how to make theoretical framework for qualitative research

Educational resources and simple solutions for your research journey

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  

Summarizing existing literature for theoretical frameworks is easy. Get our Research Ideation pack  

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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Chapter 4: Theoretical frameworks for qualitative research

Tess Tsindos

Learning outcomes

Upon completion of this chapter, you should be able to:

• Describe qualitative frameworks.
• Explain why frameworks are used in qualitative research.
• Identify various frameworks used in qualitative research.

What is a Framework?

A framework is a set of broad concepts or principles used to guide research.  As described by Varpio and colleagues 1 , a framework is a logically developed and connected set of concepts and premises – developed from one or more theories – that a researcher uses as a scaffold for their study. The researcher must define any concepts and theories that will provide the grounding for the research and link them through logical connections, and must relate these concepts to the study that is being carried out. In using a particular theory to guide their study, the researcher needs to ensure that the theoretical framework is reflected in the work in which they are engaged.

It is important to acknowledge that the terms ‘theories’ ( see Chapter 3 ), ‘frameworks’ and ‘paradigms’ are sometimes used interchangeably. However, there are differences between these concepts. To complicate matters further, theoretical frameworks and conceptual frameworks are also used. In addition, quantitative and qualitative researchers usually start from different standpoints in terms of theories and frameworks.

A diagram by Varpio and colleagues demonstrates the similarities and differences between theories and frameworks, and how they influence research approaches. 1(p991) The diagram displays the objectivist or deductive approach to research on the left-hand side. Note how the conceptual framework is first finalised before any research is commenced, and it involves the articulation of hypotheses that are to be tested using the data collected. This is often referred to as a top-down approach and/or a general (theory or framework) to a specific (data) approach.

The diagram displays the subjectivist or inductive approach to research on the right-hand side. Note how data is collected first, and through data analysis, a tentative framework is proposed. The framework is then firmed up as new insights are gained from the data analysis. This is referred to as a specific (data) to general (theory and framework) approach .

Why d o w e u se f rameworks?

A framework helps guide the questions used to elicit your data collection. A framework is not prescriptive, but it needs to be suitable for the research question(s), setting and participants. Therefore, the researcher might use different frameworks to guide different research studies.

A framework informs the study’s recruitment and sampling, and informs, guides or structures how data is collected and analysed. For example, a framework concerned with health systems will assist the researcher to analyse the data in a certain way, while a framework concerned with psychological development will have very different ways of approaching the analysis of data. This is due to the differences underpinning the concepts and premises concerned with investigating health systems, compared to the study of psychological development. The framework adopted also guides emerging interpretations of the data and helps in comparing and contrasting data across participants, cases and studies.

Some examples of foundational frameworks used to guide qualitative research in health services and public health:

• The Behaviour Change Wheel 2
• Consolidated Framework for Implementation Research (CFIR) 3
• Theoretical framework of acceptability 4
• Normalization Process Theory 5
• Candidacy Framework 6
• Aboriginal social determinants of health 7(p8)
• Social determinants of health 8
• Social model of health 9,10
• Systems theory 11
• Biopsychosocial model 12
• Discipline-specific models
• Disease-specific frameworks

E xamples of f rameworks

In Table 4.1, citations of published papers are included to demonstrate how the particular framework helps to ‘frame’ the research question and the interpretation of results.

Table 4.1. Frameworks and references

As discussed in Chapter 3, qualitative research is not an absolute science. While not all research may need a framework or theory (particularly descriptive studies, outlined in Chapter 5), the use of a framework or theory can help to position the research questions, research processes and conclusions and implications within the relevant research paradigm. Theories and frameworks also help to bring to focus areas of the research problem that may not have been considered.

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• Michie S, van Stralen MM, West R. The behaviour change wheel: a new method for characterising and designing behaviour change interventions. Implement Sci .  2011;6:42. doi:10.1186/1748-5908-6-42
• CFIR Research Team. Consolidated Framework for Implementation Research (CFIR). Center for Clinical Management Research. 2023. Accessed February 15, 2023. https://cfirguide.org/
• Sekhon M, Cartwright M, Francis JJ. Acceptability of healthcare interventions: an overview of reviews and development of a theoretical framework. BMC Health Serv Res . 2017;17:88. doi:10.1186/s12913-017-2031-8
• Murray E, Treweek S, Pope C, et al. Normalisation process theory: a framework for developing, evaluating and implementing complex interventions. BMC Med .  2010;8:63. doi:10.1186/1741-7015-8-63
• Tookey S, Renzi C, Waller J, von Wagner C, Whitaker KL. Using the candidacy framework to understand how doctor-patient interactions influence perceived eligibility to seek help for cancer alarm symptoms: a qualitative interview study. BMC Health Serv Res . 2018;18(1):937. doi:10.1186/s12913-018-3730-5
• Lyon P. Aboriginal Health in Aboriginal Hands: Community-Controlled Comprehensive Primary Health Care @ Central Australian Aboriginal Congress; 2016. Accessed February 15, 2023. https://nacchocommunique.com/wp-content/uploads/2017/09/cphc-congress-final-report.pdf
• Solar O., Irwin A. A Conceptual Framework for Action on the Social Determinants of Health:   Social Determinants of Health Discussion Paper 2 (Policy and Practice); 2010. Accessed February 22, 2023. https://www.who.int/publications/i/item/9789241500852
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• Graham-Wisener L, Nelson A, Byrne A, et al. Understanding public attitudes to death talk and advance care planning in Northern Ireland using health behaviour change theory: a qualitative study. BMC Public Health . 2022;22:906. doi:10.1186/s12889-022-13319-1
• Walker R, Quong S, Olivier P, Wu L, Xie J, Boyle J. Empowerment for behaviour change through social connections: a qualitative exploration of women’s preferences in preconception health promotion in the state of Victoria, Australia. BMC Public Health . 2022;22:1642. doi:10.1186/s12889-022-14028-5
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• Lwin KS, Bhandari AKC, Nguyen PT, et al. Factors influencing implementation of health-promoting interventions at workplaces: protocol for a scoping review. PLOS ONE . 2022;17(10):e0275887. doi:10.1371/journal.pone.0275887
• Wilhelm AK, Schwedhelm M, Bigelow M, et al. Evaluation of a school-based participatory intervention to improve school environments using the Consolidated Framework for Implementation Research. BMC Public Health . 2021;21:1615. doi:10.1186/s12889-021-11644-5
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• Laing L, Salema N-E, Jeffries M, et al. Understanding factors that could influence patient acceptability of the use of the PINCER intervention in primary care: a qualitative exploration using the Theoretical Framework of Acceptability. PLOS ONE . 2022;17(10):e0275633. doi:10.1371/journal.pone.0275633
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• Alexander SM, Agaba A, Campbell JI, et al. A qualitative study of the acceptability of remote electronic bednet use monitoring in Uganda. BMC Public Health . 2022;22:1010. doi:10.1186/s12889-022-13393
• May C, Rapley T, Mair FS, et al. Normalization Process Theory On-line Users’ Manual, Toolkit and NoMAD instrument. 2015. Accessed February 15, 2023. https://normalization-process-theory.northumbria.ac.uk/
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• Jones SE, Hamilton S, Bell R, Araújo-Soares V, White M. Acceptability of a cessation intervention for pregnant smokers: a qualitative study guided by Normalization Process Theory. BMC Public Health . 2020;20:1512. doi:10.1186/s12889-020-09608-2
• Ziegler E, Valaitis R, Yost J, Carter N, Risdon C. “Primary care is primary care”: use of Normalization Process Theory to explore the implementation of primary care services for transgender individuals in Ontario. PLOS ONE . 2019;14(4):e0215873. doi:10.1371/journal.pone.0215873
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Qualitative Research – a practical guide for health and social care researchers and practitioners Copyright © 2023 by Tess Tsindos is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License , except where otherwise noted.

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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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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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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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What is a theoretical framework?

Developing a theoretical framework for your dissertation is one of the key elements of a qualitative research project. Through writing your literature review, you are likely to have identified either a problem that need ‘fixing’ or a gap that your research may begin to fill.

The theoretical framework is your toolbox . In the toolbox are your handy tools : a set of theories, concepts, ideas and hypotheses that you will use to build a solution to the research problem or gap you have identified.

The methodology is the instruction manual: the procedure and steps you have taken, using your chosen tools, to tackle the research problem.  

Why do I need a theoretical framework?

Developing a theoretical framework shows that you have thought critically about the different ways to approach your topic, and that you have made a well-reasoned and evidenced decision about which approach will work best. Theoretical frameworks are also necessary for solving complex problems or issues from the literature, showing that you have the skills to think creatively and improvise to answer your research questions. They also allow researchers to establish new theories and approaches, that future research may go on to develop.  

How do I create a theoretical framework for my dissertation?

First, select your tools . You are likely to need a variety of tools in qualitative research – different theories, models or concepts – to help you tackle different parts of your research question.

When deciding what tools would be best for the job of answering your research questions or problem, explore what existing research in your area has used. You may find that there is a ‘standard toolbox’ for qualitative research in your field that you can borrow from or apply to your own research.

You will need to justify why your chosen tools are best for the job of answering your research questions, at what stage they are most relevant, and how they relate to each other . Some theories or models will neatly fit together and appear in the toolboxes of other researchers. However, you may wish to incorporate a model or idea that is not typical for your research area – the ‘odd one out’ in your toolbox. If this is the case, make sure you justify and account for why it is useful to you, and look for ways that it can be used in partnership with the other tools you are using.

You should also be honest about limitations , or where you need to improvise (for example, if the ‘right’ tool or approach doesn’t exist in your area).

This video from the Skills Centre includes an overview and example of how you might create a theoretical framework for your dissertation:

How do I choose the 'right' approach?

When designing your framework and choosing what to include, it can often be difficult to know if you’ve chosen the ‘right’ approach for your research questions. One way to check this is to look for consistency between your objectives, the literature in your framework, and your overall ethos for the research. This means ensuring that the literature you have used not only contributes to answering your research objectives, but that you also use theories and models that are true to your beliefs as a researcher.

Reflecting on your values and your overall ambition for the project can be a helpful step in making these decisions, as it can help you to fully connect your methodology and methods to your research aims.

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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.

Read the full text or download the PDF:

Research Process Guide

• Step 1 - Identifying and Developing a Topic
• Step 2 - Narrowing Your Topic
• Step 3 - Developing Research Questions
• Step 4 - Conducting a Literature Review
• Step 5 - Choosing a Conceptual or Theoretical Framework
• Step 6 - Determining Research Methodology
• Step 6a - Determining Research Methodology - Quantitative Research Methods
• Step 6b - Determining Research Methodology - Qualitative Design
• Step 7 - Considering Ethical Issues in Research with Human Subjects - Institutional Review Board (IRB)
• Step 8 - Collecting Data
• Step 9 - Analyzing Data
• Step 10 - Interpreting Results
• Step 11 - Writing Up Results

Step 5: Choosing a Conceptual or Theoretical Framework

For all empirical research, you must choose a conceptual or theoretical framework to “frame” or “ground” your study. Theoretical and/or conceptual frameworks are often difficult to understand and challenging to choose which is the right one (s) for your research objective (Hatch, 2002). Truthfully, it is difficult to get a real understanding of what these frameworks are and how you are supposed to find what works for your study. The discussion of your framework is addressed in your Chapter 1, the introduction and then is further explored through in-depth discussion in your Chapter 2 literature review.

“Theory is supposed to help researchers of any persuasion clarify what they are up to and to help them to explain to others what they are up to” (Walcott, 1995, p. 189, as cited in Fallon, 2016). It is important to discuss in the beginning to help researchers “clarify what they are up to” and important at the writing stage to “help explain to others what they are up to” (Fallon, 2016).  

What is the difference between the conceptual and the theoretical framework?

Often, the terms theoretical framework and conceptual framework are used interchangeably, which, in this author’s opinion, makes an already difficult to understand idea even more confusing. According to Imenda (2014) and Mensah et al. (2020), there is a very distinct difference between conceptual and theoretical frameworks, not only how they are defined but also, how and when they are used in empirical research.

Imenda (2014) contends that the framework “is the soul of every research project” (p.185). Essentially, it determines how the researcher formulates the research problem, goes about investigating the problem, and what meaning or significance the research lends to the data collected and analyzed investigating the problem.  

Very generally, you would use a theoretical framework if you were conducting deductive research as you test a theory or theories. “A theoretical framework comprises the theories expressed by experts in the field into which you plan to research, which you draw upon to provide a theoretical coat hanger for your data analysis and interpretation of results” (Kivunja, 2018, p.45 ).  Often this framework is based on established theories like, the Set Theory, evolution, the theory of matter or similar pre-existing generalizations like Newton’s law of motion (Imenda, 2014). A good theoretical framework should be linked to, and possibly emerge from your literature review.

Using a theoretical framework allows you to (Kivunja, 2018):

• Increase the credibility and validity of your research
• Interpret meaning found in data collection
• Evaluate solutions for solving your research problem

According to Mensah et al.(2020) the theoretical framework for your research is not a summary of your own thoughts about your research. Rather, it is a compilation of the thoughts of giants in your field, as they relate to your proposed research, as you understand those theories, and how you will use those theories to understand the data collected.

Additionally, Jabareen (2009) defines a conceptual framework as interlinked concepts that together provide a comprehensive  understanding of a phenomenon. “A conceptual framework is the total, logical orientation and associations of anything and everything that forms the underlying thinking, structures, plans and practices and implementation of your entire research project” (Kivunja, 2018, p. 45). You would largely use a conceptual framework when conducting inductive research, as it helps the researcher answer questions that are core to qualitative research, such as the nature of reality, the way things are and how things really work in a real world (Guba & Lincoln, 1994).

Some consideration of the following questions can help define your conceptual framework (Kinvunja, 2018):

• What do you want to do in your research? And why do you want to do it?
• How do you plan to do it?
• What meaning will you make of the data?
• Which worldview will you situate your study in? (i.e. Positivist? Interpretist? Constructivist?)

Examples of conceptual frameworks include the definitions a sociologist uses to describe a culture and the types of data an economist considers when evaluating a country’s industry. The conceptual framework consists of the ideas that are used to define research and evaluate data. Conceptual frameworks are often laid out at the beginning of a paper or an experiment description for a reader to understand the methods used (Mensah et al., 2020).

Writing it up

After choosing your framework is to articulate the theory or concept that grounds your study by defining it and demonstrating the rationale for this particular set of theories or concepts guiding your inquiry.  Write up your theoretical perspective sections for your research plan following your choice of worldview/ research paradigm. For a quantitative study you are particularly interested in theory using the procedures for a causal analysis. For qualitative research, you should locate qualitative journal articles that use a priori theory (knowledge that is acquired not through experience) that is modified during the process of research (Creswell & Creswell, 2018). Also, you should generate or develop a theory at the end of your study. For a mixed methods study which uses a transformative (critical theoretical lens) identify how the lens specifically shapes the research process.                                   

Creswell, J. W., & Creswell, J. D. (2 018). Research design: Qualitative, quantitative, and mixed methods approaches. Sage.

Fallon, M. (2016). Writing up quantitative research in the social and behavioral sciences. Sense. https://kean.idm.oclc.org/login?url=https://search.ebscohost.com/login.aspx?direct=true&AuthType=cookie,ip,url,cpid&custid=keaninf&db=nlebk&AN=1288374&site=ehost-live&scope=site&ebv=EB&ppid=pp_C1

Guba, E. G., & Lincoln, Y. S. (1994). Competing paradigms in qualitative research. Handbook of Qualitative Research, 2 (163-194), 105.

Hatch, J. A. ( 2002). Doing qualitative research in education settings. SUNY Press.

Imenda, S. (2014). Is there a conceptual difference between theoretical and conceptual frameworks?  Journal of Social Sciences, 38 (2), 185-195.

Jabareen, Y. (2009). Building a conceptual framework: Philosophy, definitions, and procedure. International Journal of Qualitative Methods, 8 (4), 49-62.

Kivunja, C. ( 2018, December 3). Distinguishing between theory, theoretical framework, and conceptual framework. The International Journal of Higher Education, 7 (6), 44-53. https://files.eric.ed.gov/fulltext/EJ1198682.pdf  

Mensah, R. O., Agyemang, F., Acquah, A., Babah, P. A., & Dontoh, J. (2020). Discourses on conceptual and theoretical frameworks in research: Meaning and implications for researchers. Journal of African Interdisciplinary Studies, 4 (5), 53-64.

• Last Updated: Jun 29, 2023 1:35 PM
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Research Frameworks: Critical Components for Reporting Qualitative Health Care Research

Qualitative health care research can provide insights into health care practices that quantitative studies cannot. However, the potential of qualitative research to improve health care is undermined by reporting that does not explain or justify the research questions and design. The vital role of research frameworks for designing and conducting quality research is widely accepted, but despite many articles and books on the topic, confusion persists about what constitutes an adequate underpinning framework, what to call it, and how to use one. This editorial clarifies some of the terminology and reinforces why research frameworks are essential for good-quality reporting of all research, especially qualitative research.

Qualitative research provides valuable insights into health care interactions and decision-making processes – for example, why and how a clinician may ignore prevailing evidence and continue making clinical decisions the way they always have. 1 The perception of qualitative health care research has improved since a 2016 article by Greenhalgh et al. highlighted the higher contributions and citation rates of qualitative research than those of contemporaneous quantitative research. 2 The Greenhalgh et al. article was subsequently supported by an open letter from 76 senior academics spanning 11 countries to the editors of the British Medical Journal . 3 Despite greater recognition and acceptance, qualitative research continues to have an “uneasy relationship with theory,” 4 which contributes to poor reporting.

As an editor for the Journal of Patient-Centered Research and Reviews , as well as Human Resources for Health , I have seen several exemplary qualitative articles with clear and coherent reporting. On the other hand, I have often been concerned by a lack of rigorous reporting, which may reflect and reinforce the outdated perception of qualitative research as the “soft option.” 5 Qualitative research is more than conducting a few semi-structured interviews, transcribing the audio recordings verbatim, coding the transcripts, and developing and reporting themes, including a few quotes. Qualitative research that benefits health care is time-consuming and labor-intensive, requires robust design, and is rooted in theory, along with comprehensive reporting. 6

What Is “Theory”?

So fundamental is theory to qualitative research that I initially toyed with titling this editorial, “ Theory: the missing link in qualitative health care research articles ,” before deeming that focus too broad. As far back as 1967, Merton 6 warned that “the word theory threatens to become meaningless.” While it cannot be overstated that “atheoretical” studies lack the underlying logic that justifies researchers’ design choices, the word theory is so overused that it is difficult to understand what constitutes an adequate theoretical foundation and what to call it.

Theory, as used in the term theoretical foundation , refers to the existing body of knowledge. 7 , 8 The existing body of knowledge consists of more than formal theories , with their explanatory and predictive characteristics, so theory implies more than just theories . Box 1 9 – 12 defines the “building blocks of formal theories.” 9 Theorizing or theory-building starts with concepts at the most concrete, experiential level, becoming progressively more abstract until a higher-level theory is developed that explains the relationships between the building blocks. 9 Grand theories are broad, representing the most abstract level of theorizing. Middle-range and explanatory theories are progressively less abstract, more specific to particular phenomena or cases (middle-range) or variables (explanatory), and testable.

The Building Blocks of Formal Theories 9

The Importance of Research Frameworks

Researchers may draw on several elements to frame their research. Generally, a framework is regarded as “a set of ideas that you use when you are forming your decisions and judgements” 13 or “a system of rules, ideas, or beliefs that is used to plan or decide something.” 14 Research frameworks may consist of a single formal theory or part thereof, any combination of several theories or relevant constructs from different theories, models (as simplified representations of formal theories), concepts from the literature and researchers’ experiences.

Although Merriam 15 was of the view that every study has a framework, whether explicit or not, there are advantages to using an explicit framework. Research frameworks map “the territory being investigated,” 8 thus helping researchers to be explicit about what informed their research design, from developing research questions and choosing appropriate methods to data analysis and interpretation. Using a framework makes research findings more meaningful 12 and promotes generalizability by situating the study and interpreting data in more general terms than the study itself. 16

Theoretical and Conceptual Frameworks

The variation in how the terms theoretical and conceptual frameworks are used may be confusing. Some researchers refer to only theoretical frameworks 17 , 18 or conceptual frameworks, 19 – 21 while others use the terms interchangeably. 7 Other researchers distinguish between the two. For example, Miles, Huberman & Saldana 8 see theoretical frameworks as based on formal theories and conceptual frameworks derived inductively from locally relevant concepts and variables, although they may include theoretical aspects. Conversely, some researchers believe that theoretical frameworks include formal theories and concepts. 18 Others argue that any differences between the two types of frameworks are semantic and, instead, emphasize using a research framework to provide coherence across the research questions, methods and interpretation of the results, irrespective of what that framework is called.

