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Writing a Comparative Case Study: Effective Guide

Table of Contents

As a researcher or student, you may be required to write a comparative case study at some point in your academic journey. A comparative study is an analysis of two or more cases. Where the aim is to compare and contrast them based on specific criteria. We created this guide to help you understand how to write a comparative case study . This article will discuss what a comparative study is, the elements of a comparative study, and how to write an effective one. We also include samples to help you get started.

What is a Comparative Case Study?

A comparative study is a research method that involves comparing two or more cases to analyze their similarities and differences . These cases can be individuals, organizations, events, or any other unit of analysis. A comparative study aims to gain a deeper understanding of the subject matter by exploring the differences and similarities between the cases.

Elements of a Comparative Study

Before diving into the writing process, it’s essential to understand the key elements that make up a comparative study. These elements include:

  • Research Question : This is the central question the study seeks to answer. It should be specific and clear, and the basis of the comparison.
  • Cases : The cases being compared should be chosen based on their significance to the research question. They should also be similar in some ways to facilitate comparison.
  • Data Collection : Data collection should be comprehensive and systematic. Data collected can be qualitative, quantitative, or both.
  • Analysis : The analysis should be based on the research question and collected data. The data should be analyzed for similarities and differences between the cases.
  • Conclusion : The conclusion should summarize the findings and answer the research question. It should also provide recommendations for future research.

How to Write a Comparative Study

Now that we have established the elements of a comparative study, let’s dive into the writing process. Here is a detailed approach on how to write a comparative study:

Choose a Topic

The first step in writing a comparative study is to choose a topic relevant to your field of study. It should be a topic that you are familiar with and interested in.

Define the Research Question

Once you have chosen a topic, define your research question. The research question should be specific and clear.

Choose Cases

The next step is to choose the cases you will compare. The cases should be relevant to your research question and have similarities to facilitate comparison.

Collect Data

Collect data on each case using qualitative, quantitative, or both methods. The data collected should be comprehensive and systematic.

Analyze Data

Analyze the data collected for each case. Look for similarities and differences between the cases. The analysis should be based on the research question.

Write the Introduction

The introduction should provide background information on the topic and state the research question.

Write the Literature Review

The literature review should give a summary of the research that has been conducted on the topic.

Write the Methodology

The methodology should describe the data collection and analysis methods used.

Present Findings

Present the findings of the analysis. The results should be organized based on the research question.

Conclusion and Recommendations

Summarize the findings and answer the research question. Provide recommendations for future research.

Sample of Comparative Case Study

To provide a better understanding of how to write a comparative study , here is an example: Comparative Study of Two Leading Airlines: ABC and XYZ

Introduction

The airline industry is highly competitive, with companies constantly seeking new ways to improve customer experiences and increase profits. ABC and XYZ are two of the world’s leading airlines, each with a distinct approach to business. This comparative case study will examine the similarities and differences between the two airlines. And provide insights into what works well in the airline industry.

Research Questions

What are the similarities and differences between ABC and XYZ regarding their approach to business, customer experience, and profitability?

Data Collection and Analysis

To collect data for this comparative study, we will use a combination of primary and secondary sources. Primary sources will include interviews with customers and employees of both airlines, while secondary sources will include financial reports, marketing materials, and industry research. After collecting the data, we will use a systematic and comprehensive approach to data analysis. We will use a framework to compare and contrast the data, looking for similarities and differences between the two airlines. We will then organize the data into categories: customer experience, revenue streams, and operational efficiency.

After analyzing the data, we found several similarities and differences between ABC and XYZ. Similarities Both airlines offer a high level of customer service, with attentive flight attendants, comfortable seating, and in-flight entertainment. They also strongly focus on safety, with rigorous training and maintenance protocols in place. Differences ABC has a reputation for luxury, with features such as private suites and shower spas in first class. On the other hand, XYZ has a reputation for reliability and efficiency, with a strong emphasis on on-time departures and arrivals. In terms of revenue streams, ABC derives a significant portion of its revenue from international travel. At the same time, XYZ has a more diverse revenue stream, focusing on domestic and international travel. ABC also has a more centralized management structure, with decision-making authority concentrated at the top. On the other hand, XYZ has a more decentralized management structure, with decision-making authority distributed throughout the organization.

This comparative case study provides valuable insights into the airline industry and the approaches taken by two leading airlines, ABC and Delta. By comparing and contrasting the two airlines, we can see the strengths and weaknesses of each method. And identify potential strategies for improving the airline industry as a whole. Ultimately, this study shows that there is no one-size-fits-all approach to doing business in the airline industry. And that success depends on a combination of factors, including customer experience, operational efficiency, and revenue streams.

Wrapping Up

A comparative study is an effective research method for analyzing case similarities and differences. Writing a comparative study can be daunting, but proper planning and organization can be an effective research method. Define your research question, choose relevant cases, collect and analyze comprehensive data, and present the findings. The steps detailed in this blog post will help you create a compelling comparative study that provides valuable insights into your research topic . Remember to stay focused on your research question. And use the data collected to provide a clear and concise analysis of the cases being compared.

Writing a Comparative Case Study: Effective Guide

Abir Ghenaiet

Abir is a data analyst and researcher. Among her interests are artificial intelligence, machine learning, and natural language processing. As a humanitarian and educator, she actively supports women in tech and promotes diversity.

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2.3: Case Selection (Or, How to Use Cases in Your Comparative Analysis)

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  • Page ID 135832

  • Dino Bozonelos, Julia Wendt, Charlotte Lee, Jessica Scarffe, Masahiro Omae, Josh Franco, Byran Martin, & Stefan Veldhuis
  • Victor Valley College, Berkeley City College, Allan Hancock College, San Diego City College, Cuyamaca College, Houston Community College, and Long Beach City College via ASCCC Open Educational Resources Initiative (OERI)

Learning Objectives

By the end of this section, you will be able to:

  • Discuss the importance of case selection in case studies.
  • Consider the implications of poor case selection.

Introduction

Case selection is an important part of any research design. Deciding how many cases, and which cases, to include, will clearly help determine the outcome of our results. If we decide to select a high number of cases, we often say that we are conducting large-N research. Large-N research is when the number of observations or cases is large enough where we would need mathematical, usually statistical, techniques to discover and interpret any correlations or causations. In order for a large-N analysis to yield any relevant findings, a number of conventions need to be observed. First, the sample needs to be representative of the studied population. Thus, if we wanted to understand the long-term effects of COVID, we would need to know the approximate details of those who contracted the virus. Once we know the parameters of the population, we can then determine a sample that represents the larger population. For example, women make up 55% of all long-term COVID survivors. Thus, any sample we generate needs to be at least 55% women.

Second, some kind of randomization technique needs to be involved in large-N research. So not only must your sample be representative, it must also randomly select people within that sample. In other words, we must have a large selection of people that fit within the population criteria, and then randomly select from those pools. Randomization would help to reduce bias in the study. Also, when cases (people with long-term COVID) are randomly chosen they tend to ensure a fairer representation of the studied population. Third, your sample needs to be large enough, hence the large-N designation for any conclusions to have any external validity. Generally speaking, the larger the number of observations/cases in the sample, the more validity we can have in the study. There is no magic number, but if using the above example, our sample of long-term COVID patients should be at least over 750 people, with an aim of around 1,200 to 1,500 people.

When it comes to comparative politics, we rarely ever reach the numbers typically used in large-N research. There are about 200 fully recognized countries, with about a dozen partially recognized countries, and even fewer areas or regions of study, such as Europe or Latin America. Given this, what is the strategy when one case, or a few cases, are being studied? What happens if we are only wanting to know the COVID-19 response in the United States, and not the rest of the world? How do we randomize this to ensure our results are not biased or are representative? These and other questions are legitimate issues that many comparativist scholars face when completing research. Does randomization work with case studies? Gerring suggests that it does not, as “any given sample may be widely representative” (pg. 87). Thus, random sampling is not a reliable approach when it comes to case studies. And even if the randomized sample is representative, there is no guarantee that the gathered evidence would be reliable.

One can make the argument that case selection may not be as important in large-N studies as they are in small-N studies. In large-N research, potential errors and/or biases may be ameliorated, especially if the sample is large enough. This is not always what happens, errors and biases most certainly can exist in large-N research. However, incorrect or biased inferences are less of a worry when we have 1,500 cases versus 15 cases. In small-N research, case selection simply matters much more.

This is why Blatter and Haverland (2012) write that, “case studies are ‘case-centered’, whereas large-N studies are ‘variable-centered’". In large-N studies we are more concerned with the conceptualization and operationalization of variables. Thus, we want to focus on which data to include in the analysis of long-term COVID patients. If we wanted to survey them, we would want to make sure we construct questions in appropriate ways. For almost all survey-based large-N research, the question responses themselves become the coded variables used in the statistical analysis.

Case selection can be driven by a number of factors in comparative politics, with the first two approaches being the more traditional. First, it can derive from the interests of the researcher(s). For example, if the researcher lives in Germany, they may want to research the spread of COVID-19 within the country, possibly using a subnational approach where the researcher may compare infection rates among German states. Second, case selection may be driven by area studies. This is still based on the interests of the researcher as generally speaking scholars pick areas of studies due to their personal interests. For example, the same researcher may research COVID-19 infection rates among European Union member-states. Finally, the selection of cases selected may be driven by the type of case study that is utilized. In this approach, cases are selected as they allow researchers to compare their similarities or their differences. Or, a case might be selected that is typical of most cases, or in contrast, a case or cases that deviate from the norm. We discuss types of case studies and their impact on case selection below.

Types of Case Studies: Descriptive vs. Causal

There are a number of different ways to categorize case studies. One of the most recent ways is through John Gerring. He wrote two editions on case study research (2017) where he posits that the central question posed by the researcher will dictate the aim of the case study. Is the study meant to be descriptive? If so, what is the researcher looking to describe? How many cases (countries, incidents, events) are there? Or is the study meant to be causal, where the researcher is looking for a cause and effect? Given this, Gerring categorizes case studies into two types: descriptive and causal.

Descriptive case studies are “not organized around a central, overarching causal hypothesis or theory” (pg. 56). Most case studies are descriptive in nature, where the researchers simply seek to describe what they observe. They are useful for transmitting information regarding the studied political phenomenon. For a descriptive case study, a scholar might choose a case that is considered typical of the population. An example could involve researching the effects of the pandemic on medium-sized cities in the US. This city would have to exhibit the tendencies of medium-sized cities throughout the entire country. First, we would have to conceptualize what we mean by ‘a medium-size city’. Second, we would then have to establish the characteristics of medium-sized US cities, so that our case selection is appropriate. Alternatively, cases could be chosen for their diversity . In keeping with our example, maybe we want to look at the effects of the pandemic on a range of US cities, from small, rural towns, to medium-sized suburban cities to large-sized urban areas.

Causal case studies are “organized around a central hypothesis about how X affects Y” (pg. 63). In causal case studies, the context around a specific political phenomenon or phenomena is important as it allows for researchers to identify the aspects that set up the conditions, the mechanisms, for that outcome to occur. Scholars refer to this as the causal mechanism , which is defined by Falleti & Lynch (2009) as “portable concepts that explain how and why a hypothesized cause, in a given context, contributes to a particular outcome”. Remember, causality is when a change in one variable verifiably causes an effect or change in another variable. For causal case studies that employ causal mechanisms, Gerring divides them into exploratory case-selection, estimating case-selection, and diagnostic case-selection. The differences revolve around how the central hypothesis is utilized in the study.

Exploratory case studies are used to identify a potential causal hypothesis. Researchers will single out the independent variables that seem to affect the outcome, or dependent variable, the most. The goal is to build up to what the causal mechanism might be by providing the context. This is also referred to as hypothesis generating as opposed to hypothesis testing. Case selection can vary widely depending on the goal of the researcher. For example, if the scholar is looking to develop an ‘ideal-type’, they might seek out an extreme case. An ideal-type is defined as a “conception or a standard of something in its highest perfection” (New Webster Dictionary). Thus, if we want to understand the ideal-type capitalist system, we want to investigate a country that practices a pure or ‘extreme’ form of the economic system.

Estimating case studies start with a hypothesis already in place. The goal is to test the hypothesis through collected data/evidence. Researchers seek to estimate the ‘causal effect’. This involves determining if the relationship between the independent and dependent variables is positive, negative, or ultimately if no relationship exists at all. Finally, diagnostic case studies are important as they help to “confirm, disconfirm, or refine a hypothesis” (Gerring 2017). Case selection can also vary in diagnostic case studies. For example, scholars can choose an least-likely case, or a case where the hypothesis is confirmed even though the context would suggest otherwise. A good example would be looking at Indian democracy, which has existed for over 70 years. India has a high level of ethnolinguistic diversity, is relatively underdeveloped economically, and a low level of modernization through large swaths of the country. All of these factors strongly suggest that India should not have democratized, or should have failed to stay a democracy in the long-term, or have disintegrated as a country.

Most Similar/Most Different Systems Approach

The discussion in the previous subsection tends to focus on case selection when it comes to a single case. Single case studies are valuable as they provide an opportunity for in-depth research on a topic that requires it. However, in comparative politics, our approach is to compare. Given this, we are required to select more than one case. This presents a different set of challenges. First, how many cases do we pick? This is a tricky question we addressed earlier. Second, how do we apply the previously mentioned case selection techniques, descriptive vs. causal? Do we pick two extreme cases if we used an exploratory approach, or two least-likely cases if choosing a diagnostic case approach?

Thankfully, an English scholar by the name of John Stuart Mill provided some insight on how we should proceed. He developed several approaches to comparison with the explicit goal of isolating a cause within a complex environment. Two of these methods, the 'method of agreement' and the 'method of difference' have influenced comparative politics. In the 'method of agreement' two or more cases are compared for their commonalities. The scholar looks to isolate the characteristic, or variable, they have in common, which is then established as the cause for their similarities. In the 'method of difference' two or more cases are compared for their differences. The scholar looks to isolate the characteristic, or variable, they do not have in common, which is then identified as the cause for their differences. From these two methods, comparativists have developed two approaches.

Book cover of John Stuart Mill's A System of Logic, Ratiocinative and Inductive, 1843

What Is the Most Similar Systems Design (MSSD)?

This approach is derived from Mill’s ‘method of difference’. In a Most Similar Systems Design Design, the cases selected for comparison are similar to each other, but the outcomes differ in result. In this approach we are interested in keeping as many of the variables the same across the elected cases, which for comparative politics often involves countries. Remember, the independent variable is the factor that doesn’t depend on changes in other variables. It is potentially the ‘cause’ in the cause and effect model. The dependent variable is the variable that is affected by, or dependent on, the presence of the independent variable. It is the ‘effect’. In a most similar systems approach the variables of interest should remain the same.

A good example involves the lack of a national healthcare system in the US. Other countries, such as New Zealand, Australia, Ireland, UK and Canada, all have robust, publicly accessible national health systems. However, the US does not. These countries all have similar systems: English heritage and language use, liberal market economies, strong democratic institutions, and high levels of wealth and education. Yet, despite these similarities, the end results vary. The US does not look like its peer countries. In other words, why do we have similar systems producing different outcomes?

What Is the Most Different Systems Design (MDSD)?

This approach is derived from Mill’s ‘method of agreement’. In a Most Different System Design, the cases selected are different from each other, but result in the same outcome. In this approach, we are interested in selecting cases that are quite different from one another, yet arrive at the same outcome. Thus, the dependent variable is the same. Different independent variables exist between the cases, such as democratic v. authoritarian regime, liberal market economy v. non-liberal market economy. Or it could include other variables such as societal homogeneity (uniformity) vs. societal heterogeneity (diversity), where a country may find itself unified ethnically/religiously/racially, or fragmented along those same lines.

