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Case Study – Methods, Examples and Guide

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A case study is a research method that involves an in-depth examination and analysis of a particular phenomenon or case, such as an individual, organization, community, event, or situation.

It is a qualitative research approach that aims to provide a detailed and comprehensive understanding of the case being studied. Case studies typically involve multiple sources of data, including interviews, observations, documents, and artifacts, which are analyzed using various techniques, such as content analysis, thematic analysis, and grounded theory. The findings of a case study are often used to develop theories, inform policy or practice, or generate new research questions.

Types of Case Study

Types and Methods of Case Study are as follows:

Single-Case Study

A single-case study is an in-depth analysis of a single case. This type of case study is useful when the researcher wants to understand a specific phenomenon in detail.

For Example , A researcher might conduct a single-case study on a particular individual to understand their experiences with a particular health condition or a specific organization to explore their management practices. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of a single-case study are often used to generate new research questions, develop theories, or inform policy or practice.

Multiple-Case Study

A multiple-case study involves the analysis of several cases that are similar in nature. This type of case study is useful when the researcher wants to identify similarities and differences between the cases.

For Example, a researcher might conduct a multiple-case study on several companies to explore the factors that contribute to their success or failure. The researcher collects data from each case, compares and contrasts the findings, and uses various techniques to analyze the data, such as comparative analysis or pattern-matching. The findings of a multiple-case study can be used to develop theories, inform policy or practice, or generate new research questions.

Exploratory Case Study

An exploratory case study is used to explore a new or understudied phenomenon. This type of case study is useful when the researcher wants to generate hypotheses or theories about the phenomenon.

For Example, a researcher might conduct an exploratory case study on a new technology to understand its potential impact on society. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as grounded theory or content analysis. The findings of an exploratory case study can be used to generate new research questions, develop theories, or inform policy or practice.

Descriptive Case Study

A descriptive case study is used to describe a particular phenomenon in detail. This type of case study is useful when the researcher wants to provide a comprehensive account of the phenomenon.

For Example, a researcher might conduct a descriptive case study on a particular community to understand its social and economic characteristics. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of a descriptive case study can be used to inform policy or practice or generate new research questions.

Instrumental Case Study

An instrumental case study is used to understand a particular phenomenon that is instrumental in achieving a particular goal. This type of case study is useful when the researcher wants to understand the role of the phenomenon in achieving the goal.

For Example, a researcher might conduct an instrumental case study on a particular policy to understand its impact on achieving a particular goal, such as reducing poverty. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of an instrumental case study can be used to inform policy or practice or generate new research questions.

Case Study Data Collection Methods

Here are some common data collection methods for case studies:

Interviews involve asking questions to individuals who have knowledge or experience relevant to the case study. Interviews can be structured (where the same questions are asked to all participants) or unstructured (where the interviewer follows up on the responses with further questions). Interviews can be conducted in person, over the phone, or through video conferencing.

Observations

Observations involve watching and recording the behavior and activities of individuals or groups relevant to the case study. Observations can be participant (where the researcher actively participates in the activities) or non-participant (where the researcher observes from a distance). Observations can be recorded using notes, audio or video recordings, or photographs.

Documents can be used as a source of information for case studies. Documents can include reports, memos, emails, letters, and other written materials related to the case study. Documents can be collected from the case study participants or from public sources.

Surveys involve asking a set of questions to a sample of individuals relevant to the case study. Surveys can be administered in person, over the phone, through mail or email, or online. Surveys can be used to gather information on attitudes, opinions, or behaviors related to the case study.

Artifacts are physical objects relevant to the case study. Artifacts can include tools, equipment, products, or other objects that provide insights into the case study phenomenon.

How to conduct Case Study Research

Conducting a case study research involves several steps that need to be followed to ensure the quality and rigor of the study. Here are the steps to conduct case study research:

• Define the research questions: The first step in conducting a case study research is to define the research questions. The research questions should be specific, measurable, and relevant to the case study phenomenon under investigation.
• Select the case: The next step is to select the case or cases to be studied. The case should be relevant to the research questions and should provide rich and diverse data that can be used to answer the research questions.
• Collect data: Data can be collected using various methods, such as interviews, observations, documents, surveys, and artifacts. The data collection method should be selected based on the research questions and the nature of the case study phenomenon.
• Analyze the data: The data collected from the case study should be analyzed using various techniques, such as content analysis, thematic analysis, or grounded theory. The analysis should be guided by the research questions and should aim to provide insights and conclusions relevant to the research questions.
• Draw conclusions: The conclusions drawn from the case study should be based on the data analysis and should be relevant to the research questions. The conclusions should be supported by evidence and should be clearly stated.
• Validate the findings: The findings of the case study should be validated by reviewing the data and the analysis with participants or other experts in the field. This helps to ensure the validity and reliability of the findings.
• Write the report: The final step is to write the report of the case study research. The report should provide a clear description of the case study phenomenon, the research questions, the data collection methods, the data analysis, the findings, and the conclusions. The report should be written in a clear and concise manner and should follow the guidelines for academic writing.

Examples of Case Study

Here are some examples of case study research:

• The Hawthorne Studies : Conducted between 1924 and 1932, the Hawthorne Studies were a series of case studies conducted by Elton Mayo and his colleagues to examine the impact of work environment on employee productivity. The studies were conducted at the Hawthorne Works plant of the Western Electric Company in Chicago and included interviews, observations, and experiments.
• The Stanford Prison Experiment: Conducted in 1971, the Stanford Prison Experiment was a case study conducted by Philip Zimbardo to examine the psychological effects of power and authority. The study involved simulating a prison environment and assigning participants to the role of guards or prisoners. The study was controversial due to the ethical issues it raised.
• The Challenger Disaster: The Challenger Disaster was a case study conducted to examine the causes of the Space Shuttle Challenger explosion in 1986. The study included interviews, observations, and analysis of data to identify the technical, organizational, and cultural factors that contributed to the disaster.
• The Enron Scandal: The Enron Scandal was a case study conducted to examine the causes of the Enron Corporation’s bankruptcy in 2001. The study included interviews, analysis of financial data, and review of documents to identify the accounting practices, corporate culture, and ethical issues that led to the company’s downfall.
• The Fukushima Nuclear Disaster : The Fukushima Nuclear Disaster was a case study conducted to examine the causes of the nuclear accident that occurred at the Fukushima Daiichi Nuclear Power Plant in Japan in 2011. The study included interviews, analysis of data, and review of documents to identify the technical, organizational, and cultural factors that contributed to the disaster.

Application of Case Study

Case studies have a wide range of applications across various fields and industries. Here are some examples:

Business and Management

Case studies are widely used in business and management to examine real-life situations and develop problem-solving skills. Case studies can help students and professionals to develop a deep understanding of business concepts, theories, and best practices.

Case studies are used in healthcare to examine patient care, treatment options, and outcomes. Case studies can help healthcare professionals to develop critical thinking skills, diagnose complex medical conditions, and develop effective treatment plans.

Case studies are used in education to examine teaching and learning practices. Case studies can help educators to develop effective teaching strategies, evaluate student progress, and identify areas for improvement.

Social Sciences

Case studies are widely used in social sciences to examine human behavior, social phenomena, and cultural practices. Case studies can help researchers to develop theories, test hypotheses, and gain insights into complex social issues.

Law and Ethics

Case studies are used in law and ethics to examine legal and ethical dilemmas. Case studies can help lawyers, policymakers, and ethical professionals to develop critical thinking skills, analyze complex cases, and make informed decisions.

Purpose of Case Study

The purpose of a case study is to provide a detailed analysis of a specific phenomenon, issue, or problem in its real-life context. A case study is a qualitative research method that involves the in-depth exploration and analysis of a particular case, which can be an individual, group, organization, event, or community.

The primary purpose of a case study is to generate a comprehensive and nuanced understanding of the case, including its history, context, and dynamics. Case studies can help researchers to identify and examine the underlying factors, processes, and mechanisms that contribute to the case and its outcomes. This can help to develop a more accurate and detailed understanding of the case, which can inform future research, practice, or policy.

Case studies can also serve other purposes, including:

• Illustrating a theory or concept: Case studies can be used to illustrate and explain theoretical concepts and frameworks, providing concrete examples of how they can be applied in real-life situations.
• Developing hypotheses: Case studies can help to generate hypotheses about the causal relationships between different factors and outcomes, which can be tested through further research.
• Providing insight into complex issues: Case studies can provide insights into complex and multifaceted issues, which may be difficult to understand through other research methods.
• Informing practice or policy: Case studies can be used to inform practice or policy by identifying best practices, lessons learned, or areas for improvement.

Advantages of Case Study Research

There are several advantages of case study research, including:

• In-depth exploration: Case study research allows for a detailed exploration and analysis of a specific phenomenon, issue, or problem in its real-life context. This can provide a comprehensive understanding of the case and its dynamics, which may not be possible through other research methods.
• Rich data: Case study research can generate rich and detailed data, including qualitative data such as interviews, observations, and documents. This can provide a nuanced understanding of the case and its complexity.
• Holistic perspective: Case study research allows for a holistic perspective of the case, taking into account the various factors, processes, and mechanisms that contribute to the case and its outcomes. This can help to develop a more accurate and comprehensive understanding of the case.
• Theory development: Case study research can help to develop and refine theories and concepts by providing empirical evidence and concrete examples of how they can be applied in real-life situations.
• Practical application: Case study research can inform practice or policy by identifying best practices, lessons learned, or areas for improvement.
• Contextualization: Case study research takes into account the specific context in which the case is situated, which can help to understand how the case is influenced by the social, cultural, and historical factors of its environment.

Limitations of Case Study Research

There are several limitations of case study research, including:

• Limited generalizability : Case studies are typically focused on a single case or a small number of cases, which limits the generalizability of the findings. The unique characteristics of the case may not be applicable to other contexts or populations, which may limit the external validity of the research.
• Biased sampling: Case studies may rely on purposive or convenience sampling, which can introduce bias into the sample selection process. This may limit the representativeness of the sample and the generalizability of the findings.
• Subjectivity: Case studies rely on the interpretation of the researcher, which can introduce subjectivity into the analysis. The researcher’s own biases, assumptions, and perspectives may influence the findings, which may limit the objectivity of the research.
• Limited control: Case studies are typically conducted in naturalistic settings, which limits the control that the researcher has over the environment and the variables being studied. This may limit the ability to establish causal relationships between variables.
• Time-consuming: Case studies can be time-consuming to conduct, as they typically involve a detailed exploration and analysis of a specific case. This may limit the feasibility of conducting multiple case studies or conducting case studies in a timely manner.
• Resource-intensive: Case studies may require significant resources, including time, funding, and expertise. This may limit the ability of researchers to conduct case studies in resource-constrained settings.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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

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

Research question

• Conceptual framework
• Conceptual vs. theoretical framework

Data collection

• Qualitative research methods
• Focus groups
• Observational research

What is a case study?

Applications for case study research, what is a good case study, process of case study design, benefits and limitations of case studies.

• Ethnographical research
• Ethical considerations
• Confidentiality and privacy
• Power dynamics
• Reflexivity

Case studies

Case studies are essential to qualitative research , offering a lens through which researchers can investigate complex phenomena within their real-life contexts. This chapter explores the concept, purpose, applications, examples, and types of case studies and provides guidance on how to conduct case study research effectively.

Whereas quantitative methods look at phenomena at scale, case study research looks at a concept or phenomenon in considerable detail. While analyzing a single case can help understand one perspective regarding the object of research inquiry, analyzing multiple cases can help obtain a more holistic sense of the topic or issue. Let's provide a basic definition of a case study, then explore its characteristics and role in the qualitative research process.

Definition of a case study

A case study in qualitative research is a strategy of inquiry that involves an in-depth investigation of a phenomenon within its real-world context. It provides researchers with the opportunity to acquire an in-depth understanding of intricate details that might not be as apparent or accessible through other methods of research. The specific case or cases being studied can be a single person, group, or organization – demarcating what constitutes a relevant case worth studying depends on the researcher and their research question .

Among qualitative research methods , a case study relies on multiple sources of evidence, such as documents, artifacts, interviews , or observations , to present a complete and nuanced understanding of the phenomenon under investigation. The objective is to illuminate the readers' understanding of the phenomenon beyond its abstract statistical or theoretical explanations.

Characteristics of case studies

Case studies typically possess a number of distinct characteristics that set them apart from other research methods. These characteristics include a focus on holistic description and explanation, flexibility in the design and data collection methods, reliance on multiple sources of evidence, and emphasis on the context in which the phenomenon occurs.

Furthermore, case studies can often involve a longitudinal examination of the case, meaning they study the case over a period of time. These characteristics allow case studies to yield comprehensive, in-depth, and richly contextualized insights about the phenomenon of interest.

The role of case studies in research

Case studies hold a unique position in the broader landscape of research methods aimed at theory development. They are instrumental when the primary research interest is to gain an intensive, detailed understanding of a phenomenon in its real-life context.

In addition, case studies can serve different purposes within research - they can be used for exploratory, descriptive, or explanatory purposes, depending on the research question and objectives. This flexibility and depth make case studies a valuable tool in the toolkit of qualitative researchers.

Remember, a well-conducted case study can offer a rich, insightful contribution to both academic and practical knowledge through theory development or theory verification, thus enhancing our understanding of complex phenomena in their real-world contexts.

What is the purpose of a case study?

Case study research aims for a more comprehensive understanding of phenomena, requiring various research methods to gather information for qualitative analysis . Ultimately, a case study can allow the researcher to gain insight into a particular object of inquiry and develop a theoretical framework relevant to the research inquiry.

Why use case studies in qualitative research?

Using case studies as a research strategy depends mainly on the nature of the research question and the researcher's access to the data.

Conducting case study research provides a level of detail and contextual richness that other research methods might not offer. They are beneficial when there's a need to understand complex social phenomena within their natural contexts.

The explanatory, exploratory, and descriptive roles of case studies

Case studies can take on various roles depending on the research objectives. They can be exploratory when the research aims to discover new phenomena or define new research questions; they are descriptive when the objective is to depict a phenomenon within its context in a detailed manner; and they can be explanatory if the goal is to understand specific relationships within the studied context. Thus, the versatility of case studies allows researchers to approach their topic from different angles, offering multiple ways to uncover and interpret the data .

The impact of case studies on knowledge development

Case studies play a significant role in knowledge development across various disciplines. Analysis of cases provides an avenue for researchers to explore phenomena within their context based on the collected data.

This can result in the production of rich, practical insights that can be instrumental in both theory-building and practice. Case studies allow researchers to delve into the intricacies and complexities of real-life situations, uncovering insights that might otherwise remain hidden.

Types of case studies

In qualitative research , a case study is not a one-size-fits-all approach. Depending on the nature of the research question and the specific objectives of the study, researchers might choose to use different types of case studies. These types differ in their focus, methodology, and the level of detail they provide about the phenomenon under investigation.

Understanding these types is crucial for selecting the most appropriate approach for your research project and effectively achieving your research goals. Let's briefly look at the main types of case studies.

Exploratory case studies

Exploratory case studies are typically conducted to develop a theory or framework around an understudied phenomenon. They can also serve as a precursor to a larger-scale research project. Exploratory case studies are useful when a researcher wants to identify the key issues or questions which can spur more extensive study or be used to develop propositions for further research. These case studies are characterized by flexibility, allowing researchers to explore various aspects of a phenomenon as they emerge, which can also form the foundation for subsequent studies.

Descriptive case studies

Descriptive case studies aim to provide a complete and accurate representation of a phenomenon or event within its context. These case studies are often based on an established theoretical framework, which guides how data is collected and analyzed. The researcher is concerned with describing the phenomenon in detail, as it occurs naturally, without trying to influence or manipulate it.

Explanatory case studies

Explanatory case studies are focused on explanation - they seek to clarify how or why certain phenomena occur. Often used in complex, real-life situations, they can be particularly valuable in clarifying causal relationships among concepts and understanding the interplay between different factors within a specific context.

Intrinsic, instrumental, and collective case studies

These three categories of case studies focus on the nature and purpose of the study. An intrinsic case study is conducted when a researcher has an inherent interest in the case itself. Instrumental case studies are employed when the case is used to provide insight into a particular issue or phenomenon. A collective case study, on the other hand, involves studying multiple cases simultaneously to investigate some general phenomena.

Each type of case study serves a different purpose and has its own strengths and challenges. The selection of the type should be guided by the research question and objectives, as well as the context and constraints of the research.

The flexibility, depth, and contextual richness offered by case studies make this approach an excellent research method for various fields of study. They enable researchers to investigate real-world phenomena within their specific contexts, capturing nuances that other research methods might miss. Across numerous fields, case studies provide valuable insights into complex issues.

Critical information systems research

Case studies provide a detailed understanding of the role and impact of information systems in different contexts. They offer a platform to explore how information systems are designed, implemented, and used and how they interact with various social, economic, and political factors. Case studies in this field often focus on examining the intricate relationship between technology, organizational processes, and user behavior, helping to uncover insights that can inform better system design and implementation.

Health research

Health research is another field where case studies are highly valuable. They offer a way to explore patient experiences, healthcare delivery processes, and the impact of various interventions in a real-world context.

Case studies can provide a deep understanding of a patient's journey, giving insights into the intricacies of disease progression, treatment effects, and the psychosocial aspects of health and illness.

Asthma research studies

Specifically within medical research, studies on asthma often employ case studies to explore the individual and environmental factors that influence asthma development, management, and outcomes. A case study can provide rich, detailed data about individual patients' experiences, from the triggers and symptoms they experience to the effectiveness of various management strategies. This can be crucial for developing patient-centered asthma care approaches.

Other fields

Apart from the fields mentioned, case studies are also extensively used in business and management research, education research, and political sciences, among many others. They provide an opportunity to delve into the intricacies of real-world situations, allowing for a comprehensive understanding of various phenomena.

Case studies, with their depth and contextual focus, offer unique insights across these varied fields. They allow researchers to illuminate the complexities of real-life situations, contributing to both theory and practice.

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Understanding the key elements of case study design is crucial for conducting rigorous and impactful case study research. A well-structured design guides the researcher through the process, ensuring that the study is methodologically sound and its findings are reliable and valid. The main elements of case study design include the research question , propositions, units of analysis, and the logic linking the data to the propositions.

The research question is the foundation of any research study. A good research question guides the direction of the study and informs the selection of the case, the methods of collecting data, and the analysis techniques. A well-formulated research question in case study research is typically clear, focused, and complex enough to merit further detailed examination of the relevant case(s).

Propositions

Propositions, though not necessary in every case study, provide a direction by stating what we might expect to find in the data collected. They guide how data is collected and analyzed by helping researchers focus on specific aspects of the case. They are particularly important in explanatory case studies, which seek to understand the relationships among concepts within the studied phenomenon.

Units of analysis

The unit of analysis refers to the case, or the main entity or entities that are being analyzed in the study. In case study research, the unit of analysis can be an individual, a group, an organization, a decision, an event, or even a time period. It's crucial to clearly define the unit of analysis, as it shapes the qualitative data analysis process by allowing the researcher to analyze a particular case and synthesize analysis across multiple case studies to draw conclusions.

Argumentation

This refers to the inferential model that allows researchers to draw conclusions from the data. The researcher needs to ensure that there is a clear link between the data, the propositions (if any), and the conclusions drawn. This argumentation is what enables the researcher to make valid and credible inferences about the phenomenon under study.

Understanding and carefully considering these elements in the design phase of a case study can significantly enhance the quality of the research. It can help ensure that the study is methodologically sound and its findings contribute meaningful insights about the case.

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Conducting a case study involves several steps, from defining the research question and selecting the case to collecting and analyzing data . This section outlines these key stages, providing a practical guide on how to conduct case study research.

Defining the research question

The first step in case study research is defining a clear, focused research question. This question should guide the entire research process, from case selection to analysis. It's crucial to ensure that the research question is suitable for a case study approach. Typically, such questions are exploratory or descriptive in nature and focus on understanding a phenomenon within its real-life context.

Selecting and defining the case

The selection of the case should be based on the research question and the objectives of the study. It involves choosing a unique example or a set of examples that provide rich, in-depth data about the phenomenon under investigation. After selecting the case, it's crucial to define it clearly, setting the boundaries of the case, including the time period and the specific context.

Previous research can help guide the case study design. When considering a case study, an example of a case could be taken from previous case study research and used to define cases in a new research inquiry. Considering recently published examples can help understand how to select and define cases effectively.

Developing a detailed case study protocol

A case study protocol outlines the procedures and general rules to be followed during the case study. This includes the data collection methods to be used, the sources of data, and the procedures for analysis. Having a detailed case study protocol ensures consistency and reliability in the study.