Like Ravitch and Riggan, 22 I regard conceptual frameworks (CFs) as the broader term. Including researchers’ perspectives and experiences in CFs provides valuable sources of originality. Novel perspectives guard against research repeating what has already been stated. 23 The term theoretical framework (TF) may be appropriate where formal published and identifiable theories or parts of such theories are used. 24 However, existing formal theories alone may not provide the current state of relevant concepts essential to understanding the motivation for and logic underlying a study. Some researchers may argue that relevant concepts may be covered in the literature review, but what is the point of literature reviews and prior findings unless authors connect them to the research questions and design? Indeed, Sutton & Straw 25 exclude literature reviews and lists of prior findings as an adequate foundation for a study, along with individual lists of variables or constructs (even when the constructs are defined), predictions or hypotheses, and diagrams that do not propose relationships. One or more of these aspects could be used in a research framework (eg, in a TF), and the literature review could (and should) focus on the theories or parts of theories (constructs), offer some critique of the theory and point out how they intend to use the theory. This would be more meaningful than merely describing the theory as the “background” to the study, without explicitly stating why and how it is being used. Similarly, a CF may include a discussion of the theories being used (basically, a TF) and a literature review of the current understanding of any relevant concepts that are not regarded as formal theory.

It may be helpful for authors to specify whether they are using a theoretical or a conceptual framework, but more importantly, authors should make explicit how they constructed and used their research framework. Some studies start with research frameworks of one type and end up with another type, 8 , 22 underscoring the need for authors to clarify the type of framework used and how it informed their research. Accepting the sheer complexity surrounding research frameworks and lamenting the difficulty of reducing the confusion around these terms, Box 2 26 – 31 and Box 3 offer examples highlighting the fundamental elements of theoretical and conceptual frameworks while acknowledging that they share a common purpose.

Examples of How Theoretical Frameworks May Be Used

Examples of How Conceptual Frameworks May Be Used

Misconceptions About Qualitative Research

Qualitative research’s “uneasy relationship with theory” 4 may be due to several misconceptions. One possible misconception is that qualitative research aims to build theory and thus does not need theoretical grounding. The reality is that all qualitative research methods, not just Grounded Theory studies focused on theory building, may lead to theory construction. 16 Similarly, all types of qualitative research, including Grounded Theory studies, should be guided by research frameworks. 16

Not using a research framework may also be due to misconceptions that qualitative research aims to understand people’s perspectives and experiences without examining them from a particular theoretical perspective or that theoretical foundations may influence researchers’ interpretations of participants’ meanings. In fact, in the same way that participants’ meanings vary, qualitative researchers’ interpretations (as opposed to descriptions) of participants’ meaning-making will differ. 32 , 33 Research frameworks thus provide a frame of reference for “making sense of the data.” 34

Studies informed by well-defined research frameworks can make a world of difference in alleviating misconceptions. Good qualitative reporting requires research frameworks that make explicit the combination of relevant theories, theoretical constructs and concepts that will permeate every aspect of the research. Irrespective of the term used, research frameworks are critical components of reporting not only qualitative but also all types of research.

Research Writing and Analysis

• NVivo Group and Study Sessions
• SPSS This link opens in a new window
• Statistical Analysis Group sessions
• Using Qualtrics
• Dissertation and Data Analysis Group Sessions
• Defense Schedule - Commons Calendar This link opens in a new window
• Research Process Flow Chart
• Research Alignment Chapter 1 This link opens in a new window
• Step 1: Seek Out Evidence
• Step 2: Explain
• Step 3: The Big Picture
• Step 4: Own It
• Step 5: Illustrate
• Annotated Bibliography
• Literature Review This link opens in a new window
• Systematic Reviews & Meta-Analyses
• How to Synthesize and Analyze
• Synthesis and Analysis Practice
• Synthesis and Analysis Group Sessions
• Problem Statement
• Purpose Statement
• Conceptual Framework
• Theoretical Framework
• Locating Theoretical and Conceptual Frameworks This link opens in a new window
• Quantitative Research Questions
• Qualitative Research Questions
• Trustworthiness of Qualitative Data
• Analysis and Coding Example- Qualitative Data
• Thematic Data Analysis in Qualitative Design
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Designing the Theoretical Framework

What is it.

• A foundational review of existing theories. 
• Serves as a roadmap or blueprint for developing arguments and supporting research.
• Overview of the theory that the research is based on.
• Can be made up of theories, principles, and concepts.

What does it do?

• Explains the why and how of a particular phenomenon within a particular body of literature.
• Connects the research subject with the theory.
• Specifies the study’s scope; makes it more valuable and generalizable.
• Guides further actions like framing the research questions, developing the literature review, and data collection and analyses.

What should be in it?

• Theory or theories that the researcher considers relevant for their research, principles, and concepts.

Theoretical Framework Guide

• Theoretical Framework Guide Use this guide to determine the guiding framework for your theoretical dissertation research.

Making a Theoretical Framework

How to make a theoretical framework.

• Specify research objectives.
• Note the prominent variables under the study.
• Explore and review the literature through keywords identified as prominent variables.
• Note the theories that contain these variables or the keywords.
• Review all selected theories again in the light of the study’s objectives, and the key variables identified.
• Search for alternative theoretical propositions in the literature that may challenge the ones already selected.
• Ensure that the framework aligns with the study’s objectives, problem statement, the main research question, methodology, data analysis, and the expected conclusion.
• Decide on the final framework and begin developing.

Example Framework

• Theoretical Framework Example for a Thesis or Dissertation This link offers an example theoretical framework.

Additional Framework Resources

Some additional helpful resources in constructing a theoretical framework for study:.

• https://www.scribbr.com/dissertation/theoretical-framework/
• https://www.scribbr.com/dissertation/theoretical-framework-example/
• https://www.projectguru.in/how-to-write-the-theoretical-framework-of-research/

Theoretical Framework Research

The term conceptual framework and theoretical framework are often and erroneously used interchangeably (Grant & Osanloo, 2014). A theoretical framework provides the theoretical assumptions for the larger context of a study, and is the foundation or ‘lens’ by which a study is developed. This framework helps to ground the research focus understudy within theoretical underpinnings and to frame the inquiry for data analysis and interpretation.  The application of theory in traditional theoretical research is to understand, explain, and predict phenomena (Swanson, 2013).

Casanave, C.P.,& Li,Y.(2015). Novices’ struggles with conceptual and theoretical framing in writing  dissertations and papers for publication. Publications,3 (2),104-119.doi:10.3390/publications3020104

Grant, C., & Osanloo, A. (2014). 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

Swanson, R. (2013). Theory building in applied disciplines . San Francisco: Berrett-Koehler Publishers.

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Theoretical Framework

Ai generator.

In the realm of academic and research endeavors, a theoretical framework stands as a guiding beacon, offering structure and direction to studies across various disciplines. Rooted in the amalgamation of elements , characteristics, and observations , a theoretical framework provides researchers with a roadmap to navigate the intricate landscape of their subject matter. This article delves into the depths of theoretical frameworks, shedding light on their definition, crafting process, and their role in research. By the end of this guide, you’ll be equipped with the knowledge to draft a robust theoretical framework that forms the cornerstone of your scholarly pursuits.

1. Literature Review Example

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What is a Theoretical Framework?

A theoretical framework is a conceptual structure that underpins research, outlining the fundamental principles, assumptions, and concepts that shape a study’s approach. It serves as a lens through which researchers view their subject matter, helping to frame the research questions, identify variables, and establish the relationships between them. A well-constructed theoretical framework not only enhances the clarity and coherence of a study but also provides a rationale for the chosen methodologies and interpretations.

How to Draft a Theoretical Framework

Embarking on the journey of constructing a theoretical framework requires a systematic approach that incorporates precision and critical thinking. The following step-by-step guide will assist you in creating a robust theoretical framework for your research, guiding you through each pivotal stage.

Step 1: Identifying the Objective:

At the heart of any theoretical framework lies a clear objective. Define the purpose of your research and the specific problem you aim to address. This step sets the stage for the subsequent construction of your framework, helping you stay focused and aligned with your research goals.

Step 2: Exploring Existing Theories and Concepts:

Delve into the existing body of knowledge within your field. Identify relevant theories, concepts, and themes that resonate with your research objective. By building upon established frameworks, you enhance the credibility and depth of your theoretical foundation.

Step 3: Establishing Relationships and Correlations:

The strength of a theoretical framework lies in its ability to establish meaningful connections. Determine the relationships and correlations between the variables and concepts you’ve identified. This step involves discerning patterns, analogies , and logical linkages that contribute to a cohesive framework.

Step 4: Defining Key Elements and Characteristics:

Assemble the key elements and characteristics that constitute your theoretical framework. Define the variables, constructs, and operational definitions that will shape your study. Ensure that these components align harmoniously to present a comprehensive and coherent structure.

How do I cite a theoretical framework in my research?

When referencing a theoretical framework in your work, follow the citation style specified by your academic institution or publisher. Typically, you would attribute the original source and provide appropriate credit within your text and bibliography.

Can I modify an existing theoretical framework to suit my study?

Absolutely. Adapting an existing theoretical framework to align with your research objectives is a common practice. However, ensure that any modifications made retain the integrity of the original framework while addressing the unique aspects of your study.

Are theoretical frameworks limited to quantitative research?

No, theoretical frameworks are essential for both quantitative and qualitative research. While they may manifest differently in each approach, their role in providing a structured foundation remains consistent.

In the intricate tapestry of research, a theoretical framework emerges as a guiding thread that weaves together concepts, variables, and relationships. By diligently crafting a theoretical framework, researchers illuminate the path toward deeper understanding and meaningful insights. As you embark on your scholarly endeavors, remember that a well-constructed theoretical framework not only elevates the quality of your work but also contributes to the ever-evolving tapestry of human knowledge.

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Article Contents

Epistemic functions of fiction—from ancient philosophy to entertainment research, a social epistemology framework of knowledge acquisition from fiction, inductive phase of theory building: a qualitative approach, social epistemology of knowledge acquisition from fictional entertainment: discussion, research implications, and future directions, epistemic functions of fiction, proposed epistemic processes, general conclusion, supplementary material, data availability, conflicts of interest, acknowledgments.

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Trust but verify? A social epistemology framework of knowledge acquisition and verification practices for fictional entertainment

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Anne Bartsch, Marie-Louise Mares, Johanna Schindler, Jessica Kühn, Ina Krack, Trust but verify? A social epistemology framework of knowledge acquisition and verification practices for fictional entertainment, Human Communication Research , Volume 50, Issue 2, April 2024, Pages 194–207, https://doi.org/10.1093/hcr/hqad036

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Fictional entertainment can serve as a vivid and easily comprehensible source of knowledge, but only if audiences are able to tell its kernel of truth apart from fantasy. In this article, we use the lens of social epistemology to develop a theoretical framework of knowledge acquisition and verification practices for fictional entertainment that integrates various extant lines of work on entertainment education, perceived realism, information processing, credibility assessment, and verification strategies. To flesh out the conceptual model derived from top-down theoretical integration, we use an inductive, bottom-up approach to theory building, assisted by qualitative research. The resulting model describes knowledge acquisition from fiction as an essentially social process characterized by a combination of epistemic trust and epistemic vigilance toward fictional content and sources, in which credibility is assessed via social knowledge sharing and verification practices.

In this article, we propose a theoretical framework of how audiences deal with fictional entertainment as a source of knowledge, with a special focus on social practices for evaluating the credibility of fictional content and sources. For many viewers, fiction can serve as a vivid and easily comprehensible source of knowledge about aspects of reality that they do not know from firsthand experience—for example history, war, current affairs, professional, criminal, or elite milieus. But what motivates audiences to examine the truth value of fiction, and what are their judgment criteria and verification practices?

Understanding how audiences decide what to believe and what to dismiss in fiction is important for several reasons. One is the large time budget individuals spend with fictional entertainment and the growing audience share of “news avoiders” whose media diets almost exclusively consist of entertainment ( Gorski & Thomas, 2021 ). Another reason concerns effects: a long line of theorizing and empirical work suggests that audiences often learn from and are persuaded by fiction. Although research has examined why and how audiences evaluate the veracity of claims in information media and interpersonal communication ( Goldman, 1999 ; Metzger et al., 2010 ; Sperber et al., 2010 ), little work has considered these processes with regard to fiction, or the epistemological challenges posed for audiences by genres that blur fiction and reality. This article presents a theoretical framework of knowledge acquisition and verification practices for fictional entertainment, based on top-down integration of various lines of work (entertainment education, perceived realism, information processing, credibility assessment, verification strategies), and bottom-up qualitative research.

As an integrative framework, we use the lens of social epistemology ( Goldman, 1999 ; Sperber et al., 2010 ; Zagzebski, 2012 ). This approach, which has primarily been applied to interpersonal sources and nonfiction, proposes that knowledge acquisition and verification practices are embedded in a social network of epistemic trust and epistemic authority relationships. We argue that the same is likely to be true for fiction.

To what extent can fiction teach us truths? This question has been a matter of scholarly debate since the times of ancient philosophy (see Golden, 1969 ; Young, 2001 ). For example, Plato was skeptical about the epistemic utility of mimetic art, which he characterized as the “shadow of a shadow” ( Golden, 1975 ), meaning an inferior and distorted representation of the material world which itself is only a representation of the world of ideas. Furthermore, he argued that poets, with their use of rhetoric, incite emotions and passions rather than reason, and were to be banished from his ideal state ( Golden, 1975 ). Aristotle’s (1968) Poetics , in contrast, emphasize the epistemic value of mimesis and catharsis . According to Aristotle, the core function of mimesis is a learning process that moves from the particular to the universal and results in an insight or inference ( Golden, 1969 ). Thus, fictional persons and events can be understood as representations of universal principles of human action that derive their truth value from their similarity with a larger set of real occurrences, rather than from their similarity with a single person or event. In the case of tragedy, the learning process involves catharsis, which can be understood as “intellectual clarification of emotions” ( Golden, 1969 , p. 145). In Aristotle’s work, the pleasure derived from mimesis and catharsis is mainly attributed to their epistemic function—the pleasure of learning an insight ( Golden, 1969 ).

Both views of fiction, as nonrational (and potentially misleading) vs. meaningful learning experience, are reflected in current entertainment research. Work emphasizing uncritical, nonreflective processing includes cultivation theory ( Gerbner & Gross, 1976 ; Shrum, 2006 ), which has drawn attention to the adoption of distorted world views based on biased portrayals of reality on television. Research examining cultivation processes suggests that quick, heuristic processing ( Shrum, 2006 ), and inaccurate memory for the source ( Mares, 1996 ) may contribute to these effects. Other work emphasizing nonreflective processing includes research on transportation ( Green & Brock, 2000 ) and narrative engagement ( Busselle & Bilandzic, 2008 ). Together, these lines of work suggest that fictional narratives can (by engaging our emotions and transporting us into the plot) reduce counter-arguing, and thereby lead to an uncritical transfer of knowledge from fiction to perceptions of social reality.

Other lines of research have focused more on the reflective processing of fictional content. For example, the Aristotelian idea that fiction may provide audiences with an opportunity to gain insight has been adopted in research on eudaimonic entertainment ( Oliver & Raney, 2011 ). This body of work suggests that individuals’ appreciation of meaningful and thought-provoking stories constitutes an important motivation for entertainment consumption, on par with hedonic motivations such as fun and suspense. In line with the notion of catharsis as intellectual clarification of emotions ( Golden, 1969 ), viewers of eudaimonic entertainment reported a sense of affective and cognitive challenge ( Bartsch & Hartmann, 2017 ), and the more moved they felt, the more they engaged in cognitive elaboration and information seeking about the social and political issues portrayed ( Bartsch & Schneider, 2014 ).

How to reconcile these seemingly contradictory views of narrative processing as an uncritical, nonreflective transfer of knowledge from fiction to reality versus meaningful and reflective insight? We propose a two-pronged approach. First, we draw on social epistemology ( Sperber et al., 2010 ) and models of perceived realism ( Busselle & Bilandzic, 2008 ) to argue that narrative understanding involves an initial, tentative stance of epistemic trust that may or may not be followed by critical and elaborate forms of processing. Second, we draw on social epistemology ( Goldman, 1999 ; Zagzebski, 2012 ) and the dual processing model of credibility assessment ( Metzger, 2007 ), to argue that social heuristics can sometimes be as rational and effective as cognitively effortful analytic strategies. Our goal is to integrate heuristic and reflective processes into a single model that would facilitate further hypothesizing not only about the precursors and nature of these processes but also the outcomes with regard to knowledge, attitudes, and behavior.

Social epistemology is a relatively young sub-discipline of philosophy that “focuses on social paths or routes to knowledge” ( Goldman, 1999 , p. 4). That is, it considers the role of secondhand knowledge provided by others (rather than our direct experience), and the social practices for evaluating the validity of such knowledge ( Goldman, 1999 ; Jäger, 2023 ; Sperber et al., 2010 ; Zagzebski, 2012 ). Working from a veristic definition of knowledge as justified true belief ( Goldman, 1999 ), social epistemology often distinguishes “weak” forms of knowledge in the sense of “true belief” adopted unreflectively from accurate sources—as opposed to “strong” forms of knowledge that require “some additional element or elements of justification or warrant for the belief” ( Goldman, 1999 , p. 23).

For example, Sperber et al. (2010) argue that acquiring knowledge from others requires an initial tentative stance of epistemic trust in order to attend to and comprehend the content. However, they note that we have “a suite of cognitive mechanisms for epistemic vigilance, targeted at the risk of being misinformed by others” (p. 359). Epistemic vigilance is conceptualized as a critical (dis)confirmation process that evaluates the credibility of both the source and the content of information communicated by others. Thus, the recipient’s tentative stance of epistemic trust in the comprehension stage can be transformed into an informed and validated sense of either acceptance or rejection of the information ( Sperber et al., 2010 ). In other words, the process of epistemic vigilance serves to clarify the reasons that either warrant rejection of the information or that may transform it from “weak” (relatively unjustified) knowledge into “strong” (relatively justified) knowledge.

The social epistemology framework was developed in the context of interpersonal communication and information media ( Goldman, 1999 ; Neuberger et al., 2023 ; Sperber et al., 2010 ). We argue that it may also be fruitfully applied to fictional entertainment media and that it bears interesting parallels and differences with current work on narrative processing, perceived realism, and credibility assessment. We describe these points of connection and difference below before laying out the theoretical and empirical case for an integrative model.

Narrative comprehension and engagement

In line with Sperber et al.’s (2010) description of tentative epistemic trust in the comprehension stage, Busselle and Bilandzic’s (2008) model of narrative comprehension and engagement posits an uncritical comprehension stage. Audiences for fiction start by positioning themselves in the fictional world, monitoring the characters’ actions, story timelines, etc., to make sense of the unfolding narrative and create a coherent mental model. The viewer’s default epistemic stance is one of accepting the story, so they can experience a sense of flow that drives enjoyment, and such acceptance may facilitate effects on knowledge, attitudes, and behavior. This tacit acceptance can be disrupted by inconsistencies that signal unreality (e.g., the narrative world seems incoherent, or narrative events differ from real-world schemas). Such moments of inconsistency may prompt a second (optional) step in which viewers make reflective judgments of external realism that compare the outcomes of narrative comprehension with real-world knowledge. However, according to the model, this stage of reflecting on realism is not needed for narrative comprehension, learning and persuasion. Indeed, in some instances, such a lack of reflection may be seen as beneficial. For example, when key health messages are embedded in fictional narratives, unreflective epistemic trust may reduce counter-arguing ( Moyer-Gusé, 2008 ; Slater & Rouner, 2002 ) resulting in “weak” but potentially life-saving knowledge.

We agree that reflective evaluations of realism are optional for narrative understanding, learning and persuasion effects to occur. Yet, in line with a social epistemology approach, we propose that such evaluations have an essential epistemic function in that they serve to sort the wheat of valid information from the chaff of make-believe, and because they help clarify reasons that justify belief in that information. That is, default trust in the comprehension stage may lead to ‘weak’ forms of knowledge ( Goldman, 1999 , p, 23) when the information happens to be true (e.g., in entertainment education campaigns that are based on scientific evidence). However, “strong” knowledge in the sense of justified true belief ( Goldman, 1999 , p. 23) requires that the belief is justified with good reasons, which arise from a process of epistemic vigilance that leads to informed confirmation or disconfirmation. In the next section, we turn to work on viewers’ judgments about what constitutes good reasons—the ways in which they evaluate the realism and informational utility of media content.

