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Empirical Research: Definition, Methods, Types and Examples

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Empirical research: Definition

Empirical research: origin, quantitative research methods, qualitative research methods, steps for conducting empirical research, empirical research methodology cycle, advantages of empirical research, disadvantages of empirical research, why is there a need for empirical research.

Empirical research is defined as any research where conclusions of the study is strictly drawn from concretely empirical evidence, and therefore “verifiable” evidence.

This empirical evidence can be gathered using quantitative market research and  qualitative market research  methods.

For example: A research is being conducted to find out if listening to happy music in the workplace while working may promote creativity? An experiment is conducted by using a music website survey on a set of audience who are exposed to happy music and another set who are not listening to music at all, and the subjects are then observed. The results derived from such a research will give empirical evidence if it does promote creativity or not.

LEARN ABOUT: Behavioral Research

You must have heard the quote” I will not believe it unless I see it”. This came from the ancient empiricists, a fundamental understanding that powered the emergence of medieval science during the renaissance period and laid the foundation of modern science, as we know it today. The word itself has its roots in greek. It is derived from the greek word empeirikos which means “experienced”.

In today’s world, the word empirical refers to collection of data using evidence that is collected through observation or experience or by using calibrated scientific instruments. All of the above origins have one thing in common which is dependence of observation and experiments to collect data and test them to come up with conclusions.

LEARN ABOUT: Causal Research

Types and methodologies of empirical research

Empirical research can be conducted and analysed using qualitative or quantitative methods.

• Quantitative research : Quantitative research methods are used to gather information through numerical data. It is used to quantify opinions, behaviors or other defined variables . These are predetermined and are in a more structured format. Some of the commonly used methods are survey, longitudinal studies, polls, etc
• Qualitative research:   Qualitative research methods are used to gather non numerical data.  It is used to find meanings, opinions, or the underlying reasons from its subjects. These methods are unstructured or semi structured. The sample size for such a research is usually small and it is a conversational type of method to provide more insight or in-depth information about the problem Some of the most popular forms of methods are focus groups, experiments, interviews, etc.

Data collected from these will need to be analysed. Empirical evidence can also be analysed either quantitatively and qualitatively. Using this, the researcher can answer empirical questions which have to be clearly defined and answerable with the findings he has got. The type of research design used will vary depending on the field in which it is going to be used. Many of them might choose to do a collective research involving quantitative and qualitative method to better answer questions which cannot be studied in a laboratory setting.

LEARN ABOUT: Qualitative Research Questions and Questionnaires

Quantitative research methods aid in analyzing the empirical evidence gathered. By using these a researcher can find out if his hypothesis is supported or not.

• Survey research: Survey research generally involves a large audience to collect a large amount of data. This is a quantitative method having a predetermined set of closed questions which are pretty easy to answer. Because of the simplicity of such a method, high responses are achieved. It is one of the most commonly used methods for all kinds of research in today’s world.

Previously, surveys were taken face to face only with maybe a recorder. However, with advancement in technology and for ease, new mediums such as emails , or social media have emerged.

For example: Depletion of energy resources is a growing concern and hence there is a need for awareness about renewable energy. According to recent studies, fossil fuels still account for around 80% of energy consumption in the United States. Even though there is a rise in the use of green energy every year, there are certain parameters because of which the general population is still not opting for green energy. In order to understand why, a survey can be conducted to gather opinions of the general population about green energy and the factors that influence their choice of switching to renewable energy. Such a survey can help institutions or governing bodies to promote appropriate awareness and incentive schemes to push the use of greener energy.

Learn more: Renewable Energy Survey Template Descriptive Research vs Correlational Research

• Experimental research: In experimental research , an experiment is set up and a hypothesis is tested by creating a situation in which one of the variable is manipulated. This is also used to check cause and effect. It is tested to see what happens to the independent variable if the other one is removed or altered. The process for such a method is usually proposing a hypothesis, experimenting on it, analyzing the findings and reporting the findings to understand if it supports the theory or not.

For example: A particular product company is trying to find what is the reason for them to not be able to capture the market. So the organisation makes changes in each one of the processes like manufacturing, marketing, sales and operations. Through the experiment they understand that sales training directly impacts the market coverage for their product. If the person is trained well, then the product will have better coverage.

• Correlational research: Correlational research is used to find relation between two set of variables . Regression analysis is generally used to predict outcomes of such a method. It can be positive, negative or neutral correlation.

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For example: Higher educated individuals will get higher paying jobs. This means higher education enables the individual to high paying job and less education will lead to lower paying jobs.

• Longitudinal study: Longitudinal study is used to understand the traits or behavior of a subject under observation after repeatedly testing the subject over a period of time. Data collected from such a method can be qualitative or quantitative in nature.

For example: A research to find out benefits of exercise. The target is asked to exercise everyday for a particular period of time and the results show higher endurance, stamina, and muscle growth. This supports the fact that exercise benefits an individual body.

• Cross sectional: Cross sectional study is an observational type of method, in which a set of audience is observed at a given point in time. In this type, the set of people are chosen in a fashion which depicts similarity in all the variables except the one which is being researched. This type does not enable the researcher to establish a cause and effect relationship as it is not observed for a continuous time period. It is majorly used by healthcare sector or the retail industry.

For example: A medical study to find the prevalence of under-nutrition disorders in kids of a given population. This will involve looking at a wide range of parameters like age, ethnicity, location, incomes  and social backgrounds. If a significant number of kids coming from poor families show under-nutrition disorders, the researcher can further investigate into it. Usually a cross sectional study is followed by a longitudinal study to find out the exact reason.

• Causal-Comparative research : This method is based on comparison. It is mainly used to find out cause-effect relationship between two variables or even multiple variables.

For example: A researcher measured the productivity of employees in a company which gave breaks to the employees during work and compared that to the employees of the company which did not give breaks at all.

LEARN ABOUT: Action Research

Some research questions need to be analysed qualitatively, as quantitative methods are not applicable there. In many cases, in-depth information is needed or a researcher may need to observe a target audience behavior, hence the results needed are in a descriptive analysis form. Qualitative research results will be descriptive rather than predictive. It enables the researcher to build or support theories for future potential quantitative research. In such a situation qualitative research methods are used to derive a conclusion to support the theory or hypothesis being studied.

LEARN ABOUT: Qualitative Interview

• Case study: Case study method is used to find more information through carefully analyzing existing cases. It is very often used for business research or to gather empirical evidence for investigation purpose. It is a method to investigate a problem within its real life context through existing cases. The researcher has to carefully analyse making sure the parameter and variables in the existing case are the same as to the case that is being investigated. Using the findings from the case study, conclusions can be drawn regarding the topic that is being studied.

For example: A report mentioning the solution provided by a company to its client. The challenges they faced during initiation and deployment, the findings of the case and solutions they offered for the problems. Such case studies are used by most companies as it forms an empirical evidence for the company to promote in order to get more business.

• Observational method:   Observational method is a process to observe and gather data from its target. Since it is a qualitative method it is time consuming and very personal. It can be said that observational research method is a part of ethnographic research which is also used to gather empirical evidence. This is usually a qualitative form of research, however in some cases it can be quantitative as well depending on what is being studied.

For example: setting up a research to observe a particular animal in the rain-forests of amazon. Such a research usually take a lot of time as observation has to be done for a set amount of time to study patterns or behavior of the subject. Another example used widely nowadays is to observe people shopping in a mall to figure out buying behavior of consumers.

• One-on-one interview: Such a method is purely qualitative and one of the most widely used. The reason being it enables a researcher get precise meaningful data if the right questions are asked. It is a conversational method where in-depth data can be gathered depending on where the conversation leads.

For example: A one-on-one interview with the finance minister to gather data on financial policies of the country and its implications on the public.

• Focus groups: Focus groups are used when a researcher wants to find answers to why, what and how questions. A small group is generally chosen for such a method and it is not necessary to interact with the group in person. A moderator is generally needed in case the group is being addressed in person. This is widely used by product companies to collect data about their brands and the product.

For example: A mobile phone manufacturer wanting to have a feedback on the dimensions of one of their models which is yet to be launched. Such studies help the company meet the demand of the customer and position their model appropriately in the market.

• Text analysis: Text analysis method is a little new compared to the other types. Such a method is used to analyse social life by going through images or words used by the individual. In today’s world, with social media playing a major part of everyone’s life, such a method enables the research to follow the pattern that relates to his study.

For example: A lot of companies ask for feedback from the customer in detail mentioning how satisfied are they with their customer support team. Such data enables the researcher to take appropriate decisions to make their support team better.

Sometimes a combination of the methods is also needed for some questions that cannot be answered using only one type of method especially when a researcher needs to gain a complete understanding of complex subject matter.