A good example involves the countries that are classified as economically liberal. The Heritage Foundation lists countries such as Singapore, Taiwan, Estonia, Australia, New Zealand, as well as Switzerland, Chile and Malaysia as either free or mostly free. These countries differ greatly from one another. Singapore and Malaysia are considered flawed or illiberal democracies (see chapter 5 for more discussion), whereas Estonia is still classified as a developing country. Australia and New Zealand are wealthy, Malaysia is not. Chile and Taiwan became economically free countries under the authoritarian military regimes, which is not the case for Switzerland. In other words, why do we have different systems producing the same outcome?

Book cover

Landscapes of Lifelong Learning Policies across Europe pp 41–60 Cite as

Comparative Case Studies: Methodological Discussion

  • Marcelo Parreira do Amaral 7  
  • Open Access
  • First Online: 25 May 2022

9640 Accesses

4 Citations

Part of the Palgrave Studies in Adult Education and Lifelong Learning book series (PSAELL)

Case Study Research has a long tradition and it has been used in different areas of social sciences to approach research questions that command context sensitiveness and attention to complexity while tapping on multiple sources. Comparative Case Studies have been suggested as providing effective tools to understanding policy and practice along three different axes of social scientific research, namely horizontal (spaces), vertical (scales), and transversal (time). The chapter, first, sketches the methodological basis of case-based research in comparative studies as a point of departure, also highlighting the requirements for comparative research. Second, the chapter focuses on presenting and discussing recent developments in scholarship to provide insights on how comparative researchers, especially those investigating educational policy and practice in the context of globalization and internationalization, have suggested some critical rethinking of case study research to account more effectively for recent conceptual shifts in the social sciences related to culture, context, space and comparison. In a third section, it presents the approach to comparative case studies adopted in the European research project YOUNG_ADULLLT that has set out to research lifelong learning policies in their embeddedness in regional economies, labour markets and individual life projects of young adults. The chapter is rounded out with some summarizing and concluding remarks.

  • Case-based research
  • Comparative case studies

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1 Introduction

Exploring landscapes of lifelong learning in Europe is a daunting task as it involves a great deal of differences across places and spaces; it entails attending to different levels and dimensions of the phenomena at hand, but not least it commands substantial sensibility to cultural and contextual idiosyncrasies. As such, case-based methodologies come to mind as tested methodological approaches to capturing and examining singular configurations such as the local settings in focus in this volume, in which lifelong learning policies for young people are explored in their multidimensional reality. The ensuing question, then, is how to ensure comparability across cases when departing from the assumption that cases are unique. Recent debates in Comparative and International Education (CIE) research are drawn from that offer important insights into the issues involved and provide a heuristic approach to comparative cases studies. Since the cases focused on in the chapters of this book all stem from a common European research project, the comparative case study methodology allows us to at once dive into the specifics and uniqueness of each case while at the same time pay attention to common treads at the national and international (European) levels.

The chapter, first, sketches the methodological basis of case-based research in comparative studies as a point of departure, also highlighting the requirements in comparative research. In what follows, second, the chapter focuses on presenting and discussing recent developments in scholarship to provide insights on how comparative researchers, especially those investigating educational policy and practice in the context of globalization and internationalization, have suggested some critical rethinking of case study research to account more effectively for recent conceptual shifts in the social sciences related to culture, context, space and comparison. In a third section, it presents the approach to comparative case studies adopted in the European research project YOUNG_ADULLLT that has set out to research lifelong learning policies in their embeddedness in regional economies, labour markets and individual life projects of young adults. The chapter is rounded out with some summarizing and concluding remarks.

2 Case-Based Research in Comparative Studies

In the past, comparativists have oftentimes regarded case study research as an alternative to comparative studies proper. At the risk of oversimplification: methodological choices in comparative and international education (CIE) research, from the 1960s onwards, have fallen primarily on either single country (small n) contextualized comparison, or on cross-national (usually large n, variable) decontextualized comparison (see Steiner-Khamsi, 2006a , 2006b , 2009). These two strands of research—notably characterized by Development and Area Studies on the one side and large-scale performance surveys of the International Association for the Evaluation of Educational Achievement (IEA) type, on the other—demarcated their fields by resorting to how context and culture were accounted for and dealt with in the studies they produced. Since the turn of the century, though, comparativists are more comfortable with case study methodology (see Little, 2000 ; Vavrus and Bartlett 2006 , 2009 ; Bartlett & Vavrus, 2017 ) and diagnoses of an “identity crisis” of the field due to a mass of single-country studies lacking comparison proper (see Schriewer, 1990 ; Wiseman & Anderson, 2013 ) started dying away. Greater acceptance of and reliance on case-based methodology has been related with research on policy and practice in the context of globalization and coupled with the intention to better account for culture and context, generating scholarship that is critical of power structures, sensitive to alterity and of other ways of knowing.

The phenomena that have been coined as constituting “globalization” and “internationalization” have played, as mentioned, a central role in the critical rethinking of case study research. In researching education under conditions of globalization, scholars placed increasing attention on case-based approaches as opportunities for investigating the contemporary complexity of policy and practice. Further, scholarly debates in the social sciences and the humanities surrounding key concepts such as culture, context, space, and place but also comparison have also contributed to a reconceptualization of case study methodology in CIE. In terms of the requirements for such an investigation, scholarship commands an adequate conceptualization that problematizes the objects of study and that does not take them as “unproblematic”, “assum[ing] a constant shared meaning”; in short, objects of study that are “fixed, abstract and absolute” (Fine, quoted in Dale & Robertson, 2009 , p. 1114). Case study research is thus required to overcome methodological “isms” in their research conceptualization (see Dale & Robertson, 2009 ; Robertson & Dale, 2017 ; see also Lange & Parreira do Amaral, 2018 ). In response to these requirements, the approaches to case study discussed in CIE depart from a conceptualization of the social world as always dynamic, emergent, somewhat in motion, and always contested. This view considers the fact that the social world is culturally produced and is never complete or at a standstill, which goes against an understanding of case as something fixed or natural. Indeed, in the past cases have often been understood almost in naturalistic ways, as if they existed out there, waiting for researchers to “discover” them. Usually, definitions of case study also referred to inquiry that aims at elucidating features of a phenomenon to yield an understanding of why, how and with what consequences something happens. One can easily find examples of cases understood simply as sites to observe/measure variables—in a nomothetic cast—or examples, where cases are viewed as specific and unique instances that can be examined in the idiographic paradigm. In contrast, rather than taking cases as pre-existing entities that are defined and selected as cases, recent case-oriented research has argued for a more emergent approach which recognizes that boundaries between phenomenon and context are often difficult to establish or overlap. For this reason, researchers are incited to see this as an exercise of “casing”, that is, of case construction. In this sense, cases here are seen as complex systems (Ragin & Becker, 1992 ) and attention is devoted to the relationships between the parts and the whole, pointing to the relevance of configurations and constellations within as well as across cases in the explanation of complex and contingent phenomena. This is particularly relevant for multi-case, comparative research since the constitution of the phenomena that will be defined, as cases will differ. Setting boundaries will thus also require researchers to account for spatial, scalar (i.e., level or levels with which a case is related) and temporal aspects.

Further, case-based research is also required to account for multiple contexts while not taking them for granted. One of the key theoretical and methodological consequences of globalization for CIE is that it required us to recognize that it alters the nature and significance of what counts as contexts (see Parreira do Amaral, 2014 ). According to Dale ( 2015 ), designating a process, or a type of event, or a particular organization, as a context, entails bestowing a particular significance on them, as processes, events, and so on that are capable of affecting other processes and events. The key point is that rather than being so intrinsically, or naturally, contexts are constructed as “contexts”. In comparative research, contexts have been typically seen as the place (or the variables) that enable us to explain why what happens in one case is different from what happens another case; what counts as context then is seen as having the same effect everywhere, although the forms it takes vary substantially (see Dale, 2015 ). In more general terms, recent case study approaches aim at accounting for the increasing complexity of the contexts in which they are embedded, which, in turn, is related to the increasing impact of globalization as the “context of contexts” (Dale, 2015 , p. 181f; see also Carter & Sealey, 2013 ; Mjoset, 2013 ). It also aims at accounting for overlapping contexts. Here it is important to note that contexts are not only to be seen in spatio-geographical terms (i.e., local, regional, national, international), but contexts may also be provided by different institutional and/or discursive contexts that create varying opportunity structures (Dale & Parreira do Amaral, 2015 ; see also Chap. 2 in this volume). What one can call temporal contexts also plays an important role, for what happens in the case unfolds as embedded not only in historical time, but may be related to different temporalities (see the concept of “timespace” as discussed by Lingard & Thompson, 2016 ) and thus are influenced by path dependence or by specific moments of crisis (Rhinard, 2019 ; see also McLeod, 2016 ). Moreover, in CIE research, the social-cultural production of the world is influenced by developments throughout the globe that take place at various places and on several scales, which in turn influence each other, but in the end, become locally relevant in different facets. As Bartlett and Vavrus write, “context is not a primordial or autonomous place; it is constituted by social interactions, political processes, and economic developments across scales and times.” ( Bartlett & Vavrus, 2017 , p. 14). Indeed, in this sense, “context is not a container for activity, it is the activity” (Bartlett & Vavrus, 2017 , p. 12, emphasis in orig.).

Also, dealing with the complexity of education policy and practice requires us to transcend the dichotomy of idiographic versus nomothetic approaches to causation. Here, it can be argued that case studies allow us to grasp and research the complexity of the world, thus offering conceptual and methodological tools to explore how phenomena viewed as cases “depend on all of the whole, the parts, the interactions among parts and whole, and the interactions of any system with other complex systems among which it is nested and with which it intersects” (Byrne, 2013 , p. 2). The understanding of causation that undergirds recent developments in case-based research aims at generalization, yet it resists ambitions to establishing universal laws in social scientific research. Focus is placed on processes while tracking the relevant factors, actors and features that help explain the “how” and the “why” questions (Bartlett and Vavrus 2017 , p. 38ff), and on “causal mechanisms”, as varying explanations of outcomes within and across cases, always contingent on interaction with other variables and dependent contexts (see Byrne, 2013 ; Ragin, 2000 ). In short, the nature of causation underlying the recent case study approaches in CIE is configurational and not foundational.

This is also in line with how CIE research regards education practice, research, and policy as a socio-cultural practice. And it refers to the production of social and cultural worlds through “social actors, with diverse motives, intentions, and levels of influence, [who] work in tandem with and/or in response to social forces” (Bartlett and Vavrus 2017 , p. 1). From this perspective, educational phenomena, such as in policymaking, are seen as a “deeply political process of cultural production engaged in and shaped by social actors in disparate locations who exert incongruent amounts of influence over the design, implementation, and evaluation of policy” ( Bartlett & Vavrus, 2017 , p. 1f). Culture here is understood in non-static and complex ways that reinforce the “importance of examining processes of sense-making as they develop over time, in distinct settings, in relation to systems of power and inequality, and in increasingly interconnected conversation with actors who do not sit physically within the circle drawn around the traditional case” (Bartlett & Vavrus, 2017 , p. 11, emphasis in orig.).

In sum, the approaches to case study put forward in CIE provide conceptual and methodological tools that allow for an analysis of education in the global context throughout scale, space, and time, which is always regarded as complexly integrated and never as isolated or independent. The following subsection discusses Comparative Case Studies (CCS) as suggested in recent comparative scholarship, which aims at attending to the methodological requirements discussed above by integrating horizontal, vertical, and transversal dimensions of comparison.

2.1 Comparative Case Studies: Horizontal, Vertical and Transversal Dimensions

Building up on their previous work on vertical case studies (Bartlett and Vavrus 2017 ; Vavrus & Bartlett, 2006 , 2009 ), Frances Vavrus and Lesley Bartlett have proposed a comparative approach to case study research that aims at meeting the requirements of culture and context sensitive research as discussed in this special issue.

As a research approach, CCS offers two theoretical-methodological lenses to research education as a socio-cultural practice. These lenses represent different views on the research object and account for the complexity of education practice, policy, and research in globalized contexts. The first lens is “context-sensitive”, which focuses on how social practices and interactions constitute and produce social contexts. As quoted above, from the perspective of a socio-cultural practice, “context is not a container for activity, it is the activity” (Vavrus and Bartlett 2017: 12, emphasis in orig.). The settings that influence and condition educational phenomena are culturally produced in different and sometimes overlapping (spatial, institutional, discursive, temporal) contexts as just mentioned. The second CCS lens is “culture-sensitive” and focuses on how socio-cultural practices produce social structures. As such, culture is a process that is emergent, dynamic, and constitutive of meaning-making as well as social structuration.

The CCS approach aims at studying educational phenomena throughout scale, time, and space by providing three axes for a “studying through” of the phenomena in question. As stated by Lesley Bartlett and Frances Vavrus with reference to comparative analyses of global education policy:

the horizontal axis compares how similar policies unfold in distinct locations that are socially produced […] and ‘complexly connected’ […]. The vertical axis insists on simultaneous attention to and across scales […]. The transversal comparison historically situates the processes or relations under consideration (Bartlett and Vavrus 2017 : 3, emphasis in orig.).

These three axes allow for a methodological conceptualization of “policy formation and appropriation across micro-, meso-, and macro levels” by not theorizing them as distinct or unrelated (Bartlett and Vavrus 2017 , p. 4). In following Latour, they state:

the macro is neither “above” nor “below” the intersections but added to them as another of their connections’ […]. In CCS research, one would pay close attention to how actions at different scales mutually influence one another (Bartlett and Vavrus 2017 , p. 13f, emphasis in orig.)

Thus, these three axes contain

processes across space and time; and [the CCS as a research design] constantly compares what is happening in one locale with what has happened in other places and historical moments. These forms of comparison are what we call horizontal, vertical, and transversal comparisons (Bartlett and Vavrus 2017 , p. 11, emphasis in orig.)

In terms of the three axes along with comparison is organized, the authors state that horizontal comparison commands attention to how historical and contemporary processes have variously influenced the “cases”, which might be constructed by focusing “people, groups of people, sites, institutions, social movements, partnerships, etc.” (Bartlett and Vavrus 2017 , p. 53) Horizontal comparisons eschew pressing categories resultant from one case others, which implies including multiple cases at the same scale in a comparative case study, while at the same time attending to “valuable contextual information” about each of them. Horizontal comparisons use units of analysis that are homologous, that is, equivalent in terms of shape, function, or institutional/organizational nature (for instance, schools, ministries, countries, etc.) ( Bartlett & Vavrus, 2017 , p. 53f). Similarly, comparative case studies may also entail tracing a phenomenon across sites, as in multi-sited ethnography (see Coleman & von Hellermann, 2012 ; Marcus, 1995 ).

Vertical comparison, in turn, does not simply imply the comparison of levels; rather it involves analysing networks and their interrelationships at different scales. For instance, in the study of policymaking in a specific case, vertical comparison would consider how actors at different scales variably respond to a policy issued at another level—be it inter−/supranational or at the subnational level. CCS assumes that their different appropriation of policy as discourse and as practice is often due to different histories of racial, ethnic, or gender politics in their communities that appropriately complicate the notion of a single cultural group (Bartlett and Vavrus 2017 , p. 73f). Establishing what counts as context in such a study would be done “by tracing the formation and appropriation of a policy” at different scales; and “by tracing the processes by which actors and actants come into relationship with one another and form non-permanent assemblages aimed at producing, implementing, resisting, and appropriating policy to achieve particular aims” ( Bartlett & Vavrus, 2017 , p. 76). A further element here is that, in this way, one may counter the common problem that comparison of cases (oftentimes countries) usually overemphasizes boundaries and treats them as separated or as self-sustaining containers, when, in reality, actors and institutions at other levels/scales significantly impact policymaking (Bartlett & Vavrus, 2017 ).