Perceptions of realism

Perceived media realism, “the way in which a media experience is seen to relate to real-world experience” ( Hall, 2003 , p. 624) has been characterized as a multidimensional construct ( Busselle & Greenberg, 2000 ; Hall, 2003 ; Potter, 1992 ). In reviewing the literature related to the perceived realism of television content, Busselle and Greenberg (2000) identified six dimensions that had been conceptualized and examined by researchers. The first, magic window , referred to young children’s erroneous beliefs that television was a window into a real world where the characters resided. Three further dimensions involved viewers’ judgments about social realism (whether content resembled real life), plausibility (whether events or characters could exist in the real world), and probability (likelihood of events or characters in the real world). Finally, two dimensions involved viewers’ identification with events or characters (e.g., feelings of similarity, closeness, involvement) and perceived utility of the content for their own lives.

Hall (2003) subsequently conducted qualitative focus group discussions to examine how audiences themselves perceived media realism, and how their understandings related to the types of theoretical conceptualizations developed by researchers. She found six empirical dimensions of realism judgments that partly overlapped with the theoretical dimensions identified by Busselle and Greenberg (2000) and that have since been replicated in quantitative survey research ( Cho et al., 2014 ). Of particular interest, the participants in Hall’s (2003) study seemed to agree on a set of three criteria of external realism that involved judgments about connections between the story and the real world: factuality, plausibility, and typicality. Factuality focused on whether the content accurately represented specific real-world persons and events. Plausibility was described similarly to the theorized dimension and typicality combined the social realism and probability dimensions. An additional three criteria were discussed by her interviewees as independent of external realism. Emotional involvement was described in similar terms as the theoretical dimension of identity; participants observed that their emotional responses to the characters and events made fiction seem more real. Narrative consistency refers to the internal coherence and lack of contradiction in a story, regardless of real-world plausibility (e.g., in science fiction or fantasy stories). Perceptual persuasiveness was described as a “compelling visual illusion” (p. 637).

The role of emotional involvement, perceptual persuasiveness, and narrative consistency in Hall’s (2003) interviews seems consistent with Busselle and Bilandzic’s (2008) description of the comprehension stage, in which smooth perceptual, emotional, and cognitive comprehension of narratives results in an uncritical state of engagement characterized by flow, attentional absorption, and transportation. In addition, Hall’s respondents discussed critical evaluations of the factuality, typicality, and plausibility of a story against real-world knowledge. As such, this work hints at the judgment criteria for epistemic vigilance toward fictional content that can lead to ‘strong’ knowledge based on justified confirmation or rejection of the content. What determines whether audiences have the resources to engage in these critical (dis)confirmation processes is suggested by work on information processing.

Cognitive capacity for narrative processing

Several theories have focused on cognitive capacity as an important constraint on individuals’ ability to comprehend and evaluate information in media narratives (e.g., Lang, 2000 , 2006 ). That is, cognitive resources for processing information, such as attentional capacity and working memory, are finite. Whether these resources are fully occupied by encoding and comprehension or there is capacity for epistemic vigilance is theorized to depend on characteristics of the content (e.g., how complex, fast-paced) and characteristics of the viewer (e.g., cognitive development, prior knowledge, and motivation).

According to the limited capacity model of motivated mediated message processing (LC4MP; Lang, 2000 ; 2006 ), a viewer’s motivation for allocating cognitive resources to specific pieces of information can be conscious and volitional. For example, if a viewer’s goal is to learn about a specific topic, such as history, then their attention and epistemic vigilance will be targeted at the historical details in a story, as opposed to details about interpersonal relationships, etc. However, those resources may also be automatically allocated by appetitive and aversive motivational systems. For example, an aversive state, such as cognitive dissonance, aroused by inconsistencies may automatically motivate scrutiny of the discrepant information. Cognitive resources are then reallocated from narrative comprehension and encoding to the process of epistemic vigilance which stores and integrates newly encoded information from the story with real-world knowledge retrieved from memory.

In addition to motivation, the LC4MP ( Lang, 2000 ) draws attention to the role of personal resources as another constraint of knowledge acquisition. Specifically, viewers’ background knowledge is theorized to play a critical role, as it can facilitate comprehension, free up attentional capacity, and provide a basis for evaluating and integrating new information. A narrative format can facilitate comprehension of information ( Lang, 2000 ), even for viewers with minimal background knowledge. Prior knowledge about the real-world situations portrayed is key, however, in the process of epistemic vigilance, because knowledge verification is recursive, in the sense that the validity of new information is evaluated against the background of knowledge that has previously been established as valid.

Given the constraints of motivation and resources, epistemic vigilance is necessarily limited and selective for “online” judgments of external realism which occur during exposure, and which may come at the cost of resources needed for narrative comprehension ( Busselle & Bilandzic, 2008 ). Alternatively, in the case of “offline” judgments, the process of epistemic vigilance can be (partly) postponed until after exposure ( Busselle & Bilandzic, 2008 ). As such, the process of epistemic vigilance can be open-ended and recursive. For example, knowledge verification may start with curiosity or confusion during exposure and may be followed up when more information is presented later in the story, or when more time and resources for elaboration are available after exposure. The validity of knowledge learned can even be revisited after a delay when new resources become available (e.g., after visiting the scene, reading a biography) or when new motivations arise (e.g., an argument about the topic).

With the limits of individual capacity in mind, collective forms of epistemic vigilance where individuals share their background knowledge and their evaluations of source credibility may be particularly useful. These social epistemological processes have primarily been examined in the context of audiences’ assessments of online information. We briefly review that literature, before identifying general principles that may equally apply to fiction.

Credibility assessment and verification of nonfiction content

A considerable body of work has examined the ways in which audiences evaluate and try to verify nonfiction information found online, given the wide array of differing claims and opinions ( Metzger et al., 2010 ; Metzger & Flanagin, 2015 ). Consistent with Sperber et al.’s (2010) notion of epistemic vigilance as involving intertwined evaluations of source and content, Metzger and Flanagin (2015 , p. 446) observe that “In the fields of communication and psychology, credibility is traditionally defined as the believability of information, and it rests largely on the trustworthiness and expertise of the information source or message, as interpreted by the information receiver.” Based on their literature review and survey research, Flanagin and Metzger (2000) identified five credibility criteria: accuracy, authority, objectivity, currency, and coverage, as well as a set of verification practices to assess these criteria—including background research about the authors (their names, organizations, contact, qualification, credentials, goals, and objectives), seeking out other sources to double-check information (its accuracy, currency, comprehensiveness, and objectivity), and looking for endorsement (an official “stamp of approval” or a recommendation from someone they know).

Consistent with the LC4MP ( Lang, 2006 ), Metzger’s (2007) dual processing model of credibility assessment posits that the cognitive complexity of strategies for credibility assessment varies as a function of ability and motivation. Like the concept of epistemic vigilance ( Sperber et al., 2010 ), the motivational component of Metzger’s (2007) model involves awareness of risks and consequences of being misinformed—depending on which, fast heuristic strategies or more elaborate analytic strategies of credibility assessment may be employed. Results from survey research and qualitative interviews suggest that the most common analytic strategies include double-checking facts, checking other websites for supporting contextual information, and considering all views on a topic ( Metzger & Flanagin, 2015 ), while heuristic strategies include reputation, endorsement, consistency with other sources, absence of expectancy violations (e.g., unprofessional appearance, attitude-inconsistency), and persuasive intent ( Metzger et al., 2010 ).

Survey results of Flanagin and Metzger (2000) indicate that heuristic strategies of credibility assessment are employed more often than analytic strategies, particularly for entertainment information but also for news and reference information. Although analytic strategies might seem to provide the best and most rational justification to accept a given piece of information as true, work on “bounded rationality” ( Simon, 1955 ) suggests that individuals may opt for “satisficing” (good enough) options when cognitive resources are limited. Indeed, Metzger et al. (2010) argued that social heuristics can be more efficient and just as effective as effortful analytic strategies, especially in environments like online media that are characterized by uncertainty and information overload. This argument resonates with the core assumption of social epistemology that individual elaboration is not the sole path to valid knowledge. The concept of epistemic authority explains the conditions under which social heuristics can be a rational tool in the process of knowledge acquisition.

Epistemic authority

Belief based on authority (e.g., taking an expert’s word as fact) is one of the most simple and powerful heuristics in social epistemology. In the words of Zagzebski (2012) , “The fact that the authority has a belief p is a reason for me to believe p that replaces my other reasons relevant to believing p and is not simply added to them.” (p. 107). If others know more than we do and if they are sincere in sharing their knowledge, then trusting their judgments can constitute a rational fast-track to knowledge for those who lack the resources and background information to generate or verify a given piece of knowledge by themselves. For example, accepting a diagnosis from a doctor (authority heuristic) is usually more rational than self-diagnosing (individual elaboration). However, for the epistemic authority heuristic to be conducive to valid knowledge, the authority’s advantage in knowledge must not only be subjectively present (we perceive them to be more expert) but also objectively present (they do actually know more than us about the topic). As Jäger (2022) noted, we may subjectively (and erroneously) trust in false authorities who disseminate misinformation unintentionally (pseudo-authorities) or intentionally (fake authorities).

In this context, credibility assessment can be understood as an evaluation of whether a source has the capacities (advanced knowledge and sincerity) that qualify it as an epistemic authority on a given topic ( Jäger, 2023 ; Zagzebski, 2012 ). Thus, credibility assessment occupies a key position at the interface of analytical and heuristic strategies: One well-founded analytical judgment concerning the epistemic authority status of a source can provide individuals with a rational basis for a potentially unlimited number of heuristic judgments concerning the validity of specific pieces of information communicated by the source. Moreover, as illustrated by the work of Metzger et al. (2010) , judgments of epistemic authority are recursive: the epistemic authority of new sources is often evaluated based on knowledge and recommendations of previously established epistemic authorities (the endorsement heuristic). Likewise, consistency of information across sources is taken as an indication that a new source has the same level of advanced knowledge as other authoritative sources. In the case of reputation, a new source is judged by its established epistemic authority relationships with other audience members.

In sum, the rationality of an individual’s assessments of credibility is not based solely on whether the processes were analytical or heuristic. Rather, it also depends on the rationality of the (potentially nested) judgments of epistemic authority that were part of that assessment (i.e., the combined rationality of epistemic vigilance toward the content and source).

Moving toward a social epistemology of fiction

In Figure 1 , we present our initial attempt to integrate these various lines of work into the bare bones of a framework of social epistemology of fiction that highlights the social dimensions of knowledge acquisition and verification practices. To summarize, research on narrative comprehension ( Busselle & Bilandzic, 2008 ) and entertainment education ( Slater & Rouner, 2002 ) suggests that audiences are willing to use fiction as an opportunity to learn from others and that they approach this communicative situation with an initial stance of epistemic trust. At the same time, research on perceived realism ( Hall, 2003 ) documents a degree of epistemic vigilance toward fictional content as expressed in judgments of external realism. Research on credibility assessments for nonfiction ( Metzger et al., 2010 ) draws attention to the social dimensions of knowledge verification, in which content credibility is interpreted in conjunction with source credibility. Audiences often extend the limitations of their own cognitive resources and background knowledge with the help of others who serve as epistemic authorities on the topic—via analytic strategies (double-checking facts, checking for supporting information) and heuristic strategies (reputation, endorsement, consistency among sources).

Knowledge acquisition from fiction as a social process: an initial conceptual model.

Note . The central columns of the figure present the proposed process of knowledge acquisition from fiction—from exposure and comprehension through epistemic vigilance toward the content and source to an informed acceptance or rejection of such knowledge. The left column of the figure presents prior findings about the boundary conditions of this process (e.g., motivations and resources for epistemic vigilance). The right column unpacks what is known about the strategies and outcomes associated with each step in the process and identifies research gaps.

In sum, we propose that learning and verification of knowledge derived from fictional entertainment media are notably social in nature and speak to the philosophical work on social epistemology and epistemic vigilance. Nonetheless, as can be seen from Figure 1 , and as we describe below, many questions remain regarding perceived epistemic functions of fiction as well as motivations, resources, judgment criteria, and verification practices for fictional content and sources. Therefore, to flesh out and refine our top-down conceptual model, we added an inductive, bottom-up element to our theory building, assisted by qualitative research.

RQ1: How do audiences describe the epistemic functions of fiction in terms of knowledge-related uses, knowledge domains of interest and types of knowledge outcomes?

RQ2: How do audiences explain their initial perceptions of realism and credibility with regard to fiction?

RQ3: What motivates audiences to engage in epistemic vigilance with regard to fiction, and which personal and social resources of knowledge do they use?

RQ4: How do audiences explain their judgments of content credibility and external realism with regard to fiction and which criteria do they use?

RQ5: How do audiences explain their judgments of source credibility with regard to fiction, which types of sources do they evaluate, and with which criteria?

RQ6: What verification practices do audiences use to evaluate the credibility of fictional content and sources?

To explore these research questions, we conducted qualitative in-depth interviews with 59 participants from different professional backgrounds: The largest group of interviewees was from the general public (29 participants). A second group came from professions often portrayed in entertainment media (e.g., medical staff, police, law, military, politics; 15 participants). Through the lens of the LC4MP ( Lang, 2000 , 2006 ), this group had favorable preconditions for epistemic vigilance toward the content in terms of resources (advanced background knowledge) and motivation (topic interest). A third group consisted of professionals concerned with the production, verification, and public distribution of knowledge (e.g., scientists, teachers, journalists; 15 participants). We expected that this group would have privileged access to resources (professional research practices and sources) and heightened motivation (accuracy standards) for epistemic vigilance toward both content and sources. Taken together, the three groups were designed to shed light on a broad spectrum of strategies for epistemic vigilance and knowledge acquisition from fiction, including epistemic goals and practices that may go beyond the motivation and resources of lay audiences. In addition, we took care to include participants from different educational backgrounds and with different entertainment preferences (e.g., novels, movies, TV series, video games). The full sample consisted of 59 participants, 29 male and 30 female, aged between 18 and 63 years (for an overview of age, gender, occupational groups, and interview IDs, see Supplementary Appendix 1 ).

The interviews were conducted in Germany and lasted about 45 min. Informed consent about the interview procedure, recording, transcription, and anonymization was obtained. A semi-structured interview guideline was used including questions about audiences’ use of fictional entertainment media as a source of knowledge (RQ1), their initial perceptions of realism (RQ2), their motivations and resources for epistemic vigilance (RQ3), their judgments of content credibility (RQ4) and source credibility (RQ5), and their verification practices (RQ6). The interviews were fully recorded, transcribed and analyzed using MAXQDA software. Consistent with an exploratory research design, the material was analyzed using both deductive categories derived from theoretical concepts and inductive categories developed from the interviews ( Mayring, 2000 ).

When asked about examples of knowledge gained from fictional entertainment, participants discussed various types of media and genres . TV series and movies were the media from which the most examples were cited, followed by novels and video games. Drama was by far the most frequently mentioned genre, followed by crime drama, comedy, science fiction, fantasy, action, and thriller. The examples discussed in the interviews included narratives based on a true story as well as purely fictional content. Figure 2 provides an overview of the main and sub-categories of statements concerning our research questions. As such, it fills in some of the gaps in Figure 1 and provides a visual summary of our refined social epistemology framework of knowledge acquisition and verification practices for fictional media content. Frequency counts of statements in each category are displayed in parentheses in Figure 2 . Additional information about frequencies of statements per sub-sample is provided in Supplementary Appendix 2 . Quotes from the interviews in the text below are annotated with participant identification numbers and transcript lines in parentheses.

Knowledge acquisition from fiction as a social process: a refined conceptual model including insights from the inductive qualitative phase of theory building.

Note . Frequency counts in parentheses reflect the number of statements per category, including the possibility of multiple statements per category in the same interview.

RQ1: Perceived epistemic functions of fiction: knowledge types, domains, and uses

Our first research question inquired about the perceived epistemic functions of fiction, specifically participants’ perception of knowledge-related uses, as well as the range of knowledge types and knowledge domains that they sought from fictional entertainment.

Knowledge-related uses

Concerning their motivations for using fictional media, most interviewees reported both entertainment motives (mood management, transportation, suspense, escapism) and epistemic motives, such as topic interest and learning—with the notable exception of journalists as the sole group who (consistent with professional norms) denied using fiction for information purposes. Many participants valued fiction as an easily accessible source of knowledge due to its comprehensibility, vividness, and emotionality, and described fiction as a fun and inclusive conversational topic. Interestingly, more than half of the participants—including journalists—mentioned that learning sometimes occurred as an unexpected byproduct from the use of fiction for entertainment purposes.

Knowledge domains

With regard to learning experiences from fictional entertainment, participants reported a remarkably broad spectrum of knowledge domains. The most frequent domain was history, followed by crime/law, politics, military/war, medicine, science/technology, lifestyle/relationships, and foreign countries. To further elucidate the perceived knowledge functions of fiction, we also analyzed the types of knowledge discussed.

Knowledge types

Factual knowledge.

With the chemist, uh, “Breaking Bad”, for example, you also have chemical, physical concepts and compounds, and in physics lessons I was never interested in that. (ID01, 43)

I have to mention “Assassin's Creed,” of course. My girlfriend and I had some weird moments in Rome, where one of the games is situated. You are standing inside the Colosseum, and you think: Wow, I’m quite familiar with this place! It’s so accurate in every detail. Also, in the Castel Sant'Angelo we thought: Oh my god, I know what’s around the corner, even if I’ve never been here before. (ID39, 6)

Practical knowledge

Another knowledge function discussed by the interviewees was the acquisition of practical knowledge for dealing with real-life situations. Examples ranged from the learning of foreign languages and technical terms to useful job-related information, for example about medical diagnoses (ID23, 71). Some interviewees even mentioned that fictional content informed their career choices (ID21, 96; ID07, 80).

Authentic knowledge of inaccessible situations and events

She attends her sister from the outbreak of her cancer till the end. And you realize what a machinery you get caught in as a patient, what they do with you, and how your environment has to live with and learns to live with it. And I thought that afterwards I understand the world of people who are terminally ill better than before. (ID35, 52)

Knowledge about the self and human nature

The video game Heavy Rain affected me deeply, because I have a son too. There is this opening scene, where the main character loses sight of his son on a crowded children's playground. And suddenly you have to answer all these questions at the police station: What time was it? What did he wear? – I wasn’t aware of these things in the game, I didn’t see it, or didn’t think it could be important. And suddenly you are confronted with it. That hit me personally, because in real life, I should have paid attention all the time. That hit me like a rock. (ID46, 7)

RQ2: Initial perceptions of realism of fictional entertainment

Our second research question dealt with audiences’ initial perceptions of realism. When asked about their intuitive sense of realism, most interviewees discussed emotional and perceptual features, narrative consistency, and/or consistency of the content with their attitudes, values, and beliefs. The first three categories were similar to the corresponding categories in Hall’s (2003) research and are therefore presented only briefly.

Emotional involvement

Many participants mentioned that their perceptions of realism were influenced by emotional responses to the characters and events, such that stronger responses of empathy and identification made the fictional content seem more real.

Perceptual plausibility

Many participants also mentioned the influence of perceptual features that contributed to their sense of felt realism. The most frequently mentioned features were visual realism (i.e., the creation of a compelling visual illusion) and the quality of acting.

Narrative consistency

The inner logic and consistency of fictional stories further contributed to perceptions of realism. Many interviewees reported that feelings of confusion or contradiction made a story seem unreal, whereas the smooth processing of self-consistent stories contributed to their sense of felt realism.

Attitude consistency

I think especially because you can participate and follow your own opinion and make your own decisions to change the course of action in the game, that makes a difference, that makes it seem more realistic. (ID42, 17)

Most participants voiced self-critical awareness that their affective, perceptual, consistency-, and attitude-based perceptions of realism were potentially biased and insufficient as a rational basis for judging the external realism and truth value of fictional content. They often reported that their initial perceptions of realism and credibility emerged from “intuition” (ID59, 76) or “gut feelings” (ID20, 54) which they were unable to explain or justify further.