The protocol should also consider how to work with the people involved in the research context to grant the research team access to collecting data. As mentioned in previous sections of this guide, establishing rapport is an essential component of qualitative research as it shapes the overall potential for collecting and analyzing data.

Collecting data

Gathering data in case study research often involves multiple sources of evidence, including documents, archival records, interviews, observations, and physical artifacts. This allows for a comprehensive understanding of the case. The process for gathering data should be systematic and carefully documented to ensure the reliability and validity of the study.

Analyzing and interpreting data

The next step is analyzing the data. This involves organizing the data , categorizing it into themes or patterns , and interpreting these patterns to answer the research question. The analysis might also involve comparing the findings with prior research or theoretical propositions.

Writing the case study report

The final step is writing the case study report . This should provide a detailed description of the case, the data, the analysis process, and the findings. The report should be clear, organized, and carefully written to ensure that the reader can understand the case and the conclusions drawn from it.

Each of these steps is crucial in ensuring that the case study research is rigorous, reliable, and provides valuable insights about the case.

The type, depth, and quality of data in your study can significantly influence the validity and utility of the study. In case study research, data is usually collected from multiple sources to provide a comprehensive and nuanced understanding of the case. This section will outline the various methods of collecting data used in case study research and discuss considerations for ensuring the quality of the data.

Interviews are a common method of gathering data in case study research. They can provide rich, in-depth data about the perspectives, experiences, and interpretations of the individuals involved in the case. Interviews can be structured , semi-structured , or unstructured , depending on the research question and the degree of flexibility needed.

Observations

Observations involve the researcher observing the case in its natural setting, providing first-hand information about the case and its context. Observations can provide data that might not be revealed in interviews or documents, such as non-verbal cues or contextual information.

Documents and artifacts

Documents and archival records provide a valuable source of data in case study research. They can include reports, letters, memos, meeting minutes, email correspondence, and various public and private documents related to the case.

These records can provide historical context, corroborate evidence from other sources, and offer insights into the case that might not be apparent from interviews or observations.

Physical artifacts refer to any physical evidence related to the case, such as tools, products, or physical environments. These artifacts can provide tangible insights into the case, complementing the data gathered from other sources.

Ensuring the quality of data collection

Determining the quality of data in case study research requires careful planning and execution. It's crucial to ensure that the data is reliable, accurate, and relevant to the research question. This involves selecting appropriate methods of collecting data, properly training interviewers or observers, and systematically recording and storing the data. It also includes considering ethical issues related to collecting and handling data, such as obtaining informed consent and ensuring the privacy and confidentiality of the participants.

Data analysis

Analyzing case study research involves making sense of the rich, detailed data to answer the research question. This process can be challenging due to the volume and complexity of case study data. However, a systematic and rigorous approach to analysis can ensure that the findings are credible and meaningful. This section outlines the main steps and considerations in analyzing data in case study research.

Organizing the data

The first step in the analysis is organizing the data. This involves sorting the data into manageable sections, often according to the data source or the theme. This step can also involve transcribing interviews, digitizing physical artifacts, or organizing observational data.

Categorizing and coding the data

Once the data is organized, the next step is to categorize or code the data. This involves identifying common themes, patterns, or concepts in the data and assigning codes to relevant data segments. Coding can be done manually or with the help of software tools, and in either case, qualitative analysis software can greatly facilitate the entire coding process. Coding helps to reduce the data to a set of themes or categories that can be more easily analyzed.

Identifying patterns and themes

After coding the data, the researcher looks for patterns or themes in the coded data. This involves comparing and contrasting the codes and looking for relationships or patterns among them. The identified patterns and themes should help answer the research question.

Interpreting the data

Once patterns and themes have been identified, the next step is to interpret these findings. This involves explaining what the patterns or themes mean in the context of the research question and the case. This interpretation should be grounded in the data, but it can also involve drawing on theoretical concepts or prior research.

Verification of the data

The last step in the analysis is verification. This involves checking the accuracy and consistency of the analysis process and confirming that the findings are supported by the data. This can involve re-checking the original data, checking the consistency of codes, or seeking feedback from research participants or peers.

Like any research method , case study research has its strengths and limitations. Researchers must be aware of these, as they can influence the design, conduct, and interpretation of the study.

Understanding the strengths and limitations of case study research can also guide researchers in deciding whether this approach is suitable for their research question . This section outlines some of the key strengths and limitations of case study research.

Benefits include the following:

• Rich, detailed data: One of the main strengths of case study research is that it can generate rich, detailed data about the case. This can provide a deep understanding of the case and its context, which can be valuable in exploring complex phenomena.
• Flexibility: Case study research is flexible in terms of design , data collection , and analysis . A sufficient degree of flexibility allows the researcher to adapt the study according to the case and the emerging findings.
• Real-world context: Case study research involves studying the case in its real-world context, which can provide valuable insights into the interplay between the case and its context.
• Multiple sources of evidence: Case study research often involves collecting data from multiple sources , which can enhance the robustness and validity of the findings.

On the other hand, researchers should consider the following limitations:

• Generalizability: A common criticism of case study research is that its findings might not be generalizable to other cases due to the specificity and uniqueness of each case.
• Time and resource intensive: Case study research can be time and resource intensive due to the depth of the investigation and the amount of collected data.
• Complexity of analysis: The rich, detailed data generated in case study research can make analyzing the data challenging.
• Subjectivity: Given the nature of case study research, there may be a higher degree of subjectivity in interpreting the data , so researchers need to reflect on this and transparently convey to audiences how the research was conducted.

Being aware of these strengths and limitations can help researchers design and conduct case study research effectively and interpret and report the findings appropriately.

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Case Study Methods and Examples

By Janet Salmons, PhD Manager, Sage Research Methods Community

What is Case Study Methodology ?

Case studies in research are both unique and uniquely confusing. The term case study is confusing because the same term is used multiple ways. The term can refer to the methodology, that is, a system of frameworks used to design a study, or the methods used to conduct it. Or, case study can refer to a type of academic writing that typically delves into a problem, process, or situation.

Case study methodology can entail the study of one or more "cases," that could be described as instances, examples, or settings where the problem or phenomenon can be examined. The researcher is tasked with defining the parameters of the case, that is, what is included and excluded. This process is called bounding the case , or setting boundaries.

Case study can be combined with other methodologies, such as ethnography, grounded theory, or phenomenology. In such studies the research on the case uses another framework to further define the study and refine the approach.

Case study is also described as a method, given particular approaches used to collect and analyze data. Case study research is conducted by almost every social science discipline: business, education, sociology, psychology. Case study research, with its reliance on multiple sources, is also a natural choice for researchers interested in trans-, inter-, or cross-disciplinary studies.

The Encyclopedia of case study research provides an overview:

The purpose of case study research is twofold: (1) to provide descriptive information and (2) to suggest theoretical relevance. Rich description enables an in-depth or sharpened understanding of the case.

It is unique given one characteristic: case studies draw from more than one data source. Case studies are inherently multimodal or mixed methods because this they use either more than one form of data within a research paradigm, or more than one form of data from different paradigms.

A case study inquiry could include multiple types of data:

multiple forms of quantitative data sources, such as Big Data + a survey

multiple forms of qualitative data sources, such as interviews + observations + documents

multiple forms of quantitative and qualitative data sources, such as surveys + interviews

Case study methodology can be used to achieve different research purposes.

Robert Yin , methodologist most associated with case study research, differentiates between descriptive , exploratory and explanatory case studies:

Descriptive : A case study whose purpose is to describe a phenomenon. Explanatory : A case study whose purpose is to explain how or why some condition came to be, or why some sequence of events occurred or did not occur. Exploratory: A case study whose purpose is to identify the research questions or procedures to be used in a subsequent study.

Robert Yin’s book is a comprehensive guide for case study researchers!

You can read the preface and Chapter 1 of Yin's book here . See the open-access articles below for some published examples of qualitative, quantitative, and mixed methods case study research.

Mills, A. J., Durepos, G., & Wiebe, E. (2010).  Encyclopedia of case study research (Vols. 1-0). Thousand Oaks, CA: SAGE Publications, Inc. doi: 10.4135/9781412957397

Yin, R. K. (2018). Case study research and applications (6th ed.). Thousand Oaks: SAGE Publications.

Open-Access Articles Using Case Study Methodology

As you can see from this collection, case study methods are used in qualitative, quantitative and mixed methods research.

Ang, C.-S., Lee, K.-F., & Dipolog-Ubanan, G. F. (2019). Determinants of First-Year Student Identity and Satisfaction in Higher Education: A Quantitative Case Study. SAGE Open. https://doi.org/10.1177/2158244019846689

Abstract. First-year undergraduates’ expectations and experience of university and student engagement variables were investigated to determine how these perceptions influence their student identity and overall course satisfaction. Data collected from 554 first-year undergraduates at a large private university were analyzed. Participants were given the adapted version of the Melbourne Centre for the Study of Higher Education Survey to self-report their learning experience and engagement in the university community. The results showed that, in general, the students’ reasons of pursuing tertiary education were to open the door to career opportunities and skill development. Moreover, students’ views on their learning and university engagement were at the moderate level. In relation to student identity and overall student satisfaction, it is encouraging to state that their perceptions of studentship and course satisfaction were rather positive. After controlling for demographics, student engagement appeared to explain more variance in student identity, whereas students’ expectations and experience explained greater variance in students’ overall course satisfaction. Implications for practice, limitations, and recommendation of this study are addressed.

Baker, A. J. (2017). Algorithms to Assess Music Cities: Case Study—Melbourne as a Music Capital. SAGE Open. https://doi.org/10.1177/2158244017691801

Abstract. The global  Mastering of a Music City  report in 2015 notes that the concept of music cities has penetrated the global political vernacular because it delivers “significant economic, employment, cultural and social benefits.” This article highlights that no empirical study has combined all these values and offers a relevant and comprehensive definition of a music city. Drawing on industry research,1 the article assesses how mathematical flowcharts, such as Algorithm A (Economics), Algorithm B (Four T’s creative index), and Algorithm C (Heritage), have contributed to the definition of a music city. Taking Melbourne as a case study, it illustrates how Algorithms A and B are used as disputed evidence about whether the city is touted as Australia’s music capital. The article connects the three algorithms to an academic framework from musicology, urban studies, cultural economics, and sociology, and proposes a benchmark Algorithm D (Music Cities definition), which offers a more holistic assessment of music activity in any urban context. The article concludes by arguing that Algorithm D offers a much-needed definition of what comprises a music city because it builds on the popular political economy focus and includes the social importance of space and cultural practices.

Brown, K., & Mondon, A. (2020). Populism, the media, and the mainstreaming of the far right: The Guardian’s coverage of populism as a case study. Politics. https://doi.org/10.1177/0263395720955036

Abstract. Populism seems to define our current political age. The term is splashed across the headlines, brandished in political speeches and commentaries, and applied extensively in numerous academic publications and conferences. This pervasive usage, or populist hype, has serious implications for our understanding of the meaning of populism itself and for our interpretation of the phenomena to which it is applied. In particular, we argue that its common conflation with far-right politics, as well as its breadth of application to other phenomena, has contributed to the mainstreaming of the far right in three main ways: (1) agenda-setting power and deflection, (2) euphemisation and trivialisation, and (3) amplification. Through a mixed-methods approach to discourse analysis, this article uses  The Guardian  newspaper as a case study to explore the development of the populist hype and the detrimental effects of the logics that it has pushed in public discourse.

Droy, L. T., Goodwin, J., & O’Connor, H. (2020). Methodological Uncertainty and Multi-Strategy Analysis: Case Study of the Long-Term Effects of Government Sponsored Youth Training on Occupational Mobility. Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique, 147–148(1–2), 200–230. https://doi.org/10.1177/0759106320939893

Abstract. Sociological practitioners often face considerable methodological uncertainty when undertaking a quantitative analysis. This methodological uncertainty encompasses both data construction (e.g. defining variables) and analysis (e.g. selecting and specifying a modelling procedure). Methodological uncertainty can lead to results that are fragile and arbitrary. Yet, many practitioners may be unaware of the potential scale of methodological uncertainty in quantitative analysis, and the recent emergence of techniques for addressing it. Recent proposals for ‘multi-strategy’ approaches seek to identify and manage methodological uncertainty in quantitative analysis. We present a case-study of a multi-strategy analysis, applied to the problem of estimating the long-term impact of 1980s UK government-sponsored youth training. We use this case study to further highlight the problem of cumulative methodological fragilities in applied quantitative sociology and to discuss and help develop multi-strategy analysis as a tool to address them.

Ebneyamini, S., & Sadeghi Moghadam, M. R. (2018). Toward Developing a Framework for Conducting Case Study Research .  International Journal of Qualitative Methods .  https://doi.org/10.1177/1609406918817954

Abstract. This article reviews the use of case study research for both practical and theoretical issues especially in management field with the emphasis on management of technology and innovation. Many researchers commented on the methodological issues of the case study research from their point of view thus, presenting a comprehensive framework was missing. We try representing a general framework with methodological and analytical perspective to design, develop, and conduct case study research. To test the coverage of our framework, we have analyzed articles in three major journals related to the management of technology and innovation to approve our framework. This study represents a general structure to guide, design, and fulfill a case study research with levels and steps necessary for researchers to use in their research.

Lai, D., & Roccu, R. (2019). Case study research and critical IR: the case for the extended case methodology. International Relations , 33 (1), 67-87. https://doi.org/10.1177/0047117818818243

Abstract. Discussions on case study methodology in International Relations (IR) have historically been dominated by positivist and neopositivist approaches. However, these are problematic for critical IR research, pointing to the need for a non-positivist case study methodology. To address this issue, this article introduces and adapts the extended case methodology as a critical, reflexivist approach to case study research, whereby the case is constructed through a dynamic interaction with theory, rather than selected, and knowledge is produced through extensions rather than generalisation. Insofar as it seeks to study the world in complex and non-linear terms, take context and positionality seriously, and generate explicitly political and emancipatory knowledge, the extended case methodology is consistent with the ontological and epistemological commitments of several critical IR approaches. Its potential is illustrated in the final part of the article with reference to researching the socioeconomic dimension of transitional justice in Bosnia and Herzegovina.

Lynch, R., Young, J. C., Boakye-Achampong, S., Jowaisas, C., Sam, J., & Norlander, B. (2020). Benefits of crowdsourcing for libraries: A case study from Africa . IFLA Journal. https://doi.org/10.1177/0340035220944940

Abstract. Many libraries in the Global South do not collect comprehensive data about themselves, which creates challenges in terms of local and international visibility. Crowdsourcing is an effective tool that engages the public to collect missing data, and it has proven to be particularly valuable in countries where governments collect little public data. Whereas crowdsourcing is often used within fields that have high levels of development funding, such as health, the authors believe that this approach would have many benefits for the library field as well. They present qualitative and quantitative evidence from 23 African countries involved in a crowdsourcing project to map libraries. The authors find benefits in terms of increased connections between stakeholders, capacity-building, and increased local visibility. These findings demonstrate the potential of crowdsourced approaches for tasks such as mapping to benefit libraries and similarly positioned institutions in the Global South in multifaceted ways.

Mason, W., Morris, K., Webb, C., Daniels, B., Featherstone, B., Bywaters, P., Mirza, N., Hooper, J., Brady, G., Bunting, L., & Scourfield, J. (2020). Toward Full Integration of Quantitative and Qualitative Methods in Case Study Research: Insights From Investigating Child Welfare Inequalities. Journal of Mixed Methods Research, 14 (2), 164-183. https://doi.org/10.1177/1558689819857972

Abstract. Delineation of the full integration of quantitative and qualitative methods throughout all stages of multisite mixed methods case study projects remains a gap in the methodological literature. This article offers advances to the field of mixed methods by detailing the application and integration of mixed methods throughout all stages of one such project; a study of child welfare inequalities. By offering a critical discussion of site selection and the management of confirmatory, expansionary and discordant data, this article contributes to the limited body of mixed methods exemplars specific to this field. We propose that our mixed methods approach provided distinctive insights into a complex social problem, offering expanded understandings of the relationship between poverty, child abuse, and neglect.

Rashid, Y., Rashid, A., Warraich, M. A., Sabir, S. S., & Waseem, A. (2019). Case Study Method: A Step-by-Step Guide for Business Researchers .  International Journal of Qualitative Methods .  https://doi.org/10.1177/1609406919862424

Abstract. Qualitative case study methodology enables researchers to conduct an in-depth exploration of intricate phenomena within some specific context. By keeping in mind research students, this article presents a systematic step-by-step guide to conduct a case study in the business discipline. Research students belonging to said discipline face issues in terms of clarity, selection, and operationalization of qualitative case study while doing their final dissertation. These issues often lead to confusion, wastage of valuable time, and wrong decisions that affect the overall outcome of the research. This article presents a checklist comprised of four phases, that is, foundation phase, prefield phase, field phase, and reporting phase. The objective of this article is to provide novice researchers with practical application of this checklist by linking all its four phases with the authors’ experiences and learning from recently conducted in-depth multiple case studies in the organizations of New Zealand. Rather than discussing case study in general, a targeted step-by-step plan with real-time research examples to conduct a case study is given.

VanWynsberghe, R., & Khan, S. (2007). Redefining Case Study. International Journal of Qualitative Methods, 80–94. https://doi.org/10.1177/160940690700600208

Abstract. In this paper the authors propose a more precise and encompassing definition of case study than is usually found. They support their definition by clarifying that case study is neither a method nor a methodology nor a research design as suggested by others. They use a case study prototype of their own design to propose common properties of case study and demonstrate how these properties support their definition. Next, they present several living myths about case study and refute them in relation to their definition. Finally, they discuss the interplay between the terms case study and unit of analysis to further delineate their definition of case study. The target audiences for this paper include case study researchers, research design and methods instructors, and graduate students interested in case study research.

More Sage Research Methods Community Posts about Case Study Research

Use research cases as the basis for individual or team activities that build skills.

Find an 10-step process for using research cases to teach methods with learning activities for individual students, teams, or small groups. (Or use the approach yourself!)

How do you decide which methodology fits your study? In this dialogue Linda Bloomberg and Janet Boberg explain the importance of a strategic approach to qualitative research design that stresses alignment with the purpose of the study.

Case study methods are used by researchers in many disciplines. Here are some open-access articles about multimodal qualitative or mixed methods designs that include both qualitative and quantitative elements.

Case study methodology is both unique, and uniquely confusing. It is unique given one characteristic: case studies draw from more than one data source.

What is case study methodology? It is unique given one characteristic: case studies draw from more than one data source. In this post find definitions and a collection of multidisciplinary examples.

Find discussion of case studies and published examples.

Istanbul as a regional computational social science hub

Experiments and quantitative research.

Research Writing and Analysis

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

What is a case study?

A Case study is: 

• An in-depth research design that primarily uses a qualitative methodology but sometimes​​ includes quantitative methodology.
• Used to examine an identifiable problem confirmed through research.
• Used to investigate an individual, group of people, organization, or event.
• Used to mostly answer "how" and "why" questions.

What are the different types of case studies?

Note: These are the primary case studies. As you continue to research and learn

about case studies you will begin to find a robust list of different types. 

Who are your case study participants?

What is triangulation ? 

Validity and credibility are an essential part of the case study. Therefore, the researcher should include triangulation to ensure trustworthiness while accurately reflecting what the researcher seeks to investigate.

How to write a Case Study?

When developing a case study, there are different ways you could present the information, but remember to include the five parts for your case study.

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11 Case research

Case research—also called case study—is a method of intensively studying a phenomenon over time within its natural setting in one or a few sites. Multiple methods of data collection, such as interviews, observations, pre-recorded documents, and secondary data, may be employed and inferences about the phenomenon of interest tend to be rich, detailed, and contextualised. Case research can be employed in a positivist manner for the purpose of theory testing or in an interpretive manner for theory building. This method is more popular in business research than in other social science disciplines.

Case research has several unique strengths over competing research methods such as experiments and survey research. First, case research can be used for either theory building or theory testing, while positivist methods can be used for theory testing only. In interpretive case research, the constructs of interest need not be known in advance, but may emerge from the data as the research progresses. Second, the research questions can be modified during the research process if the original questions are found to be less relevant or salient. This is not possible in any positivist method after the data is collected. Third, case research can help derive richer, more contextualised, and more authentic interpretation of the phenomenon of interest than most other research methods by virtue of its ability to capture a rich array of contextual data. Fourth, the phenomenon of interest can be studied from the perspectives of multiple participants and using multiple levels of analysis (e.g., individual and organisational).