In terms of the transversal axis of comparison, Bartlett and Vavrus argue that the social phenomena of interest in a case study have to be seen in light of their historical development (Bartlett & Vavrus, 2017 , p. 93), since these “historical roots” impacted on them and “continues to reverberate into the present, affecting economic relations and social issues such as migration and educational opportunities.” As such, understanding what goes on in a case requires to “understand how it came to be in the first place.” ( Bartlett & Vavrus, 2017 , p. 93) argue:

history offers an extensive fount of evidence regarding how social institutions function and how social relations are similar and different around the world. Historical analysis provides an essential opportunity to contrast how things have changed over time and to consider what has remained the same in one locale or across much broader scales. Such historical comparison reveals important insights about the flexible cultural, social, political, and economic systems humans have developed and sustained over time (Bartlett & Vavrus, 2017 , p. 94).

Further, time and space are intimately related and studying the historical development of the social phenomena of interest in a case study “allows us to assess evidence and conflicting interpretations of a phenomenon,” but also to interrogate our own assumptions about them in contemporary times (Bartlett and Vavrus 2017 ), thus analytically sharpening our historical analyses.

As argued by the authors, researching the global dimension of education practice, research or policy aims at a “studying through” of phenomena horizontally, vertically, and transversally. That is, comparative case study builds on an emergent research design and on a strong process orientation that aims at tracing not only “what”, but also “why” and “how” phenomena emerge and evolve. This approach entails “an open-ended, inductive approach to discover what […] meanings and influences are and how they are involved in these events and activities—an inherently processual orientation” (Bartlett and Vavrus 2017 , p. 7, emphasis in orig.).

The emergent research design and process orientation of the CCS relativizes a priori, somewhat static notions of case construction in CIE and emphasizes the idea of a processual “casing”. The process of casing put forward by CCS has to be understood as a dynamic and open-ended embedding of “cased” research phenomena within moments of scale, space, and time that produce varying sets of conditions or configurations.

In terms of comparison, the primary logic is well in line with more sophisticated approaches to comparison that not simply establish relationships between observable facts or pre-existing cases; rather, the comparative logic aims at establishing “relations between sets of relationships”, as argued by Jürgen Schriewer:

[the] specific method of science dissociates comparison from its quasi-natural union with resemblances; the interest in identifying similarities shifts from the level of factual contents to the level of generalizable relationships. […] One of the primary ways of extending their scope, or examining their explanatory power, is the controlled introduction of varying sets of conditions. The logic of relating relationships, which distinguishes the scientific method of comparison, comes close to meeting these requirements by systematically exploring and analysing sociocultural differences with respect to scrutinizing the credibility of theories, models or constructs (Schriewer, 1990 , p. 36).

The notion of establishing relations between sets of relationships allows to treat cases not as homogeneous (thus avoiding a universalizing notion of comparison); it establishes comparability not along similarity but based on conceptual, functional and/or theoretical equivalences and focuses on reconstructing ‘varying sets of conditions’ that are seen as relevant in social scientific explanation and theorizing, and to which then comparative case studies may contribute.

The following section aims presents the adaptation and application of a comparative case study approach in the YOUNG_ADULLLT research project.

3 Exploring Landscapes of Lifelong Learning through Case Studies

This section illustrates the usage of comparative case studies by drawing from research conducted in a European research project upon which the chapters in this volume are based. The project departed from the observation that most current European lifelong learning (LLL) policies have been designed to create economic growth and, at the same time, guarantee social inclusion and argued that, while these objectives are complementary, they are, however, not linearly nor causally related and, due to distinct orientations, different objectives, and temporal horizons, conflicts and ambiguities may arise. The project was designed as a mixed-method comparative study and aimed at results at the national, regional, and local levels, focusing in particular on policies targeting young adults in situations of near social exclusion. Using a multi-level approach with qualitative and quantitative methods, the project conducted, amongst others, local/regional 18 case studies of lifelong learning policies through a multi-method and multi-level design (see Parreira do Amaral et al., 2020 for more information). The localisation of the cases in their contexts was carried out by identifying relevant areas in terms of spatial differentiation and organisation of social and economic relations. The so defined “functional regions” allowed focus on territorial units which played a central role within their areas, not necessarily overlapping with geographical and/or administrative borders. Footnote 1

Two main objectives guided the research: first, to analyse policies and programmes at the regional and local level by identifying policymaking networks that included all social actors involved in shaping, formulating, and implementing LLL policies for young adults; second, to recognize strengths and weaknesses (overlapping, fragmented or unfocused policies and projects), thus identifying different patterns of LLL policymaking at regional level, and investigating their integration with the labour market, education and other social policies. The European research project focused predominantly on the differences between the existing lifelong learning policies in terms of their objectives and orientations and questioned their impact on young adults’ life courses, especially those young adults who find themselves in vulnerable positions. What concerned the researchers primarily was the interaction between local institutional settings, education, labour markets, policymaking landscapes, and informal initiatives that together nurture the processes of lifelong learning. They argued that it is by inquiring into the interplay of these components that the regional and local contexts of lifelong learning policymaking can be better assessed and understood. In this regard, the multi-layered approach covered a wide range of actors and levels and aimed at securing compatibility throughout the different phases and parts of the research.

The multi-level approach adopted aimed at incorporating the different levels from transnational to regional/local to individual, that is, the different places, spaces, and levels with which policies are related. The multi-method design was used to bring together the results from the quantitative, qualitative and policy/document analysis (for a discussion: Parreira do Amaral, 2020 ).

Studying the complex relationships between lifelong learning (LLL) policymaking on the one hand, and young adults’ life courses on the other, requires a carefully established research approach. This task becomes even more challenging in the light of the diverse European countries and their still more complex local and regional structures and institutions. One possible way of designing a research framework able to deal with these circumstances clearly and coherently is to adopt a multi-level or multi-layered approach. This approach recognises multiple levels and patterns of analysis and enables researchers to structure the workflow according to various perspectives. It was this multi-layered approach that the research consortium of YOUNG_ADULLLT adopted and applied in its attempts to better understand policies supporting young people in their life course.

3.1 Constructing Case Studies

In constructing case studies, the project did not apply an instrumental approach focused on the assessment of “what worked (or not)?” Rather, consistently with Bartlett and Vavrus’s proposal (Bartlett & Vavrus, 2017 ), the project decided to “understand policy as a deeply political process of cultural production engaged in and shaped by social actors in disparate locations who exert incongruent amounts of influence over the design, implementation, and evaluation of policy” ( Bartlett & Vavrus, 2017 , p. 1f). This was done in order to enhance the interactive and relational dimension among actors and levels, as well as their embeddedness in local infra-structures (education, labour, social/youth policies) according to project’s three theoretical perspectives. The analyses of the information and data integrated by our case study approach aimed at a cross-reading of the relations among the macro socio-economic dimensions, structural arrangements, governance patterns, addressee biographies and mainstream discourses that underlie the process of design and implementation of the LLL policies selected as case study. The subjective dimensions of agency and sense-making animated these analyses, and the multi-level approach contextualized them from the local to the transnational levels. Figure 3.1 below represents the analytical approach to the research material gathered in constructing the case studies. Specifically, it shows the different levels, from the transnational level down to the addressees.

figure 1

Multi-level and multi-method approach to case studies in YOUNG_ADULLLT. Source: Palumbo et al., 2019

The project partners aimed at a cross-dimensional construction of the case studies, and this implied the possibility of different entry points, for instance by moving the analytical perspective top-down or bottom-up, as well as shifting from left to right of the matrix and vice versa. Considering the “horizontal movement”, the multidimensional approach has enabled taking into consideration the mutual influence and relations among the institutional, individual, and structural dimensions (which in the project corresponded to the theoretical frames of CPE, LCR, and GOV). In addition, the “vertical movement” from the transnational to the individual level and vice versa was meant to carefully carry out a “study of flows of influence, ideas, and actions through these levels” (Bartlett and Vavrus 2017 , p. 11), emphasizing the correspondences/divergences among the perspectives of different actors at different levels. The transversal dimension, that is, the historical process, focused on the period after the financial crisis of 2007/2008 as it has impacted differently on the social and economic situations of young people, often resulting in stern conditions and higher competition in education and labour markets, which also called for a reassessment of existing policies targeting young adults in the countries studied.

Concerning the analyses, a further step included the translation of the conceptual model illustrated in Fig. 3.1 above into a heuristic table used to systematically organize the empirical data collected and guide the analyses cases constructed as multi-level and multidimensional phenomena, allowing for the establishment of interlinkages and relationships. By this approach, the analysis had the possibility of grasping the various levels at which LLL policies are negotiated and displaying the interplay of macro-structures, regional environments and institutions/organizations as well as individual expectations. Table 3.1 illustrates the operationalization of the data matrix that guided the work.

In order to ensure the presentability and intelligibility of the results, Footnote 2 a narrative approach to case studies analysis was chosen whose main task was one of “storytelling” aimed at highlighting what made each case unique and what difference it makes for LLL policymaking and to young people’s life courses. A crucial element of this entails establishing relations “between sets of relationships”, as argued above.

LLL policies were selected as starting points from which the cases themselves could be constructed and of which different stories could be developed. That stories can be told differently does not mean that they are arbitrary, rather this refers to different ways of accounting for the embedding of the specific case to its context, namely the “diverging policy frameworks, patterns of policymaking, networks of implementation, political discourses and macro-structural conditions at local level” (see Palumbo et al., 2020 , p. 220). Moreover, developing different narratives aimed at representing the various voices of the actors involved in the process—from policy-design and appropriation through to implementation—and making the different stakeholders’ and addressees’ opinions visible, creating thus intelligible narratives for the cases (see Palumbo et al., 2020 ). Analysing each case started from an entry point selected, from which a story was told. Mainly, two entry points were used: on the one hand, departing from the transversal dimension of the case and which focused on the evolution of a policy in terms of its main objectives, target groups, governance patterns and so on in order to highlight the intended and unintended effects of the “current version” of the policy within its context and according to the opinions of the actors interviewed. On the other hand, biographies were selected as starting points in an attempt to contextualize the life stories within the biographical constellations in which the young people came across the measure, the access procedures, and how their life trajectories continued in and possibly after their participation in the policy (see Palumbo et al., 2020 for examples of these narrative strategies).

4 Concluding Remarks

This chapter presented and discussed the methodological basis and requirements of conducting case studies in comparative research, such as those presented in the subsequent chapters of this volume. The Comparative Case Study approach suggested in the previous discussion offers productive and innovative ways to account sensitively to culture and contexts; it provides a useful heuristic that deals effectively with issues related to case construction, namely an emergent and dynamic approach to casing, instead of simply assuming “bounded”, pre-defined cases as the object of research; they also offer a helpful procedural, configurational approach to “causality”; and, not least, a resourceful approach to comparison that allows researchers to respect the uniqueness and integrity of each case while at the same time yielding insights and results that transcend the idiosyncrasy of the single case. In sum, CCS offers a sound approach to CIE research that is culture and context sensitive.

For a discussion of the concept of functional region, see Parreira do Amaral et al., 2020 .

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do Amaral, M.P. (2022). Comparative Case Studies: Methodological Discussion. In: Benasso, S., Bouillet, D., Neves, T., Parreira do Amaral, M. (eds) Landscapes of Lifelong Learning Policies across Europe. Palgrave Studies in Adult Education and Lifelong Learning. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-96454-2_3

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  • What Is a Case Study? | Definition, Examples & Methods

What Is a Case Study? | Definition, Examples & Methods

Published on May 8, 2019 by Shona McCombes . Revised on November 20, 2023.

A case study is a detailed study of a specific subject, such as a person, group, place, event, organization, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research.

A case study research design usually involves qualitative methods , but quantitative methods are sometimes also used. Case studies are good for describing , comparing, evaluating and understanding different aspects of a research problem .

Table of contents

When to do a case study, step 1: select a case, step 2: build a theoretical framework, step 3: collect your data, step 4: describe and analyze the case, other interesting articles.

A case study is an appropriate research design when you want to gain concrete, contextual, in-depth knowledge about a specific real-world subject. It allows you to explore the key characteristics, meanings, and implications of the case.

Case studies are often a good choice in a thesis or dissertation . They keep your project focused and manageable when you don’t have the time or resources to do large-scale research.

You might use just one complex case study where you explore a single subject in depth, or conduct multiple case studies to compare and illuminate different aspects of your research problem.

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comparing two case studies

Once you have developed your problem statement and research questions , you should be ready to choose the specific case that you want to focus on. A good case study should have the potential to:

  • Provide new or unexpected insights into the subject
  • Challenge or complicate existing assumptions and theories
  • Propose practical courses of action to resolve a problem
  • Open up new directions for future research

TipIf your research is more practical in nature and aims to simultaneously investigate an issue as you solve it, consider conducting action research instead.

Unlike quantitative or experimental research , a strong case study does not require a random or representative sample. In fact, case studies often deliberately focus on unusual, neglected, or outlying cases which may shed new light on the research problem.

Example of an outlying case studyIn the 1960s the town of Roseto, Pennsylvania was discovered to have extremely low rates of heart disease compared to the US average. It became an important case study for understanding previously neglected causes of heart disease.

However, you can also choose a more common or representative case to exemplify a particular category, experience or phenomenon.

Example of a representative case studyIn the 1920s, two sociologists used Muncie, Indiana as a case study of a typical American city that supposedly exemplified the changing culture of the US at the time.

While case studies focus more on concrete details than general theories, they should usually have some connection with theory in the field. This way the case study is not just an isolated description, but is integrated into existing knowledge about the topic. It might aim to:

  • Exemplify a theory by showing how it explains the case under investigation
  • Expand on a theory by uncovering new concepts and ideas that need to be incorporated
  • Challenge a theory by exploring an outlier case that doesn’t fit with established assumptions

To ensure that your analysis of the case has a solid academic grounding, you should conduct a literature review of sources related to the topic and develop a theoretical framework . This means identifying key concepts and theories to guide your analysis and interpretation.

There are many different research methods you can use to collect data on your subject. Case studies tend to focus on qualitative data using methods such as interviews , observations , and analysis of primary and secondary sources (e.g., newspaper articles, photographs, official records). Sometimes a case study will also collect quantitative data.

Example of a mixed methods case studyFor a case study of a wind farm development in a rural area, you could collect quantitative data on employment rates and business revenue, collect qualitative data on local people’s perceptions and experiences, and analyze local and national media coverage of the development.

The aim is to gain as thorough an understanding as possible of the case and its context.

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In writing up the case study, you need to bring together all the relevant aspects to give as complete a picture as possible of the subject.

How you report your findings depends on the type of research you are doing. Some case studies are structured like a standard scientific paper or thesis , with separate sections or chapters for the methods , results and discussion .

Others are written in a more narrative style, aiming to explore the case from various angles and analyze its meanings and implications (for example, by using textual analysis or discourse analysis ).

In all cases, though, make sure to give contextual details about the case, connect it back to the literature and theory, and discuss how it fits into wider patterns or debates.

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

  • Normal distribution
  • Degrees of freedom
  • Null hypothesis
  • Discourse analysis
  • Control groups
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  • Non-probability sampling
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  • Rosenthal effect
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Chapter 10 methods for comparative studies.

