• Daily Crossword
  • Word Puzzle
  • Word Finder
  • Word of the Day
  • Synonym of the Day
  • Word of the Year
  • Language stories
  • All featured
  • Gender and sexuality
  • All pop culture
  • Grammar Coach ™
  • Writing hub
  • Grammar essentials
  • Commonly confused
  • All writing tips
  • Pop culture
  • Writing tips

Advertisement

  • a study of an individual unit, as a person, family, or social group, usually emphasizing developmental issues and relationships with the environment, especially in order to compare a larger group to the individual unit.
  • case history .
  • the act or an instance of analysing one or more particular cases or case histories with a view to making generalizations

Discover More

Word history and origins.

Origin of case study 1

Example Sentences

In a case study from Metric Theory, Target Impression Share bidding, the total cost per click increased with both mobile and desktop devices.

It would also become the subject of a fair number of business school case studies.

Not just blog posts, you can also share other resources like case studies, podcast episodes, and webinars via Instagram Stories.

They become the architecture for a case study of Flint, expressed in a more personal and poetic way than a straightforward investigation could.

The Creek Fire was a case study in the challenge facing today’s fire analysts, who are trying to predict the movements of fires that are far more severe than those seen just a decade ago.

A case study would be your Twilight director Catherine Hardwicke.

A good case study for the minority superhero problem is Luke Cage.

He was asked to review a case study out of Lebanon that had cited his work.

Instead, now we have a political science case-study proving how political fortunes can shift and change at warp speed.

One interesting case study is Sir Arthur Evans, the original excavator and “restorer” of the Minoan palace of Knossos on Crete.

As this is a case study, it should be said that my first mistake was in discrediting my early religious experience.

The author of a recent case study of democracy in a frontier county commented on the need for this kind of investigation.

How could a case study of Virginia during this period illustrate these developments?

Related Words

  • medical history

Go to the homepage

Definition of 'case study'

Video: pronunciation of case study.

Youtube video

case study in British English

Case study in american english, examples of 'case study' in a sentence case study, trends of case study.

View usage for: All Years Last 10 years Last 50 years Last 100 years Last 300 years

In other languages case study

  • American English : case study / ˈkeɪs ˌstʌdi /
  • Brazilian Portuguese : estudo de caso
  • Chinese : 个案研究
  • European Spanish : estudio
  • French : étude de cas
  • German : Fallstudie
  • Italian : studio di caso
  • Japanese : 事例研究
  • Korean : 사례 연구
  • European Portuguese : estudo de caso
  • Latin American Spanish : estudio

Browse alphabetically case study

  • case series
  • case stated
  • case system
  • case-by-case
  • case-by-case basis
  • All ENGLISH words that begin with 'C'

Related terms of case study

  • case-study method

Quick word challenge

Quiz Review

Score: 0 / 5

Image

Wordle Helper

Tile

Scrabble Tools

Image

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, automatically generate references for free.

  • Knowledge Base
  • Methodology
  • Case Study | Definition, Examples & Methods

Case Study | Definition, Examples & Methods

Published on 5 May 2022 by Shona McCombes . Revised on 30 January 2023.

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

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

Table of contents

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

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

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

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

Prevent plagiarism, run a free check.

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

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

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

If you find yourself aiming to simultaneously investigate and solve an issue, consider conducting action research . As its name suggests, action research conducts research and takes action at the same time, and is highly iterative and flexible. 

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

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

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

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

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

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

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

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

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

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

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the ‘Cite this Scribbr article’ button to automatically add the citation to our free Reference Generator.

McCombes, S. (2023, January 30). Case Study | Definition, Examples & Methods. Scribbr. Retrieved 22 April 2024, from https://www.scribbr.co.uk/research-methods/case-studies/

Is this article helpful?

Shona McCombes

Shona McCombes

Other students also liked, correlational research | guide, design & examples, a quick guide to experimental design | 5 steps & examples, descriptive research design | definition, methods & examples.

  • Privacy Policy

Research Method

Home » Case Study – Methods, Examples and Guide

Case Study – Methods, Examples and Guide

Table of Contents

Case Study Research

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

' src=

Muhammad Hassan

Researcher, Academic Writer, Web developer

You may also like

Questionnaire

Questionnaire – Definition, Types, and Examples

Observational Research

Observational Research – Methods and Guide

Quantitative Research

Quantitative Research – Methods, Types and...

Qualitative Research Methods

Qualitative Research Methods

Explanatory Research

Explanatory Research – Types, Methods, Guide

Survey Research

Survey Research – Types, Methods, Examples

  • Bipolar Disorder
  • Therapy Center
  • When To See a Therapist
  • Types of Therapy
  • Best Online Therapy
  • Best Couples Therapy
  • Best Family Therapy
  • Managing Stress
  • Sleep and Dreaming
  • Understanding Emotions
  • Self-Improvement
  • Healthy Relationships
  • Student Resources
  • Personality Types
  • Guided Meditations
  • Verywell Mind Insights
  • 2023 Verywell Mind 25
  • Mental Health in the Classroom
  • Editorial Process
  • Meet Our Review Board
  • Crisis Support

What Is a Case Study?

Weighing the pros and cons of this method of research

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

the word case study meaning

Cara Lustik is a fact-checker and copywriter.

the word case study meaning

Verywell / Colleen Tighe

  • Pros and Cons

What Types of Case Studies Are Out There?

Where do you find data for a case study, how do i write a psychology case study.

A case study is an in-depth study of one person, group, or event. In a case study, nearly every aspect of the subject's life and history is analyzed to seek patterns and causes of behavior. Case studies can be used in many different fields, including psychology, medicine, education, anthropology, political science, and social work.

The point of a case study is to learn as much as possible about an individual or group so that the information can be generalized to many others. Unfortunately, case studies tend to be highly subjective, and it is sometimes difficult to generalize results to a larger population.

While case studies focus on a single individual or group, they follow a format similar to other types of psychology writing. If you are writing a case study, we got you—here are some rules of APA format to reference.  

At a Glance

A case study, or an in-depth study of a person, group, or event, can be a useful research tool when used wisely. In many cases, case studies are best used in situations where it would be difficult or impossible for you to conduct an experiment. They are helpful for looking at unique situations and allow researchers to gather a lot of˜ information about a specific individual or group of people. However, it's important to be cautious of any bias we draw from them as they are highly subjective.

What Are the Benefits and Limitations of Case Studies?

A case study can have its strengths and weaknesses. Researchers must consider these pros and cons before deciding if this type of study is appropriate for their needs.

One of the greatest advantages of a case study is that it allows researchers to investigate things that are often difficult or impossible to replicate in a lab. Some other benefits of a case study:

  • Allows researchers to capture information on the 'how,' 'what,' and 'why,' of something that's implemented
  • Gives researchers the chance to collect information on why one strategy might be chosen over another
  • Permits researchers to develop hypotheses that can be explored in experimental research

On the other hand, a case study can have some drawbacks:

  • It cannot necessarily be generalized to the larger population
  • Cannot demonstrate cause and effect
  • It may not be scientifically rigorous
  • It can lead to bias

Researchers may choose to perform a case study if they want to explore a unique or recently discovered phenomenon. Through their insights, researchers develop additional ideas and study questions that might be explored in future studies.

It's important to remember that the insights from case studies cannot be used to determine cause-and-effect relationships between variables. However, case studies may be used to develop hypotheses that can then be addressed in experimental research.

Case Study Examples

There have been a number of notable case studies in the history of psychology. Much of  Freud's work and theories were developed through individual case studies. Some great examples of case studies in psychology include:

  • Anna O : Anna O. was a pseudonym of a woman named Bertha Pappenheim, a patient of a physician named Josef Breuer. While she was never a patient of Freud's, Freud and Breuer discussed her case extensively. The woman was experiencing symptoms of a condition that was then known as hysteria and found that talking about her problems helped relieve her symptoms. Her case played an important part in the development of talk therapy as an approach to mental health treatment.
  • Phineas Gage : Phineas Gage was a railroad employee who experienced a terrible accident in which an explosion sent a metal rod through his skull, damaging important portions of his brain. Gage recovered from his accident but was left with serious changes in both personality and behavior.
  • Genie : Genie was a young girl subjected to horrific abuse and isolation. The case study of Genie allowed researchers to study whether language learning was possible, even after missing critical periods for language development. Her case also served as an example of how scientific research may interfere with treatment and lead to further abuse of vulnerable individuals.

Such cases demonstrate how case research can be used to study things that researchers could not replicate in experimental settings. In Genie's case, her horrific abuse denied her the opportunity to learn a language at critical points in her development.

This is clearly not something researchers could ethically replicate, but conducting a case study on Genie allowed researchers to study phenomena that are otherwise impossible to reproduce.

There are a few different types of case studies that psychologists and other researchers might use:

  • Collective case studies : These involve studying a group of individuals. Researchers might study a group of people in a certain setting or look at an entire community. For example, psychologists might explore how access to resources in a community has affected the collective mental well-being of those who live there.
  • Descriptive case studies : These involve starting with a descriptive theory. The subjects are then observed, and the information gathered is compared to the pre-existing theory.
  • Explanatory case studies : These   are often used to do causal investigations. In other words, researchers are interested in looking at factors that may have caused certain things to occur.
  • Exploratory case studies : These are sometimes used as a prelude to further, more in-depth research. This allows researchers to gather more information before developing their research questions and hypotheses .
  • Instrumental case studies : These occur when the individual or group allows researchers to understand more than what is initially obvious to observers.
  • Intrinsic case studies : This type of case study is when the researcher has a personal interest in the case. Jean Piaget's observations of his own children are good examples of how an intrinsic case study can contribute to the development of a psychological theory.

The three main case study types often used are intrinsic, instrumental, and collective. Intrinsic case studies are useful for learning about unique cases. Instrumental case studies help look at an individual to learn more about a broader issue. A collective case study can be useful for looking at several cases simultaneously.

The type of case study that psychology researchers use depends on the unique characteristics of the situation and the case itself.

There are a number of different sources and methods that researchers can use to gather information about an individual or group. Six major sources that have been identified by researchers are:

  • Archival records : Census records, survey records, and name lists are examples of archival records.
  • Direct observation : This strategy involves observing the subject, often in a natural setting . While an individual observer is sometimes used, it is more common to utilize a group of observers.
  • Documents : Letters, newspaper articles, administrative records, etc., are the types of documents often used as sources.
  • Interviews : Interviews are one of the most important methods for gathering information in case studies. An interview can involve structured survey questions or more open-ended questions.
  • Participant observation : When the researcher serves as a participant in events and observes the actions and outcomes, it is called participant observation.
  • Physical artifacts : Tools, objects, instruments, and other artifacts are often observed during a direct observation of the subject.

If you have been directed to write a case study for a psychology course, be sure to check with your instructor for any specific guidelines you need to follow. If you are writing your case study for a professional publication, check with the publisher for their specific guidelines for submitting a case study.

Here is a general outline of what should be included in a case study.

Section 1: A Case History

This section will have the following structure and content:

Background information : The first section of your paper will present your client's background. Include factors such as age, gender, work, health status, family mental health history, family and social relationships, drug and alcohol history, life difficulties, goals, and coping skills and weaknesses.

Description of the presenting problem : In the next section of your case study, you will describe the problem or symptoms that the client presented with.

Describe any physical, emotional, or sensory symptoms reported by the client. Thoughts, feelings, and perceptions related to the symptoms should also be noted. Any screening or diagnostic assessments that are used should also be described in detail and all scores reported.

Your diagnosis : Provide your diagnosis and give the appropriate Diagnostic and Statistical Manual code. Explain how you reached your diagnosis, how the client's symptoms fit the diagnostic criteria for the disorder(s), or any possible difficulties in reaching a diagnosis.

Section 2: Treatment Plan

This portion of the paper will address the chosen treatment for the condition. This might also include the theoretical basis for the chosen treatment or any other evidence that might exist to support why this approach was chosen.

  • Cognitive behavioral approach : Explain how a cognitive behavioral therapist would approach treatment. Offer background information on cognitive behavioral therapy and describe the treatment sessions, client response, and outcome of this type of treatment. Make note of any difficulties or successes encountered by your client during treatment.
  • Humanistic approach : Describe a humanistic approach that could be used to treat your client, such as client-centered therapy . Provide information on the type of treatment you chose, the client's reaction to the treatment, and the end result of this approach. Explain why the treatment was successful or unsuccessful.
  • Psychoanalytic approach : Describe how a psychoanalytic therapist would view the client's problem. Provide some background on the psychoanalytic approach and cite relevant references. Explain how psychoanalytic therapy would be used to treat the client, how the client would respond to therapy, and the effectiveness of this treatment approach.
  • Pharmacological approach : If treatment primarily involves the use of medications, explain which medications were used and why. Provide background on the effectiveness of these medications and how monotherapy may compare with an approach that combines medications with therapy or other treatments.

This section of a case study should also include information about the treatment goals, process, and outcomes.

When you are writing a case study, you should also include a section where you discuss the case study itself, including the strengths and limitiations of the study. You should note how the findings of your case study might support previous research. 

In your discussion section, you should also describe some of the implications of your case study. What ideas or findings might require further exploration? How might researchers go about exploring some of these questions in additional studies?

Need More Tips?

Here are a few additional pointers to keep in mind when formatting your case study:

  • Never refer to the subject of your case study as "the client." Instead, use their name or a pseudonym.
  • Read examples of case studies to gain an idea about the style and format.
  • Remember to use APA format when citing references .

Crowe S, Cresswell K, Robertson A, Huby G, Avery A, Sheikh A. The case study approach .  BMC Med Res Methodol . 2011;11:100.

Crowe S, Cresswell K, Robertson A, Huby G, Avery A, Sheikh A. The case study approach . BMC Med Res Methodol . 2011 Jun 27;11:100. doi:10.1186/1471-2288-11-100

Gagnon, Yves-Chantal.  The Case Study as Research Method: A Practical Handbook . Canada, Chicago Review Press Incorporated DBA Independent Pub Group, 2010.

Yin, Robert K. Case Study Research and Applications: Design and Methods . United States, SAGE Publications, 2017.

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Organizing Your Social Sciences Research Assignments

  • Annotated Bibliography
  • Analyzing a Scholarly Journal Article
  • Group Presentations
  • Dealing with Nervousness
  • Using Visual Aids
  • Grading Someone Else's Paper
  • Types of Structured Group Activities
  • Group Project Survival Skills
  • Leading a Class Discussion
  • Multiple Book Review Essay
  • Reviewing Collected Works
  • Writing a Case Analysis Paper
  • Writing a Case Study
  • About Informed Consent
  • Writing Field Notes
  • Writing a Policy Memo
  • Writing a Reflective Paper
  • Writing a Research Proposal
  • Generative AI and Writing
  • Acknowledgments

A case study research paper examines a person, place, event, condition, phenomenon, or other type of subject of analysis in order to extrapolate  key themes and results that help predict future trends, illuminate previously hidden issues that can be applied to practice, and/or provide a means for understanding an important research problem with greater clarity. A case study research paper usually examines a single subject of analysis, but case study papers can also be designed as a comparative investigation that shows relationships between two or more subjects. The methods used to study a case can rest within a quantitative, qualitative, or mixed-method investigative paradigm.

Case Studies. Writing@CSU. Colorado State University; Mills, Albert J. , Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010 ; “What is a Case Study?” In Swanborn, Peter G. Case Study Research: What, Why and How? London: SAGE, 2010.

How to Approach Writing a Case Study Research Paper

General information about how to choose a topic to investigate can be found under the " Choosing a Research Problem " tab in the Organizing Your Social Sciences Research Paper writing guide. Review this page because it may help you identify a subject of analysis that can be investigated using a case study design.

However, identifying a case to investigate involves more than choosing the research problem . A case study encompasses a problem contextualized around the application of in-depth analysis, interpretation, and discussion, often resulting in specific recommendations for action or for improving existing conditions. As Seawright and Gerring note, practical considerations such as time and access to information can influence case selection, but these issues should not be the sole factors used in describing the methodological justification for identifying a particular case to study. Given this, selecting a case includes considering the following:

  • The case represents an unusual or atypical example of a research problem that requires more in-depth analysis? Cases often represent a topic that rests on the fringes of prior investigations because the case may provide new ways of understanding the research problem. For example, if the research problem is to identify strategies to improve policies that support girl's access to secondary education in predominantly Muslim nations, you could consider using Azerbaijan as a case study rather than selecting a more obvious nation in the Middle East. Doing so may reveal important new insights into recommending how governments in other predominantly Muslim nations can formulate policies that support improved access to education for girls.
  • The case provides important insight or illuminate a previously hidden problem? In-depth analysis of a case can be based on the hypothesis that the case study will reveal trends or issues that have not been exposed in prior research or will reveal new and important implications for practice. For example, anecdotal evidence may suggest drug use among homeless veterans is related to their patterns of travel throughout the day. Assuming prior studies have not looked at individual travel choices as a way to study access to illicit drug use, a case study that observes a homeless veteran could reveal how issues of personal mobility choices facilitate regular access to illicit drugs. Note that it is important to conduct a thorough literature review to ensure that your assumption about the need to reveal new insights or previously hidden problems is valid and evidence-based.
  • The case challenges and offers a counter-point to prevailing assumptions? Over time, research on any given topic can fall into a trap of developing assumptions based on outdated studies that are still applied to new or changing conditions or the idea that something should simply be accepted as "common sense," even though the issue has not been thoroughly tested in current practice. A case study analysis may offer an opportunity to gather evidence that challenges prevailing assumptions about a research problem and provide a new set of recommendations applied to practice that have not been tested previously. For example, perhaps there has been a long practice among scholars to apply a particular theory in explaining the relationship between two subjects of analysis. Your case could challenge this assumption by applying an innovative theoretical framework [perhaps borrowed from another discipline] to explore whether this approach offers new ways of understanding the research problem. Taking a contrarian stance is one of the most important ways that new knowledge and understanding develops from existing literature.
  • The case provides an opportunity to pursue action leading to the resolution of a problem? Another way to think about choosing a case to study is to consider how the results from investigating a particular case may result in findings that reveal ways in which to resolve an existing or emerging problem. For example, studying the case of an unforeseen incident, such as a fatal accident at a railroad crossing, can reveal hidden issues that could be applied to preventative measures that contribute to reducing the chance of accidents in the future. In this example, a case study investigating the accident could lead to a better understanding of where to strategically locate additional signals at other railroad crossings so as to better warn drivers of an approaching train, particularly when visibility is hindered by heavy rain, fog, or at night.
  • The case offers a new direction in future research? A case study can be used as a tool for an exploratory investigation that highlights the need for further research about the problem. A case can be used when there are few studies that help predict an outcome or that establish a clear understanding about how best to proceed in addressing a problem. For example, after conducting a thorough literature review [very important!], you discover that little research exists showing the ways in which women contribute to promoting water conservation in rural communities of east central Africa. A case study of how women contribute to saving water in a rural village of Uganda can lay the foundation for understanding the need for more thorough research that documents how women in their roles as cooks and family caregivers think about water as a valuable resource within their community. This example of a case study could also point to the need for scholars to build new theoretical frameworks around the topic [e.g., applying feminist theories of work and family to the issue of water conservation].

