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• How to Write a Literature Review | Guide, Examples, & Templates

How to Write a Literature Review | Guide, Examples, & Templates

Published on January 2, 2023 by Shona McCombes . Revised on September 11, 2023.

What is a literature review? A literature review is a survey of scholarly sources on a specific topic. It provides an overview of current knowledge, allowing you to identify relevant theories, methods, and gaps in the existing research that you can later apply to your paper, thesis, or dissertation topic .

There are five key steps to writing a literature review:

• Search for relevant literature
• Evaluate sources
• Identify themes, debates, and gaps
• Outline the structure
• Write your literature review

A good literature review doesn’t just summarize sources—it analyzes, synthesizes , and critically evaluates to give a clear picture of the state of knowledge on the subject.

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Table of contents

What is the purpose of a literature review, examples of literature reviews, step 1 – search for relevant literature, step 2 – evaluate and select sources, step 3 – identify themes, debates, and gaps, step 4 – outline your literature review’s structure, step 5 – write your literature review, free lecture slides, other interesting articles, frequently asked questions, introduction.

• Quick Run-through
• Step 1 & 2

When you write a thesis , dissertation , or research paper , you will likely have to conduct a literature review to situate your research within existing knowledge. The literature review gives you a chance to:

• Demonstrate your familiarity with the topic and its scholarly context
• Develop a theoretical framework and methodology for your research
• Position your work in relation to other researchers and theorists
• Show how your research addresses a gap or contributes to a debate
• Evaluate the current state of research and demonstrate your knowledge of the scholarly debates around your topic.

Writing literature reviews is a particularly important skill if you want to apply for graduate school or pursue a career in research. We’ve written a step-by-step guide that you can follow below.

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Writing literature reviews can be quite challenging! A good starting point could be to look at some examples, depending on what kind of literature review you’d like to write.

• Example literature review #1: “Why Do People Migrate? A Review of the Theoretical Literature” ( Theoretical literature review about the development of economic migration theory from the 1950s to today.)
• Example literature review #2: “Literature review as a research methodology: An overview and guidelines” ( Methodological literature review about interdisciplinary knowledge acquisition and production.)
• Example literature review #3: “The Use of Technology in English Language Learning: A Literature Review” ( Thematic literature review about the effects of technology on language acquisition.)
• Example literature review #4: “Learners’ Listening Comprehension Difficulties in English Language Learning: A Literature Review” ( Chronological literature review about how the concept of listening skills has changed over time.)

You can also check out our templates with literature review examples and sample outlines at the links below.

Download Word doc Download Google doc

Before you begin searching for literature, you need a clearly defined topic .

If you are writing the literature review section of a dissertation or research paper, you will search for literature related to your research problem and questions .

Make a list of keywords

Start by creating a list of keywords related to your research question. Include each of the key concepts or variables you’re interested in, and list any synonyms and related terms. You can add to this list as you discover new keywords in the process of your literature search.

• Social media, Facebook, Instagram, Twitter, Snapchat, TikTok
• Body image, self-perception, self-esteem, mental health
• Generation Z, teenagers, adolescents, youth

Search for relevant sources

Use your keywords to begin searching for sources. Some useful databases to search for journals and articles include:

• Your university’s library catalogue
• Google Scholar
• Project Muse (humanities and social sciences)
• Medline (life sciences and biomedicine)
• EconLit (economics)
• Inspec (physics, engineering and computer science)

You can also use boolean operators to help narrow down your search.

Make sure to read the abstract to find out whether an article is relevant to your question. When you find a useful book or article, you can check the bibliography to find other relevant sources.

You likely won’t be able to read absolutely everything that has been written on your topic, so it will be necessary to evaluate which sources are most relevant to your research question.

For each publication, ask yourself:

• What question or problem is the author addressing?
• What are the key concepts and how are they defined?
• What are the key theories, models, and methods?
• Does the research use established frameworks or take an innovative approach?
• What are the results and conclusions of the study?
• How does the publication relate to other literature in the field? Does it confirm, add to, or challenge established knowledge?
• What are the strengths and weaknesses of the research?

Make sure the sources you use are credible , and make sure you read any landmark studies and major theories in your field of research.

You can use our template to summarize and evaluate sources you’re thinking about using. Click on either button below to download.

Take notes and cite your sources

As you read, you should also begin the writing process. Take notes that you can later incorporate into the text of your literature review.

It is important to keep track of your sources with citations to avoid plagiarism . It can be helpful to make an annotated bibliography , where you compile full citation information and write a paragraph of summary and analysis for each source. This helps you remember what you read and saves time later in the process.

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To begin organizing your literature review’s argument and structure, be sure you understand the connections and relationships between the sources you’ve read. Based on your reading and notes, you can look for:

• Trends and patterns (in theory, method or results): do certain approaches become more or less popular over time?
• Themes: what questions or concepts recur across the literature?
• Debates, conflicts and contradictions: where do sources disagree?
• Pivotal publications: are there any influential theories or studies that changed the direction of the field?
• Gaps: what is missing from the literature? Are there weaknesses that need to be addressed?

This step will help you work out the structure of your literature review and (if applicable) show how your own research will contribute to existing knowledge.

• Most research has focused on young women.
• There is an increasing interest in the visual aspects of social media.
• But there is still a lack of robust research on highly visual platforms like Instagram and Snapchat—this is a gap that you could address in your own research.

There are various approaches to organizing the body of a literature review. Depending on the length of your literature review, you can combine several of these strategies (for example, your overall structure might be thematic, but each theme is discussed chronologically).

Chronological

The simplest approach is to trace the development of the topic over time. However, if you choose this strategy, be careful to avoid simply listing and summarizing sources in order.

Try to analyze patterns, turning points and key debates that have shaped the direction of the field. Give your interpretation of how and why certain developments occurred.

If you have found some recurring central themes, you can organize your literature review into subsections that address different aspects of the topic.

For example, if you are reviewing literature about inequalities in migrant health outcomes, key themes might include healthcare policy, language barriers, cultural attitudes, legal status, and economic access.

Methodological

If you draw your sources from different disciplines or fields that use a variety of research methods , you might want to compare the results and conclusions that emerge from different approaches. For example:

• Look at what results have emerged in qualitative versus quantitative research
• Discuss how the topic has been approached by empirical versus theoretical scholarship
• Divide the literature into sociological, historical, and cultural sources

Theoretical

A literature review is often the foundation for a theoretical framework . You can use it to discuss various theories, models, and definitions of key concepts.

You might argue for the relevance of a specific theoretical approach, or combine various theoretical concepts to create a framework for your research.

Like any other academic text , your literature review should have an introduction , a main body, and a conclusion . What you include in each depends on the objective of your literature review.

The introduction should clearly establish the focus and purpose of the literature review.

Depending on the length of your literature review, you might want to divide the body into subsections. You can use a subheading for each theme, time period, or methodological approach.

As you write, you can follow these tips:

• Summarize and synthesize: give an overview of the main points of each source and combine them into a coherent whole
• Analyze and interpret: don’t just paraphrase other researchers — add your own interpretations where possible, discussing the significance of findings in relation to the literature as a whole
• Critically evaluate: mention the strengths and weaknesses of your sources
• Write in well-structured paragraphs: use transition words and topic sentences to draw connections, comparisons and contrasts

In the conclusion, you should summarize the key findings you have taken from the literature and emphasize their significance.

When you’ve finished writing and revising your literature review, don’t forget to proofread thoroughly before submitting. Not a language expert? Check out Scribbr’s professional proofreading services !

This article has been adapted into lecture slides that you can use to teach your students about writing a literature review.

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

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

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

It is often written as part of a thesis, dissertation , or research paper , in order to situate your work in relation to existing knowledge.

There are several reasons to conduct a literature review at the beginning of a research project:

• To familiarize yourself with the current state of knowledge on your topic
• To ensure that you’re not just repeating what others have already done
• To identify gaps in knowledge and unresolved problems that your research can address
• To develop your theoretical framework and methodology
• To provide an overview of the key findings and debates on the topic

Writing the literature review shows your reader how your work relates to existing research and what new insights it will contribute.

The literature review usually comes near the beginning of your thesis or dissertation . After the introduction , it grounds your research in a scholarly field and leads directly to your theoretical framework or methodology .

A literature review is a survey of credible sources on a topic, often used in dissertations , theses, and research papers . Literature reviews give an overview of knowledge on a subject, helping you identify relevant theories and methods, as well as gaps in existing research. Literature reviews are set up similarly to other  academic texts , with an introduction , a main body, and a conclusion .

An  annotated bibliography is a list of  source references that has a short description (called an annotation ) for each of the sources. It is often assigned as part of the research process for a  paper .  

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Libraries | Research Guides

Literature reviews, what is a literature review, learning more about how to do a literature review.

• Planning the Review
• The Research Question
• Choosing Where to Search
• Organizing the Review
• Writing the Review

A literature review is a review and synthesis of existing research on a topic or research question. A literature review is meant to analyze the scholarly literature, make connections across writings and identify strengths, weaknesses, trends, and missing conversations. A literature review should address different aspects of a topic as it relates to your research question. A literature review goes beyond a description or summary of the literature you have read. 