We recently published a blog that talks about examples of qualitative data in education ; why don’t you check it out for more ideas?

Learn More: Data Collection Methods: Types & Examples

Since empirical research is based on observation and capturing experiences, it is important to plan the steps to conduct the experiment and how to analyse it. This will enable the researcher to resolve problems or obstacles which can occur during the experiment.

Step #1: Define the purpose of the research

This is the step where the researcher has to answer questions like what exactly do I want to find out? What is the problem statement? Are there any issues in terms of the availability of knowledge, data, time or resources. Will this research be more beneficial than what it will cost.

Before going ahead, a researcher has to clearly define his purpose for the research and set up a plan to carry out further tasks.

Step #2 : Supporting theories and relevant literature

The researcher needs to find out if there are theories which can be linked to his research problem . He has to figure out if any theory can help him support his findings. All kind of relevant literature will help the researcher to find if there are others who have researched this before, or what are the problems faced during this research. The researcher will also have to set up assumptions and also find out if there is any history regarding his research problem

Step #3: Creation of Hypothesis and measurement

Before beginning the actual research he needs to provide himself a working hypothesis or guess what will be the probable result. Researcher has to set up variables, decide the environment for the research and find out how can he relate between the variables.

Researcher will also need to define the units of measurements, tolerable degree for errors, and find out if the measurement chosen will be acceptable by others.

Step #4: Methodology, research design and data collection

In this step, the researcher has to define a strategy for conducting his research. He has to set up experiments to collect data which will enable him to propose the hypothesis. The researcher will decide whether he will need experimental or non experimental method for conducting the research. The type of research design will vary depending on the field in which the research is being conducted. Last but not the least, the researcher will have to find out parameters that will affect the validity of the research design. Data collection will need to be done by choosing appropriate samples depending on the research question. To carry out the research, he can use one of the many sampling techniques. Once data collection is complete, researcher will have empirical data which needs to be analysed.

LEARN ABOUT: Best Data Collection Tools

Step #5: Data Analysis and result

Data analysis can be done in two ways, qualitatively and quantitatively. Researcher will need to find out what qualitative method or quantitative method will be needed or will he need a combination of both. Depending on the unit of analysis of his data, he will know if his hypothesis is supported or rejected. Analyzing this data is the most important part to support his hypothesis.

Step #6: Conclusion

A report will need to be made with the findings of the research. The researcher can give the theories and literature that support his research. He can make suggestions or recommendations for further research on his topic.

A.D. de Groot, a famous dutch psychologist and a chess expert conducted some of the most notable experiments using chess in the 1940’s. During his study, he came up with a cycle which is consistent and now widely used to conduct empirical research. It consists of 5 phases with each phase being as important as the next one. The empirical cycle captures the process of coming up with hypothesis about how certain subjects work or behave and then testing these hypothesis against empirical data in a systematic and rigorous approach. It can be said that it characterizes the deductive approach to science. Following is the empirical cycle.

• Observation: At this phase an idea is sparked for proposing a hypothesis. During this phase empirical data is gathered using observation. For example: a particular species of flower bloom in a different color only during a specific season.
• Induction: Inductive reasoning is then carried out to form a general conclusion from the data gathered through observation. For example: As stated above it is observed that the species of flower blooms in a different color during a specific season. A researcher may ask a question “does the temperature in the season cause the color change in the flower?” He can assume that is the case, however it is a mere conjecture and hence an experiment needs to be set up to support this hypothesis. So he tags a few set of flowers kept at a different temperature and observes if they still change the color?
• Deduction: This phase helps the researcher to deduce a conclusion out of his experiment. This has to be based on logic and rationality to come up with specific unbiased results.For example: In the experiment, if the tagged flowers in a different temperature environment do not change the color then it can be concluded that temperature plays a role in changing the color of the bloom.
• Testing: This phase involves the researcher to return to empirical methods to put his hypothesis to the test. The researcher now needs to make sense of his data and hence needs to use statistical analysis plans to determine the temperature and bloom color relationship. If the researcher finds out that most flowers bloom a different color when exposed to the certain temperature and the others do not when the temperature is different, he has found support to his hypothesis. Please note this not proof but just a support to his hypothesis.
• Evaluation: This phase is generally forgotten by most but is an important one to keep gaining knowledge. During this phase the researcher puts forth the data he has collected, the support argument and his conclusion. The researcher also states the limitations for the experiment and his hypothesis and suggests tips for others to pick it up and continue a more in-depth research for others in the future. LEARN MORE: Population vs Sample

LEARN MORE: Population vs Sample

There is a reason why empirical research is one of the most widely used method. There are a few advantages associated with it. Following are a few of them.

• It is used to authenticate traditional research through various experiments and observations.
• This research methodology makes the research being conducted more competent and authentic.
• It enables a researcher understand the dynamic changes that can happen and change his strategy accordingly.
• The level of control in such a research is high so the researcher can control multiple variables.
• It plays a vital role in increasing internal validity .

Even though empirical research makes the research more competent and authentic, it does have a few disadvantages. Following are a few of them.

• Such a research needs patience as it can be very time consuming. The researcher has to collect data from multiple sources and the parameters involved are quite a few, which will lead to a time consuming research.
• Most of the time, a researcher will need to conduct research at different locations or in different environments, this can lead to an expensive affair.
• There are a few rules in which experiments can be performed and hence permissions are needed. Many a times, it is very difficult to get certain permissions to carry out different methods of this research.
• Collection of data can be a problem sometimes, as it has to be collected from a variety of sources through different methods.

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Empirical research is important in today’s world because most people believe in something only that they can see, hear or experience. It is used to validate multiple hypothesis and increase human knowledge and continue doing it to keep advancing in various fields.

For example: Pharmaceutical companies use empirical research to try out a specific drug on controlled groups or random groups to study the effect and cause. This way, they prove certain theories they had proposed for the specific drug. Such research is very important as sometimes it can lead to finding a cure for a disease that has existed for many years. It is useful in science and many other fields like history, social sciences, business, etc.

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With the advancement in today’s world, empirical research has become critical and a norm in many fields to support their hypothesis and gain more knowledge. The methods mentioned above are very useful for carrying out such research. However, a number of new methods will keep coming up as the nature of new investigative questions keeps getting unique or changing.

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What is Empirical Research? Definition, Methods, Examples

Appinio Research · 09.02.2024 · 36min read

Ever wondered how we gather the facts, unveil hidden truths, and make informed decisions in a world filled with questions? Empirical research holds the key.

In this guide, we'll delve deep into the art and science of empirical research, unraveling its methods, mysteries, and manifold applications. From defining the core principles to mastering data analysis and reporting findings, we're here to equip you with the knowledge and tools to navigate the empirical landscape.

What is Empirical Research?

Empirical research is the cornerstone of scientific inquiry, providing a systematic and structured approach to investigating the world around us. It is the process of gathering and analyzing empirical or observable data to test hypotheses, answer research questions, or gain insights into various phenomena. This form of research relies on evidence derived from direct observation or experimentation, allowing researchers to draw conclusions based on real-world data rather than purely theoretical or speculative reasoning.

Characteristics of Empirical Research

Empirical research is characterized by several key features:

• Observation and Measurement : It involves the systematic observation or measurement of variables, events, or behaviors.
• Data Collection : Researchers collect data through various methods, such as surveys, experiments, observations, or interviews.
• Testable Hypotheses : Empirical research often starts with testable hypotheses that are evaluated using collected data.
• Quantitative or Qualitative Data : Data can be quantitative (numerical) or qualitative (non-numerical), depending on the research design.
• Statistical Analysis : Quantitative data often undergo statistical analysis to determine patterns , relationships, or significance.
• Objectivity and Replicability : Empirical research strives for objectivity, minimizing researcher bias . It should be replicable, allowing other researchers to conduct the same study to verify results.
• Conclusions and Generalizations : Empirical research generates findings based on data and aims to make generalizations about larger populations or phenomena.

Importance of Empirical Research

Empirical research plays a pivotal role in advancing knowledge across various disciplines. Its importance extends to academia, industry, and society as a whole. Here are several reasons why empirical research is essential:

• Evidence-Based Knowledge : Empirical research provides a solid foundation of evidence-based knowledge. It enables us to test hypotheses, confirm or refute theories, and build a robust understanding of the world.
• Scientific Progress : In the scientific community, empirical research fuels progress by expanding the boundaries of existing knowledge. It contributes to the development of theories and the formulation of new research questions.
• Problem Solving : Empirical research is instrumental in addressing real-world problems and challenges. It offers insights and data-driven solutions to complex issues in fields like healthcare, economics, and environmental science.
• Informed Decision-Making : In policymaking, business, and healthcare, empirical research informs decision-makers by providing data-driven insights. It guides strategies, investments, and policies for optimal outcomes.
• Quality Assurance : Empirical research is essential for quality assurance and validation in various industries, including pharmaceuticals, manufacturing, and technology. It ensures that products and processes meet established standards.
• Continuous Improvement : Businesses and organizations use empirical research to evaluate performance, customer satisfaction , and product effectiveness. This data-driven approach fosters continuous improvement and innovation.
• Human Advancement : Empirical research in fields like medicine and psychology contributes to the betterment of human health and well-being. It leads to medical breakthroughs, improved therapies, and enhanced psychological interventions.
• Critical Thinking and Problem Solving : Engaging in empirical research fosters critical thinking skills, problem-solving abilities, and a deep appreciation for evidence-based decision-making.