Eisenhardt, Kathleen M. “Building Theories from Case Study Research.” Academy of Management Review 14 (October 1989): 532-550; Emmel, Nick. Sampling and Choosing Cases in Qualitative Research: A Realist Approach . Thousand Oaks, CA: SAGE Publications, 2013; Gerring, John. “What Is a Case Study and What Is It Good for?” American Political Science Review 98 (May 2004): 341-354; Mills, Albert J. , Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010; Seawright, Jason and John Gerring. "Case Selection Techniques in Case Study Research." Political Research Quarterly 61 (June 2008): 294-308.

Structure and Writing Style

The purpose of a paper in the social sciences designed around a case study is to thoroughly investigate a subject of analysis in order to reveal a new understanding about the research problem and, in so doing, contributing new knowledge to what is already known from previous studies. In applied social sciences disciplines [e.g., education, social work, public administration, etc.], case studies may also be used to reveal best practices, highlight key programs, or investigate interesting aspects of professional work.

In general, the structure of a case study research paper is not all that different from a standard college-level research paper. However, there are subtle differences you should be aware of. Here are the key elements to organizing and writing a case study research paper.

I.  Introduction

As with any research paper, your introduction should serve as a roadmap for your readers to ascertain the scope and purpose of your study . The introduction to a case study research paper, however, should not only describe the research problem and its significance, but you should also succinctly describe why the case is being used and how it relates to addressing the problem. The two elements should be linked. With this in mind, a good introduction answers these four questions:

  • What is being studied? Describe the research problem and describe the subject of analysis [the case] you have chosen to address the problem. Explain how they are linked and what elements of the case will help to expand knowledge and understanding about the problem.
  • Why is this topic important to investigate? Describe the significance of the research problem and state why a case study design and the subject of analysis that the paper is designed around is appropriate in addressing the problem.
  • What did we know about this topic before I did this study? Provide background that helps lead the reader into the more in-depth literature review to follow. If applicable, summarize prior case study research applied to the research problem and why it fails to adequately address the problem. Describe why your case will be useful. If no prior case studies have been used to address the research problem, explain why you have selected this subject of analysis.
  • How will this study advance new knowledge or new ways of understanding? Explain why your case study will be suitable in helping to expand knowledge and understanding about the research problem.

Each of these questions should be addressed in no more than a few paragraphs. Exceptions to this can be when you are addressing a complex research problem or subject of analysis that requires more in-depth background information.

II.  Literature Review

The literature review for a case study research paper is generally structured the same as it is for any college-level research paper. The difference, however, is that the literature review is focused on providing background information and  enabling historical interpretation of the subject of analysis in relation to the research problem the case is intended to address . This includes synthesizing studies that help to:

  • Place relevant works in the context of their contribution to understanding the case study being investigated . This would involve summarizing studies that have used a similar subject of analysis to investigate the research problem. If there is literature using the same or a very similar case to study, you need to explain why duplicating past research is important [e.g., conditions have changed; prior studies were conducted long ago, etc.].
  • Describe the relationship each work has to the others under consideration that informs the reader why this case is applicable . Your literature review should include a description of any works that support using the case to investigate the research problem and the underlying research questions.
  • Identify new ways to interpret prior research using the case study . If applicable, review any research that has examined the research problem using a different research design. Explain how your use of a case study design may reveal new knowledge or a new perspective or that can redirect research in an important new direction.
  • Resolve conflicts amongst seemingly contradictory previous studies . This refers to synthesizing any literature that points to unresolved issues of concern about the research problem and describing how the subject of analysis that forms the case study can help resolve these existing contradictions.
  • Point the way in fulfilling a need for additional research . Your review should examine any literature that lays a foundation for understanding why your case study design and the subject of analysis around which you have designed your study may reveal a new way of approaching the research problem or offer a perspective that points to the need for additional research.
  • Expose any gaps that exist in the literature that the case study could help to fill . Summarize any literature that not only shows how your subject of analysis contributes to understanding the research problem, but how your case contributes to a new way of understanding the problem that prior research has failed to do.
  • Locate your own research within the context of existing literature [very important!] . Collectively, your literature review should always place your case study within the larger domain of prior research about the problem. The overarching purpose of reviewing pertinent literature in a case study paper is to demonstrate that you have thoroughly identified and synthesized prior studies in relation to explaining the relevance of the case in addressing the research problem.

III.  Method

In this section, you explain why you selected a particular case [i.e., subject of analysis] and the strategy you used to identify and ultimately decide that your case was appropriate in addressing the research problem. The way you describe the methods used varies depending on the type of subject of analysis that constitutes your case study.

If your subject of analysis is an incident or event . In the social and behavioral sciences, the event or incident that represents the case to be studied is usually bounded by time and place, with a clear beginning and end and with an identifiable location or position relative to its surroundings. The subject of analysis can be a rare or critical event or it can focus on a typical or regular event. The purpose of studying a rare event is to illuminate new ways of thinking about the broader research problem or to test a hypothesis. Critical incident case studies must describe the method by which you identified the event and explain the process by which you determined the validity of this case to inform broader perspectives about the research problem or to reveal new findings. However, the event does not have to be a rare or uniquely significant to support new thinking about the research problem or to challenge an existing hypothesis. For example, Walo, Bull, and Breen conducted a case study to identify and evaluate the direct and indirect economic benefits and costs of a local sports event in the City of Lismore, New South Wales, Australia. The purpose of their study was to provide new insights from measuring the impact of a typical local sports event that prior studies could not measure well because they focused on large "mega-events." Whether the event is rare or not, the methods section should include an explanation of the following characteristics of the event: a) when did it take place; b) what were the underlying circumstances leading to the event; and, c) what were the consequences of the event in relation to the research problem.

If your subject of analysis is a person. Explain why you selected this particular individual to be studied and describe what experiences they have had that provide an opportunity to advance new understandings about the research problem. Mention any background about this person which might help the reader understand the significance of their experiences that make them worthy of study. This includes describing the relationships this person has had with other people, institutions, and/or events that support using them as the subject for a case study research paper. It is particularly important to differentiate the person as the subject of analysis from others and to succinctly explain how the person relates to examining the research problem [e.g., why is one politician in a particular local election used to show an increase in voter turnout from any other candidate running in the election]. Note that these issues apply to a specific group of people used as a case study unit of analysis [e.g., a classroom of students].

If your subject of analysis is a place. In general, a case study that investigates a place suggests a subject of analysis that is unique or special in some way and that this uniqueness can be used to build new understanding or knowledge about the research problem. A case study of a place must not only describe its various attributes relevant to the research problem [e.g., physical, social, historical, cultural, economic, political], but you must state the method by which you determined that this place will illuminate new understandings about the research problem. It is also important to articulate why a particular place as the case for study is being used if similar places also exist [i.e., if you are studying patterns of homeless encampments of veterans in open spaces, explain why you are studying Echo Park in Los Angeles rather than Griffith Park?]. If applicable, describe what type of human activity involving this place makes it a good choice to study [e.g., prior research suggests Echo Park has more homeless veterans].

If your subject of analysis is a phenomenon. A phenomenon refers to a fact, occurrence, or circumstance that can be studied or observed but with the cause or explanation to be in question. In this sense, a phenomenon that forms your subject of analysis can encompass anything that can be observed or presumed to exist but is not fully understood. In the social and behavioral sciences, the case usually focuses on human interaction within a complex physical, social, economic, cultural, or political system. For example, the phenomenon could be the observation that many vehicles used by ISIS fighters are small trucks with English language advertisements on them. The research problem could be that ISIS fighters are difficult to combat because they are highly mobile. The research questions could be how and by what means are these vehicles used by ISIS being supplied to the militants and how might supply lines to these vehicles be cut off? How might knowing the suppliers of these trucks reveal larger networks of collaborators and financial support? A case study of a phenomenon most often encompasses an in-depth analysis of a cause and effect that is grounded in an interactive relationship between people and their environment in some way.

NOTE:   The choice of the case or set of cases to study cannot appear random. Evidence that supports the method by which you identified and chose your subject of analysis should clearly support investigation of the research problem and linked to key findings from your literature review. Be sure to cite any studies that helped you determine that the case you chose was appropriate for examining the problem.

IV.  Discussion

The main elements of your discussion section are generally the same as any research paper, but centered around interpreting and drawing conclusions about the key findings from your analysis of the case study. Note that a general social sciences research paper may contain a separate section to report findings. However, in a paper designed around a case study, it is common to combine a description of the results with the discussion about their implications. The objectives of your discussion section should include the following:

Reiterate the Research Problem/State the Major Findings Briefly reiterate the research problem you are investigating and explain why the subject of analysis around which you designed the case study were used. You should then describe the findings revealed from your study of the case using direct, declarative, and succinct proclamation of the study results. Highlight any findings that were unexpected or especially profound.

Explain the Meaning of the Findings and Why They are Important Systematically explain the meaning of your case study findings and why you believe they are important. Begin this part of the section by repeating what you consider to be your most important or surprising finding first, then systematically review each finding. Be sure to thoroughly extrapolate what your analysis of the case can tell the reader about situations or conditions beyond the actual case that was studied while, at the same time, being careful not to misconstrue or conflate a finding that undermines the external validity of your conclusions.

Relate the Findings to Similar Studies No study in the social sciences is so novel or possesses such a restricted focus that it has absolutely no relation to previously published research. The discussion section should relate your case study results to those found in other studies, particularly if questions raised from prior studies served as the motivation for choosing your subject of analysis. This is important because comparing and contrasting the findings of other studies helps support the overall importance of your results and it highlights how and in what ways your case study design and the subject of analysis differs from prior research about the topic.

Consider Alternative Explanations of the Findings Remember that the purpose of social science research is to discover and not to prove. When writing the discussion section, you should carefully consider all possible explanations revealed by the case study results, rather than just those that fit your hypothesis or prior assumptions and biases. Be alert to what the in-depth analysis of the case may reveal about the research problem, including offering a contrarian perspective to what scholars have stated in prior research if that is how the findings can be interpreted from your case.

Acknowledge the Study's Limitations You can state the study's limitations in the conclusion section of your paper but describing the limitations of your subject of analysis in the discussion section provides an opportunity to identify the limitations and explain why they are not significant. This part of the discussion section should also note any unanswered questions or issues your case study could not address. More detailed information about how to document any limitations to your research can be found here .

Suggest Areas for Further Research Although your case study may offer important insights about the research problem, there are likely additional questions related to the problem that remain unanswered or findings that unexpectedly revealed themselves as a result of your in-depth analysis of the case. Be sure that the recommendations for further research are linked to the research problem and that you explain why your recommendations are valid in other contexts and based on the original assumptions of your study.

V.  Conclusion

As with any research paper, you should summarize your conclusion in clear, simple language; emphasize how the findings from your case study differs from or supports prior research and why. Do not simply reiterate the discussion section. Provide a synthesis of key findings presented in the paper to show how these converge to address the research problem. If you haven't already done so in the discussion section, be sure to document the limitations of your case study and any need for further research.

The function of your paper's conclusion is to: 1) reiterate the main argument supported by the findings from your case study; 2) state clearly the context, background, and necessity of pursuing the research problem using a case study design in relation to an issue, controversy, or a gap found from reviewing the literature; and, 3) provide a place to persuasively and succinctly restate the significance of your research problem, given that the reader has now been presented with in-depth information about the topic.

Consider the following points to help ensure your conclusion is appropriate:

  • If the argument or purpose of your paper is complex, you may need to summarize these points for your reader.
  • If prior to your conclusion, you have not yet explained the significance of your findings or if you are proceeding inductively, use the conclusion of your paper to describe your main points and explain their significance.
  • Move from a detailed to a general level of consideration of the case study's findings that returns the topic to the context provided by the introduction or within a new context that emerges from your case study findings.

Note that, depending on the discipline you are writing in or the preferences of your professor, the concluding paragraph may contain your final reflections on the evidence presented as it applies to practice or on the essay's central research problem. However, the nature of being introspective about the subject of analysis you have investigated will depend on whether you are explicitly asked to express your observations in this way.

Problems to Avoid

Overgeneralization One of the goals of a case study is to lay a foundation for understanding broader trends and issues applied to similar circumstances. However, be careful when drawing conclusions from your case study. They must be evidence-based and grounded in the results of the study; otherwise, it is merely speculation. Looking at a prior example, it would be incorrect to state that a factor in improving girls access to education in Azerbaijan and the policy implications this may have for improving access in other Muslim nations is due to girls access to social media if there is no documentary evidence from your case study to indicate this. There may be anecdotal evidence that retention rates were better for girls who were engaged with social media, but this observation would only point to the need for further research and would not be a definitive finding if this was not a part of your original research agenda.

Failure to Document Limitations No case is going to reveal all that needs to be understood about a research problem. Therefore, just as you have to clearly state the limitations of a general research study , you must describe the specific limitations inherent in the subject of analysis. For example, the case of studying how women conceptualize the need for water conservation in a village in Uganda could have limited application in other cultural contexts or in areas where fresh water from rivers or lakes is plentiful and, therefore, conservation is understood more in terms of managing access rather than preserving access to a scarce resource.

Failure to Extrapolate All Possible Implications Just as you don't want to over-generalize from your case study findings, you also have to be thorough in the consideration of all possible outcomes or recommendations derived from your findings. If you do not, your reader may question the validity of your analysis, particularly if you failed to document an obvious outcome from your case study research. For example, in the case of studying the accident at the railroad crossing to evaluate where and what types of warning signals should be located, you failed to take into consideration speed limit signage as well as warning signals. When designing your case study, be sure you have thoroughly addressed all aspects of the problem and do not leave gaps in your analysis that leave the reader questioning the results.

Case Studies. Writing@CSU. Colorado State University; Gerring, John. Case Study Research: Principles and Practices . New York: Cambridge University Press, 2007; Merriam, Sharan B. Qualitative Research and Case Study Applications in Education . Rev. ed. San Francisco, CA: Jossey-Bass, 1998; Miller, Lisa L. “The Use of Case Studies in Law and Social Science Research.” Annual Review of Law and Social Science 14 (2018): TBD; Mills, Albert J., Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010; Putney, LeAnn Grogan. "Case Study." In Encyclopedia of Research Design , Neil J. Salkind, editor. (Thousand Oaks, CA: SAGE Publications, 2010), pp. 116-120; Simons, Helen. Case Study Research in Practice . London: SAGE Publications, 2009;  Kratochwill,  Thomas R. and Joel R. Levin, editors. Single-Case Research Design and Analysis: New Development for Psychology and Education .  Hilldsale, NJ: Lawrence Erlbaum Associates, 1992; Swanborn, Peter G. Case Study Research: What, Why and How? London : SAGE, 2010; Yin, Robert K. Case Study Research: Design and Methods . 6th edition. Los Angeles, CA, SAGE Publications, 2014; Walo, Maree, Adrian Bull, and Helen Breen. “Achieving Economic Benefits at Local Events: A Case Study of a Local Sports Event.” Festival Management and Event Tourism 4 (1996): 95-106.

Writing Tip

At Least Five Misconceptions about Case Study Research

Social science case studies are often perceived as limited in their ability to create new knowledge because they are not randomly selected and findings cannot be generalized to larger populations. Flyvbjerg examines five misunderstandings about case study research and systematically "corrects" each one. To quote, these are:

Misunderstanding 1 :  General, theoretical [context-independent] knowledge is more valuable than concrete, practical [context-dependent] knowledge. Misunderstanding 2 :  One cannot generalize on the basis of an individual case; therefore, the case study cannot contribute to scientific development. Misunderstanding 3 :  The case study is most useful for generating hypotheses; that is, in the first stage of a total research process, whereas other methods are more suitable for hypotheses testing and theory building. Misunderstanding 4 :  The case study contains a bias toward verification, that is, a tendency to confirm the researcher’s preconceived notions. Misunderstanding 5 :  It is often difficult to summarize and develop general propositions and theories on the basis of specific case studies [p. 221].

