christensen & Golino, 2021a ).

Following this procedure, we were then able to robustly retrieve the underlying structural and dimensional organization of the CoreGRID Appraisals and MiniGRID components in both scenarios.

Network centrality indices estimation

To address our second research question, we followed the guidelines by Epskamp et al. ( 2018 ). We computed the centrality metrics of Node Strength and Expected Influence, and evaluated their stability. Centrality indices are measures of node importance and indicate which node plays a pivotal role in the network. Node Strength indicates how strongly a node is directly connected to all the other nodes in the network. Expected Influence centrality, on the other hand, is a measure of positive connectivity (Epskamp et al., 2018 ). The larger these parameters, the more influential a given node is in the network. To evaluate the stability of these aforementioned centrality indices, we applied the case-dropping subset bootstrap (Epskamp et al., 2018 ). This method verifies if centrality indices, after iteratively dropping a predefined percentage of cases (i.e., observations) from the dataset, are still stably correlated with the centrality indices of the original dataset. Their stability is measured by a parameter called the correlation-stability (CS) coefficient (Epskamp et al., 2018 ): values above 0.25 indicate acceptable stability, and values above 0.5 indicate optimal stability. Following Epskamp et al. ( 2018 ) guidelines, we also estimated the trustworthiness of edge weights via bootstrapped confidence intervals and via bootstrapped difference tests, which are reported in details in the Supplementary Material. Given that centrality indices are estimated in relation to the network and not to the retrieved dimensions, we also report the results from network loadings: the highest the network loading for a given node is, the most central this node is to its assigned dimension (Christensen & Golino, 2021b ).

Within-dimension and between-dimension mean edge weight comparison

To address our third goal, we followed the procedure recently outlined by Lange and Zickfeld ( 2023 ). Even though dimensionality estimation can provide a visual understanding of emotion components connections, a formal test is needed and was hence conducted. Specifically, the first formal test assesses if edges between the retrieved EGA dimensions are different from zero. This would confirm the utility of using networks to model emotion components: otherwise, emotion components would be perfectly independent and separable, which is against the CPM. The second test assesses if within-dimension edges are stronger than between-dimension edges, which would provide additional insight into coherence among the CPM emotion components. Bootstrapping techniques were used, in conjunction with an adapted version of an equivalence test based on the 95% bias-corrected and accelerated (BCa) confidence intervals and Holm correction for statistical significance testing. We refer the reader to the original publication and script by Lange and Zickfeld ( 2023 ) for further analytical details.

Further exploratory testing

Recently, in a multi-sample study, Schlegel and Scherer ( 2018 ) found an age effect on Emotion Knowledge, that is, the ability to understand and recognize the emotions of others from a componential perspective. Subjects were presented with the five emotion components described in the CPM and had to select those that best represented a given emotional episode. The authors found that emotion understanding increased with age until reaching a plateau in middle and late adulthood, with women scoring slightly higher on the construct. However, to the best of our knowledge, studies examining these demographic differences in age and gender on each and all the five CPM components are virtually absent. The only exception is the recent study by Young and Mikels ( 2020 ) who tested if age differences in the appraisal of personal, other- or circumstantial control over the consequences of ambiguous social and non-social situations emerged in a sample of 50 older adults (M Age  = 62.8; SD = 5.2) and 50 younger adults (M Age  = 22.8; SD = 2.1). Interestingly, older adults appraised situations higher in terms of personal control, and lower in terms of negativity (but similar in terms of positivity), compared to younger adults (Young & Mikels, 2020 ). Given this recent evidence, we deemed appropriate to control for the effects of age (above or below the median age in years; for a similar approach, see McCormick et al., 2023 ) on all CPM components through the metric invariance analyses with permutation tests developed by Jamison et al. ( 2022 ) in the EGA framework. For the sake of comprehensiveness, we also tested for metric invariance for incentive groups (Group 1 versus Group 2) and for gender. While the former test is not expected to yield significant results, gender differences may appear spuriously due to the unbalanced nature of our sample (83% females). We report these exploratory results in detail in the Supplementary Material retrievable at our OSF link. In both scenarios, metric invariance analyses on the CoreGRID Appraisal and MiniGRID items retained in the final EGA models showed no significant differences in network loadings for median age, sex and group belonging as the grouping variables (Table S7-S9 for the negative scenario and Table S10-12 for the positive scenario). Since none of these testings resulted significant, the variables age, gender and groups were not considered further in the modelling process.