• Sage Research Methods Core This link opens in a new window SAGE Research Methods supports research at all levels by providing material to guide users through every step of the research process. SAGE Research Methods is the ultimate methods library with more than 1000 books, reference works, journal articles, and instructional videos by world-leading academics from across the social sciences, including the largest collection of qualitative methods books available online from any scholarly publisher. – Publisher

• Next: Planning the Review >>
• Last Updated: Jul 8, 2024 11:22 AM
• URL: https://libguides.northwestern.edu/literaturereviews

• University of Texas Libraries

Literature Reviews

• What is a literature review?
• Steps in the Literature Review Process
• Define your research question
• Determine inclusion and exclusion criteria
• Choose databases and search
• Review Results
• Synthesize Results
• Analyze Results
• Librarian Support
• Artificial Intelligence (AI) Tools

What is a Literature Review?

A literature or narrative review is a comprehensive review and analysis of the published literature on a specific topic or research question. The literature that is reviewed contains: books, articles, academic articles, conference proceedings, association papers, and dissertations. It contains the most pertinent studies and points to important past and current research and practices. It provides background and context, and shows how your research will contribute to the field. 

A literature review should: 

• Provide a comprehensive and updated review of the literature;
• Explain why this review has taken place;
• Articulate a position or hypothesis;
• Acknowledge and account for conflicting and corroborating points of view

From  S age Research Methods

Purpose of a Literature Review

A literature review can be written as an introduction to a study to:

• Demonstrate how a study fills a gap in research
• Compare a study with other research that's been done

Or it can be a separate work (a research article on its own) which:

• Organizes or describes a topic
• Describes variables within a particular issue/problem

Limitations of a Literature Review

Some of the limitations of a literature review are:

• It's a snapshot in time. Unlike other reviews, this one has beginning, a middle and an end. There may be future developments that could make your work less relevant.
• It may be too focused. Some niche studies may miss the bigger picture.
• It can be difficult to be comprehensive. There is no way to make sure all the literature on a topic was considered.
• It is easy to be biased if you stick to top tier journals. There may be other places where people are publishing exemplary research. Look to open access publications and conferences to reflect a more inclusive collection. Also, make sure to include opposing views (and not just supporting evidence).

Source: Grant, Maria J., and Andrew Booth. “A Typology of Reviews: An Analysis of 14 Review Types and Associated Methodologies.” Health Information & Libraries Journal, vol. 26, no. 2, June 2009, pp. 91–108. Wiley Online Library, doi:10.1111/j.1471-1842.2009.00848.x.

Librarian Assistance

For help, please contact the librarian for your subject area.  We have a guide to library specialists by subject .

• Last Updated: Aug 26, 2024 5:59 AM
• URL: https://guides.lib.utexas.edu/literaturereviews

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Literature Review | Definition

Literature Review refers to systematically analyzing and summarizing existing research and theoretical frameworks on a particular topic.

Introduction to Literature Review

A literature review is a fundamental component of any research project, particularly in social sciences. It involves critically examining and synthesizing the available knowledge on a specific topic. The goal is to understand what has already been explored, identify gaps, and situate new research within the broader scholarly conversation. The literature review provides the background and context for a research question, ensuring that the study is grounded in existing knowledge and theoretical frameworks.

Purpose of a Literature Review

The literature review serves several key purposes within the research process:

• Identifying Gaps in Knowledge : One of the primary purposes of a literature review is to reveal areas where research is lacking. By evaluating what has already been studied, researchers can pinpoint gaps and opportunities for further investigation.
• Establishing Context : It places a research question in the context of the broader field. Researchers can show how their work relates to previous studies and why their research is necessary by exploring past theories and findings.
• Avoiding Duplication : A thorough review ensures that researchers do not unintentionally duplicate existing studies. It also allows researchers to build on previous work rather than repeat it.
• Supporting Methodological Choices : Reviewing the methods used in earlier studies helps researchers choose appropriate research designs and methodologies for their own projects. Researchers can assess what approaches have been successful or problematic in the past.
• Developing a Theoretical Framework : Literature reviews help identify and outline theoretical frameworks relevant to the research. By aligning a study with a particular theory, researchers can provide a structured lens through which to analyze their data.

Types of Literature Reviews

There are various types of literature reviews, each with a specific focus and methodology. Understanding these differences helps researchers choose the best approach for their own study.

Narrative (Traditional) Review

A narrative review provides a broad overview of the research on a particular topic. It synthesizes findings from multiple studies but often lacks a structured methodology. Narrative reviews are typically less systematic than other types and may focus on summarizing key findings, theories, and debates in the literature. This type of review is commonly used to set the stage for new research by providing context and identifying general trends.

Systematic Review

A systematic review is more structured and follows a specific methodology to identify, evaluate, and synthesize all relevant studies on a particular research question. The aim is to minimize bias and provide a comprehensive summary of the existing evidence. Systematic reviews often include detailed criteria for including or excluding studies, ensuring that the review is thorough and transparent. This type of review is particularly common in medical and health research but is increasingly used in the social sciences.

Meta-Analysis

A meta-analysis is a specific type of systematic review that uses statistical techniques to combine the results of multiple studies. By pooling data from various studies, researchers can identify patterns and relationships that may not be evident in individual studies. Meta-analyses are often used to provide more robust conclusions about a research question, particularly when individual studies have small sample sizes.

Scoping Review

A scoping review is used to map the existing literature on a broad topic. Unlike systematic reviews, scoping reviews are not focused on answering a specific research question. Instead, they aim to provide an overview of the range of evidence available and highlight gaps in the literature. Scoping reviews are often used when a field is emerging or when researchers want to explore the breadth of available research before narrowing down their focus.

Critical Review

A critical review goes beyond summarizing the literature to evaluate and critique the methodologies, theories, and findings of the studies. The goal is to assess the strengths and weaknesses of the existing research and propose new perspectives or directions for future research. Critical reviews are valuable for advancing theoretical discussions and offering deeper insights into the state of the field.

Stand-Alone Literature Reviews

A stand-alone literature review is a comprehensive analysis of the literature on a specific topic, presented independently of any new research study. Unlike literature reviews that are embedded within research papers, stand-alone reviews focus solely on synthesizing existing knowledge. They do not introduce new empirical research but serve as a resource to consolidate findings, evaluate theories, and provide a detailed understanding of a subject area. These reviews are often published in academic journals as independent articles, serving as a valuable resource for scholars, practitioners, and policymakers.

Purpose of Stand-Alone Literature Reviews

Stand-alone literature reviews have a distinct role in the research ecosystem. Their primary purposes include:

• Summarizing the Current State of Knowledge : Stand-alone reviews provide a snapshot of what is known about a particular topic at a given time. By synthesizing findings from multiple studies, they offer a clear, consolidated understanding of the subject matter.
• Identifying Gaps and Future Research Directions : Just like embedded reviews, stand-alone literature reviews highlight areas where knowledge is lacking. However, because these reviews are more comprehensive, they can offer a deeper analysis of research gaps, which is helpful for guiding future investigations.
• Evaluating and Critiquing Theories and Methods : A stand-alone review often includes a critical evaluation of the methodologies and theoretical frameworks used in previous studies. This level of scrutiny can help refine research methods or propose new theoretical approaches.
• Providing a Resource for Practitioners : In fields such as public health, education, and social work, stand-alone literature reviews can offer valuable insights for practitioners who may not have the time to sift through individual studies. A comprehensive review provides a single document that summarizes key findings and recommendations for practice.

Structure of Stand-Alone Literature Reviews

While stand-alone literature reviews vary in length and scope, they generally follow a structured format similar to that of systematic reviews. Common elements include:

• Introduction : The review begins with an introduction that outlines the topic, the purpose of the review, and the research questions guiding the synthesis. This section sets the stage by explaining why the review is important and what gaps or problems it seeks to address.
• Thematic Analysis or Synthesis : The main body of the review is dedicated to synthesizing the findings from the selected studies. It often organizes the literature into themes or categories based on key issues, theories, or methods. For example, in a review of the effects of social media on mental health, themes might include “positive impacts,” “negative impacts,” and “methodological limitations.”
• Discussion and Conclusion : The review concludes by summarizing the main findings and discussing their implications. This section often emphasizes gaps in the literature and suggests areas for future research. In stand-alone reviews, this discussion may also include recommendations for practice or policy based on the review’s findings.

Benefits of Stand-Alone Literature Reviews

Stand-alone literature reviews provide several advantages for both researchers and the broader academic community:

• Comprehensive Insight : Because these reviews are not limited by space constraints typical of embedded literature reviews in research papers, they often provide a more thorough analysis of the topic.
• Resource Efficiency : For researchers new to a field, a stand-alone literature review offers a one-stop resource that summarizes all relevant research. This can save time and effort compared to reading multiple individual studies.
• Setting the Research Agenda : By clearly identifying gaps and inconsistencies in the literature, stand-alone reviews help set the research agenda for future studies. They provide a foundation for subsequent research by clarifying what is already known and what remains to be discovered.

Challenges of Stand-Alone Literature Reviews

While valuable, stand-alone literature reviews also present some challenges:

• Time-Consuming : Conducting a comprehensive stand-alone review can be time-intensive. Reviewing hundreds of studies, synthesizing findings, and ensuring a balanced perspective takes a significant amount of time and effort.
• Potential for Bias : Despite efforts to remain objective, there is always the risk of bias in selecting studies or interpreting findings. Researchers must be careful to avoid cherry-picking studies that support a particular viewpoint.
• Limited New Contributions : Because stand-alone literature reviews do not present original research, they may be seen as less innovative or groundbreaking. However, their value lies in providing a critical synthesis rather than introducing new data.