While writing your paper, think introspectively about how you addressed these misconceptions because to do so can help you strengthen the validity and reliability of your research by clarifying issues of case selection, the testing and challenging of existing assumptions, the interpretation of key findings, and the summation of case outcomes. Think of a case study research paper as a complete, in-depth narrative about the specific properties and key characteristics of your subject of analysis applied to the research problem.

Flyvbjerg, Bent. “Five Misunderstandings About Case-Study Research.” Qualitative Inquiry 12 (April 2006): 219-245.

  • << Previous: Writing a Case Analysis Paper
  • Next: Writing a Field Report >>
  • Last Updated: Mar 6, 2024 1:00 PM
  • URL: https://libguides.usc.edu/writingguide/assignments
  • Dictionaries home
  • American English
  • Collocations
  • German-English
  • Grammar home
  • Practical English Usage
  • Learn & Practise Grammar (Beta)
  • Word Lists home
  • My Word Lists
  • Recent additions
  • Resources home
  • Text Checker

Definition of case study noun from the Oxford Advanced American Dictionary

Take your English to the next level

The Oxford Learner’s Thesaurus explains the difference between groups of similar words. Try it for free as part of the Oxford Advanced Learner’s Dictionary app

the word case study meaning

The Fossil Encased in "Case In Point"

"In point" only lives on in this phrase.

Dictionary Entries Near case

Cite this entry.

“Case.” Merriam-Webster.com Dictionary , Merriam-Webster, https://www.merriam-webster.com/dictionary/case. Accessed 28 Apr. 2024.

Kids Definition

Kids definition of case.

 (Entry 1 of 2)

Kids Definition of case  (Entry 2 of 2)

Middle English cas "situation needing action," from early French cas (same meaning), from Latin casus "fall, chance," from cadere "to fall, happen, come by chance"

Middle English cas "box, container," from early French case, chase (same meaning), from Latin capsa "chest, box," from capere "to take" — related to capture , cash

Medical Definition

Medical definition of case, legal definition, legal definition of case.

Note: A test case is selected from a number of cases in order to avoid a flood of litigation. All of the parties to the cases must agree to accept the outcome of the test case as binding.

Legal Definition of case  (Entry 2 of 2)

Latin casus accident, event, set of circumstances, literally, act of falling

More from Merriam-Webster on case

Nglish: Translation of case for Spanish Speakers

Britannica English: Translation of case for Arabic Speakers

Britannica.com: Encyclopedia article about case

Subscribe to America's largest dictionary and get thousands more definitions and advanced search—ad free!

Play Quordle: Guess all four words in a limited number of tries.  Each of your guesses must be a real 5-letter word.

Can you solve 4 words at once?

Word of the day.

See Definitions and Examples »

Get Word of the Day daily email!

Popular in Grammar & Usage

More commonly misspelled words, commonly misspelled words, how to use em dashes (—), en dashes (–) , and hyphens (-), absent letters that are heard anyway, how to use accents and diacritical marks, popular in wordplay, the words of the week - apr. 26, 9 superb owl words, 'gaslighting,' 'woke,' 'democracy,' and other top lookups, 10 words for lesser-known games and sports, your favorite band is in the dictionary, games & quizzes.

Play Blossom: Solve today's spelling word game by finding as many words as you can using just 7 letters. Longer words score more points.

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • View all journals
  • My Account Login
  • Explore content
  • About the journal
  • Publish with us
  • Sign up for alerts
  • Open access
  • Published: 01 April 2024

Adaptive neighborhood rough set model for hybrid data processing: a case study on Parkinson’s disease behavioral analysis

  • Imran Raza 1 ,
  • Muhammad Hasan Jamal 1 ,
  • Rizwan Qureshi 1 ,
  • Abdul Karim Shahid 1 ,
  • Angel Olider Rojas Vistorte 2 , 3 , 4 ,
  • Md Abdus Samad 5 &
  • Imran Ashraf 5  

Scientific Reports volume  14 , Article number:  7635 ( 2024 ) Cite this article

234 Accesses

Metrics details

  • Computational biology and bioinformatics
  • Machine learning

Extracting knowledge from hybrid data, comprising both categorical and numerical data, poses significant challenges due to the inherent difficulty in preserving information and practical meanings during the conversion process. To address this challenge, hybrid data processing methods, combining complementary rough sets, have emerged as a promising approach for handling uncertainty. However, selecting an appropriate model and effectively utilizing it in data mining requires a thorough qualitative and quantitative comparison of existing hybrid data processing models. This research aims to contribute to the analysis of hybrid data processing models based on neighborhood rough sets by investigating the inherent relationships among these models. We propose a generic neighborhood rough set-based hybrid model specifically designed for processing hybrid data, thereby enhancing the efficacy of the data mining process without resorting to discretization and avoiding information loss or practical meaning degradation in datasets. The proposed scheme dynamically adapts the threshold value for the neighborhood approximation space according to the characteristics of the given datasets, ensuring optimal performance without sacrificing accuracy. To evaluate the effectiveness of the proposed scheme, we develop a testbed tailored for Parkinson’s patients, a domain where hybrid data processing is particularly relevant. The experimental results demonstrate that the proposed scheme consistently outperforms existing schemes in adaptively handling both numerical and categorical data, achieving an impressive accuracy of 95% on the Parkinson’s dataset. Overall, this research contributes to advancing hybrid data processing techniques by providing a robust and adaptive solution that addresses the challenges associated with handling hybrid data, particularly in the context of Parkinson’s disease analysis.

Similar content being viewed by others

the word case study meaning

Soft ordered double quantitative approximations based three-way decisions and their applications

the word case study meaning

Hybrid similarity relation based mutual information for feature selection in intuitionistic fuzzy rough framework and its applications

the word case study meaning

A dynamic fuzzy rule-based inference system using fuzzy inference with semantic reasoning

Introduction.

The advancement of technology has facilitated the accumulation of vast amounts of data from various sources such as databases, web repositories, and files, necessitating robust tools for analysis and decision-making 1 , 2 . Data mining, employing techniques such as support vector machine (SVM), decision trees, neural networks, clustering, fuzzy logic, and genetic algorithms, plays a pivotal role in extracting information and uncovering hidden patterns within the data 3 , 4 . However, the complexity of the data landscape, characterized by high dimensionality, heterogeneity, and non-traditional structures, renders the data mining process inherently challenging 5 , 6 . To tackle these challenges effectively, a combination of complementary and cooperative intelligent techniques, including SVM, fuzzy logic, probabilistic reasoning, genetic algorithms, and neural networks, has been advocated 7 , 8 .

Hybrid intelligent systems, amalgamating various intelligent techniques, have emerged as a promising approach to enhance the efficacy of data mining. Adaptive neuro-fuzzy inference systems (ANFIS) have laid the groundwork for intelligent systems in data mining techniques, providing a foundation for exploring complex data relationships 7 , 8 . Moreover, the theory of rough sets has found practical application in tasks such as attribute selection, data reduction, decision rule generation, and pattern extraction, contributing to the development of intelligent systems for knowledge discovery 7 , 8 . Extracting meaningful knowledge from hybrid data, which encompasses both categorical and numerical data, presents a significant challenge. Two predominant strategies have emerged to address this challenge 9 , 10 . The first strategy involves employing numerical data processing techniques such as Principal Component Analysis (PCA) 11 , 12 , Neural Networks 13 , 14 , 15 , 16 , and SVM 17 . However, this approach necessitates converting categorical data into numerical equivalents, leading to a loss of contextual meaning 18 , 19 . The second strategy leverages rough set theory alongside methods tailored for categorical data. Nonetheless, applying rough set theory to numerical data requires a discretization process, resulting in information loss 20 , 21 . Numerous hybrid data processing methods have been proposed, combining rough sets and fuzzy sets to handle uncertainty 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 . However, selecting an appropriate rough set model for a given dataset necessitates exploring the inherent relationships among existing models, presenting a challenge for users. The selection and utilization of an appropriate model in data mining thus demand qualitative and quantitative comparisons of existing hybrid data processing models.

This research endeavors to present a comprehensive analysis of hybrid data processing models, with a specific focus on those rooted in neighborhood rough sets (NRS). By investigating the inherent interconnections among these models, this study aims to elucidate their complex dynamics. To address the challenges posed by hybrid data, a novel hybrid model founded on NRS is introduced. This model enhances the efficiency of the data mining process without discretization mitigating information loss and ambiguity in data interpretation. Notably, the adaptability of the proposed model, particularly in adjusting the threshold value governing the neighborhood approximation space, ensures optimal performance aligned with dataset characteristics while maintaining high accuracy. A dedicated testbed tailored for Parkinson’s patients is developed to evaluate the real-world effectiveness of the proposed approach. Furthermore, a rigorous evaluation of the proposed model is conducted, encompassing both accuracy and overall effectiveness. Encouragingly, the results demonstrate that the proposed scheme surpasses alternative approaches, adeptly managing both numerical and categorical data through an adaptive framework.

The major contributions, listed below, collectively emphasize the innovative hybrid data processing model, the adaptive nature of its thresholding mechanism, and the empirical validation using a Parkinson’s patient testbed, underscoring the relevance and significance of the study’s findings.

Novel Hybrid Data Processing Model: This research introduces a novel hybrid data processing model based on NRS, preserving the practical meaning of both numerical and categorical data types. Unlike conventional methods, it minimizes information loss while optimizing interpretability. The proposed distance function combines Euclidean and Levenshtein distances with weighted calculations and dynamic selection mechanisms to enhance accuracy and realism in neighborhood approximation spaces.

Adaptive Thresholding Mechanism: Another key contribution is the integration of an adaptive thresholding mechanism within the hybrid model. This feature dynamically adjusts the threshold value based on dataset characteristics, ensuring optimal performance and yielding more accurate and contextually relevant results.

Empirical Validation through Parkinson’s Testbed: This research provides a dedicated testbed for analyzing behavioral data from Parkinson’s patients, allowing rigorous evaluation of the proposed hybrid data processing model. Utilizing real-world datasets enhances the model’s practical applicability and advances knowledge in medical data analysis and diagnosis.

The subsequent structure of the paper unfolds as follows: section “ Related work ” delves into the related work. The proposed model is introduced in section “ Adaptive neighborhood rough set model ”, Section “ Instrumentation ” underscores the instrumentation aspect, section “ Result and discussion ” unfolds the presentation of results and ensuing discussions, while section “ Conclusion and future work ” provides the concluding remarks for the paper. A list of notations used in this study is provided in Table  1 .

Related work

Rough set-based approaches have been utilized in various applications like bankruptcy prediction 42 , attribute/feature subset selection 43 , 44 , cancer prediction 45 , 46 , etc. In addition, recently, several innovative hybrid models have emerged, blending the realms of fuzzy logic and non-randomized systems (NRSs). One such development is presented by Yin et al. 47 , who introduce a parameterized hybrid fuzzy similarity relation. They apply this relation to the task of granulating multilabel data, subsequently extending it to the domain of multilabel learning. To construct a noise-tolerant multilabel fuzzy NRS model (NT-MLFNRS), they leverage the inclusion relationship between fuzzy neighborhood granules and fuzzy decisions. Building upon NT-MLFNRS, Yin et al. also devise a noise-resistant heuristic multilabel feature selection (NRFSFN) algorithm. To further enhance the efficiency of feature selection and address the complexities associated with handling large-scale multilabel datasets, they culminate their efforts by introducing an efficient extended version of NRFSFN known as ENFSFN.

Sang et al. 48 explore incremental feature selection methodologies, introducing a novel conditional entropy metric tailored for dynamic ordered data robustness. Their approach introduces the concept of a fuzzy dominance neighborhood rough set (FDNRS) and defines a conditional entropy metric with robustness, leveraging the FDNRS model. This metric serves as an evaluation criterion for features, and it is integrated into a heuristic feature selection algorithm. The resulting incremental feature selection algorithm is built upon this innovative model

Wang et al. 19 introduced the Fuzzy Rough Iterative Computational (FRIC) model, addressing challenges in hybrid information systems (HIS). Their framework includes a specialized distance function for object sets, enhancing object differentiation precision within HIS. Utilizing this function, they establish fuzzy symmetric relations among objects to formulate fuzzy rough approximations. Additionally, they introduce evaluation functions like fuzzy positive regions, dependency functions, and attribute importance functions to assess classification capabilities of attribute sets. They developed an attribute reduction algorithm tailored for hybrid data based on FRIC principles. This work contributes significantly to HIS analysis, providing a robust framework for data classification and feature selection in complex hybrid information systems.

Xu et al. 49 introduced a novel Fitting Fuzzy Rough Set (FRS) model enriched with relative dependency complement mutual information. This model addresses challenges related to data distribution and precision enhancement of fuzzy information granules. They utilized relative distance to mitigate the influence of data distribution on fuzzy similarity relationships and introduced a fitting fuzzy neighborhood radius optimized for enhancing the precision of fuzzy information granules. Within this model, the authors conducted a comprehensive analysis of information uncertainty, introducing definitions of relative complement information entropy and formulating a multiview uncertainty measure based on relative dependency complement mutual information. This work significantly advances our understanding of managing information uncertainty within FRS models, making a valuable contribution to computational modeling and data analysis.

Jiang et al. 50 presented an innovative approach for multiattribute decision-making (MADM) rooted in PROMETHEE II methodologies. Building upon the NRS model, they introduce two additional variants of covering-based variable precision fuzzy rough sets (CVPFRSs) by applying fuzzy logical operators, specifically type-I CVPFRSs and type-II CVPFRSs. In the context of MADM, their method entails the selection of medicines using an algorithm that leverages the identified features.

Qu et al. 51 introduced the concept of Adaptive Neighborhood Rough Sets (ANRSs), aiming for effective integration of feature separation and linkage with classification. They utilize the mRMR-based Feature Selection Algorithm (FSRMI), demonstrating outstanding performance across various selected datasets. However, it’s worth noting that FSRMI may not consistently outperform other algorithms on all datasets.

Xu et al. 52 introduced the Fuzzy Neighborhood Joint Entropy Model (FNSIJE) for feature selection, leveraging fuzzy neighborhood self-information measures and joint entropy to capture combined feature information. FNSIJE comprehensively analyzes the neighborhood decision system, considering noise, uncertainty, and ambiguity. To improve classification performance, the authors devised a new forward search method. Experimental results demonstrated the effectiveness of FNSIJE-KS, efficiently selecting fewer features for both low-dimensional UCI datasets and high-dimensional gene datasets while maintaining optimal classification performance. This approach advances feature selection techniques in machine learning and data analysis.

In 53 , the authors introduced a novel multi-label feature selection method utilizing fuzzy NRS to optimize classification performance in multi-label fuzzy neighborhood decision systems. By combining the NRS and FRS models a Multi-Label Fuzzy NRS model is introduced. They devised a fuzzy neighborhood approximation accuracy metric and crafted a hybrid metric integrating fuzzy neighborhood approximate accuracy with fuzzy neighborhood conditional entropy for attribute importance evaluation. Rigorous evaluation of their methods across ten diverse multi-label datasets showcased significant progress in multi-label feature selection techniques, promising enhanced classification performance in complex multi-label scenarios.

Sanget et al. 54 introduced the Fuzzy Dominance Neighborhood Rough Set (NRS) model for Interval-Valued Ordered Decision Systems (IvODS), along with a robust conditional entropy measure to assess monotonic consistency within IvODS. They also presented two incremental feature selection algorithms. Experimental results on nine publicly available datasets showcased the robustness of their proposed metric and the effectiveness and efficiency of the incremental algorithms, particularly in dynamic IvODS updates. This research significantly advances the application of fuzzy dominance NRS models in IvODS scenarios, providing valuable insights for data analysis and decision-making processes.

Zheng et al. 55 generalized the FRSs using axiomatic and constructive approaches. A pair of dual generalized fuzzy approximation operators is defined using arbitrary fuzzy relation in the constructive approach. Different classes of FRSs are characterized using different sets of axioms. The postulates governing fuzzy approximation operators ensure the presence of specific categories of fuzzy relations yielding identical operators. Using a generalized FRS model, Hu et al. 18 introduced an efficient algorithm for hybrid attribute reduction based on fuzzy relations constructing a forward greedy algorithm for hybrid attribute reduction resulting in optimal classification performance with lesser selected features and higher accuracy. Considering the similarity between two objects, Wang et al. 36 redefine fuzzy upper and lower approximations. The existing concepts of knowledge reduction are extending fuzzy environment resulting in a heuristic algorithm to learn fuzzy rules.

Gogoi et al. 56 use rough set theory for generating decision rules from inconsistent data. The proposed scheme uses indiscernibility relation to find inconsistencies in the data generating minimized and non-redundant rules using lower and upper approximations. The proposed scheme is based on the LEM2 algorithm 57 which performs the local covering option for generating minimum and non-redundant sets of classification rules and does not consider the global covering. The scheme is evaluated on a variety of data sets from the UCI Machine Learning Repository. All these data sets are either categorical or numerical having variable feature spaces. The proposed scheme performs consistently better for categorical data sets, as it is designed to handle inconsistencies in the data having at least one inconsistency. Results show that the proposed scheme generates minimized rule without reducing the feature space unlike other schemes, which compromise the feature space.

In 58 , the authors introduced a novel NRS model to address attribute reduction in noisy systems with heterogeneous attributes. This model extends traditional NRS by incorporating tolerance neighborhood relation and probabilistic theory, resulting in more comprehensive information granules. It evaluates the significance of heterogeneous attributes by considering neighborhood dependency and aims to maximize classification consistency within selected feature spaces. The feature space reduction algorithm employs an incremental approach, adding features while preserving maximal dependency in each round and halting when a new feature no longer increases dependency. This approach selects fewer features than other methods while achieving significantly improved classification performance, demonstrating its effectiveness in attribute reduction for noisy systems.