Empirical research empowers us to explore, understand, and improve the world around us. It forms the bedrock of scientific inquiry and drives progress in countless domains, shaping our understanding of both the natural and social sciences.

How to Conduct Empirical Research?

So, you've decided to dive into the world of empirical research. Let's begin by exploring the crucial steps involved in getting started with your research project.

1. Select a Research Topic

Selecting the right research topic is the cornerstone of a successful empirical study. It's essential to choose a topic that not only piques your interest but also aligns with your research goals and objectives. Here's how to go about it:

• Identify Your Interests : Start by reflecting on your passions and interests. What topics fascinate you the most? Your enthusiasm will be your driving force throughout the research process.
• Brainstorm Ideas : Engage in brainstorming sessions to generate potential research topics. Consider the questions you've always wanted to answer or the issues that intrigue you.
• Relevance and Significance : Assess the relevance and significance of your chosen topic. Does it contribute to existing knowledge? Is it a pressing issue in your field of study or the broader community?
• Feasibility : Evaluate the feasibility of your research topic. Do you have access to the necessary resources, data, and participants (if applicable)?

2. Formulate Research Questions

Once you've narrowed down your research topic, the next step is to formulate clear and precise research questions . These questions will guide your entire research process and shape your study's direction. To create effective research questions:

• Specificity : Ensure that your research questions are specific and focused. Vague or overly broad questions can lead to inconclusive results.
• Relevance : Your research questions should directly relate to your chosen topic. They should address gaps in knowledge or contribute to solving a particular problem.
• Testability : Ensure that your questions are testable through empirical methods. You should be able to gather data and analyze it to answer these questions.
• Avoid Bias : Craft your questions in a way that avoids leading or biased language. Maintain neutrality to uphold the integrity of your research.

3. Review Existing Literature

Before you embark on your empirical research journey, it's essential to immerse yourself in the existing body of literature related to your chosen topic. This step, often referred to as a literature review, serves several purposes:

• Contextualization : Understand the historical context and current state of research in your field. What have previous studies found, and what questions remain unanswered?
• Identifying Gaps : Identify gaps or areas where existing research falls short. These gaps will help you formulate meaningful research questions and hypotheses.
• Theory Development : If your study is theoretical, consider how existing theories apply to your topic. If it's empirical, understand how previous studies have approached data collection and analysis.
• Methodological Insights : Learn from the methodologies employed in previous research. What methods were successful, and what challenges did researchers face?

4. Define Variables

Variables are fundamental components of empirical research. They are the factors or characteristics that can change or be manipulated during your study. Properly defining and categorizing variables is crucial for the clarity and validity of your research. Here's what you need to know:

• Independent Variables : These are the variables that you, as the researcher, manipulate or control. They are the "cause" in cause-and-effect relationships.
• Dependent Variables : Dependent variables are the outcomes or responses that you measure or observe. They are the "effect" influenced by changes in independent variables.
• Operational Definitions : To ensure consistency and clarity, provide operational definitions for your variables. Specify how you will measure or manipulate each variable.
• Control Variables : In some studies, controlling for other variables that may influence your dependent variable is essential. These are known as control variables.

Understanding these foundational aspects of empirical research will set a solid foundation for the rest of your journey. Now that you've grasped the essentials of getting started, let's delve deeper into the intricacies of research design.

Empirical Research Design

Now that you've selected your research topic, formulated research questions, and defined your variables, it's time to delve into the heart of your empirical research journey – research design . This pivotal step determines how you will collect data and what methods you'll employ to answer your research questions. Let's explore the various facets of research design in detail.

Types of Empirical Research

Empirical research can take on several forms, each with its own unique approach and methodologies. Understanding the different types of empirical research will help you choose the most suitable design for your study. Here are some common types:

• Experimental Research : In this type, researchers manipulate one or more independent variables to observe their impact on dependent variables. It's highly controlled and often conducted in a laboratory setting.
• Observational Research : Observational research involves the systematic observation of subjects or phenomena without intervention. Researchers are passive observers, documenting behaviors, events, or patterns.
• Survey Research : Surveys are used to collect data through structured questionnaires or interviews. This method is efficient for gathering information from a large number of participants.
• Case Study Research : Case studies focus on in-depth exploration of one or a few cases. Researchers gather detailed information through various sources such as interviews, documents, and observations.
• Qualitative Research : Qualitative research aims to understand behaviors, experiences, and opinions in depth. It often involves open-ended questions, interviews, and thematic analysis.
• Quantitative Research : Quantitative research collects numerical data and relies on statistical analysis to draw conclusions. It involves structured questionnaires, experiments, and surveys.

Your choice of research type should align with your research questions and objectives. Experimental research, for example, is ideal for testing cause-and-effect relationships, while qualitative research is more suitable for exploring complex phenomena.

Experimental Design

Experimental research is a systematic approach to studying causal relationships. It's characterized by the manipulation of one or more independent variables while controlling for other factors. Here are some key aspects of experimental design:

• Control and Experimental Groups : Participants are randomly assigned to either a control group or an experimental group. The independent variable is manipulated for the experimental group but not for the control group.
• Randomization : Randomization is crucial to eliminate bias in group assignment. It ensures that each participant has an equal chance of being in either group.
• Hypothesis Testing : Experimental research often involves hypothesis testing. Researchers formulate hypotheses about the expected effects of the independent variable and use statistical analysis to test these hypotheses.

Observational Design

Observational research entails careful and systematic observation of subjects or phenomena. It's advantageous when you want to understand natural behaviors or events. Key aspects of observational design include:

• Participant Observation : Researchers immerse themselves in the environment they are studying. They become part of the group being observed, allowing for a deep understanding of behaviors.
• Non-Participant Observation : In non-participant observation, researchers remain separate from the subjects. They observe and document behaviors without direct involvement.
• Data Collection Methods : Observational research can involve various data collection methods, such as field notes, video recordings, photographs, or coding of observed behaviors.

Survey Design

Surveys are a popular choice for collecting data from a large number of participants. Effective survey design is essential to ensure the validity and reliability of your data. Consider the following:

• Questionnaire Design : Create clear and concise questions that are easy for participants to understand. Avoid leading or biased questions.
• Sampling Methods : Decide on the appropriate sampling method for your study, whether it's random, stratified, or convenience sampling.
• Data Collection Tools : Choose the right tools for data collection, whether it's paper surveys, online questionnaires, or face-to-face interviews.

Case Study Design

Case studies are an in-depth exploration of one or a few cases to gain a deep understanding of a particular phenomenon. Key aspects of case study design include:

• Single Case vs. Multiple Case Studies : Decide whether you'll focus on a single case or multiple cases. Single case studies are intensive and allow for detailed examination, while multiple case studies provide comparative insights.
• Data Collection Methods : Gather data through interviews, observations, document analysis, or a combination of these methods.

Qualitative vs. Quantitative Research

In empirical research, you'll often encounter the distinction between qualitative and quantitative research . Here's a closer look at these two approaches:

• Qualitative Research : Qualitative research seeks an in-depth understanding of human behavior, experiences, and perspectives. It involves open-ended questions, interviews, and the analysis of textual or narrative data. Qualitative research is exploratory and often used when the research question is complex and requires a nuanced understanding.
• Quantitative Research : Quantitative research collects numerical data and employs statistical analysis to draw conclusions. It involves structured questionnaires, experiments, and surveys. Quantitative research is ideal for testing hypotheses and establishing cause-and-effect relationships.

Understanding the various research design options is crucial in determining the most appropriate approach for your study. Your choice should align with your research questions, objectives, and the nature of the phenomenon you're investigating.

Data Collection for Empirical Research

Now that you've established your research design, it's time to roll up your sleeves and collect the data that will fuel your empirical research. Effective data collection is essential for obtaining accurate and reliable results.