RQ3: Motivations and resources for epistemic vigilance

Such initial, “weak” judgments of realism can be subject to a process of critical scrutiny that can lead to “stronger”, more justified reasons to accept or correct the initial judgment. RQ3 inquired about audiences’ motivations and resources for this process of epistemic vigilance.

Motivations for epistemic vigilance

This horror scenario where you're scared that it could really happen that the world is going to end because of the economic crisis, somehow… I don't know, it was just so unbelievable that I had to google it. (ID29, 108)

Resources for epistemic vigilance

Or international conflicts on a military level, what are the structures, how do nations work together? How, if you go into the details, how do different nations fly together, how do they organize? There was reference to maneuvers that I've been part of myself, and somehow the circle closes when you say, yes, I've seen this, I've been part of it. (ID03, 49)

For example, with colleagues at school, other historians or other acquainted colleagues. And with [first name], my son, I talk about it quite a lot, especially in the case of historical series. With people who are also interested in history. You compare a bit: Was it like that or was it different, what do the sources say? (ID58, 50)

It is important to note, however, that some participants mentioned situations when, despite their critical awareness and resources for epistemic vigilance, they “contented” themselves with an unresolved sense of epistemic uncertainty. (ID59, 38; ID02, 68)

RQ4: Epistemic vigilance toward the content: judgments of external realism

Interview statements concerning participants’ epistemic vigilance toward the content of fictional entertainment mainly replicated the criteria of external realism identified in prior research ( Hall, 2003 ). Therefore, the findings are summarized relatively briefly.

One of the critical judgment criteria reported by the interviewees was how consistent the fictional content was with preexisting factual knowledge, especially in the case of participants with first-hand experience of the issues portrayed.

Participants criticized the lack of realism and insight in fictional stories that simply reproduced social stereotypes or genre routines. Conversely, the content was judged more credible if the resources, abilities and responses of the characters were consistent with participants’ real-life experiences.

Plausibility

Judgments of plausibility dealt with the causal logic and coherence of stories concerning physical, social, and psychological principles that apply in the real world.

RQ5: Epistemic vigilance toward the source: judgments of source credibility

Participants mentioned considering the credibility of specific entertainment media and genres. For example, books (ID16, 44) and historical dramas (ID37, 43) were mentioned as relatively credible compared to other media and genres such as comedy and fantasy (ID30, 55). In addition, participants said that they considered the credibility of specific persons (e.g., authors, directors, actors) and production teams behind specific media titles.

There are thriller authors like Frederick Forsyth. I think he’s incredibly good. He’s formerly been a journalist himself and a MI6 agent, and his thrillers always border on reality. And it always feels like someone leaked some information to him that you don’t know yourself, but it recently happened exactly like this. (ID05, 145)

Probably it’s that I have heard any details that occur in it before, and I use those as fixpoints whether the rest is also credible. So, if I already know some information and I know it's true, then I think okay, the rest will be fine as well. (ID19, 48) When there are too many inconsistencies that simply don’t fit with my personal experience. Or when I simply know that things can't be like that, like in the mountain film, when I see that there's a wrong knot in the rope, and I think to myself - then it's all wrong from start to finish. (ID14, 87)

RQ6: Verification practices for knowledge derived from fictional entertainment

Our sixth and final research question inquired about audiences’ use of verification practices. In addition to comparing fictional content with their own background knowledge, participants discussed a broad spectrum of social verification strategies. As reported above, initial perceptions of realism were shaped by smooth emotional, perceptual, narrative, and attitude-consistent processing, which can already be interpreted as a basic form of credibility assessment in line with the expectancy violation heuristic ( Metzger et al., 2010 ). Further heuristic strategies of credibility assessment included reputation and endorsement.

When Oliver Stone makes a movie about the war in Vietnam or so, then it is preceded by quite different and much deeper research. So, it very much depends, uh, what kind of format are we dealing with, and how high are the standards that the makers set for themselves. (ID17, 10) Actors are a very good indicator, I think, because there are actors who are very knowledgeable and who would never act in any bullshit film. (ID29, 71)

Endorsement

Mostly, I proceed from Wikipedia to other sources, as they always report how realistic is the film, what kind of reviews did it get. That means, Wikipedia aggregates the film reviews, most of which are also concerned with the truth content. (ID15, 76) Some colleagues discussed the truth content of House of Cards, especially those who have been foreign correspondents in the US. Of course, it's exciting for them because they can compare it with their own experience and it's quite interesting to hear what they say. (ID51, 44)

Double-checking facts and consistency with nonfiction media

Yes, I do research quite often. At home in my standard literature, but also in scientific publications. I also do research on the Internet. Or, if I’m very interested, and I have the feeling that the truth is distorted and there is a historical misrepresentation, then I also get appropriate literature. (ID05, 68)

Seeking supporting contextual information

Sometimes, like in the case of The Big Short, I start to talk with people and to get information otherwise, like I started to watch economics lectures, just because I was interested. It was actually like, I watched several finance movies, including other, less realistic ones, like The Wolf of Wall Street, and that led me to get mentally involved with the topic, and in the next step to get actually informed about it. (ID13, 149)

It is important to note, however, that social verification was not a standard practice for most participants. Although a majority remembered some or even regular situations when they extended the boundaries of their own knowledge by consulting knowledge provided by others, social verification strategies required motivation and access to social resources.

RQ1–6: Sub-sample considerations

Across the set of research questions, the epistemic goals and practices reported by our three groups of participants were largely comparable. Although space limitations preclude detailed analysis here, Supplementary Appendix 2 gives the frequency counts of statements per subsample. Of particular interest from a social epistemology perspective, social heuristics, such as reputation, endorsement, and consistency with other trusted sources were mentioned by lay and expert audiences alike—meaning that both relied on a network of trusted epistemic authorities to extend the boundaries of their own knowledge. What was qualitatively different between groups, however, was the privileged access of experts to personal and social resources for epistemic vigilance, including advanced background knowledge, professional research skills, and high-quality sources (e.g., scientific literature and well-informed colleagues). Therefore, despite the structural similarities of knowledge acquisition processes, the quality of outcomes likely differed between lay and expert audiences.

It is important to note that our interview sample was not representative of the general population. Experts with first-hand experience and knowledge-related professions were oversampled to gain insight into a spectrum of strategies for epistemic vigilance, including strategies that may go beyond the motivation and resources of lay audiences. Using a qualitative approach, we were able to observe important similarities of knowledge acquisition and verification practices across subsamples. However, our interview sample was inadequate to assess the frequency and efficacy with which such practices are used. Further quantitative research is needed to examine their prevalence and outcomes in the general population.

Our theoretical and empirical investigation set out to explore the process of knowledge acquisition from fiction with a special focus on social practices for epistemic vigilance toward fictional content and sources. Overall, our findings are consistent with and suggest important extensions to the research literature on perceived realism ( Busselle & Bilandzic, 2008 ; Hall, 2003 ), entertainment education ( Moyer-Gusé, 2008 ; Slater & Rouner, 2002 ), and dual process models of entertainment ( Bartsch & Schneider, 2014 ). By integrating this literature with work on social epistemology ( Goldmann, 1999 ; Sperber et al., 2010 ; Zagzebski, 2012 ), information processing ( Lang, 2000 ), credibility assessment ( Metzger et al., 2010 ), and inductive findings from our qualitative study, knowledge acquisition from fiction can be conceptualized as a complex process with important social dimensions. Figure 2 provides a visual summary of our proposed social epistemology framework. Instead of reiterating all the theoretical assumptions that informed our model, we focus our explication on novel findings from the inductive phase of theory building and discuss how the emergent constructs can be operationalized for further research testing the proposed processes and boundary conditions.

The interviews provided new insight into the diversity of perceived knowledge functions of fictional entertainment, including topic interest in domains comparable to information media (e.g., history, politics, war, crime, medicine, and science). In some cases, fiction was sought intentionally as a vivid and easily comprehensible source of knowledge, but participants also reported that learning often occurred as an unexpected byproduct of entertainment. The knowledge types discussed were not limited to factual information but also included knowledge of practical use and generalized interpretive knowledge concerning the authentic experience of inaccessible or unknown situations, and knowledge about the self and human nature. Such complex knowledge structures that enable meaningful integration and interpretation of information beyond individual facts were emphasized by many participants as a particular strength of fiction compared to information media. They seem to bear resemblance with concepts from the epistemology of art and fiction such as mimesis and catharsis ( Aristotle, 1968 ; Golden, 1969 ).

The distinction between these different types of knowledge has implications for the conceptualization and measurement of knowledge outcomes from fiction. Factual knowledge is well-operationalized ( Lang, 2000 ) in terms of both cued recall (e.g., multiple-choice items) and free recall (e.g., open-ended answers). However, the assessment of practical knowledge for dealing with real-life situations might require additional indicators such as perceived usefulness, actual application of knowledge, and outcomes of such application. Similarly, generalized interpretive knowledge still awaits systematic operationalization to measure what viewers learn about the meaning and lived experiences of depicted situations, or about the self and human nature. Assessing such complex interpretive knowledge structures may require an initial step of gathering open-ended responses (e.g., thought-listing, essay-writing), which can then be coded or translated into standardized items to generate quantitative measures. Research on eudaimonic entertainment ( Bartsch et al., 2020 ; Oliver & Hartmann, 2010 ) has experimented with such measures, but their operationalization is still in its infancy.

Conceptual and operational progress concerning the types of knowledge derived from fiction could facilitate research on downstream, persuasive effects. For example, factual knowledge can serve as a corrective for error and ignorance, which can change the argument base for attitudes and behavioral intentions. Practical knowledge can add an element of self-efficacy to attitudes and intentions that may otherwise remain inconsequential ( Moyer-Gusé, 2008 ). Interpretive knowledge can change the perceived relevance and evaluation of facts. For example, stories that illustrate the meaning and emotional significance of facts from the perspective of people affected have been found to stimulate information seeking, political participation, and attitude change towards stigmatized social groups ( Bartsch & Schneider, 2014 ; Oliver et al., 2012 ). Further refinement of knowledge variables can help elucidate the array of persuasive effects of fiction, and the preconditions needed for them to occur.

As shown in Figure 2 , our model describes a sequence in which audience members pass through an initial stage of narrative comprehension and tentative epistemic trust and then may engage in varying levels of epistemic vigilance toward the source and content, which in turn give rise to more or less informed judgments to accept or reject the information.

The narrative comprehension part of our model is one area that was already relatively well-researched (for overviews, see Busselle & Bilandzic, 2008 ; Moyer-Gusé, 2008 ; Lang, 2000 ). As summarized earlier, emotional involvement, compelling imagery, and narrative consistency can foster a state of transportation associated with unreflective epistemic trust, knowledge acquisition and persuasion. Our interviewees also mentioned attitude consistency as a factor of initial epistemic trust, although prior work indicates that mistrust and resistance to attitude-inconsistent information can be mitigated by transportation ( Moyer-Gusé, 2008 ).

Less is known about the process of epistemic vigilance in which relatively “weak” and unjustified knowledge from the narrative comprehension stage can be transformed into “stronger”, more justified knowledge or rejection of the content. Below, we explicate the inductive findings and testable propositions we derived concerning the ways in which motivations and resources for epistemic vigilance interact in predicting credibility judgments, verification strategies, and knowledge outcomes.

In a nutshell, effortful, time-consuming credibility assessments and verification strategies require more motivation than simple heuristics, but access to resources can lower the motivational threshold, such that the same strategies require less time and effort. In particular, verification processes can be facilitated and accelerated with the help of epistemic authorities who offer pre-processed information, arguments and interpretations. Therefore, our model proposes that motivations and resources for epistemic vigilance should interact to predict the quantity and quality of (a) judgments of content credibility; (b) judgments of source credibility; and (c) verification strategies employed. These three factors should in turn predict the accuracy and justification of viewers’ decisions whether to accept or reject knowledge presented in fictional media. Thus, indirectly, motivations and resources for epistemic vigilance should also predict the quantity and quality of (d) knowledge items learned. Below, we walk through the components of the model including possible operationalizations.

Consistent with the LC4MP ( Lang, 2000 , 2006 ), our interviewees reported intentional, goal-directed motivations for reallocating cognitive resources to epistemic vigilance (topic interest, verification of claims that the content was based on a true story) as well as automatic resource allocation (aroused by emotions and discrepancies). Future research to assess the impact of these motivations may operationalize intentional epistemic vigilance through instructions and learning goals, and may prompt automatic forms of epistemic vigilance by stimulus features that arouse epistemic emotions such as surprise, curiosity, and confusion ( Vogl et al., 2020 ).

Also consistent with the LC4MP ( Lang, 2000 ), our participants described using their background knowledge as a resource to assess the veracity of information. Additionally, the social epistemology perspective ( Goldman, 1999 ; Zagzebski, 2012 ) suggests that individuals’ resources for epistemic vigilance may be enlarged by their networks of trusted epistemic authorities. Consistent with this, our interviewees reported that they relied on online resources such as Wikipedia, traditional information media like news and documentaries, as well as interpersonal communication with well-informed family members, friends, and colleagues. Personal knowledge resources can be operationalized in further research via self-report or by experimental assignment to background information conditions. Access to social knowledge resources could be assessed via (self-)observation or be manipulated by allowing vs. restricting the use of communication technologies.

Epistemic vigilance toward the content: assessment of external realism

As in the study of Hall (2003) , our interviewees judged the external realism of fictional content not only by its factuality but also by its typicality and plausibility. These latter criteria seem to reflect a type of epistemic vigilance that probes the validity of generalized interpretive knowledge about the lived experience of people in the situations portrayed, rather than the accuracy of specific facts. Therefore, the number of facts evaluated provides only one indicator of external realism judgments which may be complemented with qualitative and/or quantitative assessment of details and arguments that informed typicality and plausibility judgments.

Epistemic vigilance toward the source: assessment of source credibility

Participants’ discussion of source credibility provided initial qualitative evidence that the concept of epistemic vigilance toward the source ( Sperber et al., 2010 ) can be meaningfully applied to fictional sources. Not all criteria of online credibility assessments observed by Flanagin and Metzger (2000) were mentioned by our interviewees, but their judgments of expertise, research practices, and pars-pro-toto judgments of the perceived (in)accuracy of insider knowledge seemed to reflect assessment of epistemic authority and source accuracy. Whether source credibility is evaluated at all provides a first indicator of epistemic vigilance. More detailed assessments may consider the number and quality of reasons given (e.g., using one vague criterion such as genre vs. using multiple specific criteria such as expert advisors, research effort, insider knowledge, or recommendation from well-informed others).

Verification practices

In addition to evaluating content and source credibility based on their own background knowledge, participants reported a broad range of social verification practices. As noted by Metzger et al. (2010) , it is often difficult to empirically distinguish between analytic and heuristic strategies or to divide heuristics into mutually exclusive categories. In our interviews, fact-checking and seeking supporting information overlapped with checking for consistency with non-fiction sources. Moreover, social heuristics, such as reputation and endorsement, were sometimes mentioned in conjunction with elaborate strategies, such as reading multiple reviews or extensive discussions with those who recommended the source. Further observational research is needed to better understand the social dimensions of verification strategies, but self-reported time, effort, and cross-verification of sources may be used as a first approximation to assess the intensity of verification behavior.

Knowledge outcomes

Motivation and resources are assumed to predict both processes and outcomes of information processing. Specifically, the LC4MP ( Lang, 2000 ) assumes that the extent of resources allocated to encoding, reflection and storage of information predicts the ease of subsequent retrieval. Therefore, epistemic vigilance should not only increase the accuracy and justification of viewers’ decisions whether to accept or reject knowledge presented in fictional media (the quality of knowledge outcomes), but it should also increase the probability that such knowledge can be remembered via free or cued recall (the quantity of knowledge outcomes).

It is important to note, however, from an epistemological standpoint ( Goldman, 1999 ; Jäger, 2022 ), that knowledge outcomes are determined not only by the process of epistemic vigilance but also by the information quality of the source. The quality of information presented in fictional entertainment can vary widely, from realistic stories based on historical or scientific evidence (including entertainment education) to scripted reality, unrealistic fantasy, conspiracy fiction, or ideological propaganda stories. Thus, initial epistemic trust in the comprehension stage may result in “weak” but accurate knowledge or complete misinformation, depending on the accuracy of the content. The concept of epistemic authority ( Jäger, 2022 ; Zagzebski, 2012 ) offers a lens through which the rationality of epistemic trust can be evaluated: Is the source adequately knowledgeable (e.g., via background research or expert advisors), and sincerely committed not to distort the truth (e.g., for the sake of drama or ideology)? Epistemic vigilance can be understood as viewers’ attempt to answer these questions for themselves or with the help of well-informed others. However, a comprehensive understanding of the social epistemology of fiction also needs to consider the information quality of fictional entertainment by analyzing the content and how it is produced.

In the context of a changing media landscape where the lines between fact and fiction, information, misinformation, inaccuracy, error, and blatant lies are increasingly blurred, there are increasing demands on audiences’ epistemic vigilance and responsibility to double-check the knowledge they have learned from media content. We propose that fiction is no different in this regard from other information sources with uncertain truth-value that already constitute a large and constantly rising share of individuals’ present-day media diets ( Ha et al., 2021 ). Indeed, our study highlights important similarities between the social epistemological processes already studied with regard to information media and those reported by our participants in evaluating fiction. By integrating research across these seeming divides of fact and fiction, our model may help elucidate critical audience skills that individuals use to resolve epistemic uncertainty in general—not only in the case of fiction but in the case of other types of media content as well. We hope that our model will help advance the theoretical and empirical integration of research on audiences’ motivations, resources, judgment criteria and verification practices concerning the truth value of knowledge learned from the media, across the divide of entertainment and information media.

Supplementary material is available at Human Communication Research online.

The data underlying this article cannot be shared publicly for the privacy of individuals that participated in the qualitative interview study. The data will be shared on reasonable request to the corresponding author.

None declared.

We gratefully acknowledge the contribution of the first author’s former students to the interview corpus analyzed in this article: Lea Pfefferle, Theresa Leitner, Lone Posthumus, Marie Blankenburg, Michael Burner, Alina Brucklachner, Annemarie Eschbaumer, Theresa Haberl, Ekaterina Kastner, Elena Knölker, Nina Kremer, Alexander Kreutz, Susanne Heudecker, Miriam Mannhart, Antonia Markiewitz, Nathalie Proske, Sharon Schießler, Tosca Strassberger, Melanie Schuster, and Sebastian Schwarz.

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• Published: 06 August 2024

De-escalating aggression in acute inpatient mental health settings: a behaviour change theory-informed, secondary qualitative analysis of staff and patient perspectives

• Owen Price 1 ,
• Christopher J. Armitage 2 , 3 , 4 ,
• Penny Bee 1 ,
• Helen Brooks 1 ,
• Karina Lovell 1 ,
• Debbie Butler 5 ,
• Lindsey Cree 1 ,
• Paul Fishwick 1 ,
• Andrew Grundy 1 ,
• Isobel Johnston 1 ,
• Peter Mcpherson 6 ,
• Holly Riches 7 ,
• Anne Scott 1 ,
• Lauren Walker 8 &
• Cat Papastavrou Brooks 9  

BMC Psychiatry volume  24 , Article number:  548 ( 2024 ) Cite this article

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Metrics details

De-escalation is often advocated to reduce harm associated with violence and use of restrictive interventions, but there is insufficient understanding of factors that influence de-escalation behaviour in practice. For the first time, using behaviour change and implementation science methodology, this paper aims to identify the drivers that will enhance de-escalation in acute inpatient and psychiatric intensive care mental health settings.

Secondary analysis of 46 qualitative interviews with ward staff ( n  = 20) and patients ( n  = 26) informed by the Theoretical Domains Framework.

Capabilities for de-escalation included knowledge (impact of trauma on memory and self-regulation and the aetiology and experience of voice hearing) and skills (emotional self-regulation, distress validation, reducing social distance, confirming autonomy, setting limits and problem-solving). Opportunities for de-escalation were limited by dysfunctional risk management cultures/ relationships between ward staff and clinical leadership, and a lack of patient involvement in safety maintenance. Motivation to engage in de-escalation was limited by negative emotion associated with moral formulations of patients and internal attributions for behaviour.

In addition to training that enhances knowledge and skills, interventions to enhance de-escalation should target ward and organisational cultures, as well as making fundamental changes to the social and physical structure of inpatient mental health wards. Psychological interventions targeting negative emotion in staff are needed to increase motivation. This paper provides a new evidence-based framework of indicative changes that will enhance de-escalation in adult acute mental health inpatient and PICU settings.