Francis Lau and Anne Holbrook .

10.1. Introduction

In eHealth evaluation, comparative studies aim to find out whether group differences in eHealth system adoption make a difference in important outcomes. These groups may differ in their composition, the type of system in use, and the setting where they work over a given time duration. The comparisons are to determine whether significant differences exist for some predefined measures between these groups, while controlling for as many of the conditions as possible such as the composition, system, setting and duration.

According to the typology by Friedman and Wyatt (2006) , comparative studies take on an objective view where events such as the use and effect of an eHealth system can be defined, measured and compared through a set of variables to prove or disprove a hypothesis. For comparative studies, the design options are experimental versus observational and prospective versus retro­­spective. The quality of eHealth comparative studies depends on such aspects of methodological design as the choice of variables, sample size, sources of bias, confounders, and adherence to quality and reporting guidelines.

In this chapter we focus on experimental studies as one type of comparative study and their methodological considerations that have been reported in the eHealth literature. Also included are three case examples to show how these studies are done.

10.2. Types of Comparative Studies

Experimental studies are one type of comparative study where a sample of participants is identified and assigned to different conditions for a given time duration, then compared for differences. An example is a hospital with two care units where one is assigned a cpoe system to process medication orders electronically while the other continues its usual practice without a cpoe . The participants in the unit assigned to the cpoe are called the intervention group and those assigned to usual practice are the control group. The comparison can be performance or outcome focused, such as the ratio of correct orders processed or the occurrence of adverse drug events in the two groups during the given time period. Experimental studies can take on a randomized or non-randomized design. These are described below.

10.2.1. Randomized Experiments

In a randomized design, the participants are randomly assigned to two or more groups using a known randomization technique such as a random number table. The design is prospective in nature since the groups are assigned concurrently, after which the intervention is applied then measured and compared. Three types of experimental designs seen in eHealth evaluation are described below ( Friedman & Wyatt, 2006 ; Zwarenstein & Treweek, 2009 ).

Randomized controlled trials ( rct s) – In rct s participants are randomly assigned to an intervention or a control group. The randomization can occur at the patient, provider or organization level, which is known as the unit of allocation. For instance, at the patient level one can randomly assign half of the patients to receive emr reminders while the other half do not. At the provider level, one can assign half of the providers to receive the reminders while the other half continues with their usual practice. At the organization level, such as a multisite hospital, one can randomly assign emr reminders to some of the sites but not others. Cluster randomized controlled trials ( crct s) – In crct s, clusters of participants are randomized rather than by individual participant since they are found in naturally occurring groups such as living in the same communities. For instance, clinics in one city may be randomized as a cluster to receive emr reminders while clinics in another city continue their usual practice. Pragmatic trials – Unlike rct s that seek to find out if an intervention such as a cpoe system works under ideal conditions, pragmatic trials are designed to find out if the intervention works under usual conditions. The goal is to make the design and findings relevant to and practical for decision-makers to apply in usual settings. As such, pragmatic trials have few criteria for selecting study participants, flexibility in implementing the intervention, usual practice as the comparator, the same compliance and follow-up intensity as usual practice, and outcomes that are relevant to decision-makers.

10.2.2. Non-randomized Experiments

Non-randomized design is used when it is neither feasible nor ethical to randomize participants into groups for comparison. It is sometimes referred to as a quasi-experimental design. The design can involve the use of prospective or retrospective data from the same or different participants as the control group. Three types of non-randomized designs are described below ( Harris et al., 2006 ).

Intervention group only with pretest and post-test design – This design involves only one group where a pretest or baseline measure is taken as the control period, the intervention is implemented, and a post-test measure is taken as the intervention period for comparison. For example, one can compare the rates of medication errors before and after the implementation of a cpoe system in a hospital. To increase study quality, one can add a second pretest period to decrease the probability that the pretest and post-test difference is due to chance, such as an unusually low medication error rate in the first pretest period. Other ways to increase study quality include adding an unrelated outcome such as patient case-mix that should not be affected, removing the intervention to see if the difference remains, and removing then re-implementing the intervention to see if the differences vary accordingly. Intervention and control groups with post-test design – This design involves two groups where the intervention is implemented in one group and compared with a second group without the intervention, based on a post-test measure from both groups. For example, one can implement a cpoe system in one care unit as the intervention group with a second unit as the control group and compare the post-test medication error rates in both units over six months. To increase study quality, one can add one or more pretest periods to both groups, or implement the intervention to the control group at a later time to measure for similar but delayed effects. Interrupted time series ( its ) design – In its design, multiple measures are taken from one group in equal time intervals, interrupted by the implementation of the intervention. The multiple pretest and post-test measures decrease the probability that the differences detected are due to chance or unrelated effects. An example is to take six consecutive monthly medication error rates as the pretest measures, implement the cpoe system, then take another six consecutive monthly medication error rates as the post-test measures for comparison in error rate differences over 12 months. To increase study quality, one may add a concurrent control group for comparison to be more convinced that the intervention produced the change.

10.3. Methodological Considerations

The quality of comparative studies is dependent on their internal and external validity. Internal validity refers to the extent to which conclusions can be drawn correctly from the study setting, participants, intervention, measures, analysis and interpretations. External validity refers to the extent to which the conclusions can be generalized to other settings. The major factors that influence validity are described below.

10.3.1. Choice of Variables

Variables are specific measurable features that can influence validity. In comparative studies, the choice of dependent and independent variables and whether they are categorical and/or continuous in values can affect the type of questions, study design and analysis to be considered. These are described below ( Friedman & Wyatt, 2006 ).

Dependent variables – This refers to outcomes of interest; they are also known as outcome variables. An example is the rate of medication errors as an outcome in determining whether cpoe can improve patient safety. Independent variables – This refers to variables that can explain the measured values of the dependent variables. For instance, the characteristics of the setting, participants and intervention can influence the effects of cpoe . Categorical variables – This refers to variables with measured values in discrete categories or levels. Examples are the type of providers (e.g., nurses, physicians and pharmacists), the presence or absence of a disease, and pain scale (e.g., 0 to 10 in increments of 1). Categorical variables are analyzed using non-parametric methods such as chi-square and odds ratio. Continuous variables – This refers to variables that can take on infinite values within an interval limited only by the desired precision. Examples are blood pressure, heart rate and body temperature. Continuous variables are analyzed using parametric methods such as t -test, analysis of variance or multiple regression.

10.3.2. Sample Size

Sample size is the number of participants to include in a study. It can refer to patients, providers or organizations depending on how the unit of allocation is defined. There are four parts to calculating sample size. They are described below ( Noordzij et al., 2010 ).

Significance level – This refers to the probability that a positive finding is due to chance alone. It is usually set at 0.05, which means having a less than 5% chance of drawing a false positive conclusion. Power – This refers to the ability to detect the true effect based on a sample from the population. It is usually set at 0.8, which means having at least an 80% chance of drawing a correct conclusion. Effect size – This refers to the minimal clinically relevant difference that can be detected between comparison groups. For continuous variables, the effect is a numerical value such as a 10-kilogram weight difference between two groups. For categorical variables, it is a percentage such as a 10% difference in medication error rates. Variability – This refers to the population variance of the outcome of interest, which is often unknown and is estimated by way of standard deviation ( sd ) from pilot or previous studies for continuous outcome.

Table 10.1. Sample Size Equations for Comparing Two Groups with Continuous and Categorical Outcome Variables.

Sample Size Equations for Comparing Two Groups with Continuous and Categorical Outcome Variables.

An example of sample size calculation for an rct to examine the effect of cds on improving systolic blood pressure of hypertensive patients is provided in the Appendix. Refer to the Biomath website from Columbia University (n.d.) for a simple Web-based sample size / power calculator.

10.3.3. Sources of Bias

There are five common sources of biases in comparative studies. They are selection, performance, detection, attrition and reporting biases ( Higgins & Green, 2011 ). These biases, and the ways to minimize them, are described below ( Vervloet et al., 2012 ).

Selection or allocation bias – This refers to differences between the composition of comparison groups in terms of the response to the intervention. An example is having sicker or older patients in the control group than those in the intervention group when evaluating the effect of emr reminders. To reduce selection bias, one can apply randomization and concealment when assigning participants to groups and ensure their compositions are comparable at baseline. Performance bias – This refers to differences between groups in the care they received, aside from the intervention being evaluated. An example is the different ways by which reminders are triggered and used within and across groups such as electronic, paper and phone reminders for patients and providers. To reduce performance bias, one may standardize the intervention and blind participants from knowing whether an intervention was received and which intervention was received. Detection or measurement bias – This refers to differences between groups in how outcomes are determined. An example is where outcome assessors pay more attention to outcomes of patients known to be in the intervention group. To reduce detection bias, one may blind assessors from participants when measuring outcomes and ensure the same timing for assessment across groups. Attrition bias – This refers to differences between groups in ways that participants are withdrawn from the study. An example is the low rate of participant response in the intervention group despite having received reminders for follow-up care. To reduce attrition bias, one needs to acknowledge the dropout rate and analyze data according to an intent-to-treat principle (i.e., include data from those who dropped out in the analysis). Reporting bias – This refers to differences between reported and unreported findings. Examples include biases in publication, time lag, citation, language and outcome reporting depending on the nature and direction of the results. To reduce reporting bias, one may make the study protocol available with all pre-specified outcomes and report all expected outcomes in published results.

10.3.4. Confounders

Confounders are factors other than the intervention of interest that can distort the effect because they are associated with both the intervention and the outcome. For instance, in a study to demonstrate whether the adoption of a medication order entry system led to lower medication costs, there can be a number of potential confounders that can affect the outcome. These may include severity of illness of the patients, provider knowledge and experience with the system, and hospital policy on prescribing medications ( Harris et al., 2006 ). Another example is the evaluation of the effect of an antibiotic reminder system on the rate of post-operative deep venous thromboses ( dvt s). The confounders can be general improvements in clinical practice during the study such as prescribing patterns and post-operative care that are not related to the reminders ( Friedman & Wyatt, 2006 ).

To control for confounding effects, one may consider the use of matching, stratification and modelling. Matching involves the selection of similar groups with respect to their composition and behaviours. Stratification involves the division of participants into subgroups by selected variables, such as comorbidity index to control for severity of illness. Modelling involves the use of statistical techniques such as multiple regression to adjust for the effects of specific variables such as age, sex and/or severity of illness ( Higgins & Green, 2011 ).

10.3.5. Guidelines on Quality and Reporting

There are guidelines on the quality and reporting of comparative studies. The grade (Grading of Recommendations Assessment, Development and Evaluation) guidelines provide explicit criteria for rating the quality of studies in randomized trials and observational studies ( Guyatt et al., 2011 ). The extended consort (Consolidated Standards of Reporting Trials) Statements for non-pharmacologic trials ( Boutron, Moher, Altman, Schulz, & Ravaud, 2008 ), pragmatic trials ( Zwarestein et al., 2008 ), and eHealth interventions ( Baker et al., 2010 ) provide reporting guidelines for randomized trials.

The grade guidelines offer a system of rating quality of evidence in systematic reviews and guidelines. In this approach, to support estimates of intervention effects rct s start as high-quality evidence and observational studies as low-quality evidence. For each outcome in a study, five factors may rate down the quality of evidence. The final quality of evidence for each outcome would fall into one of high, moderate, low, and very low quality. These factors are listed below (for more details on the rating system, refer to Guyatt et al., 2011 ).

Design limitations – For rct s they cover the lack of allocation concealment, lack of blinding, large loss to follow-up, trial stopped early or selective outcome reporting. Inconsistency of results – Variations in outcomes due to unexplained heterogeneity. An example is the unexpected variation of effects across subgroups of patients by severity of illness in the use of preventive care reminders. Indirectness of evidence – Reliance on indirect comparisons due to restrictions in study populations, intervention, comparator or outcomes. An example is the 30-day readmission rate as a surrogate outcome for quality of computer-supported emergency care in hospitals. Imprecision of results – Studies with small sample size and few events typically would have wide confidence intervals and are considered of low quality. Publication bias – The selective reporting of results at the individual study level is already covered under design limitations, but is included here for completeness as it is relevant when rating quality of evidence across studies in systematic reviews.

The original consort Statement has 22 checklist items for reporting rct s. For non-pharmacologic trials extensions have been made to 11 items. For pragmatic trials extensions have been made to eight items. These items are listed below. For further details, readers can refer to Boutron and colleagues (2008) and the consort website ( consort , n.d.).

Title and abstract – one item on the means of randomization used. Introduction – one item on background, rationale, and problem addressed by the intervention. Methods – 10 items on participants, interventions, objectives, outcomes, sample size, randomization (sequence generation, allocation concealment, implementation), blinding (masking), and statistical methods. Results – seven items on participant flow, recruitment, baseline data, numbers analyzed, outcomes and estimation, ancillary analyses, adverse events. Discussion – three items on interpretation, generalizability, overall evidence.

The consort Statement for eHealth interventions describes the relevance of the consort recommendations to the design and reporting of eHealth studies with an emphasis on Internet-based interventions for direct use by patients, such as online health information resources, decision aides and phr s. Of particular importance is the need to clearly define the intervention components, their role in the overall care process, target population, implementation process, primary and secondary outcomes, denominators for outcome analyses, and real world potential (for details refer to Baker et al., 2010 ).

10.4. Case Examples

10.4.1. pragmatic rct in vascular risk decision support.

Holbrook and colleagues (2011) conducted a pragmatic rct to examine the effects of a cds intervention on vascular care and outcomes for older adults. The study is summarized below.

Setting – Community-based primary care practices with emr s in one Canadian province. Participants – English-speaking patients 55 years of age or older with diagnosed vascular disease, no cognitive impairment and not living in a nursing home, who had a provider visit in the past 12 months. Intervention – A Web-based individualized vascular tracking and advice cds system for eight top vascular risk factors and two diabetic risk factors, for use by both providers and patients and their families. Providers and staff could update the patient’s profile at any time and the cds algorithm ran nightly to update recommendations and colour highlighting used in the tracker interface. Intervention patients had Web access to the tracker, a print version mailed to them prior to the visit, and telephone support on advice. Design – Pragmatic, one-year, two-arm, multicentre rct , with randomization upon patient consent by phone, using an allocation-concealed online program. Randomization was by patient with stratification by provider using a block size of six. Trained reviewers examined emr data and conducted patient telephone interviews to collect risk factors, vascular history, and vascular events. Providers completed questionnaires on the intervention at study end. Patients had final 12-month lab checks on urine albumin, low-density lipoprotein cholesterol, and A1c levels. Outcomes – Primary outcome was based on change in process composite score ( pcs ) computed as the sum of frequency-weighted process score for each of the eight main risk factors with a maximum score of 27. The process was considered met if a risk factor had been checked. pcs was measured at baseline and study end with the difference as the individual primary outcome scores. The main secondary outcome was a clinical composite score ( ccs ) based on the same eight risk factors compared in two ways: a comparison of the mean number of clinical variables on target and the percentage of patients with improvement between the two groups. Other secondary outcomes were actual vascular event rates, individual pcs and ccs components, ratings of usability, continuity of care, patient ability to manage vascular risk, and quality of life using the EuroQol five dimensions questionnaire ( eq-5D) . Analysis – 1,100 patients were needed to achieve 90% power in detecting a one-point pcs difference between groups with a standard deviation of five points, two-tailed t -test for mean difference at 5% significance level, and a withdrawal rate of 10%. The pcs , ccs and eq-5D scores were analyzed using a generalized estimating equation accounting for clustering within providers. Descriptive statistics and χ2 tests or exact tests were done with other outcomes. Findings – 1,102 patients and 49 providers enrolled in the study. The intervention group with 545 patients had significant pcs improvement with a difference of 4.70 ( p < .001) on a 27-point scale. The intervention group also had significantly higher odds of rating improvements in their continuity of care (4.178, p < .001) and ability to improve their vascular health (3.07, p < .001). There was no significant change in vascular events, clinical variables and quality of life. Overall the cds intervention led to reduced vascular risks but not to improved clinical outcomes in a one-year follow-up.