Sampling Methods

Sampling methods are critical in empirical research, as they determine the subset of individuals or elements from your target population that you will study. Here are some standard sampling methods:

• Random Sampling : Random sampling ensures that every member of the population has an equal chance of being selected. It minimizes bias and is often used in quantitative research.
• Stratified Sampling : Stratified sampling involves dividing the population into subgroups or strata based on specific characteristics (e.g., age, gender, location). Samples are then randomly selected from each stratum, ensuring representation of all subgroups.
• Convenience Sampling : Convenience sampling involves selecting participants who are readily available or easily accessible. While it's convenient, it may introduce bias and limit the generalizability of results.
• Snowball Sampling : Snowball sampling is instrumental when studying hard-to-reach or hidden populations. One participant leads you to another, creating a "snowball" effect. This method is common in qualitative research.
• Purposive Sampling : In purposive sampling, researchers deliberately select participants who meet specific criteria relevant to their research questions. It's often used in qualitative studies to gather in-depth information.

The choice of sampling method depends on the nature of your research, available resources, and the degree of precision required. It's crucial to carefully consider your sampling strategy to ensure that your sample accurately represents your target population.

Data Collection Instruments

Data collection instruments are the tools you use to gather information from your participants or sources. These instruments should be designed to capture the data you need accurately. Here are some popular data collection instruments:

• Questionnaires : Questionnaires consist of structured questions with predefined response options. When designing questionnaires, consider the clarity of questions, the order of questions, and the response format (e.g., Likert scale , multiple-choice).
• Interviews : Interviews involve direct communication between the researcher and participants. They can be structured (with predetermined questions) or unstructured (open-ended). Effective interviews require active listening and probing for deeper insights.
• Observations : Observations entail systematically and objectively recording behaviors, events, or phenomena. Researchers must establish clear criteria for what to observe, how to record observations, and when to observe.
• Surveys : Surveys are a common data collection instrument for quantitative research. They can be administered through various means, including online surveys, paper surveys, and telephone surveys.
• Documents and Archives : In some cases, data may be collected from existing documents, records, or archives. Ensure that the sources are reliable, relevant, and properly documented.

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Data Collection Procedures

Data collection procedures outline the step-by-step process for gathering data. These procedures should be meticulously planned and executed to maintain the integrity of your research.

• Training : If you have a research team, ensure that they are trained in data collection methods and protocols. Consistency in data collection is crucial.
• Pilot Testing : Before launching your data collection, conduct a pilot test with a small group to identify any potential problems with your instruments or procedures. Make necessary adjustments based on feedback.
• Data Recording : Establish a systematic method for recording data. This may include timestamps, codes, or identifiers for each data point.
• Data Security : Safeguard the confidentiality and security of collected data. Ensure that only authorized individuals have access to the data.
• Data Storage : Properly organize and store your data in a secure location, whether in physical or digital form. Back up data to prevent loss.

Ethical Considerations

Ethical considerations are paramount in empirical research, as they ensure the well-being and rights of participants are protected.

• Informed Consent : Obtain informed consent from participants, providing clear information about the research purpose, procedures, risks, and their right to withdraw at any time.
• Privacy and Confidentiality : Protect the privacy and confidentiality of participants. Ensure that data is anonymized and sensitive information is kept confidential.
• Beneficence : Ensure that your research benefits participants and society while minimizing harm. Consider the potential risks and benefits of your study.
• Honesty and Integrity : Conduct research with honesty and integrity. Report findings accurately and transparently, even if they are not what you expected.
• Respect for Participants : Treat participants with respect, dignity, and sensitivity to cultural differences. Avoid any form of coercion or manipulation.
• Institutional Review Board (IRB) : If required, seek approval from an IRB or ethics committee before conducting your research, particularly when working with human participants.

Adhering to ethical guidelines is not only essential for the ethical conduct of research but also crucial for the credibility and validity of your study. Ethical research practices build trust between researchers and participants and contribute to the advancement of knowledge with integrity.

With a solid understanding of data collection, including sampling methods, instruments, procedures, and ethical considerations, you are now well-equipped to gather the data needed to answer your research questions.

Empirical Research Data Analysis

Now comes the exciting phase of data analysis, where the raw data you've diligently collected starts to yield insights and answers to your research questions. We will explore the various aspects of data analysis, from preparing your data to drawing meaningful conclusions through statistics and visualization.

Data Preparation

Data preparation is the crucial first step in data analysis. It involves cleaning, organizing, and transforming your raw data into a format that is ready for analysis. Effective data preparation ensures the accuracy and reliability of your results.

• Data Cleaning : Identify and rectify errors, missing values, and inconsistencies in your dataset. This may involve correcting typos, removing outliers, and imputing missing data.
• Data Coding : Assign numerical values or codes to categorical variables to make them suitable for statistical analysis. For example, converting "Yes" and "No" to 1 and 0.
• Data Transformation : Transform variables as needed to meet the assumptions of the statistical tests you plan to use. Common transformations include logarithmic or square root transformations.
• Data Integration : If your data comes from multiple sources, integrate it into a unified dataset, ensuring that variables match and align.
• Data Documentation : Maintain clear documentation of all data preparation steps, as well as the rationale behind each decision. This transparency is essential for replicability.

Effective data preparation lays the foundation for accurate and meaningful analysis. It allows you to trust the results that will follow in the subsequent stages.

Descriptive Statistics

Descriptive statistics help you summarize and make sense of your data by providing a clear overview of its key characteristics. These statistics are essential for understanding the central tendencies, variability, and distribution of your variables. Descriptive statistics include:

• Measures of Central Tendency : These include the mean (average), median (middle value), and mode (most frequent value). They help you understand the typical or central value of your data.
• Measures of Dispersion : Measures like the range, variance, and standard deviation provide insights into the spread or variability of your data points.
• Frequency Distributions : Creating frequency distributions or histograms allows you to visualize the distribution of your data across different values or categories.

Descriptive statistics provide the initial insights needed to understand your data's basic characteristics, which can inform further analysis.

Inferential Statistics

Inferential statistics take your analysis to the next level by allowing you to make inferences or predictions about a larger population based on your sample data. These methods help you test hypotheses and draw meaningful conclusions. Key concepts in inferential statistics include:

• Hypothesis Testing : Hypothesis tests (e.g., t-tests , chi-squared tests ) help you determine whether observed differences or associations in your data are statistically significant or occurred by chance.
• Confidence Intervals : Confidence intervals provide a range within which population parameters (e.g., population mean) are likely to fall based on your sample data.
• Regression Analysis : Regression models (linear, logistic, etc.) help you explore relationships between variables and make predictions.
• Analysis of Variance (ANOVA) : ANOVA tests are used to compare means between multiple groups, allowing you to assess whether differences are statistically significant.

Chi-Square Calculator :

t-Test Calculator :

One-way ANOVA Calculator :

Inferential statistics are powerful tools for drawing conclusions from your data and assessing the generalizability of your findings to the broader population.

Qualitative Data Analysis

Qualitative data analysis is employed when working with non-numerical data, such as text, interviews, or open-ended survey responses. It focuses on understanding the underlying themes, patterns, and meanings within qualitative data. Qualitative analysis techniques include:

• Thematic Analysis : Identifying and analyzing recurring themes or patterns within textual data.
• Content Analysis : Categorizing and coding qualitative data to extract meaningful insights.
• Grounded Theory : Developing theories or frameworks based on emergent themes from the data.
• Narrative Analysis : Examining the structure and content of narratives to uncover meaning.

Qualitative data analysis provides a rich and nuanced understanding of complex phenomena and human experiences.

Data Visualization

Data visualization is the art of representing data graphically to make complex information more understandable and accessible. Effective data visualization can reveal patterns, trends, and outliers in your data. Common types of data visualization include:

• Bar Charts and Histograms : Used to display the distribution of categorical data or discrete data .
• Line Charts : Ideal for showing trends and changes in data over time.
• Scatter Plots : Visualize relationships and correlations between two variables.
• Pie Charts : Display the composition of a whole in terms of its parts.
• Heatmaps : Depict patterns and relationships in multidimensional data through color-coding.
• Box Plots : Provide a summary of the data distribution, including outliers.
• Interactive Dashboards : Create dynamic visualizations that allow users to explore data interactively.

Data visualization not only enhances your understanding of the data but also serves as a powerful communication tool to convey your findings to others.

As you embark on the data analysis phase of your empirical research, remember that the specific methods and techniques you choose will depend on your research questions, data type, and objectives. Effective data analysis transforms raw data into valuable insights, bringing you closer to the answers you seek.

How to Report Empirical Research Results?

At this stage, you get to share your empirical research findings with the world. Effective reporting and presentation of your results are crucial for communicating your research's impact and insights.

1. Write the Research Paper

Writing a research paper is the culmination of your empirical research journey. It's where you synthesize your findings, provide context, and contribute to the body of knowledge in your field.