Peer Review reports

Introduction

Violence in acute inpatient mental health settings is a pervasive problem that is experienced by both staff and patients [ 1 ]. It can result in physical and psychological trauma [ 2 ], interference with treatment and recovery [ 3 ], and avoidable health service costs associated with staff sickness, high turnover, and litigation payments [ 4 ]. Whilst patients in these environments are reliant either on staff or their own interpersonal or physical attributes for protection [ 1 ], staff have a range of formal interventions available to incapacitate violence, including manual restraint (preventing movement through physical contact), coerced intramuscular psychotropic medicines, and seclusion (isolation in a locked room) [ 5 ]. Collectively, these interventions are referred to as “restrictive interventions”.

Restrictive interventions are prima facie intended to maintain safety, yet restraint is the most common cause of staff injuries [ 2 ] and event sequencing studies show that the imposition of restrictive interventions can be a cause, rather than a resolution, of violence [ 6 ]. Notwithstanding the complex and competing arguments about their legitimacy, interventions such as physical restraint and forced medicines are, in and of themselves, explicitly violent acts [ 7 ]. Restraint is psychologically traumatising and retraumatising for patients [ 8 ], can result in patient deaths [ 9 ] and significant, potentially unnecessary, health service expenditure [ 10 ] with attendant implications for patient safety [ 11 ]. Whilst ostensibly intended as a last resort to avert violence, there is evidence that restraint is used in inappropriate contexts, for example, as punishment [ 8 ], to provide respite for staff [ 12 ], as revenge [ 13 ] or to satisfy sadistic impulse [ 14 ]. Moreover, despite substantial government investment in programmes to reduce restraint [ 15 ], scandals involving its abuse persist [ 16 ]. Recent and compelling evidence indicates that, despite new legislation mandating reporting [ 17 ], restraint is systematically underreported by some English mental health providers [ 18 ], raising the prospect that the extent of restraint remains concealed and underestimated.

‘De-escalation,’ a term which refers to a complex range of psychosocial techniques designed to reduce aggression at its escalation phase, is recommended in clinical guidelines nationally [ 5 ] and internationally [ 19 ]. There is scant evidence that the shift in policy focus to non-physical management of aggression has translated into changes in routine practice. Indeed, patients report either that there is a proportion of staff who opt for restraint too soon [ 20 ] or, more generally, that restrictive interventions, rather than de-escalation, are used in response to escalating aggression [ 13 ]. Survey data indicates that staff often identify restrictive interventions as a form of de-escalation [ 21 ]. The apparent inability of staff respondents to differentiate between psychosocial and physical management of escalations may corroborate patient reports that restrictive interventions are used as a first-line response.

The Capabilities, Opportunities and Motivations model of Behaviour change [ 22 ], proposes that people’s behaviour is driven by their capabilities, opportunities, and motivations to engage in a given behaviour (e.g., de-escalation). Application of behaviour change theory is especially vital where, such as in the case of de-escalation, there is evidence of sustained dysfunction in the implementation of a healthcare intervention [ 23 ]. Empirical evidence provides some evidence of the kinds of capabilities, opportunities and motivations that are required to engage in de-escalation. For example, qualitative interview studies with staff indicate that capabilities include techniques such as ‘delimiting’ (manipulating the environment to induce calm and prevent multiple, simultaneous escalations) [ 24 ], problem-solving, reframing and negotiation [ 25 , 26 ]. Whereas staff tend to advocate specific skills and techniques, data from patient interviews places more emphasis on values and knowledge-based components. For example, patients emphasise: rule bending, reduced social distance, authenticity, proactive attention to patient emotions, psychological understanding, and moral commitments that are resilient to abusive nursing and organisational cultures [ 13 ]. Areas of agreement between staff and patient accounts include the ability to personalise de-escalation [ 13 , 25 , 27 ] and the importance of emotional self-regulation [ 13 , 25 ].

The differences in values in respect of de-escalation between staff and patients may point to the problem of otherness [ 28 ] that characterise staff-patient relationships within psychiatric models of care. Any clinician-patient dynamic (notwithstanding the dimensions of difference i.e. age, race, nationality, sexuality, gender, social class that can give rise to othering in any relationship), typically involves a differential in health status (the presence of a pathology), expertise (clinical training) and authority (designated powers of diagnosis and prescription). These relational preconditions can undermine authentic interactions and create distance in relationships between professionals and patients in any healthcare context [ 29 ]. They are perhaps especially alienating in psychiatry, where: patients do not always voluntarily present with symptomatic complaints [ 30 ]; arguably, clinicians provide only subjective evidence of pathology [ 31 ]; patients often fundamentally disagree with the knowledge claims and ethical basis underpinning the training and designated powers of clinicians [ 32 ].

A model of “expert”-delivered, standardised clinical skills and techniques to treat a defined pathology is reflected both in traditional conceptualisations of de-escalation [ 33 ] as well as in what staff value in respect of de-escalation in qualitative interviews [ 24 , 25 , 26 ]. Argument that this formula may be misapplied in the case of de-escalation includes the observation that aggression is not a pathological behaviour in all contexts (e.g. self-defence) [ 34 ]. Indeed, evidence suggests that aggression in these settings is often preceded by staff behaviour i.e. either by aversive communication or through the imposition of unwanted interventions e.g. forced medicines [ 35 ]. The conceptualisation of de-escalation as involving a set of discrete and standardisable techniques conflicts with the importance of personalisation [ 13 , 25 , 27 ] and, moreover, potentially encourages a view of patients as objects to be ‘done to,’ resulting in the perceptions of inauthenticity and dehumanisation that patients report in qualitative interview studies [ 13 ]. This problem may also explain why traditional models of staff de-escalation “skills”-training have provided limited evidence of effectiveness [ 36 ].

Existing literature also provides indications of factors that inhibit and/ or create opportunities for de-escalation. Staff and patient perspectives are aligned in the view that paperwork diverts nursing staff from therapeutic contact rendering them unable to respond to early signs of distress with de-escalation [ 13 , 37 ] and that petty rules and draconian inflexibility can create alienation that is not amenable to de-escalation [ 13 , 25 ]. Patients and staff both support the view that physical environments conducive with de-escalation have a range of internal and external areas for de-escalation [ 13 , 25 ] and are equipped with sensory rooms and equipment [ 38 ]. Staff participants, alone, identify lockable doors used to partition sections of the ward and prevent spread, as helpful [ 25 , 39 ].

Previous evidence reveals a complex range of factors influencing motivation to use de-escalation. An important concern for staff is the possibility that tolerance of aggressive behaviour will result in a contagion effect among patients and multiple, simultaneous escalations which are impossible to manage safely [ 25 , 40 ]. This fear may result in premature use of coerced intramuscular medicines to prevent spread [ 25 , 37 , 40 ] and it is a fear that may be exacerbated by short staffing [ 37 ]. There is agreement across staff and patient perspectives that moral judgements related to perceived aggression function reduce motivation to use de-escalation and instead increase desire to respond punitively [ 13 , 25 , 41 ]. Patient perspectives, alone, imply darker, inverse influences on motivation to use de-escalation, such as sadistic tendencies (in a minority of staff) and an absence of organisational systems of accountability that might provide a restraining influence on these [ 13 ]. Although inferences can be made from previous evidence related to the capabilities, opportunities and motivations required to engage in de-escalation in adult acute inpatient and PICU settings, to the authors’ knowledge, there has been no previous theoretically informed and systematic analysis of the complete range of factors that may influence implementation.

To identify, using the Theoretical Domains Framework, the relevant factors influencing successful de-escalation of aggression in adult acute inpatient mental health settings, from the perspective of clinical staff and patients.

Study design

Secondary qualitative data analysis [ 42 ] of 46 semi structured interviews with ward staff ( n  = 20) and patients ( n  = 26). Secondary qualitative data analysis involves the use of previously collected datasets to generate new social or methodological understanding [ 43 ], typically using a different theoretical lens to the original analysis [ 44 ].

Theoretical framework

The Theoretical Domains Framework (TDF) [ 45 ], was selected over competing frameworks for exploring implementation problems [e.g. Normalisation Process Theory [ 46 ] and the Consolidated Framework for Implementation Research [ 47 ]] because it (a) provides a comprehensive model of behaviour change, (b) was specifically developed to identify determinants of professional behaviour change and (c) because it enables direct mapping to behaviour change techniques that can inform intervention development. The TDF expands into 14 domains:

Capabilities: Knowledge; Skills; Memory, attention, and decision processes; behavioural regulation.

Opportunities: Environmental context and resources; Social influences.

Motivations: Social/professional role and identity; beliefs about capabilities; optimism; beliefs about consequences; reinforcement; intentions; goals; emotion.

It is probable, given the complexity of the TDF, that prior inductive investigations, such as the two descriptive qualitative research studies [ 13 , 25 ] that we originally published using the same dataset as the current study, may have missed factors that are relevant. The present study, informed by the TDF, re-analyses collected data from our original qualitative interview studies with ward staff and patients to identify factors that influence staff engagement in de-escalation. Such investigations are needed to inform the development of targeted behaviour change interventions to improve staff, patient, and service level outcomes.

Study setting and recruitment

Patient participants were recruited from seven wards in three UK National Health Service (NHS) Mental Health Trusts in Northwest England. Wards included six adult acute inpatient mental health wards (three female only, two mixed, one male only) and one Psychiatric Intensive Care Unit. Staff participants were recruited from five wards in three UK NHS Mental Health Trusts in Northwest England. Wards included three PICUs and two adult acute inpatient mental health wards (one male only, one female only).

Both ward staff and patients were recruited via nurses working in the relevant clinical settings, who distributed recruitment packs to all eligible staff and patients. Interested staff and patients returned ‘consent-to-contact’ forms to the recruiting nurses and, only then, were potential participants approached by researchers. Patient capacity to consent was assessed by the nurse-in-charge on duty at the agreed date and time of the interview.

Inclusion criteria

All patients were eligible to participate provided they were an English speaking, current inpatient who had direct experience of the phenomenon of interest (defined as having been involved in an incident requiring de-escalation within the past 12 months) and provided informed consent. Staff were eligible provided they were ward-based (defined as nursing assistants, staff nurses, team leaders and ward managers) and had rich experience of the phenomena of interest (defined as having worked within the acute or PICU environment for a minimum of six months).

The dataset comprised qualitative interviews with 26 patients and 20 ward staff. The patient interviews ranged between 3 min and 1 h and 50 min, and the ward staff interviews between 25 min and 1 h and 27 min. Both ward staff and patient participant groups were purposively sampled [ 48 ]. A sample of ward staff was sought with variation in qualified and unqualified nurses, genders, ages, and clinical experience. The patient sample was selected with consideration to ranges of ages, genders, ethnicities, diagnoses (self-reported), experience of restrictive interventions, use of illicit substances within the past 12 months, detention status, time spent as an inpatient in the past 12 months, and number of previous admissions. The complete sample characteristics of both participant groups have been published previously [ 13 , 25 ].

Data collection

Staff and patient interviews were guided by interview schedules with appropriately tailored language (via the engagement of a patient and public involvement advisory panel) for both groups. The interviews asked staff and patients to discuss their experiences with de-escalation and to identify barriers to use and effectiveness at the level of individuals (staff or patient characteristics), ward environments (physical and social) and healthcare organisations. Data collection continued until no new ideas, perspectives and concepts were emerging from the interviews. The interviews were conducted in 2014, were digitally recorded and transcribed verbatim.

Ethical considerations

Ethical approval for the re-analysis was sought and received a favourable opinion from Yorkshire and Humber NHS Research Ethics Committee (18-YH-0035).

Data analysis

Data were analysed using Framework Analysis [ 49 ], which allows for theoretical (deductive) and atheoretical (inductive) coding. Consistent with the theoretical approach to the study, our analysis was primarily deductive, with sections of data being coded to a priori theoretical domains. However, data coded to each theoretical domain was subsequently coded inductively to identify recurrent issues emerging within theoretical domains. The specific analytical processes were as follows. The 46 transcripts were detached from their original codes and uploaded to NVivo10 (a qualitative data analysis software package). A large matrix was then developed with 46 rows representing cases and columns representing the 14 domains of the TDF. An additional “other” column was created for any data coded as falling outside of the TDF. Summary links were then created between sections of data relevant to each theoretical domain (or other category) and the relevant cell of the matrix. The linked data summaries were then coded inductively to identify recurrent issues emerging within matrix columns. The final stage of the analysis to was to identify most prominent theoretical domains, customary in TDF-informed qualitative studies on the basis that it helps to inform the development of interventions that are targeted at the most important factors influencing behaviour [ 50 ]. This was achieved via team decision using criteria employed in previous qualitative studies informed by the TDF. Namely, that prominent domains are (a) frequently agreed by participants as being important and/or (b) discussed by participants in great depth [ 51 ].

Rigour and reflexivity

Measures to ensure the rigour of the analysis included multiple analysts involved in the coding of data [ 52 ] and the derivation of subthemes within a priori theoretical domains. To support the confirmability of interpretations, verbatim quotes are provided throughout the presentation of results [ 53 ]. Multiple perspectives, including academic, clinical and patient, on the data were incorporated in the analysis [ 54 ]. Analysts that coded data were the lead author (OP, a mental health nursing academic), two lived experience researchers (AG & LC) and two current nursing assistants working in in-patient mental health settings (IJ & HR). A summary of the developing analysis was shared, over a series of meetings, with a lived experienced group comprised of current service users, all with inpatient experience (DB, PF, AS, LW) who provided feedback on the interpretations and conceptualisations of the core analysis team. At the end of this process, the analysis was shared to elicit feedback from the wider research team which consisted of health service researchers with clinical backgrounds (KL) and methodologists including a qualitative researcher (PB), a behaviour change scientist (CA) and an implementation scientist (HB).

The psychological background of the research team and patient involvement in the analysis may have led to an unbalanced perspective on the data, where assumptions about the ethics of restrictive interventions and the desirability of more psychologically informed practice, overlooked the pragmatic reality of risk management at the coalface. We took steps to address this problem, firstly by the recruitment of two current nursing assistants (HR and IJ) to the analysis team and, secondly, through regular meetings held between analysts to interrogate assumptions and consider alternative interpretations in the coding of data.

De-escalation experiences were, typically, described as involving interactions between a lone patient and either a single staff member or groups of staff. Both ward staff and patients described intense focus on the physical behaviour and emotional expression of interlocutors during de-escalation encounters, and fluctuating changes in cognition, affect and arousal (labelled internal states ) resulting from perception (e.g., perceived intention, perceived attitude). Changes in internal states were responded to, by both staff and patients, with self-regulating actions (e.g., cognitive strategies such as self-talk) and actions to regulate the internal states of others by changing perceptions. For example, through explanation, through stimulation of positive memories and/or reminders of context (this could be patients reminding staff of the professional context of the encounter or vice-versa), or by manipulating the environment to create calmer conditions for dialogue. These actions, whether internally or externally directed, were labelled regulatory actions in the analysis.

Analysing staff and patient accounts adjacently, revealed de-escalation as a reciprocal, intersubjective ‘process’ rather than involving a unidirectional application of a discrete set of staff techniques. Indeed, there were numerous vivid descriptions provided of patients de-escalating dysregulated staff behaviour (Table  1 ). The phenomenon of “de-escalation,” therefore, according to our analysis, is reciprocal, involves fluctuating changes in internal states which are modified by internally and externally directed regulatory actions. The de-escalation process derived from our analysis is graphicalised in Fig.  1 and a table of evidence supporting each process component (reciprocity, perceptions, internal states, regulatory actions) is provided in Table  1 .

The following exploration of theoretical domains provides an in-depth examination of factors influencing ward staff and patient ability to regulate themselves and each other within the central phenomenon of the de-escalation process. The most prominent theoretical domains that emerged from the analysis in terms of de-escalation capabilities were Knowledge (related to trauma and auditory hallucinations) and Skills [a wide range of skills were identified by participants and used to develop a De-escalation Techniques Taxonomy (Table  2 )]. In terms of the creation of opportunities for de-escalation, both Environmental Context and Resources (participants identified extensive aspects the social and physical environment that restricted opportunity for de-escalation) and Social Influences (cultural attitudes to vulnerability in staff and relationships between ward staff and clinical leadership characterised by blame and distance) featured prominently in the data. The prominent theoretical domain relevant to increasing motivation to use de-escalation was Emotion (addressing negative emotion in staff associated with moral formulations of patients and internal attributions for behaviour). A detailed examination of each theoretical domain follows.

The De-escalation process

Capabilities

Accounts underscored knowledge of psychological trauma as a precondition for de-escalation engagement. This required staff awareness of how abuse and other dysfunctional family dynamics are re-enacted contemporaneously within relationships and conflictual encounters. A key element was knowledge of aggressive behavioural scripts [scripts are memory structures that are developed from repeated exposure to the same experience, activated with minimal or no conscious effort [ 55 ]]. For example, the following patient describes how aggression scripts could be activated and deactivated by differing staff approaches:

“At the other hospital, I was restrained… injected several times… when staff come running in, I stand back ready for a fight… because I’ve had it done to me as a child with my mother, my mum was a beater. This time around (the current admission) they sit me down and go; what’s the problem… go for a walk, go for a cig, just go to the shop. One of the staff… she’d make me go into the bedroom, she’d make me lay on the bed with my hands on my belly… that really calmed me down… and she stroked my hair, and she reminded me of my mum…That’s twice, three times we’ve done it now and I’ve not had PRN for I’d say about a month.” ( Patient, acute ward ).

Deactivation of aggressive behavioural scripts could be achieved by staff responses that were unexpected or surprising , enabling interactions to move outside of the anticipated dialogue and away from retaliation and antagonism. These responses typically involved humour, clownish playfulness or relaxing of rules or kindness when containment and/or consequences were expected.

The relevant knowledge factor identified by staff participants related to reducing distress in aggression they linked with auditory hallucinations, for example:

“I think hearing voices when somebody’s got voices that are obviously saying horrible things. And for them to then…switch off from them and focus on you, I think is really challenging for staff. We’ve got a lady and what she experiences, I don’t know, but she gets so aggressive when she’s distressed. Nothing you say will help calm her down. The more you talk, the more she wants to hit you.” ( Team leader, acute ward ).

Psychological skills

Given that de-escalation has traditionally been conceptualised as synonymous with skills and techniques [ 33 , 56 , 57 ], it was perhaps unsurprising that accounts, and especially staff accounts, provided rich data in relation to psychological skills. These data could be organised into six skill domains, divided into a single ‘internal regulation’ domain and five ‘external regulation’ domains. The internal regulation domain referred to the ability to remain calm (domain 1). External regulation domains related, firstly, to abilities involved in connecting with the patient such as confirming and validating distress (domain 2) and reducing social distance i.e., engaging with patients in authentic, human interactions on equal terms (domain 3). They, secondly, related to external actions designed to create the cognitive, emotional, and physical conditions needed for de-escalation. For example, through autonomy-confirming (e.g., providing time and space, offering choices) and limit-setting (e.g., instructions and deterrents) techniques, (domain 4) and through problem solving and reframing techniques (e.g., context reminders, stimulation of positive memories, modifying attributions) (domain 5). The pliability domain (domain 6) cut across connecting domains and referred to the extent of staff ability to mould their behaviours to individual patient preferences and the changing dynamics of aggressive incidents as they unfolded. For example, some staff referred to using variation of intimacy and informality depending on their knowledge of each patient. Female patients, often described valuing, in terms of de-escalation, staff who were able to combine empathy and understanding with a firmness and discipline that enabled the containment of difficult emotions, e.g.,

They can hold their selves, you don’t want to mess with them…but they’re beautiful women inside, they’re so loving and caring and they come into work and they’re dead joyful and as soon as they walk in, we all smile because we love them… they’ve got the thing of intimidation, not a scary way but a way of not going to mess with you… But they’ve got that loving side to them as well, not threatening, loving.” (Patient, acute ward) .

Identification of the six psychological skill domains enabled the generation of the De-escalation Technique Taxonomy, presented in Table  2 with supporting evidence.

Physical skills

The physical skills identified by participants, perhaps, counterintuitively, aimed to communicate vulnerability by communicating non-violent intent and rendering violent actions socially incongruent. For example, staff described deliberately taking a seat during verbal confrontations, even when this was unreciprocated by the patient, for this reason. Patients accounts referred to staff remaining seated when they were confronted by a patient with a grievance, from a standing position, and experienced this as belittling. This demonstrated how behaviours that are similar, at surface level, can provoke radically different emotional responses depending on intent. Sitting down during confrontations may communicate vulnerability by relinquishing an optimal stance for self-defence. Remaining seated at the onset of a confrontation may communicate a lack of concern that is experienced as deliberately provocative.