The descriptive statistics of the untransformed variables after reversing the marked items are shown in Table  2 (see Table S2 in the Supplementary Material for the descriptive statistics of the transformed variables). For the sake of clarity, in the network analyses, an “S” and “P” prefixes were added to the appraisals and emotional reactivity items from Table  1 to distinguish between those belonging to the Social Rejection and to the Positive scenarios, respectively. The reader can thus refer to Table  1 for variables content.

Social rejection scenario

To answer our first research question regarding the Social Rejection Scenario, after applying the default EGA approach to all 33 transformed CoreGRID Appraisal and MiniGRID items, we first checked for local dependence issues. UVA identified three pairs of redundant items (see Table  1 for items content): SAC2 and SAC4 (wTO = 0.293); SRF1 and SRF2 (wTO = 0.400); and SRA2 and SRA3 (wTO = 0.505). The ratio of network loadings (main/cross-loadings) were as follows: SAC2 = Inf (i.e., perfect loading on assigned dimension) versus SAC4 = 54.289; SRF1 = 2.405 versus SRF2 = 1.712; SRA2 = 2.405 versus SRA3 = 6.416. Therefore, only SAC2, SRF1 and SRA3 were retained in the subsequent analyses.

To explore structural consistency and replicability of the dimensions emerging from these locally reduced data, bootEGA was then performed. The median number of dimensions found via bootEGA in the reduced dataset was 3, with acceptable confidence intervals (95% CI [1.41, 4.59]). However, their structural consistency was very low (0.390, 0.334, and 0.194 for dimension 1,2, and 3, respectively), with item stability indices varying between 25 and 100%, indicating overall instability (Fig. S2 , left panel): as recommended, we therefore removed items with items stability indices below 75% (Christensen & Golino, 2021a ), ending up with 23 nodes. We then repeated the bootEGA procedure, now obtaining satisfactory structural consistency (0.808, 0.952, and 0.996 for dimension 1,2, and 3, respectively) and item stability range (between 91 and 100%). Following existing guidelines, and to further strengthen the structural consistency of our dimensions, we did not retain items with network loadings lower than 0.15, as this denotes weak dimensional belonging (Christensen et al., 2023 ; Maertens et al., 2023 ). With this procedure, two appraisals were discarded: SAI7 (urgency) and SAI8 (personal agency).

The final reduced structure included 21 items from the CoreGRID and MiniGRID , and 90 non-zero edges. The median number of dimensions extracted by bootEGA was 3, with optimal confidence intervals (95% CI [2.55, 3.45]) and even better structural consistency (0.966, 0.972, and 0.984 for dimension 1,2, and 3, respectively) and item stability range (between 97 and 100%; Fig. S2 , right panel). Figure  1 shows the structural and dimensional organization of CPM emotion components in the Social Rejection Scenario.

Estimated network structure and dimensionality results for EGA for the final reduced data set, with unstable items removed. Items labels start with an “S”, denoting their belonging to the Social Rejection Scenario. Connection strength between nodes is represented by lines thickness. Red and green lines indicate negative and positive relations, respectively.