10.4.2. Non-randomized Experiment in Antibiotic Prescribing in Primary Care

Mainous, Lambourne, and Nietert (2013) conducted a prospective non-randomized trial to examine the impact of a cds system on antibiotic prescribing for acute respiratory infections ( ari s) in primary care. The study is summarized below.

Setting – A primary care research network in the United States whose members use a common emr and pool data quarterly for quality improvement and research studies. Participants – An intervention group with nine practices across nine states, and a control group with 61 practices. Intervention – Point-of-care cds tool as customizable progress note templates based on existing emr features. cds recommendations reflect Centre for Disease Control and Prevention ( cdc ) guidelines based on a patient’s predominant presenting symptoms and age. cds was used to assist in ari diagnosis, prompt antibiotic use, record diagnosis and treatment decisions, and access printable patient and provider education resources from the cdc . Design – The intervention group received a multi-method intervention to facilitate provider cds adoption that included quarterly audit and feedback, best practice dissemination meetings, academic detailing site visits, performance review and cds training. The control group did not receive information on the intervention, the cds or education. Baseline data collection was for three months with follow-up of 15 months after cds implementation. Outcomes – The outcomes were frequency of inappropriate prescribing during an ari episode, broad-spectrum antibiotic use and diagnostic shift. Inappropriate prescribing was computed by dividing the number of ari episodes with diagnoses in the inappropriate category that had an antibiotic prescription by the total number of ari episodes with diagnosis for which antibiotics are inappropriate. Broad-spectrum antibiotic use was computed by all ari episodes with a broad-spectrum antibiotic prescription by the total number of ari episodes with an antibiotic prescription. Antibiotic drift was computed in two ways: dividing the number of ari episodes with diagnoses where antibiotics are appropriate by the total number of ari episodes with an antibiotic prescription; and dividing the number of ari episodes where antibiotics were inappropriate by the total number of ari episodes. Process measure included frequency of cds template use and whether the outcome measures differed by cds usage. Analysis – Outcomes were measured quarterly for each practice, weighted by the number of ari episodes during the quarter to assign greater weight to practices with greater numbers of relevant episodes and to periods with greater numbers of relevant episodes. Weighted means and 95% ci s were computed separately for adult and pediatric (less than 18 years of age) patients for each time period for both groups. Baseline means in outcome measures were compared between the two groups using weighted independent-sample t -tests. Linear mixed models were used to compare changes over the 18-month period. The models included time, intervention status, and were adjusted for practice characteristics such as specialty, size, region and baseline ari s. Random practice effects were included to account for clustering of repeated measures on practices over time. P -values of less than 0.05 were considered significant. Findings – For adult patients, inappropriate prescribing in ari episodes declined more among the intervention group (-0.6%) than the control group (4.2%)( p = 0.03), and prescribing of broad-spectrum antibiotics declined by 16.6% in the intervention group versus an increase of 1.1% in the control group ( p < 0.0001). For pediatric patients, there was a similar decline of 19.7% in the intervention group versus an increase of 0.9% in the control group ( p < 0.0001). In summary, the cds had a modest effect in reducing inappropriate prescribing for adults, but had a substantial effect in reducing the prescribing of broad-spectrum antibiotics in adult and pediatric patients.

10.4.3. Interrupted Time Series on EHR Impact in Nursing Care

Dowding, Turley, and Garrido (2012) conducted a prospective its study to examine the impact of ehr implementation on nursing care processes and outcomes. The study is summarized below.

Setting – Kaiser Permanente ( kp ) as a large not-for-profit integrated healthcare organization in the United States. Participants – 29 kp hospitals in the northern and southern regions of California. Intervention – An integrated ehr system implemented at all hospitals with cpoe , nursing documentation and risk assessment tools. The nursing component for risk assessment documentation of pressure ulcers and falls was consistent across hospitals and developed by clinical nurses and informaticists by consensus. Design – its design with monthly data on pressure ulcers and quarterly data on fall rates and risk collected over seven years between 2003 and 2009. All data were collected at the unit level for each hospital. Outcomes – Process measures were the proportion of patients with a fall risk assessment done and the proportion with a hospital-acquired pressure ulcer ( hapu ) risk assessment done within 24 hours of admission. Outcome measures were fall and hapu rates as part of the unit-level nursing care process and nursing sensitive outcome data collected routinely for all California hospitals. Fall rate was defined as the number of unplanned descents to the floor per 1,000 patient days, and hapu rate was the percentage of patients with stages i-IV or unstageable ulcer on the day of data collection. Analysis – Fall and hapu risk data were synchronized using the month in which the ehr was implemented at each hospital as time zero and aggregated across hospitals for each time period. Multivariate regression analysis was used to examine the effect of time, region and ehr . Findings – The ehr was associated with significant increase in document rates for hapu risk (2.21; 95% CI 0.67 to 3.75) and non-significant increase for fall risk (0.36; -3.58 to 4.30). The ehr was associated with 13% decrease in hapu rates (-0.76; -1.37 to -0.16) but no change in fall rates (-0.091; -0.29 to 011). Hospital region was a significant predictor of variation for hapu (0.72; 0.30 to 1.14) and fall rates (0.57; 0.41 to 0.72). During the study period, hapu rates decreased significantly (-0.16; -0.20 to -0.13) but not fall rates (0.0052; -0.01 to 0.02). In summary, ehr implementation was associated with a reduction in the number of hapu s but not patient falls, and changes over time and hospital region also affected outcomes.

10.5. Summary

In this chapter we introduced randomized and non-randomized experimental designs as two types of comparative studies used in eHealth evaluation. Randomization is the highest quality design as it reduces bias, but it is not always feasible. The methodological issues addressed include choice of variables, sample size, sources of biases, confounders, and adherence to reporting guidelines. Three case examples were included to show how eHealth comparative studies are done.

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Appendix. Example of Sample Size Calculation

This is an example of sample size calculation for an rct that examines the effect of a cds system on reducing systolic blood pressure in hypertensive patients. The case is adapted from the example described in the publication by Noordzij et al. (2010) .

(a) Systolic blood pressure as a continuous outcome measured in mmHg

Based on similar studies in the literature with similar patients, the systolic blood pressure values from the comparison groups are expected to be normally distributed with a standard deviation of 20 mmHg. The evaluator wishes to detect a clinically relevant difference of 15 mmHg in systolic blood pressure as an outcome between the intervention group with cds and the control group without cds . Assuming a significance level or alpha of 0.05 for 2-tailed t -test and power of 0.80, the corresponding multipliers 1 are 1.96 and 0.842, respectively. Using the sample size equation for continuous outcome below we can calculate the sample size needed for the above study.

n = 2[(a+b)2σ2]/(μ1-μ2)2 where

n = sample size for each group

μ1 = population mean of systolic blood pressures in intervention group

μ2 = population mean of systolic blood pressures in control group

μ1- μ2 = desired difference in mean systolic blood pressures between groups

σ = population variance

a = multiplier for significance level (or alpha)

b = multiplier for power (or 1-beta)

Providing the values in the equation would give the sample size (n) of 28 samples per group as the result

n = 2[(1.96+0.842)2(202)]/152 or 28 samples per group

(b) Systolic blood pressure as a categorical outcome measured as below or above 140 mmHg (i.e., hypertension yes/no)

In this example a systolic blood pressure from a sample that is above 140 mmHg is considered an event of the patient with hypertension. Based on published literature the proportion of patients in the general population with hypertension is 30%. The evaluator wishes to detect a clinically relevant difference of 10% in systolic blood pressure as an outcome between the intervention group with cds and the control group without cds . This means the expected proportion of patients with hypertension is 20% (p1 = 0.2) in the intervention group and 30% (p2 = 0.3) in the control group. Assuming a significance level or alpha of 0.05 for 2-tailed t -test and power of 0.80 the corresponding multipliers are 1.96 and 0.842, respectively. Using the sample size equation for categorical outcome below, we can calculate the sample size needed for the above study.

n = [(a+b)2(p1q1+p2q2)]/χ2

p1 = proportion of patients with hypertension in intervention group

q1 = proportion of patients without hypertension in intervention group (or 1-p1)

p2 = proportion of patients with hypertension in control group

q2 = proportion of patients without hypertension in control group (or 1-p2)

χ = desired difference in proportion of hypertensive patients between two groups

Providing the values in the equation would give the sample size (n) of 291 samples per group as the result

n = [(1.96+0.842)2((0.2)(0.8)+(0.3)(0.7))]/(0.1)2 or 291 samples per group

From Table 3 on p. 1392 of Noordzij et al. (2010).

This publication is licensed under a Creative Commons License, Attribution-Noncommercial 4.0 International License (CC BY-NC 4.0): see https://creativecommons.org/licenses/by-nc/4.0/

  • Cite this Page Lau F, Holbrook A. Chapter 10 Methods for Comparative Studies. In: Lau F, Kuziemsky C, editors. Handbook of eHealth Evaluation: An Evidence-based Approach [Internet]. Victoria (BC): University of Victoria; 2017 Feb 27.
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Comparative case studies

Comparative case studies can be useful to check variation in program implementation. 

Comparative case studies are another way of checking if results match the program theory. Each context and environment is different. The comparative case study can help the evaluator check whether the program theory holds for each different context and environment. If implementation differs, the reasons and results can be recorded. The opposite is also true, similar patterns across sites can increase the confidence in results.

Evaluators used a comparative case study method for the National Cancer Institute’s (NCI’s) Community Cancer Centers Program (NCCCP). The aim of this program was to expand cancer research and deliver the latest, most advanced cancer care to a greater number of Americans in the communities in which they live via community hospitals. The evaluation examined each of the program components (listed below) at each program site. The six program components were:

  • increasing capacity to collect biospecimens per NCI’s best practices;
  • enhancing clinical trials (CT) research;
  • reducing disparities across the cancer continuum;
  • improving the use of information technology (IT) and electronic medical records (EMRs) to support improvements in research and care delivery;
  • improving quality of cancer care and related areas, such as the development of integrated, multidisciplinary care teams; and
  • placing greater emphasis on survivorship and palliative care.

The evaluators use of this method assisted in providing recommendations at the program level as well as to each specific program site.

Advice for choosing this method

  • Compare cases with the same outcome but differences in an intervention (known as MDD, most different design)
  • Compare cases with the same intervention but differences in outcomes (known as MSD, most similar design)

Advice for using this method

  • Consider the variables of each case, and which cases can be matched for comparison.
  • Provide the evaluator with as much detail and background on each case as possible. Provide advice on possible criteria for matching.

National Cancer Institute, (2007).  NCI Community Cancer Centers Program Evaluation (NCCCP) . Retrieved from website: https://digitalscholarship.unlv.edu/jhdrp/vol8/iss1/4/

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  • Broadening the range of designs and methods for impact evaluations

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Case Studies and Comparative Analysis

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A case study is an in-depth, detailed examination of a particular case (or cases) within a real-world context. Generally, a case study can highlight an individual, group, organization, event, belief system, or action. A case study does not necessarily have to be one observation, but may include many observations (one or multiple individuals and entities across multiple time periods, all within the same case study). Comparative analysis, on the other hand, is a method that compares two or more of anything (documents, data sets, political systems etc.) – though sometimes a form of comparative analysis is used to compare two or more cases studies, demonstrating the links between these two methods. Text adapted from Wikipedia .

The resources below have been curated by the E-International Relations team. You can find more resources on our methods homepage .

Types of Case Study by Graham R Gibbs (YouTube)

Comparative Politics: What and how to compare by Patrick Theiner (YouTube)

Comparative Case Studies – Avoid bias, ensure case studies represent population, not anomalies by Delwyn Goodrick (YouTube)

Websites Writing a Case Study by PLNU (Website).

Qualitative Comparative Analysis by Wendy Olsen (Website).

Further Reading on E-International Relations

  • Qualitative, Quantitative and Mixed Methods Approaches
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  • Ethnography in International Relations
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  • Research Ethics
  • Introduction to Research Methods

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International Comparative Case Studies: Multiple Methods in Action

  • By: Roger Penn
  • Product: Sage Research Methods Cases Part 2
  • Publisher: SAGE Publications Ltd
  • Publication year: 2019
  • Online pub date: January 02, 2019
  • Discipline: Business and Management
  • Methods: Case study research , Comparative research , Multiple methods
  • DOI: https:// doi. org/10.4135/9781526467041
  • Keywords: job skills , language , paper industry , plants , publications , skilled work , teams , trade unions , United States Show all Show less
  • Online ISBN: 9781526467041 Copyright: © SAGE Publications Ltd 2019 More information Less information

This case sets out the multiple methods deployed in an international comparison of paper mills. The research involved a combination of research methods, including interviews, observations, focus groups, questionnaires, and secondary analysis. The six case studies were designed to probe existing theories concerning the relationship between technological change and skilled work and, in particular, the impact of computerization of paper manufacturing on the job skills of production and maintenance workers. The six case studies were located in Britain, Australia, and the United States, and in each plant, the same set of questions was asked, using the same combination of methods. The case outlines the complex issues surrounding access to the six mills. In particular, it focuses on the vital need to gain the agreement and confidence of both management and trade unions in order to conduct effective fieldwork. There proved to be very little existing research on the topic of paper mills in the social scientific literature. Rather, the case discusses the wide range of non-academic literature that provided useful insights into the global paper industry and the computerization of production that was underway at the time of the empirical research. The case reveals the close interplay of observation and interviews in the case studies. Both methods involve questioning the social world and were intertwined in practice throughout. The use of a semi-structured interview schedule and subsequently a more formalized questionnaire ensured that the questioning followed closely bounded parameters. The case also reveals how existing theories were modified as a result of the findings and applied in revised form in subsequent empirical research.

Learning Outcomes

By the end of this case, students should be able to

  • Understand how to undertake a case study
  • Grasp how to integrate a multiplicity of different research methods in a comparative case study
  • Understand how observation and interviewing can be combined to produce an effective and rich explanation of social phenomena
  • Understand how empirical research is both embedded within prior theoretical debates and can be used to develop new theoretical formulations

Introduction

This Case Study in Research Methods sets out the multiple methods used in an international comparison of paper mills in Britain, Australia, and the United States. The research involved the combination of a range of research methods including individual face-to-face interviews, observations in the field, focus groups, questionnaire design and implementation, and secondary analysis of relevant documents. It also involved the production of diagrams as hermeneutic devices. The case studies were designed to test existing theories as well as to contribute to the development of new theoretical explanations.

The Context

The immediate context for the development of the case study research analyzed in this Research Methods Case was my earlier research into skilled workers in the British class structure (see Penn, 1985a ). This was driven by the disjunction between the discourse of sociologists and historians as to when an homogenous “working class” could be said to have existed in Britain and when it ceased to exist as a result of the division between skilled and nonskilled workers. In that research, I had examined economic differentials between skilled and nonskilled workers since the mid nineteenth century and also how skilled work had been reproduced through mechanisms of social exclusion. This had led me into the debate about technological change and skill in the contemporary workplace at the time. In particular, I read the seminal neo-Marxist work of Braverman (1975), which argued that there was a pervasive process of deskilling underway in the contemporary workplace as a result of the advent of computerization. However, his evidence for this thesis was poor and highly tendentious.