Zhu et al. 59 propose a fault tolerance scheme combining kernel method, NRS, and statistical features to adaptively select sensitive features. They employ a Gaussian kernel function with NRS to map fault data to a high-dimensional space. Their feature selection algorithm utilizes the hyper-sphere radius in high-dimensional feature space as the neighborhood value, selecting features based on significance measure regardless of the classification algorithm. A wrapper deploys a classification algorithm to evaluate selected features, choosing a subset for optimal classification. Experimental results demonstrate precise determination of the neighborhood value by mapping data into a high-dimensional space using the kernel function and hyper-sphere radius. This methodology proficiently selects sensitive fault features, diagnoses fault types, and identifies fault degrees in rolling bearing datasets.

A neighborhood covering a rough set model for the fuzziness of decision systems is proposed that solves the problem of hybrid decision systems having both fuzzy and numerical attributes 60 . The fuzzy neighborhood relation measures the indiscernibility relation and approximates the universe space using information granules, which deal with fuzzy attributes directly. The experimental results evaluate the influence of neighborhood operator size on the accuracy and attribute reduction of fuzzy neighborhood rough sets. The attribute reduction increases with the increase in the threshold size. A feature will not distinguish any samples and cannot reduce attributes if the neighborhood operator exceeds a certain value.

Hou et al. 61 applied NRS reduction techniques to cancer molecular classification, focusing on gene expression profiles. Their method introduced a novel perspective by using gene occurrence probability in selected gene subsets to indicate tumor classification efficacy. Unlike traditional methods, it integrated both Filters and Wrappers, enhancing classification performance while being computationally efficient. Additionally, they developed an ensemble classifier to improve accuracy and stability without overfitting. Experimental results showed the method achieved high prediction accuracy, identified potential cancer biomarkers, and demonstrated stability in performance.

Table  2 gives a comparison of existing rough set-based schemes for quantitative and qualitative analysis. The comparative parameters include handling hybrid data, generalized NRS, attribute reduction, classification, and accuracy rate. Most of the existing schemes do not handle hybrid data sets without discretization resulting in information loss and a lack of practical meanings. Another parameter to evaluate the effectiveness of the existing scheme is the ability to adapt the threshold value according to the given data sets. Most of the schemes do not adapt threshold values for neighborhood approximation space resulting in variable accuracy rates for different datasets. The end-user has to adjust the value of the threshold for different datasets without understanding its impact in terms of overfitting. Selecting a large threshold value will result in more global rules resulting in poor accuracy. There needs to be a mechanism to adaptively choose the value of the threshold considering both the global and local information without compromising on the accuracy rate. The schemes are also evaluated for their ability to attribute reduction using NRS. This can greatly improve processing time and accuracy by not considering insignificant attributes. The comparative analysis shows that most of the NRS-based existing schemes perform better than many other well-known schemes in terms of accuracy. Most of these schemes have a higher accuracy rate than CART, C4.5, and k NN. This makes the NRS-based schemes a choice for attribute reduction and classification.

Adaptive neighborhood rough set model

The detailed analysis of existing techniques highlights the need for a generalized NRS-based classification technique to handle both categorical and numerical data. The proposed NRS-based techniques not only handle the hybrid information granules but also dynamically select the threshold \(\delta \) producing optimal results with a high accuracy rate. The proposed scheme considers a hybrid tuple \(HIS=\langle U_h,\ Q_h,\ V,\ f \rangle \) , where \(U_h\) is nonempty set of hybrid records \(\{x_{h1},\ x_{h2},\ x_{h3},\ \ldots ,\ x_{hn}\}\) , \(Q_h=\left\{ q_{h1},\ q_{h2},\ \ q_{h3},\ \ldots \,\ q_{hn}\right\} \) is the non-empty set of hybrid features. \( V_{q_h}\) is the domain of attribute \(q_h\) and \(V=\ \cup _{q_h\in Q_h}V_{q_h}\) , and \(f=U_h\ x\ Q_h\rightarrow V\) is a total function such \(f\left( x_h,q_h\right) \in V_{q_h}\) for each \(q_h\in Q_h, x_h\in U_h\) , called information function. \(\langle U_h,\ Q_h,\ V,\ f\rangle \) is also known as a decision table if \(Q_h=C_h\cup D\) , where \(C_h\) is the set of hybrid condition attributes and D is the decision attribute.

A neighborhood relation N is calculated using this set of hybrid samples \(U_h\) creating the neighborhood approximation space \(\langle U_h,\ N\rangle \) which contains information granules \( \left\{ \delta ({x_h}_i)\big |{x_h}_i\in U_h\right\} \) based on some distance function \(\Delta \) . For an arbitrary sample \({x_h}_i\in U_h\) and \(B \subseteq C_h\) , the neighborhood \(\delta _B({x_h}_i)\) of \({x_h}_i\) in the subspace B is defined as \(\delta _B\left( {x_h}_i\right) =\{{x_h}_j\left| {x_h}_j\right. \in U_h,\ \Delta B(x_i,x_j) \le \delta \}\) . The scheme proposes a new hybrid distance function to handle both the categorical and numerical features in an approximation space.

The proposed distance function uses Euclidean distance for numerical features and Levenshtein distance for categorical features. The distance function also takes care of the significant features calculating weighted distance for both the categorical and numerical features. The proposed algorithm dynamically selects the distance function at the run time. The use of Levenshtein distance for categorical features provides precise distance for optimal neighborhood approximation space providing better results. Existing techniques add 1 to distance if two strings do not match in calculating the distance for categorical data and add 0 otherwise. This may not result in a realistic neighborhood approximation space.

The neighborhood size depends on the threshold \(\delta \) . The neighborhood will contain more samples if \(\delta \) is greater and results in more rules not considering the local information data. The accuracy rate of the NRS greatly depends on the selection of threshold values. The proposed scheme dynamically calculates the threshold value for any given dataset considering both local and global information. The threshold calculation formula is given below where \({min}_D\) is the minimum distance between the set of training samples and the test sample containing local information and \(R_D\) is the range of distance between the set of training samples and the test sample containing the global information.

The proposed scheme then calculates the lower and upper approximations given a neighborhood space \(\langle U_h, N\rangle \) for \(X \subseteq U_h\) , the lower and upper approximations of X are defined as:

Given a hybrid neighborhood decision table \(HNDT=\langle U_h,\ C_h\cup \ D, V, f\rangle \) , \(\{ X_{h1},X_{h2},\ \ldots ,\ X_{hN} \}\) are the sample hybrid subjects with decision 1 to N , \(\delta _B\left( x_{hi}\right) \) is the information granules generated by attributes \(B \subseteq C_h\) , then the lower and upper approximation is defined as:

and the boundary region of D is defined as:

The lower and upper approximation spaces are the set of rules, which are used to classify a test sample. A test sample forms its neighborhood using a lower approximation having all the rules with a distance less than a dynamically calculated threshold value. The majority voting is used in the neighborhood of a test sample to decide the class of a test sample. K-fold cross-validation is used to measure the accuracy of the proposed scheme where the value k is 10. The algorithm 1 of the proposed scheme has a time complexity of \(O(nm^{2})\) where n is the number of clients and m is the size of the categorial data.

figure a

Instrumentation

The proposed generalized rough set model has been rigorously assessed through the development of a testbed designed for the classification of Parkinson’s patients. It has also been subjected to testing using various standard datasets sourced from the University of California at Irvine machine learning data repository 63 . This research underscores the increasing significance of biomedical engineering in healthcare, particularly in light of the growing prevalence of Parkinson’s disease, which ranks as the second most common neurodegenerative condition, impacting over 1% of the population aged 65 and above 64 . The disease manifests through distinct motor symptoms like resting tremors, bradykinesia (slowness of movement), rigidity, and poor balance, with medication-related side effects such as wearing off and dyskinesias 65 .

In this study, to address the need for a reliable quantitative method for assessing motor complications in Parkinson’s patients, the data collection process involves utilizing a home-monitoring system equipped with wireless wearable sensors. These sensors were specifically deployed to closely monitor Parkinson’s patients with severe tremors in real time. It’s important to note that all patients involved in the study were clinically diagnosed with Parkinson’s disease. Additionally, before data collection, proper consent was obtained from each participant, and the study protocol was approved by the ethical committee of our university. The data collected from these sensors is then analyzed, yielding reliable quantitative information that can significantly aid clinical decision-making within both routine patient care and clinical trials of innovative treatments.

figure 1

Testbed for Parkinson’s patients.

Figure  1 illustrates a real-time Testbed designed for monitoring Parkinson’s patients. This system utilizes a tri-axial accelerometer to capture three signals, one for each axis \((x,\ y,\ and\ z)\) , resulting in a total of 18 channels of data. The sensors employed in this setup employ ZigBee (IEEE 802.15.4 infrastructure) protocol to transmit data to a computer at a sampling rate of 62.5 Hz. To ensure synchronization of the transmitted signals, a transition protocol is applied. These data packets are received through the Serial Forwarder using the TinyOS platform ( http://www.tinyos.net ). The recorded acceleration data is represented as digital signals and can be visualized on an oscilloscope. The frequency domain data is obtained by applying the Fast Fourier Transform (FFT) to the signal, resulting in an ARFF file format that is then employed for classification purposes. The experimental flowchart is shown in Fig.  2 .

figure 2

Experimental flowchart.

The real-time testbed includes various components to capture data using the Unified Parkinson’s Disease Rating Scale (UPDRS). TelosB MTM-CM5000-MSP and MTM-CM3000-MSP sensors are used to send and receive radio signals from the sensor to the PC. These sensors are based on an open-source TelosB/Tmote Sky platform, designed and developed by the University of California, Berkeley.

TelosB sensor uses the IEEE 802.15.4 wireless structure and the embedded sensors can measure temperature, relative humidity, and light. In CM3000, the USB connector is replaced with an ERNI connector that is compatible with interface modules. Also, the Hirose 51-pin connector makes this more versatile as it can be attachable to any sensor board family, and the coverage area is increased using SMA design by a 5dBi external antenna 66 . These components can be used for a variety of applications such as low-power Wireless Sensor Networks (WSN) platforms, network monitoring, and environment monitoring systems.

MTS-EX1000 sensor board is used for the amplification of the voltage/current value from the accelerometer. The EX1000 is an attachable board that supports the CMXXXX series of wireless sensors network Motes (Hirose 51-pin connector). The basic functionality of EX1000 is to connect the external sensors with CMXX00 communication modules to enhance the mote’s I/O capability and support different kinds of sensors based on the sensor type and its output signal. ADXL-345 Tri-accelerometer sensor is used to calculate body motion along x, y, and z-axis relative to gravity. It is a small, thin, low-power, 3-axis accelerometer that calculates high resolution (13-bit) measurements at up to ±16g. Its digital output, in 16-bit twos complement format, is accessible through either an SPI (3- or 4-wire) or I2C digital interface. A customized main circuit board is used having a programmed IC, registers, and transistors. Its basic functionality is to convert the digital data, accessed through the ADXL-345 sensor, into analog form and send it to MTS1000.

Result and discussion

The proposed generalized and ANRS is evaluated against different data sets taken from the machine learning data repository, at the University of California at Irvine. In addition to these common data sets, a real-time Testbed for Parkinson’s patients is also used to evaluate the proposed scheme. The hybrid data of 500 people was collected using the Testbed for Parkinson’s patients including 10 Parkinson’s patients, 20 people have abnormal and uncontrolled hand movements, and the rest of the samples were taken approximating the hand movements of Parkinson’s patients. The objective of this evaluation is to compare the accuracy rate of the proposed scheme with CART, k NN, and SVM having both simple and complex datasets containing numerical and hybrid features respectively. The results also demonstrate the selection of radius r for dynamically calculating the threshold value.

Table  3 provides the details of the datasets used for the evaluation of the proposed scheme including the training and test ratio used for evaluation in addition to data type, total number of instances, total feature, a feature considered for evaluation, and number of classes. The hybrid datasets are also selected to evaluate to performance of the proposed scheme against the hybrid feature space without discretization preventing information loss.

The accuracy of the NRS is greatly dependent on the threshold value. Most of the existing techniques do not dynamically adapt the threshold \(\delta \) value for different hybrid datasets. This results in the variant of NRS suitable for specific datasets with different threshold values. A specific threshold value may produce better results for one dataset and poor results for others requiring a more generic threshold value catering to different datasets with optimal results. The proposed scheme introduces an adaptable threshold calculation mechanism to achieve optimal results regardless of the datasets under evaluation. The radius value plays a pivotal role in forming a neighborhood, as the threshold values consider both the local and global information of the NRS to calculate neighborhood approximation space. Table  4 shows the accuracy rate having different values of the radius of the NRS. The proposed threshold mechanism provides better results for all datasets if the value of the radius is 0.002. Results also show that assigning no weight to the radius produces poor results, as it will then only consider the local information for the approximation space. Selecting other weights for radius may produce better results for one dataset but not for all datasets.

Table  5 presents the comparative analysis of the proposed scheme with k NN, Naive Bayes, and C45. The results show that the proposed scheme performs well against other well-known techniques for both the categorical and numerical features space. Naive Bayes and C45 also result in information loss, as these techniques cannot process the hybrid data. So the proposed scheme handles the hybrid data without compromising on the information completeness producing acceptable results. K-fold cross-validation is used to measure the accuracy of the proposed scheme. Each dataset is divided into 10 subsets to use one of the K subsets as the test set and the other K-1 subsets as training sets. Then the average accuracy of all K trials is computed with the advantage of having results regardless of the dataset division.

Conclusion and future work

This work evaluates the existing NRS-based scheme for handling hybrid data sets i.e. numerical and categorical features. The comparative analysis of existing NRS-based schemes shows that there is a need for a generic NRS-based approach to adapt the threshold selection forming neighborhood approximation space. A generalized and ANRS-based scheme is proposed to handle both the categorical and numerical features avoiding information loss and lack of practical meanings. The proposed scheme uses a Euclidean and Levenshtein distance to calculate the upper and lower approximation of NRS for numerical and categorical features respectively. Euclidean and Levenshtein distances have been modified to handle the impact of outliers in calculating the approximation spaces. The proposed scheme defines an adaptive threshold mechanism for calculating neighborhood approximation space regardless of the data set under consideration. A Testbed is developed for real-time behavioral analysis of Parkinson’s patients evaluating the effectiveness of the proposed scheme. The evaluation results show that the proposed scheme provides better accuracy than k NN, C4.5, and Naive Bayes for both the categorical and numerical feature space achieving 95% accuracy on the Parkinson’s dataset. The proposed scheme will be evaluated against the hybrid data set having more than two classes in future work. Additionally, in future work, we aim to explore the following areas; (i) conduct longitudinal studies to track the progression of Parkinson’s disease over time, allowing for a deeper understanding of how behavioral patterns evolve and how interventions may impact disease trajectory, (ii) explore the integration of additional data sources, such as genetic data, imaging studies, and environmental factors, to provide a more comprehensive understanding of Parkinson’s disease etiology and progression, (iii) validate our findings in larger and more diverse patient populations and investigate the feasibility of implementing our proposed approach in clinical settings to support healthcare providers in decision-making processes, (iv) investigate novel biomarkers or physiological signals that may provide additional insights into Parkinson’s disease progression and motor complications, potentially leading to the development of new diagnostic and monitoring tools, and (v) conduct patient-centered outcomes research to better understand the impact of Parkinson’s disease on patients’ quality of life, functional abilities, and overall well-being, with a focus on developing personalized treatment approaches.

Data availability

The datasets used in this study are publicly available at the following links:

Bupa 67 : https://doi.org/10.24432/C54G67 , Sonar 68 : https://doi.org/10.24432/C5T01Q , Mammographic Mass 69 : https://doi.org/10.24432/C53K6Z , Haberman’s Survival 70 : https://doi.org/10.24432/C5XK51 , Credit-g 71 : https://doi.org/10.24432/C5NC77 , Lymmography 73 : https://doi.org/10.24432/C54598 , Splice 74 : https://doi.org/10.24432/C5M888 , Optdigits 75 : https://doi.org/10.24432/C50P49 , Pendigits 76 : https://doi.org/10.1137/1.9781611972825.9 , Pageblocks 77 : https://doi.org/10.24432/C5J590 , Statlog 78 : https://doi.org/10.24432/C55887 , Magic04 79 : https://doi.org/10.1609/aaai.v29i1.9277 .

Gaber, M. M. Scientific Data Mining and Knowledge Discovery Vol. 1 (Springer, 2009).

Google Scholar  

Hajirahimi, Z. & Khashei, M. Weighting approaches in data mining and knowledge discovery: A review. Neural Process. Lett. 55 , 10393–10438 (2023).

Article   Google Scholar  

Kantardzic, M. Data Mining: Concepts, Models, Methods, and Algorithms (Wiley, 2011).

Book   Google Scholar  

Shu, X. & Ye, Y. Knowledge discovery: Methods from data mining and machine learning. Soc. Sci. Res. 110 , 102817 (2023).

Article   PubMed   Google Scholar  

Tan, P.-N., Steinbach, M. & Kumar, V. Introduction to Data Mining (Pearson Education India, 2016).

Khan, S. & Shaheen, M. From data mining to wisdom mining. J. Inf. Sci. 49 , 952–975 (2023).

Engelbrecht, A. P. Computational Intelligence: An Introduction (Wiley, 2007).

Bhateja, V., Yang, X.-S., Lin, J.C.-W. & Das, R. Evolution in computational intelligence. In Evolution (Springer, 2023).

Wei, W., Liang, J. & Qian, Y. A comparative study of rough sets for hybrid data. Inf. Sci. 190 , 1–16 (2012).