On dimension 1, labelled “Valence/Relevance”, loaded the following items: SAR2 (relevance of personal goal); SAR3 (unpleasantness); SAI2 (negative consequences); SAI4 (need for immediate response); SAC6 (inability to live with consequences); SAN1 (violation of socially accepted norms); SAN2 (violation of personal norms); SRF1 (intensity of emotions); and SRT1 (wanting to tackle the situation). On dimension 2, labelled “Unexpectedness/Coping”, loaded the following items: SAR1 (suddenness); SAI6 (unpredictability); SAC1 (uncontrollability); SAC2 (no control of consequences); SAC3 (no dominance); SAC4 (no power over consequences); SAC5 (powerlessness). Finally, on dimension 3, labelled “Arousal/Expressivity”, loaded the following MiniGRID items: SRA1 (felt weak limbs); SRA3 (breathing faster); SRA4 (sweating); SRE1 (dropped jaw); SRE3 (closed eyes); and SRE4 (speaking more loudly).

To answer our second research question, again focusing on the Social Rejection scenario, we computed the centrality indices of Strength and Expected Influence of the network (Fig.  2 ).

Centrality indices (z-scores) of the CoreGRID Appraisal Component and MiniGRID in the Social Rejection Scenario. Respective communities are indicated

We then investigated the stability of the centrality indices via the case-dropping subset bootstrap approach (Epskamp et al., 2018 ). The CS -coefficients of Strength ( CS (cor = 0.7) = 0.672), and Expected Influence ( CS (cor = 0.7) = 0.672) were all above the cutoff of 0.5. Overall, we can be confident about the interpretation of these centrality metrics (Fig. S3 ).

Results from the edge-weight bootstrapped confidence intervals and bootstrapped difference tests supported the findings that edges were stable, and that the strongest and weakest edges were significantly different from each other (see Figs. S4 , S5 , and Table S3 ). SAI2, SRF1, SRA3, SAC5, and SRA1 were therefore robustly confirmed to be central to the network, in order of magnitude (see Fig, S5 , bottom panels).

Table S4 reports the network loadings for the three dimensions in the Social Rejection Scenario. The results are quite similar to the centrality indices reported in Fig.  2 : SAI2 also emerged as the node with the highest network loading (0.39) within the Valence/Relevance dimension. While SRA1 emerged as the node with the highest network loading (0.39) within the Arousal/Expressivity dimension, SRA3 emerged as slightly more central to the entire network. Similarly, SAC1 emerged as the node with the highest network loading (0.35) within the Unexpectedness/Coping dimension: however, it was not the most central to the entire network, which appeared to be SAC5 instead.

Finally, to answer our third research question for the Social Rejection scenario, the bootstrapped analyses results following Lange and Zickfeld ( 2023 ) procedure are reported in Table  3 . Overall, the average edge between all dimension contrasts were statistically and significantly different from zero (at p  < 0.001 and p  < 0.01), meaning that dimensions were not independent from each other. This is visually evident from Fig.  1 from the dense interconnections between nodes across dimensions.

All the tests concerning the differences of average within- and between-dimension edges were significantly different from zero ( p  < 0.001), meaning that within-dimension edges were stronger than between-dimension edges, for each set of dimension comparisons.

Positive scenario

To answer our first research question regarding the Positive scenario, and after applying the default EGA approach to all 33 transformed CoreGRID Appraisal and MiniGRID items, we first checked for local dependence issues. UVA identified two pairs of redundant items (see Table  1 for item content): PRF1 and PRF2 (wTO = 0.505), as well as PRA2 and PRA3 (wTO = 0.466). The ratio of network loadings (main/cross-loadings) were as follows: PRF1 = 7.134 versus PRF2 = 6.221; PRA2 = 12.505 versus PRA3 = 2.151. Therefore, PRF1 and PRA2 were retained in the subsequent analyses.