Other physical behaviours intended to communicate vulnerability included ensuring a minimal staff presence necessary to maintain safety and adopting an open body posture with arms kept by sides. A minority of staff participants reported that keeping their arms by their sides interfered with their ability to conceal visible tremor, perceived as necessary to avoiding emboldening patients who were perceived as seeking the ‘upper hand’ ( Team leader, acute ward ). Relatedly, there was broad agreement among staff that visible anxiety could either provoke unhelpful feelings of stigma during confrontations or undermine patients’ confidence in their ability to help. Patients did not always share this view, for example:

“I’m not bothered whether they come across as nervous, because I’ll respond to that, I’ll calm down to that because I’d see them as a vulnerable person. I’m not a bully so if they came across as nervous then I’d calm down a lot more.” ( Patient, acute ward ).

Opportunities

Social influences.

Accounts indicated that opportunities for de-escalation were often limited by risk management cultures at ward level. These cultures appeared underpinned by an understandable fear of adverse safety events like violence occurring. This fear was managed by a hyper-valuation of ‘ consistency ,’ which referred to the rigid application of rule systems and cultural norms without consideration to situational context (for example, variations in interpersonal boundaries and rules depending on the risk profile and/or the preferences of the patient concerned). Such cultures were exemplified by the meticulous maintenance of narrow interpersonal boundaries, efforts to control patient narratives about their experiences as inpatients, intolerance of dissent, and unconditional demands for respect of staff (without concomitant expectations that respect would be shown to patients). The sense of injustice provoked by the latter of these was exacerbated by the presence of what patients described as ‘propaganda materials’ (Patient, acute ward) displayed in the clinical environments e.g.,

“There are posters up everywhere saying ‘Care Assistants: Respect Us.” Well, I drew my own poster saying respect patients. They didn’t like it; I was told to put it away.” ( Patient, acute ward ).

There was little evidence that these practices served their intended aims. Accounts presented staff as entrenched in a maladaptive cycle of violence, where fear of violence was managed by the compulsive heaping on of more rules and tighter boundaries, provoking further violence, such as that described by the following patient:

“Some are “that’s the rule, that’s the way it is.” The girls were watching a film…Nurse X came in and switched it off at dead on midnight. The film finished at quarter past twelve. She went “that’s the rule, it goes off at twelve” …so she had three people ready to strangle her.” ( Patient, acute ward ).

There were indications that that these cultures were maintained through the stigmatisation of vulnerability and insularity . For example, vulnerable colleagues (e.g., new starters, newly qualified nurses, students, and temporary staff) were often regarded as a threat to established practices and in need of socialising to existing cultural norms. As discussed in the capabilities theme, many staff had internalised the notion that the physical expression of vulnerability (anxiety) was incompatible with competence. However, this was not uniformly the case. The following nurse’s description of her emotion regulation style, highlights both the importance of acceptance to her mastery of anxiety but, also, demonstrates how this form of self-talk could be undermined by cultures in which anxiety is viewed as synonymous with weakness:

“I put my hands together so that you can control your hands a bit more. I guess I maybe just say (self-talk), if you do shake it’s not a problem, if you do get scared, you can be scared, but I guess you just try and put your body a bit stiff so you can’t shake!” ( Staff nurse, PICU ).

The data indicate that attitudes to vulnerable staff, and to vulnerability within staff, may serve to socialise out of staff the very qualities that make them suited to de-escalation (e.g., being flexible, offering choice, expressing vulnerability).

The second culture-maintaining factor was insularity. Staff described distant relationships with management characterised by blame-based contact. This distance was exemplified by colloquialisms such as ‘ivory tower’ ( Nursing assistant, acute ward ) and patient references to management as ‘ the people upstairs ’ ( Patient, acute ward ). Management styles characterised by blame and distance could create a culture of back-covering and secrecy that restricted the flow of accurate information from wards concerning de-escalation events and opportunities for senior leadership to intervene where toxic cultures had emerged, e.g.,

‘There is a protective culture… being open is a challenge, and people will only learn where they’re being open. We need to be accountable but one of the concerns currently is there’s this culture of staff are to blame and it just always allows them (incidents) to go under the radar every time… don’t upset the apple cart… You get a lot of that going on – very protective…’ ( Team leader, PICU ).

Environmental context and resources

Staff and patient participants identified an extensive range of potentially modifiable factors associated with the social and physical environment that undermined patients’ capacity for self-regulation when de-escalation was required. These factors tended to confer on patients’ feelings of exclusion, dependence, inferiority, and humiliation and related to visual evidence of coercion within the environment (e.g., zero tolerance posters) and social processes such as handovers, ward rounds, admission processes, prescribing consultations, mealtimes, medication rounds and any experience involving extending waiting times. Patients also prioritised improved management of sensory input and conflict within the patient community.

Patients and staff had extensive suggestions for making the environment more compatible with de-escalation. They felt that carers should be involved in de-escalation planning as early in the admission as possible and that unqualified staff should be involved in ward rounds, to equip them with the knowledge they often needed to de-escalate typical patient concerns arising from inadequate medical communication (e.g., information on side effects). They felt that these structural problems ensured that those who knew most about the patient had least input into decision making relevant to de-escalation.

“ ‘I’ve been here two years; I’ve never sat in a ward round… because a lot of the time patients come out of ward rounds highly agitated… we’re trying to calm them down, but we don’t know what happens … they want to know about medication. They want to know about side effects… It’s always, I’ll get the nurse… but they’ve also got so much other stuff going on… there must be some stuff we can help with.” ( Nursing assistant, PICU ).

Other suggestions included improved input of service users into handovers, keeping the door to the nursing office open to patients (patients waiting outside and difficulty rousing staff from within was a constant source of escalation evident in the data), eliminating institutionalised practices around medication times (queuing and use of the ‘stable door’) and staff eating meals together to address undignified aspects such as being observed eating:

“On < deleted ward name >  they are during mealtimes; they’ll go out and they’ll sit. Members of staff don’t all congregate on one table, there’ll be one on every table having a chat and having lunch and talking. That breaks down the us and them barrier… Christ, they’re living on this ward, be part of it. Don’t separate yourself…I don’t see it’s us and them, I see a person, not a patient.” ( Nursing assistant, PICU ).

Patients and staff agreed that environmental noise, especially the sound of others’ distress, could contribute to a contagion effect of escalations. However, patients felt that staff typically addressed this through the joyless suppression of all noise, without reference to meaning and context. Instead, they felt that environments should be equipped with calming spaces with sensory equipment that would provide sanctuary from others. Patients felt that ward rules mandating patient assembly (e.g., bedroom lock-offs) and the rendering of internal and/or external ward areas ‘out-of-bounds’ restricted opportunities to de-escalate conflict within the patient community.

Considering the data in terms of motivation, almost by definition, required reflection on who staff want to de-escalate and whom they consider worthy of de-escalation. This was evident in the language employed by staff both in the staff interviews and in patient interviews describing staff behaviour. These data indicated that staff commonly use the term ‘behavioural’ to signal to each other and to patients, whether an observed behaviour could be detached from mental illness and whether it was, thereby, worthy of compassion and attention in response, e.g.:

“I think the staff was making fun of her. I don’t think it was her perspective. The member of staff said to her, there’s nothing much wrong with you. We’ll get you discharged… It seems to me you’ve got plenty of behavioural issues. And she went, I’ve had a diagnosis, what are you talking about? And she went, yes, yes, I know what kind of diagnosis you’ve had…which just…who are you talking to? Who do you think you are? By ‘behavioural’, they mean that if you scream and shout about something you haven’t got a mental illness, you just can’t control your behaviour.” ( Patient, acute ward ).

There was, albeit, rarely, some reflection on the degree of accuracy these assessments could have given the complexity of psychopathologies and trauma histories characterising inpatient populations, e.g.:

“Certain staff members will think they’re just messing about. One of the phrases I always think oh, they don’t know what they’re talking about, is oh it’s all behavioural. It means nothing, that… What people mean when they say it’s all behavioural is they know what they’re doing, they’ve got capacity, they’re doing it on purpose because they’re a bad person. They may have learnt behaviours that get a response, but it’s not necessarily their fault. They might have had a horrendous upbringing, and that type of behaviour was the only way they could get attention.” ( Ward manager, acute ward ).

Moral judgements about volition and intent were, not exclusively, but more readily applied to patients designated with the label of ‘personality disorder.’ Staff expressed significant negative emotion when discussing de-escalation in this perceived group. Their accounts were characterised by internal attributions (i.e., dispositional, trait-based explanations for behaviour) and dichotomous thinking (i.e., they tended to discuss patients with ‘personality disorder’ as a definable collective with common shared behaviours and attitudes), the latter with some irony given that ‘splitting’ was a transgression they often attributed to people they identified with this group, e.g.:

“It’s just the manipulation that these people with personality disorders present with, there’s a lot of splitting of staff. Like, one of member of staff is great, and they’re saying another member of staff is treating me rubbish, whereas you treat me nice. And, they’re saying to another member of staff, he treats me rubbish, whereas you treat me nice.” ( Staff nurse, PICU ).

There was evidence that such dichotomous thinking could directly inform differential treatment in respect of potentially de-escalating practices, e.g.:

‘ It’s about knowing your diagnoses. Someone who’s got a diagnosis of personality disorder doesn’t warrant flexibility, because they’re going to take the piss basically… If you know someone’s got that (personality disorder), be mindful of it and don’t give too much ground. Whereas someone who’s say got schizophrenia, well, just the weird example, say they don’t like to be seen eating as part of their delusion system. Say, right, okay, I’ll come and sit with you while you eat something cold in your bedroom.’ ( Staff nurse, PICU ).

Patients, by contrast, often provided more nuanced, situation-based formulations of suboptimal staff behaviour related to de-escalation, e.g.:

“The NHS are cutting monies down for staff and they’re running around, because they don’t get a break, you knock on that room because we’ve got to get our milk out of that room, but when they’re trying to eat their poor little dinner in the poor little 15 minutes they’ve got and we’re mithering them for milk and mithering them for biscuits… So, I can understand anger from the staff point of view too.” ( Patient, acute ward ).

This study used behaviour change theory and implementation science methodology to identify factors that influence de-escalation behaviour in acute mental health inpatient and PICU settings. This analysis enabled the generation a framework of indicative behaviour changes required to enhance de-escalation in adult mental health acute inpatient and PICU settings. This framework (presented in Table  3 ) indicates that, to enhance de-escalation, behaviour changes are needed at every layer of inpatient organisational structures and across professional disciplines (i.e., nursing, clinical psychology, occupational therapy, and psychiatry). The following discussion will outline the novel contributions our paper makes to understanding how capabilities can be enhanced, opportunities created, and motivation increased, to foster the conditions in which de-escalation in acute inpatient mental health settings can occur more often and more successfully.

Enhancing capabilities

Our analysis offers the following new understanding of how de-escalation capabilities should be enhanced. Firstly, we developed, through synthesis of participant perspectives, a new way of conceptualising de-escalation, the ‘De-escalation Process’ which posits that de-escalation is a reciprocal, intersubjective process, involving non-linear changes in staff and patient internal states (cognition, affect, and arousal) that result from perception (perceived intent or attitude) and are modified by internally directed (e.g., cognitive strategies such as self-talk) and externally directed regulatory actions (e.g. explanation, context reminders). This way of understanding de-escalation is consistent with the most highly cited psychological models of aggression [e.g [ 55 ]]. and challenges prior framings of de-escalation as involving the unidirectional application of a formal set of staff techniques [e.g [ 33 , 56 , 57 ]]. The key implication of this conceptualisation is that it may undermine models of training focused on skills-based training delivered to staff alone. Novel interventions seeking to enhance de-escalation should refocus content to addressing sources of interpersonal and environmental stress that undermine staff and patient capacity for self-regulation and/or consider intervention models that train patients as well as staff in de-escalation. In respect of the latter option, training content could be based around the De-escalation Techniques Taxonomy we developed from staff and patient perspectives on helpful de-escalation behaviours.

Creating opportunities

The sources of interpersonal and environmental stress perceived as reducing the regulation capacity of staff and patients during de-escalation were wide ranging. These included: coercive messaging in ward signage; conduct of ward rounds and shift handovers; adverse experience of the admission process; insufficient collaboration in antipsychotic prescribing; ward rules, and features of the physical environment including segregated staff and patient spaces and the lack of sensory modulation rooms. There were also important staff team and organisational cultural barriers identified involving negative attitudes to vulnerability in staff (perceived as undermining emotion regulation capacity) and stigmatisation of therapeutic intimacy in staff-patient relationships (undermining the authentic connections perceived as important to de-escalation). Relationships between ward staff and senior clinical leaders characterised by blame and distance impeded transparent analyses of conflict events through which learning about de-escalation could occur.

Existing interventions to reduce restrictive interventions including the Six Core Strategies [ 58 ] and Safewards [ 59 ] both target environment and culture. Both models have demonstrated robust evidence of effectiveness [ 60 , 61 ]. However, neither model explicitly targets ward round conduct, attitudes to vulnerability in staff or collaborative antipsychotic prescribing. Our analysis indicates these are likely to be important targets for interventions to enhance de-escalation.

Increasing motivation

The influence of negative emotion in staff on motivation to use de-escalation, raises important questions about the nature and extent of psychological support for ward staff in the challenging work that they are required to do. Indeed, accounts showed that staff teams exhibited many patterns of cognition, affect and behaviour that are typical of people who have experienced complex trauma. For example, repetition-compulsion [ 62 ] in the bolstering of draconian rule systems despite apparently clear evidence of their harmful effects. An approximation of contempt for vulnerability was observed in attitudes toward potentially vulnerable staff (e.g., non-regular staff, students, new starters, newly qualified staff), a trait that can be found in people who have been raised in environments where predation is the norm [ 63 ].

Importantly, in staff discussion of people designated with the label of ‘personality disorder,’ there was clear evidence of staff engaging in the psychological defence mechanism splitting , which involves the failure to incorporate both positive and negative aspects in appraisals of people and situations [ 64 ]. Moreover, staff tended to discuss patients designated with this label as belonging to a collective with shared attributes, indicating that they had developed a rigid internal representation of who a ‘personality disordered’ patient is. Wider literature related to the inpatient experience of people designated with these labels, presents a perception that staff view everything they say and do through the lens of the ‘personality disorder’ label [ 65 ], suggesting that staff may interact with the internal representation of people within this perceived group, rather than the external reality of the individual. It is possible that these phenomena serve a psychologically protective function for staff. For example, splitting of patients in to ‘all bad’ groups, may avoid the need to confront therapeutic inefficacy. Interacting with internal representations, rather than individuals, may enable staff to distance themselves from patients’ suffering and bring a sense of order and predictability to distressing experiences such as witnessing self-harm. Human beings are, however, complex, and do not fit comfortably into taxonomic classification systems. Being treated as a label rather than a person is likely to provoke feelings of oppression and injustice that are incommensurate with de-escalation. These self-protective mechanisms require skilful psychological interventions that do not provoke counterproductive moral injury.

There was a broader problem with staff formulations of aggressive behaviour, characterised by moral judgements and internal attributions, that seemed to undermine their tendency to adopt de-escalating approaches. This problem seemed rooted in an overestimation of the accuracy of clinical judgements of volition and intent. It is established in experimental psychology that humans have limited ability to accurately predict the intentions and motives of others through observation alone [ 66 ] and this problem may be reflected in empirical evidence reflecting the unreliability of clinical judgement [ 67 ] and clinicians’ poor interpersonal accuracy (the ability to interpret another person’s psychological states, traits, and behavioural cues) [ 68 ].

Interventions are needed which deconstruct moral judgements and promote situational formulations of behaviour. Moral judgements arise from the negative emotion that is provoked by needs-meeting behaviours, rather than the needs that drive behaviour [ 69 ]. For example, a moral judgement can be formulated about self-harm but not the need for relief from unbearable distress. Human needs are present or absent and are without moral dimension. Identifying unmet needs through signalling emotions, followed by a structured review of feelings and needs sequences with reference to relevant contextual factors (e.g., their historical, institutional, and wider social context) is likely to be useful in deconstructing these counter-de-escalating formulations. It is important also to acknowledge that patients presented more nuanced, situation-based explanations for unhelpful staff behaviour during de-escalation. This indicates that trauma alone cannot explain staff attitudes because patients, too, are exposed to trauma in inpatient settings [ 1 ], often overlaying [ 70 ] as well as invoking [ 71 ] developmental traumas. Attitudes, therefore, are likely explained by a combination of, and interaction between, a traumatic and unpredictable working environment, on one hand, and a psychiatric paradigm that encourages crude categorisations of expressions of distress and either/or thinking, on the other.

Limitations

There are important limitations of our work for consideration. The dataset for the secondary analysis is almost a decade old. There have been substantial policy programmes in the area of reducing restrictive interventions in the UK [ 15 ], as well as new evidence-based interventions for reduction [ 60 ], since the data were collected. It could be argued that our analysis is undermined because (a) it lacks relevance to contemporary practice and (b) because the data were interpreted by researchers who viewed the data with reference to theoretical and evidential updates that have occurred since the time of data collection. In terms of the former critique, there are reasons to believe that our analysis has retained relevance to contemporary practice. Firstly, we have published two recent papers using contemporary datasets [ 72 , 73 ], albeit in forensic mental health inpatient settings, that support these findings. Secondly, the problems depicted in recent abuse scandals [ 14 ], share many of the attitudinal and cultural signifiers as those illuminated by our analysis. The latter critique alludes to the concept of ‘presentism’ in which past events are interpreted and potentially distorted by contemporary values and understandings [ 74 ]. It is difficult to determine with any precision the extent that this phenomenon influenced interpretations but would certainly have had some. Considering evidence that contemporary practice may not have evolved consistently with relatively recent care philosophies such as ‘least restrictive practice’ [ 75 ] and ‘trauma-informed care’ [ 76 ], analyses informed by recent knowledge and understanding are likely to have value whether applied to recently collected or somewhat older datasets such as our own.

An additional limitation of our work relates to the identification of most prominent theoretical domains. Whilst identifying most prominent domains is considered desirable in TDF-informed analyses (because it is likely to reveal the most important influences on behaviour within capability-opportunity-motivation configurations) [ 50 ], it is possible that important factors within minor domains were excluded from the final analysis.

Conclusions

Interventions to enhance de-escalation in adult acute inpatient settings should enhance capabilities, create opportunities, and increase motivation. Capabilities should be enhanced by increasing knowledge of traumatic experiences and their implications for memory and self-regulation, and the aetiology and experience of voice hearing and strategies for reducing distress. Interventions should enhance skills in emotional self-regulation, validating distress, reducing social distance, confirming autonomy, setting limits, and problem solving and re-framing. Opportunities for de-escalation can be created by modifying risk management cultures (particularly in terms of limit-setting, cultural conceptualisations of appropriate professional boundaries and cultural attitudes to vulnerability in staff) and improving working relationships between clinical leadership and ward staff. Interventions targeting the environment should increase service user involvement in shift handovers and prescribing, reduce social isolation and use-of-force on admission and audit the environment to address a range of common flashpoints that undermine de-escalation efforts. Motivation to engage in de-escalation may be increased by psychological interventions that undermine moral judgements about, and internal attributions for, aggressive behaviour.

Data availability

The datasets analysed during the current study are not publicly available due to the fact they contain personal data, for example, job roles, place of work, colleague names, family names and circumstances, which could identify the participant, but are available from the corresponding author on reasonable request.

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Acknowledgements

The authors wish to thank all participants for giving their time.

This study is funded by the National Institute for Health Research (Health Technology Assessment Programme; Ref: 16/101/02). The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. The funder had no input into: the design of the study; the collection, analysis, and interpretation of data or the writing of the manuscript.