Steps in Conducting a Literature Review

Conducting a literature review involves a systematic process to ensure that it is comprehensive and unbiased. While the steps may vary slightly depending on the type of review, the general process is as follows:

1. Define the Research Question or Topic

Before starting a literature review, researchers must clearly define their research question or topic. This step is critical because it helps narrow the focus of the review and ensures that the search for relevant literature is targeted and efficient. A well-defined research question will guide the entire review process.

2. Conduct a Comprehensive Search

The next step is to search for relevant literature. This involves identifying key databases, journals, and other sources that contain scholarly articles related to the research question. Common databases for social science research include:

• Criminal Justice Abstracts
• PubMed (for health-related research)

In addition to searching these databases, researchers should consider including gray literature, such as government reports, theses, and conference papers, to ensure a comprehensive review.

3. Evaluate and Select Relevant Studies

Once the literature search is complete, the next step is to evaluate the studies for relevance and quality. Researchers should establish clear inclusion and exclusion criteria to help filter out studies that are not pertinent to the research question. This might include factors such as publication date, study design, sample size, and relevance to the research topic.

4. Organize and Analyze the Literature

After selecting the relevant studies, researchers must organize the literature to make it easier to analyze and synthesize. Grouping studies by themes, methodologies, or findings can help identify patterns and relationships in the literature. Creating a literature matrix or concept map can also help researchers visualize connections between studies.

5. Synthesize the Findings

The heart of the literature review is the synthesis of findings. Rather than simply summarizing individual studies, researchers must integrate the results to provide a cohesive understanding of the topic. This involves highlighting similarities and differences between studies, identifying trends, and discussing the implications of the findings for the research question.

6. Write the Review

The final step is writing the literature review. The review should be well-organized and clearly structured, with sections that address the key themes or findings from the literature. Researchers should also critically engage with the literature by discussing the strengths and limitations of existing studies and identifying gaps for future research.

Common Challenges

Conducting a literature review can be a challenging process. Some common difficulties include:

1. Managing the Volume of Literature

With the vast amount of research published in many fields, it can be overwhelming to sift through the literature. Researchers must strike a balance between being comprehensive and focused, ensuring that they include the most relevant studies without getting bogged down in irrelevant material.

2. Maintaining Objectivity

It can be difficult to remain objective when reviewing literature, particularly if researchers have a preconceived idea of what they hope to find. Using a systematic approach and clear inclusion criteria can help minimize bias in the review process.

3. Synthesizing Diverse Findings

In many cases, the literature on a particular topic may include studies with conflicting findings or different methodologies. Synthesizing these diverse results in a meaningful way can be challenging, but it is crucial for providing a well-rounded understanding of the research.

4. Time Constraints

Literature reviews can be time-consuming, particularly if the field has a large body of research. Researchers must manage their time effectively, prioritizing key studies and staying focused on their research question.

Best Practices for Conducting a Literature Review

To ensure that a literature review is thorough, well-organized, and meaningful, researchers should follow several best practices:

• Be Systematic : Whether conducting a narrative review or a systematic review, it is important to follow a clear and organized process.
• Use Multiple Databases : Searching a variety of databases ensures that the literature review is comprehensive and includes studies from different disciplines.
• Keep Detailed Records : Documenting the search process, including the databases searched, keywords used, and studies included or excluded, is essential for transparency and reproducibility.
• Critically Engage with the Literature : Rather than simply summarizing existing studies, researchers should critically assess the methodologies, findings, and theories in the literature.
• Seek Peer Feedback : Getting feedback from colleagues or mentors can help identify gaps or areas where the review could be improved.

A literature review is an essential step in the research process. It helps researchers build on existing knowledge, identify gaps, and develop a theoretical framework for their studies. By carefully evaluating and synthesizing the available literature, researchers can position their work within the broader academic conversation, ensuring that their research contributes meaningfully to the field.

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Home > Books > National Security in the Digital and Information Age

The Front End of Innovation in Defense: A Comprehensive Literature Review

Submitted: 18 January 2024 Reviewed: 02 March 2024 Published: 30 April 2024

DOI: 10.5772/intechopen.1005191

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Innovation management, a multifaceted organizational process encompassing opportunities and ideas from inception to implementation, demands a systematic approach, particularly in the critical initial phase known as the Front End of Innovation (FEI). This pivotal phase significantly influences the entire innovation management chain. Despite its recognized importance, FEI in the defense sector has yet to be systematically addressed in the academic literature. Recognizing the vital role of FEI in the defense sector, this study addresses this deficiency through a systematic review, scrutinizing 24 documents from the scientific literature (Scopus and Web of Science databases) and gray literature (government defense documents). This research systematically maps key activities identified in seminal FEI models. These activities include the identification and analysis of opportunities; generation, enrichment, and screening of ideas; product concept definition; and consideration of influencing factors. Concurrently, this work aligns defense practices with established innovation models and provides valuable insights for optimizing the management dynamics of the military innovation process. Through this systematic inquiry, this study contributes to a nuanced understanding of the FEI in the defense sector, offering practical implications for enhancing defense innovation development.

• front end of innovation
• literature review

Author Information

Romullo girardi *.

• Military Institute of Engineering, Rio de Janeiro, Brazil
• INESC TEC and Faculty of Engineering, University of Porto, Porto, Portugal

Juraci Ferreira Galdino

Paulo césar pellanda.

*Address all correspondence to: [email protected]

1. Introduction

Innovation management, a complex and broad organizational process covering the entire spectrum, from identifying new opportunities and ideas to their practical implementation, poses significant challenges for managers across all organizational levels [ 1 ].

Notably, innovation seldom fails due to a lack of creativity; instead, it is the absence of discipline that plays a pivotal role in innovation failures [ 2 ]. From this perspective, Boeddrich [ 3 ] contends that systematic and structured procedures in the early phase, known as the Front End of Innovation (FEI), are imperative to avert adverse effects throughout the innovation management chain.

Multiple researchers emphasize that enhancing FEI activities contributes positively to organizational outcomes, bolstering the likelihood of successful innovation development [ 3 , 4 , 5 , 6 , 7 , 8 , 9 ]. Yet, the successful adoption of a FEI model requires considering some factors like organizational size and culture, as well as decision-making styles [ 10 , 11 ].

Despite the increasing attention to FEI as a complex and multidisciplinary field [ 12 ], the defense context of FEI has not been sufficiently addressed in the academic literature, a gap this study endeavors to address. Therefore, this research aims to unravel the dynamics of FEI in the military sector through a systematic literature review, focusing on the research question: How can the current literature on the early phase of the innovation process in defense be mapped within seminal FEI models?

This question is pertinent given the Armed Forces’ distinct organizational culture, demanding innovation to sustain high-tech operational capabilities and mainly requiring innovations capable of inducing technological surprise in the theater of operations. Aligning defense practices with established models in innovation literature can furnish invaluable insights for improving the management dynamics of the military’s initial innovation phase. Moreover, by reviewing approaches used by different countries, the study recognizes that the suitability and significance of FEI management practices can differ across national defense contexts. It emphasizes how cultural and procedural nuances impact the development and adoption of new technologies in military settings.

Structured around the research question, this paper is organized as follows: Section 2 provides a theoretical foundation on FEI, seminal FEI models, and defense peculiarities. Section 3 outlines the research methodology. Section 4 delineates the mapping of the FEI in the defense sector within seminal FEI models. Section 5 discusses salient aspects identified throughout the study. Finally, Section 6 highlights the concluding remarks, outlining directions for future research.

2. Theoretical foundation

Before exploring the current literature on the early stage of the innovation process in defense, it is essential to understand the foundational topics involved: the FEI concept, the seminal FEI models, and the unique aspects of the military sector.

2.1 Front end of innovation (FEI)

The Fuzzy Front End (FFE) refers to the earliest stage in the New Product Development (NPD) process. This term was popularized by Smith and Reinertsen [ 13 ], as pointed out by Khurana and Rosenthal [ 10 ].

In 2002, Koen et al. [ 14 ] proposed the term Front End of Innovation (FEI), considering that the adjective “fuzzy” is “mysterious, lacks accountability, and cannot be critically evaluated” ([ 14 ], p. 30). The new term dissociated the idea that the initial phase of the innovation process was nebulous and uncontrollable. In this approach, the FEI is described as “those activities that come before the formal and well-structured NPD process” ([ 14 ], p. 30).

Figure 1 illustrates the breakdown of the product innovation management process into three phases: FEI, NPD, and implementation (the commercialization of the product in the market). The circular shape of the FEI suggests that ideas should flow and iterate until the formal definition of products is developed. In contrast, the NPD phase is depicted as a series of sequential, well-structured, and chronologically ordered steps [ 14 , 15 ].

Breakdown of the product innovation management process. Source: Adapted from Koen et al. [ 14 , 15 ].

The FEI emerges as a crucial driver of positive outcomes for new products and, consequently, the overall success of the business [ 16 ]. Markham [ 6 ] underscores the profound impact of early-phase activities on product performance, emphasizing that the success of the front end stands as the strongest independent predictor of all NPD performance variables.

Selecting an appropriate FEI model requires careful consideration of various factors, including organizational size and culture, as well as decision-making style [ 10 , 11 ]. As a response to these diverse organizational needs, numerous FEI models have been developed over time, offering distinct approaches to navigate their complexities, as detailed in the next section.