To explore structural consistency and replicability of the dimensions emerging from these locally reduced data, bootEGA was then performed. The median number of dimensions found via bootEGA in the reduced dataset was 4, with acceptable confidence intervals (95% CI [2.06, 5.93]). However, their structural consistency was very low (0.282, 0.350, 0.436 and 0.950 for dimension 1, 2, 3, and 4, respectively), with the appearance of other residual dimensions. Item stability indices varied between 19 and 100%, indicating overall instability (Fig. S6 , left panel). As recommended, we thus removed items with item stability indices below 75% (Christensen & Golino, 2021a ), ending up with 18 nodes. We then repeated the bootEGA procedure, obtaining acceptable– but not satisfactory– structural consistency (0.524, 0.720, and 0.968 for dimension 1, 2, and 3, respectively) and item stability range (between 53 and 100%). Following existing guidelines, and to further strengthen the structural consistency of our dimensions, we did not retain items with network loadings lower than 0.15, as this denotes weak dimensional belonging (Christensen et al., 2023 ; Maertens et al., 2023 ). With this procedure, two appraisals were discarded: PAR2 (personal relevance) and PAR4 (other relevance).

The final reduced structure included 16 items from the CoreGRID Appraisal component and MiniGRID , and 58 non-zero edges. The median number of dimensions extracted by bootEGA was 3, with optimal confidence intervals (95% CI [2.79, 3.21]), and satisfactory structural consistency (0.984, 0.868, and 0.990 for dimension 1, 2, and 3, respectively) and item stability range (between 90 and 100%; Fig. S6 , right panel). Figure  3 shows the structural and dimensional organization of CPM emotion components in the Positive Scenario.

Estimated network structure and dimensionality results for EGA for the final reduced data set, with unstable items removed. Items labels start with an “P”, denoting their belonging to the Positive Scenario. Connection strength between nodes is represented by lines thickness. Red and green lines indicate negative and positive relations, respectively

On dimension 1, labelled “Self-Valence/Coping”, loaded the following items: PAR3 (pleasantness); PAI2 (reversed; original formulation: negative consequences); PAI9 (expectations confirmed); PAC5 (reversed; original formulation: powerless); PAC6 (reversed; original formulation: inability to live with consequences); and PAN2 (reversed; original formulation: violation of personal norms). On dimension 2, labelled “Other-Novelty/Relevance”, loaded: PAR1 (suddenness); PAI3 (reversed; original formulation: chance-caused); PAI4 (reversed; original formulation: need for immediate response); and PAI5 (reversed; original formulation: other-agency). On dimension 3, labelled “Emo-Reactivity”, loaded all the MiniGRID items: PRF1 (intensity of emotion state); PRA2 (heartbeat getting faster); PRA4 (sweating); PRE4 (speaking more loudly); PRT1 (wanted to tackle the situation), and PRT2 (wanted to sing and dance).

To answer our second research question, still on the Positive scenario, we computed the centrality indices of Strength and Expected Influence of the network (Fig.  4 ).

Centrality indices (z-scores) of the CoreGRID Appraisal Component and MiniGRID in the Positive Scenario. Respective communities are indicated

The CS -coefficients of Strength ( CS (cor = 0.7) = 0.672) and Expected Influence ( CS (cor = 0.7) = 0.672) were all above the cutoff of 0.5 (Fig. S7 ). Similarly to the Social Rejection scenario, results from the edge-weight bootstrapped confidence intervals and bootstrapped difference tests supported the findings that edges were stable, and that the strongest and weakest edges were significantly different from each other (see Figs. S8 , S9 and Table S5 ). PAR3 and PRF1were confirmed to be the most central to the entire network, followed by PRA2, PAI9, and PRT2, albeit less robustly (see Fig, S9, bottom panels).

Table S6 reports the network loadings for the three dimensions in the Positive Scenario. The results are quite similar to the centrality indices reported in Fig.  4 : PAR3 emerged as the node with the highest network loading (0.37) within the Self-Valence/Coping dimension. PRF1 emerged as the node with the second highest network loading (0.37) within the Emo-Reactivity dimension, preceded by PRA2, and it was the most central to the entire network. PAR1 emerged as the node with the highest network loading (0.43) within the Other-Novelty/Relevance dimension: however, it was not the most central to the entire network, possibly due to the small size of this dimension.