At the same time, case research also has some inherent weaknesses. Because it involves no experimental control, internal validity of inferences remain weak. Of course, this is a common problem for all research methods except experiments. However, as described later, the problem of controls may be addressed in case research using ‘natural controls’. Second, the quality of inferences derived from case research depends heavily on the integrative powers of the researcher. An experienced researcher may see concepts and patterns in case data that a novice researcher may miss. Hence, the findings are sometimes criticised as being subjective. Finally, because the inferences are heavily contextualised, it may be difficult to generalise inferences from case research to other contexts or other organisations.

It is important to recognise that case research is different from case descriptions such as Harvard case studies discussed in business classes. While case descriptions typically describe an organisational problem in rich detail with the goal of stimulating classroom discussion and critical thinking among students, or analysing how well an organisation handled a specific problem, case research is a formal research technique that involves a scientific method to derive explanations of organisational phenomena.

Case research is a difficult research method that requires advanced research skills on the part of the researcher, and is therefore often prone to error. Benbasat, Goldstein and Mead (1987) [1] describe five problems frequently encountered in case research studies. First, many case research studies start without specific research questions, and therefore end up without having any specific answers or insightful inferences. Second, case sites are often chosen based on access and convenience, rather than based on the fit with the research questions, and are therefore cannot adequately address the research questions of interest. Third, researchers often do not validate or triangulate data collected using multiple means, which may lead to biased interpretation based on responses from biased interviewees. Fourth, many studies provide very little details on how data was collected (e.g., what interview questions were used, which documents were examined, the organisational positions of each interviewee, etc.) or analysed, which may raise doubts about the reliability of the inferences. Finally, despite its strength as a longitudinal research method, many case research studies do not follow through a phenomenon in a longitudinal manner, and hence present only a cross-sectional and limited view of organisational processes and phenomena that are temporal in nature.

Key decisions in case research

Several key decisions must be made by a researcher when considering a case research method. First, is this the right method for the research questions being studied? The case research method is particularly appropriate for exploratory studies, for discovering relevant constructs in areas where theory building is in the formative stages, for studies where the experiences of participants and context of actions are critical, and for studies aimed at understanding complex, temporal processes (why and how) rather than factors or causes (what). This method is well-suited for studying complex organisational processes that involve multiple participants and interacting sequences of events, such as organisational change and large-scale technology implementation projects.

Second, what is the appropriate unit of analysis for a case research study? Since case research can simultaneously examine multiple units of analyses, the researcher must decide whether she wishes to study a phenomenon at the individual, group, or organisational level or at multiple levels. For instance, a study of group decision-making or group work may combine individual-level constructs such as individual participation in group activities with group-level constructs, such as group cohesion and group leadership, to derive richer understanding than can be achieved from a single level of analysis.

Third, should the researcher employ a single-case or multiple-case design? The single-case design is more appropriate at the outset of theory generation, if the situation is unique or extreme, if it is revelatory (i.e., the situation was previously inaccessible for scientific investigation), or if it represents a critical or contrary case for testing a well-formulated theory. The multiple-case design is more appropriate for theory testing, for establishing generalisability of inferences, and for developing richer and more nuanced interpretations of a phenomenon. Yin (1984) [2] recommends the use of multiple case sites with replication logic, viewing each case site as similar to one experimental study, and following rules of scientific rigor similar to that used in positivist research.

Fourth, what sites should be chosen for case research? Given the contextualised nature of inferences derived from case research, site selection is a particularly critical issue because selecting the wrong site may lead to the wrong inferences. If the goal of the research is to test theories or examine generalisability of inferences, then dissimilar case sites should be selected to increase variance in observations. For instance, if the goal of the research is to understand the process of technology implementation in firms, a mix of large, mid-sized, and small firms should be selected to examine whether the technology implementation process differs with firm size. Site selection should not be opportunistic or based on convenience, but rather based on the fit with research questions though a process called ‘theoretical sampling’.

Fifth, what techniques of data collection should be used in case research? Although interview (either open-ended/unstructured or focused/structured) is by far the most popular data collection technique for case research, interview data can be supplemented or corroborated with other techniques such as direct observation (e.g., attending executive meetings, briefings, and planning sessions), documentation (e.g., internal reports, presentations, and memoranda, as well as external accounts such as newspaper reports), archival records (e.g., organisational charts, financial records, etc.), and physical artefacts (e.g., devices, outputs, tools). Furthermore, the researcher should triangulate or validate observed data by comparing responses between interviewees.

Conducting case research

Most case research studies tend to be interpretive in nature. Interpretive case research is an inductive technique where evidence collected from one or more case sites is systematically analysed and synthesised to allow concepts and patterns to emerge for the purpose of building new theories or expanding existing ones. Eisenhardt (1989) [3] proposed a ‘roadmap’ for building theories from case research—a slightly modified version of which is described below. For positivist case research, some of the following stages may need to be rearranged or modified, however sampling, data collection, and data analytic techniques should generally remain the same.

Define research questions. Like any other scientific research, case research must also start with defining research questions that are theoretically and practically interesting, and identifying some intuitive expectations about possible answers to those research questions or preliminary constructs to guide initial case design. In positivist case research, the preliminary constructs are based on theory, while no such theories or hypotheses should be considered ex ante in interpretive research. These research questions and constructs may be changed in interpretive case research later on, if needed, but not in positivist case research.

Select case sites. The researcher should use a process of ‘theoretical sampling’—not random sampling—to identify case sites. In this approach, case sites are chosen based on theoretical rather than statistical considerations—for instance, to replicate previous cases, to extend preliminary theories, or to fill theoretical categories or polar types. Care should be taken to ensure that the selected sites fit the nature of research questions, minimise extraneous variance or noise due to firm size, industry effects, and so forth, and maximise variance in the dependent variables of interest. For instance, if the goal of the research is to examine how some firms innovate better than others, the researcher should select firms of similar size within the same industry to reduce industry or size effects, and select some more innovative and some less innovative firms to increase variation in firm innovation. Instead of cold-calling or writing to a potential site, it is better to contact someone at executive level inside each firm who has the authority to approve the project, or someone who can identify a person of authority. During initial conversations, the researcher should describe the nature and purpose of the project, any potential benefits to the case site, how the collected data will be used, the people involved in data collection (other researchers, research assistants, etc.), desired interviewees, and the amount of time, effort, and expense required of the sponsoring organisation. The researcher must also assure confidentiality, privacy, and anonymity of both the firm and the individual respondents.

Create instruments and protocols. Since the primary mode of data collection in case research is interviews, an interview protocol should be designed to guide the interview process. This is essentially a list of questions to be asked. Questions may be open-ended (unstructured) or closed-ended (structured) or a combination of both. The interview protocol must be strictly followed, and the interviewer must not change the order of questions or skip any question during the interview process, although some deviations are allowed to probe further into a respondent’s comments if they are ambiguous or interesting. The interviewer must maintain a neutral tone, and not lead respondents in any specific direction—for example, by agreeing or disagreeing with any response. More detailed interviewing techniques are discussed in the chapter on surveys. In addition, additional sources of data—such as internal documents and memorandums, annual reports, financial statements, newspaper articles, and direct observations—should be sought to supplement and validate interview data.

Select respondents. Select interview respondents at different organisational levels, departments, and positions to obtain divergent perspectives on the phenomenon of interest. A random sampling of interviewees is most preferable, however a snowball sample is acceptable, as long as a diversity of perspectives is represented in the sample. Interviewees must be selected based on their personal involvement with the phenomenon under investigation and their ability and willingness to answer the researcher’s questions accurately and adequately, and not based on convenience or access.

Start data collection . It is usually a good idea to electronically record interviews for future reference. However, such recording must only be done with the interviewee’s consent. Even when interviews are being recorded, the interviewer should take notes to capture important comments or critical observations, behavioural responses (e.g., the respondent’s body language), and the researcher’s personal impressions about the respondent and his/her comments. After each interview is completed, the entire interview should be transcribed verbatim into a text document for analysis.

Conduct within-case data analysis. Data analysis may follow or overlap with data collection. Overlapping data collection and analysis has the advantage of adjusting the data collection process based on themes emerging from data analysis, or to further probe into these themes. Data analysis is done in two stages. In the first stage (within-case analysis), the researcher should examine emergent concepts separately at each case site and patterns between these concepts to generate an initial theory of the problem of interest. The researcher can use interview data subjectively to ‘make sense’ of the research problem in conjunction with using his/her personal observations or experience at the case site. Alternatively, a coding strategy such as Glaser and Strauss’ (1967) [4] grounded theory approach, using techniques such as open coding, axial coding, and selective coding, may be used to derive a chain of evidence and inferences. These techniques are discussed in detail in a later chapter. Homegrown techniques, such as graphical representation of data (e.g., network diagram) or sequence analysis (for longitudinal data) may also be used. Note that there is no predefined way of analysing the various types of case data, and the data analytic techniques can be modified to fit the nature of the research project.

Conduct cross-case analysis. Multi-site case research requires cross-case analysis as the second stage of data analysis. In such analysis, the researcher should look for similar concepts and patterns between different case sites, ignoring contextual differences that may lead to idiosyncratic conclusions. Such patterns may be used for validating the initial theory, or for refining it—by adding or dropping concepts and relationships—to develop a more inclusive and generalisable theory. This analysis may take several forms. For instance, the researcher may select categories (e.g., firm size, industry, etc.) and look for within-group similarities and between-group differences (e.g., high versus low performers, innovators versus laggards). Alternatively, they can compare firms in a pairwise manner listing similarities and differences across pairs of firms.

Build and test hypotheses. Tenative hypotheses are constructed based on emergent concepts and themes that are generalisable across case sites. These hypotheses should be compared iteratively with observed evidence to see if they fit the observed data, and if not, the constructs or relationships should be refined. Also the researcher should compare the emergent constructs and hypotheses with those reported in the prior literature to make a case for their internal validity and generalisability. Conflicting findings must not be rejected, but rather reconciled using creative thinking to generate greater insight into the emergent theory. When further iterations between theory and data yield no new insights or changes in the existing theory, ‘theoretical saturation’ is reached and the theory building process is complete.

Write case research report. In writing the report, the researcher should describe very clearly the detailed process used for sampling, data collection, data analysis, and hypotheses development, so that readers can independently assess the reasonableness, strength, and consistency of the reported inferences. A high level of clarity in research methods is needed to ensure that the findings are not biased by the researcher’s preconceptions.

Interpretive case research exemplar

Perhaps the best way to learn about interpretive case research is to examine an illustrative example. One such example is Eisenhardt’s (1989) [5] study of how executives make decisions in high-velocity environments (HVE). Readers are advised to read the original paper published in Academy of Management Journal before reading the synopsis in this chapter. In this study, Eisenhardt examined how executive teams in some HVE firms make fast decisions, while those in other firms cannot, and whether faster decisions improve or worsen firm performance in such environments. HVE was defined as one where demand, competition, and technology changes so rapidly and discontinuously that the information available is often inaccurate, unavailable or obsolete. The implicit assumptions were thatit is hard to make fast decisions with inadequate information in HVE, and fast decisions may not be efficient and may result in poor firm performance.

Reviewing the prior literature on executive decision-making, Eisenhardt found several patterns, although none of these patterns were specific to high-velocity environments. The literature suggested that in the interest of expediency, firms that make faster decisions obtain input from fewer sources, consider fewer alternatives, make limited analysis, restrict user participation in decision-making, centralise decision-making authority, and have limited internal conflicts. However, Eisenhardt contended that these views may not necessarily explain how decision makers make decisions in high-velocity environments, where decisions must be made quickly and with incomplete information, while maintaining high decision quality.

To examine this phenomenon, Eisenhardt conducted an inductive study of eight firms in the personal computing industry. The personal computing industry was undergoing dramatic changes in technology with the introduction of the UNIX operating system, RISC architecture, and 64KB random access memory in the 1980s, increased competition with the entry of IBM into the personal computing business, and growing customer demand with double-digit demand growth, and therefore fit the profile of the high-velocity environment. This was a multiple case design with replication logic, where each case was expected to confirm or disconfirm inferences from other cases. Case sites were selected based on their access and proximity to the researcher, however, all of these firms operated in the high-velocity personal computing industry in California’s Silicon Valley area. The collocation of firms in the same industry and the same area ruled out any ‘noise’ or variance in dependent variables (decision speed or performance) attributable to industry or geographic differences.

The study employed an embedded design with multiple levels of analysis: decision (comparing multiple strategic decisions within each firm), executive teams (comparing different teams responsible for strategic decisions), and the firm (overall firm performance). Data was collected from five sources:

Initial interviews with Chief Executive Officers . CEOs were asked questions about their firm’s competitive strategy, distinctive competencies, major competitors, performance, and recent/ongoing major strategic decisions. Based on these interviews, several strategic decisions were selected in each firm for further investigation. Four criteria were used to select decisions: the decisions must involve the firm’s strategic positioning, the decisions must have high stakes, the decisions must involve multiple functions, and the decisions must be representative of strategic decision-making process in that firm.

Interviews with divisional heads . Each divisional head was asked sixteen open-ended questions, ranging from their firm’s competitive strategy, functional strategy, top management team members, frequency and nature of interaction with team, typical decision-making processes, how each of the decisions were made, and how long it took them to make those decisions. Interviews lasted between one and a half and two hours, and sometimes extended to four hours. To focus on facts and actual events rather than respondents’ perceptions or interpretations, a ‘courtroom’ style questioning was employed, such as ‘When did this happen?’, ‘What did you do?’, etc. Interviews were conducted by two people, and the data was validated by cross-checking facts and impressions made by the interviewer and notetaker. All interview data was recorded, however notes were also taken during each interview, which ended with the interviewer’s overall impressions. Using a ‘24-hour rule’, detailed field notes were completed within 24 hours of the interview, so that some data or impressions were not lost to recall.

Questionnaires . Executive team members at each firm were asked tocomplete a survey questionnaire that captured quantitative data on the extent of conflict and power distribution in their firm.

Secondary data . Industry reports and internal documents such as demographics of the executive teams responsible for strategic decisions, financial performance of firms, and so forth, were examined.

Personal observation . Lastly, the researcher attended a one-day strategy session and a weekly executive meeting at two firms in her sample.

Data analysis involved a combination of quantitative and qualitative techniques. Quantitative data on conflict and power were analysed for patterns across firms/decisions. Qualitative interview data was combined into decision climate profiles, using profile traits (e.g., impatience) mentioned by more than one executive. For within-case analysis, decision stories were created for each strategic decision by combining executive accounts of the key decision events into a timeline. For cross-case analysis, pairs of firms were compared for similarities and differences, categorised along variables of interest such as decision speed and firm performance. Based on these analyses, tentative constructs and propositions were derived inductively from each decision story within firm categories. Each decision case was revisited to confirm the proposed relationships. The inferred propositions were compared with findings from the existing literature to examine differences, and to generate new insights from the case findings. Finally, the validated propositions were synthesised into an inductive theory of strategic decision-making by firms in high-velocity environments.

Inferences derived from this multiple case research contradicted several decision-making patterns expected from the existing literature. First, fast decision-makers in high-velocity environments used more information, and not less information as suggested by the previous literature. However, these decision-makers used more real-time information—an insight not available from prior research—which helped them identify and respond to problems, opportunities, and changing circumstances faster. Second, fast decision-makers examined more—not fewer—alternatives. However, they considered these multiple alternatives in a simultaneous manner, while slower decision-makers examined fewer alternatives in a sequential manner. Third, fast decision-makers did not centralise decision-making or restrict inputs from others as the literature suggested. Rather, these firms used a two-tiered decision process in which experienced counsellors were asked for inputs in the first stage, followed by a rapid comparison and decision selection in the second stage. Fourth, fast decision-makers did not have less conflict—as expected from the literature—but employed better conflict resolution techniques to reduce conflict and improve decision-making speed. Finally, fast decision-makers exhibited superior firm performance by virtue of their built-in cognitive, emotional, and political processes that led to rapid closure of major decisions.

Positivist case research exemplar

Case research can also be used in a positivist manner to test theories or hypotheses. Such studies are rare, but Markus (1983) [6] provides an exemplary illustration in her study of technology implementation at the pseudonymous Golden Triangle Company (GTC). The goal of this study was to understand why a newly implemented financial information system (FIS)—intended to improve the productivity and performance of accountants at GTC—was supported by accountants at GTC’s corporate headquarters, but resisted by divisional accountants at GTC branches. Given the uniqueness of the phenomenon of interest, this was a single-case research study.

To explore the reasons behind user resistance of FIS, Markus posited three alternative explanations:

System-determined theory : The resistance was caused by factors related to an inadequate system, such as its technical deficiencies, poor ergonomic design, or lack of user friendliness.

People-determined theory : The resistance was caused by factors internal to users, such as the accountants’ cognitive styles or personality traits that were incompatible with using the system.

Interaction theory : The resistance was not caused not by factors intrinsic to the system or the people, but by the interaction between the two set of factors. Specifically, interaction theory suggested that the FIS engendered a redistribution of intra-organisational power, and accountants who lost organisational status, relevance, or power as a result of FIS implementation resisted the system while those gaining power favoured it.

In order to test the three theories, Markus predicted alternative outcomes expected from each theoretical explanation and analysed the extent to which those predictions matched with her observations at GTC. For instance, the system-determined theory suggested that since user resistance was caused by an inadequate system, fixing the technical problems of the system would eliminate resistance. The computer running the FIS system was subsequently upgraded with a more powerful operating system, online processing (from initial batch processing, which delayed immediate processing of accounting information), and a simplified software for new account creation by managers. One year after these changes were made, the resistant users were still resisting the system and felt that it should be replaced. Hence, the system-determined theory was rejected.

The people-determined theory predicted that replacing individual resistors or co-opting them with less resistant users would reduce their resistance toward the FIS. Subsequently, GTC started a job rotation and mobility policy, moving accountants in and out of the resistant divisions, but resistance not only persisted, but in some cases increased. In one instance, an accountant who was one of the system’s designers and advocates when he worked for corporate accounting started resisting the system after he was moved to the divisional controller’s office. Failure to realise the predictions of the people-determined theory led to the rejection of this theory.

Finally, the interaction theory predicted that neither changing the system nor the people (i.e., user education or job rotation policies) would reduce resistance until the power imbalance and redistribution from the pre-implementation phase was addressed. Before FIS implementation, divisional accountants at GTC felt that they owned all accounting data related to their divisional operations. They maintained this data in thick, manual ledger books, controlled others’ access to the data, and could reconcile unusual accounting events before releasing those reports. Corporate accountants relied heavily on divisional accountants for access to the divisional data for corporate reporting and consolidation. Because the FIS system automatically collected all data at the source and consolidated it into a single corporate database, it obviated the need for divisional accountants, loosened their control and autonomy over their division’s accounting data, and making their job somewhat irrelevant. Corporate accountants could now query the database and access divisional data directly without going through the divisional accountants, analyse and compare the performance of individual divisions, and report unusual patterns and activities to the executive committee, resulting in further erosion of the divisions’ power. Though Markus did not empirically test this theory, her observations about the redistribution of organisational power, coupled with the rejection of the two alternative theories, led to the justification of interaction theory.

Comparisons with traditional research

Positivist case research, aimed at hypotheses testing, is often criticised by natural science researchers as lacking in controlled observations, controlled deductions, replicability, and generalisability of findings—the traditional principles of positivist research. However, these criticisms can be overcome through appropriate case research designs. For instance, the problem of controlled observations refers to the difficulty of obtaining experimental or statistical control in case research. However, case researchers can compensate for such lack of controls by employing ’natural controls’. This natural control in Markus’ (1983) study was the corporate accountant who was one of the system advocates initially, but started resisting it once he moved to the controlling division. In this instance, the change in his behaviour may be attributed to his new divisional position. However, such natural controls cannot be anticipated in advance, and case researchers may overlook them unless they are proactively looking for such controls. Incidentally, natural controls are also used in natural science disciplines such as astronomy, geology, and human biology—for example, waiting for comets to pass close enough to the earth in order to make inferences about comets and their composition.

Third, the problem of replicability refers to the difficulty of observing the same phenomenon considering the uniqueness and idiosyncrasy of a given case site. However, using Markus’ three theories as an illustration, a different researcher can test the same theories at a different case site, where three different predictions may emerge based on the idiosyncratic nature of the new case site, and the three resulting predictions may be tested accordingly. In other words, it is possible to replicate the inferences of case research, even if the case research site or context may not be replicable.