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Division of Nursing, Midwifery and Social Work, School of Health Sciences, University of Manchester, Oxford Road, Manchester, M13 9PL, England

Owen Price, Penny Bee, Helen Brooks, Karina Lovell, Lindsey Cree, Paul Fishwick, Andrew Grundy, Isobel Johnston & Anne Scott

Manchester Centre for Health Psychology, School of Health Sciences, University of Manchester, Oxford Road, Manchester, M13 9PL, England

Christopher J. Armitage

Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, Nelson Street, Manchester, M13 9NQ, England

NIHR Greater Manchester Patient Safety Translational Research Centre, School of Health Sciences, University of Manchester, Oxford Road, Manchester, M13 9PL, England

Institute of Mental Health, University of Nottingham, Triumph Road, Nottingham, NG7 2TU, England

Debbie Butler

Division of Psychiatry, University College London, Tottenham Court Road, London, W1T 7NF, England

Peter Mcpherson

Merseycare NHS Foundation Trust, Kings Business Park, Prescot, L34 1PJ, England

Holly Riches

School of Health and Psychological Sciences, City, University of London, Northampton Square, London, EC1V 0HB, England

Lauren Walker

Population Health Sciences, Bristol Medical School, University of Bristol, 39 Whatley Road, Bristol, BS8 2PS, England

Cat Papastavrou Brooks

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Contributions

OP, CJA, PB, HB & KL contributed to conception and design. The data were acquired by OP. Analysis and interpretation was conducted by OP, CPB, DB, LC, PF, AG, IJ, PM, AS, LW & HR. All authors were involved in drafting the manuscript or revising it critically. All authors gave final approval of the version to be published.

Corresponding author

Correspondence to Owen Price .

Ethics declarations

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Ethical approval for the study was sought and received a favourable opinion from Yorkshire and Humber NHS Research Ethics Committee (18-YH-0035). Every participant provided informed consent to participate in the original study. When gaining informed consent to participate, participants consented to analysis and reanalysis of their data.

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Models and frameworks for assessing the implementation of clinical practice guidelines: a systematic review

• Nicole Freitas de Mello   ORCID: orcid.org/0000-0002-5228-6691 1 , 2 ,
• Sarah Nascimento Silva   ORCID: orcid.org/0000-0002-1087-9819 3 ,
• Dalila Fernandes Gomes   ORCID: orcid.org/0000-0002-2864-0806 1 , 2 ,
• Juliana da Motta Girardi   ORCID: orcid.org/0000-0002-7547-7722 4 &
• Jorge Otávio Maia Barreto   ORCID: orcid.org/0000-0002-7648-0472 2 , 4  

Implementation Science volume  19 , Article number:  59 ( 2024 ) Cite this article

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The implementation of clinical practice guidelines (CPGs) is a cyclical process in which the evaluation stage can facilitate continuous improvement. Implementation science has utilized theoretical approaches, such as models and frameworks, to understand and address this process. This article aims to provide a comprehensive overview of the models and frameworks used to assess the implementation of CPGs.

A systematic review was conducted following the Cochrane methodology, with adaptations to the "selection process" due to the unique nature of this review. The findings were reported following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) reporting guidelines. Electronic databases were searched from their inception until May 15, 2023. A predetermined strategy and manual searches were conducted to identify relevant documents from health institutions worldwide. Eligible studies presented models and frameworks for assessing the implementation of CPGs. Information on the characteristics of the documents, the context in which the models were used (specific objectives, level of use, type of health service, target group), and the characteristics of each model or framework (name, domain evaluated, and model limitations) were extracted. The domains of the models were analyzed according to the key constructs: strategies, context, outcomes, fidelity, adaptation, sustainability, process, and intervention. A subgroup analysis was performed grouping models and frameworks according to their levels of use (clinical, organizational, and policy) and type of health service (community, ambulatorial, hospital, institutional). The JBI’s critical appraisal tools were utilized by two independent researchers to assess the trustworthiness, relevance, and results of the included studies.

Database searches yielded 14,395 studies, of which 80 full texts were reviewed. Eight studies were included in the data analysis and four methodological guidelines were additionally included from the manual search. The risk of bias in the studies was considered non-critical for the results of this systematic review. A total of ten models/frameworks for assessing the implementation of CPGs were found. The level of use was mainly policy, the most common type of health service was institutional, and the major target group was professionals directly involved in clinical practice. The evaluated domains differed between the models and there were also differences in their conceptualization. All the models addressed the domain "Context", especially at the micro level (8/12), followed by the multilevel (7/12). The domains "Outcome" (9/12), "Intervention" (8/12), "Strategies" (7/12), and "Process" (5/12) were frequently addressed, while "Sustainability" was found only in one study, and "Fidelity/Adaptation" was not observed.

Conclusions

The use of models and frameworks for assessing the implementation of CPGs is still incipient. This systematic review may help stakeholders choose or adapt the most appropriate model or framework to assess CPGs implementation based on their specific health context.

Trial registration

PROSPERO (International Prospective Register of Systematic Reviews) registration number: CRD42022335884. Registered on June 7, 2022.

Peer Review reports

Contributions to the literature

Although the number of theoretical approaches has grown in recent years, there are still important gaps to be explored in the use of models and frameworks to assess the implementation of clinical practice guidelines (CPGs). This systematic review aims to contribute knowledge to overcome these gaps.

Despite the great advances in implementation science, evaluating the implementation of CPGs remains a challenge, and models and frameworks could support improvements in this field.

This study demonstrates that the available models and frameworks do not cover all characteristics and domains necessary for a complete evaluation of CPGs implementation.

The presented findings contribute to the field of implementation science, encouraging debate on choices and adaptations of models and frameworks for implementation research and evaluation.

Substantial investments have been made in clinical research and development in recent decades, increasing the medical knowledge base and the availability of health technologies [ 1 ]. The use of clinical practice guidelines (CPGs) has increased worldwide to guide best health practices and to maximize healthcare investments. A CPG can be defined as "any formal statements systematically developed to assist practitioner and patient decisions about appropriate health care for specific clinical circumstances" [ 2 ] and has the potential to improve patient care by promoting interventions of proven benefit and discouraging ineffective interventions. Furthermore, they can promote efficiency in resource allocation and provide support for managers and health professionals in decision-making [ 3 , 4 ].

However, having a quality CPG does not guarantee that the expected health benefits will be obtained. In fact, putting these devices to use still presents a challenge for most health services across distinct levels of government. In addition to the development of guidelines with high methodological rigor, those recommendations need to be available to their users; these recommendations involve the diffusion and dissemination stages, and they need to be used in clinical practice (implemented), which usually requires behavioral changes and appropriate resources and infrastructure. All these stages involve an iterative and complex process called implementation, which is defined as the process of putting new practices within a setting into use [ 5 , 6 ].

Implementation is a cyclical process, and the evaluation is one of its key stages, which allows continuous improvement of CPGs development and implementation strategies. It consists of verifying whether clinical practice is being performed as recommended (process evaluation or formative evaluation) and whether the expected results and impact are being reached (summative evaluation) [ 7 , 8 , 9 ]. Although the importance of the implementation evaluation stage has been recognized, research on how these guidelines are implemented is scarce [ 10 ]. This paper focused on the process of assessing CPGs implementation.

To understand and improve this complex process, implementation science provides a systematic set of principles and methods to integrate research findings and other evidence-based practices into routine practice and improve the quality and effectiveness of health services and care [ 11 ]. The field of implementation science uses theoretical approaches that have varying degrees of specificity based on the current state of knowledge and are structured based on theories, models, and frameworks [ 5 , 12 , 13 ]. A "Model" is defined as "a simplified depiction of a more complex world with relatively precise assumptions about cause and effect", and a "framework" is defined as "a broad set of constructs that organize concepts and data descriptively without specifying causal relationships" [ 9 ]. Although these concepts are distinct, in this paper, their use will be interchangeable, as they are typically like checklists of factors relevant to various aspects of implementation.

There are a variety of theoretical approaches available in implementation science [ 5 , 14 ], which can make choosing the most appropriate challenging [ 5 ]. Some models and frameworks have been categorized as "evaluation models" by providing a structure for evaluating implementation endeavors [ 15 ], even though theoretical approaches from other categories can also be applied for evaluation purposes because they specify concepts and constructs that may be operationalized and measured [ 13 ]. Two frameworks that can specify implementation aspects that should be evaluated as part of intervention studies are RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) [ 16 ] and PRECEDE-PROCEED (Predisposing, Reinforcing and Enabling Constructs in Educational Diagnosis and Evaluation-Policy, Regulatory, and Organizational Constructs in Educational and Environmental Development) [ 17 ]. Although the number of theoretical approaches has grown in recent years, the use of models and frameworks to evaluate the implementation of guidelines still seems to be a challenge.

This article aims to provide a complete map of the models and frameworks applied to assess the implementation of CPGs. The aim is also to subside debate and choices on models and frameworks for the research and evaluation of the implementation processes of CPGs and thus to facilitate the continued development of the field of implementation as well as to contribute to healthcare policy and practice.

A systematic review was conducted following the Cochrane methodology [ 18 ], with adaptations to the "selection process" due to the unique nature of this review (details can be found in the respective section). The review protocol was registered in PROSPERO (registration number: CRD42022335884) on June 7, 2022. This report adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [ 19 ] and a completed checklist is provided in Additional File 1.

Eligibility criteria

The SDMO approach (Types of Studies, Types of Data, Types of Methods, Outcomes) [ 20 ] was utilized in this systematic review, outlined as follows:

Types of studies

All types of studies were considered for inclusion, as the assessment of CPG implementation can benefit from a diverse range of study designs, including randomized clinical trials/experimental studies, scale/tool development, systematic reviews, opinion pieces, qualitative studies, peer-reviewed articles, books, reports, and unpublished theses.

Studies were categorized based on their methodological designs, which guided the synthesis, risk of bias assessment, and presentation of results.

Study protocols and conference abstracts were excluded due to insufficient information for this review.

Types of data

Studies that evaluated the implementation of CPGs either independently or as part of a multifaceted intervention.

Guidelines for evaluating CPG implementation.

Inclusion of CPGs related to any context, clinical area, intervention, and patient characteristics.

No restrictions were placed on publication date or language.

Exclusion criteria

General guidelines were excluded, as this review focused on 'models for evaluating clinical practice guidelines implementation' rather than the guidelines themselves.

Studies that focused solely on implementation determinants as barriers and enablers were excluded, as this review aimed to explore comprehensive models/frameworks.

Studies evaluating programs and policies were excluded.

Studies that only assessed implementation strategies (isolated actions) rather than the implementation process itself were excluded.

Studies that focused solely on the impact or results of implementation (summative evaluation) were excluded.

Types of methods

Not applicable.

All potential models or frameworks for assessing the implementation of CPG (evaluation models/frameworks), as well as their characteristics: name; specific objectives; levels of use (clinical, organizational, and policy); health system (public, private, or both); type of health service (community, ambulatorial, hospital, institutional, homecare); domains or outcomes evaluated; type of recommendation evaluated; context; limitations of the model.

Model was defined as "a deliberated simplification of a phenomenon on a specific aspect" [ 21 ].

Framework was defined as "structure, overview outline, system, or plan consisting of various descriptive categories" [ 21 ].

Models or frameworks used solely for the CPG development, dissemination, or implementation phase.

Models/frameworks used solely for assessment processes other than implementation, such as for the development or dissemination phase.

Data sources and literature search

The systematic search was conducted on July 31, 2022 (and updated on May 15, 2023) in the following electronic databases: MEDLINE/PubMed, Centre for Reviews and Dissemination (CRD), the Cochrane Library, Cumulative Index to Nursing and Allied Health Literature (CINAHL), EMBASE, Epistemonikos, Global Health, Health Systems Evidence, PDQ-Evidence, PsycINFO, Rx for Change (Canadian Agency for Drugs and Technologies in Health, CADTH), Scopus, Web of Science and Virtual Health Library (VHL). The Google Scholar database was used for the manual selection of studies (first 10 pages).

Additionally, hand searches were performed on the lists of references included in the systematic reviews and citations of the included studies, as well as on the websites of institutions working on CPGs development and implementation: Guidelines International Networks (GIN), National Institute for Health and Care Excellence (NICE; United Kingdom), World Health Organization (WHO), Centers for Disease Control and Prevention (CDC; USA), Institute of Medicine (IOM; USA), Australian Department of Health and Aged Care (ADH), Healthcare Improvement Scotland (SIGN), National Health and Medical Research Council (NHMRC; Australia), Queensland Health, The Joanna Briggs Institute (JBI), Ministry of Health and Social Policy of Spain, Ministry of Health of Brazil and Capes Theses and Dissertations Catalog.

The search strategy combined terms related to "clinical practice guidelines" (practice guidelines, practice guidelines as topic, clinical protocols), "implementation", "assessment" (assessment, evaluation), and "models, framework". The free term "monitoring" was not used because it was regularly related to clinical monitoring and not to implementation monitoring. The search strategies adapted for the electronic databases are presented in an additional file (see Additional file 2).

Study selection process

The results of the literature search from scientific databases, excluding the CRD database, were imported into Mendeley Reference Management software to remove duplicates. They were then transferred to the Rayyan platform ( https://rayyan.qcri.org ) [ 22 ] for the screening process. Initially, studies related to the "assessment of implementation of the CPG" were selected. The titles were first screened independently by two pairs of reviewers (first selection: four reviewers, NM, JB, SS, and JG; update: a pair of reviewers, NM and DG). The title screening was broad, including all potentially relevant studies on CPG and the implementation process. Following that, the abstracts were independently screened by the same group of reviewers. The abstract screening was more focused, specifically selecting studies that addressed CPG and the evaluation of the implementation process. In the next step, full-text articles were reviewed independently by a pair of reviewers (NM, DG) to identify those that explicitly presented "models" or "frameworks" for assessing the implementation of the CPG. Disagreements regarding the eligibility of studies were resolved through discussion and consensus, and by a third reviewer (JB) when necessary. One reviewer (NM) conducted manual searches, and the inclusion of documents was discussed with the other reviewers.

Risk of bias assessment of studies

The selected studies were independently classified and evaluated according to their methodological designs by two investigators (NM and JG). This review employed JBI’s critical appraisal tools to assess the trustworthiness, relevance and results of the included studies [ 23 ] and these tools are presented in additional files (see Additional file 3 and Additional file 4). Disagreements were resolved by consensus or consultation with the other reviewers. Methodological guidelines and noncomparative and before–after studies were not evaluated because JBI does not have specific tools for assessing these types of documents. Although the studies were assessed for quality, they were not excluded on this basis.

Data extraction

The data was independently extracted by two reviewers (NM, DG) using a Microsoft Excel spreadsheet. Discrepancies were discussed and resolved by consensus. The following information was extracted:

Document characteristics : author; year of publication; title; study design; instrument of evaluation; country; guideline context;

Usage context of the models : specific objectives; level of use (clinical, organizational, and policy); type of health service (community, ambulatorial, hospital, institutional); target group (guideline developers, clinicians; health professionals; health-policy decision-makers; health-care organizations; service managers);

Model and framework characteristics : name, domain evaluated, and model limitations.

The set of information to be extracted, shown in the systematic review protocol, was adjusted to improve the organization of the analysis.

The "level of use" refers to the scope of the model used. "Clinical" was considered when the evaluation focused on individual practices, "organizational" when practices were within a health service institution, and "policy" when the evaluation was more systemic and covered different health services or institutions.

The "type of health service" indicated the category of health service where the model/framework was used (or can be used) to assess the implementation of the CPG, related to the complexity of healthcare. "Community" is related to primary health care; "ambulatorial" is related to secondary health care; "hospital" is related to tertiary health care; and "institutional" represented models/frameworks not specific to a particular type of health service.

The "target group" included stakeholders related to the use of the model/framework for evaluating the implementation of the CPG, such as clinicians, health professionals, guideline developers, health policy-makers, health organizations, and service managers.

The category "health system" (public, private, or both) mentioned in the systematic review protocol was not found in the literature obtained and was removed as an extraction variable. Similarly, the variables "type of recommendation evaluated" and "context" were grouped because the same information was included in the "guideline context" section of the study.

Some selected documents presented models or frameworks recognized by the scientific field, including some that were validated. However, some studies adapted the model to this context. Therefore, the domain analysis covered all models or frameworks domains evaluated by (or suggested for evaluation by) the document analyzed.

Data analysis and synthesis

The results were tabulated using narrative synthesis with an aggregative approach, without meta-analysis, aiming to summarize the documents descriptively for the organization, description, interpretation and explanation of the study findings [ 24 , 25 ].

The model/framework domains evaluated in each document were studied according to Nilsen et al.’s constructs: "strategies", "context", "outcomes", "fidelity", "adaptation" and "sustainability". For this study, "strategies" were described as structured and planned initiatives used to enhance the implementation of clinical practice [ 26 ].

The definition of "context" varies in the literature. Despite that, this review considered it as the set of circumstances or factors surrounding a particular implementation effort, such as organizational support, financial resources, social relations and support, leadership, and organizational culture [ 26 , 27 ]. The domain "context" was subdivided according to the level of health care into "micro" (individual perspective), "meso" (organizational perspective), "macro" (systemic perspective), and "multiple" (when there is an issue involving more than one level of health care).

The "outcomes" domain was related to the results of the implementation process (unlike clinical outcomes) and was stratified according to the following constructs: acceptability, appropriateness, feasibility, adoption, cost, and penetration. All these concepts align with the definitions of Proctor et al. (2011), although we decided to separate "fidelity" and "sustainability" as independent domains similar to Nilsen [ 26 , 28 ].

"Fidelity" and "adaptation" were considered the same domain, as they are complementary pieces of the same issue. In this study, implementation fidelity refers to how closely guidelines are followed as intended by their developers or designers. On the other hand, adaptation involves making changes to the content or delivery of a guideline to better fit the needs of a specific context. The "sustainability" domain was defined as evaluations about the continuation or permanence over time of the CPG implementation.

Additionally, the domain "process" was utilized to address issues related to the implementation process itself, rather than focusing solely on the outcomes of the implementation process, as done by Wang et al. [ 14 ]. Furthermore, the "intervention" domain was introduced to distinguish aspects related to the CPG characteristics that can impact its implementation, such as the complexity of the recommendation.

A subgroup analysis was performed with models and frameworks categorized based on their levels of use (clinical, organizational, and policy) and the type of health service (community, ambulatorial, hospital, institutional) associated with the CPG. The goal is to assist stakeholders (politicians, clinicians, researchers, or others) in selecting the most suitable model for evaluating CPG implementation based on their specific health context.

Search results

Database searches yielded 26,011 studies, of which 107 full texts were reviewed. During the full-text review, 99 articles were excluded: 41 studies did not mention a model or framework for assessing the implementation of the CPG, 31 studies evaluated only implementation strategies (isolated actions) rather than the implementation process itself, and 27 articles were not related to the implementation assessment. Therefore, eight studies were included in the data analysis. The updated search did not reveal additional relevant studies. The main reason for study exclusion was that they did not use models or frameworks to assess CPG implementation. Additionally, four methodological guidelines were included from the manual search (Fig.  1 ).

PRISMA diagram. Acronyms: ADH—Australian Department of Health, CINAHL—Cumulative Index to Nursing and Allied Health Literature, CDC—Centers for Disease Control and Prevention, CRD—Centre for Reviews and Dissemination, GIN—Guidelines International Networks, HSE—Health Systems Evidence, IOM—Institute of Medicine, JBI—The Joanna Briggs Institute, MHB—Ministry of Health of Brazil, NICE—National Institute for Health and Care Excellence, NHMRC—National Health and Medical Research Council, MSPS – Ministerio de Sanidad Y Política Social (Spain), SIGN—Scottish Intercollegiate Guidelines Network, VHL – Virtual Health Library, WHO—World Health Organization. Legend: Reason A –The study evaluated only implementation strategies (isolated actions) rather than the implementation process itself. Reason B – The study did not mention a model or framework for assessing the implementation of the intervention. Reason C – The study was not related to the implementation assessment. Adapted from Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021;372:n71. https://doi.org/10.1136/bmj.n71 . For more information, visit:

According to the JBI’s critical appraisal tools, the overall assessment of the studies indicates their acceptance for the systematic review.

The cross-sectional studies lacked clear information regarding "confounding factors" or "strategies to address confounding factors". This was understandable given the nature of the study, where such details are not typically included. However, the reviewers did not find this lack of information to be critical, allowing the studies to be included in the review. The results of this methodological quality assessment can be found in an additional file (see Additional file 5).

In the qualitative studies, there was some ambiguity regarding the questions: "Is there a statement locating the researcher culturally or theoretically?" and "Is the influence of the researcher on the research, and vice versa, addressed?". However, the reviewers decided to include the studies and deemed the methodological quality sufficient for the analysis in this article, based on the other information analyzed. The results of this methodological quality assessment can be found in an additional file (see Additional file 6).