Finally, to answer our third research question regarding the Positive scenario, the bootstrapped analyses results following Lange and Zickfeld ( 2023 ) procedure are reported in Table  4 . Overall, the average edge between all dimension contrasts were statistically and significantly different from zero (at p  < 0.001 and p  < 0.01), meaning that dimensions were not independent from each other. This is visually evident from Fig.  3 from the dense interconnections between nodes across dimensions.

With this study, we aimed to contribute to the existing heterogeneous and sparse multi-componential literature on emotion components using network analysis.

Our first goal was to uncover the structural and dimensional organization of emotion components within the CPM framework in different contexts. Overall, we found densely interconnected networks, with nodes clustering into three dimensions in each scenario. Within their assigned dimensions, some appraisals and emotion responses were unstable and were removed from the models. This is consistent with a variable-set approach to appraisal theories (Fernando et al., 2017 ). Indeed, not all appraisals and emotion responses might be salient in all situations, as cues to make a certain appraisal might be missing. Moreover, an emotion state could be present without the need for a certain appraisal (Fernando et al., 2017 ). To the best of our knowledge, only one other study investigated the influence of context on the semantic meaning of emotion terms within the CPM. Gentsch et al. ( 2018 ) similarly found that appraisal was the least stable component when embedded in an achievement versus a generalised context. In our study, the three-dimensional structure differed in two interesting ways. First, whereas in the negative scenario the focus was on the subjects’ goals, needs, consequences, and coping, in the positive scenario, there was a clearly distinguished self- and other-oriented dimensions. Studies of the appraisal profiles of several positive emotions (Yih et al., 2020 ) have similarly shown the presence of an “other” orientation component. Second, the experiential and action tendency components loaded onto the “Valence/Relevance” and the “Emo-Reactivity” dimensions for the negative and positive scenarios, respectively. One explanation for this finding could lie in the scenario contents themselves. In other words, the negative context could push the responses towards a Valence/Relevance dimension given the unexpectedness feature of the scenario and the need to restore the situation by acting out, something that is not needed in the positive scenario. Similar to our results, Gentsch et al. ( 2018 ) also found that the experiential component qualitatively changed following appraisal changes depending on the context.

Additionally, we replicated the findings by Fontaine et al. ( 2022 ) by retrieving the two stable and transversal dimensions of Valence and Arousal in both scenarios. As further hypothesized, we found that a clearly separated Power dimension emerged in the negative scenario, which we labelled Unexpectedness/Coping, and which included the four Coping Potential appraisals. This Power dimension did not emerge in the positive scenario, where these types of appraisals were less numerous and clustered with Valence-related appraisals, again in line with Fontaine et al. ( 2022 ). We also found their hypothesized patterns of Novelty– Power– Arousal relations. In the positive scenario, the appraisal of immediateness (belonging to the Other-Novelty/Relevance dimension) was moderately and negatively connected to the Action Tendency (behavioral response) component item “Wanted to tackle the situation”. In the negative scenario, the appraisals of suddenness and unpredictability (belonging to the Unexpectedness/Coping dimension) were moderately and strongly connected to the appraisal of uncontrollability (belonging to the Unexpectedness/Coping dimension), respectively. In other words, the higher the Novelty, the lower the Power. In our networks, we found virtually no evidence for the Novelty-Arousal direct relation, only very marginally in the positive scenario, in the direction hypothesized by Fontaine et al. ( 2022 ). The appraisal of suddenness (belonging to the Self-Valence/Coping dimension) was negatively and very weakly correlated with arousal symptoms of sweating (belonging to the Emotion Reactivity dimension). Finally, we found evidence for the Power-Arousal relationship. In the positive scenario, the appraisal of power over the situation (belonging to the Self-Valence/Coping dimension) was negatively correlated with arousal symptoms of sweating (belonging to the Emo-Reactivity dimension). Similarly, in the negative scenario, the appraisal of powerlessness (belonging to the Unexpectedness/Coping dimension) was positively and weakly correlated with arousal symptoms of increased breathing (belonging to the Arousal/Expressivity dimension).