2.2 Seminal FEI models

In an integrative literature review, Pereira et al. [ 12 ] found that 26% of articles related to FEI contributed in terms of frameworks, models, processes, tools, and methodologies, exemplifying endeavors to structure the early phase of the innovation process in specific contexts.

While recent contributions are significant, seminal works have produced models that served as reference points for structuring the FEI. Table 1 provides an overview of the four seminal models identified by Pereira et al. [ 12 , 20 ].

Seminal FEI models.

Source: Adapted from Pereira et al. [ 12 , 20 ].

Stage 0 (Discovery) : In this inaugural stage, the organization actively generates ideas for new products.

Gate 1 (Idea screen) : Ideas undergo a concise evaluation based on strategic, feasibility, and market criteria. Financial considerations are deferred at this point. Accepted ideas proceed to the next phase.

Stage 1 (Scoping) : The accepted idea transitions into a project, initiating a dual evaluation process:

Market evaluation : Involves research, user contact, and conceptual testing to determine market size and acceptance.

Technical evaluation : Encompasses feasibility, costs, and development timelines.

Gate 2 (Second screen) : Comprehensive information from market and technical evaluations prompts a reassessment of the project’s viability. If approved, the project advances to the next stage.

Stage 2 (Build business case) : Positioned just before product development, this stage involves:

Assessing the project’s attractiveness.

Defining clear objectives.

Conducting market, technical, operational, and financial evaluations.

Gate 3 (Development) : A pivotal decision point where the organization determines resource allocation for project development [ 17 , 18 ].

The FEI within the stage-gate model. Source: Adapted from Cooper [ 17 ].

Pre-Phase Zero : This initial phase concentrates on the continuous identification of opportunities within the organization. It involves generating ideas and conducting technological and market analyzes. When a promising opportunity is identified, it triggers the transition to Phase Zero. The authors emphasize that this phase should occur continuously within the organization.

Phase Zero : This phase is initiated when Pre-Phase Zero identifies a promising opportunity. Its primary objective is to define the concept of a new product.

Phase One : Following the conceptualization of the new product, Phase One focuses on analyzing feasibility and planning the project to initiate the NPD process formally. It is crucial to maintain a constant interface with the organization’s product and portfolio strategy throughout the entire process.

Three Phase Front End model. Source: Khurana and Rosenthal [ 11 ].

The New Concept Development (NCD) model, proposed by Koen et al. [ 14 , 15 ], is a theoretical construction composed of the three fundamental concepts: controllable activities, “engine” and influencing factors. Controllable activities represent the elements that the organization can control. The “engine” encompasses the controllable aspects of the organization that are responsible for driving the activities of the FEI. Finally, the influencing factors are variables that have an impact on the FEI and are relatively outside of the organization’s control [ 14 , 15 ]. Table 2 details the structure of the NCD model. In the structure of the NCD model, organizational capabilities are classified as an influencing factor because they usually change very slowly and are therefore uncontrollable. Alternatively, organizational capabilities can be incorporated into the “engine” to the extent that the organization can modify and control them [ 14 ].

Structure of the NCD model.

Source: Koen et al. [ 14 ].

The model proposed by Reid and De Brentani [ 19 ] provides a unique focus on disruptive innovations, highlighting their distinct entry into the organization compared to incremental innovations. According to this model, disruptive innovations typically originate from the external environment. Figure 4 illustrates how the front end of the innovation process initiates its flow based on information from the external environment, involving the identification of unstructured problems and the recognition of opportunities. This model emphasizes that disruptive innovations follow a distinctive path, with the FEI process being strongly influenced by external inputs. The opportunities identified undergo thorough analyzes and decisions at various organizational levels before being formally integrated into an NPD project [ 19 ].

The Fuzzy Front End of new product development for discontinuous innovations. Source: Reid and De Brentani [ 19 ].

The seminal models presented – Cooper’s Stage-Gate Model, Khurana, and Rosenthal’s Three Phase Front End Model, Koen et al.’s New Concept Development (NCD) Model, and Reid and De Brentani’s Model for Discontinuous Innovations – vary in focus, approach, depth, and structuring of activities. Despite these differences, a common thread emerges as they collectively address the FEI through key activities: identification and analysis of opportunities, generation, enrichment, and screening of ideas, product concept definition, and consideration of influencing factors (encompassing the outside world, market and technology information, scenario planning, competitive analysis, and organizational issues such as culture, leadership, strategy, portfolio, and capabilities).

The ultimate objective of these FEI activities is to formulate a well-defined product concept before entering the formal NPD stage. Table 3 establishes the correspondence between FEI activities and the structures of the seminal models.

FEI activities and their relationship with the seminal models.

To mitigate potential ambiguities in the interpretation of certain terms related to the FEI, Table 4 provides standardized reference definitions. This table serves as a reference guide, providing clear and standardized definitions for key terms associated with the FEI, enhancing clarity and consistency in their interpretation.

Definitions for terms related to the FEI.

2.3 Defense sector

High technological level : The defense industry requires substantial investments in research, development, and innovation to create sophisticated products such as aircraft, ships, weapons, and systems. These must operate safely and reliably under severe conditions [ 25 ], often characterized as Complex Products and Systems (CoPS). CoPS involve customization, production in small quantities by a few companies, integration of diverse knowledge areas, and a lifecycle spanning decades [ 26 ].

Technological duality : Innovations developed for military purposes may have civilian applications (spin-off) and vice versa (spin-in) [ 27 , 28 ]. Dual-use technologies, like GPS and the Internet, initially developed for defense, now find widespread civilian applications.

Governmental dependence : The defense market is highly regulated and relies on government contracts, resulting in a strong dependence on public resources. From a demand perspective, the defense market operates as a monopsony, with the State being the primary purchaser of goods and services [ 29 , 30 , 31 ].

High market concentration : Global defense market dominance by a few companies leads to limited competition and protectionist practices. Oligopolies in the defense market can collude, manipulate prices, limit competition, or engage in practices like dumping [ 32 ] to control strategic interests [ 31 , 33 ].

Vulnerability to geopolitical issues : The demand for defense equipment is influenced by geopolitical conflicts and international relations, resulting in a volatile market subject to sudden changes. Companies may exploit geopolitical issues for financial or strategic reasons, impacting commitments during times of national crisis [ 31 , 34 ].

In summary, the defense sector is characterized by its strategic importance, technological advancement, dual-use nature, governmental dependence, market concentration, and vulnerability to geopolitical issues. This situation is a combination of a monopoly/oligopoly, where a few major global players dominate the supply, and a monopsony, where the State centralizes the demand. Recognizing these peculiarities highlights the need for a comprehensive exploration of FEI dynamics within the defense sector.

3. Methodology

Databases : Scopus and Web of Science (WoS), aligning with the methodology outlined by Ferreira et al. [ 36 ].

Search string : The search string was crafted by combining key terms related to the FEI and the defense sector. The FEI-related terms were derived from a frequency analysis of authors’ keywords, following the methodology of Ferreira et al. [ 36 ]. To capture the comprehensive scope of the defense sector, terms related to aerospace were also incorporated, acknowledging that certain countries treat both topics as a unified strategic theme. For instance, the United States has the U.S. Space Force under its Department of Defense [ 37 ]. The search was conducted on September 21, 2023, focusing on terms found in the title, abstract, and keywords:

Scopus database: TITLE-ABS-KEY((“front end of innovation” OR “front-end of innovation” OR “front end innovation” OR “front-end innovation” OR “fuzzy front end” OR “fuzzy front-end”) AND (“military” OR “defense” OR “defense” OR “navy” OR “army” OR “air force” OR “aerospace” OR “aeronautic*” OR “astronautic*” OR “avionics”)).

WoS database: TS = ((“front end of innovation” OR “front-end of innovation” OR “front end innovation” OR “front-end innovation” OR “fuzzy front end” OR “fuzzy front-end”) AND (“military” OR “defense” OR “defense” OR “navy” OR “army” OR “air force” OR “aerospace” OR “aeronautic*” OR “astronautic*” OR “avionics”)).

Inclusion criteria : publications in English, Portuguese, or Spanish were considered, and the accessibility of the entire document was taken into account. Additionally, the publication had to address explicitly the FEI in the defense context.

The academic literature search yielded five documents from the Scopus database and two from WoS. Upon analysis, one redundancy was identified, resulting in six unique documents. Subsequently, it was observed that two articles did not meet the inclusion criteria, leaving four documents within the review scope. Following this initial search, the snowball technique was applied to identify relevant documents citing or cited by the selected publications. Additional efforts were made to explore works authored by the selected publications’ authors, uncovering three more documents.

In parallel with the academic literature search, the exploration of government defense management agencies’ websites led to the identification of 17 more documents. Therefore, while the academic literature contributed documents presenting general aspects of FEI in the defense sector, the gray literature addressed defense management in specific nations, ensuring representation across continents and encompassing both developed and developing countries. The nations (or alliances) covered included Australia, Brazil, China, India, NATO (North Atlantic Treaty Organization), the United Kingdom, the United States, and South Africa.

Thus, a total of 24 documents were selected for review. It is noteworthy that, during the research, no review works similar to this article were found. The steps of the review are represented in summary in Figure 5 , using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) diagram, a tool for presenting the flow of information through the different phases of a systematic literature review [ 38 ].

Stages of the systematic literature review. Source: Adapted from Page et al. [ 38 ].

4. Front end of innovation in the defense sector

The investigation of FEI in the defense sector is structured based on content mapping of the selected review documents, focusing on key FEI activities outlined in Section 2.2. These activities include the identification and analysis of opportunities; generation, enrichment, and screening of ideas; product concept definition; and consideration of influencing factors.