Article   ADS   MathSciNet   Google Scholar  

Kumari, N. & Acharjya, D. Data classification using rough set and bioinspired computing in healthcare applications—An extensive review. Multimedia Tools Appl. 82 , 13479–13505 (2023).

Martinez, A. M. & Kak, A. C. PCA versus LDA. IEEE Trans. Pattern Anal. Mach. Intell. 23 , 228–233 (2001).

Brereton, R. G. Principal components analysis with several objects and variables. J. Chemom. 37 (4), e3408 (2023).

Article   CAS   Google Scholar  

De, R. K., Basak, J. & Pal, S. K. Neuro-fuzzy feature evaluation with theoretical analysis. Neural Netw. 12 , 1429–1455 (1999).

Talpur, N. et al. Deep neuro-fuzzy system application trends, challenges, and future perspectives: A systematic survey. Artif. Intell. Rev. 56 , 865–913 (2023).

Jang, J.-S.R., Sun, C.-T. & Mizutani, E. Neuro-fuzzy and soft computing—A computational approach to learning and machine intelligence [book review]. IEEE Trans. Autom. Control 42 , 1482–1484 (1997).

Ouifak, H. & Idri, A. Application of neuro-fuzzy ensembles across domains: A systematic review of the two last decades (2000–2022). Eng. Appl. Artif. Intell. 124 , 106582 (2023).

Jung, T. & Kim, J. A new support vector machine for categorical features. Expert Syst. Appl. 229 , 120449 (2023).

Hu, Q., Xie, Z. & Yu, D. Hybrid attribute reduction based on a novel fuzzy-rough model and information granulation. Pattern Recognit. 40 , 3509–3521 (2007).

Article   ADS   Google Scholar  

Wang, P., He, J. & Li, Z. Attribute reduction for hybrid data based on fuzzy rough iterative computation model. Inf. Sci. 632 , 555–575 (2023).

Yeung, D. S., Chen, D., Tsang, E. C., Lee, J. W. & Xizhao, W. On the generalization of fuzzy rough sets. IEEE Trans. Fuzzy Syst. 13 , 343–361 (2005).

Gao, L., Yao, B.-X. & Li, L.-Q. L-fuzzy generalized neighborhood system-based pessimistic l-fuzzy rough sets and its applications. Soft Comput. 27 , 7773–7788 (2023).

Bhatt, R. B. & Gopal, M. On fuzzy-rough sets approach to feature selection. Pattern Recognit. Lett. 26 , 965–975 (2005).

Dubois, D. & Prade, H. Putting fuzzy sets and rough sets together. Intell. Decis. Support 23 , 203–232 (1992).

Jensen, R. & Shen, Q. Fuzzy-rough sets for descriptive dimensionality reduction. In 2002 IEEE World Congress on Computational Intelligence. 2002 IEEE International Conference on Fuzzy Systems. FUZZ-IEEE’02. Proceedings (Cat. No. 02CH37291) , vol. 1, 29–34 (IEEE, 2002).

Pedrycz, W. & Vukovich, G. Feature analysis through information granulation and fuzzy sets. Pattern Recognit. 35 , 825–834 (2002).

Jensen, R. & Shen, Q. Fuzzy-rough sets assisted attribute selection. IEEE Trans. Fuzzy Syst. 15 , 73–89 (2007).

Shen, Q. & Jensen, R. Selecting informative features with fuzzy-rough sets and its application for complex systems monitoring. Pattern Recognit. 37 , 1351–1363 (2004).

Wang, X., Tsang, E. C., Zhao, S., Chen, D. & Yeung, D. S. Learning fuzzy rules from fuzzy samples based on rough set technique. Inf. Sci. 177 , 4493–4514 (2007).

Article   MathSciNet   Google Scholar  

Wei, W., Liang, J., Qian, Y. & Wang, F. An attribute reduction approach and its accelerated version for hybrid data. In 2009 8th IEEE International Conference on Cognitive Informatics , 167–173 (IEEE, 2009).

Yin, T., Chen, H., Li, T., Yuan, Z. & Luo, C. Robust feature selection using label enhancement and \(\beta \) -precision fuzzy rough sets for multilabel fuzzy decision system. Fuzzy Sets Syst. 461 , 108462 (2023).

Yin, T. et al. Exploiting feature multi-correlations for multilabel feature selection in robust multi-neighborhood fuzzy \(\beta \) covering space. Inf. Fusion 104 , 102150 (2024).

Yin, T. et al. A robust multilabel feature selection approach based on graph structure considering fuzzy dependency and feature interaction. IEEE Trans. Fuzzy Syst. 31 , 4516–4528. https://doi.org/10.1109/TFUZZ.2023.3287193 (2023).

Huang, W., She, Y., He, X. & Ding, W. Fuzzy rough sets-based incremental feature selection for hierarchical classification. IEEE Trans. Fuzzy Syst. https://doi.org/10.1109/TFUZZ.2023.3300913 (2023).

Dong, L., Wang, R. & Chen, D. Incremental feature selection with fuzzy rough sets for dynamic data sets. Fuzzy Sets Syst. 467 , 108503 (2023).

Chakraborty, M. K. & Samanta, P. Fuzzy sets and rough sets: A mathematical narrative. In Fuzzy, Rough and Intuitionistic Fuzzy Set Approaches for Data Handling: Theory and Applications , 1–21 (Springer, 2023).

Wang, Z., Chen, H., Yuan, Z. & Li, T. Fuzzy-rough hybrid dimensionality reduction. Fuzzy Sets Syst. 459 , 95–117 (2023).

Xue, Z.-A., Jing, M.-M., Li, Y.-X. & Zheng, Y. Variable precision multi-granulation covering rough intuitionistic fuzzy sets. Granul. Comput. 8 , 577–596 (2023).

Akram, M., Nawaz, H. S. & Deveci, M. Attribute reduction and information granulation in pythagorean fuzzy formal contexts. Expert Systems Appl. 222 , 119794 (2023).

Hu, M., Guo, Y., Chen, D., Tsang, E. C. & Zhang, Q. Attribute reduction based on neighborhood constrained fuzzy rough sets. Knowl. Based Syst. 274 , 110632 (2023).

Zhang, C., Ding, J., Zhan, J., Sangaiah, A. K. & Li, D. Fuzzy intelligence learning based on bounded rationality in IOMT systems: A case study in Parkinson’s disease. IEEE Trans. Comput. Soc. Syst. 10 , 1607–1621. https://doi.org/10.1109/TCSS.2022.3221933 (2023).

Zhang, C. & Zhang, J. Three-way group decisions with incomplete spherical fuzzy information for treating Parkinson’s disease using IOMT devices. Wireless Communications and Mobile Computing , vol. 2022 (2022).

Jain, P., Tiwari, A. K. & Som, T. Improving financial bankruptcy prediction using oversampling followed by fuzzy rough feature selection via evolutionary search. In Computational Management: Applications of Computational Intelligence in Business Management , 455–471 (Springer, 2021).

Shreevastava, S., Singh, S., Tiwari, A. & Som, T. Different classes ratio and Laplace summation operator based intuitionistic fuzzy rough attribute selection. Iran. J. Fuzzy Syst. 18 , 67–82 (2021).

MathSciNet   Google Scholar  

Shreevastava, S., Tiwari, A. & Som, T. Feature subset selection of semi-supervised data: an intuitionistic fuzzy-rough set-based concept. In Proceedings of International Ethical Hacking Conference 2018: eHaCON 2018, Kolkata, India , 303–315 (Springer, 2019).

Tiwari, A. K., Nath, A., Subbiah, K. & Shukla, K. K. Enhanced prediction for observed peptide count in protein mass spectrometry data by optimally balancing the training dataset. Int. J. Pattern Recognit. Artif. Intell. 31 , 1750040 (2017).

Jain, P., Tiwari, A. K. & Som, T. An intuitionistic fuzzy bireduct model and its application to cancer treatment. Comput. Ind. Eng. 168 , 108124 (2022).

Yin, T., Chen, H., Yuan, Z., Li, T. & Liu, K. Noise-resistant multilabel fuzzy neighborhood rough sets for feature subset selection. Inf. Sci. 621 , 200–226 (2023).

Sang, B., Chen, H., Yang, L., Li, T. & Xu, W. Incremental feature selection using a conditional entropy based on fuzzy dominance neighborhood rough sets. IEEE Trans. Fuzzy Syst. 30 , 1683–1697 (2021).

Xu, J., Meng, X., Qu, K., Sun, Y. & Hou, Q. Feature selection using relative dependency complement mutual information in fitting fuzzy rough set model. Appl. Intell. 53 , 18239–18262 (2023).

Jiang, H., Zhan, J. & Chen, D. Promethee ii method based on variable precision fuzzy rough sets with fuzzy neighborhoods. Artif. Intell. Rev. 54 , 1281–1319 (2021).

Qu, K., Xu, J., Han, Z. & Xu, S. Maximum relevance minimum redundancy-based feature selection using rough mutual information in adaptive neighborhood rough sets. Appl. Intell. 53 , 17727–17746 (2023).

Xu, J., Yuan, M. & Ma, Y. Feature selection using self-information and entropy-based uncertainty measure for fuzzy neighborhood rough set. Complex Intell. Syst. 8 , 287–305 (2022).

Xu, J., Shen, K. & Sun, L. Multi-label feature selection based on fuzzy neighborhood rough sets. Complex Intell. Syst. 8 , 2105–2129 (2022).

Sang, B. et al. Feature selection for dynamic interval-valued ordered data based on fuzzy dominance neighborhood rough set. Knowl. Based Syst. 227 , 107223 (2021).

Wu, W.-Z., Mi, J.-S. & Zhang, W.-X. Generalized fuzzy rough sets. Inf. Sci. 151 , 263–282 (2003).

Gogoi, P., Bhattacharyya, D. K. & Kalita, J. K. A rough set-based effective rule generation method for classification with an application in intrusion detection. Int. J. Secur. Netw. 8 , 61–71 (2013).

Grzymala-Busse, J. W. Knowledge acquisition under uncertainty—A rough set approach. J. Intell. Robot. Syst. 1 , 3–16 (1988).

Jing, S. & She, K. Heterogeneous attribute reduction in noisy system based on a generalized neighborhood rough sets model. World Acad. Sci. Eng. Technol. 75 , 1067–1072 (2011).

Zhu, X., Zhang, Y. & Zhu, Y. Intelligent fault diagnosis of rolling bearing based on kernel neighborhood rough sets and statistical features. J. Mech. Sci. Technol. 26 , 2649–2657 (2012).

Zhao, B.-T. & Jia, X.-F. Neighborhood covering rough set model of fuzzy decision system. Int. J. Comput. Sci. Issues 10 , 51 (2013).

Hou, M.-L. et al. Neighborhood rough set reduction-based gene selection and prioritization for gene expression profile analysis and molecular cancer classification. J Biomed Biotechnol. 2010 , 726413 (2010).

Article   PubMed   PubMed Central   Google Scholar  

He, M.-X. & Qiu, D.-D. A intrusion detection method based on neighborhood rough set. TELKOMNIKA Indones. J. Electr. Eng. 11 , 3736–3741 (2013).

ADS   Google Scholar  

Newman, D. J., Hettich, S., Blake, C. L. & Merz, C. UCI repository of machine learning databases (1998).

Aarsland, D. et al. Parkinson disease-associated cognitive impairment. Nat. Rev. Dis. Primers 7 , 47 (2021).

Lang, A. E. & Lozano, A. M. Parkinson’s disease. N. Engl. J. Med. 339 , 1130–1143 (1998).

Article   CAS   PubMed   Google Scholar  

Engin, M. et al. The classification of human tremor signals using artificial neural network. Expert Syst. Appl. 33 , 754–761 (2007).

Liver Disorders. UCI Machine Learning Repository. https://doi.org/10.24432/C54G67 (1990).

Sejnowski, T. & Gorman, R. Connectionist bench (sonar, mines vs. rocks). UCI Machine Learning Repository. https://doi.org/10.24432/C5T01Q

Elter, M. Mammographic Mass. UCI Machine Learning Repository. https://doi.org/10.24432/C53K6Z (2007).

Haberman, S. Haberman’s Survival. UCI Machine Learning Repository. https://doi.org/10.24432/C5XK51 (1999).

Hofmann, H. Statlog (German Credit Data). UCI Machine Learning Repository. https://doi.org/10.24432/C5NC77 (1994).

Kubat, M., Holte, R. C. & Matwin, S. Machine learning for the detection of oil spills in satellite radar images. Mach. Learn. 30 , 195–215 (1998).

Zwitter, M. & Soklic, M. Lymphography. UCI Machine Learning Repository. https://doi.org/10.24432/C54598 (1988).

Molecular Biology (Splice-junction Gene Sequences). UCI Machine Learning Repository. https://doi.org/10.24432/C5M888 (1992).

Alpaydin, E. & Kaynak, C. Optical Recognition of Handwritten Digits. UCI Machine Learning Repository. https://doi.org/10.24432/C50P49 (1998).

Schubert, E., Wojdanowski, R., Zimek, A. & Kriegel, H.-P. On evaluation of outlier rankings and outlier scores. In Proceedings of the 2012 SIAM International Conference on Data Mining , 1047–1058 (SIAM, 2012).

Malerba, D. Page Blocks Classification. UCI Machine Learning Repository. https://doi.org/10.24432/C5J590 (1995).

Srinivasan, A. Statlog (Landsat Satellite). UCI Machine Learning Repository. https://doi.org/10.24432/C55887 (1993).

Rossi, R. A. & Ahmed, N. K. The network data repository with interactive graph analytics and visualization. In AAAI (2015).

Download references

Acknowledgements

This research was funded by the European University of Atlantic.

Author information

Authors and affiliations.

Department of Computer Science, COMSATS University Islamabad, Lahore Campus, Lahore, 54000, Pakistan

Imran Raza, Muhammad Hasan Jamal, Rizwan Qureshi & Abdul Karim Shahid

Universidad Europea del Atlántico, Isabel Torres 21, 39011, Santander, Spain

Angel Olider Rojas Vistorte

Universidad Internacional Iberoamericana Campeche, 24560, Campeche, Mexico

Universidade Internacional do Cuanza, Cuito, Bié, Angola

Department of Information and Communication Engineering, Yeungnam University, Gyeongsan-si, Gyeongsangbuk-do, 38541, South Korea

Md Abdus Samad & Imran Ashraf

You can also search for this author in PubMed   Google Scholar

Contributions

Imran Raza: Conceptualization, Formal analysis, Writing—original draft; Muhammad Hasan Jamal: Conceptualization, Data curation, Writing—original draft; Rizwan Qureshi: Data curation, Formal analysis, Methodology; Abdul Karim Shahid: Project administration, Software, Visualization; Angel Olider Rojas Vistorte: Funding acquisition, Investigation, Project administration; Md Abdus Samad: Investigation, Software, Resources; Imran Ashraf: Supervision, Validation, Writing —review and editing. All authors reviewed the manuscript and approved it.

Corresponding authors

Correspondence to Md Abdus Samad or Imran Ashraf .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cite this article.

Raza, I., Jamal, M.H., Qureshi, R. et al. Adaptive neighborhood rough set model for hybrid data processing: a case study on Parkinson’s disease behavioral analysis. Sci Rep 14 , 7635 (2024). https://doi.org/10.1038/s41598-024-57547-4

Download citation

Received : 01 October 2023

Accepted : 19 March 2024

Published : 01 April 2024

DOI : https://doi.org/10.1038/s41598-024-57547-4

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

By submitting a comment you agree to abide by our Terms and Community Guidelines . If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Quick links

  • Explore articles by subject
  • Guide to authors
  • Editorial policies

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

the word case study meaning

institution icon

  • Philosophy East and West

A Leaky Boat Holding Wine: A Study of the Word-Meaning Debate in Wei-Jin Six Dynasties Period Thought by Jing Yuan (review)

  • University of Hawai'i Press
  • Volume 74, Number 2, April 2024
  • 10.1353/pew.2024.a925202
  • View Citation

Related Content

Additional Information

  • Buy Article for $16.00 (USD)

pdf

  • Buy Digital Article for $16.00 (USD)
  • Buy Complete Digital Issue for $29.00 (USD)

Project MUSE Mission

Project MUSE promotes the creation and dissemination of essential humanities and social science resources through collaboration with libraries, publishers, and scholars worldwide. Forged from a partnership between a university press and a library, Project MUSE is a trusted part of the academic and scholarly community it serves.

MUSE logo

2715 North Charles Street Baltimore, Maryland, USA 21218

+1 (410) 516-6989 [email protected]

©2024 Project MUSE. Produced by Johns Hopkins University Press in collaboration with The Sheridan Libraries.

Now and Always, The Trusted Content Your Research Requires

Project MUSE logo

Built on the Johns Hopkins University Campus

This website uses cookies to ensure you get the best experience on our website. Without cookies your experience may not be seamless.

Numbers, Facts and Trends Shaping Your World

Read our research on:

Full Topic List

Regions & Countries

  • Publications
  • Our Methods
  • Short Reads
  • Tools & Resources

Read Our Research On:

the word case study meaning

What It Means To Be Asian in America

The lived experiences and perspectives of asian americans in their own words.

Asians are the fastest growing racial and ethnic group in the United States. More than 24 million Americans in the U.S. trace their roots to more than 20 countries in East and Southeast Asia and the Indian subcontinent.

The majority of Asian Americans are immigrants, coming to understand what they left behind and building their lives in the United States. At the same time, there is a fast growing, U.S.-born generation of Asian Americans who are navigating their own connections to familial heritage and their own experiences growing up in the U.S.