From the above results, a differentiated componential organization emerges as a function of the context, which was also confirmed by the centrality metrics. Indeed, our second goal was to identify the most important node(s) within each network among a truly context relevant pool of features, and within each dimension. Given the similarity of findings, we focus here on the Expected Influence parameter, given its extended use in network research (Robinaugh et al., 2016 ). In the negative scenario, the Expected Influence parameter reported that the appraisal of negative consequences, the current emotion intensity, the appraisal of powerlessness, as well as the autonomic responses of distress (i.e., feeling the limbs weak) and arousal (i.e., breathing faster) were the nodes that, when activated, were responsible for the subsequent activation of the whole network and activation persistence. Similarly, in the positive scenario, the appraisals of situational pleasantness and the intensity state were the nodes with the highest Expected Influence value. The differentiated component patterns tell an interesting story: while in both scenarios the experiential component plays an important role in the network, in a negative context, appraising its consequences and recruiting physical resources as in a fight or flight situation are more central than in the positive context, where the focus seems to be more on the “here and now” in terms of valence and feelings. These findings are consistent with an evolutionary perspective of appraisal, whose paramount goal is to ensure personal well-being in adverse conditions (Ellsworth & Scherer, 2003 ). Moreover, the fact that the appraisal of powerlessness emerged as one of the most central node in the negative scenario is consistent with the attention it has received in appraisal research as a plausible cause for the onset of emotion disorders (Mehu & Scherer, 2015 ). This has recently been shown to be the case when the appraisal of personal coping potential is chronically underestimated, leading to appraisal biases that can impact healthy affectivity in the long run (Scherer et al., 2022 ).

Inspired by the recent work of Lange and Zickfeld ( 2023 ), our third goal was to investigate the relations of emotion components between and within dimensions, and to test if they significantly differ from zero. Overall, we showed, visually and via formal testing, that features within the same emotion components (e.g., appraisal) were more connected to each other than across emotion components, a sign of emotion coherence (Lange et al., 2020 ). For example, within the same appraisal dimension, we found strong relations among valence-oriented features (i.e., appraisal of negative/positive consequences) and unpleasantness/pleasantness of situation. Similarly, within an emotion response dimension, we also found strong relations among emotion response components, such as the distress symptoms of limb weakness and sweating and the autonomic arousal feature of respiration acceleration in the Social Rejection Scenario, or the intensity of the emotion state, the action tendency of wanting to sing and dance, and the arousal response of heart beating faster in the Positive Scenario. This is consistent with Lange and Zickfeld ( 2021 ), who found that the powerlessness/coping potential-related items were more strongly interconnected than with other appraisal categories; and that physiological reactions items also showed thicker edges between them.

Interestingly, when considering the dimensional shift of the experiential component in the two scenarios (i.e., clustering with appraisal in the Social Rejection Scenario, and with emotion responses in the Positive Scenario), we witnessed something similar to Mauss et al. ( 2005 ). After administering an emotionally salient film clip, alternating amusing and sadness scenes, the authors found that the intensity of the experience of amusement correlated with the concordance of physiological and behavioural components, while this was not the case at higher levels of sadness experience. Mauss et al. ( 2005 ) argue that the intensity of the experience of sadness could be decoupled from the other emotion responses because of social pressure, requiring hence to be controlled. This rationale also appears to apply well to the findings in our negative scenario.