• Title and Abstract : Craft a clear and concise title that reflects your research's essence. The abstract should provide a brief summary of your research objectives, methods, findings, and implications.
• Introduction : In the introduction, introduce your research topic, state your research questions or hypotheses, and explain the significance of your study. Provide context by discussing relevant literature.
• Methods : Describe your research design, data collection methods, and sampling procedures. Be precise and transparent, allowing readers to understand how you conducted your study.
• Results : Present your findings in a clear and organized manner. Use tables, graphs, and statistical analyses to support your results. Avoid interpreting your findings in this section; focus on the presentation of raw data.
• Discussion : Interpret your findings and discuss their implications. Relate your results to your research questions and the existing literature. Address any limitations of your study and suggest avenues for future research.
• Conclusion : Summarize the key points of your research and its significance. Restate your main findings and their implications.
• References : Cite all sources used in your research following a specific citation style (e.g., APA, MLA, Chicago). Ensure accuracy and consistency in your citations.
• Appendices : Include any supplementary material, such as questionnaires, data coding sheets, or additional analyses, in the appendices.

Writing a research paper is a skill that improves with practice. Ensure clarity, coherence, and conciseness in your writing to make your research accessible to a broader audience.

2. Create Visuals and Tables

Visuals and tables are powerful tools for presenting complex data in an accessible and understandable manner.

• Clarity : Ensure that your visuals and tables are clear and easy to interpret. Use descriptive titles and labels.
• Consistency : Maintain consistency in formatting, such as font size and style, across all visuals and tables.
• Appropriateness : Choose the most suitable visual representation for your data. Bar charts, line graphs, and scatter plots work well for different types of data.
• Simplicity : Avoid clutter and unnecessary details. Focus on conveying the main points.
• Accessibility : Make sure your visuals and tables are accessible to a broad audience, including those with visual impairments.
• Captions : Include informative captions that explain the significance of each visual or table.

Compelling visuals and tables enhance the reader's understanding of your research and can be the key to conveying complex information efficiently.

3. Interpret Findings

Interpreting your findings is where you bridge the gap between data and meaning. It's your opportunity to provide context, discuss implications, and offer insights. When interpreting your findings:

• Relate to Research Questions : Discuss how your findings directly address your research questions or hypotheses.
• Compare with Literature : Analyze how your results align with or deviate from previous research in your field. What insights can you draw from these comparisons?
• Discuss Limitations : Be transparent about the limitations of your study. Address any constraints, biases, or potential sources of error.
• Practical Implications : Explore the real-world implications of your findings. How can they be applied or inform decision-making?
• Future Research Directions : Suggest areas for future research based on the gaps or unanswered questions that emerged from your study.

Interpreting findings goes beyond simply presenting data; it's about weaving a narrative that helps readers grasp the significance of your research in the broader context.

With your research paper written, structured, and enriched with visuals, and your findings expertly interpreted, you are now prepared to communicate your research effectively. Sharing your insights and contributing to the body of knowledge in your field is a significant accomplishment in empirical research.

Examples of Empirical Research

To solidify your understanding of empirical research, let's delve into some real-world examples across different fields. These examples will illustrate how empirical research is applied to gather data, analyze findings, and draw conclusions.

Social Sciences

In the realm of social sciences, consider a sociological study exploring the impact of socioeconomic status on educational attainment. Researchers gather data from a diverse group of individuals, including their family backgrounds, income levels, and academic achievements.

Through statistical analysis, they can identify correlations and trends, revealing whether individuals from lower socioeconomic backgrounds are less likely to attain higher levels of education. This empirical research helps shed light on societal inequalities and informs policymakers on potential interventions to address disparities in educational access.

Environmental Science

Environmental scientists often employ empirical research to assess the effects of environmental changes. For instance, researchers studying the impact of climate change on wildlife might collect data on animal populations, weather patterns, and habitat conditions over an extended period.

By analyzing this empirical data, they can identify correlations between climate fluctuations and changes in wildlife behavior, migration patterns, or population sizes. This empirical research is crucial for understanding the ecological consequences of climate change and informing conservation efforts.

Business and Economics

In the business world, empirical research is essential for making data-driven decisions. Consider a market research study conducted by a business seeking to launch a new product. They collect data through surveys , focus groups , and consumer behavior analysis.

By examining this empirical data, the company can gauge consumer preferences, demand, and potential market size. Empirical research in business helps guide product development, pricing strategies, and marketing campaigns, increasing the likelihood of a successful product launch.

Psychological studies frequently rely on empirical research to understand human behavior and cognition. For instance, a psychologist interested in examining the impact of stress on memory might design an experiment. Participants are exposed to stress-inducing situations, and their memory performance is assessed through various tasks.

By analyzing the data collected, the psychologist can determine whether stress has a significant effect on memory recall. This empirical research contributes to our understanding of the complex interplay between psychological factors and cognitive processes.

These examples highlight the versatility and applicability of empirical research across diverse fields. Whether in medicine, social sciences, environmental science, business, or psychology, empirical research serves as a fundamental tool for gaining insights, testing hypotheses, and driving advancements in knowledge and practice.

Conclusion for Empirical Research

Empirical research is a powerful tool for gaining insights, testing hypotheses, and making informed decisions. By following the steps outlined in this guide, you've learned how to select research topics, collect data, analyze findings, and effectively communicate your research to the world. Remember, empirical research is a journey of discovery, and each step you take brings you closer to a deeper understanding of the world around you. Whether you're a scientist, a student, or someone curious about the process, the principles of empirical research empower you to explore, learn, and contribute to the ever-expanding realm of knowledge.

How to Collect Data for Empirical Research?

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Home » Case Study – Methods, Examples and Guide

Case Study – Methods, Examples and Guide

Table of Contents

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

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

Types of Case Study

Types and Methods of Case Study are as follows:

Single-Case Study

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

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

Multiple-Case Study

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

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

Exploratory Case Study

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

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

Descriptive Case Study

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

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

Instrumental Case Study

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

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

Case Study Data Collection Methods

Here are some common data collection methods for case studies:

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

Observations

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

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

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

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

How to conduct Case Study Research

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

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

Examples of Case Study

Here are some examples of case study research:

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

Application of Case Study

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

Business and Management

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

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

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

Social Sciences

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

Law and Ethics

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

Purpose of Case Study

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

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

Case studies can also serve other purposes, including:

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

Advantages of Case Study Research

There are several advantages of case study research, including:

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

Limitations of Case Study Research

There are several limitations of case study research, including:

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

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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• What is Empirical Research Study? [Examples & Method]

The bulk of human decisions relies on evidence, that is, what can be measured or proven as valid. In choosing between plausible alternatives, individuals are more likely to tilt towards the option that is proven to work, and this is the same approach adopted in empirical research. 

In empirical research, the researcher arrives at outcomes by testing his or her empirical evidence using qualitative or quantitative methods of observation, as determined by the nature of the research. An empirical research study is set apart from other research approaches by its methodology and features hence; it is important for every researcher to know what constitutes this investigation method. 

What is Empirical Research? 

Empirical research is a type of research methodology that makes use of verifiable evidence in order to arrive at research outcomes. In other words, this  type of research relies solely on evidence obtained through observation or scientific data collection methods. 

Empirical research can be carried out using qualitative or quantitative observation methods , depending on the data sample, that is, quantifiable data or non-numerical data . Unlike theoretical research that depends on preconceived notions about the research variables, empirical research carries a scientific investigation to measure the experimental probability of the research variables 

Characteristics of Empirical Research

• Research Questions

An empirical research begins with a set of research questions that guide the investigation. In many cases, these research questions constitute the research hypothesis which is tested using qualitative and quantitative methods as dictated by the nature of the research.

In an empirical research study, the research questions are built around the core of the research, that is, the central issue which the research seeks to resolve. They also determine the course of the research by highlighting the specific objectives and aims of the systematic investigation. 

• Definition of the Research Variables

The research variables are clearly defined in terms of their population, types, characteristics, and behaviors. In other words, the data sample is clearly delimited and placed within the context of the research. 

• Description of the Research Methodology

 An empirical research also clearly outlines the methods adopted in the systematic investigation. Here, the research process is described in detail including the selection criteria for the data sample, qualitative or quantitative research methods plus testing instruments. 

An empirical research is usually divided into 4 parts which are the introduction, methodology, findings, and discussions. The introduction provides a background of the empirical study while the methodology describes the research design, processes, and tools for the systematic investigation. 

The findings refer to the research outcomes and they can be outlined as statistical data or in the form of information obtained through the qualitative observation of research variables. The discussions highlight the significance of the study and its contributions to knowledge. 

Uses of Empirical Research

Without any doubt, empirical research is one of the most useful methods of systematic investigation. It can be used for validating multiple research hypotheses in different fields including Law, Medicine, and Anthropology. 