This debate about contemporary trends in skill prompted a series of empirical investigations into skilled work that coalesced into the Skilled Worker Project at Lancaster University. These pieces of research culminated in the publication of Class, Power and Technology ( Penn, 1990a ) and subsequently Skill and Occupational Change ( Penn, 1994 ). The research included projects on the coal, metalworking, and telecommunications industries and also—centrally—the manufacture of paper which forms the basis for the present Case Study in Research Methods. Why did I undertake research into the paper industry? A major factor was its close proximity. Two mills were located within 10 miles of my home in Lancaster, and there were many other mills in the broader North West region of England.

Case Studies

The incorporation of case studies has been integral to the teaching of law and management within business schools for over a century. The use of case studies has also become a central method in the social and management sciences. They rose to prominence in the mid-20th century with the publication of seminal studies in the United States like Yankee City ( Warner & Lunt, 1941 ) and Middletown ( Lynd & Lynd, 1957 ). Subsequently, case studies became prominent in the development of economic sociology in Britain with the publication of the Affluent Worker series ( Goldthorpe, Lockwood, Bechhofer, & Platt, 1968a , 1968b , 1969 ) set in three factories in Luton and later within Gallie’s (1978) In Search of the New Working Class , which was located in four oil refineries, two in Britain and two in France.

Case studies rely on both quantitative and qualitative evidence (see Yin, 2004, p. xv) and embody a set of multiple methods that can only be determined within the process of the actual empirical research itself (see George and Bennett, 2005 ). Case studies can involve single or multiple cases ( Bartlett & Vavrus, 2017 ; Yin, 2004). They can also involve comparisons within countries (which was the case in the Social Change and Economic Life Research Initiative in Britain in 1985) or comparisons across countries, as exemplified by Gallie (1978) . As Hantrais and Mangen (1996) put it,

for the study to be cross-national and comparative, individuals or teams should set out to study particular issues or phenomena in two or more countries with the express intention of comparing their manifestations in different socio-cultural settings, using the same research instruments. (p. 1)

A case study is an “in-depth, multifaceted investigation conducted in great detail and relying upon a variety of data sources” (see Feagin, Orum, & Sjoberg, 1991 , p. 2). It involves an examination of social phenomena in detail and in context. Case studies allow the grounding of observations and concepts about social patterns within natural settings. They also permit and facilitate theoretical innovation and generalizations. Indeed, case studies are central to the development of what Glaser and Strauss (1967) termed “grounded theory” and involve a dialectical methodology where research questions and evidence interact and interplay in the comparison of rival abstract theories. They involve multiple styles of empirical research (see George and Bennett, 2005 ) and centre upon the “triangulation of results from different sources” (see Yin, 2014 , p. 241).

Case studies can be used to examine and also to help generate new theories of how the social world is organized. Unlike the natural sciences, social scientists rarely conduct classic controlled experiments to test for the impact of one factor on a specific outcome. Rather, they probe the world as it is naturally constituted and structured and ascertain the impact of a variety of social factors upon specific outcomes in the social world.

The Empirical Research

The study of technological change and job skills in the paper industry had two phases. The first involved three case studies of local paper mills in England—James Cropper’s of Burneside, Henry Cooke’s in Beetham, and Thames Board in Workington (see Penn & Scattergood, 1985 ). The focus was on changes in technology and job skills in the main production processes at the three mills. These were examined between 1970 and 1984. Such a recent historical time frame was manageable as respondents could—in the main—remember the production process at the earlier date and make informed comparisons between that earlier time and the contemporary era in 1984. The second phase of the research involved returning to all three of these original plants and probing technical change and job skills in greater detail and also extending the research to two paper mills in Australia and one in the United States (see Penn & Scattergood, 1988 ). The Australian research conducted in the autumn of 1984 was funded by a grant from the Australian Studies Centre and the American research took place during a sabbatical at UC Berkeley in the spring of 1985. This was supported by a grant from the Lancaster University Research Fund to assist research on skilled workers in the United States. In each of the six case studies, the same set of questions was asked, using the same array of methods.

The two phases of the research were designed to probe the competing theories about the putative effects of technological change on job skills. These were grounded in the sociological literature at the time and could be seen as mutually exclusive. The first was the “deskilling” thesis associated with Braverman and, more widely, with neo-Marxism. This argued that technical change produced decreasing levels of skill over time. The counter-theory was the “skilling” thesis associated with post-industrialism and human capital theory which posited a general increase in levels of skill associated with technical change in the twentieth century. Much of this debate revolved around the putative effects of computerization which was growing rapidly in workplaces during the 1980s.

It was essential to gain access to the plants that formed the cornerstone of the empirical research. In the first phase of the research in Britain, letters were sent initially to the managing directors of the three firms. These were sent by post on university-headed paper and outlined the basic parameters of the proposed research and sought a meeting to discuss the research more fully. These proved successful and the research team undertook preliminary interviews and observations of the production process at each of the three plants. Each mill produced a different product. Cropper’s manufactured colored paper and card, Thames Board produced glossy carton board that ended up in the outer packaging of cereal and soap powder boxes and Henry Cooke’s made specialty papers used in the packaging of frozen foods.

Each of the three plants was unionized. Indeed, at each factory, there was more than one trade union represented. The cooperation of these unions was also sought as we proposed to observe and also interview the workforce. Without the cooperation of the unions, the research would have not been possible. Each union was contacted by letter. In the case of the Amalgamated Engineering Union (AEU), the letter was sent to their District Secretary in Barrow and his agreement received by letter. In the cases of the Electricians’ Union (Electrical, Electronic, Telecommunications and Plumbing Union [EEPTU]) and the Paperworkers’ Union (Society of Graphical and Allied Trades [SOGAT]), it proved necessary to visit their respective headquarters to gain their approval. This was achieved successfully in each case, but the process took several months. Without this approval it would have proved impossible to conduct the fieldwork as we were constantly asked by the workforce if their union had agreed to our research.

Similar methods were used to gain access to the two paper mills researched in Australia. Letters were sent to the managing directors at Australian Paper Mills (APM) in Botany Bay and Australian Newsprint Mills (ANM) in Albury. The letters outlined the proposed comparative research and included a copy of the earlier U.K.-based research for their information. The relevant trade unions were also contacted and a series of meetings with them organized. After positive responses from all parties, fieldwork was undertaken in the autumn of 1984. Access to the James River plant in Halsey Oregon was facilitated by Professor Sally Hacker from the Sociology Department at Oregon State University. She contacted the plant prior to my visit to Corvallis and enclosed a copy of the U.K. research report to provide the context for the U.S. stage of the proposed comparative research.

Literature Review

A central part of any research project involves a literature review of pertinent previous work (see Fink, 2013; Ridley, 2008 for the best texts on how to undertake an effective literature review). However, there was very little literature directly pertinent to the paper industry itself: most literature dealt with the more general issues of technical change and the division of labour. A wide range of specialist industry publications were consulted. These included National Economic Development Office Reports as well as the monthly trade journal Paper and the annual Paper: Review of the Year. Documents were collected from the companies researched (including annual reports to shareholders) and from the various trade unions, including the National Graphical Association’s “The Way Forward” as well as a copy of the agreement on “Programmable Logic Controllers” at APM in Botany Bay. I also attended an industry-based conference on automation which led to the publication of my presentation in the specialist journal Automation in 1985.

Observation

A core method of the research involved observation of production processes in the six paper mills. These were combined with interviews or, more precisely, detailed context-specific intensive questioning of what was being observed. A paper mill is a very large physical environment with enormous machines manufacturing paper and board. One area of production was a great puzzle initially, and this involved the mixing of dyes to produce colored paper and board at Cropper’s. The skilled workers in this crucial area of the plant were called beatermen (they were all men). Computers had been added to the working environment over recent years, but it took the research team a long time to understand this process. This was partly because these skilled workers were not keen to divulge too much initially about the recipes that they used to achieve a color match. Halle (1987) described similar reticence among chemical worker in his study America’s Working Man . The other factor in our puzzlement was our initial failure to grasp the distinction between computerized monitoring and computerized control of production processes. Computerized control involves computers automatically adjusting the production process as a result of information received from sensors embedded within the machinery itself. None of the six mills had such systems. Rather, they employed computerized monitoring systems. These provided information for skilled production workers on how the production process was functioning but—critically—these same workers were required to decide which adjustments to make themselves. In the case of color blending, the new computerized system provided information on whether the color mix was more or less the same as the template color desired. However, it did not provide any guidance on what to do when there was a mismatch. The research team discovered that dyes could vary in color: one barrel of vermillion could well be different from another. We also discovered that different batches of pulp would react differently to the same dyes. Finally, it became clear (albeit belatedly) that each beaterman had a different idea on which combination of dyes should be added to generate a change in the mix. This information had been hard won by the research team and the result of extensive engagement with these specialist skilled workers that had involved both detailed observations and prolonged questioning over a succession of visits in the field.

The other central method used in the six case studies of paper mills in Britain, Australia, and the United States was interviewing (the best current guide to interviewing remains Arksey & Knight, 1999 ). These ranged in form. The initial phase of each of the six case studies entailed open-ended, unstructured interviews with senior managers and trade union officials in order to secure access for the subsequent fieldwork. These always took place at their places of work, and it was important to dress appropriately for these preliminary interviews which, at that time, meant a suit or a jacket and tie. The interviews were open-ended and designed to explain the nature of the proposed research. Clearly, being a university academic helped in all cases and the first report on the British phase of the research assisted in obtaining access to the Australian and American plants.

Subsequent interviews were also open-ended and lasted between 40 and 180 min. However, they were semi-structured and based upon a set of questions that had been formulated by the research team, but these interviews were also free flowing and covered many other topics as well. The interviews were recorded and notes taken during them as well. This was part of the wider process of understanding the language of descriptions used within the industry. The schedule meant that each interview produced a set of answers that could be compared across cases and, by extension, across countries.

Focus Groups

The research used two focus groups to probe the issues surrounding technical change and the division of labour in greater depth (see Kreuger & Casey, 2014 ; Morgan & Kreuger, 1997 for the best guides to focus groups). Focus groups have many advantages. They are particularly useful for probing group attitudes, feelings, and beliefs. Both focus groups were hybrid in the sense that the two groups had been organized by management at Cropper’s and Thames Board respectively. The first, at Cropper’s involved a group of 10 production workers who were attending a course in the company’s training suite and lasted 2 hr. The research team was invited to sit in and observe this meeting, and then, we were allowed to participate in the group discussion and ask our own questions. Notes were taken during these discussions and typed up immediately afterwards. The second involved a group of 16 employees at Thames Board and lasted from 9.30 am to 4 pm. The central aim of the meeting was to introduce the workforce to a new style of management and working called “Total Quality Management.” The team was invited to participate in this meeting, and once again extensive notes were taken.

Both hybrid focus groups provided insights into the everyday language of descriptions prevalent within the two firms. The central advantage of these focus groups was that it helped the research team understand the issues of technical change and job skills within the paper industry as perceived by the workforce itself. They also provided an insight into the everyday language used to discuss these topics. Indeed, it provided a route into the wider language of the organization. Every organization has a set of codes to describe that organization which can prove obscure to outsiders. In my own work, I had encountered this in several pieces of research I had conducted. The first involved participant observation among telephone maintenance technicians (see Penn, 1991b). The language that they used to describe British Telecom and their jobs was opaque to put it mildly. Part of any successful fieldwork involves the researcher “learning the language of descriptions” (see Garfinkel, 1967 ). I experienced very similar issues when I researched the changing skills of coal miners (see Penn & Simpson, 1986 ). I spent a great deal of time in discussions with miners about the occupational system at the time of the research as well as in previous periods. This proved extremely complicated to achieve.

These two hybrid focus groups raised a wide range of issues that were probed in more detail subsequently by the research. Of particular interest were the debates between members of the workforce over issues of skill and demarcation. Clearly, there was considerable anxiety surrounding both technical change and new styles of management as well as fear concerning the putative effects of computerization on working practices and job skills.

Questioning the Social World: The Interplay of Observation and Interviews

The two core methods used in these six case studies involved observation and interviews. However, the two methods were closely entwined in practice. When observing the production process in a paper mill, a series of questions arose that were posed to the workforce. This was somewhat intrusive, but generally, the research team discovered that most of the workforce was more than happy to discuss what was going on. At the beginning, our questions were overly general and rather abstract, but as we learned the linguistic codes used within the industry and also the language used to describe the occupational system, our questions became much more specific. The research involved a continuous questioning of participants in the workplace and an interplay between observations and interviews. This was particularly evident in Australia and the United States. Indeed, Professor Sally Hacker who accompanied me on my visit to the paper mill in Halsey, Oregon, was kind enough to recognize this subsequently at the annual meeting of the American Sociological Association in Chicago in 1987 when she spoke about how the workforce had reacted positively to my detailed questions. Gaining such proficiency, knowledge, and confidence took time. It is an iterative process that can only be learned in the field through the actual process of detailed questioning itself. It very much involves trial and error. This dialectical learning process led directly to the discovery of a range of key conceptual findings that became integral to the Skilled Worker Project and to wider debates in economic sociology.

The first involved the critical distinction between production and maintenance skills. The effects of computerization on these two areas of work were distinctive and should not be elided. In general terms, computerization of production processes generates more skilled maintenance workers and fewer skilled production workers. Clearly, some occupational groups gain numerically while others do not. If the two groups are conflated and combined, then the overall effect will be zero! This central finding rendered the traditional focus of industrial sociology exclusively on production workers obsolete and potentially highly misleading. Given that production workers in paper mills are generally organized in separate trade unions to maintenance workers, technical change will also impact asymmetrically on industrial relations within plants. This was evident across all six case studies in the three countries.

The second important discovery made as a result of the interplay of observation and interviews involved the two trajectories into skilled work evident in all six mills. Maintenance workers such as electricians and fitters had all undergone traditional apprenticeships lasting at least three years in their late teens. This formed the core basis for their skilled status. Skilled production workers such as machinemen and beatermen experienced a very different path into skilled work. They progressed along an internal career ladder that culminated in their skilled status and pay. This could take between 10 and 20 years to achieve and was identical in all three countries. This discovery led to the realization that many other industries had a similar bifurcated structure to skilled work. These included steel, coal, and textiles. This insight transformed the debate about skilled workers away from a narrow focus on apprenticed workers (see Penn, 1994 ). These differing trajectories of skilled work were central to the internal discourse about skill and relative pay within these paper mills. Skilled maintenance workers with apprenticeship qualifications were reluctant to accept the claims of skilled production workers to an equivalent “skill” in all six mills.

The interplay of observation and interviews was also evident in the development of our understanding of the technologies that had been implemented in each of the mills. This took some time as the team did not know a great deal initially about these details. Fortunately, only a small number of firms manufacture papermaking machinery and even fewer provide the computer systems that are bolted onto these machines. Once again, the interplay of observation and interviews led the team to develop an expertise in these areas that facilitated a deepening of the overall research. We discovered that not only were maintenance skills increasing in terms of the numbers of skilled maintenance workers employed over time but that there was an asymmetry in these developments. There had been an increasing premium on electronic skills but less in terms of mechanical skills. This affected electricians and mechanics directly and had led to a range of similar demarcation disputes in the three countries. These had occurred irrespective of whether the skilled trades were in separate or the same trade unions. Once again the deep-seated, taken-for-granted assumptions of industrial sociology were challenged by these empirical findings: none of which would have been possible without the combination of observation and interviews.