Focusing on the CPM, similarly to Meuleman et al. ( 2019 ), we found strong correlations between emotion response components, a sign of emotion coherence. For example, in the positive scenario, we replicated Meuleman et al. ( 2019 )’s positive correlations between the expressive response of “Spoke more loudly” and the action tendency responses of “Wanted to sing and dance” and “Wanted to tackle the situation”, as well as the arousal-related emotion responses of faster heartbeat and sweating, although with some differences in magnitude. Similarly, in the negative scenario, we replicated the positive correlation between the expressive responses of "Jaw drop" and “Spoke more loudly”, and between the latter and the action tendency response of “Wanted to tackle the situation”, and the arousal-related emotion response of sweating, although again with some differences in magnitude. We however also noticed several discrepancies. For example, concerning appraisal-emotion response relations, we found in our Social Rejection Scenario that the appraisal of personal goal relevance was only slightly positively associated with the action tendency component of “Wanting to tackle the situation”. The opposite is true for Meuleman et al. ( 2019 ). In our study, the appraisal of suddenness was not directly related to any emotion response variables, while in Meuleman et al. ( 2019 ) it was moderately and positively correlated with the expressivity factor of “Jaw drop”. Overall, we believe that the standing discrepancies between our results and previous componential literature may be due to the estimation of conditional dependencies, i.e., controlling for all other variables in the network, which may have led to weaker/absent correlations between certain nodes in our study. Another explanation could lie in the estimation of composite scores via principal component analysis in Meuleman et al. ( 2019 ), which might have led to more parsimonious but less nuanced models. Finally, we could argue that Lange and Zickfeld ( 2021 ) have a preponderance of feeling components at the expense of the other components.

From a theoretical standpoint, we provided evidence for the utility of a variable-set conceptualisation of multi-componential emotional episodes (Fernando et al., 2017 ). This approach has been recently proposed as an alternative to early approaches in appraisal theories focused on finding fixed and prototypical patterns of components (Moors, 2024 ). In a data-driven way, we showed that not all appraisals were indeed relevant to a specific context and emotional episode. In other words, we were able to identify the variability in appraisal-emotion response relations across situations (Fernando et al., 2017 ). Moreover, we provided evidence for the interconnection of a comprehensive spectrum of emotion components with advanced and refined analyses, urged within the CPM framework by Scherer and Moors ( 2019 ), extending beyond employing pairs of appraisals (e.g., pleasantness, relevance, and goal conduciveness; Aue & Scherer, 2008 ; Kreibig et al., 2012 ; van Reekum et al., 2004 ) or a limited number of appraisals (Menétrey et al., 2022 ), or appraisal clusters (Meuleman et al., 2019 ). With the present study, we showed how emotion components cluster and cohere differently in different contexts, contributing to a conversation in the field on the topic of emotion coherence which has been long debated (Constantinou et al., 2023 ; Gentsch et al., 2014 ; Sznycer & Cohen, 2021 ). Interestingly, in line with recent evidence (Lange, 2023 ; Lohani et al., 2018 ), we found stronger coherence of emotion components in a negatively salient context, marked by a denser network and a higher number of non-zero edges compared to a positively salient context, which generally speaking is also less researched upon.

From a practical standpoint, the knowledge produced can subsequently inform studies on real-life structural organisation of emotion components and their reciprocal influences (Fontaine et al., 2022 ; Scherer, 2019 ), spurring the field towards the application of networks to ecological momentary assessment of emotion components. This will honour the dynamic system approach roots of emotional episodes as theorised in the CPM (Lewis, 2005 ; Sander et al., 2005 ). More importantly though, we have confirmed the centrality in a negative context of the appraisal of powerlessness, which resonates with recent evidence on the role of the broader Coping Potential appraisal category in predicting the frequency of negative emotions and emotional disturbances (Mehu & Scherer, 2015 ; Scherer, 2020 , 2022 ). Urgency in addressing cognitive biases within this category in young people has thus been strongly vocalized in the field (Scherer et al., 2022 ), as affective disturbances appear to be potentially triggered or worsened by transitioning to university (Duffy et al., 2019 ). Thus, our findings can guide educators, university counsellors and psychologists in the tailoring of existing psychoeducational programs to specifically young students by promoting empowered appraisal along with the strengthening of coping skills (Anderson et al., 2024 ; Compas et al., 2017 ) in the face of daily, ambiguous social situations. Psychologists and university counsellors should also collaborate with policymakers in raising public awareness on mental health well-being in this young population, which appears to have increasingly worsened in the last decade (Arakelyan et al., 2023 ) and in securing a place for the aforementioned psychoeducational interventions in educational curricula across colleges and universities. In turn, policymakers should ensure the allocation of resources for professional developmental programs to train educators, counsellors and teachers, as well as for the optimal implementation and delivery of these interventions.