• Empirical Research in Law : In Law, empirical research is used to study institutions, rules, procedures, and personnel of the law, with a view to understanding how they operate and what effects they have. It makes use of direct methods rather than secondary sources, and this helps you to arrive at more valid conclusions.
• Empirical Research in Medicine : In medicine, empirical research is used to test and validate multiple hypotheses and increase human knowledge.
• Empirical Research in Anthropology : In anthropology, empirical research is used as an evidence-based systematic method of inquiry into patterns of human behaviors and cultures. This helps to validate and advance human knowledge.

Discover how Extrapolation Powers statistical research: Definition, examples, types, and applications explained.

The Empirical Research Cycle

The empirical research cycle is a 5-phase cycle that outlines the systematic processes for conducting and empirical research. It was developed by Dutch psychologist, A.D. de Groot in the 1940s and it aligns 5 important stages that can be viewed as deductive approaches to empirical research. 

In the empirical research methodological cycle, all processes are interconnected and none of the processes is more important than the other. This cycle clearly outlines the different phases involved in generating the research hypotheses and testing these hypotheses systematically using the empirical data. 

• Observation: This is the process of gathering empirical data for the research. At this stage, the researcher gathers relevant empirical data using qualitative or quantitative observation methods, and this goes ahead to inform the research hypotheses.
• Induction: At this stage, the researcher makes use of inductive reasoning in order to arrive at a general probable research conclusion based on his or her observation. The researcher generates a general assumption that attempts to explain the empirical data and s/he goes on to observe the empirical data in line with this assumption.
• Deduction: This is the deductive reasoning stage. This is where the researcher generates hypotheses by applying logic and rationality to his or her observation.
• Testing: Here, the researcher puts the hypotheses to test using qualitative or quantitative research methods. In the testing stage, the researcher combines relevant instruments of systematic investigation with empirical methods in order to arrive at objective results that support or negate the research hypotheses.
• Evaluation: The evaluation research is the final stage in an empirical research study. Here, the research outlines the empirical data, the research findings and the supporting arguments plus any challenges encountered during the research process.

This information is useful for further research. 

Learn about qualitative data: uncover its types and examples here.

Examples of Empirical Research 

• An empirical research study can be carried out to determine if listening to happy music improves the mood of individuals. The researcher may need to conduct an experiment that involves exposing individuals to happy music to see if this improves their moods.

The findings from such an experiment will provide empirical evidence that confirms or refutes the hypotheses. 

• An empirical research study can also be carried out to determine the effects of a new drug on specific groups of people. The researcher may expose the research subjects to controlled quantities of the drug and observe research subjects to controlled quantities of the drug and observe the effects over a specific period of time to gather empirical data.
• Another example of empirical research is measuring the levels of noise pollution found in an urban area to determine the average levels of sound exposure experienced by its inhabitants. Here, the researcher may have to administer questionnaires or carry out a survey in order to gather relevant data based on the experiences of the research subjects.
• Empirical research can also be carried out to determine the relationship between seasonal migration and the body mass of flying birds. A researcher may need to observe the birds and carry out necessary observation and experimentation in order to arrive at objective outcomes that answer the research question.

Empirical Research Data Collection Methods

Empirical data can be gathered using qualitative and quantitative data collection methods. Quantitative data collection methods are used for numerical data gathering while qualitative data collection processes are used to gather empirical data that cannot be quantified, that is, non-numerical data. 

The following are common methods of gathering data in empirical research

• Survey/ Questionnaire

A survey is a method of data gathering that is typically employed by researchers to gather large sets of data from a specific number of respondents with regards to a research subject. This method of data gathering is often used for quantitative data collection , although it can also be deployed during quantitative research.

A survey contains a set of questions that can range from close-ended to open-ended questions together with other question types that revolve around the research subject. A survey can be administered physically or with the use of online data-gathering platforms like Formplus. 

Empirical data can also be collected by carrying out an experiment. An experiment is a controlled simulation in which one or more of the research variables is manipulated using a set of interconnected processes in order to confirm or refute the research hypotheses.

An experiment is a useful method of measuring causality; that is cause and effect between dependent and independent variables in a research environment. It is an integral data gathering method in an empirical research study because it involves testing calculated assumptions in order to arrive at the most valid data and research outcomes. 

T he case study method is another common data gathering method in an empirical research study. It involves sifting through and analyzing relevant cases and real-life experiences about the research subject or research variables in order to discover in-depth information that can serve as empirical data.

• Observation

The observational method is a method of qualitative data gathering that requires the researcher to study the behaviors of research variables in their natural environments in order to gather relevant information that can serve as empirical data.

How to collect Empirical Research Data with Questionnaire

With Formplus, you can create a survey or questionnaire for collecting empirical data from your research subjects. Formplus also offers multiple form sharing options so that you can share your empirical research survey to research subjects via a variety of methods.

Here is a step-by-step guide of how to collect empirical data using Formplus:

Sign in to Formplus

In the Formplus builder, you can easily create your empirical research survey by dragging and dropping preferred fields into your form. To access the Formplus builder, you will need to create an account on Formplus. 

Once you do this, sign in to your account and click on “Create Form ” to begin. 

Unlock the secrets of Quantitative Data: Click here to explore the types and examples.

Edit Form Title

Click on the field provided to input your form title, for example, “Empirical Research Survey”.

Edit Form  

• Click on the edit button to edit the form.
• Add Fields: Drag and drop preferred form fields into your form in the Formplus builder inputs column. There are several field input options for survey forms in the Formplus builder.
• Edit fields
• Click on “Save”
• Preview form.

Customize Form

Formplus allows you to add unique features to your empirical research survey form. You can personalize your survey using various customization options. Here, you can add background images, your organization’s logo, and use other styling options. You can also change the display theme of your form. 

• Share your Form Link with Respondents

Formplus offers multiple form sharing options which enables you to easily share your empirical research survey form with respondents. You can use the direct social media sharing buttons to share your form link to your organization’s social media pages. 

You can send out your survey form as email invitations to your research subjects too. If you wish, you can share your form’s QR code or embed it on your organization’s website for easy access. 

Empirical vs Non-Empirical Research

Empirical and non-empirical research are common methods of systematic investigation employed by researchers. Unlike empirical research that tests hypotheses in order to arrive at valid research outcomes, non-empirical research theorizes the logical assumptions of research variables. 

Definition: Empirical research is a research approach that makes use of evidence-based data while non-empirical research is a research approach that makes use of theoretical data. 

Method: In empirical research, the researcher arrives at valid outcomes by mainly observing research variables, creating a hypothesis and experimenting on research variables to confirm or refute the hypothesis. In non-empirical research, the researcher relies on inductive and deductive reasoning to theorize logical assumptions about the research subjects.

The major difference between the research methodology of empirical and non-empirical research is while the assumptions are tested in empirical research, they are entirely theorized in non-empirical research. 

Data Sample: Empirical research makes use of empirical data while non-empirical research does not make use of empirical data. Empirical data refers to information that is gathered through experience or observation. 

Unlike empirical research, theoretical or non-empirical research does not rely on data gathered through evidence. Rather, it works with logical assumptions and beliefs about the research subject. 

Data Collection Methods : Empirical research makes use of quantitative and qualitative data gathering methods which may include surveys, experiments, and methods of observation. This helps the researcher to gather empirical data, that is, data backed by evidence.  

Non-empirical research, on the other hand, does not make use of qualitative or quantitative methods of data collection . Instead, the researcher gathers relevant data through critical studies, systematic review and meta-analysis. 

Advantages of Empirical Research 

• Empirical research is flexible. In this type of systematic investigation, the researcher can adjust the research methodology including the data sample size, data gathering methods plus the data analysis methods as necessitated by the research process.
• It helps the research to understand how the research outcomes can be influenced by different research environments.
• Empirical research study helps the researcher to develop relevant analytical and observation skills that can be useful in dynamic research contexts.
• This type of research approach allows the researcher to control multiple research variables in order to arrive at the most relevant research outcomes.
• Empirical research is widely considered as one of the most authentic and competent research designs.
• It improves the internal validity of traditional research using a variety of experiments and research observation methods.

Disadvantages of Empirical Research 

• An empirical research study is time-consuming because the researcher needs to gather the empirical data from multiple resources which typically takes a lot of time.
• It is not a cost-effective research approach. Usually, this method of research incurs a lot of cost because of the monetary demands of the field research.
• It may be difficult to gather the needed empirical data sample because of the multiple data gathering methods employed in an empirical research study.
• It may be difficult to gain access to some communities and firms during the data gathering process and this can affect the validity of the research.
• The report from an empirical research study is intensive and can be very lengthy in nature.