Fourth, case research tends to examine unique and non-replicable phenomena that may not be generalised to other settings. Generalisability in natural sciences is established through additional studies. Likewise, additional case studies conducted in different contexts with different predictions can establish generalisability of findings if such findings are observed to be consistent across studies.

Lastly, British philosopher Karl Popper described four requirements of scientific theories: theories should be falsifiable, they should be logically consistent, they should have adequate predictive ability, and they should provide better explanation than rival theories. In case research, the first three requirements can be improved by increasing the degrees of freedom of observed findings—for example, by increasing the number of case sites, the number of alternative predictions, and the number of levels of analysis examined. This was accomplished in Markus’ study by examining the behaviour of multiple groups (divisional accountants and corporate accountants) and providing multiple (three) rival explanations. Popper’s fourth condition was accomplished in this study when one hypothesis was found to match observed evidence better than the two rival hypotheses.

• Benbasat, I., Goldstein, D. K., & Mead, M. (1987). The case research strategy in studies of information systems. MIS Quarterly , 11(3), 369–386. ↵
• Yin, R. (1984). Case study research: Design and methods . London: Sage Publications. ↵
• Eisenhardt, K. M. (1989). Building theories from case research. Academy of Management Review , 14(4), 532–550 ↵
• Glaser, B., & Strauss, A. (1967). The discovery of grounded theory: Strategies for qualitative research . New York: Aldine Pub Co. ↵
• Eisenhardt, K. M. (1989). Making fast strategic decisions in high-velocity environments. Academy of Management Journal , 32(3), 543–576. ↵
• Markus, M. L. (1983). Power, politics and MIS implementations. Communications of the ACM , 26(6), 430–444. ↵

Social Science Research: Principles, Methods and Practices (Revised edition) Copyright © 2019 by Anol Bhattacherjee is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Case Studies | January 15, 2020

How to a Create Compelling Case Study Using Surveys (+Examples)

There are things you can kill - a good story is certainly not one of them. Stories are immortal, particularly when they are captivating, insightful, and memorable. 

When Plato said, "those who tell stories rule the world," he certainly wasn't thinking about marketing, but nowhere could that quote be even more real and emphatic.

Seth Godin couldn't have put it better: "marketing is no longer about the stuff that you make, but about the stories you tell." That is why case studies are crucial to the growth of every business .

A case study is content that details the success story of a product or service. Typically, it outlines the problems the client had and how the service or product of a business resolved them. In this article you’ll learn:

• Know why your business needs to invest in case studies
• Learn how to prepare a case study 
• Learn how surveys can make your case more effective
• Different ways to use case studies for maximum impact

Featured Resource:

This guide shares a process for making compelling case studies to convert more prospects. To make the most out of it, we’ve prepared a case study template, checklist, and 13 examples you can use for inspiration. 

Table of Contents

Why should you invest in a case study?

Almost every business can improve its results by investing in case studies. Below are a few reasons case studies are invaluable for your business.

Shows prospective clients how you work

Sometimes, leads don’t realize they have a certain problem that your product or service can resolve. A case study can provide a clear overview of the value you bring to the table. This is particularly useful for business and marketing consultants , where the outcomes may not be as visible.

It establishes your authority

Case studies are particularly effective for companies offering a product or service focused on a certain niche. They show how a company like theirs benefitted from your service. Ninja Outreach is a good example of this.

It has gathered case studies that focus on the problems of their various customer personas. This ranges from a firm running a PR campaign to an eCommerce store doing email outreach to land guest post placements. Each case study is designed to resonate with a specific customer persona to help them see the value of the product.

It Shows Prospective Clients How you Work

A good case study illustrates how you work and approach a problem. For example, if one of your unique selling points is excellent customer service, a case study can highlight this through the words of an existing client.

A good case study can also help set expectations. For example, your case study might explain how you start every project with a two week review period. Or your company works in sprints. Again, it clarifies what a customer should expect when working with you. 

It’s an Excellent Lead Generation Tool

When you’ve dialed in your messaging, you’re attracting the right type of visitor and they believe your service is right for them. The only thing left is proof of results and a case study can serve that purpose. When you use it for lead generation and require prospects to download it, you know they’re qualified and can follow up with them confidently. 

People researching a company often look for social endorsements before making a purchase or investing in a service. It is part of the customer journey . Social proof, like that offered in the form of a case study, can help convert a warm lead into a customer.

How to Prepare Your Case Study

We’ve covered some of the reasons why a case study can be such an essential element of your business development strategy . Now, let’s focus on how to create a case study that engages and converts a lead and plays a role in turning them into a customer.

Start with a Clear Objective

Ultimately, the objective of your case study is the same; to help turn a warm lead into a paying customer. To do that with case studies, you should understand who you’re targeting . 

A customer persona will make this easier. It should reflect the different types of people or companies that seek your service and your case studies should be created to appeal to them.

Find the right candidate for your case study

If you have delivered value, finding clients for case studies should be easy. A case study doesn’t only benefit you; the client being featured receives several benefits including backlinks and exposure of their brand. 

You don’t always have to wait until the end of the contract to ask a client to be your case study. You can ask for a case study as soon as you deliver a solution that works. However, this should be determined on a case-by-case basis. 

Select Medium(s)

While most people are familiar with written case studies, there are many other ways to share your message. These days podcasts shows , platforms like Pinterest, and video channels have a huge say in marketing. Choose as many mediums as you can so you’re creating content the way your visitor wants to consume it.

Though this article is mainly for people who are writing a case study, it can be used during the research process for a video testimonial. 

Why Use Surveys When Creating a Case Study?

The effectiveness of a case study is based on the insights you get from the client. While you probably have the outcomes clearly defined before you start the process, the little details make your content engaging.

When preparing a case study, you should collect two types of data; quantitative and qualitative. Quantitative data refers to that which can be measured. This covers things like profit, traffic to the website, leads, conversions, etc.

Qualitative data refers to opinions and sentiments about a product or service. Essentially, it’s about what the client has to say about your product or service.

Questionnaires help you extract accurate quantitative and qualitative information. This will put you in the best position to create case studies that are valuable resources for your business.

What Questions Should You Ask in a Survey?

The questions in a case study survey should revolve around the following:

• The challenge or problem the client was facing
• How the challenge was addressed
• The benefits the client experienced or is experiencing

You should ask a mixture of closed (yes or no questions) as well as open-ended questions . Your questions should be simple and straight to the point. Some simple questions you can ask include:

• How was the problem you faced affecting your business?
• If you didn’t find our solution, where would you be now?
• Did you seek other solutions? Were they any help?
• Why did you choose us over our competitors?
• What was your most memorable moment working with us?
• How has our solution transformed your business?

Don’t overburden the client with a truckload of questions: 20 questions or less should suffice.

Your survey will help you prepare for a follow-up interview where you can ask clarifying questions based on the information you received. Read more about choosing the right type of surveys in this article .

The importance of storytelling

Let’s dig deeper into the importance of storytelling. Dr. Howard Gardner, a professor at Harvard University aptly remarked: “Stories constitute the single most powerful weapon in a leader’s arsenal.”

Data, insights, and statistics from surveys and interviews are critical, but an engaging study will have its roots in a story. Rob Walker and Joshua Glenn put the power of stories to the test by purchasing various “insignificant” objects each for $1.25 on average. 

They engaged about 200 writers to help put a narrative to the objects on eBay. Each item had a heartfelt short story written underneath. Guess what? The items, on average, sold for  2,700% above their original price.

People make emotional decisions regarding purchases, and that is why stories can ramp the value of your products. Our brains are hardwired for stories . Here are simple ways to inject storytelling in your case study.

• Make your client the hero: Everybody loves heroes. Imagine Superman was killed right at the beginning of the movie. There would undoubtedly be a money-back hashtag immediately trending. 
• Let the client tell the story: Focus on the client’s story because yours naturally supports it.
• Write in an engaging way: Don’t write in a boring, dry, and monotonous style. Give life to your content by writing in a conversational tone. If you can’t then hire someone from one of the popular freelancing websites  who is well-versed in case studies.
• Give evidence : That’s the name of the game: evidence. Then, back up your client’s claims with screenshots, pictures, infographics, etc. 

4 Ways to use a case study in your sales funnel

Sales funnels are crucial to the bottom line. With a well-laid-out sales funnel, businesses can plan, strategize, and optimize their customer’s buying journey. Here’s a general idea of what a sales funnel looks like.

Here are some ways to integrate case studies into your sales funnel.

Make it accessible on your website

Case studies should be readily accessible on your website because they help your visitor learn more about your company and move down the sales funnel.

Make your case studies, particularly recent ones, prominent on your website. Consider placing it on your home page or within your main navigation. Many companies have a dedicated case study page or section on their site like this:

Source: crazyegg.com

Take out some quotes from your case studies, have your designers add a touch to it, and put it on your website, along with a link to the case study posts. You can also link to your case studies from landing pages.

Incorporate Your Case Study in an Email Marketing Campaign

When a person signs up to your email list, they are open to learning more about your company. You can use your email marketing software to introduce the prospect to your brand, familiarize them with your service, and generate revenue.

It is natural to incorporate case studies within your email campaigns. Particularly so if you are an agency selling a service.

The case study forms a natural reference point as the prospect learns about your company and the products and services you offer. Check out this insightful article on email marketing to learn more about the topic.

Use it for Cold Email Outreach

Cold emails are a powerful sales approach for generating leads and getting conversions. Businesses often cold pitch to leads that have little knowledge of the company approaching them.

A case study attached to a professional email , as a PDF, is a logical way to introduce them to the service you deliver. Alternatively, you could insert extracts from a case study into the email you are sending to a lead.

Here’s an example:

Use your case study in your sales meetings

Researching, writing, and creating a case study is a time-consuming process. However, through this process, you learn a lot about the pain points your customers faced and the benefits they accrued.

All of this information is useful when pitching to a prospect. You can draw on this knowledge to better align the product or service you are providing with the problems a lead faces. This ability to empathize can help you make a sale. It’s particularly important in B2B sales because there’s a lot of money on the line. You can incorporate case studies into your business proposal and use them to illustrate your process and the value you bring to the table.

Of course, a case study is a useful prop for a sales meeting. Provided in the form of a brochure, they give people something to leaf through after a meeting. You can also use it in a meeting when making a point.

According to Global Trust in Advertising and Brand Messages , a report by Nielsen, online consumer reviews are the second most trusted source of brand recommendation. Case studies are, in essence, strong peer recommendations. 

This lends credence to your business. People are more likely to believe claims from consumers like them, who share their problems. 

When fleshed out, the best case studies are based on the information you glean from clients. That is where surveys are crucial. Use the points listed above to give your case studies an X-factor that’ll help you drum up more revenue.

Owen Baker is a content marketer for Voila Norbert, an online email verification tool . He’s spent over a decade in online marketing. He enjoys sharing his knowledge of content marketing across a range of websites.

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Integrating case study and survey research methods: an example in information systems

• Original Article
• Published: 01 January 1994
• Volume 3 , pages 112–126, ( 1994 )

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• G.G. Gable 1  

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The case for combining research methods generally, and more specifically that for combining qualitative and quantitative methods, is strong. Yet, research designs that extensively integrate both fieldwork (e.g. case studies) and survey research are rare. Moreover, some journals tend tacitly to specialise by methodology thereby encouraging purity of method. The multi-method model of research, while not new, has not been appreciated. In this respect it is useful to describe its usage through example. By reference to a recently completed study of IS consultant engagement success factors this paper presents an analysis of the benefits of integrating case study and survey research methods. The emphasis is on the qualitative case study method and how it can complement more quantitative survey research. Benefits are demonstrated through specific examples from the reference study.

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Gable, G. Integrating case study and survey research methods: an example in information systems. Eur J Inf Syst 3 , 112–126 (1994). https://doi.org/10.1057/ejis.1994.12

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• v.35(45); 2020 Nov 23

Reporting Survey Based Studies – a Primer for Authors

Prithvi sanjeevkumar gaur.

1 Smt. Kashibai Navale Medical College and General Hospital, Pune, India.

Olena Zimba

2 Department of Internal Medicine No. 2, Danylo Halytsky Lviv National Medical University, Lviv, Ukraine.

Vikas Agarwal

3 Department Clinical Immunology and Rheumatology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India.

Latika Gupta

Associated data.

The coronavirus disease 2019 (COVID-19) pandemic has led to a massive rise in survey-based research. The paucity of perspicuous guidelines for conducting surveys may pose a challenge to the conduct of ethical, valid and meticulous research. The aim of this paper is to guide authors aiming to publish in scholarly journals regarding the methods and means to carry out surveys for valid outcomes. The paper outlines the various aspects, from planning, execution and dissemination of surveys followed by the data analysis and choosing target journals. While providing a comprehensive understanding of the scenarios most conducive to carrying out a survey, the role of ethical approval, survey validation and pilot testing, this brief delves deeper into the survey designs, methods of dissemination, the ways to secure and maintain data anonymity, the various analytical approaches, the reporting techniques and the process of choosing the appropriate journal. Further, the authors analyze retracted survey-based studies and the reasons for the same. This review article intends to guide authors to improve the quality of survey-based research by describing the essential tools and means to do the same with the hope to improve the utility of such studies.

Graphical Abstract

INTRODUCTION

Surveys are the principal method used to address topics that require individual self-report about beliefs, knowledge, attitudes, opinions or satisfaction, which cannot be assessed using other approaches. 1 This research method allows information to be collected by asking a set of questions on a specific topic to a subset of people and generalizing the results to a larger population. Assessment of opinions in a valid and reliable way require clear, structured and precise reporting of results. This is possible with a survey based out of a meticulous design, followed by validation and pilot testing. 2 The aim of this opinion piece is to provide practical advice to conduct survey-based research. It details the ethical and methodological aspects to be undertaken while performing a survey, the online platforms available for distributing survey, and the implications of survey-based research.

Survey-based research is a means to obtain quick data, and such studies are relatively easy to conduct and analyse, and are cost-effective (under a majority of the circumstances). 3 These are also one of the most convenient methods of obtaining data about rare diseases. 4 With major technological advancements and improved global interconnectivity, especially during the coronavirus disease 2019 (COVID-19) pandemic, surveys have surpassed other means of research due to their distinctive advantage of a wider reach, including respondents from various parts of the world having diverse cultures and geographically disparate locations. Moreover, survey-based research allows flexibility to the investigator and respondent alike. 5 While the investigator(s) may tailor the survey dates and duration as per their availability, the respondents are allowed the convenience of responding to the survey at ease, in the comfort of their homes, and at a time when they can answer the questions with greater focus and to the best of their abilities. 6 Respondent biases inherent to environmental stressors can be significantly reduced by this approach. 5 It also allows responses across time-zones, which may be a major impediment to other forms of research or data-collection. This allows distant placement of the investigator from the respondents.

Various digital tools are now available for designing surveys ( Table 1 ). 7 Most of these are free with separate premium paid options. The analysis of data can be made simpler and cleaning process almost obsolete by minimising open-ended answer choices. 8 Close-ended answers makes data collection and analysis efficient, by generating an excel which can be directly accessed and analysed. 9 Minimizing the number of questions and making all questions mandatory can further aid this process by bringing uniformity to the responses and analysis simpler. Surveys are arguably also the most engaging form of research, conditional to the skill of the investigator.

Q/t = questions per typeform, A/m = answers per month, Q/s = questions per survey, A/s = answers per survey, NA = not applicable, NPS = net promoter score.

Data protection laws now mandate anonymity while collecting data for most surveys, particularly when they are exempt from ethical review. 10 , 11 Anonymization has the potential to reduce (or at times even eliminate) social desirability bias which gains particular relevance when targeting responses from socially isolated or vulnerable communities (e.g. LGBTQ and low socio-economic strata communities) or minority groups (religious, ethnic and medical) or controversial topics (drug abuse, using language editing software).

Moreover, surveys could be the primary methodology to explore a hypothesis until it evolves into a more sophisticated and partly validated idea after which it can be probed further in a systematic and structured manner using other research methods.

The aim of this paper is to reduce the incorrect reporting of surveys. The paper also intends to inform researchers of the various aspects of survey-based studies and the multiple points that need to be taken under consideration while conducting survey-based research.

SURVEYS IN THE COVID-19 PANDEMIC

The COVID-19 has led to a distinctive rise in survey-based research. 12 The need to socially distance amid widespread lockdowns reduced patient visits to the hospital and brought most other forms of research to a standstill in the early pandemic period. A large number of level-3 bio-safety laboratories are being engaged for research pertaining to COVID-19, thereby limiting the options to conduct laboratory-based research. 13 , 14 Therefore, surveys appear to be the most viable option for researchers to explore hypotheses related to the situation and its impact in such times. 15

LIMITATIONS WHILE CONDUCTING SURVEY-BASED RESEARCH

Designing a fine survey is an arduous task and requires skill even though clear guidelines are available in regard to the same. Survey design requires extensive thoughtfulness on the core questions (based on the hypothesis or the primary research question), with consideration of all possible answers, and the inclusion of open-ended options to allow recording other possibilities. A survey should be robust, in regard to the questions gathered and the answer choices available, it must be validated, and pilot tested. 16 The survey design may be supplanted with answer choices tailored for the convenience of the responder, to reduce the effort while making it more engaging. Survey dissemination and engagement of respondents also requires experience and skill. 17

Furthermore, the absence of an interviewer prevents us from gaining clarification on responses of open-ended questions if any. Internet surveys are also prone to survey fraud by erroneous reporting. Hence, anonymity of surveys is a boon and a bane. The sample sizes are skewed as it lacks representation of population absent on the Internet like the senile or the underprivileged. The illiterate population also lacks representation in survey-based research.

The “Enhancing the QUAlity and Transparency Of health Research” network (EQUATOR) provides two separate guidelines replete with checklists to ensure valid reporting of e-survey methodology. These include “The Checklist for Reporting Results of Internet E-Surveys” (CHERRIES) statement and “ The Journal of Medical Internet Research ” (JMIR) checklist.

COMMON TYPES OF SURVEY-BASED RESEARCH

From a clinician's standpoint, the common survey types include those centered around problems faced by the patients or physicians. 18 Surveys collecting the opinions of various clinicians on a debated clinical topic or feedback forms typically served after attending medical conferences or prescribing a new drug or trying a new method for a given procedure are also surveys. The formulation of clinical practice guidelines entails Delphi exercises using paper surveys, which are yet another form of survey-mediated research.

Size of the survey depends on its intent. They could be large or small surveys. Therefore, identification of the intent behind the survey is essential to allow the investigator to form a hypothesis and then explore it further. Large population-based or provider-based surveys are often done and generate mammoth data over the years. E.g. The National Health and Nutrition Examination Survey, The National Health Interview Survey and the National Ambulatory Medical Care Survey.

SCENARIOS FOR CONDUCTING SURVEY-BASED RESEARCH

Despite all said and done about the convenience of conducting survey-based research, it is prudent to conduct a feasibility check before embarking on one. Certain scenarios may be the key determinants in determining the fate of survey-based research ( Table 2 ).

ETHICS APPROVAL FOR SURVEY-BASED RESEARCH

Approval from the Institutional Review Board should be taken as per requirement according to the CHERRIES checklist. However, rules for approval are different as per the country or nation and therefore, local rules must be checked and followed. For instance, in India, the Indian Council of Medical Research released an article in 2017, stating that the concept of broad consent has been updated which is defined “consent for an unspecified range of future research subject to a few contents and/or process restrictions.” It talks about “the flexibility of Indian ethics committees to review a multicentric study proposal for research involving low or minimal risk, survey or studies using anonymized samples or data or low or minimal risk public health research.” The reporting of approvals received and applied for and the procedure of written, informed consent followed must be clear and transparent. 10 , 19

The use of incentives in surveys is also an ethical concern. 20 The different of incentives that can be used are monetary or non-monetary. Monetary incentives are usually discouraged as these may attract the wrong population due to the temptation of the monetary benefit. However, monetary incentives have been seen to make survey receive greater traction even though this is yet to proven. Monetary incentives are not only provided in terms of cash or cheque but also in the form of free articles, discount coupons, phone cards, e-money or cashback value. 21 These methods though tempting must be seldom used. If used, their use must be disclosed and justified in the report. The use of non-monetary incentives like a meeting with a famous personality or access to restricted and authorized areas. These can also help pique the interest of the respondents.