In a new Pew Research Center analysis based on dozens of focus groups, Asian American participants described the challenges of navigating their own identity in a nation where the label “Asian” brings expectations about their origins, behavior and physical self. Read on to see, in their own words, what it means to be Asian in America.

  • Introduction

Table of Contents

This is how i view my identity, this is how others see and treat me, this is what it means to be home in america, about this project, methodological note, acknowledgments.

No single experience defines what it means to be Asian in the United States today. Instead, Asian Americans’ lived experiences are in part shaped by where they were born, how connected they are to their family’s ethnic origins, and how others – both Asians and non-Asians – see and engage with them in their daily lives. Yet despite diverse experiences, backgrounds and origins, shared experiences and common themes emerged when we asked: “What does it mean to be Asian in America?”

In the fall of 2021, Pew Research Center undertook the largest focus group study it had ever conducted – 66 focus groups with 264 total participants – to hear Asian Americans talk about their lived experiences in America. The focus groups were organized into 18 distinct Asian ethnic origin groups, fielded in 18 languages and moderated by members of their own ethnic groups. Because of the pandemic, the focus groups were conducted virtually, allowing us to recruit participants from all parts of the United States. This approach allowed us to hear a diverse set of voices – especially from less populous Asian ethnic groups whose views, attitudes and opinions are seldom presented in traditional polling. The approach also allowed us to explore the reasons behind people’s opinions and choices about what it means to belong in America, beyond the preset response options of a traditional survey.

The terms “Asian,” “Asians living in the United States” and “Asian American” are used interchangeably throughout this essay to refer to U.S. adults who self-identify as Asian, either alone or in combination with other races or Hispanic identity.

“The United States” and “the U.S.” are used interchangeably with “America” for variations in the writing.

Multiracial participants are those who indicate they are of two or more racial backgrounds (one of which is Asian). Multiethnic participants are those who indicate they are of two or more ethnicities, including those identified as Asian with Hispanic background.

U.S. born refers to people born in the 50 U.S. states or the District of Columbia, Puerto Rico, or other U.S. territories.

Immigrant refers to people who were not U.S. citizens at birth – in other words, those born outside the U.S., Puerto Rico or other U.S. territories to parents who were not U.S. citizens. The terms “immigrant,” “first generation” and “foreign born” are used interchangeably in this report.  

Second generation refers to people born in the 50 states or the District of Columbia with at least one first-generation, or immigrant, parent.

The pan-ethnic term “Asian American” describes the population of about 22 million people living in the United States who trace their roots to more than 20 countries in East and Southeast Asia and the Indian subcontinent. The term was popularized by U.S. student activists in the 1960s and was eventually adopted by the U.S. Census Bureau. However, the “Asian” label masks the diverse demographics and wide economic disparities across the largest national origin groups (such as Chinese, Indian, Filipino) and the less populous ones (such as Bhutanese, Hmong and Nepalese) living in America. It also hides the varied circumstances of groups immigrated to the U.S. and how they started their lives there. The population’s diversity often presents challenges . Conventional survey methods typically reflect the voices of larger groups without fully capturing the broad range of views, attitudes, life starting points and perspectives experienced by Asian Americans. They can also limit understanding of the shared experiences across this diverse population.

A chart listing the 18 ethnic origins included in Pew Research Center's 66 focus groups, and the composition of the focus groups by income and birth place.

Across all focus groups, some common findings emerged. Participants highlighted how the pan-ethnic “Asian” label used in the U.S. represented only one part of how they think of themselves. For example, recently arrived Asian immigrant participants told us they are drawn more to their ethnic identity than to the more general, U.S.-created pan-ethnic Asian American identity. Meanwhile, U.S.-born Asian participants shared how they identified, at times, as Asian but also, at other times, by their ethnic origin and as Americans.

Another common finding among focus group participants is the disconnect they noted between how they see themselves and how others view them. Sometimes this led to maltreatment of them or their families, especially at heightened moments in American history such as during Japanese incarceration during World War II, the aftermath of 9/11 and, more recently, the COVID-19 pandemic. Beyond these specific moments, many in the focus groups offered their own experiences that had revealed other people’s assumptions or misconceptions about their identity.

Another shared finding is the multiple ways in which participants take and express pride in their cultural and ethnic backgrounds while also feeling at home in America, celebrating and blending their unique cultural traditions and practices with those of other Americans.

This focus group project is part of a broader research agenda about Asians living in the United States. The findings presented here offer a small glimpse of what participants told us, in their own words, about how they identify themselves, how others see and treat them, and more generally, what it means to be Asian in America.

Illustrations by Jing Li

Publications from the Being Asian in America project

  • Read the data essay: What It Means to Be Asian in America
  • Watch the documentary: Being Asian in America
  • Explore the interactive: In Their Own Words: The Diverse Perspectives of Being Asian in America
  • View expanded interviews: Extended Interviews: Being Asian in America
  • About this research project: More on the Being Asian in America project
  • Q&A: Why and how Pew Research Center conducted 66 focus groups with Asian Americans

the word case study meaning

One of the topics covered in each focus group was how participants viewed their own racial or ethnic identity. Moderators asked them how they viewed themselves, and what experiences informed their views about their identity. These discussions not only highlighted differences in how participants thought about their own racial or ethnic background, but they also revealed how different settings can influence how they would choose to identify themselves. Across all focus groups, the general theme emerged that being Asian was only one part of how participants viewed themselves.

The pan-ethnic label ‘Asian’ is often used more in formal settings

the word case study meaning

“I think when I think of the Asian Americans, I think that we’re all unique and different. We come from different cultures and backgrounds. We come from unique stories, not just as a group, but just as individual humans.” Mali , documentary participant

Many participants described a complicated relationship with the pan-ethnic labels “Asian” or “Asian American.” For some, using the term was less of an active choice and more of an imposed one, with participants discussing the disconnect between how they would like to identify themselves and the available choices often found in formal settings. For example, an immigrant Pakistani woman remarked how she typically sees “Asian American” on forms, but not more specific options. Similarly, an immigrant Burmese woman described her experience of applying for jobs and having to identify as “Asian,” as opposed to identifying by her ethnic background, because no other options were available. These experiences highlight the challenges organizations like government agencies and employers have in developing surveys or forms that ask respondents about their identity. A common sentiment is one like this:

“I guess … I feel like I just kind of check off ‘Asian’ [for] an application or the test forms. That’s the only time I would identify as Asian. But Asian is too broad. Asia is a big continent. Yeah, I feel like it’s just too broad. To specify things, you’re Taiwanese American, that’s exactly where you came from.”

–U.S.-born woman of Taiwanese origin in early 20s

Smaller ethnic groups default to ‘Asian’ since their groups are less recognizable

Other participants shared how their experiences in explaining the geographic location and culture of their origin country led them to prefer “Asian” when talking about themselves with others. This theme was especially prominent among those belonging to smaller origin groups such as Bangladeshis and Bhutanese. A Lao participant remarked she would initially say “Asian American” because people might not be familiar with “Lao.”

“​​[When I fill out] forms, I select ‘Asian American,’ and that’s why I consider myself as an Asian American. [It is difficult to identify as] Nepali American [since] there are no such options in forms. That’s why, Asian American is fine to me.”

–Immigrant woman of Nepalese origin in late 20s

“Coming to a big country like [the United States], when people ask where we are from … there are some people who have no idea about Bhutan, so we end up introducing ourselves as being Asian.”

–Immigrant woman of Bhutanese origin in late 40s

But for many, ‘Asian’ as a label or identity just doesn’t fit

Many participants felt that neither “Asian” nor “Asian American” truly captures how they view themselves and their identity. They argue that these labels are too broad or too ambiguous, as there are so many different groups included within these labels. For example, a U.S.-born Pakistani man remarked on how “Asian” lumps many groups together – that the term is not limited to South Asian groups such as Indian and Pakistani, but also includes East Asian groups. Similarly, an immigrant Nepalese man described how “Asian” often means Chinese for many Americans. A Filipino woman summed it up this way:

“Now I consider myself to be both Filipino and Asian American, but growing up in [Southern California] … I didn’t start to identify as Asian American until college because in [the Los Angeles suburb where I lived], it’s a big mix of everything – Black, Latino, Pacific Islander and Asian … when I would go into spaces where there were a lot of other Asians, especially East Asians, I didn’t feel like I belonged. … In media, right, like people still associate Asian with being East Asian.”

–U.S.-born woman of Filipino origin in mid-20s

Participants also noted they have encountered confusion or the tendency for others to view Asian Americans as people from mostly East Asian countries, such as China, Japan and Korea. For some, this confusion even extends to interactions with other Asian American groups. A Pakistani man remarked on how he rarely finds Pakistani or Indian brands when he visits Asian stores. Instead, he recalled mostly finding Vietnamese, Korean and Chinese items.

Among participants of South Asian descent, some identified with the label “South Asian” more than just “Asian.” There were other nuances, too, when it comes to the labels people choose. Some Indian participants, for example, said people sometimes group them with Native Americans who are also referred to as Indians in the United States. This Indian woman shared her experience at school:

“I love South Asian or ‘Desi’ only because up until recently … it’s fairly new to say South Asian. I’ve always said ‘Desi’ because growing up … I’ve had to say I’m the red dot Indian, not the feather Indian. So annoying, you know? … Always a distinction that I’ve had to make.”

–U.S.-born woman of Indian origin in late 20s

Participants with multiethnic or multiracial backgrounds described their own unique experiences with their identity. Rather than choosing one racial or ethnic group over the other, some participants described identifying with both groups, since this more accurately describes how they see themselves. In some cases, this choice reflected the history of the Asian diaspora. For example, an immigrant Cambodian man described being both Khmer/Cambodian and Chinese, since his grandparents came from China. Some other participants recalled going through an “identity crisis” as they navigated between multiple identities. As one woman explained:

“I would say I went through an identity crisis. … It’s because of being multicultural. … There’s also French in the mix within my family, too. Because I don’t identify, speak or understand the language, I really can’t connect to the French roots … I’m in between like Cambodian and Thai, and then Chinese and then French … I finally lumped it up. I’m just an Asian American and proud of all my roots.”

–U.S.-born woman of Cambodian origin in mid-30s

In other cases, the choice reflected U.S. patterns of intermarriage. Asian newlyweds have the highest intermarriage rate of any racial or ethnic group in the country. One Japanese-origin man with Hispanic roots noted:

“So I would like to see myself as a Hispanic Asian American. I want to say Hispanic first because I have more of my mom’s culture in me than my dad’s culture. In fact, I actually have more American culture than my dad’s culture for what I do normally. So I guess, Hispanic American Asian.”

–U.S.-born man of Hispanic and Japanese origin in early 40s

Other identities beyond race or ethnicity are also important

Focus group participants also talked about their identity beyond the racial or ethnic dimension. For example, one Chinese woman noted that the best term to describe her would be “immigrant.” Faith and religious ties were also important to some. One immigrant participant talked about his love of Pakistani values and how religion is intermingled into Pakistani culture. Another woman explained:

“[Japanese language and culture] are very important to me and ingrained in me because they were always part of my life, and I felt them when I was growing up. Even the word itadakimasu reflects Japanese culture or the tradition. Shinto religion is a part of the culture. They are part of my identity, and they are very important to me.”

–Immigrant woman of Japanese origin in mid-30s

For some, gender is another important aspect of identity. One Korean participant emphasized that being a woman is an important part of her identity. For others, sexual orientation is an essential part of their overall identity. One U.S.-born Filipino participant described herself as “queer Asian American.” Another participant put it this way:

“I belong to the [LGBTQ] community … before, what we only know is gay and lesbian. We don’t know about being queer, nonbinary. [Here], my horizon of knowing what genders and gender roles is also expanded … in the Philippines, if you’ll be with same sex, you’re considered gay or lesbian. But here … what’s happening is so broad, on how you identify yourself.”

–Immigrant woman of Filipino origin in early 20s

Immigrant identity is tied to their ethnic heritage

A chart showing how participants in the focus groups described the differences between race-centered and ethnicity-centered identities.

Participants born outside the United States tended to link their identity with their ethnic heritage. Some felt strongly connected with their ethnic ties due to their citizenship status. For others, the lack of permanent residency or citizenship meant they have stronger ties to their ethnicity and birthplace. And in some cases, participants said they held on to their ethnic identity even after they became U.S. citizens. One woman emphasized that she will always be Taiwanese because she was born there, despite now living in the U.S.

For other participants, family origin played a central role in their identity, regardless of their status in the U.S. According to some of them, this attitude was heavily influenced by their memories and experiences in early childhood when they were still living in their countries of origin. These influences are so profound that even after decades of living in the U.S., some still feel the strong connection to their ethnic roots. And those with U.S.-born children talked about sending their kids to special educational programs in the U.S. to learn about their ethnic heritage.

“Yes, as for me, I hold that I am Khmer because our nationality cannot be deleted, our identity is Khmer as I hold that I am Khmer … so I try, even [with] my children today, I try to learn Khmer through Zoom through the so-called Khmer Parent Association.”

–Immigrant man of Cambodian origin in late 50s

Navigating life in America is an adjustment

Many participants pointed to cultural differences they have noticed between their ethnic culture and U.S. culture. One of the most distinct differences is in food. For some participants, their strong attachment to the unique dishes of their families and their countries of origin helps them maintain strong ties to their ethnic identity. One Sri Lankan participant shared that her roots are still in Sri Lanka, since she still follows Sri Lankan traditions in the U.S. such as preparing kiribath (rice with coconut milk) and celebrating Ramadan.

For other participants, interactions in social settings with those outside their own ethnic group circles highlighted cultural differences. One Bangladeshi woman talked about how Bengalis share personal stories and challenges with each other, while others in the U.S. like to have “small talk” about TV series or clothes.

Many immigrants in the focus groups have found it is easier to socialize when they are around others belonging to their ethnicity. When interacting with others who don’t share the same ethnicity, participants noted they must be more self-aware about cultural differences to avoid making mistakes in social interactions. Here, participants described the importance of learning to “fit in,” to avoid feeling left out or excluded. One Korean woman said:

“Every time I go to a party, I feel unwelcome. … In Korea, when I invite guests to my house and one person sits without talking, I come over and talk and treat them as a host. But in the United States, I have to go and mingle. I hate mingling so much. I have to talk and keep going through unimportant stories. In Korea, I am assigned to a dinner or gathering. I have a party with a sense of security. In America, I have nowhere to sit, and I don’t know where to go and who to talk to.”

–Immigrant woman of Korean origin in mid-40s

And a Bhutanese immigrant explained:

“In my case, I am not an American. I consider myself a Bhutanese. … I am a Bhutanese because I do not know American culture to consider myself as an American. It is very difficult to understand the sense of humor in America. So, we are pure Bhutanese in America.”

–Immigrant man of Bhutanese origin in early 40s

Language was also a key aspect of identity for the participants. Many immigrants in the focus groups said they speak a language other than English at home and in their daily lives. One Vietnamese man considered himself Vietnamese since his Vietnamese is better than his English. Others emphasized their English skills. A Bangladeshi participant felt that she was more accepted in the workplace when she does more “American” things and speaks fluent English, rather than sharing things from Bangladeshi culture. She felt that others in her workplace correlate her English fluency with her ability to do her job. For others born in the U.S., the language they speak at home influences their connection to their ethnic roots.

“Now if I go to my work and do show my Bengali culture and Asian culture, they are not going to take anything out of it. So, basically, I have to show something that they are interested in. I have to show that I am American, [that] I can speak English fluently. I can do whatever you give me as a responsibility. So, in those cases I can’t show anything about my culture.”

–Immigrant woman of Bangladeshi origin in late 20s

“Being bi-ethnic and tri-cultural creates so many unique dynamics, and … one of the dynamics has to do with … what it is to be Americanized. … One of the things that played a role into how I associate the identity is language. Now, my father never spoke Spanish to me … because he wanted me to develop a fluency in English, because for him, he struggled with English. What happened was three out of the four people that raised me were Khmer … they spoke to me in Khmer. We’d eat breakfast, lunch and dinner speaking Khmer. We’d go to the temple in Khmer with the language and we’d also watch videos and movies in Khmer. … Looking into why I strongly identify with the heritage, one of the reasons is [that] speaking that language connects to the home I used to have [as my families have passed away].”

–U.S.-born man of Cambodian origin in early 30s

Balancing between individualistic and collective thinking

For some immigrant participants, the main differences between themselves and others who are seen as “truly American” were less about cultural differences, or how people behave, and more about differences in “mindset,” or how people think . Those who identified strongly with their ethnicity discussed how their way of thinking is different from a “typical American.” To some, the “American mentality” is more individualistic, with less judgment on what one should do or how they should act . One immigrant Japanese man, for example, talked about how other Japanese-origin co-workers in the U.S. would work without taking breaks because it’s culturally inconsiderate to take a break while others continued working. However, he would speak up for himself and other workers when they are not taking any work breaks. He attributed this to his “American” way of thinking, which encourages people to stand up for themselves.

Some U.S.-born participants who grew up in an immigrant family described the cultural clashes that happened between themselves and their immigrant parents. Participants talked about how the second generation (children of immigrant parents) struggles to pursue their own dreams while still living up to the traditional expectations of their immigrant parents.

“I feel like one of the biggest things I’ve seen, just like [my] Asian American friends overall, is the kind of family-individualistic clash … like wanting to do your own thing is like, is kind of instilled in you as an American, like go and … follow your dream. But then you just grow up with such a sense of like also wanting to be there for your family and to live up to those expectations, and I feel like that’s something that’s very pronounced in Asian cultures.”

–U.S.-born man of Indian origin in mid-20s

Discussions also highlighted differences about gender roles between growing up in America compared with elsewhere.