The final important discovery was the intermittent use of skill. Much of the time skilled production and skilled maintenance workers would be scanning the large number of computer monitors which provided continuous information about the ongoing manufacturing processes. In some respects, it might have appeared as if they were doing very little, but in fact, they were assessing how the machinery was functioning. Only when problems began to emerge did the various skilled workers jump into action. Given the intermittent nature of these episodes, considerable time in the field was necessary to capture and interpret these phenomena.

Questionnaires

The research also made some use of questionnaires in its second phase. These questionnaires were formalized versions of the initial schedule of questions used during the semi-structured interviews in the first phase. In both instances, the main aim was to ensure that the same sets of questions were asked at each of the six plants and the same information collected in order to facilitate comparisons across the case studies. Such a structure to questioning in comparative case study research is an essential part of organizing such research and serves to make the data collection manageable.

The research team created a diagram titled “The Production of Paper” (see Penn & Scattergood, 1985 , p. 627) as a heuristic device to represent the production process in a paper mill in a simplified form and to complement the written analyses. In particular, the diagram provided a visual guide to the location of the various occupations within the overall production process. Nowadays, it would probably prove possible to take photographs of the production process and the various types of work associated with papermaking, but the diagram would still provide a useful guide to the phenomena analyzed in the six case studies ( Figure 1 ).

Figure 1. The production of paper.

Figure

Theoretical Developments

The case studies were designed to probe the competing theories of the relationship between technical change and the division of labour within the broader sociological literature. The compensatory theory of skill had been devised during the early phases of the British fieldwork and was probed extensively in the two published analyses. The compensatory theory of skill suggested that “technical change generates both skilling and deskilling” ( Penn & Scattergood, 1985 , p. 615) and that “technological changes tend to deskill direct production roles but put an increased premium on a range of ancillary tasks that are associated with the installation, maintenance and programming of automated machinery” ( Penn & Scattergood, 1985 , p. 616). The case studies probed this theory in detail and concluded that “technical change did generate positive effects on skill but not much in the way of deskilling” ( Penn & Scattergood, 1985 , p. 625). As a result of these findings, the compensatory theory of skill was modified for subsequent research and extended to include clerical and secretarial workers as well (see Penn, 1994 ). The development of theory progresses best with the interplay of empirical research findings and conceptual reformulations.

Practical Lessons Learned

The main lessons of this case study involved the importance of integrating a wide range of different research methods and techniques for the successful implementation of comparative case study research. The central methods involved interviews and observations. These were supplemented with questionnaires and secondary research as well as literature searches. In each of the six case studies, the same set of questions was asked, deploying the same combination of methods. The data collected from observations and interviews were triangulated to develop the overall interpretation. Indeed, the two core methods were intertwined within the fieldwork itself. The research process was iterative and cumulative. A central feature of the research involved translating the industrial and occupational language used routinely within the paper industry globally into a more general language of descriptions suitable for non-specialists and more generally for use within economic sociology.

Exercises and Discussion Questions

  • 1. How important are observations for understanding how workplaces function?
  • 2. How can researchers learn the “language of descriptions” within a case study of a specific organization?
  • 3. What sort of visual data could be integrated into a comparative case study like the one analyzed? How would it improve the analysis?
  • 4. How could extending the comparative research outlined in this case to countries where English is not the first language be developed?

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Lab 2 - ST 352

  • Study Protocol
  • Open access
  • Published: 20 February 2024

The PEP++ study protocol: a cluster-randomised controlled trial on the effectiveness of an enhanced regimen of post-exposure prophylaxis for close contacts of persons affected by leprosy to prevent disease transmission

  • Duane C. Hinders 1 ,
  • Anneke T. Taal 1 ,
  • Suchitra Lisam 2 ,
  • Aymée M. da Rocha 3 ,
  • Nand Lal Banstola 4 ,
  • Prativa Bhandari 4 ,
  • Abhijit Saha 5 ,
  • Jugal Kishore 6 ,
  • Virginia O. Fernandes 7 ,
  • Abu Sufian Chowdhury 5 ,
  • Anna T. van ‘t Noordende 1 ,
  • Liesbeth Mieras 1 ,
  • Jan Hendrik Richardus 8 &
  • Wim H. van Brakel 1  

BMC Infectious Diseases volume  24 , Article number:  226 ( 2024 ) Cite this article

Metrics details

Leprosy is an infectious disease with a slow decline in global annual caseload in the past two decades. Active case finding and post-exposure prophylaxis (PEP) with a single dose of rifampicin (SDR) are recommended by the World Health Organization as measures for leprosy elimination. However, more potent PEP regimens are needed to increase the effect in groups highest at risk (i.e., household members and blood relatives, especially of multibacillary patients). The PEP++ trial will assess the effectiveness of an enhanced preventive regimen against leprosy in high-endemic districts in India, Brazil, Bangladesh, and Nepal compared with SDR-PEP.

The PEP++ study is a cluster-randomised controlled trial in selected districts of India, Brazil, Bangladesh, and Nepal. Sub-districts will be allocated randomly to the intervention and control arms. Leprosy patients detected from 2015 − 22 living in the districts will be approached to list their close contacts for enrolment in the study. All consenting participants will be screened for signs and symptoms of leprosy and tuberculosis (TB). In the intervention arm, eligible contacts receive the enhanced PEP++ regimen with three doses of rifampicin (150 − 600 mg) and clarithromycin (150 − 500 mg) administered at four-weekly intervals, whereas those in the control arm receive SDR-PEP. Follow-up screening for leprosy will be done for each individual two years after the final dose is administered. Cox’ proportion hazards analysis and Poisson regression will be used to compare the incidence rate ratios between the intervention and control areas as the primary study outcome.

Past studies have shown that the level of SDR-PEP effectiveness is not uniform across contexts or in relation to leprosy patients. To address this, a number of recent trials are seeking to strengthen PEP regimens either through the use of new medications or by increasing the dosage of the existing ones. However, few studies focus on the impact of multiple doses of chemoprophylaxis using a combination of antibiotics. The PEP++ trial will investigate effectiveness of both an enhanced regimen and use geospatial analysis for PEP administration in the study communities.

Trial registration

NL7022 on the Dutch Trial Register on April 12, 2018. Protocol version 9.0 updated on 18 August 2022 https://www.onderzoekmetmensen.nl/en/trial/23060

Peer Review reports

Leprosy, or Hansen’s disease, is an infectious disease caused by Mycobacterium leprae [ 1 ]. Although the transmission is not fully understood, the main mode is human-to-human via respiratory aerosols through coughing and sneezing. Prolonged and frequent close contact with an infectious person who has not started treatment is necessary for transmission [ 1 , 2 ]. Therefore, individuals living in the same household as a person affected by the disease, neighbours and other family members are at a higher risk of being infected [ 2 ].

In 2022, the number of new leprosy patients reported globally was 174,087. The majority of the world’s leprosy patients (78%) live in three countries: India (60%), Brazil (11%) and Indonesia (7%). An additional 17% come from the next 20 global priority countries, including Bangladesh and Nepal [ 3 ]. Between 2010 and 2019, the annual decrease in new leprosy cases globally was a modest 2% per year [ 4 ]. Therefore, new interventions, such as more precise active case finding and chemoprophylaxis, are essential to reduce the global caseload.

Trials to study the effectiveness of chemoprophylaxis to prevent leprosy have been conducted for decades. The first successful leprosy chemoprophylaxis trials were conducted with dapsone administered weekly or biweekly for months or years with limited effectiveness [ 5 ]. More research was required for more powerful single dose regimens. Rifampicin (RMP), recognised as the most effective bactericidal agent against M . leprae , was subsequently researched [ 6 ]. A single dose of rifampicin as leprosy post-exposure prophylaxis (SDR-PEP) was administered to close contacts of leprosy patients to prevent the disease in several studies [ 7 , 8 , 9 ].

The effectiveness of SDR-PEP as chemoprophylaxis was most firmly established in COLEP, a randomised, placebo-controlled, double-blind trial in Bangladesh [ 7 ]. The COLEP study found an overall reduction in leprosy incidence of 57% among contacts in the intervention group in the first two years [ 10 ]. Feasibility and acceptability of implementing SDR-PEP in routine leprosy control programmes was investigated thereafter in eight countries in the leprosy post-exposure prophylaxis (LPEP) programme [ 8 , 11 ]. As a result of these successful studies, the screening of close contacts of new leprosy patients combined with administration of SDR-PEP has been included in the World Health Organization (WHO) Guidelines for the Diagnosis, Treatment and Prevention of Leprosy [ 12 ]. Despite the overall protective effect of 57%, it was much lower among blood-related contacts and household members of multibacillary (MB) leprosy cases [ 10 ]. Therefore, a more potent post-exposure prophylaxis (PEP) regimen is needed to prevent disease especially among those at greater risk of developing the disease.

In 2016, NLR developed the idea for a large multi-country trial testing the effectiveness of an enhanced PEP regimen to significantly reduce the new case detection and stop the transmission of leprosy. An international expert meeting recommended a regimen consisting of three doses of a combination of two highly bactericidal and accessible antibiotics: RMP and moxifloxacin (MXF) for adults and RMP and clarithromycin (CLR) for children [ 13 ]. In 2018, however, the European Medicines Agency (EMA) restricted the use of MXF as preventive treatment because of potential long-lasting and disabling side effects. In response to these restrictions, leprosy experts recommended to use the combination of RMP and CLR for both adults and children. This combination therapy using repeated doses has been tested in a nude mouse model [ 14 ]. Results showed that the PEP++ combination (RMP/CLR) has a greater effect compared to any single antibiotic. This increased effectiveness has not, however, been tested in human populations in endemic countries to date. In this trial, we hypothesise that the leprosy incidence will be reduced more substantially in areas where the enhanced regimen is administered, thus demonstrating the effectiveness of the enhanced regimen.

Methods and design

The primary objective of the PEP++ randomised controlled trial (RCT) is to provide evidence of the effectiveness of an enhanced post-exposure prophylaxis regimen (PEP++) compared to the currently recommended regimen of SDR-PEP. Each study district will have an adverse events committee to monitor the frequency and severity of such events in each study arm and ensure participant safety.

Secondary study objectives seek to provide evidence of:

The acceptability and cost-effectiveness of PEP++ as a preventive intervention

The accuracy of geospatial methods to identify target areas for blanket campaigns, and

The effectiveness of community education and behaviour change (CEBC) interventions to change the perception of leprosy and reduce stigma

Study design

The study will use a cluster-randomised non-blinded controlled trial design with two arms to compare the effectiveness of three doses of RMP/CLR (the PEP++ regimen) with SDR-PEP in the prevention of leprosy disease among contacts of newly diagnosed leprosy patients. The randomisation units will sub-district divisions in each country context that will be randomly allocated to the two study arms.

All eligible leprosy patients in the districts will be asked to enumerate their close contacts. These individuals will subsequently be approached and enrolled in the study. Those contacts who provide informed consent are screened for signs of leprosy and tuberculosis and for inclusion eligibility. Contacts of leprosy patients living in the intervention arm receive the PEP++ regimen while those in the control arm receive SDR-PEP. All participants included in the study will be followed up two years after receiving the final dose of PEP++ or SDR-PEP.

The residences of the leprosy cases approached for the study will be geocoded in order to develop epidemiological maps that identify clusters of leprosy cases. After the regimen trial intake is concluded, blanket campaigns with SDR-PEP will be implemented in these clusters (high-risk areas) to reduce leprosy incidence at the population level. The study schedule is presented in Fig.  1 . A checklist of Recommendations for Clinical Intervention Trials (SPIRIT) is also available (Supplementary file 1 ).

figure 1

Study schedule of enrolment, interventions, and assessments

Study setting

This study will be conducted in two districts in India, Brazil, and Bangladesh and three districts in Nepal. Together these four countries accounted for 128,727 new leprosy cases in 2022, or 73.9% of the global caseload of 174,087 [ 3 ]. The districts/municipalities were selected per country based on the number of new leprosy cases detected in recent years, availability of contact screening and diagnostic services for leprosy, and logistical feasibility. For ease of study implementation and operational considerations, the districts are located in a single state or province in each country. A mix of urban, rural, and peri-urban settings was sought in order to show the replicability of the intervention across contexts in the future.

Participants

In this trial, we approach recently detected leprosy patients (index cases) as derived from leprosy programme registries in the four countries. The total number of new leprosy cases per study site is presented in Table  1 . These patients must have been detected in 2015 or later, give informed consent to participate in the study, and be willing to list their close contacts. The target population for preventive treatment is comprised of household contacts, family members, neighbours, and other social contacts (jointly denominated as ‘close contacts’) as listed by the index cases. These contacts are individuals who have had intensive contact with a leprosy patient for approximately 20 h per week during at least three months in the year before the index case was diagnosed. From previous studies, it is expected that approximately 20 close contacts per index case will be listed, depending on the study setting. All close contacts listed by an index case and located by the research staff are enrolled in the study with a unique identification code (UIC) and receive information on the study.

The contacts who consent to participate in the trial will first be screened by the research staff for signs and symptoms of leprosy and tuberculosis (TB) and checked for eligibility criteria. Exclusion criteria for the administration of preventive treatment are refusal to provide informed consent, a history of liver, renal or cardiac disease or a known allergy to RMP and/or CLR. Contacts are also temporarily ineligible if: pregnant or breastfeeding, under the age of two years, received RMP for any reason in the last two years or using contraindicated medicines for non-chronic use. If these conditions change during the trial intake period, they may still be included in the study. In the presence of any possible signs of leprosy, the participant will be referred to the closest qualified health centre for confirmation of diagnosis. Those who are confirmed as a new leprosy case are subsequently requested to list their close contacts for enrolment in the study.

Randomisation

The allocation of intervention and control arms in the countries has been done blindly using stratified randomisation. For each country, the randomisation unit has been determined via consultation with local government officials and project staff. This resulted in the use of territories/neighbourhoods in Brazil, blocks in India, municipalities in Nepal and unions in Bangladesh. These randomisation units were divided into two strata based on the number of clusters and the number of cases in clusters (based on geospatial analysis results with data from 2015–2020) followed by random sampling into intervention or control arms.

Sample size

The calculation of the sample size is based on the primary objective to find differences in new case detection rates (NCDR). The first is a difference in NCDR in the population in the intervention area after four years, compared to the baseline rate in 2019. The year 2019 is selected as the baseline to avoid any effect of the COVID-19 pandemic. The second is the difference in incidence rates in the contact groups between the close contacts who have received PEP++ and controls who have received SDR-PEP.

The sample size calculation for the difference in rates in the close contacts is based on the NCDR found in contacts in the COLEP trial sample. The NCDR in the SDR intervention group was 291/100,000 over 2 years, or an annual rate of 146/100,000. To reduce this rate by 50%, using a power of 90%, a significance level of 0.05, design effect of 1.5, correction for non-eligibility of 25% and loss to follow-up of 25%, we aimed to enrol 202,360 close contacts. This should result in giving PEP to at least 162,000 participants.

Outcome measures

The primary outcome measures of the trial will be the number of new leprosy cases detected, the number of child cases detected, and the incidence rate ratios of each arm compared with 2019 baseline. These will be measured at the two-year follow-up of the trial. In addition, the cost-effectiveness and acceptability of PEP++ as a preventive intervention will be measured as separate side studies. The added value of geospatial methods will be measured by the proportion of new leprosy cases in clusters and non-clusters.