Conclusion 

Empirical research is an important method of systematic investigation because it gives the researcher the opportunity to test the validity of different assumptions, in the form of hypotheses, before arriving at any findings. Hence, it is a more research approach. 

There are different quantitative and qualitative methods of data gathering employed during an empirical research study based on the purpose of the research which include surveys, experiments, and various observatory methods. Surveys are one of the most common methods or empirical data collection and they can be administered online or physically. 

You can use Formplus to create and administer your online empirical research survey. Formplus allows you to create survey forms that you can share with target respondents in order to obtain valuable feedback about your research context, question or subject. 

In the form builder, you can add different fields to your survey form and you can also modify these form fields to suit your research process. Sign up to Formplus to access the form builder and start creating powerful online empirical research survey forms. 

Connect to Formplus, Get Started Now - It's Free!

• advantage of empirical research
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Research Methodologies Guide

• Action Research
• Bibliometrics

Case Studies

• Content Analysis
• Digital Scholarship This link opens in a new window
• Documentary
• Ethnography
• Focus Groups
• Grounded Theory
• Life Histories/Autobiographies
• Longitudinal
• Participant Observation
• Qualitative Research (General)
• Quasi-Experimental Design
• Usability Studies

"A case study is an empirical inquiry that investigates a contemporary phenomenon within its real-life context, especially when the boundaries between phenomenon and context are not clearly evident" (Yin, 1994).

It refers to a type of research in which a case (an event, issue, population, or other item being studied) is analyzed, often through the use of multiple methods of analysis.

Tools commonly used in case studies include:

• Observations

For more information about case studies, review the resources below:

Books and articles

• Five Misunderstandings About Case Study Research [pdf] An article reflecting on common issues in case study research.
• Case Study Research and Applications by Robert K. Yin Publication Date: 2017
• Qualitative Research Through Case Studies by Max Travers Publication Date: 2001
• Unravelling the Mysteries of Case Study Research by Marilyn L. Taylor; Mikael Søndergaard Publication Date: 2017

Additional Resources

• Case Studies A tutorial on case study research from Colorado State University.
• Case Study - Wikipedia, the free encyclopedia. Wikipedia can be a useful place to start your research- check the citations at the bottom of the article for more information.
• << Previous: Bibliometrics
• Next: Content Analysis >>
• Last Updated: Sep 11, 2024 11:05 AM
• URL: https://instr.iastate.libguides.com/researchmethods

• MAY 16, 2024

What Is Empirical Research? Definition, Types & Samples in 2024

by Imed Bouchrika, Phd

Co-Founder and Chief Data Scientist

How was the world formed? Are there parallel universes? Why does time move forward but never in reverse? These are longstanding questions that have yet to receive definitive answers up to now.

In research, these are called empirical questions, which ask about how the world is, how the world works, etc. Such questions are addressed by a corresponding type of study—called empirical research or the empirical method—which is concerned with actual events and phenomena.

What is an empirical study? Research is empirical if it seeks to find a general story or explanation, one that applies to various cases and across time. The empirical approach functions to create new knowledge about the way the world actually works. This article discusses the empirical research definition, concepts, types, processes, and other important aspects of this method. It also tackles the importance of identifying evidence in research .

I. What is Empirical Research?

A. definitions.

What is empirical evidence? Empirical research is defined as any study whose conclusions are exclusively derived from concrete, verifiable evidence. The term empirical basically means that it is guided by scientific experimentation and/or evidence. Likewise, a study is empirical when it uses real-world evidence in investigating its assertions.

This research type is founded on the view that direct observation of phenomena is a proper way to measure reality and generate truth about the world (Bhattacharya, 2008). And by its name, it is a methodology in research that observes the rules of empiricism and uses quantitative and qualitative methods for gathering evidence.

For instance, a study is being conducted to determine if working from home helps in reducing stress from highly-demanding jobs. An experiment is conducted using two groups of employees, one working at their homes, the other working at the office. Each group was observed. The outcomes derived from this research will provide empirical evidence if working from home does help reduce stress or not. This also applies to entrepreneurs when they use a small business idea generator instead of manual procedures.

It was the ancient Greek medical practitioners who originated the term empirical ( empeirikos which means “experienced") when they began to deviate from the long-observed dogmatic principles to start depending on observed phenomena. Later on, empiricism pertained to a theory of knowledge in philosophy, which follows the belief that knowledge comes from evidence and experience derived particularly using the senses.

What ancient philosophers considered empirical research pertained to the reliance on observable data to design and test theories and reach conclusions. As such, empirical research is used to produce knowledge that is based on experience. At present, the word “empirical" pertains to the gathering of data using evidence that is derived through experience or observation or by using calibrated scientific tools.

Most of today’s outstanding empirical research outputs are published in prestigious journals. These scientific publications are considered high-impact journals because they publish research articles that tend to be the most cited in their fields.

II. Types and Methodologies of Empirical Research

Empirical research is done using either qualitative or quantitative methods.

Qualitative research Qualitative research methods are utilized for gathering non-numerical data. It is used to determine the underlying reasons, views, or meanings from study participants or subjects. Under the qualitative research design, empirical studies had evolved to test the conventional concepts of evidence and truth while still observing the fundamental principles of recognizing the subjects beings studied as empirical (Powner, 2015).

This method can be semi-structured or unstructured. Results from this research type are more descriptive than predictive. It allows the researcher to write a conclusion to support the hypothesis or theory being examined.

Due to realities like time and resources, the sample size of qualitative research is typically small. It is designed to offer in-depth information or more insight regarding the problem. Some of the most popular forms of methods are interviews, experiments, and focus groups.

Quantitative research   Quantitative research methods are used for gathering information via numerical data. This type is used to measure behavior, personal views, preferences, and other variables. Quantitative studies are in a more structured format, while the variables used are predetermined.

Data gathered from quantitative studies is analyzed to address the empirical questions. Some of the commonly used quantitative methods are polls, surveys, and longitudinal or cohort studies.

There are situations when using a single research method is not enough to adequately answer the questions being studied. In such cases, a combination of both qualitative and quantitative methods is necessary. Also, papers can also make use of both primary and secondary research methods

III. Qualitative Empirical Research Methods

Some research question examples need to be gathered and analyzed qualitatively or quantitatively, depending on the nature of the study. These not only supply answers to empirical questions but also outline one’s scope of work . Here are the general types of qualitative research methods.

Observational Method

This involves observing and gathering data from study subjects. As a qualitative approach, observation is quite personal and time-intensive. It is often used in ethnographic studies to obtain empirical evidence.

The observational method is a part of the ethnographic research design, e.g., archival research, survey, etc. However, while it is commonly used for qualitative purposes, observation is also utilized for quantitative research, such as when observing measurable variables like weight, age, scale, etc.

One remarkable observational research was conducted by Abbott et al. (2016), a team of physicists from the Advanced Laser Interferometer Gravitational-Wave Observatory who examined the very first direct observation of gravitational waves. According to Google Scholar’s (2019) Metrics ranking, this study is among the most highly cited articles from the world’s most influential journals (Crew, 2019).

This method is exclusively qualitative and is one of the most widely used (Jamshed, 2014). Its popularity is mainly due to its ability to allow researchers to obtain precise, relevant information if the correct questions are asked.

This method is a form of a conversational approach, where in-depth data can be obtained. Interviews are commonly used in the social sciences and humanities, such as for interviewing resource persons.

This method is used to identify extensive information through an in-depth analysis of existing cases. It is typically used to obtain empirical evidence for investigating problems or business studies.

When conducting case studies, the researcher must carefully perform the empirical analysis, ensuring the variables and parameters in the current case are similar to the case being examined. From the findings of a case study, conclusions can be deduced about the topic being investigated.

Case studies are commonly used in studying the experience of organizations, groups of persons, geographic locations, etc.

Textual Analysis

This primarily involves the process of describing, interpreting, and understanding textual content. It typically seeks to connect the text to a broader artistic, cultural, political, or social context (Fairclough, 2003).

A relatively new research method, textual analysis is often used nowadays to elaborate on the trends and patterns of media content, especially social media. Data obtained from this approach are primarily used to determine customer buying habits and preferences for product development, and designing marketing campaigns.

Focus Groups

A focus group is a thoroughly planned discussion guided by a moderator and conducted to derive opinions on a designated topic. Essentially a group interview or collective conversation, this method offers a notably meaningful approach to think through particular issues or concerns (Kamberelis & Dimitriadis, 2011).

This research method is used when a researcher wants to know the answers to “how," “what," and “why" questions. Nowadays, focus groups are among the most widely used methods by consumer product producers for designing and/or improving products that people prefer.

IV. Quantitative Empirical Research Methods

Quantitative methods primarily help researchers to better analyze the gathered evidence. Here are the most common types of quantitative research techniques:

A research hypothesis is commonly tested using an experiment, which involves the creation of a controlled environment where the variables are maneuvered. Aside from determining the cause and effect, this method helps in knowing testing outcomes, such as when altering or removing variables.