DESIGNING A SURVEY

As mentioned earlier, the design of a survey is reflective of the skill of the investigator curating it. 22 Survey builders can be used to design an efficient survey. These offer majority of the basic features needed to construct a survey, free of charge. Therefore, surveys can be designed from scratch, using pre-designed templates or by using previous survey designs as inspiration. Taking surveys could be made convenient by using the various aids available ( Table 1 ). Moreover, even the investigator should be mindful of the unintended response effects of ordering and context of survey questions. 23

Surveys using clear, unambiguous, simple and well-articulated language record precise answers. 24 A well-designed survey accounts for the culture, language and convenience of the target demographic. The age, region, country and occupation of the target population is also considered before constructing a survey. Consistency is maintained in the terms used in the survey and abbreviations are avoided to allow the respondents to have a clear understanding of the question being answered. Universal abbreviations or previously indexed abbreviations maintain the unambiguity of the survey.

Surveys beginning with broad, easy and non-specific questions as compared to sensitive, tedious and non-specific ones receive more accurate and complete answers. 25 Questionnaires designed such that the relatively tedious and long questions requiring the respondent to do some nit-picking are placed at the end improves the response rate of the survey. This prevents the respondent to be discouraged to answer the survey at the beginning itself and motivates the respondent to finish the survey at the end. All questions must provide a non-response option and all questions should be made mandatory to increase completeness of the survey. Questions can be framed in close-ended or open-ended fashion. However, close-ended questions are easier to analyze and are less tedious to answer by the respondent and therefore must be the main component in a survey. Open-ended questions have minimal use as they are tedious, take time to answer and require fine articulation of one's thoughts. Also, their minimal use is advocated because the interpretation of such answers requires dedication in terms of time and energy due to the diverse nature of the responses which is difficult to promise owing to the large sample sizes. 26 However, whenever the closed choices do not cover all probabilities, an open answer choice must be added. 27 , 28

Screening questions to meet certain criteria to gain access to the survey in cases where inclusion criteria need to be established to maintain authenticity of target demographic. Similarly, logic function can be used to apply an exclusion. This allows clean and clear record of responses and makes the job of an investigator easier. The respondents can or cannot have the option to return to the previous page or question to alter their answer as per the investigator's preference.

The range of responses received can be reduced in case of questions directed towards the feelings or opinions of people by using slider scales, or a Likert scale. 29 , 30 In questions having multiple answers, check boxes are efficient. When a large number of answers are possible, dropdown menus reduce the arduousness. 31 Matrix scales can be used to answer questions requiring grading or having a similar range of answers for multiple conditions. Maximum respondent participation and complete survey responses can be ensured by reducing the survey time. Quiz mode or weighted modes allow the respondent to shuffle between questions and allows scoring of quizzes and can be used to complement other weighted scoring systems. 32 A flowchart depicting a survey construct is presented as Fig. 1 .

Survey validation

Validation testing though tedious and meticulous, is worthy effort as the accuracy of a survey is determined by its validity. It is indicative of the of the sample of the survey and the specificity of the questions such that the data acquired is streamlined to answer the questions being posed or to determine a hypothesis. 33 , 34 Face validation determines the mannerism of construction of questions such that necessary data is collected. Content validation determines the relation of the topic being addressed and its related areas with the questions being asked. Internal validation makes sure that the questions being posed are directed towards the outcome of the survey. Finally, Test – retest validation determines the stability of questions over a period of time by testing the questionnaire twice and maintaining a time interval between the two tests. For surveys determining knowledge of respondents pertaining to a certain subject, it is advised to have a panel of experts for undertaking the validation process. 2 , 35

Reliability testing

If the questions in the survey are posed in a manner so as to elicit the same or similar response from the respondents irrespective of the language or construction of the question, the survey is said to be reliable. It is thereby, a marker of the consistency of the survey. This stands to be of considerable importance in knowledge-based researches where recall ability is tested by making the survey available for answering by the same participants at regular intervals. It can also be used to maintain authenticity of the survey, by varying the construction of the questions.

Designing a cover letter

A cover letter is the primary means of communication with the respondent, with the intent to introduce the respondent to the survey. A cover letter should include the purpose of the survey, details of those who are conducting it, including contact details in case clarifications are desired. It should also clearly depict the action required by the respondent. Data anonymization may be crucial to many respondents and is their right. This should be respected in a clear description of the data handling process while disseminating the survey. A good cover letter is the key to building trust with the respondent population and can be the forerunner to better response rates. Imparting a sense of purpose is vital to ideationally incentivize the respondent population. 36 , 37 Adding the credentials of the team conducting the survey may further aid the process. It is seen that an advance intimation of the survey prepares the respondents while improving their compliance.

The design of a cover letter needs much attention. It should be captivating, clear, precise and use a vocabulary and language specific to the target population for the survey. Active voice should be used to make a greater impact. Crowding of the details must be avoided. Using italics, bold fonts or underlining may be used to highlight critical information. the tone ought to be polite, respectful, and grateful in advance. The use of capital letters is at best avoided, as it is surrogate for shouting in verbal speech and may impart a bad taste.

The dates of the survey may be intimated, so the respondents may prepare themselves for taking it at a time conducive to them. While, emailing a closed group in a convenience sampled survey, using the name of the addressee may impart a customized experience and enhance trust building and possibly compliance. Appropriate use of salutations like Mr./Ms./Mrs. may be considered. Various portals such as SurveyMonkey allow the researchers to save an address list on the website. These may then be reached out using an embedded survey link from a verified email address to minimize bouncing back of emails.

The body of the cover letter must be short, crisp and not exceed 2–3 paragraphs under idea circumstances. Ernest efforts to protect confidentiality may go a long way in enhancing response rates. 38 While it is enticing to provide incentives to enhance response, these are best avoided. 38 , 39 In cases when indirect incentives are offered, such as provision of results of the survey, these may be clearly stated in the cover letter. Lastly, a formal closing note with the signatures of the lead investigator are welcome. 38 , 40

Designing questions

Well-constructed questionnaires are essentially the backbone of successful survey-based studies. With this type of research, the primary concern is the adequate promotion and dissemination of the questionnaire to the target population. The careful of selection of sample population, therefore, needs to be with minimal flaws. The method of conducting survey is an essential determinant of the response rate observed. 41 Broadly, surveys are of two types: closed and open. Depending on the sample population the method of conducting the survey must be determined.

Various doctors use their own patients as the target demographic, as it improves compliance. However, this is effective in surveys aiming towards a geographically specific, fairly common disease as the sample size needs to be adequate. Response bias can be identified by the data collected from respondent and non-respondent groups. 42 , 43 Therefore, to choose a target population whose database of baseline characteristics is already known is more efficacious. In cases of surveys focused on patients having a rare group of diseases, online surveys or e-surveys can be conducted. Data can also be gathered from the multiple national organizations and societies all over the world. 44 , 45 Computer generated random selection can be done from this data to choose participants and they can be reached out to using emails or social media platforms like WhatsApp and LinkedIn. In both these scenarios, closed questionnaires can be conducted. These have restricted access either through a URL link or through e-mail.

In surveys targeting an issue faced by a larger demographic (e.g. pandemics like the COVID-19, flu vaccines and socio-political scenarios), open surveys seem like the more viable option as they can be easily accessed by majority of the public and ensures large number of responses, thereby increasing the accuracy of the study. Survey length should be optimal to avoid poor response rates. 25 , 46

SURVEY DISSEMINATION

Uniform distribution of the survey ensures equitable opportunity to the entire target population to access the questionnaire and participate in it. While deciding the target demographic communities should be studied and the process of “lurking” is sometimes practiced. Multiple sampling methods are available ( Fig. 1 ). 47

Distribution of survey to the target demographic could be done using emails. Even though e-mails reach a large proportion of the target population, an unknown sender could be blocked, making the use of personal or a previously used email preferable for correspondence. Adding a cover letter along with the invite adds a personal touch and is hence, advisable. Some platforms allow the sender to link the survey portal with the sender's email after verifying it. Noteworthily, despite repeated email reminders, personal communication over the phone or instant messaging improved responses in the authors' experience. 48 , 49

Distribution of the survey over other social media platforms (SMPs, namely WhatsApp, Facebook, Instagram, Twitter, LinkedIn etc.) is also practiced. 50 , 51 , 52 Surveys distributed on every available platform ensures maximal outreach. 53 Other smartphone apps can also be used for wider survey dissemination. 50 , 54 It is important to be mindful of the target population while choosing the platform for dissemination of the survey as some SMPs such as WhatsApp are more popular in India, while others like WeChat are used more widely in China, and similarly Facebook among the European population. Professional accounts or popular social accounts can be used to promote and increase the outreach for a survey. 55 Incentives such as internet giveaways or meet and greets with their favorite social media influencer have been used to motivate people to participate.

However, social-media platforms do not allow calculation of the denominator of the target population, resulting in inability to gather the accurate response rate. Moreover, this method of collecting data may result in a respondent bias inherent to a community that has a greater online presence. 43 The inability to gather the demographics of the non-respondents (in a bid to identify and prove that they were no different from respondents) can be another challenge in convenience sampling, unlike in cohort-based studies.

Lastly, manually filling of surveys, over the telephone, by narrating the questions and answer choices to the respondents is used as the last-ditch resort to achieve a high desired response rate. 56 Studies reveal that surveys released on Mondays, Fridays, and Sundays receive more traction. Also, reminders set at regular intervals of time help receive more responses. Data collection can be improved in collaborative research by syncing surveys to fill out electronic case record forms. 57 , 58 , 59

Data anonymity refers to the protection of data received as a part of the survey. This data must be stored and handled in accordance with the patient privacy rights/privacy protection laws in reference to surveys. Ethically, the data must be received on a single source file handled by one individual. Sharing or publishing this data on any public platform is considered a breach of the patient's privacy. 11 In convenience sampled surveys conducted by e-mailing a predesignated group, the emails shall remain confidential, as inadvertent sharing of these as supplementary data in the manuscript may amount to a violation of the ethical standards. 60 A completely anonymized e-survey discourages collection of Internet protocol addresses in addition to other patient details such as names and emails.

Data anonymity gives the respondent the confidence to be candid and answer the survey without inhibitions. This is especially apparent in minority groups or communities facing societal bias (sex workers, transgenders, lower caste communities, women). Data anonymity aids in giving the respondents/participants respite regarding their privacy. As the respondents play a primary role in data collection, data anonymity plays a vital role in survey-based research.

DATA HANDLING OF SURVEYS

The data collected from the survey responses are compiled in a .xls, .csv or .xlxs format by the survey tool itself. The data can be viewed during the survey duration or after its completion. To ensure data anonymity, minimal number of people should have access to these results. The data should then be sifted through to invalidate false, incorrect or incomplete data. The relevant and complete data should then be analyzed qualitatively and quantitatively, as per the aim of the study. Statistical aids like pie charts, graphs and data tables can be used to report relative data.

ANALYSIS OF SURVEY DATA

Analysis of the responses recorded is done after the time made available to answer the survey is complete. This ensures that statistical and hypothetical conclusions are established after careful study of the entire database. Incomplete and complete answers can be used to make analysis conditional on the study. Survey-based studies require careful consideration of various aspects of the survey such as the time required to complete the survey. 61 Cut-off points in the time frame allow authentic answers to be recorded and analyzed as compared to disingenuous completed questionnaires. Methods of handling incomplete questionnaires and atypical timestamps must be pre-decided to maintain consistency. Since, surveys are the only way to reach people especially during the COVID-19 pandemic, disingenuous survey practices must not be followed as these will later be used to form a preliminary hypothesis.

REPORTING SURVEY-BASED RESEARCH

Reporting the survey-based research is by far the most challenging part of this method. A well-reported survey-based study is a comprehensive report covering all the aspects of conducting a survey-based research.

The design of the survey mentioning the target demographic, sample size, language, type, methodology of the survey and the inclusion-exclusion criteria followed comprises a descriptive report of a survey-based study. Details regarding the conduction of pilot-testing, validation testing, reliability testing and user-interface testing add value to the report and supports the data and analysis. Measures taken to prevent bias and ensure consistency and precision are key inclusions in a report. The report usually mentions approvals received, if any, along with the written, informed, consent taken from the participants to use the data received for research purposes. It also gives detailed accounts of the different distribution and promotional methods followed.

A detailed account of the data input and collection methods along with tools used to maintain the anonymity of the participants and the steps taken to ensure singular participation from individual respondents indicate a well-structured report. Descriptive information of the website used, visitors received and the externally influencing factors of the survey is included. Detailed reporting of the post-survey analysis including the number of analysts involved, data cleaning required, if any, statistical analysis done and the probable hypothesis concluded is a key feature of a well-reported survey-based research. Methods used to do statistical corrections, if used, should be included in the report. The EQUATOR network has two checklists, “The Checklist for Reporting Results of Internet E-Surveys” (CHERRIES) statement and “ The Journal of Medical Internet Research ” (JMIR) checklist, that can be utilized to construct a well-framed report. 62 , 63 Importantly, self-reporting of biases and errors avoids the carrying forward of false hypothesis as a basis of more advanced research. References should be cited using standard recommendations, and guided by the journal specifications. 64

CHOOSING A TARGET JOURNAL FOR SURVEY-BASED RESEARCH

Surveys can be published as original articles, brief reports or as a letter to the editor. Interestingly, most modern journals do not actively make mention of surveys in the instructions to the author. Thus, depending on the study design, the authors may choose the article category, cohort or case-control interview or survey-based study. It is prudent to mention the type of study in the title. Titles albeit not too long, should not exceed 10–12 words, and may feature the type of study design for clarity after a semicolon for greater citation potential.

While the choice of journal is largely based on the study subject and left to the authors discretion, it may be worthwhile exploring trends in a journal archive before proceeding with submission. 65 Although the article format is similar across most journals, specific rules relevant to the target journal may be followed for drafting the article structure before submission.

RETRACTION OF ARTICLES

Articles that are removed from the publication after being released are retracted articles. These are usually retracted when new discrepancies come to light regarding, the methodology followed, plagiarism, incorrect statistical analysis, inappropriate authorship, fake peer review, fake reporting and such. 66 A sufficient increase in such papers has been noticed. 67

We carried out a search of “surveys” on Retraction Watch on 31st August 2020 and received 81 search results published between November 2006 to June 2020, out of which 3 were repeated. Out of the 78 results, 37 (47.4%) articles were surveys, 23 (29.4%) showed as unknown types and 18 (23.2%) reported other types of research. ( Supplementary Table 1 ). Fig. 2 gives a detailed description of the causes of retraction of the surveys we found and its geographic distribution.

A good survey ought to be designed with a clear objective, the design being precise and focused with close-ended questions and all probabilities included. Use of rating scales, multiple choice questions and checkboxes and maintaining a logical question sequence engages the respondent while simplifying data entry and analysis for the investigator. Conducting pilot-testing is vital to identify and rectify deficiencies in the survey design and answer choices. The target demographic should be defined well, and invitations sent accordingly, with periodic reminders as appropriate. While reporting the survey, maintaining transparency in the methods employed and clearly stating the shortcomings and biases to prevent advocating an invalid hypothesis.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

• Conceptualization: Gaur PS, Zimba O, Agarwal V, Gupta L.
• Visualization: Gaur PS, Zimba O, Agarwal V, Gupta L.
• Writing - original draft: Gaur PS, Gupta L.

SUPPLEMENTARY MATERIAL

Reporting survey based research

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• Doing Survey Research | A Step-by-Step Guide & Examples

Doing Survey Research | A Step-by-Step Guide & Examples

Published on 6 May 2022 by Shona McCombes . Revised on 10 October 2022.

Survey research means collecting information about a group of people by asking them questions and analysing the results. To conduct an effective survey, follow these six steps:

• Determine who will participate in the survey
• Decide the type of survey (mail, online, or in-person)
• Design the survey questions and layout
• Distribute the survey
• Analyse the responses
• Write up the results

Surveys are a flexible method of data collection that can be used in many different types of research .

Table of contents

What are surveys used for, step 1: define the population and sample, step 2: decide on the type of survey, step 3: design the survey questions, step 4: distribute the survey and collect responses, step 5: analyse the survey results, step 6: write up the survey results, frequently asked questions about surveys.

Surveys are used as a method of gathering data in many different fields. They are a good choice when you want to find out about the characteristics, preferences, opinions, or beliefs of a group of people.

Common uses of survey research include:

• Social research: Investigating the experiences and characteristics of different social groups
• Market research: Finding out what customers think about products, services, and companies
• Health research: Collecting data from patients about symptoms and treatments
• Politics: Measuring public opinion about parties and policies
• Psychology: Researching personality traits, preferences, and behaviours

Surveys can be used in both cross-sectional studies , where you collect data just once, and longitudinal studies , where you survey the same sample several times over an extended period.

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Before you start conducting survey research, you should already have a clear research question that defines what you want to find out. Based on this question, you need to determine exactly who you will target to participate in the survey.

Populations

The target population is the specific group of people that you want to find out about. This group can be very broad or relatively narrow. For example:

• The population of Brazil
• University students in the UK
• Second-generation immigrants in the Netherlands
• Customers of a specific company aged 18 to 24
• British transgender women over the age of 50

Your survey should aim to produce results that can be generalised to the whole population. That means you need to carefully define exactly who you want to draw conclusions about.

It’s rarely possible to survey the entire population of your research – it would be very difficult to get a response from every person in Brazil or every university student in the UK. Instead, you will usually survey a sample from the population.

The sample size depends on how big the population is. You can use an online sample calculator to work out how many responses you need.

There are many sampling methods that allow you to generalise to broad populations. In general, though, the sample should aim to be representative of the population as a whole. The larger and more representative your sample, the more valid your conclusions.

There are two main types of survey:

• A questionnaire , where a list of questions is distributed by post, online, or in person, and respondents fill it out themselves
• An interview , where the researcher asks a set of questions by phone or in person and records the responses

Which type you choose depends on the sample size and location, as well as the focus of the research.

Questionnaires

Sending out a paper survey by post is a common method of gathering demographic information (for example, in a government census of the population).

• You can easily access a large sample.
• You have some control over who is included in the sample (e.g., residents of a specific region).
• The response rate is often low.

Online surveys are a popular choice for students doing dissertation research , due to the low cost and flexibility of this method. There are many online tools available for constructing surveys, such as SurveyMonkey and Google Forms .

• You can quickly access a large sample without constraints on time or location.
• The data is easy to process and analyse.
• The anonymity and accessibility of online surveys mean you have less control over who responds.

If your research focuses on a specific location, you can distribute a written questionnaire to be completed by respondents on the spot. For example, you could approach the customers of a shopping centre or ask all students to complete a questionnaire at the end of a class.

• You can screen respondents to make sure only people in the target population are included in the sample.
• You can collect time- and location-specific data (e.g., the opinions of a shop’s weekday customers).
• The sample size will be smaller, so this method is less suitable for collecting data on broad populations.

Oral interviews are a useful method for smaller sample sizes. They allow you to gather more in-depth information on people’s opinions and preferences. You can conduct interviews by phone or in person.

• You have personal contact with respondents, so you know exactly who will be included in the sample in advance.
• You can clarify questions and ask for follow-up information when necessary.
• The lack of anonymity may cause respondents to answer less honestly, and there is more risk of researcher bias.

Like questionnaires, interviews can be used to collect quantitative data : the researcher records each response as a category or rating and statistically analyses the results. But they are more commonly used to collect qualitative data : the interviewees’ full responses are transcribed and analysed individually to gain a richer understanding of their opinions and feelings.

Next, you need to decide which questions you will ask and how you will ask them. It’s important to consider:

• The type of questions
• The content of the questions
• The phrasing of the questions
• The ordering and layout of the survey

Open-ended vs closed-ended questions

There are two main forms of survey questions: open-ended and closed-ended. Many surveys use a combination of both.

Closed-ended questions give the respondent a predetermined set of answers to choose from. A closed-ended question can include:

• A binary answer (e.g., yes/no or agree/disagree )
• A scale (e.g., a Likert scale with five points ranging from strongly agree to strongly disagree )
• A list of options with a single answer possible (e.g., age categories)
• A list of options with multiple answers possible (e.g., leisure interests)

Closed-ended questions are best for quantitative research . They provide you with numerical data that can be statistically analysed to find patterns, trends, and correlations .

Open-ended questions are best for qualitative research. This type of question has no predetermined answers to choose from. Instead, the respondent answers in their own words.

Open questions are most common in interviews, but you can also use them in questionnaires. They are often useful as follow-up questions to ask for more detailed explanations of responses to the closed questions.

The content of the survey questions

To ensure the validity and reliability of your results, you need to carefully consider each question in the survey. All questions should be narrowly focused with enough context for the respondent to answer accurately. Avoid questions that are not directly relevant to the survey’s purpose.

When constructing closed-ended questions, ensure that the options cover all possibilities. If you include a list of options that isn’t exhaustive, you can add an ‘other’ field.