4.1 Identification and analysis of opportunities

The identification and analysis of opportunities serve as the primary catalyst for the FEI process. It occurs when an organization recognizes a gap, whether related to business or technology issues. This gap represents the difference between the current state and a desired future state, presenting an opportunity that can be exploited to gain a competitive advantage, address a threat, solve a problem, or enhance a situation [ 14 ]. As stressed by Khurana and Rosenthal [ 11 ], the phase of identifying and analyzing opportunities should be an ongoing and continuous process within an organization.

In the defense sector, the identification and analysis of opportunities are intricately tied to Capability-Based Planning (CBP), a central process in strategic defense management [ 39 , 40 ]. This strategic planning paradigm, initially utilized in the United States Nuclear Program during the 1960s, saw broader adoption by the U.S. Department of Defense in 2001, becoming a reference for armed forces worldwide [ 41 ]. From this standpoint, Table 5 provides a mapping of the phase of identification and analysis of opportunities within the documents reviewed.

Approaches to identification and analysis of opportunities within the review documents.

4.2 Generation, enrichment, and screening of ideas

According to Koen et al. [ 14 ], the generation and enrichment of ideas follow the identification and analysis of opportunities. An idea, as conceptualized by the authors, represents the most preliminary form of a new product or service, typically outlining a high-level vision for the planned solution related to the identified opportunity [ 14 ]. Cooper [ 17 ], in the stage-gate model, underscores that ideas for new products must undergo initial screening, known as gate 1, before being integrated into an organization’s project [ 17 ]. Reid and De Brentani [ 19 ] also stress the importance of a formal analysis of opportunities/ideas at the corporate level before progressing to the project level [ 19 ].

In the defense sector, as outlined in Table 6 , the identification of the need for a new product occurs when a capability gap analysis indicates the necessity for a new materiel solution. This triggers the formal process of acquiring a defense product. Table 6 provides a mapping of the phase of generation, enrichment, and screening of ideas within the reviewed documents.

Approaches to idea generation, enrichment, and screening within the review documents.

4.3 Product concept definition

According to Koen et al. [ 14 ], a well-defined product concept should entail a comprehensive configuration, offering both written and visual descriptions that encapsulate the primary features, customer benefits, and a broad understanding of the required technologies. This stage in product development represents the final step preceding the formal NPD process [ 14 ]. The models proposed by Khurana and Rosenthal [ 11 ], Reid and De Brentani [ 19 ], and Cooper [ 17 ] also emphasize the significance of product concept development, feasibility analysis, project planning, and decision-making as crucial prerequisites before formally entering the NPD phase.

In the defense sector, the Armed Forces commonly adopt the systems engineering lifecycle concept to structure their acquisition processes [ 56 ]. Within this framework, the product concept undergoes development through a top-down approach, comprising two distinct phases: logical description (problem domain) and physical description (solution domain). The logical or functional description essentially outlines the intended functionalities of the new product from the user’s perspective, providing an operational view. Building upon the logical description, the physical description then defines the high-level architecture of the product elements, encompassing systems, subsystems, assemblies, and/or components, from a technical perspective [ 57 , 58 , 59 ]. Table 7 provides a mapping of the product concept definition phase within the reviewed documents.

Approaches to product concept definition within the review documents.

4.4 Consideration of influencing factors

According to Koen et al. [ 14 ], influencing factors are variables that impact FEI and are relatively outside the organization’s control. Table 8 maps the influencing factors considered in the review documents.

Influencing factors within the review documents.

5. Discussion

After presenting the review results, it is essential to delve deeper into key findings and considerations identified throughout the study.

5.1 Synthetic diagnosis of the results

Table 9 provides a condensed overview, offering a synthetic diagnosis of the results derived from the review. It succinctly outlines FEI activities in the defense sector and establishes connections with the influencing factors under consideration.

FEI activities in the defense sector.

5.2 Peculiarities of FEI in the defense sector

After systematically mapping the FEI in defense sector against established FEI models, several distinct aspects specific to the military context have emerged, as shown in Table 10 .

Peculiarities of FEI in the defense sector.

5.3 Contributions to the FEI literature

Use of systems engineering approach : The defense sector prominently employs systems engineering activities during the early phase of military innovation. This approach encompasses requirements engineering and systems lifecycle management, aspects not explicitly emphasized in traditional FEI models.

Relevance of technological duality, criticality, and maturity : Concepts such as technological duality, criticality, and maturity play a crucial role in military FEI. These factors, while not extensively covered in established FEI models, are instrumental in decision-making processes, risk mitigation, and the strategic development of defense capabilities.

Organizational capabilities as the “engine” of FEI : In contrast to seminal NPD models that classify organizational capabilities as influencing factors, the defense sector integrates organizational capabilities as a fundamental component of the FEI “engine.” Capability-based planning is a central element in identifying and analyzing opportunities, as well as in generating, enriching, and screening ideas.

“Implementation” of military innovation : The implementation of military innovation necessitates a broader interpretation compared to traditional FEI models. In defense, implementation occurs when a new or improved product is seamlessly integrated into the capability’s portfolio of an Armed Force. This integration involves adjustments in various non-technological aspects, emphasizing the symbiosis between technological and doctrinal advancement.

Continuity in project leadership : Recognizing the high turnover of military leaders and the extended durations of defense projects, the continuity of leadership emerges as a critical consideration. Seminal FEI models do not explicitly address managing leadership continuity in NPD project planning.

Moreover, it is noteworthy that recent contributions in the FEI literature have started to delve deeper into the alignment between organizational strategy and FEI activities. Unlike seminal models that treat this issue generically, recent works, such as the integrative ontologies developed by Pereira et al. [ 20 ] and Castro and Ferreira [ 72 , 73 ], provide management artifacts designed to align organizational strategic vision with FEI activities. Employing the design science paradigm, these artifacts integrate constructs, models, methods, and instantiations, thereby enriching the strategic dimension of FEI literature.

5.4 Contributions to the defense literature

The defense sector, encompassing products ranging from CoPS to mass-produced items, presents a unique challenge due to its diverse complexity and production volume [ 74 ]. While the CoPS research area has an established connection with systems engineering literature, the realm of mass-produced products aligns more closely with the theoretical foundations of the FEI literature. Notably, defense documents predominantly draw from the CoPS approach, sparingly incorporating principles from mass production. However, recognizing that the military context spans both worlds, the integration of these approaches becomes crucial, and mapping established FEI models within the dynamics of the initial phase of the military innovation process serves as a valuable step in achieving this harmonization.

Moreover, the FEI literature, characterized by well-defined seminal models and recent integrative ontologies (as discussed in the previous section), contrasts with the more heterogeneous nature of the systems engineering literature. The latter encompasses diverse authors, countries, organizations, and standardization bodies, each adhering to distinct management models with unique nomenclatures and structures [ 43 , 44 , 45 , 47 , 48 , 54 , 55 , 57 , 58 , 59 ]. In this context, the FEI literature emerges as a unifying force, facilitating the creation of a common representation of knowledge related to the early stage of the military innovation process. This not only streamlines communication among specialists, decision-makers, managers, researchers, entrepreneurs, and other stakeholders in the defense field but also promotes greater efficiency in navigating the diverse landscape of defense innovation.

5.5 Limitations

Selection of seminal FEI models : The identification of seminal FEI models relied on findings from Pereira et al. [ 12 , 20 ] and co-citation analysis of FEI-related works available in the Scopus and WoS databases. Alternative criteria for model selection might yield a different set of seminal documents, potentially influencing the analysis.

Data collection in gray literature : The exploration of gray literature related to FEI in the military sector was constrained by the availability of documents on government websites of defense management agencies. This limitation could result in an incomplete representation of the landscape.

Scope of mapping : The review presented an initial mapping of FEI in the defense sector within seminal models. A more comprehensive and structured mapping could be achieved through the adoption of more robust methodological approaches, such as the design science paradigm [ 75 , 76 ]. This suggests that there is potential for a more in-depth and detailed examination of FEI activities in the defense sector.

Acknowledging these limitations is essential for a nuanced understanding of the scope and implications of the study, guiding future research endeavors in this domain.

6. Conclusion

This study aimed to comprehensively explore the dynamics of FEI in the defense sector through a systematic review encompassing 24 documents from both academic and gray literature. By analyzing seminal FEI models, the research mapped key activities within the defense context, including the identification and analysis of opportunities, generation, enrichment, and screening of ideas, product concept definition, and consideration of influencing factors.

The study’s contributions extend to both FEI and defense literature, introducing original perspectives. Notably, it emphasized the systems engineering approach, national strategic focus, technological duality, technological criticality, technological maturity, organizational capabilities as the “engine”, the unique concept of “implementation” in military innovation, and the importance of continuity in project leadership.

Acknowledging limitations, such as the criteria for selecting seminal FEI models, constraints in accessing gray literature, and the preliminary nature of the mapping, the study calls for future research to employ more robust methodologies, like the design science paradigm [ 75 , 76 ], for an in-depth understanding of the initial phase of the military innovation process.

In conclusion, this research lays a foundation for further exploration and synthesis of knowledge, contributing to the advancement of both FEI theory and its application in the defense sector.

Acknowledgments

This work was supported by the Brazilian Army (Atv PCENA V23-011).