Intervention implementation

Post-exposure prophylaxis will be offered to all eligible participants. Those in the intervention arm will receive three doses of RMP/CLR (PEP++ regimen) with four-week intervals. To increase the acceptability and reduce the potential adverse events, extended-release clarithromycin will be offered where available for purchase. An additional four-week tolerance exists for each repeated dose so that an interval of eight weeks between doses is valid. Participants in the control arm will receive SDR-PEP. The medication dosages of the PEP++ and SDR-PEP regimens per age group are presented in Table  2 . Both regimens will be provided only under supervision of the research staff and/or medical officers. The date, dosage and type of PEP will be recorded for each eligible person in the study.

The risk of inducing rifampicin resistance in M. leprae or M. tuberculosis after providing a single dose of rifampicin is considered negligible because only repeated doses of a single antibiotic will increase the risk of resistance [ 15 ]. Moreover, participants that have received rifampicin in the last two years or that show any signs or symptoms of TB or leprosy will not receive PEP. Contacts confirmed to have TB or leprosy will be treated according to the national guidelines.

Leprosy perception

A person’s perception of leprosy can negatively affect health-seeking behaviour and the acceptance of new interventions [ 16 ]. Therefore, contextualised community education and behaviour change (CEBC) materials are developed as part of the study to change the perception (knowledge, attitudes, beliefs, and emotions) regarding leprosy and reduce stigma, as well as to increase the community acceptance of preventive treatment. First, a leprosy perception study was conducted in each country to investigate the perceptions of leprosy patients, contacts, community members and health workers regarding leprosy, i.e., the way people see leprosy, what they know about leprosy and their attitudes, beliefs and reported behaviour towards persons affected by leprosy [ 17 , 18 ]. A mixed-method approach will be used to measure the perception, including in-depth interviews, focus group discussions (FGDs), the knowledge, attitudes, and practices (KAP) tool, the Explanatory Model Interview Catalogue Community Stigma Scale (EMIC-CSS) and the Social Distance Scale (SDS). During a workshop, leprosy affected persons and other key stakeholders will use the outcomes of the perception study to develop messages for the CEBC materials. The CEBC materials will be distributed throughout the implementation areas and piloted before the start of the trial [ 19 ].

Geospatial methods

Prior to the trial implementation, geospatial analysis was done to develop epidemiological maps and determine the target areas for blanket campaigns. The latitude and longitude of all patient’s residents registered from 2015 to 2021 were collected using the mobile application MapitPro (version 7.6.0). All data points were checked for clustering in open-source Quantum Geographic Information System (QGIS) version 3.4.1 (QGIS Developer team, Madeira (2018)). A contextualised spatial analysis approach was developed to identify small and precise clusters in each implementation area. This approach included non-statistical geospatial methods combined with expert consultation. During the expert consultations, country-specific definitions of a cluster were determined considering the local context [ 20 ].

  • Blanket campaigns

As predicted by mathematical modelling, a larger reduction in new cases detected can be achieved by implementing additional blanket campaigns in the identified clusters. For each index case in a cluster, the households not listed as close (neighbour) contacts within a radius of approximately 100 m will be visited until 80 to 100 participants (blanket contacts) are included in the study. If this results in over 80% of the cluster area being covered, then the entire population will be invited for participation. These blanket contacts are, similar to the close contacts, asked for consent to participate in the trial, screened for signs and symptoms of leprosy and when eligible, are provided SDR-PEP.

Data collection

Data collection will be done offline using the Research Electronic Data Capture (REDCap) system created at Vanderbilt University in the United States. Specific forms and modules were developed by the study teams, translated to the local languages, and downloaded to tablets and smartphones for field usage. First, a unique identification code (UIC) will be created for each close contact in the trial to anonymise the data. The UIC is linked to the index case and will be used to link the different data collection forms that will be created for each contact. Contacts are then visited at home and asked to sign a consent form if they are willing to participate. Disclosure of the identity of the index case is avoided whenever possible when approaching neighbours and social contacts.

From all contacts, we will collect demographic data (e.g., name, age, gender), information on the relationship with the index case and the results from the screening and eligibility questions in the close contact registration form. The date and dosage of the PEP administered is recorded in either the SDR-PEP form or PEP++ forms (i.e., first, second and third dose). Moreover, any side effects or adverse events due to SDR-PEP or PEP++ will be registered in the adverse event form. During the trial, the GPS coordinates of all participants and new leprosy patients will be collected to determine the spatial effectiveness of PEP. all case records and GPS data are stored temporarily on the mobile study devices and uploaded daily to a national server in each country.

Data analysis

Data from the PEP++ trial will be analysed primarily through quantitative methods using descriptive analysis for all variables. Table 3 outlines the tools to be used to measure and analyse the study outcomes.

Dissemination

Study outcomes are expected to be applicable for wider replication and scaling up throughout the four study countries, as well as in other countries with highly endemic regions. The national and international study teams will write extensively on the outcomes of the study. All publications will go before a project publications committee with the approval of the local Principal Investigator before submission to open-access, peer-reviewed journals. It will also be well represented in international congresses and events by the study teams in the four countries involved. Communications with the WHO and relevant Ministries of Health will take place throughout the project with the long-term sustainability of the approach in mind.

Although SDR-PEP distribution to household contacts is currently the standard WHO-recommended preventive treatment for leprosy, it may not be sufficient to stop leprosy infection in contacts who are already incubating leprosy disease. In the COLEP trial, the effectiveness of SDR-PEP was lowest among blood-relatives and household contacts [ 10 ]. To meet the needs of this group, recent studies with stronger regimens and/or different antibiotics have been conducted or are ongoing. The PEOPLE project in the Comoros and Madagascar assessed the effectiveness of a single double dose of rifampicin (SDDR) among household contacts [ 21 ]. Preliminary study data show that SDDR is effective in reducing the risk of leprosy even among household contacts and also at the population level (Hasker et al., accepted for publication). However, the effectiveness was still limited and the authors suggested that other stronger regimens should be tested. Therefore, the same study group is currently evaluating the effectiveness of a new enhanced PEP regimen consisting of bedaquiline and rifampicin in a four-year trial in the Comoros [ 22 ]. Bedaquiline is a more potent and longer acting antibiotic, which is used for latent TB infection and multidrug resistant pulmonary TB. It has not been used as leprosy preventive treatment before and is therefore undergoing a series of drug trials as part of this study. Rifapentine is another potent and longer-acting antibiotic that has been known as a promising candidate in the fight against leprosy for many years. A recent study in Southwest China showed that a single dose of rifapentine reduced the cumulative incidence of leprosy among household contacts by 84% compared with an untreated control group. It was considerably more effective than single-dose rifampicin in the target group [ 23 ]. If made available at affordable rates in all leprosy endemic countries, these powerful bactericidal agents offer hope of better single-dose protective regimens in the future.

Nevertheless, the study by Lenz et al. (2020) of M. leprae -infected nude mice showed that four multi-drug, multi-dose regimens were more effective to stop bacterial growth than any single-dose intervention, even those using multiple antibiotics with rifapentine [ 14 ]. The team concluded that ‘multi-dose PEP may be required to control infection in highly susceptible individuals with subclinical leprosy to prevent disease and decrease transmission.’ The PEP++ trial seeks to provide evidence to back up these laboratory findings and show that an enhanced multi-dose regimen of existing antibiotics is a powerful tool to reduce the risk of leprosy across a range of health systems under real-life field conditions.

Finally, several studies show that targeting the households of leprosy patients only is insufficient to stop transmission [ 10 , 21 , 24 ]. Community members within a 100-m radius of the leprosy patient’s house are also at a higher risk to develop leprosy. Targeted population-wide approaches or focal mass drug administration campaigns are therefore also needed. Little evidence has been published on the impact and cost-effectiveness of these approaches. The five-islands study in Indonesia by Bakker et al. (2005) compared a population-wide SDR-PEP approach with a contact-based approach [ 6 ]. They found a larger decrease in the risk of leprosy on the island using the population-wide approach. However, this was an island setting with low mobility of the population. Therefore, to collect additional evidence on the effectiveness of population-wide approaches, we will conduct blanket campaigns in identified clusters targeting 80 to 100 community members per index case.

A large-scale reduction in transmission across a large area will require a comprehensive application of ‘PEP services’, including SDR-PEP distribution to neighbours and social contacts, active case detection, community education and capacity strengthening of health workers. Following the individual- and population-level data analysis of this study, we expect to have evidence that it is possible to accelerate the reduction in leprosy incidence within a few years through implementation of the enhanced PEP++ regimen combined with SDR-PEP blanket campaigns and health system strengthening components as appropriate.

Availability of data and materials

No datasets were generated or analysed during the current study.

Abbreviations

Community education and behaviour change

  • Clarithromycin

Contact transmission and chemoprophylaxis in leprosy study

European Medicines Agency

Explanatory Model Interview Catalogue Community Stigma Scale

Geographic Information System

Global Positioning System

Knowledge, Attitudes and Practices measure

Leprosy post-exposure prophylaxis programme

Multi-drug therapy

  • Post-exposure prophylaxis

Enhanced multi-drug, multi-dose regimen leprosy post-exposure prophylaxis

Quantum Geographic Information System

Randomised controlled trial

Research Electronic Data Capture System

Single dose of rifampicin as leprosy post-exposure prophylaxis

Social Distance Scale

Stochastic individual-based model for transmission and control of leprosy

Tuberculosis

Unique identification code

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Acknowledgements

Our appreciation goes to all those involved in the PEP++ research consortium (listed individually below), the study participants, and their communities. We are grateful for the support, time and dedication of the following partners involved in each country:

* Bangladesh: The Leprosy Mission International Bangladesh (study coordinator); Federal Ministry of Health, Dhaka; District Governments of Nilphamari and Rangpur

* Brazil: NHR Brasil (study coordinator), the Federal University of Ceará (UFC) – Clinical Research Unit, Federal Ministry of Health, State Health Secretariat of Ceará, Municipal Health Secretariats of Fortaleza and Sobral, School of Family Health (Sobral), MORHAN

* India: NLR India (study coordinator), Vardhman Mahavir Medical College/Safdarjung Hospital, Federal Ministry of Health and Family Welfare, Central Leprosy Division; Uttar Pradesh State Leprosy Office, Chandauli and Fatehpur District Leprosy Offices, The Leprosy Mission Trust India (TLMTI), APAL

* Nepal: NLR Nepal (study coordinator), B.P. Koirala Institute of Health Sciences, Federal Ministry of Health and Population, Madesh Pradesh Provincial Government, Dhanusha and Mahottari District Governments, Nepal Leprosy Trust (NLT), The Leprosy Mission Nepal (TLMN)

* Netherlands: Erasmus University Medical Center, Rotterdam

* United Kingdom: The Leprosy Mission International, Brentford.

PEP++ Research Consortium

Bangladesh: Abu Sufian Chowdhury, Abhijit Saha, Shaikh A. Shahed Hossain, Salomon Sumon Halder, Surendra Nath Singh, Rishad Choudhury Robin, Sohel Marndi, Md. Anwar Hossain, Md. Rashidul Hasan, Johan Chandra Roy

Brazil: Virginia O. Fernandes, Aymée M da Rocha, Marcos Virmond, Zoica Bakirtzief Pereira, José A. Menezes da Silva, Juliana Cavalcante Ribeiro Ramos, Alberto Novaes Ramos Jr, Jaqueline Caracas Barbosa, Josafá Gonçalves Barreto, Adriana Reis, Nagila Nathaly Lima Ferreira, Renato Lima

France: Emmanuelle Cambau

India: Jugal Kishore, Suchitra Lisam, Ashok Agarwal, Danish Suhail, Anil Kumar, Sudarshan Mandal, Jaya Dehalvi, Hemanta K. Kar, Atif Sadiq, Sanjay K. Srivastava, Akshat Garg

Indonesia: Cita Rosita Prakoeswa, Asken Sinaga, Teky Budiawan, Linda Astari, Md. Atoillah Isfandiari, Ulfah Abqari

Nepal: Nand Lal Banstola, Prativa Bhandari, Bikash M. Singh, Nilamber Jha, Andriyash Magar, Bipin K. Yadav, Milan Tamang, Yugal K. Singh

Netherlands: Wim H. van Brakel, Duane C. Hinders, Anneke T. Taal, Anna T. van ’t Noordende, Liesbeth Mieras, Jan Hendrik Richardus, Tom Hambridge, Daan Nieboer

Norway: Paul Saunderson

United Kingdom: Jannine Ebenso, Cairns Smith

Funding for the study in Brazil, India and Nepal has been put forward by the Dutch Postcode Lottery (NPL) with counterpart funding made available by NLR, Amsterdam. Financial support for the intervention in Bangladesh has been provided by The Leprosy Mission International (TLMI) and its global fellowship members. The funders had no role in development, implementation, analysis of results, or preparation of the manuscript.

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Duane C. Hinders, Anneke T. Taal, Anna T. van ‘t Noordende, Liesbeth Mieras & Wim H. van Brakel

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Suchitra Lisam

NHR Brasil, Fortaleza, Brazil

Aymée M. da Rocha

NLR Nepal, Kathmandu, Nepal

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TLMI Bangladesh, Dhaka, Bangladesh

Abhijit Saha & Abu Sufian Chowdhury

Vardhman Mahavir Medical College/Safdarjung Hospital, Delhi, India

Jugal Kishore

Federal University of Ceará, Fortaleza, Brazil

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Contributions

DH, ATT, ATN, LM, WB designed the study. DH, ATT, ATN, LM and WB drafted the manuscript. All authors revised and approved the manuscript.

Corresponding author

Correspondence to Duane C. Hinders .

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The PEP++ study has gone before and been approved by institutional review boards in Bangladesh, Brazil, India, and Nepal under the names of the national Principal Investigators. It has also been reviewed favourably by the Bangladesh Medical Research Council, Indian Council of Medical Research, and Nepal Health Research Council. Each index case, close contact and blanket contact approached in the project receives verbal and written study information from the research assistants and be requested to sign a paper informed consent form (ICF). Participants receive details on possible side effects from the antibiotics and have the right to refuse participation or withdraw informed consent at any point in the study. When dealing with a child/adolescent under the age of 18 or a person with mental disabilities, the ICF will be presented to and signed by the legal guardian. The ICFs will be stored and catalogued according to the national requirements of each country. The PEP++ clinical trial and project are registered on Dutch Trial Register, under trial registration NL7022 (formerly NTR7221) with the title Stop the Transmission of Leprosy. It was originally registered on April 12, 2018, and last updated on August 18, 2022. https://www.onderzoekmetmensen.nl/en/trial/23060 .

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Hinders, D.C., Taal, A.T., Lisam, S. et al. The PEP++ study protocol: a cluster-randomised controlled trial on the effectiveness of an enhanced regimen of post-exposure prophylaxis for close contacts of persons affected by leprosy to prevent disease transmission. BMC Infect Dis 24 , 226 (2024). https://doi.org/10.1186/s12879-024-09125-2

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    case, and then the rule, reasoning, and facts of your case. The structure of the two explanations should mirror one another. Others prefer to start out with the unifying rule and reasoning, and then compare the facts of the two cases. Whichever way you decide to structure it, maintain that same structure for each case comparison so the reader ...

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    Background Leprosy is an infectious disease with a slow decline in global annual caseload in the past two decades. Active case finding and post-exposure prophylaxis (PEP) with a single dose of rifampicin (SDR) are recommended by the World Health Organization as measures for leprosy elimination. However, more potent PEP regimens are needed to increase the effect in groups highest at risk (i.e ...