Phrasing the survey questions

In terms of language, the survey questions should be as clear and precise as possible. Tailor the questions to your target population, keeping in mind their level of knowledge of the topic.

Use language that respondents will easily understand, and avoid words with vague or ambiguous meanings. Make sure your questions are phrased neutrally, with no bias towards one answer or another.

Ordering the survey questions

The questions should be arranged in a logical order. Start with easy, non-sensitive, closed-ended questions that will encourage the respondent to continue.

If the survey covers several different topics or themes, group together related questions. You can divide a questionnaire into sections to help respondents understand what is being asked in each part.

If a question refers back to or depends on the answer to a previous question, they should be placed directly next to one another.

Before you start, create a clear plan for where, when, how, and with whom you will conduct the survey. Determine in advance how many responses you require and how you will gain access to the sample.

When you are satisfied that you have created a strong research design suitable for answering your research questions, you can conduct the survey through your method of choice – by post, online, or in person.

There are many methods of analysing the results of your survey. First you have to process the data, usually with the help of a computer program to sort all the responses. You should also cleanse the data by removing incomplete or incorrectly completed responses.

If you asked open-ended questions, you will have to code the responses by assigning labels to each response and organising them into categories or themes. You can also use more qualitative methods, such as thematic analysis , which is especially suitable for analysing interviews.

Statistical analysis is usually conducted using programs like SPSS or Stata. The same set of survey data can be subject to many analyses.

Finally, when you have collected and analysed all the necessary data, you will write it up as part of your thesis, dissertation , or research paper .

In the methodology section, you describe exactly how you conducted the survey. You should explain the types of questions you used, the sampling method, when and where the survey took place, and the response rate. You can include the full questionnaire as an appendix and refer to it in the text if relevant.

Then introduce the analysis by describing how you prepared the data and the statistical methods you used to analyse it. In the results section, you summarise the key results from your analysis.

A Likert scale is a rating scale that quantitatively assesses opinions, attitudes, or behaviours. It is made up of four or more questions that measure a single attitude or trait when response scores are combined.

To use a Likert scale in a survey , you present participants with Likert-type questions or statements, and a continuum of items, usually with five or seven possible responses, to capture their degree of agreement.

Individual Likert-type questions are generally considered ordinal data , because the items have clear rank order, but don’t have an even distribution.

Overall Likert scale scores are sometimes treated as interval data. These scores are considered to have directionality and even spacing between them.

The type of data determines what statistical tests you should use to analyse your data.

A questionnaire is a data collection tool or instrument, while a survey is an overarching research method that involves collecting and analysing data from people using questionnaires.

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Case Studies vs. Surveys

What's the difference.

Case studies and surveys are both research methods used in various fields to gather information and insights. However, they differ in their approach and purpose. Case studies involve in-depth analysis of a specific individual, group, or situation, aiming to understand the complexities and unique aspects of the subject. They provide detailed qualitative data and allow researchers to explore causal relationships. On the other hand, surveys involve collecting data from a larger sample size through standardized questionnaires or interviews. Surveys are more focused on obtaining quantitative data and generalizing findings to a larger population. While case studies offer rich and detailed information, surveys provide a broader perspective and statistical analysis. Ultimately, the choice between these methods depends on the research objectives and the nature of the research question.

Further Detail

Introduction.

When conducting research, it is essential to choose the most appropriate method to gather data and analyze information. Two commonly used research methods are case studies and surveys. Both methods have their own unique attributes and can provide valuable insights, but they differ in terms of their approach, data collection, and analysis techniques. In this article, we will explore the attributes of case studies and surveys, highlighting their strengths and limitations.

Case Studies

Case studies are an in-depth examination of a particular individual, group, or phenomenon. They involve a comprehensive analysis of a specific case, often using multiple sources of data such as interviews, observations, and documents. Case studies are particularly useful when researchers aim to understand complex social phenomena or explore rare events. They provide a detailed and holistic view of the subject under investigation.

One of the key attributes of case studies is their ability to generate rich and detailed qualitative data. By using various data collection methods, researchers can gather a wide range of information, including personal experiences, attitudes, and behaviors. This depth of data allows for a comprehensive understanding of the case, capturing nuances and complexities that may not be captured by other research methods.

Furthermore, case studies are often conducted in real-world settings, providing a high level of ecological validity. Researchers can observe and analyze the subject within its natural context, which enhances the external validity of the findings. This attribute is particularly valuable when studying complex social phenomena that are influenced by contextual factors.

However, case studies also have limitations. Due to their in-depth nature, case studies are time-consuming and resource-intensive. They require significant effort to collect and analyze data, making them less suitable for large-scale studies. Additionally, the findings of case studies may lack generalizability, as they are often focused on specific cases or contexts. Therefore, caution must be exercised when applying the results of a case study to a broader population.

Surveys, on the other hand, are a research method that involves collecting data from a large number of participants using standardized questionnaires or interviews. Surveys are widely used in social sciences and market research to gather quantitative data and identify patterns or trends within a population. They provide a snapshot of the opinions, attitudes, and behaviors of a specific group.

One of the primary attributes of surveys is their ability to collect data from a large and diverse sample. By reaching a significant number of participants, surveys allow researchers to generalize their findings to a broader population. This attribute makes surveys particularly useful when studying large-scale phenomena or when the goal is to make statistical inferences.

Moreover, surveys offer a structured and standardized approach to data collection. The use of pre-determined questions and response options ensures consistency across participants, making it easier to compare and analyze the data. Surveys also allow for efficient data collection, as they can be administered to a large number of participants simultaneously, reducing the time and resources required.

However, surveys also have limitations. They rely heavily on self-reporting, which may introduce response biases or inaccuracies. Participants may provide socially desirable responses or misunderstand the questions, leading to biased or unreliable data. Additionally, surveys often provide limited depth of information, as they focus on collecting quantitative data rather than exploring the underlying reasons or motivations behind participants' responses.

Comparing Case Studies and Surveys

While case studies and surveys differ in their approach and data collection techniques, they both have their own strengths and limitations. Case studies offer a detailed and holistic understanding of a specific case or phenomenon, capturing rich qualitative data and providing high ecological validity. However, they are time-consuming, resource-intensive, and may lack generalizability.

On the other hand, surveys allow for data collection from a large and diverse sample, enabling generalizability and statistical inferences. They offer a structured and efficient approach to data collection, but may suffer from response biases and provide limited depth of information.

Choosing between case studies and surveys depends on the research objectives, the nature of the phenomenon under investigation, and the available resources. If the goal is to explore complex social phenomena in-depth and within their natural context, a case study may be the most appropriate method. However, if the aim is to gather data from a large population and make statistical inferences, a survey would be more suitable.

It is worth noting that case studies and surveys are not mutually exclusive. In fact, they can complement each other in a mixed-methods approach. Researchers can use a case study to gain a deep understanding of a specific case and then conduct a survey to validate or generalize the findings to a larger population.

Case studies and surveys are valuable research methods that offer unique attributes and insights. Case studies provide a detailed and holistic understanding of a specific case or phenomenon, capturing rich qualitative data and enhancing external validity. Surveys, on the other hand, allow for data collection from a large and diverse sample, enabling generalizability and statistical inferences. Both methods have their own strengths and limitations, and the choice between them depends on the research objectives and available resources. By understanding the attributes of case studies and surveys, researchers can make informed decisions and conduct rigorous and impactful research.

Comparisons may contain inaccurate information about people, places, or facts. Please report any issues.

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Survey Research: Definition, Examples and Methods

Survey Research is a quantitative research method used for collecting data from a set of respondents. It has been perhaps one of the most used methodologies in the industry for several years due to the multiple benefits and advantages that it has when collecting and analyzing data.

LEARN ABOUT: Behavioral Research

In this article, you will learn everything about survey research, such as types, methods, and examples.

Survey Research Definition

Survey Research is defined as the process of conducting research using surveys that researchers send to survey respondents. The data collected from surveys is then statistically analyzed to draw meaningful research conclusions. In the 21st century, every organization’s eager to understand what their customers think about their products or services and make better business decisions. Researchers can conduct research in multiple ways, but surveys are proven to be one of the most effective and trustworthy research methods. An online survey is a method for extracting information about a significant business matter from an individual or a group of individuals. It consists of structured survey questions that motivate the participants to respond. Creditable survey research can give these businesses access to a vast information bank. Organizations in media, other companies, and even governments rely on survey research to obtain accurate data.

The traditional definition of survey research is a quantitative method for collecting information from a pool of respondents by asking multiple survey questions. This research type includes the recruitment of individuals collection, and analysis of data. It’s useful for researchers who aim to communicate new features or trends to their respondents.

LEARN ABOUT: Level of Analysis Generally, it’s the primary step towards obtaining quick information about mainstream topics and conducting more rigorous and detailed quantitative research methods like surveys/polls or qualitative research methods like focus groups/on-call interviews can follow. There are many situations where researchers can conduct research using a blend of both qualitative and quantitative strategies.

LEARN ABOUT: Survey Sampling

Survey Research Methods

Survey research methods can be derived based on two critical factors: Survey research tool and time involved in conducting research. There are three main survey research methods, divided based on the medium of conducting survey research:

• Online/ Email:   Online survey research is one of the most popular survey research methods today. The survey cost involved in online survey research is extremely minimal, and the responses gathered are highly accurate.
• Phone:  Survey research conducted over the telephone ( CATI survey ) can be useful in collecting data from a more extensive section of the target population. There are chances that the money invested in phone surveys will be higher than other mediums, and the time required will be higher.
• Face-to-face:  Researchers conduct face-to-face in-depth interviews in situations where there is a complicated problem to solve. The response rate for this method is the highest, but it can be costly.

Further, based on the time taken, survey research can be classified into two methods:

• Longitudinal survey research:  Longitudinal survey research involves conducting survey research over a continuum of time and spread across years and decades. The data collected using this survey research method from one time period to another is qualitative or quantitative. Respondent behavior, preferences, and attitudes are continuously observed over time to analyze reasons for a change in behavior or preferences. For example, suppose a researcher intends to learn about the eating habits of teenagers. In that case, he/she will follow a sample of teenagers over a considerable period to ensure that the collected information is reliable. Often, cross-sectional survey research follows a longitudinal study .
• Cross-sectional survey research:  Researchers conduct a cross-sectional survey to collect insights from a target audience at a particular time interval. This survey research method is implemented in various sectors such as retail, education, healthcare, SME businesses, etc. Cross-sectional studies can either be descriptive or analytical. It is quick and helps researchers collect information in a brief period. Researchers rely on the cross-sectional survey research method in situations where descriptive analysis of a subject is required.

Survey research also is bifurcated according to the sampling methods used to form samples for research: Probability and Non-probability sampling. Every individual in a population should be considered equally to be a part of the survey research sample. Probability sampling is a sampling method in which the researcher chooses the elements based on probability theory. The are various probability research methods, such as simple random sampling , systematic sampling, cluster sampling, stratified random sampling, etc. Non-probability sampling is a sampling method where the researcher uses his/her knowledge and experience to form samples.

LEARN ABOUT: Survey Sample Sizes

The various non-probability sampling techniques are :

• Convenience sampling
• Snowball sampling
• Consecutive sampling
• Judgemental sampling
• Quota sampling

Process of implementing survey research methods:

• Decide survey questions:  Brainstorm and put together valid survey questions that are grammatically and logically appropriate. Understanding the objective and expected outcomes of the survey helps a lot. There are many surveys where details of responses are not as important as gaining insights about what customers prefer from the provided options. In such situations, a researcher can include multiple-choice questions or closed-ended questions . Whereas, if researchers need to obtain details about specific issues, they can consist of open-ended questions in the questionnaire. Ideally, the surveys should include a smart balance of open-ended and closed-ended questions. Use survey questions like Likert Scale , Semantic Scale, Net Promoter Score question, etc., to avoid fence-sitting.

LEARN ABOUT: System Usability Scale

• Finalize a target audience:  Send out relevant surveys as per the target audience and filter out irrelevant questions as per the requirement. The survey research will be instrumental in case the target population decides on a sample. This way, results can be according to the desired market and be generalized to the entire population.

LEARN ABOUT:  Testimonial Questions

• Send out surveys via decided mediums:  Distribute the surveys to the target audience and patiently wait for the feedback and comments- this is the most crucial step of the survey research. The survey needs to be scheduled, keeping in mind the nature of the target audience and its regions. Surveys can be conducted via email, embedded in a website, shared via social media, etc., to gain maximum responses.
• Analyze survey results:  Analyze the feedback in real-time and identify patterns in the responses which might lead to a much-needed breakthrough for your organization. GAP, TURF Analysis , Conjoint analysis, Cross tabulation, and many such survey feedback analysis methods can be used to spot and shed light on respondent behavior. Researchers can use the results to implement corrective measures to improve customer/employee satisfaction.

Reasons to conduct survey research

The most crucial and integral reason for conducting market research using surveys is that you can collect answers regarding specific, essential questions. You can ask these questions in multiple survey formats as per the target audience and the intent of the survey. Before designing a study, every organization must figure out the objective of carrying this out so that the study can be structured, planned, and executed to perfection.

LEARN ABOUT: Research Process Steps

Questions that need to be on your mind while designing a survey are:

• What is the primary aim of conducting the survey?
• How do you plan to utilize the collected survey data?
• What type of decisions do you plan to take based on the points mentioned above?

There are three critical reasons why an organization must conduct survey research.

• Understand respondent behavior to get solutions to your queries:  If you’ve carefully curated a survey, the respondents will provide insights about what they like about your organization as well as suggestions for improvement. To motivate them to respond, you must be very vocal about how secure their responses will be and how you will utilize the answers. This will push them to be 100% honest about their feedback, opinions, and comments. Online surveys or mobile surveys have proved their privacy, and due to this, more and more respondents feel free to put forth their feedback through these mediums.
• Present a medium for discussion:  A survey can be the perfect platform for respondents to provide criticism or applause for an organization. Important topics like product quality or quality of customer service etc., can be put on the table for discussion. A way you can do it is by including open-ended questions where the respondents can write their thoughts. This will make it easy for you to correlate your survey to what you intend to do with your product or service.
• Strategy for never-ending improvements:  An organization can establish the target audience’s attributes from the pilot phase of survey research . Researchers can use the criticism and feedback received from this survey to improve the product/services. Once the company successfully makes the improvements, it can send out another survey to measure the change in feedback keeping the pilot phase the benchmark. By doing this activity, the organization can track what was effectively improved and what still needs improvement.

Survey Research Scales

There are four main scales for the measurement of variables:

• Nominal Scale:  A nominal scale associates numbers with variables for mere naming or labeling, and the numbers usually have no other relevance. It is the most basic of the four levels of measurement.
• Ordinal Scale:  The ordinal scale has an innate order within the variables along with labels. It establishes the rank between the variables of a scale but not the difference value between the variables.
• Interval Scale:  The interval scale is a step ahead in comparison to the other two scales. Along with establishing a rank and name of variables, the scale also makes known the difference between the two variables. The only drawback is that there is no fixed start point of the scale, i.e., the actual zero value is absent.
• Ratio Scale:  The ratio scale is the most advanced measurement scale, which has variables that are labeled in order and have a calculated difference between variables. In addition to what interval scale orders, this scale has a fixed starting point, i.e., the actual zero value is present.

Benefits of survey research

In case survey research is used for all the right purposes and is implemented properly, marketers can benefit by gaining useful, trustworthy data that they can use to better the ROI of the organization.

Other benefits of survey research are:

• Minimum investment:  Mobile surveys and online surveys have minimal finance invested per respondent. Even with the gifts and other incentives provided to the people who participate in the study, online surveys are extremely economical compared to paper-based surveys.
• Versatile sources for response collection:  You can conduct surveys via various mediums like online and mobile surveys. You can further classify them into qualitative mediums like focus groups , and interviews and quantitative mediums like customer-centric surveys. Due to the offline survey response collection option, researchers can conduct surveys in remote areas with limited internet connectivity. This can make data collection and analysis more convenient and extensive.
• Reliable for respondents:  Surveys are extremely secure as the respondent details and responses are kept safeguarded. This anonymity makes respondents answer the survey questions candidly and with absolute honesty. An organization seeking to receive explicit responses for its survey research must mention that it will be confidential.

Survey research design

Researchers implement a survey research design in cases where there is a limited cost involved and there is a need to access details easily. This method is often used by small and large organizations to understand and analyze new trends, market demands, and opinions. Collecting information through tactfully designed survey research can be much more effective and productive than a casually conducted survey.

There are five stages of survey research design:

• Decide an aim of the research:  There can be multiple reasons for a researcher to conduct a survey, but they need to decide a purpose for the research. This is the primary stage of survey research as it can mold the entire path of a survey, impacting its results.
• Filter the sample from target population:  Who to target? is an essential question that a researcher should answer and keep in mind while conducting research. The precision of the results is driven by who the members of a sample are and how useful their opinions are. The quality of respondents in a sample is essential for the results received for research and not the quantity. If a researcher seeks to understand whether a product feature will work well with their target market, he/she can conduct survey research with a group of market experts for that product or technology.
• Zero-in on a survey method:  Many qualitative and quantitative research methods can be discussed and decided. Focus groups, online interviews, surveys, polls, questionnaires, etc. can be carried out with a pre-decided sample of individuals.
• Design the questionnaire:  What will the content of the survey be? A researcher is required to answer this question to be able to design it effectively. What will the content of the cover letter be? Or what are the survey questions of this questionnaire? Understand the target market thoroughly to create a questionnaire that targets a sample to gain insights about a survey research topic.
• Send out surveys and analyze results:  Once the researcher decides on which questions to include in a study, they can send it across to the selected sample . Answers obtained from this survey can be analyzed to make product-related or marketing-related decisions.

Survey examples: 10 tips to design the perfect research survey

Picking the right survey design can be the key to gaining the information you need to make crucial decisions for all your research. It is essential to choose the right topic, choose the right question types, and pick a corresponding design. If this is your first time creating a survey, it can seem like an intimidating task. But with QuestionPro, each step of the process is made simple and easy.

Below are 10 Tips To Design The Perfect Research Survey:

• Set your SMART goals:  Before conducting any market research or creating a particular plan, set your SMART Goals . What is that you want to achieve with the survey? How will you measure it promptly, and what are the results you are expecting?
• Choose the right questions:  Designing a survey can be a tricky task. Asking the right questions may help you get the answers you are looking for and ease the task of analyzing. So, always choose those specific questions – relevant to your research.
• Begin your survey with a generalized question:  Preferably, start your survey with a general question to understand whether the respondent uses the product or not. That also provides an excellent base and intro for your survey.
• Enhance your survey:  Choose the best, most relevant, 15-20 questions. Frame each question as a different question type based on the kind of answer you would like to gather from each. Create a survey using different types of questions such as multiple-choice, rating scale, open-ended, etc. Look at more survey examples and four measurement scales every researcher should remember.
• Prepare yes/no questions:  You may also want to use yes/no questions to separate people or branch them into groups of those who “have purchased” and those who “have not yet purchased” your products or services. Once you separate them, you can ask them different questions.
• Test all electronic devices:  It becomes effortless to distribute your surveys if respondents can answer them on different electronic devices like mobiles, tablets, etc. Once you have created your survey, it’s time to TEST. You can also make any corrections if needed at this stage.
• Distribute your survey:  Once your survey is ready, it is time to share and distribute it to the right audience. You can share handouts and share them via email, social media, and other industry-related offline/online communities.
• Collect and analyze responses:  After distributing your survey, it is time to gather all responses. Make sure you store your results in a particular document or an Excel sheet with all the necessary categories mentioned so that you don’t lose your data. Remember, this is the most crucial stage. Segregate your responses based on demographics, psychographics, and behavior. This is because, as a researcher, you must know where your responses are coming from. It will help you to analyze, predict decisions, and help write the summary report.
• Prepare your summary report:  Now is the time to share your analysis. At this stage, you should mention all the responses gathered from a survey in a fixed format. Also, the reader/customer must get clarity about your goal, which you were trying to gain from the study. Questions such as – whether the product or service has been used/preferred or not. Do respondents prefer some other product to another? Any recommendations?

Having a tool that helps you carry out all the necessary steps to carry out this type of study is a vital part of any project. At QuestionPro, we have helped more than 10,000 clients around the world to carry out data collection in a simple and effective way, in addition to offering a wide range of solutions to take advantage of this data in the best possible way.

From dashboards, advanced analysis tools, automation, and dedicated functions, in QuestionPro, you will find everything you need to execute your research projects effectively. Uncover insights that matter the most!

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2.2 Approaches to Research

Learning objectives.