We thank Dr. João José Pinto Ferreira (INESC TEC and Faculty of Engineering, University of Porto) for his expertise and help in writing the manuscript.

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• Volume 14, Issue 9
• Identifying markers of health-seeking behaviour and healthcare access in UK electronic health records
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• http://orcid.org/0000-0002-7770-1863 Sophie Graham 1 ,
• Jemma L Walker 2 , 3 ,
• Nick Andrews 3 ,
• Dorothea Nitsch 1 , 4 , 5 ,
• Edward P K Parker 1 ,
• Helen McDonald 6
• 1 London School of Hygiene & Tropical Medicine Faculty of Epidemiology and Public Health , London , UK
• 2 Faculty of Epidemiology and Population Health , London School of Hygiene and Tropical Medicine , London , UK
• 3 UK Health Security Agency , London , UK
• 4 UK Renal Registry , Bristol , UK
• 5 Renal Unit, Royal Free London NHS Foundation Trust , Hertfordshire , UK
• 6 University of Bath , Bath , UK
• Correspondence to Sophie Graham; sophie.graham{at}lshtm.ac.uk

Objective To assess the feasibility of identifying markers of health-seeking behaviour and healthcare access in UK electronic health records (EHR), for identifying populations at risk of poor health outcomes and adjusting for confounding in epidemiological studies.

Design Cross-sectional observational study using the Clinical Practice Research Datalink Aurum prelinked to Hospital Episode Statistics.

Setting Individual-level routine clinical data from 13 million patients across general practices (GPs) and secondary data in England.

Participants Individuals aged ≥66 years on 1 September 2019.

Main outcome measures We used the Theory of Planned Behaviour (TPB) model and the literature to iteratively develop criteria for markers selection. Based on this we selected 15 markers: those that represented uptake of public health interventions, markers of active healthcare access/use and markers of lack of access/underuse. We calculated the prevalence of each marker using relevant lookback periods prior to the index date (1 September 2019) and compared with national estimates. We assessed the correlation coefficients (phi) between markers with inferred hierarchical clustering.

Results We included 1 991 284 individuals (mean age: 75.9 and 54.0% women). The prevalence of markers ranged from <0.1% (low-value prescriptions) to 92.6% (GP visits), and most were in line with national estimates; for example, 73.3% for influenza vaccination in the 2018/2019 season, compared with 72.4% in national estimates. Screening markers, for example, abdominal aortic aneurysm screening were under-recorded even in age-eligible groups (54.3% in 65–69 years old vs 76.1% in national estimates in men). Overall, marker correlations were low (<0.5) and clustered into groups according to underlying determinants from the TPB model.

Conclusion Overall, markers of health-seeking behaviour and healthcare access can be identified in UK EHRs. The generally low correlations between different markers of health-seeking behaviour and healthcare access suggest a range of variables are needed to capture different determinants of healthcare use.

• primary health care
• vaccination
• epidemiologic studies
• health services

Data availability statement

Data may be obtained from a third party and are not publicly available. These data were obtained from the Clinical Practice Research Datalink, provided by the UK Medicines and Healthcare products Regulatory Agency. The authors’ licence for using these data does not allow sharing of raw data with third parties. Information about access to Clinical Practice Research Datalink data is available here: https://www.cprd.com/research-applications . Code lists for this study are available at https://doi.org/10.17037/DATA.00003684 and code at https://github.com/grahams99/Health-seeking-behaviour .

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See:  https://creativecommons.org/licenses/by/4.0/ .

https://doi.org/10.1136/bmjopen-2023-081781

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Strengths and limitations of this study

This is the first known study in the UK that has identified proxies or markers of health-seeking behaviour or healthcare access.

We used linked electronic health records from primary and secondary care so that a range of different health utilisation markers could be identified.

We identified a large population of over 2 million individuals.

For some of the markers (eg, bone density scans), health need could not be entirely separated from health behaviour and access.

Marker prevalences showed different patterns by age, and these findings might not be generalisable to younger age groups (<65 years).

Health-seeking behaviour can be defined as ‘any activity undertaken by a person believing [themselves] to be healthy, for the purpose of preventing disease or detecting it in an asymptomatic stage’. 1 Healthcare access can be defined as ‘the ability to obtain healthcare services such as prevention, diagnosis, treatment, and management of diseases, illness, disorders, and other health-impacting conditions’. 2 Healthcare professionals or researchers might be interested in identifying patients with a lack of health-seeking behaviour or healthcare access, since these individuals are likely to suffer from worse clinical outcomes. Health-seeking behaviour and healthcare access may also be a key confounder in observational studies, and failure to account for this may undermine the validity of results. This type of confounding is thought to have contributed to overestimates of the protective effect of influenza vaccinations against all-cause mortality in observational cohort studies. 3 Information on health-seeking behaviour and healthcare access can be collected prospectively through surveys or interviews; for example, in the English Longitudinal Study of Ageing study. 4 Typically, in routinely-recorded data such as electronic health records (EHRs) it is difficult to identify health-seeking behaviour and healthcare access since they are not directly recorded. Suitable markers would need to represent interactions with the healthcare system (ie, healthcare utilisation), preferably with limited dependence on underlying health needs. Behavioural scientists have a variety of models for explaining the determinants for healthcare utilisation. For example, the updated Theory of Planned Behaviour (TPB) model 5 describes the psychological, physical, contextual and socio-demographic determinants for healthcare utilisation. Psychological determinants include influences on the micro and macro level such as societal attitudes, but also personal prior experiences. Physical determinants are on the micro-level and include lifestyle factors such as drug consumption, body mass index and physical activity. Context determinants are on the macro-level and include potential external barriers such as recommendations from healthcare professionals or geopolitical influences. Socio-demographic determinants are on the micro-level and include individual characteristics such as sex, age and living arrangements. These models demonstrate that there are a range of different determinants and therefore many different markers are likely required to capture all the underlying influences.

Three recent studies in the USA 6–8 introduced adjusting for markers of health-seeking behaviour and healthcare access in observational research. However, it is not known to what extent suitable markers can be identified in UK EHR. This study aimed to identify markers of health-seeking behaviour and healthcare access in UK EHRs, compare their prevalence to available national estimates and explore correlations between different markers. This study will focus on individuals aged over 65 years as health-seeking behaviour and healthcare access vary by age 9 and because they have high morbidity and mortality. 10

Data sources, study design and population

We used the Clinical Practice Research Datalink (CPRD) Aurum prelinked to Hospital Episode Statistics (HES) admitted patient care (APC). For more information on this data source, see table 1 .

• View inline

Description of the CPRD Aurum-HES APC data sources

This was a cross-sectional study design that included a study population of individuals in England aged 66 years or older on 1 September 2019 identified in the CPRD-HES data. 1 September 2019 was selected as the index date for all individuals. We only included individuals with a general practice (GP) registration start date before 1 September 2018 to allow for a minimum 1-year pre-index period for marker identification.

Marker selection

We used the TPB model to define our aim of identifying healthcare utilisation driven by determinants other than physical and mental health. We selected candidate markers available within the CPRD Aurum-HES data using our own formal criteria (see table 2 ). The criteria were developed with input from two clinical epidemiologists on UK clinical practice and data recording (DN and HIM). Candidate markers from the aforementioned US studies 6–8 were tested against our developed criteria to iteratively make improvements to the criteria and to identify additional potential markers. Candidate markers that failed to meet our prespecified criteria included interactions linked with underlying health needs (eg, for cardiovascular disease screening, depression screening, hospital visits) and programmes not available to all individuals (eg, Shingrix vaccination; see online supplemental table 1 for a full list of excluded markers). We selected 15 markers that included abdominal aortic aneurysm (AAA) screening; breast cancer screening; bowel cancer screening; cervical cancer screening; influenza vaccination; pneumococcal vaccination; National Health Service (NHS) health checks; prostate-specific antigen (PSA) testing; bone density scans; low-value procedures; glucosamine use (low-value prescription); GP visits; did not attend (DNA) primary care visit; hospital visit for ambulatory care sensitive (ACS) condition; and blood pressure measurements. In general, the criteria were a good fit for the markers, but there was some tolerance for minor deviations, particularly for accepting some influence of underlying health conditions ( online supplemental table 2 ).

Supplemental material

Criteria used to assess inclusion of markers of health-seeking behaviour and healthcare access

Some markers represented active health-seeking behaviour and healthcare access, such as the uptake of recommended vaccinations. Other markers represented a lack of health-seeking behaviour and healthcare access—such as DNA for primary care visits, and hospital visits for ACS conditions. ACS conditions are conditions for which effective community care can help prevent the need for hospital admission. 11 If an individual has a visit to the hospital for an ACS condition, then this could signify either barriers to healthcare access on the macro level (eg, inundated GP), barriers on the individual level (eg, language barriers) or a lack of health-seeking behaviour. Low-value procedures and low-value prescriptions are those that the National Institutes of Health and Care Excellence recommended to no longer provide in UK clinical practice since they were deemed to have little or no benefit, while still incurring an avoidable cost. 12 13 We considered both to be indicators of active health-seeking behaviour or healthcare access from a patient perspective, as patients were receiving (non-recommended) care for their perceived needs.

Marker operational definitions

The operational definition of each marker includes code lists (sets of diagnostic or prescription codes that represent a given clinical concept 14 ) and lookback periods to apply in the current study data sets ( table 3 ).