Finally, regarding the generalizability of our findings, although the validation and application of the GRID instrument have been carried out cross-culturally (Fontaine et al., 2013 , 2022 ), appraisal profiles of positive (Cong et al., 2022 ) and negative (Roseman et al., 1995 ) emotions appear to be modulated by cultural belonging. Thus, emotion components clusters and coherence could also differ across cultures (Lange et al., 2020 ; Mesquita & Ellsworth, 2001 ; Zickfeld et al., 2019 ). Moreover, the young age of our sample prevents generalization of our findings to older populations, as age differences in appraisal processes have been recently showed by Young and Mikels ( 2020 ), although in a small sample. Thus, future studies should tackle these empirical questions, and attempt replication of our findings in larger samples, diversified for culture of belonging and age.

Limitation and future directions

Our study has several limitations. First of all, as we found some evidence of items multi-dimensionality (i.e., item cross-loadings on other dimensions; see Tables S4 and S6), future studies could conduct hierarchical network analysis, a method recently proposed (Jiménez et al., 2023 ). This approach would allow disentangling the variance accounted for in the CoreGRID Appraisal component and MiniGRID items by the four identified higher order factors and replicating the lower-order factors, as in Fontaine et al. ( 2013 ), and explore in a more nuanced way the hypotheses set by Fontaine et al. ( 2022 ). Second, psychometric network analysis does not provide information about the degree of variable endorsement (Lange et al., 2020 ). Hence, we cannot claim that the edges connecting the emotion components in this study apply similarly to everyone. This will require further personalized evidence using techniques such as network comparison tests (van Borkulo et al., 2022 ) or moderated networks (Haslbeck et al., 2021 ). Moreover, network models cannot convey information about causal relationships between nodes as the edges are partial correlation coefficients. In other words, the directionality of effects between two nodes cannot be established (Lange & Zickfeld, 2021 ). Finally, as discussed above, we acknowledge the non-generalizability of our findings, given the employment of only two scenarios, and the exploratory modelling of CPM components, whose dynamic and sequentiality assumptions cannot be met in cross-correlational network models (Lange et al., 2020 ). However, we believe that our work can inspire future researchers to apply network models to emotion components embedded in more diverse contexts, with varying degrees of ambiguity and potentially inform further ecological momentary assessment studies of appraisals and emotional response in everyday life situations.

Overall, this study explored the relationships between emotion components in three novel ways: 1) by using networks, 2) by embedding these in a multi-componential framework, and 3) by providing context to emotion components. Our results can be informative for applied research, such as in educational settings, where understanding the interconnections and centrality of components could aid the personalization of interventions.

Data availability

De-identified data, analyses code and supplementary material are available at https://osf.io/t9f43/

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Acknowledgements

We are grateful to Professor Farrell and Professor Zimmer-Gembeck for sharing their scenarios with us. We are grateful to Professor Christensen for the insightful correspondence on network loadings.

This work was supported by a Swiss National Science Foundation Eccellenza Grant (no PCEFP1_186836) to E.D-G.

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Sacchi, L., Dan-Glauser, E. Network analyses of emotion components: an exploratory application to the component process model of emotion. Curr Psychol (2024). https://doi.org/10.1007/s12144-024-06479-3

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