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

• Describe the different research methods used by psychologists
• Discuss the strengths and weaknesses of case studies, naturalistic observation, surveys, and archival research
• Compare longitudinal and cross-sectional approaches to research
• Compare and contrast correlation and causation

There are many research methods available to psychologists in their efforts to understand, describe, and explain behavior and the cognitive and biological processes that underlie it. Some methods rely on observational techniques. Other approaches involve interactions between the researcher and the individuals who are being studied—ranging from a series of simple questions to extensive, in-depth interviews—to well-controlled experiments.

Each of these research methods has unique strengths and weaknesses, and each method may only be appropriate for certain types of research questions. For example, studies that rely primarily on observation produce incredible amounts of information, but the ability to apply this information to the larger population is somewhat limited because of small sample sizes. Survey research, on the other hand, allows researchers to easily collect data from relatively large samples. While this allows for results to be generalized to the larger population more easily, the information that can be collected on any given survey is somewhat limited and subject to problems associated with any type of self-reported data. Some researchers conduct archival research by using existing records. While this can be a fairly inexpensive way to collect data that can provide insight into a number of research questions, researchers using this approach have no control on how or what kind of data was collected. All of the methods described thus far are correlational in nature. This means that researchers can speak to important relationships that might exist between two or more variables of interest. However, correlational data cannot be used to make claims about cause-and-effect relationships.

Correlational research can find a relationship between two variables, but the only way a researcher can claim that the relationship between the variables is cause and effect is to perform an experiment. In experimental research, which will be discussed later in this chapter, there is a tremendous amount of control over variables of interest. While this is a powerful approach, experiments are often conducted in artificial settings. This calls into question the validity of experimental findings with regard to how they would apply in real-world settings. In addition, many of the questions that psychologists would like to answer cannot be pursued through experimental research because of ethical concerns.

Clinical or Case Studies

In 2011, the New York Times published a feature story on Krista and Tatiana Hogan, Canadian twin girls. These particular twins are unique because Krista and Tatiana are conjoined twins, connected at the head. There is evidence that the two girls are connected in a part of the brain called the thalamus, which is a major sensory relay center. Most incoming sensory information is sent through the thalamus before reaching higher regions of the cerebral cortex for processing.

Link to Learning

Watch this CBC video about Krista's and Tatiana's lives to learn more.

The implications of this potential connection mean that it might be possible for one twin to experience the sensations of the other twin. For instance, if Krista is watching a particularly funny television program, Tatiana might smile or laugh even if she is not watching the program. This particular possibility has piqued the interest of many neuroscientists who seek to understand how the brain uses sensory information.

These twins represent an enormous resource in the study of the brain, and since their condition is very rare, it is likely that as long as their family agrees, scientists will follow these girls very closely throughout their lives to gain as much information as possible (Dominus, 2011).

Over time, it has become clear that while Krista and Tatiana share some sensory experiences and motor control, they remain two distinct individuals, which provides invaluable insight for researchers interested in the mind and the brain (Egnor, 2017).

In observational research, scientists are conducting a clinical or case study when they focus on one person or just a few individuals. Indeed, some scientists spend their entire careers studying just 10–20 individuals. Why would they do this? Obviously, when they focus their attention on a very small number of people, they can gain a precious amount of insight into those cases. The richness of information that is collected in clinical or case studies is unmatched by any other single research method. This allows the researcher to have a very deep understanding of the individuals and the particular phenomenon being studied.

If clinical or case studies provide so much information, why are they not more frequent among researchers? As it turns out, the major benefit of this particular approach is also a weakness. As mentioned earlier, this approach is often used when studying individuals who are interesting to researchers because they have a rare characteristic. Therefore, the individuals who serve as the focus of case studies are not like most other people. If scientists ultimately want to explain all behavior, focusing attention on such a special group of people can make it difficult to generalize any observations to the larger population as a whole. Generalizing refers to the ability to apply the findings of a particular research project to larger segments of society. Again, case studies provide enormous amounts of information, but since the cases are so specific, the potential to apply what’s learned to the average person may be very limited.

Naturalistic Observation

If you want to understand how behavior occurs, one of the best ways to gain information is to simply observe the behavior in its natural context. However, people might change their behavior in unexpected ways if they know they are being observed. How do researchers obtain accurate information when people tend to hide their natural behavior? As an example, imagine that your professor asks everyone in your class to raise their hand if they always wash their hands after using the restroom. Chances are that almost everyone in the classroom will raise their hand, but do you think hand washing after every trip to the restroom is really that universal?

This is very similar to the phenomenon mentioned earlier in this chapter: many individuals do not feel comfortable answering a question honestly. But if we are committed to finding out the facts about hand washing, we have other options available to us.

Suppose we send a classmate into the restroom to actually watch whether everyone washes their hands after using the restroom. Will our observer blend into the restroom environment by wearing a white lab coat, sitting with a clipboard, and staring at the sinks? We want our researcher to be inconspicuous—perhaps standing at one of the sinks pretending to put in contact lenses while secretly recording the relevant information. This type of observational study is called naturalistic observation : observing behavior in its natural setting. To better understand peer exclusion, Suzanne Fanger collaborated with colleagues at the University of Texas to observe the behavior of preschool children on a playground. How did the observers remain inconspicuous over the duration of the study? They equipped a few of the children with wireless microphones (which the children quickly forgot about) and observed while taking notes from a distance. Also, the children in that particular preschool (a “laboratory preschool”) were accustomed to having observers on the playground (Fanger, Frankel, & Hazen, 2012).

It is critical that the observer be as unobtrusive and as inconspicuous as possible: when people know they are being watched, they are less likely to behave naturally. If you have any doubt about this, ask yourself how your driving behavior might differ in two situations: In the first situation, you are driving down a deserted highway during the middle of the day; in the second situation, you are being followed by a police car down the same deserted highway ( Figure 2.7 ).

It should be pointed out that naturalistic observation is not limited to research involving humans. Indeed, some of the best-known examples of naturalistic observation involve researchers going into the field to observe various kinds of animals in their own environments. As with human studies, the researchers maintain their distance and avoid interfering with the animal subjects so as not to influence their natural behaviors. Scientists have used this technique to study social hierarchies and interactions among animals ranging from ground squirrels to gorillas. The information provided by these studies is invaluable in understanding how those animals organize socially and communicate with one another. The anthropologist Jane Goodall , for example, spent nearly five decades observing the behavior of chimpanzees in Africa ( Figure 2.8 ). As an illustration of the types of concerns that a researcher might encounter in naturalistic observation, some scientists criticized Goodall for giving the chimps names instead of referring to them by numbers—using names was thought to undermine the emotional detachment required for the objectivity of the study (McKie, 2010).

The greatest benefit of naturalistic observation is the validity , or accuracy, of information collected unobtrusively in a natural setting. Having individuals behave as they normally would in a given situation means that we have a higher degree of ecological validity, or realism, than we might achieve with other research approaches. Therefore, our ability to generalize the findings of the research to real-world situations is enhanced. If done correctly, we need not worry about people or animals modifying their behavior simply because they are being observed. Sometimes, people may assume that reality programs give us a glimpse into authentic human behavior. However, the principle of inconspicuous observation is violated as reality stars are followed by camera crews and are interviewed on camera for personal confessionals. Given that environment, we must doubt how natural and realistic their behaviors are.

The major downside of naturalistic observation is that they are often difficult to set up and control. In our restroom study, what if you stood in the restroom all day prepared to record people’s hand washing behavior and no one came in? Or, what if you have been closely observing a troop of gorillas for weeks only to find that they migrated to a new place while you were sleeping in your tent? The benefit of realistic data comes at a cost. As a researcher you have no control of when (or if) you have behavior to observe. In addition, this type of observational research often requires significant investments of time, money, and a good dose of luck.

Sometimes studies involve structured observation. In these cases, people are observed while engaging in set, specific tasks. An excellent example of structured observation comes from Strange Situation by Mary Ainsworth (you will read more about this in the chapter on lifespan development). The Strange Situation is a procedure used to evaluate attachment styles that exist between an infant and caregiver. In this scenario, caregivers bring their infants into a room filled with toys. The Strange Situation involves a number of phases, including a stranger coming into the room, the caregiver leaving the room, and the caregiver’s return to the room. The infant’s behavior is closely monitored at each phase, but it is the behavior of the infant upon being reunited with the caregiver that is most telling in terms of characterizing the infant’s attachment style with the caregiver.

Another potential problem in observational research is observer bias . Generally, people who act as observers are closely involved in the research project and may unconsciously skew their observations to fit their research goals or expectations. To protect against this type of bias, researchers should have clear criteria established for the types of behaviors recorded and how those behaviors should be classified. In addition, researchers often compare observations of the same event by multiple observers, in order to test inter-rater reliability : a measure of reliability that assesses the consistency of observations by different observers.

Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally ( Figure 2.9 ). Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.

Surveys allow researchers to gather data from larger samples than may be afforded by other research methods . A sample is a subset of individuals selected from a population , which is the overall group of individuals that the researchers are interested in. Researchers study the sample and seek to generalize their findings to the population. Generally, researchers will begin this process by calculating various measures of central tendency from the data they have collected. These measures provide an overall summary of what a typical response looks like. There are three measures of central tendency: mode, median, and mean. The mode is the most frequently occurring response, the median lies at the middle of a given data set, and the mean is the arithmetic average of all data points. Means tend to be most useful in conducting additional analyses like those described below; however, means are very sensitive to the effects of outliers, and so one must be aware of those effects when making assessments of what measures of central tendency tell us about a data set in question.

There is both strength and weakness of the survey in comparison to case studies. By using surveys, we can collect information from a larger sample of people. A larger sample is better able to reflect the actual diversity of the population, thus allowing better generalizability. Therefore, if our sample is sufficiently large and diverse, we can assume that the data we collect from the survey can be generalized to the larger population with more certainty than the information collected through a case study. However, given the greater number of people involved, we are not able to collect the same depth of information on each person that would be collected in a case study.

Another potential weakness of surveys is something we touched on earlier in this chapter: People don't always give accurate responses. They may lie, misremember, or answer questions in a way that they think makes them look good. For example, people may report drinking less alcohol than is actually the case.

Any number of research questions can be answered through the use of surveys. One real-world example is the research conducted by Jenkins, Ruppel, Kizer, Yehl, and Griffin (2012) about the backlash against the US Arab-American community following the terrorist attacks of September 11, 2001. Jenkins and colleagues wanted to determine to what extent these negative attitudes toward Arab-Americans still existed nearly a decade after the attacks occurred. In one study, 140 research participants filled out a survey with 10 questions, including questions asking directly about the participant’s overt prejudicial attitudes toward people of various ethnicities. The survey also asked indirect questions about how likely the participant would be to interact with a person of a given ethnicity in a variety of settings (such as, “How likely do you think it is that you would introduce yourself to a person of Arab-American descent?”). The results of the research suggested that participants were unwilling to report prejudicial attitudes toward any ethnic group. However, there were significant differences between their pattern of responses to questions about social interaction with Arab-Americans compared to other ethnic groups: they indicated less willingness for social interaction with Arab-Americans compared to the other ethnic groups. This suggested that the participants harbored subtle forms of prejudice against Arab-Americans, despite their assertions that this was not the case (Jenkins et al., 2012).

Archival Research

Some researchers gain access to large amounts of data without interacting with a single research participant. Instead, they use existing records to answer various research questions. This type of research approach is known as archival research . Archival research relies on looking at past records or data sets to look for interesting patterns or relationships.

For example, a researcher might access the academic records of all individuals who enrolled in college within the past ten years and calculate how long it took them to complete their degrees, as well as course loads, grades, and extracurricular involvement. Archival research could provide important information about who is most likely to complete their education, and it could help identify important risk factors for struggling students ( Figure 2.10 ).

In comparing archival research to other research methods, there are several important distinctions. For one, the researcher employing archival research never directly interacts with research participants. Therefore, the investment of time and money to collect data is considerably less with archival research. Additionally, researchers have no control over what information was originally collected. Therefore, research questions have to be tailored so they can be answered within the structure of the existing data sets. There is also no guarantee of consistency between the records from one source to another, which might make comparing and contrasting different data sets problematic.

Longitudinal and Cross-Sectional Research

Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again at age 40.

Another approach is cross-sectional research. In cross-sectional research , a researcher compares multiple segments of the population at the same time. Using the dietary habits example above, the researcher might directly compare different groups of people by age. Instead of studying a group of people for 20 years to see how their dietary habits changed from decade to decade, the researcher would study a group of 20-year-old individuals and compare them to a group of 30-year-old individuals and a group of 40-year-old individuals. While cross-sectional research requires a shorter-term investment, it is also limited by differences that exist between the different generations (or cohorts) that have nothing to do with age per se, but rather reflect the social and cultural experiences of different generations of individuals that make them different from one another.

To illustrate this concept, consider the following survey findings. In recent years there has been significant growth in the popular support of same-sex marriage. Many studies on this topic break down survey participants into different age groups. In general, younger people are more supportive of same-sex marriage than are those who are older (Jones, 2013). Does this mean that as we age we become less open to the idea of same-sex marriage, or does this mean that older individuals have different perspectives because of the social climates in which they grew up? Longitudinal research is a powerful approach because the same individuals are involved in the research project over time, which means that the researchers need to be less concerned with differences among cohorts affecting the results of their study.

Often longitudinal studies are employed when researching various diseases in an effort to understand particular risk factors. Such studies often involve tens of thousands of individuals who are followed for several decades. Given the enormous number of people involved in these studies, researchers can feel confident that their findings can be generalized to the larger population. The Cancer Prevention Study-3 (CPS-3) is one of a series of longitudinal studies sponsored by the American Cancer Society aimed at determining predictive risk factors associated with cancer. When participants enter the study, they complete a survey about their lives and family histories, providing information on factors that might cause or prevent the development of cancer. Then every few years the participants receive additional surveys to complete. In the end, hundreds of thousands of participants will be tracked over 20 years to determine which of them develop cancer and which do not.

Clearly, this type of research is important and potentially very informative. For instance, earlier longitudinal studies sponsored by the American Cancer Society provided some of the first scientific demonstrations of the now well-established links between increased rates of cancer and smoking (American Cancer Society, n.d.) ( Figure 2.11 ).

As with any research strategy, longitudinal research is not without limitations. For one, these studies require an incredible time investment by the researcher and research participants. Given that some longitudinal studies take years, if not decades, to complete, the results will not be known for a considerable period of time. In addition to the time demands, these studies also require a substantial financial investment. Many researchers are unable to commit the resources necessary to see a longitudinal project through to the end.

Research participants must also be willing to continue their participation for an extended period of time, and this can be problematic. People move, get married and take new names, get ill, and eventually die. Even without significant life changes, some people may simply choose to discontinue their participation in the project. As a result, the attrition rates, or reduction in the number of research participants due to dropouts, in longitudinal studies are quite high and increase over the course of a project. For this reason, researchers using this approach typically recruit many participants fully expecting that a substantial number will drop out before the end. As the study progresses, they continually check whether the sample still represents the larger population, and make adjustments as necessary.

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• Nasogastric tube feeding under physical restraint of children and young people with mental disorders: a comprehensive audit and case series across paediatric wards in England
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• http://orcid.org/0000-0002-2863-158X Sarah Fuller 1 , 2 ,
• http://orcid.org/0000-0002-8315-9548 Emerie Sheridan 2 ,
• http://orcid.org/0000-0003-0883-8791 Lee D Hudson 3 ,
• http://orcid.org/0000-0001-7257-6605 Dasha Nicholls 2
• 1 Child and Adolescent Mental Health , Northamptonshire Healthcare NHS Foundation Trust , Northampton , Northamptonshire , UK
• 2 Department of Brain Sciences , Imperial College London , London , UK
• 3 Population, Policy & Practice Research Programme , UCL Institute of Child Health , London , UK
• Correspondence to Sarah Fuller, Child and Adolescent Mental Health, Northamptonshire Healthcare NHS Foundation Trust, Northampton, Northamptonshire, UK; sarah.fuller{at}nhs.net

Objective To estimate the number of patients on paediatric wards in England who received nasogastric tube (NGT) feeding under physical restraint from April 2022 to March 2023, identify the demographics and clinical characteristics of these patients, and which personnel facilitated the restraint.

Design Audit and anonymous case series

Setting Paediatric wards in England.

Patients Children and young people receiving this intervention in a 1-year period.

Outcome measures An online survey was sent to all paediatric wards in England, with the option of submitting anonymous case studies.

Results 136/143 (95.1%) acute paediatric units responded. 144 young people received this intervention across 55 (38.5%) paediatric units. The predominant diagnosis was anorexia nervosa (64.5%), age range 9–18 years (M=14.2, SD=2.1). The duration of NGT feeding under restraint ranged from 1 to 425 days, (M = 60.2, SD=80.4). Numerous personnel facilitated the restraints, including mental health nurses, paediatric nurses, security staff, healthcare assistants and parents/carers.

Conclusion NGT feeding under restraint is a relatively common intervention in acute paediatric units in England. Understanding the demographics of those receiving this intervention may highlight where additional support is needed. Further research is needed to understand when this intervention transitions from a lifesaving intervention to ongoing management.

• Child Psychiatry
• Mental health
• Paediatrics
• Adolescent Health

https://doi.org/10.1136/archdischild-2024-327039

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WHAT IS ALREADY KNOWN ON THIS TOPIC

Nasogastric tube (NGT) feeding under restraint is relatively common on mental health wards, occurs more often for adolescent than adult patients, typically involves patients with anorexia nervosa and can be both lifesaving and traumatising. Individualised care planning and multidisciplinary, collaborative decision-making can mitigate negative impacts and improve patient experience.

WHAT THIS STUDY ADDS

This is the first national survey and case series of children and young people who received NGT feeding under restraint for a mental health condition in English paediatric wards. Patients receiving the intervention were more diverse than in mental health settings and we identified variation in practice nationally. Many personnel delivering the intervention had received no specific training.

HOW THIS STUDY MIGHT AFFECT RESEARCH PRACTICE OR POLICY

Understanding the demographics and clinical characteristics of those who need this intervention may highlight where additional clinical guidance is needed.

The number of children and young people (CYP) developing an eating disorder (ED) has increased over the past decade, 1 2 and consequently more CYP, particularly with restrictive EDs such as anorexia nervosa (AN), have required hospitalisation for medical instability, in line with the international guidelines. 3 4 Initial inpatient treatment involves nutritional rehabilitation; CYP are offered a structured meal plan to reintroduce nutrition in a way that avoids refeeding syndrome. 3 Ideally, meal plans should be made in collaboration with patients and parents.

If oral nutritional rehabilitation is unsuccessful and there is medical compromise, a treating team may consider passing a nasogastric tube (NGT). 5 , 6 Research suggests that supportive NGT feeding not only improves nutritional intake and promotes weight restoration but can also reduce drive for thinness and body dissatisfaction. 7 However, clinicians can be faced with the dilemma of how to facilitate lifesaving nutrition when a patient is refusing the above options. While it is potentially lifesaving, NGT feeding under physical restraint is highly restrictive, coercive and traumatic for everyone involved and requires appropriate legal authoritisation. 8 NGT feeding under physical restraint does not have a formal definition within the mental health act (MHA). For this paper, it can be considered as any act of restraint by staff to enable a single feed to be given safely via NGT. It can include any intervention from holding of hands to prevent the removal of the NGT, up to multiple staff being required to keep the patients’ head and body still to maintain the safety of the patient during the feeding process.

National data suggest that over recent years, and exacerbated by the COVID-19 pandemic, CYP presenting to paediatric wards 9 and emergency facilities 10 who needed hospitalisation were of higher acuity, needed longer admissions and were more likely to need NGT feeding. 11 Anecdotal reports suggest many paediatric wards were having to facilitate NGT feeding under physical restraint for the first time. However, national data on rates of this intervention on paediatric wards are lacking. Such data are important to allow a better understanding of the resource and training needs of paediatric units and are an essential requirement to improve care. We, therefore, conducted a national survey in England to identify number of patients on paediatric wards receiving NGT feeding under physical restraint for a mental disorder. We explored demographics and clinical characteristics of patients, duration of intervention delivery, and who facilitated the restraint.

We used an online survey open to clinicians working on paediatric units in England from 1 April 2022 to 31 March 2023 identified from a list provided by the Royal College of Paediatrics and Child Health (RCPCH). We excluded hospitals exclusively providing specialist paediatric services, for example, cancer centres and those with time-limited day service, for example, 8:00-18:00.