Use of markers in UK clinical practice and operational definitions

For code lists, existing validated code lists were used where possible. Primarily we searched for code lists that were incentivised for national use through the Quality and Outcomes Framework 15 or those that were validated through research. If code lists were not available using these sources, then they were developed using keyword searches (based on Medical Subject Headings terms with corresponding synonyms). Where possible the code lists aimed to be as specific as possible (‘narrow code lists’) and therefore codes were excluded if they were not clearly relevant. For example, for most screening markers we required the code to specify ‘screen’ or ‘screening’ but for bowel cancer, we also allowed Faecal Immunochemical Tests (FIT) as these were in routine use in the national screening programme during the study period, but were not a first choice for symptomatic testing at the time. 16 17 As a sensitivity analysis, for AAA, breast cancer and cervical cancer screening, since the same procedure may be recorded for a screening test as for diagnostic tests investigating symptoms, we also included a broader code list that included codes that specified the relevant procedure, but did not specify ‘screen’ or ‘screening’. Full inclusion and exclusion list were reviewed by a clinical epidemiologist (HIM) and differences were agreed upon discussion and third-party review (EPKP). The search terms that were used to create the code lists and the code lists that were used can be found on the LSHTM data compass ( https://doi.org/10.17037/DATA.00003684 ).

The lookback periods for each marker were developed by first identifying how each of these markers are recommended for use in current UK clinical practice. For markers that are available to all at any time, the lookback period reflected the expected frequency of healthcare use in UK clinical practice. For example, for markers that were expected to be frequently recorded (eg, blood pressure measurements) we used a 1-year lookback. For markers that were expected to be less frequently recorded (eg, hospital visit for ACS conditions) a 5-year lookback was used. For markers with an upper age limit of eligibility (ie, screening and NHS health checks), we ensured the lookback period reflected the timely administration of these markers (since we were interested in capturing strong evidence of health-seeking behaviour and healthcare access). For example, breast cancer screening is offered to women every 3 years aged 50–71 years 18 and therefore the lookback period covered the last 4 years of age-eligibility (3 years plus an additional year for the uncertainty of age as the only year of birth is recorded in CPRD) for breast cancer screening, until the index date. We included all follow-up time until the index date to allow for delayed recording due to the transition to electronic records among older individuals. As a sensitivity analysis, since we were concerned that including years after the upper age of eligibility might have meant we included more symptomatic individuals rather than healthy individuals accessing screening programmes, we also employed a restricted lookback that stopped the look back at the upper age of eligibility (see online supplemental figure 1 ).

Prevalence estimates

For prevalence calculations, the denominator was all individuals aged ≥66 years on 1 September 2019 and the numerator was ≥1 occurrence of the marker in the relevant lookback period. We also calculated prevalence stratified by sex (given the inclusion of several sex-specific markers) and age in 5-year bands (65–69, 70–74, 75–79, 80–84, 85–89, 90–95 and 95+ years).

We compared prevalence estimates to national estimates from PHE fingertips or from published literature, preferentially selecting for recent estimates from the UK in the relevant age group. The prevalence estimates from these sources can be found in table 4 and sources are detailed in online supplemental table 4 .

Prevalence of markers

Correlations

The correlation of all the markers within the population sample was assessed using a phi correlation matrix. The phi coefficient is designed to measure the association between binary variables, and is equivalent to a Pearson correlation when applied to binary data. It ranges from −1 to 1, where 0 signifies no relationship between the variables, 1 is a perfect positive relationship and −1 is a perfect negative relationship. 19 Variables were ordered via complete linkage hierarchical clustering which was visualised by adorning dendrograms onto the correlation matrices (heatmaply_cor in R).

The clustering of markers was compared with a theoretical grouping using the updated TPB model. 5 The theoretical grouping was based on the underlying determinants from the updated TPB model ( table 4 ). Specifically, we grouped markers into four groups: those with strong psychological influences (‘psychologically determined’; eg, vaccinations), those with strong contextual influences (‘contextually determined’; eg, screening and NHS health checks) and those fully or partially dependent on physical need. Physically determined markers were further separated into those likely to represent lack of health-seeking behaviour or healthcare access (eg, DNA primary care visit and ACS condition hospital visit; ‘physically determined with lack of access’) and those likely to represent active health-seeking behaviour or straightforward healthcare access (‘physically determined with active access’).

All programming was conducted using R (V.4.2.1–4.2.3) and the programming code can be found on GitHub ( https://github.com/grahams99/Health-seeking-behaviour ).

Patient and public involvement

No patient or public involvement in the study as anonymised patient data set was used in the analysis.

Overall, 1 991 284 individuals were included (54.0% women, mean (SD) age: 75.9 (7.4); online supplemental table 5 ).

The prevalence of markers in the overall population ranged from <0.1% for low-value prescriptions to 92.6% for GP visits. The proportion with at least one GP visit was so high that we conducted a post-hoc analysis that revealed the median (IQR) number of GP visits was 7 (4–11) with some patients having over 25 visits per year ( online supplemental figure 2 ). The prevalence of markers was similar between men and women, except for sex-specific markers ( table 4 ). For screening and NHS health checks, broad code lists with standard lookback periods had the highest prevalence, whereas narrow code list with restrictive lookback had the lowest. For AAA screening and NHS health checks, changing the operational definition changed the prevalence <2% ( online supplemental table 6 ). The prevalence of most markers was in line with national estimates, particularly for the vaccinations, PSA testing and bone density scans. For example, 73.3% of individuals in the current study had an influenza vaccination with national estimates reporting 72.4% influenza vaccination uptake among ≥65 years old in the 2019/2020 influenza vaccination season. 20 The prevalence of screening and NHS health checks in the overall population was lower than national estimates, although this generally improved in comparison to currently eligible age-groups ( figure 1 ). Hospital visit for an ACS condition were higher than literature estimates as it was not possible to differentiate planned and unplanned hospitalisations in the current data sets (9.5% in the current study vs 0.1% in literature).

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Prevalence of markers, stratified by age category. Note: the numbers and proportions for these bar charts can be found in online supplemental table 7 . AAA, abdominal aortic aneurysm; ACS, ambulatory care sensitive; DNA, do not attend; GP, general practice; NHS, National Health Service; PSA, prostate-specific antigen.

The prevalence of markers typically varied by age category, with a number of patterns evident ( figure 1 ). The recorded prevalence of markers with upper age eligibility (screening and NHS health checks) decreased with age (eg, 28.0% in 65–69 years old vs 1.5% in 85–89 years old for NHS health checks), whereas the prevalence of ACS conditions, blood pressure measurements and vaccinations rose with age (eg, 62.9% in 65–69 years old vs 80.5% in 85–89 years old for influenza vaccination). Although more common in younger age groups, screening marker prevalence still fell short of national estimates in currently eligible age-groups (eg, 54.3% in 65–69 years old vs 76.1% in national estimates for AAA screening in men). PSA tests, bone density scans, low-value procedures, low-value prescriptions and DNA primary care visits peaked at 75–89 years, with lower prevalence in younger and older individuals. GP visits were consistent across age categories. As expected, the proportion of individuals with ≥1 GP visit was very high. The post-hoc analysis revealed the number of GP visits increased by age category until the last age strata (90+ years), when it decreased slightly ( online supplemental figure 3 ).

Using broad rather than narrow code lists, the estimated prevalences were similar for AAA screening across all age strata and for breast cancer screening in those aged 65–69 years. For all other breast cancer screening strata and for cervical cancer screening, broad code lists resulted in a higher prevalence than narrow. For standard versus restricted lookback periods, the prevalence was the same for individuals entering the cohort below the upper age of eligibility of that marker, whereas after this point there was a lower prevalence in the restricted versus standard age strata.

In the overall study population, unsurprisingly, GP visits were strongly correlated with blood pressure measurements (phi φ 0.42) and influenza vaccination (0.33). Blood pressure measurements were also strongly correlated with influenza vaccination (0.23). Markers with the strongest negative correlation were blood pressure measurements and NHS health checks (−0.14) ( figure 2 ). Among men, GP visits and blood pressure measurements had the strongest positive correlation (0.45), followed by influenza and pneumococcal vaccinations (0.42). Other strong correlations included GP visits and pneumococcal vaccination (0.36) and blood pressure measurements and influenza vaccination (0.25) ( figure 2 ). Among women, GP visits were also strongly correlated with blood pressure measurements (0.40) and blood pressure measurements with influenza vaccination (0.30). There were also strong correlations between pneumococcal vaccination with influenza vaccination (0.39), bowel cancer screening and NHS health checks (0.23) ( figure 2 ).

Correlation matrix plots. The correlations are calculated using phi coefficient for binary variables. The clustering is visualised through the adorned dendrograms which are ordered via complete linkage hierarchical clustering. The size and the shading of the bubble represent the strength of the correlation. Note: the correlation coefficients for these plots can be found in online supplemental tables 8–10 . AAA, abdominal aortic aneurysm; ACS, ambulatory care sensitive; DNA, did not attend; GP, general practice; NHS, National Health Service; TPB, Theory of Planned Behaviour.

Markers that were clustered together in the correlation matrices were: (1) blood pressure measurements, GP visits and influenza and pneumococcal vaccinations; (2) NHS health checks and bowel, cervical, breast cancer and AAA screening; and (3) ACS conditions, primary care DNA, bone density scans and low-value procedures. Markers from group 2 generally had a weak negative correlation with markers from group 3. When comparing these data-driven clusters with the theoretical grouping of markers there were some similarities. In both methods the ‘contextually determined’ (ie, NHS health checks and screenings) were grouped together as well as the ‘physically determined with a lack of healthcare access’ (ie, ACS conditions and primary care DNA). On the other hand, GP visits and blood pressure measurements were grouped with ‘psychologically determined’ markers in the data-driven approach, but with the ‘physically determined with active healthcare access’ in the theoretical grouping.