Documents characteristics (Table  1 )

The documents were directed to several continents: Australia/Oceania (4/12) [ 31 , 33 , 36 , 37 ], North America (4/12 [ 30 , 32 , 38 , 39 ], Europe (2/12 [ 29 , 35 ] and Asia (2/12) [ 34 , 40 ]. The types of documents were classified as cross-sectional studies (4/12) [ 29 , 32 , 34 , 38 ], methodological guidelines (4/12) [ 33 , 35 , 36 , 37 ], mixed methods studies (3/12) [ 30 , 31 , 39 ] or noncomparative studies (1/12) [ 40 ]. In terms of the instrument of evaluation, most of the documents used a survey/questionnaire (6/12) [ 29 , 30 , 31 , 32 , 34 , 38 ], while three (3/12) used qualitative instruments (interviews, group discussions) [ 30 , 31 , 39 ], one used a checklist [ 37 ], one used an audit [ 33 ] and three (3/12) did not define a specific instrument to measure [ 35 , 36 , 40 ].

Considering the clinical areas covered, most studies evaluated the implementation of nonspecific (general) clinical areas [ 29 , 33 , 35 , 36 , 37 , 40 ]. However, some studies focused on specific clinical contexts, such as mental health [ 32 , 38 ], oncology [ 39 ], fall prevention [ 31 ], spinal cord injury [ 30 ], and sexually transmitted infections [ 34 ].

Usage context of the models (Table  1 )

Specific objectives.

All the studies highlighted the purpose of guiding the process of evaluating the implementation of CPGs, even if they evaluated CPGs from generic or different clinical areas.

Levels of use

The most common level of use of the models/frameworks identified to assess the implementation of CPGs was policy (6/12) [ 33 , 35 , 36 , 37 , 39 , 40 ]. In this level, the model is used in a systematic way to evaluate all the processes involved in CPGs implementation and is primarily related to methodological guidelines. This was followed by the organizational level of use (5/12) [ 30 , 31 , 32 , 38 , 39 ], where the model is used to evaluate the implementation of CPGs in a specific institution, considering its specific environment. Finally, the clinical level of use (2/12) [ 29 , 34 ] focuses on individual practice and the factors that can influence the implementation of CPGs by professionals.

Type of health service

Institutional services were predominant (5/12) [ 33 , 35 , 36 , 37 , 40 ] and included methodological guidelines and a study of model development and validation. Hospitals were the second most common type of health service (4/12) [ 29 , 30 , 31 , 34 ], followed by ambulatorial (2/12) [ 32 , 34 ] and community health services (1/12) [ 32 ]. Two studies did not specify which type of health service the assessment addressed [ 38 , 39 ].

Target group

The focus of the target group was professionals directly involved in clinical practice (6/12) [ 29 , 31 , 32 , 34 , 38 , 40 ], namely, health professionals and clinicians. Other less related stakeholders included guideline developers (2/12) [ 39 , 40 ], health policy decision makers (1/12) [ 39 ], and healthcare organizations (1/12) [ 39 ]. The target group was not defined in the methodological guidelines, although all the mentioned stakeholders could be related to these documents.

Model and framework characteristics

Models and frameworks for assessing the implementation of cpgs.

The Consolidated Framework for Implementation Research (CFIR) [ 31 , 38 ] and the Promoting Action on Research Implementation in Health Systems (PARiHS) framework [ 29 , 30 ] were the most commonly employed frameworks within the selected documents. The other models mentioned were: Goal commitment and implementation of practice guidelines framework [ 32 ]; Guideline to identify key indicators [ 35 ]; Guideline implementation checklist [ 37 ]; Guideline implementation evaluation tool [ 40 ]; JBI Implementation Framework [ 33 ]; Reach, effectiveness, adoption, implementation and maintenance (RE-AIM) framework [ 34 ]; The Guideline Implementability Framework [ 39 ] and an unnamed model [ 36 ].

Domains evaluated

The number of domains evaluated (or suggested for evaluation) by the documents varied between three and five, with the majority focusing on three domains. All the models addressed the domain "context", with a particular emphasis on the micro level of the health care context (8/12) [ 29 , 31 , 34 , 35 , 36 , 37 , 38 , 39 ], followed by the multilevel (7/12) [ 29 , 31 , 32 , 33 , 38 , 39 , 40 ], meso level (4/12) [ 30 , 35 , 39 , 40 ] and macro level (2/12) [ 37 , 39 ]. The "Outcome" domain was evaluated in nine models. Within this domain, the most frequently evaluated subdomain was "adoption" (6/12) [ 29 , 32 , 34 , 35 , 36 , 37 ], followed by "acceptability" (4/12) [ 30 , 32 , 35 , 39 ], "appropriateness" (3/12) [ 32 , 34 , 36 ], "feasibility" (3/12) [ 29 , 32 , 36 ], "cost" (1/12) [ 35 ] and "penetration" (1/12) [ 34 ]. Regarding the other domains, "Intervention" (8/12) [ 29 , 31 , 34 , 35 , 36 , 38 , 39 , 40 ], "Strategies" (7/12) [ 29 , 30 , 33 , 35 , 36 , 37 , 40 ] and "Process" (5/12) [ 29 , 31 , 32 , 33 , 38 ] were frequently addressed in the models, while "Sustainability" (1/12) [ 34 ] was only found in one model, and "Fidelity/Adaptation" was not observed. The domains presented by the models and frameworks and evaluated in the documents are shown in Table  2 .

Limitations of the models

Only two documents mentioned limitations in the use of the model or frameworks. These two studies reported limitations in the use of CFIR: "is complex and cumbersome and requires tailoring of the key variables to the specific context", and "this framework should be supplemented with other important factors and local features to achieve a sound basis for the planning and realization of an ongoing project" [ 31 , 38 ]. Limitations in the use of other models or frameworks are not reported.

Subgroup analysis

Following the subgroup analysis (Table  3 ), five different models/frameworks were utilized at the policy level by institutional health services. These included the Guideline Implementation Evaluation Tool [ 40 ], the NHMRC tool (model name not defined) [ 36 ], the JBI Implementation Framework + GRiP [ 33 ], Guideline to identify key indicators [ 35 ], and the Guideline implementation checklist [ 37 ]. Additionally, the "Guideline Implementability Framework" [ 39 ] was implemented at the policy level without restrictions based on the type of health service. Regarding the organizational level, the models used varied depending on the type of service. The "Goal commitment and implementation of practice guidelines framework" [ 32 ] was applied in community and ambulatory health services, while "PARiHS" [ 29 , 30 ] and "CFIR" [ 31 , 38 ] were utilized in hospitals. In contexts where the type of health service was not defined, "CFIR" [ 31 , 38 ] and "The Guideline Implementability Framework" [ 39 ] were employed. Lastly, at the clinical level, "RE-AIM" [ 34 ] was utilized in ambulatory and hospital services, and PARiHS [ 29 , 30 ] was specifically used in hospital services.

Key findings

This systematic review identified 10 models/ frameworks used to assess the implementation of CPGs in various health system contexts. These documents shared similar objectives in utilizing models and frameworks for assessment. The primary level of use was policy, the most common type of health service was institutional, and the main target group of the documents was professionals directly involved in clinical practice. The models and frameworks presented varied analytical domains, with sometimes divergent concepts used in these domains. This study is innovative in its emphasis on the evaluation stage of CPG implementation and in summarizing aspects and domains aimed at the practical application of these models.

The small number of documents contrasts with studies that present an extensive range of models and frameworks available in implementation science. The findings suggest that the use of models and frameworks to evaluate the implementation of CPGs is still in its early stages. Among the selected documents, there was a predominance of cross-sectional studies and methodological guidelines, which strongly influenced how the implementation evaluation was conducted. This was primarily done through surveys/questionnaires, qualitative methods (interviews, group discussions), and non-specific measurement instruments. Regarding the subject areas evaluated, most studies focused on a general clinical area, while others explored different clinical areas. This suggests that the evaluation of CPG implementation has been carried out in various contexts.

The models were chosen independently of the categories proposed in the literature, with their usage categorized for purposes other than implementation evaluation, as is the case with CFIR and PARiHS. This practice was described by Nilsen et al. who suggested that models and frameworks from other categories can also be applied for evaluation purposes because they specify concepts and constructs that may be operationalized and measured [ 14 , 15 , 42 , 43 ].

The results highlight the increased use of models and frameworks in evaluation processes at the policy level and institutional environments, followed by the organizational level in hospital settings. This finding contradicts a review that reported the policy level as an area that was not as well studied [ 44 ]. The use of different models at the institutional level is also emphasized in the subgroup analysis. This may suggest that the greater the impact (social, financial/economic, and organizational) of implementing CPGs, the greater the interest and need to establish well-defined and robust processes. In this context, the evaluation stage stands out as crucial, and the investment of resources and efforts to structure this stage becomes even more advantageous [ 10 , 45 ]. Two studies (16,7%) evaluated the implementation of CPGs at the individual level (clinical level). These studies stand out for their potential to analyze variations in clinical practice in greater depth.

In contrast to the level of use and type of health service most strongly indicated in the documents, with systemic approaches, the target group most observed was professionals directly involved in clinical practice. This suggests an emphasis on evaluating individual behaviors. This same emphasis is observed in the analysis of the models, in which there is a predominance of evaluating the micro level of the health context and the "adoption" subdomain, in contrast with the sub-use of domains such as "cost" and "process". Cassetti et al. observed the same phenomenon in their review, in which studies evaluating the implementation of CPGs mainly adopted a behavioral change approach to tackle those issues, without considering the influence of wider social determinants of health [ 10 ]. However, the literature widely reiterates that multiple factors impact the implementation of CPGs, and different actions are required to make them effective [ 6 , 46 , 47 ]. As a result, there is enormous potential for the development and adaptation of models and frameworks aimed at more systemic evaluation processes that consider institutional and organizational aspects.

In analyzing the model domains, most models focused on evaluating only some aspects of implementation (three domains). All models evaluated the "context", highlighting its significant influence on implementation [ 9 , 26 ]. Context is an essential effect modifier for providing research evidence to guide decisions on implementation strategies [ 48 ]. Contextualizing a guideline involves integrating research or other evidence into a specific circumstance [ 49 ]. The analysis of this domain was adjusted to include all possible contextual aspects, even if they were initially allocated to other domains. Some contextual aspects presented by the models vary in comprehensiveness, such as the assessment of the "timing and nature of stakeholder engagement" [ 39 ], which includes individual engagement by healthcare professionals and organizational involvement in CPG implementation. While the importance of context is universally recognized, its conceptualization and interpretation differ across studies and models. This divergence is also evident in other domains, consistent with existing literature [ 14 ]. Efforts to address this conceptual divergence in implementation science are ongoing, but further research and development are needed in this field [ 26 ].

The main subdomain evaluated was "adoption" within the outcome domain. This may be attributed to the ease of accessing information on the adoption of the CPG, whether through computerized system records, patient records, or self-reports from healthcare professionals or patients themselves. The "acceptability" subdomain pertains to the perception among implementation stakeholders that a particular CPG is agreeable, palatable or satisfactory. On the other hand, "appropriateness" encompasses the perceived fit, relevance or compatibility of the CPG for a specific practice setting, provider, or consumer, or its perceived fit to address a particular issue or problem [ 26 ]. Both subdomains are subjective and rely on stakeholders' interpretations and perceptions of the issue being analyzed, making them susceptible to reporting biases. Moreover, obtaining this information requires direct consultation with stakeholders, which can be challenging for some evaluation processes, particularly in institutional contexts.

The evaluation of the subdomains "feasibility" (the extent to which a CPG can be successfully used or carried out within a given agency or setting), "cost" (the cost impact of an implementation effort), and "penetration" (the extent to which an intervention or treatment is integrated within a service setting and its subsystems) [ 26 ] was rarely observed in the documents. This may be related to the greater complexity of obtaining information on these aspects, as they involve cross-cutting and multifactorial issues. In other words, it would be difficult to gather this information during evaluations with health practitioners as the target group. This highlights the need for evaluation processes of CPGs implementation involving multiple stakeholders, even if the evaluation is adjusted for each of these groups.

Although the models do not establish the "intervention" domain, we thought it pertinent in this study to delimit the issues that are intrinsic to CPGs, such as methodological quality or clarity in establishing recommendations. These issues were quite common in the models evaluated but were considered in other domains (e.g., in "context"). Studies have reported the importance of evaluating these issues intrinsic to CPGs [ 47 , 50 ] and their influence on the implementation process [ 51 ].

The models explicitly present the "strategies" domain, and its evaluation was usually included in the assessments. This is likely due to the expansion of scientific and practical studies in implementation science that involve theoretical approaches to the development and application of interventions to improve the implementation of evidence-based practices. However, these interventions themselves are not guaranteed to be effective, as reported in a previous review that showed unclear results indicating that the strategies had affected successful implementation [ 52 ]. Furthermore, model domains end up not covering all the complexity surrounding the strategies and their development and implementation process. For example, the ‘Guideline implementation evaluation tool’ evaluates whether guideline developers have designed and provided auxiliary tools to promote the implementation of guidelines [ 40 ], but this does not mean that these tools would work as expected.

The "process" domain was identified in the CFIR [ 31 , 38 ], JBI/GRiP [ 33 ], and PARiHS [ 29 ] frameworks. While it may be included in other domains of analysis, its distinct separation is crucial for defining operational issues when assessing the implementation process, such as determining if and how the use of the mentioned CPG was evaluated [ 3 ]. Despite its presence in multiple models, there is still limited detail in the evaluation guidelines, which makes it difficult to operationalize the concept. Further research is needed to better define the "process" domain and its connections and boundaries with other domains.

The domain of "sustainability" was only observed in the RE-AIM framework, which is categorized as an evaluation framework [ 34 ]. In its acronym, the letter M stands for "maintenance" and corresponds to the assessment of whether the user maintains use, typically longer than 6 months. The presence of this domain highlights the need for continuous evaluation of CPGs implementation in the short, medium, and long term. Although the RE-AIM framework includes this domain, it was not used in the questionnaire developed in the study. One probable reason is that the evaluation of CPGs implementation is still conducted on a one-off basis and not as a continuous improvement process. Considering that changes in clinical practices are inherent over time, evaluating and monitoring changes throughout the duration of the CPG could be an important strategy for ensuring its implementation. This is an emerging field that requires additional investment and research.

The "Fidelity/Adaptation" domain was not observed in the models. These emerging concepts involve the extent to which a CPG is being conducted exactly as planned or whether it is undergoing adjustments and adaptations. Whether or not there is fidelity or adaptation in the implementation of CPGs does not presuppose greater or lesser effectiveness; after all, some adaptations may be necessary to implement general CPGs in specific contexts. The absence of this domain in all the models and frameworks may suggest that they are not relevant aspects for evaluating implementation or that there is a lack of knowledge of these complex concepts. This may suggest difficulty in expressing concepts in specific evaluative questions. However, further studies are warranted to determine the comprehensiveness of these concepts.

It is important to note the customization of the domains of analysis, with some domains presented in the models not being evaluated in the studies, while others were complementarily included. This can be seen in Jeong et al. [ 34 ], where the "intervention" domain in the evaluation with the RE-AIM framework reinforced the aim of theoretical approaches such as guiding the process and not determining norms. Despite this, few limitations were reported for the models, suggesting that the use of models in these studies reflects the application of these models to defined contexts without a deep critical analysis of their domains.

Limitations

This review has several limitations. First, only a few studies and methodological guidelines that explicitly present models and frameworks for assessing the implementation of CPGs have been found. This means that few alternative models could be analyzed and presented in this review. Second, this review adopted multiple analytical categories (e.g., level of use, health service, target group, and domains evaluated), whose terminology has varied enormously in the studies and documents selected, especially for the "domains evaluated" category. This difficulty in harmonizing the taxonomy used in the area has already been reported [ 26 ] and has significant potential to confuse. For this reason, studies and initiatives are needed to align understandings between concepts and, as far as possible, standardize them. Third, in some studies/documents, the information extracted was not clear about the analytical category. This required an in-depth interpretative process of the studies, which was conducted in pairs to avoid inappropriate interpretations.

Implications

This study contributes to the literature and clinical practice management by describing models and frameworks specifically used to assess the implementation of CPGs based on their level of use, type of health service, target group related to the CPG, and the evaluated domains. While there are existing reviews on the theories, frameworks, and models used in implementation science, this review addresses aspects not previously covered in the literature. This valuable information can assist stakeholders (such as politicians, clinicians, researchers, etc.) in selecting or adapting the most appropriate model to assess CPG implementation based on their health context. Furthermore, this study is expected to guide future research on developing or adapting models to assess the implementation of CPGs in various contexts.

The use of models and frameworks to evaluate the implementation remains a challenge. Studies should clearly state the level of model use, the type of health service evaluated, and the target group. The domains evaluated in these models may need adaptation to specific contexts. Nevertheless, utilizing models to assess CPGs implementation is crucial as they can guide a more thorough and systematic evaluation process, aiding in the continuous improvement of CPGs implementation. The findings of this systematic review offer valuable insights for stakeholders in selecting or adjusting models and frameworks for CPGs evaluation, supporting future theoretical advancements and research.

Availability of data and materials

Abbreviations.

Australian Department of Health and Aged Care

Canadian Agency for Drugs and Technologies in Health

Centers for Disease Control and

Consolidated Framework for Implementation Research

Cumulative Index to Nursing and Allied Health Literature

Clinical practice guideline

Centre for Reviews and Dissemination

Guidelines International Networks

Getting Research into Practice

Health Systems Evidence

Institute of Medicine

The Joanna Briggs Institute

Ministry of Health of Brazil

Ministerio de Sanidad y Política Social

National Health and Medical Research Council

National Institute for Health and Care Excellence

Promoting action on research implementation in health systems framework

Predisposing, Reinforcing and Enabling Constructs in Educational Diagnosis and Evaluation-Policy, Regulatory, and Organizational Constructs in Educational and Environmental Development

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

International Prospective Register of Systematic Reviews

Reach, effectiveness, adoption, implementation, and maintenance framework

Healthcare Improvement Scotland

United States of America

Virtual Health Library

World Health Organization

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This study is supported by the Fundação de Apoio à Pesquisa do Distrito Federal (FAPDF). FAPDF Award Term (TOA) nº 44/2024—FAPDF/SUCTI/COOBE (SEI/GDF – Process 00193–00000404/2024–22). The content in this article is solely the responsibility of the authors and does not necessarily represent the official views of the FAPDF.

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NFM and JOMB conceived the idea and the protocol for this study. NFM conducted the literature search. NFM, SNS, JMG and JOMB conducted the data collection with advice and consensus gathering from JOMB. The NFM and JMG assessed the quality of the studies. NFM and DFG conducted the data extraction. NFM performed the analysis and synthesis of the results with advice and consensus gathering from JOMB. NFM drafted the manuscript. JOMB critically revised the first version of the manuscript. All the authors revised and approved the submitted version.

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Supplementary Information

13012_2024_1389_moesm1_esm.docx.

Additional file 1: PRISMA checklist. Description of data: Completed PRISMA checklist used for reporting the results of this systematic review.

Additional file 2: Literature search. Description of data: The search strategies adapted for the electronic databases.

13012_2024_1389_moesm3_esm.doc.

Additional file 3: JBI’s critical appraisal tools for cross-sectional studies. Description of data: JBI’s critical appraisal tools to assess the trustworthiness, relevance, and results of the included studies. This is specific for cross-sectional studies.

13012_2024_1389_MOESM4_ESM.doc

Additional file 4: JBI’s critical appraisal tools for qualitative studies. Description of data: JBI’s critical appraisal tools to assess the trustworthiness, relevance, and results of the included studies. This is specific for qualitative studies.

13012_2024_1389_MOESM5_ESM.doc

Additional file 5: Methodological quality assessment results for cross-sectional studies. Description of data: Methodological quality assessment results for cross-sectional studies using JBI’s critical appraisal tools.

13012_2024_1389_MOESM6_ESM.doc

Additional file 6: Methodological quality assessment results for the qualitative studies. Description of data: Methodological quality assessment results for qualitative studies using JBI’s critical appraisal tools.

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Freitas de Mello, N., Nascimento Silva, S., Gomes, D.F. et al. Models and frameworks for assessing the implementation of clinical practice guidelines: a systematic review. Implementation Sci 19 , 59 (2024). https://doi.org/10.1186/s13012-024-01389-1

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Received : 06 February 2024

Accepted : 01 August 2024

Published : 07 August 2024

DOI : https://doi.org/10.1186/s13012-024-01389-1

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