We invited one clinician, for example, paediatrician, paediatric nurse manager or senior clinician such as paediatric dietitians from each eligible unit to provide information for the survey. The NHS trust and paediatric unit names were collected to monitor response rate, but clinicians remained anonymous. Services who had not responded after 3 months were contacted via telephone or email to encourage participation. Additionally, respondents were invited to submit up to 10 anonymised case studies of patients who had received NGT feeding under physical restraint.

Survey distribution

The survey and case studies were hosted on Qualtrics. Links were sent via networks within the RCPCH Young Persons Special Interest Group, the British Dietetic Association’s paediatric and mental health groups, posted on the British Eating Disorders Society platform, and via CYP mental health inpatient services provider collaborative networks (Kent and Sussex, West Midlands, East of England, Northeast and Yorkshire). Using multiple clinical networks ensured the survey reached a range of participants. Duplicate responses from the same unit were excluded.

Patient and public involvement

We implemented a steering group to have oversight of the project, which consisted of expert clinicians (a consultant paediatrician, two consultant child and adolescent psychiatrists and a consultant clinical psychologist), three parents whose children had received this intervention on a paediatric ward and a person with lived experience. We held biannual meetings to guide project development, including the research aims, audit questions, case study requirements and interpretation of results.

Data reporting

Data are reported using raw numbers, percentages and averages were appropriate. For normally distributed data, means and SD were used for averages, where not median and IQRs. From surveys we present 136 responses, from case studies we present 90 patients.

We identified 143 eligible hospitals and received survey responses from 136 (95.1% response rate). We removed 20 duplicate responses and 2 responses from paediatric wards outside England.

A total of 90 case studies were reported from 50 paediatric wards. We removed 16 incomplete case studies.

Prevalence of NGT feeding under physical restraint during the reporting period

Of 55 of the 136 paediatric wards (38.5%) reported having delivered NGT feeding under restraint for at least one CYP during the reporting period. A total of 144 CYP were reported to have received this intervention during the time surveyed. The number of patients requiring this intervention per paediatric ward ranged from 1 to 13 (Median=2, IQR = 3).

Presenting problem

The most reported primary diagnosis in both the survey and case series was AN, accounting for 93 (64.5%) of reported patients in the survey and 57 (63.3%) of case studies. The second most common reported reason was food refusal in the absence of feeding or ED psychopathology, including obsessive compulsive disorder (OCD: 28 (19.4%)) and psychosis (11 (12.2%)) ( table 1 ).

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Primary diagnosis/presentation of patients in the audit and case series

Personnel providing restraint

Of 33 (24.3%) paediatric units who reported delivering this intervention used mental health agency staff nurses, 29 (21.3%) used paediatric nurses, 22 (16.2%) used security staff, 16 (11.8%) used healthcare assistants, 11 (8.1%) used mental health nurses employed by the ward, 9 (6.6%) used nursing assistants, 4 (2.9%) used parents or carers and 8 (5.9%) used other staff members (eg, mental health nurses employed by the mental health trust).

Case series

The age of patients reported in the case studies ranged from 9 to 18 years old, (M = 14.2, SD=2.1) (see figure 1 ). A total of 81 (90.0%) were white, 4 (4.5%) were mixed ethnicity, 3 (3.3%) were Asian, 1 (1.1%) was ‘other ethnicities not specified’ and 1 (1.1%) had unknown ethnicity. Gender was predominantly cis-female 69, (76.7%), 5 (5.6%) were cis-male and 16 (17.7%) identified as a different gender from that assigned at birth (12 (13.3%) identifying as transgender women and 4 (4.4%) as non-binary).

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Age distribution of patients in the submitted case studies (n = 90).

For 39 (43.3%) CYP, this was the first paediatric admission; 51 (56.7%) had a previous paediatric admission. A total of 18 (20.0%) of CYP had no secondary diagnosis, 26 (28.9%) had one secondary diagnosis and 46 (51.1%) had two or more secondary diagnoses. These included autism-spectrum disorder (39, 43.3%), depression (30, 33.3%), anxiety (30, 33.3%) and emotionally unstable personality disorder (15, 16.7%).

Paediatric Early Warning Scores (PEWS) were provided in 37.8% of cases; all scored 4 or below. In some cases, comments such as ‘tachycardia’ or ‘life at risk’ were provided.

Intervention duration

The duration of NGT feeding under physical restraint ranged from 1 to 425 days, (M = 60.2, SD=80.4) and the mode was 21. The number of restraints per day ranged from 1 to 5, (M=2.34, SD=1.09) and a mode of 3.

Legal status

Most patients received this intervention under a legal framework. Of 79 (84.5%) were detained under the MHA, 3 (3.3%) were treated under the children’s act, 1 (1.1%) was treated under a court order. A single lifesaving feed was given to one patient (1.1%) who did not need further treatment. Nine patients (10%) received this intervention without a legal framework under parental consent.

Patient outcome

Following the paediatric in-patient admission, 51 patients (56.7%) were transferred to inpatient CYP MHS, 18 (20.0%) were discharged home with community CYP MHS care, 15 (16.7%) were admitted elsewhere (eg, adult ED unit), and outcome for two patients (2.2%) was unknown. Four patients (4.4%) remained on the paediatric ward for further treatment.

To our knowledge, this is the first national survey and case series of CYP receiving NGT feeding under restraint in English paediatric wards with the only similar previous research undertaken in mental health inpatient units in England. 8 12 13 We found that around a third of paediatric units had provided NGT under restraint in the previous year. The most common primary diagnosis in the paediatric setting was AN, which is consistent with the diagnostic profile of CYP receiving the intervention in CYP specialist mental health inpatient care (Specialist Eating Disorder Unit (SEDU): 75.9% (n=236)) and in CYP non-SEDU settings (72% (n=126)). 12

The mean age of CYP requiring the intervention was 14.2 years, which is consistent with the peak age of onset for restrictive ED, however age distribution may also be affected by admission policies as many paediatric wards in England only admit CYP under 16. 14 Previous research in mental health settings suggests that NGT feeding under restraint is implemented more frequently in CYP than adults. 12 This may reflect the greater likelihood of medical instability in CYP, due to lower body fat reserves, or a lower threshold for restrictive interventions in this age group. As this is the first survey of its kind, we cannot be sure whether NGT feeding under restraint in paediatrics is a practice that is increasing or decreasing. National monitoring is needed to determine temporal trends.

Within our sample, the predominant gender was cis-female (76.7%) and cis-male (5.6%), reflecting the typical gender split for AN. However, a number identified differently to their gender assigned at birth (n=12, 13.3%), identifying as either transgender or non-binary (n=4, 4.4%). This finding mirrored the findings in mental health settings 12 and may reflect clinician bias in case reporting. 15 . However, it could reflect increased mental health risk in CYP of non-binary gender, emphasising the importance of providing gender-affirming care, 16 17 and understanding how and why gender dysphoria can contribute to someone developing an ED.

Duration of NGT feeding under physical restraint ranged from 1 to 425 days (M=60.2, SD=80.4) and a mode of 21 days. Typically, medical stabilisation and refeeding in the context of malnutrition takes 7–10 days, 12 suggesting that the intervention is being used beyond the point of achieving medical stability. The MHA in England gives clear guidance regarding restrictive interventions, stating that they should be used for the shortest period and that they should be used when the action is proportional to the risk to life. Whether NGT feeding past the point of medical stabilisation to protect against weight loss or physical health decompensation is justified in terms of proportionality to the risks of physical injury and trauma is an important ethical and legal question. 8 Furthermore, nine patients (10%) received this intervention without any legal framework. There is guidance for paediatricians regarding the legal frameworks this intervention requires. 18

Details of the patient’s clinical risk 3 were not assessed as this can change rapidly and requires many data items. Where PEWS scores were reported, these were generally in the lower risk categories. The sensitivity and specificity of PEWS in ED have not been established.

The number of restraints per day ranged from 1 to 5 (M = 2.34, SD=1.09). Current guidance on how to adapt dietetic practice when NGT feeding under physical restraint advises reducing the number of feeds to 1–2 per day, in line with the ‘least restrictive practice’ principle of the MHA. 18 19 This has training implications.

We found that a range of personnel facilitated the physical restraints, most commonly agency nurses, who are often unknown to the trust/service. While decisions about who should be involved in the restraint remain operational within each hospital trust, the MHA stipulates that restraint must be carried out by appropriately trained staff. Four wards (2.9%) reported using parents or carers to facilitate the restraints for NGT feeding and they are unlikely to meet this legal requirement. Iatrogenic harm from parents facilitating this intervention has not been studied.

A total of 22 of the paediatric units reported using of security staff to facilitate restraints for NGT feeding. This may be the only staff group in an acute hospital that are trained in the use of restraint. However, this training may not be specific to the needs of this clinical intervention. A potential solution is to provide all staff likely to be involved in restraints with bespoke training appropriate for the clinical risks involved in NGT feeding.

Our case series suggested that most patients were transferred to specialist CYP or adult inpatient mental health bed (73.4% in total). However, 18 patients did not require inpatient transfer and were discharged to community care. This finding suggests that with the right support, the need for NGT feeding under restraint may not automatically be an indication for inpatient mental health hospitalisation. Given the lack of evidence for the cost-effectiveness of inpatient care for ED, 20 alternatives to inpatient admission are that are integrated with paediatric settings reduce readmission, length of stay and adverse outcomes are needed. 21

Strengths and limitations

This study has important strengths. The response rate was high (95.1%) and, therefore, representative of the population studied and will accurately reflect national data. Likewise, the number of case studies submitted describes a substantial clinical cohort.

There are a few limitations, however. The survey and case series relied on clinician recall and, therefore, there may be some clinician bias. 15 CYP admitted to adult medical wards would not be included in the prevalence figures. As our data are cross-sectional and there is no previous representative comparison, we cannot say whether NGT feeding under restraint in general paediatric settings has changed over time.

Potential implications and future directions

We have described a realistic picture of patients fed by NGT under physical restraint in paediatric wards at a national level, demonstrating frequency and a clinical profile of those receiving the intervention. This is an important and significant issue for many acute paediatric units and highlights training and resource needs. We have also identified potential areas to target for improvement to support these patients—in particular, tackling prolonged feeding practices, who does the restraint, and alternative models of care. While our data describe overall patterns of admissions, understanding and contextualising our findings, in particular, how patient and system factors influence clinical decision-making is now needed. Focusing on why some patients received NGT feeding under restraint only briefly and others for months would be of interest. Better understanding of the legal and ethical status of NGT feeding under restraint beyond the point of medical stabilisation would also be of interest.

Conclusions

In conclusion, this is the first national survey combined with a case series of NGT feeding under physical restraint in general paediatric settings. We found this to be an important and common issue. Further granular research is now needed to understand how care might be improved and developed.

Ethics statements

Patient consent for publication.

Not applicable.

Ethics approval

Northamptonshire Healthcare NHS Foundation Trust Research and Development Department approved the study as a clinical audit and exempt from ethics approval.

Acknowledgments

The research steering group consisted of the authors and Dr Daniel Shears, Dr Jacinta Tan, Mathew Wilson, Sophie Davies, Nicola Green, Annie Baimbridge, Mark Turner. DN is supported by the National Institute for Health Research (NIHR) Applied Research Collaboration Northwest London and NIHR Imperial Biomedical Research Collaboration. The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care.

• van Eeden AE ,
• van Hoeken D ,
• NHS Digital
• College of Psychiatrists
• Academy for Eating Disorders
• Fuller SJ ,
• Thomson S ,
• Chapman S ,
• Cave E , et al
• Pruccoli J ,
• Romagnoli G , et al
• Sturza J , et al
• Milliren CE ,
• Richmond TK ,
• Schlapfer L ,
• Gettis MA ,
• Dutreuil V , et al
• Tan J, SJ ,
• DeCosta H ,
• Goddings A-L
• Taube A, LT ,
• Tylleskar T
• Telingator CJ
• Geilhufe B ,
• Silverstein S , et al
• Philpot U , Working Group
• Philpot U, P ,
• Hudson LD , et al
• Gowers SG ,
• Roberts C , et al
• Amet M , et al

X @ChattyDietitian, @DashaNicholls

Contributors SF is the clinical lead dietitian for CAMHS in Northamptonshire Healthcare NHS Foundation Trust and a Research Dietitian at Imperial College London. ES is a research assistant at Imperial College London. SF and ES conducted the survey, data analysis and drafted the manuscript. LH is part of the project steering group and reviewed the final manuscript. DN conceived the research, contributed to the analysis and reviewed the final manuscript. DN is the guarantor for the research and publication.

Funding This research was funded by the Humber and North Yorkshire Specialist Mental Health Learning Disability and Autism Provider Collaborative. The views expressed are those of the authors and not necessarily of the Humber and North Yorkshire Specialist Mental Health Learning Disability and Autism Provider Collaborative.

Competing interests None declared.

Provenance and peer review Not commissioned; externally peer-reviewed.

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Among hybrid workers who are not self-employed, most (63%) say their employer requires them to work in person a certain number of days per week or month. About six-in-ten hybrid workers (59%) say they work from home three or more days in a typical week, while 41% say they do so two days or fewer.

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Many hybrid workers would prefer to spend more time working from home than they currently do. About a third (34%) of those who are currently working from home most of the time say, if they had the choice, they’d like to work from home all the time. And among those who are working from home some of the time, half say they’d like to do so all (18%) or most (32%) of the time.

Pew Research Center conducted this analysis to study how the COVID-19 pandemic has affected the workplace and specifically how workers with jobs that can be done from home have adapted their work schedules. To do this, we surveyed 5,775 U.S. adults who are working part time or full time and who have only one job or who have more than one job but consider one of them to be their primary job. All the workers who took part are members of the Center’s American Trends Panel (ATP), an online survey panel that is recruited through national, random sampling of residential addresses.

Address-based sampling ensures that nearly all U.S. adults have a chance of selection. The survey is weighted to be representative of the U.S. adult population by gender, race, ethnicity, partisan affiliation, education and other categories. Read more about the ATP’s methodology .

Here are the questions used for this analysis, along with responses, and the survey’s methodology .

The majority of U.S. workers overall (61%) do not have jobs that can be done from home. Workers with lower incomes and those without a four-year college degree are more likely to fall into this category. Among those who do have teleworkable jobs, Hispanic adults and those without a college degree are among the most likely to say they rarely or never work from home.

When looking at all employed adults ages 18 and older in the United States, Pew Research Center estimates that about 14% – or roughly 22 million people – are currently working from home all the time.

The advantages and disadvantages of working from home

Workers who are not self-employed and who are teleworking at least some of the time see one clear advantage – and relatively few downsides – to working from home. By far the biggest perceived upside to working from home is the balance it provides: 71% of those who work from home all, most or some of the time say doing so helps them balance their work and personal lives. That includes 52% who say it helps them a lot with this.

About one-in-ten (12%) of those who are at least occasionally working from home say it hurts their ability to strike the right work-life balance, and 17% say it neither helps nor hurts. There is no significant gender difference in these views. However, parents with children younger than 18 are somewhat more likely than workers without children in that age range to say working from home is helpful in this regard (76% vs. 69%).

A majority of those who are working from home at least some of the time (56%) say this arrangement helps them get their work done and meet deadlines. Only 7% say working from home hurts their ability to do these things, and 37% say it neither helps nor hurts.

There are other aspects of work – some of them related to career advancement – where the impact of working from home seems minimal:

• When asked how working from home affects whether they are given important assignments, 77% of those who are at least sometimes working from home say it neither helps nor hurts, while 14% say it helps and 9% say it hurts.
• When it comes to their chances of getting ahead at work, 63% of teleworkers say working from home neither helps or hurts, while 18% say it helps and 19% say it hurts.
• A narrow majority of teleworkers (54%) say working from home neither helps nor hurts with opportunities to be mentored at work. Among those who do see an impact, it’s perceived to be more negative than positive: 36% say working from home hurts opportunities to be mentored and 10% say it helps.

One aspect of work that many remote workers say working from home makes more challenging is connecting with co-workers: 53% of those who work from home at least some of the time say working from home hurts their ability to feel connected with co-workers, while 37% say it neither helps nor hurts. Only 10% say it helps them feel connected.

In spite of this, those who work from home all the time or occasionally are no less satisfied with their relationship with co-workers than those who never work from home. Roughly two-thirds of workers – whether they are working exclusively from home, follow a hybrid schedule or don’t work from home at all – say they are extremely or very satisfied with these relationships. In addition, among those with teleworkable jobs, employed adults who work from home all the time are about as likely as hybrid workers to say they have at least one close friend at work.

Feeling connected with co-workers is one area where many workers who rarely or never work from home see an advantage in their setup. About four-in-ten of these workers (41%) say the fact that they rarely or never work from home helps in how connected they feel to their co-workers. A similar share (42%) say it neither helps nor hurts, and 17% say it hurts.

At the same time, those who rarely or never work from home are less likely than teleworkers to say their current arrangement helps them achieve work-life balance. A third of these workers say the fact that they rarely or never work from home hurts their ability to balance their work and personal lives, while 40% say it neither helps nor hurts and 27% say it helps.

When it comes to other aspects of work, many of those who rarely or never work from home say their arrangement is neither helpful nor hurtful. This is true when it comes to opportunities to be mentored (53% say this), their ability to get work done and meet deadlines (57%), their chances of getting ahead in their job (68%) and whether they are given important assignments (74%).

Most adults with teleworkable jobs who work from home at least some of the time (71%) say their manager or supervisor trusts them a great deal to get their work done when they’re doing so. Those who work from home all the time are the most likely to feel trusted: 79% of these workers say their manager trusts them a great deal, compared with 64% of hybrid workers.

Hybrid workers feel about as trusted when they’re not working from home: 68% say their manager or supervisor trusts them a great deal to get their work done when they’re not teleworking.

Note: Here are the questions used for this analysis, along with responses, and the survey’s methodology .

• Business & Workplace
• Coronavirus (COVID-19)

A look at small businesses in the U.S.

Majorities of adults see decline of union membership as bad for the u.s. and working people, a look at black-owned businesses in the u.s., from businesses and banks to colleges and churches: americans’ views of u.s. institutions, 2023 saw some of the biggest, hardest-fought labor disputes in recent decades, most popular.

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6 in 10 U.S. Catholics are in favor of abortion rights, Pew Research report finds

Jason DeRose

Pope Francis remains popular among U.S. Catholics, with 75% having favorable views of him, according to a Pew Research report. But many self-identified Catholics disagree with various teachings of their church. Andrew Medichini/AP hide caption

Pope Francis remains popular among U.S. Catholics, with 75% having favorable views of him, according to a Pew Research report. But many self-identified Catholics disagree with various teachings of their church.

Catholics in the U.S., one of the country's largest single Christian groups, hold far more diverse views on abortion rights than the official teaching of their church.

While the Catholic Church itself holds that abortion is wrong and should not be legal, 6 in 10 U.S. adult Catholics say abortion should be legal in all or most cases, according to a newly released profile of Catholicism by Pew Research .

Catholic opinion about abortion rights, according to the report, tends to align with political leanings: Fewer Catholic Republicans favor legal abortion than Catholic Democrats. And Pew says Hispanic Catholics, who make up one-third of the U.S. church, are slightly more in favor of legal abortion than white Catholics.

Despite church prohibitions, Catholics still choose IVF to have children

Pew found that 20% of the U.S. population identifies as Catholic, but only about 3 in 10 say they attend mass regularly. Opinions about abortion rights appear to be related to how often someone worships — just 34% of Catholics who attend mass weekly say abortion should be legal in all or most cases, whereas that number jumps to 68% among those who attend mass monthly or less.

Most U.S. Catholics are white (57%), but that number has dropped by 8 percentage points since 2007, according the new report. About 33% identify as Hispanic, 4% Asian, 2% Black, and 3% describe themselves as another race.

Pew Research also found that as of February, Pope Francis remains highly popular, with 75% of U.S. Catholics rating him favorably. However, there is a partisan divide, with Catholic Democrats more strongly supporting him.

About 4 in 10 U.S. Catholics view Francis as a major agent of change, with 3 in 10 saying he is a minor agent of change.

Catholic Church works to explain what same-sex blessings are and are not

Pew reports that many U.S. Catholics would welcome more change. Some 83% say they want the church to allow the use of contraception, 69% say priests should be allowed to get married, 64% say women should be allowed to become priests, and 54% say the Catholic Church should recognize same-sex marriage.

In December 2023, the Vatican issued guidance to priests that they may bless people in same-sex relationships. But the church insists those blessings not be construed in any way to be a form of marriage or even take place as part of a worship service.

• Pope Francis
• Abortion rights
• Catholic church
• Pew Research