“As a woman or being a girl, because of your gender, you have to keep your mouth shut [and] wait so that they call on you for you to speak up. … I do respect our elders and I do respect hearing their guidance but I also want them to learn to hear from the younger person … because we have things to share that they might not know and that [are] important … so I like to challenge gender roles or traditional roles because it is something that [because] I was born and raised here [in America], I learn that we all have the equal rights to be able to speak and share our thoughts and ideas.”

U.S. born have mixed ties to their family’s heritage

the word case study meaning

“I think being Hmong is somewhat of being free, but being free of others’ perceptions of you or of others’ attempts to assimilate you or attempts to put pressure on you. I feel like being Hmong is to resist, really.” Pa Houa , documentary participant

How U.S.-born participants identify themselves depends on their familiarity with their own heritage, whom they are talking with, where they are when asked about their identity and what the answer is used for. Some mentioned that they have stronger ethnic ties because they are very familiar with their family’s ethnic heritage. Others talked about how their eating habits and preferred dishes made them feel closer to their ethnic identity. For example, one Korean participant shared his journey of getting closer to his Korean heritage because of Korean food and customs. When some participants shared their reasons for feeling closer to their ethnic identity, they also expressed a strong sense of pride with their unique cultural and ethnic heritage.

“I definitely consider myself Japanese American. I mean I’m Japanese and American. Really, ever since I’ve grown up, I’ve really admired Japanese culture. I grew up watching a lot of anime and Japanese black and white films. Just learning about [it], I would hear about Japanese stuff from my grandparents … myself, and my family having blended Japanese culture and American culture together.”

–U.S.-born man of Japanese origin in late 20s

Meanwhile, participants who were not familiar with their family’s heritage showed less connection with their ethnic ties. One U.S.-born woman said she has a hard time calling herself Cambodian, as she is “not close to the Cambodian community.” Participants with stronger ethnic ties talked about relating to their specific ethnic group more than the broader Asian group. Another woman noted that being Vietnamese is “more specific and unique than just being Asian” and said that she didn’t feel she belonged with other Asians. Some participants also disliked being seen as or called “Asian,” in part because they want to distinguish themselves from other Asian groups. For example, one Taiwanese woman introduces herself as Taiwanese when she can, because she had frequently been seen as Chinese.

Some in the focus groups described how their views of their own identities shifted as they grew older. For example, some U.S.-born and immigrant participants who came to the U.S. at younger ages described how their experiences in high school and the need to “fit in” were important in shaping their own identities. A Chinese woman put it this way:

“So basically, all I know is that I was born in the United States. Again, when I came back, I didn’t feel any barrier with my other friends who are White or Black. … Then I got a little confused in high school when I had trouble self-identifying if I am Asian, Chinese American, like who am I. … Should I completely immerse myself in the American culture? Should I also keep my Chinese identity and stuff like that? So yeah, that was like the middle of that mist. Now, I’m pretty clear about myself. I think I am Chinese American, Asian American, whatever people want.”

–U.S.-born woman of Chinese origin in early 20s

Identity is influenced by birthplace

the word case study meaning

“I identified myself first and foremost as American. Even on the forms that you fill out that says, you know, ‘Asian’ or ‘Chinese’ or ‘other,’ I would check the ‘other’ box, and I would put ‘American Chinese’ instead of ‘Chinese American.’” Brent , documentary participant

When talking about what it means to be “American,” participants offered their own definitions. For some, “American” is associated with acquiring a distinct identity alongside their ethnic or racial backgrounds, rather than replacing them. One Indian participant put it this way:

“I would also say [that I am] Indian American just because I find myself always bouncing between the two … it’s not even like dual identity, it just is one whole identity for me, like there’s not this separation. … I’m doing [both] Indian things [and] American things. … They use that term like ABCD … ‘American Born Confused Desi’ … I don’t feel that way anymore, although there are those moments … but I would say [that I am] Indian American for sure.”

–U.S.-born woman of Indian origin in early 30s

Meanwhile, some U.S.-born participants view being American as central to their identity while also valuing the culture of their family’s heritage.

Many immigrant participants associated the term “American” with immigration status or citizenship. One Taiwanese woman said she can’t call herself American since she doesn’t have a U.S. passport. Notably, U.S. citizenship is an important milestone for many immigrant participants, giving them a stronger sense of belonging and ultimately calling themselves American. A Bangladeshi participant shared that she hasn’t received U.S. citizenship yet, and she would call herself American after she receives her U.S. passport.

Other participants gave an even narrower definition, saying only those born and raised in the United States are truly American. One Taiwanese woman mentioned that her son would be American since he was born, raised and educated in the U.S. She added that while she has U.S. citizenship, she didn’t consider herself American since she didn’t grow up in the U.S. This narrower definition has implications for belonging. Some immigrants in the groups said they could never become truly American since the way they express themselves is so different from those who were born and raised in the U.S. A Japanese woman pointed out that Japanese people “are still very intimidated by authorities,” while those born and raised in America give their opinions without hesitation.

“As soon as I arrived, I called myself a Burmese immigrant. I had a green card, but I still wasn’t an American citizen. … Now I have become a U.S. citizen, so now I am a Burmese American.”

–Immigrant man of Burmese origin in mid-30s

“Since I was born … and raised here, I kind of always view myself as American first who just happened to be Asian or Chinese. So I actually don’t like the term Chinese American or Asian American. I’m American Asian or American Chinese. I view myself as American first.”

–U.S.-born man of Chinese origin in early 60s

“[I used to think of myself as] Filipino, but recently I started saying ‘Filipino American’ because I got [U.S.] citizenship. And it just sounds weird to say Filipino American, but I’m trying to … I want to accept it. I feel like it’s now marry-able to my identity.”

–Immigrant woman of Filipino origin in early 30s

For others, American identity is about the process of ‘becoming’ culturally American

A Venn diagram showing how participants in the focus group study described their racial or ethnic identity overlaps with their American identity

Immigrant participants also emphasized how their experiences and time living in America inform their views of being an “American.” As a result, some started to see themselves as Americans after spending more than a decade in the U.S. One Taiwanese man considered himself an American since he knows more about the U.S. than Taiwan after living in the U.S. for over 52 years.

But for other immigrant participants, the process of “becoming” American is not about how long they have lived in the U.S., but rather how familiar they are with American culture and their ability to speak English with little to no accent. This is especially true for those whose first language is not English, as learning and speaking it without an accent can be a big challenge for some. One Bangladeshi participant shared that his pronunciation of “hot water” was very different from American English, resulting in confusions in communication. By contrast, those who were more confident in their English skills felt they can better understand American culture and values as a result, leading them to a stronger connection with an American identity.

“[My friends and family tease me for being Americanized when I go back to Japan.] I think I seem a little different to people who live in Japan. I don’t think they mean anything bad, and they [were] just joking, because I already know that I seem a little different to people who live in Japan.”

–Immigrant man of Japanese origin in mid-40s

“I value my Hmong culture, and language, and ethnicity, but I also do acknowledge, again, that I was born here in America and I’m grateful that I was born here, and I was given opportunities that my parents weren’t given opportunities for.”

–U.S.-born woman of Hmong origin in early 30s

the word case study meaning

During the focus group discussions about identity, a recurring theme emerged about the difference between how participants saw themselves and how others see them. When asked to elaborate on their experiences and their points of view, some participants shared experiences they had with people misidentifying their race or ethnicity. Others talked about their frustration with being labeled the “model minority.” In all these discussions, participants shed light on the negative impacts that mistaken assumptions and labels had on their lives.

All people see is ‘Asian’

For many, interactions with others (non-Asians and Asians alike) often required explaining their backgrounds, reacting to stereotypes, and for those from smaller origin groups in particular, correcting the misconception that being “Asian” means you come from one of the larger Asian ethnic groups. Several participants remarked that in their own experiences, when others think about Asians, they tend to think of someone who is Chinese. As one immigrant Filipino woman put it, “Interacting with [non-Asians in the U.S.], it’s hard. … Well, first, I look Spanish. I mean, I don’t look Asian, so would you guess – it’s like they have a vision of what an Asian [should] look like.” Similarly, an immigrant Indonesian man remarked how Americans tended to see Asians primarily through their physical features, which not all Asian groups share.

Several participants also described how the tendency to view Asians as a monolithic group can be even more common in the wake of the COVID-19 pandemic.

“The first [thing people think of me as] is just Chinese. ‘You guys are just Chinese.’ I’m not the only one who felt [this] after the COVID-19 outbreak. ‘Whether you’re Japanese, Korean, or Southeast Asian, you’re just Chinese [to Americans]. I should avoid you.’ I’ve felt this way before, but I think I’ve felt it a bit more after the COVID-19 outbreak.”

–Immigrant woman of Korean origin in early 30s

At the same time, other participants described their own experiences trying to convince others that they are Asian or Asian American. This was a common experience among Southeast Asian participants.

“I have to convince people I’m Asian, not Middle Eastern. … If you type in Asian or you say Asian, most people associate it with Chinese food, Japanese food, karate, and like all these things but then they don’t associate it with you.”

–U.S.-born man of Pakistani origin in early 30s

The model minority myth and its impact

the word case study meaning

“I’ve never really done the best academically, compared to all my other Asian peers too. I never really excelled. I wasn’t in honors. … Those stereotypes, I think really [have] taken a toll on my self-esteem.” Diane , documentary participant

Across focus groups, immigrant and U.S.-born participants described the challenges of the seemingly positive stereotypes of Asians as intelligent, gifted in technical roles and hardworking. Participants often referred to this as the “model minority myth.”

The label “model minority” was coined in the 1960s and has been used to characterize Asian Americans as financially and educationally successful and hardworking when compared with other groups. However, for many Asians living in the United States, these characterizations do not align with their lived experiences or reflect their socioeconomic backgrounds. Indeed, among Asian origin groups in the U.S., there are wide differences in economic and social experiences. 

Academic research on the model minority myth has pointed to its impact beyond Asian Americans and towards other racial and ethnic groups, especially Black Americans, in the U.S. Some argue that the model minority myth has been used to justify policies that overlook the historical circumstances and impacts of colonialism, slavery, discrimination and segregation on other non-White racial and ethnic groups.

Many participants noted ways in which the model minority myth has been harmful. For some, expectations based on the myth didn’t match their own experiences of coming from impoverished communities. Some also recalled experiences at school when they struggled to meet their teachers’ expectations in math and science.

“As an Asian person, I feel like there’s that stereotype that Asian students are high achievers academically. They’re good at math and science. … I was a pretty mediocre student, and math and science were actually my weakest subjects, so I feel like it’s either way you lose. Teachers expect you to fit a certain stereotype and if you’re not, then you’re a disappointment, but at the same time, even if you are good at math and science, that just means that you’re fitting a stereotype. It’s [actually] your own achievement, but your teachers might think, ‘Oh, it’s because they’re Asian,’ and that diminishes your achievement.”

–U.S.-born woman of Korean origin in late 20s

Some participants felt that even when being Asian worked in their favor in the job market, they encountered stereotypes that “Asians can do quality work with less compensation” or that “Asians would not complain about anything at work.”

“There is a joke from foreigners and even Asian Americans that says, ‘No matter what you do, Asians always do the best.’ You need to get A, not just B-plus. Otherwise, you’ll be a disgrace to the family. … Even Silicon Valley hires Asian because [an] Asian’s wage is cheaper but [they] can work better. When [work] visa overflow happens, they hire Asians like Chinese and Indian to work in IT fields because we are good at this and do not complain about anything.”

–Immigrant man of Thai origin in early 40s

Others expressed frustration that people were placing them in the model minority box. One Indian woman put it this way:

“Indian people and Asian people, like … our parents or grandparents are the ones who immigrated here … against all odds. … A lot of Indian and Asian people have succeeded and have done really well for themselves because they’ve worked themselves to the bone. So now the expectations [of] the newer generations who were born here are incredibly unrealistic and high. And you get that not only from your family and the Indian community, but you’re also getting it from all of the American people around you, expecting you to be … insanely good at math, play an instrument, you know how to do this, you know how to do that, but it’s not true. And it’s just living with those expectations, it’s difficult.”

–U.S.-born woman of Indian origin in early 20s

Whether U.S. born or immigrants, Asians are often seen by others as foreigners

the word case study meaning

“Being only not quite 10 years old, it was kind of exciting to ride on a bus to go someplace. But when we went to Pomona, the assembly center, we were stuck in one of the stalls they used for the animals.” Tokiko , documentary participant

Across all focus groups, participants highlighted a common question they are asked in America when meeting people for the first time: “Where are you really from?” For participants, this question implied that people think they are “foreigners,” even though they may be longtime residents or citizens of the United States or were born in the country. One man of Vietnamese origin shared his experience with strangers who assumed that he and his friends are North Korean. Perhaps even more hurtful, participants mentioned that this meant people had a preconceived notion of what an “American” is supposed to look like, sound like or act like. One Chinese woman said that White Americans treated people like herself as outsiders based on her skin color and appearance, even though she was raised in the U.S.

Many focus group participants also acknowledged the common stereotype of treating Asians as “forever foreigners.” Some immigrant participants said they felt exhausted from constantly being asked this question by people even when they speak perfect English with no accent. During the discussion, a Korean immigrant man recalled that someone had said to him, “You speak English well, but where are you from?” One Filipino participant shared her experience during the first six months in the U.S.:

“You know, I spoke English fine. But there were certain things that, you know, people constantly questioning you like, oh, where are you from? When did you come here? You know, just asking about your experience to the point where … you become fed up with it after a while.”

–Immigrant woman of Filipino origin in mid-30s

U.S.-born participants also talked about experiences when others asked where they are from. Many shared that they would not talk about their ethnic origin right away when answering such a question because it often led to misunderstandings and assumptions that they are immigrants.

“I always get that question of, you know, ‘Where are you from?’ and I’m like, ‘I’m from America.’ And then they’re like, ‘No. Where are you from-from ?’ and I’m like, ‘Yeah, my family is from Pakistan,’ so it’s like I always had like that dual identity even though it’s never attached to me because I am like, of Pakistani descent.”

–U.S.-born man of Pakistani origin in early 20s

One Korean woman born in the U.S. said that once people know she is Korean, they ask even more offensive questions such as “Are you from North or South Korea?” or “Do you still eat dogs?”

In a similar situation, this U.S.-born Indian woman shared her responses:

“I find that there’s a, ‘So but where are you from?’ Like even in professional settings when they feel comfortable enough to ask you. ‘So – so where are you from?’ ‘Oh, I was born in [names city], Colorado. Like at [the hospital], down the street.’ ‘No, but like where are you from?’ ‘My mother’s womb?’”

–U.S.-born woman of Indian origin in early 40s

Ignorance and misinformation about Asian identity can lead to contentious encounters

the word case study meaning

“I have dealt with kids who just gave up on their Sikh identity, cut their hair and groomed their beard and everything. They just wanted to fit in and not have to deal with it, especially [those] who are victim or bullied in any incident.” Surinder , documentary participant

In some cases, ignorance and misinformation about Asians in the U.S. lead to inappropriate comments or questions and uncomfortable or dangerous situations. Participants shared their frustration when others asked about their country of origin, and they then had to explain their identity or correct misunderstandings or stereotypes about their background. At other times, some participants faced ignorant comments about their ethnicity, which sometimes led to more contentious encounters. For example, some Indian or Pakistani participants talked about the attacks or verbal abuse they experienced from others blaming them for the 9/11 terrorist attacks. Others discussed the racial slurs directed toward them since the COVID-19 pandemic in 2020. Some Japanese participants recalled their families losing everything and being incarcerated during World War II and the long-term effect it had on their lives.

“I think like right now with the coronavirus, I think we’re just Chinese, Chinese American, well, just Asian American or Asians in general, you’re just going through the same struggles right now. Like everyone is just blaming whoever looks Asian about the virus. You don’t feel safe.”

–U.S.-born man of Chinese origin in early 30s

“At the beginning of the pandemic, a friend and I went to celebrate her birthday at a club and like these guys just kept calling us COVID.”

–U.S.-born woman of Korean origin in early 20s

“There [were] a lot of instances after 9/11. One day, somebody put a poster about 9/11 [in front of] my business. He was wearing a gun. … On the poster, it was written ‘you Arabs, go back to your country.’ And then someone came inside. He pointed his gun at me and said ‘Go back to your country.’”

–Immigrant man of Pakistani origin in mid-60s

“[My parents went through the] internment camps during World War II. And my dad, he was in high school, so he was – they were building the camps and then he was put into the Santa Anita horse track place, the stables there. And then they were sent – all the Japanese Americans were sent to different camps, right, during World War II and – in California. Yeah, and they lost everything, yeah.”

–U.S.-born woman of Japanese origin in mid-60s

the word case study meaning

As focus group participants contemplated their identity during the discussions, many talked about their sense of belonging in America. Although some felt frustrated with people misunderstanding their ethnic heritage, they didn’t take a negative view of life in America. Instead, many participants – both immigrant and U.S. born – took pride in their unique cultural and ethnic backgrounds. In these discussions, people gave their own definitions of America as a place with a diverse set of cultures, with their ethnic heritage being a part of it.

Taking pride in their unique cultures

the word case study meaning

“Being a Pakistani American, I’m proud. … Because I work hard, and I make true my dreams from here.” Shahid , documentary participant

Despite the challenges of adapting to life in America for immigrant participants or of navigating their dual cultural identity for U.S.-born ones, focus group participants called America their home. And while participants talked about their identities in different ways – ethnic identity, racial (Asian) identity, and being American – they take pride in their unique cultures. Many also expressed a strong sense of responsibility to give back or support their community, sharing their cultural heritage with others on their own terms.