A statement of the principal findings

Overall, this study found that it is feasible to identify markers of health-seeking behaviour and healthcare access in UK EHRs. The prevalence of these markers ranged significantly and were generally in line with national estimates. Screening and NHS health checks were under-recorded in the EHR data, although prevalence was closer to national estimates among younger age groups that were currently eligible for these programmes. The prevalence and pattern of markers differed by age, with AAA screening declining with older age and hospital visits for ACS condition increasing. Correlations between markers revealed clusters that aligned well with theoretical groupings informed by the updated TPB model based on psychological, contextual and physical underlying determinants.

Strengths and weaknesses of the study

To our knowledge, this is the first study that has systematically identified proxies or markers of health-seeking behaviour or healthcare access using routinely collected data in the UK. Previous studies have adjusted for variables that may reflect confounding by health-seeking behaviour such as GP consultations, but without an explicit framework for selecting these. Our study demonstrates that a framework is beneficial since health-seeking behaviour and healthcare access are complex phenomena with multiple determinants, which may behave differently and vary by age and sex. Due to the number of different determinants that influence healthcare utilisation according to the updated TPB model, markers cannot solely be thought to solely represent either health-seeking behaviour or healthcare access. Linkage across primary and secondary care also strengthened this study as different types of healthcare utilisation with different underlying determinants could be captured. We included a large and representative cohort of over 2 million individuals aged 66 years and over in England. For some of the markers, older individuals might not have been historically eligible for services, which represents an important caveat during the interpretation of prevalence estimates. We accounted for this by calculating age-stratified prevalence, but for some of the prevalence comparisons the numerator and denominator populations need to be considered. For example, for NHS health checks the national estimate is of eligible individuals only (ie, those without pre-existing conditions 21 ), whereas our denominator included all individuals aged ≥66 years in English.

The study also only measured markers of health-seeking behaviour and healthcare access at a single point in time: these characteristics are not static, and individual behaviour and service accessibility can change over time. In addition, for some of the identified markers the influence of health needs could not be entirely separated from health-seeking behaviour and healthcare access and therefore in some cases prevalence would be driven to some extent by health needs. These findings might also not be generalisable to younger individuals where perhaps there are other contextual determinants to consider (eg, occupation). 9

Strengths and weaknesses in relation to other studies/discussing important differences in results

Previous studies that have used EHR to identify markers of health-seeking behaviour and healthcare access in the USA 6–8 are in a considerably different context from the UK in terms of health services provided (eg, screening programmes might differ), the healthcare system, claims-based recording systems and underlying determinants of health. This is likely to explain the different prevalence of markers identified in the current study. For example, the prevalence of pneumococcal vaccination was only around 11.4% in a study of ≥65 years old identified in the Medicare database with an influenza vaccination during the 2019/2020 season, 7 whereas the prevalence was 62.4% in the current study. Screening coverage differs significantly between countries, for example, a global repository for breast, cervical and colorectal screening programmes reported that breast cancer screening coverage ranged from 1.7% in Bangladesh to 85.5% in the UK. For cervical cancer, coverage ranged from 2.1% in Côte d’Ivoire to 86.3% in Sweden and for colorectal cancer coverage ranged from 0.6% in Hungary to 64.5% in the Netherlands. 22 Some countries might not even offer these preventative measures as free healthcare services or may offer them at different time points. In addition, within countries, some markers might change in how they adhere to the developed criteria over time or in different settings. For example, in the UK NICE guidance has recommended FIT tests for symptomatic testing since 2022. 17 These differences support the importance of context-specific markers of health-seeking behaviour and healthcare access.

Our study adds to a growing body of literature highlighting the potential to capture proxies of healthcare access and health-seeking behaviour. In prior studies in the USA, these proxies were included as confounders during the estimation of vaccine effectiveness and they could play a similar role during observational studies in a UK context. 7

The meaning of the study: possible explanations and implications for researchers, clinicians and policymakers

The correlations between markers in the data are likely dictated by co-occurrence of these healthcare interactions (eg, blood pressure measurements might be taken when influenza vaccinations are administered) or influenced by individual patient characteristics (eg, age, underlying health conditions). Positive correlations (eg, the high positive correlation between AAA screening and bowel cancer screening) is likely because the prevalence of both these markers are highest among 65–69 years old with declining prevalence with age ( figure 1 ). Negative correlations (eg, the high negative correlation between NHS health checks and influenza vaccinations) are likely due to underlying health conditions. For example, NHS health checks are offered to those without a list of pre-existing conditions, 21 whereas the majority of the same conditions would qualify an individual for influenza vaccination prioritisation. 23 This aligns with expectations according to the updated TPB model. 5

Based on the findings presented here, we propose several recommendations and considerations for researchers that wish to identify health-seeking behaviour and healthcare access in EHRs—whether to study healthcare use directly, or to quantify or adjust for confounding.

First, a range of different markers are required to fully represent both active health-seeking behaviour and healthcare access, or lack of these. Since health-seeking behaviour/healthcare access is such a complex phenomenon, it may be useful to include markers with different underlying determinants from the updated TPB model (psychologically, contextually and physically determined). If multiple markers are available, they can be included as separate confounders in multivariate models, or researchers may wish to consider tools such as high-dimensional propensity scores to guide study-specific confounder identification, prioritisation and adjustment. 24

Second, the optimal code lists will depend on the precise research question. Narrow code lists (eg, using government incentivised code lists) can identify markers of health-seeking behaviour and healthcare access with high specificity. Broader code lists will capture more events, but may be more influenced by underlying health needs. For markers with specific age-eligibility (eg, screening or NHS health checks) look-back periods that restrict to time periods when individuals were age eligible improved specificity. However, more relaxed lookback periods might be preferred if there are expected to be artefacts in data recording such as transfer of historical information to EHRs.

Third, prior to adjusting for health-seeking behaviour and healthcare access, interactions by age, sex and underlying health conditions should be considered. Markers that were recently introduced into clinical practice (eg, AAA screening was introduced in the UK in 2013 25 ) will likely decrease in prevalence with increasing age and can be supplemented with markers that increase with increasing age (eg, ACS conditions). Otherwise, markers with relatively consistent prevalence across age strata are available (eg, GP visits or blood pressure measurements). If markers that are restricted to specific sex (eg, breast cancer screening) are used then these can be supplemented with markers of the opposite sex (eg, AAA screening). For markers where there is some partial influence of underlying health conditions (eg, pneumococcal vaccinations recommended to all but may be more highly prioritised among those with high-risk conditions) can be supplemented with markers that are administered to those that are healthier (eg, NHS health checks).

Unanswered questions and future research

Future researchers who are concerned with potential confounding from health-seeking behaviour and healthcare access in their study can use these markers to quantify and adjust for confounding. Where possible, a range of markers with different underlying determinants from the updated TPB model should be used and possible interactions by age, sex and underlying condition should be considered. Future research may identify key confounders within each theoretical group or cluster that are sufficient for confounding adjustment, although these are likely to be study-specific.

Common data models across data sets could increase the efficiency and comparability of research investigating or adjusting for health-seeking behaviour and healthcare access, but future research is needed to identify suitable markers in alternative data sets and establish comparability. Additional markers may be identified in alternative data sets using the developed criteria.

Overall, markers of health-seeking behaviour and healthcare access can be identified in UK EHR, with prevalence estimates in line with national estimates. National screening programme estimates still fell short of national estimates even when restricting to currently eligible age groups. The generally low correlations between different proxy markers of health-seeking behaviour and healthcare access, and different age-profiles of markers, suggest a range of variables are needed to capture different determinants of healthcare use.

Ethics statements

Patient consent for publication.

Not applicable.

Ethics approval

The protocol for the study received scientific and ethical approval from the CPRD Research Data Governance committee (#22_002202). All patient data is anonymised before being released to researchers and therefore patient consent is not required. Patients that do not wish to provide their data to CPRD for research purposes can opt out of the system.

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EPKP and HM contributed equally.

Contributors Study concepts: SG, NA, JLW and HM. Study design: All authors. Data acquisition: SG. Programming: SG, EPKP and HM. Statistical analysis: SG. Supervision: EPKP, NA, JLW and HM. Interpretation of results: All authors. Manuscript preparation: SG. Manuscript editing: All authors. Manuscript review: All authors. Manuscript approval: All authors. The guarantor of the study is SG who accepts full responsibility for the finished work and the conduct of the study, had access to the data and controlled the decision to publish.

Funding SG, EPKP, NA, JLW and HIM are funded by the National Institute of Health and Care Research (NIHR) Health Protection Research Unit in Vaccines and Immunisation (grant reference: NIHR200929), a partnership between UK Health Security Agency (UKHSA) and London School of Hygiene and Tropical Medicine. The views expressed are those of the author(s) and not necessarily those of the NIHR, UKHSA or the Department of Health and Social Care.

Disclaimer The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or UKHSA.

Competing interests SG is also a part-time salaried employee of Evidera, which is a business unit of Pharmaceutical Product Development (PPD), part of Thermo Fisher Scientific.

Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Provenance and peer review Not commissioned; externally peer reviewed.

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