“Right now it has been a little difficult. I think it has been for all Asians because of the COVID issue … but I’m glad that we’re all here [in America]. I think we should be proud to be here. I’m glad that our families have traveled here, and we can help make life better for communities, our families and ourselves. I think that’s really a wonderful thing. We can be those role models for a lot of the future, the younger folks. I hope that something I did in the last years will have impacted either my family, friends or students that I taught in other community things that I’ve done. So you hope that it helps someplace along the line.”

“I am very proud of my culture. … There is not a single Bengali at my workplace, but people know the name of my country. Maybe many years [later] – educated people know all about the country. So, I don’t have to explain that there is a small country next to India and Nepal. It’s beyond saying. People after all know Bangladesh. And there are so many Bengali present here as well. So, I am very proud to be a Bangladeshi.”

Where home is

When asked about the definition of home, some immigrant participants said home is where their families are located. Immigrants in the focus groups came to the United States by various paths, whether through work opportunities, reuniting with family or seeking a safe haven as refugees. Along their journey, some received support from family members, their local community or other individuals, while others overcame challenges by themselves. Either way, they take pride in establishing their home in America and can feel hurt when someone tells them to “go back to your country.” In response, one Laotian woman in her mid-40s said, “This is my home. My country. Go away.”

“If you ask me personally, I view my home as my house … then I would say my house is with my family because wherever I go, I cannot marry if I do not have my family so that is how I would answer.”

–Immigrant man of Hmong origin in late 30s

“[If somebody yelled at me ‘go back to your country’] I’d feel angry because this is my country! I live here. America is my country. I grew up here and worked here … I’d say, ‘This is my country! You go back to your country! … I will not go anywhere. This is my home. I will live here.’ That’s what I’d say.”

–Immigrant woman of Laotian origin in early 50s

‘American’ means to blend their unique cultural and ethnic heritage with that in the U.S.

the word case study meaning

“I want to teach my children two traditions – one American and one Vietnamese – so they can compare and choose for themselves the best route in life.” Helen , documentary participant (translated from Vietnamese)

Both U.S.-born and immigrant participants in the focus groups shared their experiences of navigating a dual cultural environment between their ethnic heritage and American culture. A common thread that emerged was that being Asian in America is a process of blending two or more identities as one.

“Yeah, I want to say that’s how I feel – because like thinking about it, I would call my dad Lao but I would call myself Laotian American because I think I’m a little more integrated in the American society and I’ve also been a little more Americanized, compared to my dad. So that’s how I would see it.”

–U.S.-born man of Laotian origin in late 20s

“I mean, Bangladeshi Americans who are here, we are carrying Bangladeshi culture, religion, food. I am also trying to be Americanized like the Americans. Regarding language, eating habits.”

–Immigrant man of Bangladeshi origin in mid-50s

“Just like there is Chinese American, Mexican American, Japanese American, Italian American, so there is Indian American. I don’t want to give up Indianness. I am American by nationality, but I am Indian by birth. So whenever I talk, I try to show both the flags as well, both Indian and American flags. Just because you make new relatives but don’t forget the old relatives.”

–Immigrant man of Indian origin in late 40s

the word case study meaning

Pew Research Center designed these focus groups to better understand how members of an ethnically diverse Asian population think about their place in America and life here. By including participants of different languages, immigration or refugee experiences, educational backgrounds, and income levels, this focus group study aimed to capture in people’s own words what it means to be Asian in America. The discussions in these groups may or may not resonate with all Asians living in the United States. Browse excerpts from our focus groups with the interactive quote sorter below, view a video documentary focused on the topics discussed in the focus groups, or tell us your story of belonging in America via social media. The focus group project is part of a broader research project studying the diverse experiences of Asians living in the U.S.

Read sortable quotes from our focus groups

Browse excerpts in the interactive quote sorter from focus group participants in response to the question “What does it mean to be [Vietnamese, Thai, Sri Lankan, Hmong, etc.] like yourself in America?” This interactive allows you to sort quotes from focus group participants by ethnic origin, nativity (U.S. born or born in another country), gender and age.

Video documentary

Videos throughout the data essay illustrate what focus group participants discussed. Those recorded in these videos did not participate in the focus groups but were sampled to have similar demographic characteristics and thematically relevant stories.

Watch the full video documentary and watch additional shorter video clips related to the themes of this data essay.

Share the story of your family and your identity

Did the voices in this data essay resonate? Share your story of what it means to be Asian in America with @pewresearch. Tell us your story by using the hashtag #BeingAsianInAmerica and @pewidentity on Twitter, as well as #BeingAsianInAmerica and @pewresearch on Instagram.

This cross-ethnic, comparative qualitative research project explores the identity, economic mobility, representation, and experiences of immigration and discrimination among the Asian population in the United States. The analysis is based on 66 focus groups we conducted virtually in the fall of 2021 and included 264 participants from across the U.S. More information about the groups and analysis can be found in this appendix .

Pew Research Center is a subsidiary of The Pew Charitable Trusts, its primary funder. This data essay was funded by The Pew Charitable Trusts, with generous support from the Chan Zuckerberg Initiative DAF, an advised fund of the Silicon Valley Community Foundation; the Robert Wood Johnson Foundation; the Henry Luce Foundation; The Wallace H. Coulter Foundation; The Dirk and Charlene Kabcenell Foundation; The Long Family Foundation; Lu-Hebert Fund; Gee Family Foundation; Joseph Cotchett; the Julian Abdey and Sabrina Moyle Charitable Fund; and Nanci Nishimura.

The accompanying video clips and video documentary were made possible by The Pew Charitable Trusts, with generous support from The Sobrato Family Foundation and The Long Family Foundation.

We would also like to thank the Leaders Forum for its thought leadership and valuable assistance in helping make this study possible. This is a collaborative effort based on the input and analysis of a number of individuals and experts at Pew Research Center and outside experts.

1615 L St. NW, Suite 800 Washington, DC 20036 USA (+1) 202-419-4300 | Main (+1) 202-857-8562 | Fax (+1) 202-419-4372 |  Media Inquiries

Research Topics

  • Age & Generations
  • Coronavirus (COVID-19)
  • Economy & Work
  • Family & Relationships
  • Gender & LGBTQ
  • Immigration & Migration
  • International Affairs
  • Internet & Technology
  • Methodological Research
  • News Habits & Media
  • Non-U.S. Governments
  • Other Topics
  • Politics & Policy
  • Race & Ethnicity
  • Email Newsletters

ABOUT PEW RESEARCH CENTER  Pew Research Center is a nonpartisan fact tank that informs the public about the issues, attitudes and trends shaping the world. It conducts public opinion polling, demographic research, media content analysis and other empirical social science research. Pew Research Center does not take policy positions. It is a subsidiary of  The Pew Charitable Trusts .

Copyright 2024 Pew Research Center

Terms & Conditions

Privacy Policy

Cookie Settings

Reprints, Permissions & Use Policy

Cambridge Dictionary

  • Cambridge Dictionary +Plus

Meaning of case in English

Your browser doesn't support HTML5 audio

case noun ( SITUATION )

  • We don't usually accept late applications , but in this case we will make an exception .
  • The newspaper photo apparently showed him in Rome but it was a case of mistaken identity .
  • He may possibly decide not to come, in which case there's no problem .
  • In special cases the manager will stretch the rules .
  • advertisement
  • benchmarking
  • cross-section
  • for instance idiom
  • illustration
  • incarnation
  • quintessence

You can also find related words, phrases, and synonyms in the topics:

case noun ( PROBLEM )

  • He has been cited as the co-respondent in the divorce case.
  • The court's decision on this case will turn the clock back 50 years .
  • The lack of evidence means that the case is unlikely to go to court .
  • The jury took five days to deliberate on the case.
  • His lawyers have decided not to proceed with the case.
  • civilian casualty
  • convalescent
  • day patient
  • health tourist
  • medical tourist
  • non-responder

case noun ( CONTAINER )

  • The crown , decorated with diamonds and other precious stones , was exhibited in a special case.
  • Inside the small wooden case is a gold-chain necklace .
  • Don't forget to put the thermometer back in its case.
  • I emptied the closet and put my belongings into the black overnight case.
  • "Can you lift this case?" "It depends on how heavy it is."
  • I've lashed your case to the roof rack .
  • The boys brought a few cases of beer .
  • biscuit tin
  • packing case

case noun ( ARGUMENT )

  • The case against her was circumstantial .
  • You can argue the case either way.
  • The shareholders seem to think that the executive board is overstating the case for a merger .
  • They paid a high-powered attorney to plead their case .
  • Once again he tried to press his case for promotion .
  • argumentation
  • ascribe something to something
  • explanation
  • explication
  • extenuating
  • extenuation
  • talk your way out of something idiom
  • unclarified
  • warrantable
  • warrantably

case noun ( GRAMMAR )

  • appositively
  • attributively
  • direct object
  • indirect object
  • post-modifier
  • postposition
  • postpositional
  • postpositive

case noun ( WRITING )

  • 3-D printing
  • indentation
  • pre-publish
  • print on demand
  • print something out
  • typographical
  • unpublished

case | American Dictionary

Case noun [c] ( situation ), case noun [c] ( problem ), case noun [c] ( argument ), case noun [c] ( container ), case noun [c] ( grammar ), case | business english, examples of case, collocations with case.

These are words often used in combination with case .

Click on a collocation to see more examples of it.

Translations of case

Get a quick, free translation!

{{randomImageQuizHook.quizId}}

Word of the Day

doggie day care

a place where owners can leave their dogs when they are at work or away from home in the daytime, or the care the dogs receive when they are there

Dead ringers and peas in pods (Talking about similarities, Part 2)

Dead ringers and peas in pods (Talking about similarities, Part 2)

the word case study meaning

Learn more with +Plus

  • Recent and Recommended {{#preferredDictionaries}} {{name}} {{/preferredDictionaries}}
  • Definitions Clear explanations of natural written and spoken English English Learner’s Dictionary Essential British English Essential American English
  • Grammar and thesaurus Usage explanations of natural written and spoken English Grammar Thesaurus
  • Pronunciation British and American pronunciations with audio English Pronunciation
  • English–Chinese (Simplified) Chinese (Simplified)–English
  • English–Chinese (Traditional) Chinese (Traditional)–English
  • English–Dutch Dutch–English
  • English–French French–English
  • English–German German–English
  • English–Indonesian Indonesian–English
  • English–Italian Italian–English
  • English–Japanese Japanese–English
  • English–Norwegian Norwegian–English
  • English–Polish Polish–English
  • English–Portuguese Portuguese–English
  • English–Spanish Spanish–English
  • English–Swedish Swedish–English
  • Dictionary +Plus Word Lists
  • case (SITUATION)
  • in that case
  • (not) the case
  • in any case
  • (just) in case
  • in case of something
  • in the case of someone/something
  • a case of something
  • a case in point
  • as is the case
  • as the case may be
  • case (PROBLEM)
  • case (CONTAINER)
  • case (ARGUMENT)
  • case (GRAMMAR)
  • case (WRITING)
  • case the joint
  • Business    Noun
  • Collocations
  • Translations
  • All translations

Add case to one of your lists below, or create a new one.

{{message}}

Something went wrong.

There was a problem sending your report.

  • Study Guides
  • Homework Questions

AGB Case Study 2

IMAGES

  1. What is a Case Study? [+6 Types of Case Studies]

    the word case study meaning

  2. PPT

    the word case study meaning

  3. Everything you should know about the Case studies

    the word case study meaning

  4. How to Write a Case Study

    the word case study meaning

  5. Case Study: Definition, Examples, Types, and How to Write

    the word case study meaning

  6. case study meaning and characteristics

    the word case study meaning

VIDEO

  1. How to Write a Case Study? A Step-By-Step Guide to Writing a Case Study

  2. How To Write A Case Study?

  3. What is case study and how to conduct case study research

  4. What Is A Case Study?

  5. Types of Case Study [Explanation with Examples]

  6. how to write a case study in research paper

COMMENTS

  1. What Is a Case Study?

    Revised on November 20, 2023. A case study is a detailed study of a specific subject, such as a person, group, place, event, organization, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research. A case study research design usually involves qualitative methods, but quantitative methods are ...

  2. CASE STUDY

    CASE STUDY meaning: 1. a detailed account giving information about the development of a person, group, or thing…. Learn more.

  3. CASE STUDY

    CASE STUDY definition: 1. a detailed account giving information about the development of a person, group, or thing…. Learn more.

  4. Case study Definition & Meaning

    case study: [noun] an intensive analysis of an individual unit (such as a person or community) stressing developmental factors in relation to environment.

  5. CASE STUDY Definition & Meaning

    Case study definition: a study of an individual unit, as a person, family, or social group, usually emphasizing developmental issues and relationships with the environment, especially in order to compare a larger group to the individual unit.. See examples of CASE STUDY used in a sentence.

  6. Case study

    case study: 1 n a detailed analysis of a person or group from a social or psychological or medical point of view Type of: analysis an investigation of the component parts of a whole and their relations in making up the whole n a careful study of some social unit (as a corporation or division within a corporation) that attempts to determine ...

  7. case study noun

    a person, group of people, situation, etc. that is used to study a particular idea or theory . Athletes make an interesting case study for doctors. See case study in the Oxford Advanced American Dictionary See case study in the Oxford Learner's Dictionary of Academic English

  8. CASE STUDY definition and meaning

    The act or an instance of analysing one or more particular cases or case histories with a view.... Click for English pronunciations, examples sentences, video.

  9. Case Study

    Case studies tend to focus on qualitative data using methods such as interviews, observations, and analysis of primary and secondary sources (e.g., newspaper articles, photographs, official records). Sometimes a case study will also collect quantitative data. Example: Mixed methods case study. For a case study of a wind farm development in a ...

  10. case study

    case study meaning: a report about a particular person or thing, to show an example of a general principle. Learn more.

  11. Case study Definition & Meaning

    plural case studies. Britannica Dictionary definition of CASE STUDY. [count] : a published report about a person, group, or situation that has been studied over time. a case study of prisoners. also : a situation in real life that can be looked at or studied to learn about something. The company's recent history is a case study in bad management.

  12. Case study

    A case study is a detailed description and assessment of a specific situation in the real world, often for the purpose of deriving generalizations and other insights about the subject of the case study. Case studies can be about an individual, a group of people, an organization, or an event, and they are used in multiple fields, including business, health care, anthropology, political science ...

  13. What is a Case Study? Definition & Examples

    A case study is an in-depth investigation of a single person, group, event, or community. This research method involves intensively analyzing a subject to understand its complexity and context. The richness of a case study comes from its ability to capture detailed, qualitative data that can offer insights into a process or subject matter that ...

  14. Case Study

    Defnition: 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.

  15. Case Study: Definition, Examples, Types, and How to Write

    A case study is an in-depth study of one person, group, or event. In a case study, nearly every aspect of the subject's life and history is analyzed to seek patterns and causes of behavior. Case studies can be used in many different fields, including psychology, medicine, education, anthropology, political science, and social work.

  16. Writing a Case Study

    A case study research paper examines a person, place, event, condition, phenomenon, or other type of subject of analysis in order to extrapolate key themes and results that help predict future trends, illuminate previously hidden issues that can be applied to practice, and/or provide a means for understanding an important research problem with greater clarity.

  17. CASE STUDY Synonyms: 38 Similar Words

    Synonyms for CASE STUDY: record, report, history, case history, chronology, diary, story, version, chronicle, testimony

  18. case study noun

    Definition of case study noun in Oxford Advanced American Dictionary. Meaning, pronunciation, picture, example sentences, grammar, usage notes, synonyms and more.

  19. Case Study Methodology of Qualitative Research: Key Attributes and

    A case study is one of the most commonly used methodologies of social research. This article attempts to look into the various dimensions of a case study research strategy, the different epistemological strands which determine the particular case study type and approach adopted in the field, discusses the factors which can enhance the effectiveness of a case study research, and the debate ...

  20. Case study

    A case study is an in-depth, detailed examination of a particular case (or cases) within a real-world context. For example, case studies in medicine may focus on an individual patient or ailment; case studies in business might cover a particular firm's strategy or a broader market; similarly, case studies in politics can range from a narrow happening over time like the operations of a specific ...

  21. Case Definition & Meaning

    case: [noun] a set of circumstances or conditions. a situation requiring investigation or action (as by the police). the object of investigation or consideration.

  22. Adaptive neighborhood rough set model for hybrid data ...

    Extracting knowledge from hybrid data, comprising both categorical and numerical data, poses significant challenges due to the inherent difficulty in preserving information and practical meanings ...

  23. Project MUSE

    A Leaky Boat Holding Wine: A Study of the Word-Meaning Debate in Wei-Jin Six Dynasties Period Thought by Jing Yuan (review) Run Gu; Philosophy East and West; University of Hawai'i Press; Volume 74, Number 2, April 2024; pp. 1-3; 10.1353/pew.2024.a925202; Review

  24. Pew Research Center

    Pew Research Center

  25. CASE

    CASE definition: 1. a particular situation or example of something: 2. because of the mentioned situation: 3…. Learn more.

  26. AGB Case Study 2 (pdf)

    AGB 302: Week 2 Case Study Assignment A. What does Amul Cooperative mean for Farmers: List three benefits to farmers: (min 150 words in total for all three benefits) The Amul Cooperative means that farmers can finally receive a more fair price for their product due to the revenue sharing practice implemented. Amul allowed their farmers to both be paid a fair price while simultaneously allowing ...

  27. Biden just signed a potential TikTok ban into law. Here's what ...

    President Joe Biden signed a bill Wednesday that could lead to a nationwide TikTok ban, escalating a massive threat to the company's US operations. Congress had passed the bill this week as part ...