Traditionally, experimental, laboratory-based research is used to advance knowledge in the physical and life sciences, including psychology. In recent decades, more and more social scientists are also adopting lab experiments (Falk & Heckman, 2009).

Survey research is designed to generate statistical data about a target audience (Fowler, 2014). Surveys can involve large, medium, or small populations and can either be a one-time event or a continuing process

Governments across the world are among the heavy users of continuing surveys, such as for census of populations or labor force surveys. This is a quantitative method that uses predetermined sets of closed questions that are easy to answer, thus enabling the gathering and analysis of large data sets.

In the past, surveys used to be expensive and time-consuming. But with the advancement in technology, new survey tools like social media and emails have made this research method easier and cheaper.

Causal-Comparative research

This method leverages the strength of comparison. It is primarily utilized to determine the cause and effect relationship among variables (Schenker & Rumrill, 2004).

For instance, a causal-comparative study measured the productivity of employees in an organization that allows remote work setup and compared that to the staff of another organization that does not offer work from home arrangements.

Cross-sectional research

While the observation method considers study subjects at a given point in time, cross-sectional research focuses on the similarity in all variables except the one being studied. 

This type does not allow for the determination of cause-effect relationships since subjects are now observed continuously. A cross-sectional study is often followed by longitudinal research to determine the precise causes. It is used mainly by pharmaceutical firms and retailers.

Longitudinal study

A longitudinal method of research is used for understanding the traits or behavior of a subject under observation after repeatedly testing the subject over a certain period of time. Data collected using this method can be qualitative or quantitative in nature. 

A commonly-used form of longitudinal research is the cohort study. For instance, in 1951, a cohort study called the British Doctors Study (Doll et al., 2004) was initiated, which compared smokers and non-smokers in the UK. The study continued through 2001. As early as 1956, the study gave undeniable proof of the direct link between smoking and the incidence of lung cancer.

Correlational research

This method is used to determine the relationships and prevalence among variables (Curtis et al., 2016). It commonly employs regression as the statistical treatment for predicting the study’s outcomes, which can only be a negative, neutral, or positive correlation.

A classic example of empirical research with correlational research is when studying if high education helps in obtaining better-paying jobs. If outcomes indicate that higher education does allow individuals to have high-salaried jobs, then it follows that people with less education tend to have lower-paying jobs.

V. Steps for Conducting Empirical Research

Since empirical research is based on observation and capturing experiences, it is important to plan the steps to conduct the experiment and how to analyze it. This will enable the researcher to resolve problems or obstacles, which can occur during the experiment.

Step #1: Establishing the research objective

In this initial step, the researcher must be clear about what he or she precisely wants to do in the study. He or she should likewise frame the problem statement, plans of action, and determine any potential issues with the available resources, schedule, etc. for the research.

Most importantly, the researcher must be able to ascertain whether the study will be more beneficial than the cost it will incur.

Step #2: Reviewing relevant literature and supporting theories

The researcher must determine relevant theories or models to his or her research problem. If there are any such theories or models, they must understand how it can help in supporting the study outcomes.

Relevant literature must also be consulted. The researcher must be able to identify previous studies that examined similar problems or subjects, as well as determine the issues encountered.

Step #3: Framing the hypothesis and measurement

The researcher must frame an initial hypothesis or educated guess that could be the likely outcome. Variables must be established, along with the research context.

Units of measurements should also be defined, including the allowable margin of errors. The researcher must determine if the selected measures will be accepted by other scholars.

Step #4: Defining the research design, methodology, and data collection techniques

Before proceeding with the study, the researcher must establish an appropriate approach for the research. He or she must organize experiments to gather data that will allow him or her to frame the hypothesis.

The researcher should also decide whether he or she will use a nonexperimental or experimental technique to perform the study. Likewise, the  type of research design will depend on the type of study being conducted.

Finally, the researcher must determine the parameters that will influence the validity of the research design. Data gathering must be performed by selecting suitable samples based on the research question. After gathering the empirical data, the analysis follows.

Step #5: Conducting data analysis and framing the results

Data analysis is done either quantitatively or qualitatively. Depending on the nature of the study, the researcher must determine which method of data analysis is the appropriate one, or whether a combination of the two is suitable.

The outcomes of this step determine if the hypothesis is supported or rejected. This is why data analysis is considered as one of the most crucial steps in any research undertaking.

Step #6: Making conclusions

A report must be prepared in that it presents the findings and the entire research proceeding. If the researcher intends to disseminate his or her findings to a wider audience, the report will be converted into an article for publication. Aside from including the typical parts from the introduction and literature view, up to the methods, analysis, and conclusions, the researcher should also make recommendations for further research on his or her topic.

To ensure the originality and credibility of the report or research, it is essential to employ a plagiarism checker. By using a reliable plagiarism checker, the researcher can verify the uniqueness of their work and avoid any unintentional instances of plagiarism. This step helps maintain the integrity of the research and ensures that the recommendations for further research are based on the researcher’s own original insights. Incorporating a plagiarism checker into the writing process provides an additional layer of assurance and professionalism, enhancing the impact of the report or article in the academic community. Educators can also check the originality of their students’ research by utilizing a free plagiarism checker for teachers .

VI. Empirical Research Cycle

The empirical research cycle is composed of five phases, with each one considered as important as the next phase (de Groot, 1969). This rigorous and systematic method can consistently capture the process of framing hypotheses on how certain subjects behave or function and then testing them versus empirical data. It is considered to typify the deductive approach to science.

These are the five phases of the empirical research cycle:

1. Observation

During this initial phase, an idea is triggered for presenting a hypothesis. It involves the use of observation to gather empirical data. For example :

Consumers tend to consult first their smartphones before buying something in-store .

2. Induction

Inductive reasoning is then conducted to frame a general conclusion from the data gathered through observation. For example:

As mentioned earlier, most consumers tend to consult first their smartphones before buying something in-store .

A researcher may pose the question, “Does the tendency to use a smartphone indicate that today’s consumers need to be informed before making purchasing decisions?" The researcher can assume that is the case. Nonetheless, since it is still just a supposition, an experiment must be conducted to support or reject this hypothesis.

The researcher decided to conduct an online survey to inquire about the buying habits of a certain sample population of buyers at brick-and-mortar stores. This is to determine whether people always look at their smartphones first before making a purchase.

3. Deduction

This phase enables the researcher to figure out a conclusion out of the experiment. This must be based on rationality and logic in order to arrive at particular, unbiased outcomes. For example:

In the experiment, if a shopper consults first his or her smartphone before buying in-store, then it can be concluded that the shopper needs information to help him or her make informed buying decisions .

This phase involves the researcher going back to the empirical research steps to test the hypothesis. There is now the need to analyze and validate the data using appropriate statistical methods.

If the researcher confirms that in-store shoppers do consult their smartphones for product information before making a purchase, the researcher has found support for the hypothesis. However, it should be noted that this is just support of the hypothesis, not proof of a reality.

5. Evaluation

This phase is often neglected by many but is actually a crucial step to help keep expanding knowledge. During this stage, the researcher presents the gathered data, the supporting contention/s, and conclusions.

The researcher likewise puts forth the limitations of the study and his hypothesis. In addition, the researcher makes recommendations for further studies on the same topic with expanded variables.

VII. Advantages and Disadvantages of Empirical Research

Since the time of the ancient Greeks, empirical research had been providing the world with numerous benefits. The following are a few of them:

• Empirical research is used to validate previous research findings and frameworks.
• It assumes a critical role in enhancing internal validity.
• The degree of control is high, which enables the researcher to manage numerous variables.
• It allows a researcher to comprehend the progressive changes that can occur, and thus enables him to modify an approach when needed.
• Being based on facts and experience makes a research project more authentic and competent.

Disadvantages

Despite the many benefits it brings, empirical research is far from perfect. The following are some of its drawbacks:

• Being evidence-based, data collection is a common problem especially when the research involves different sources and multiple methods.
• It can be time-consuming, especially for longitudinal research.
• Requesting permission to perform certain methods can be difficult, especially when a study involves human subjects.
• Conducting research in multiple locations can be very expensive.
• The propensity of even seasoned researchers to incorrectly interpret the statistical significance. For instance, Amrhein et al. (2019) made an analysis of 791 articles from five journals and found that half incorrectly interpreted that non-significance indicates zero effect.

VIII. Samples of Empirical Research

There are many types of empirical research. And, they can take many formsfrom basic research to action research like community project efforts. Here are some notable empirical research examples:

Professional Research

• Research on Information Technology
• Research on Infectious Diseases
• Research on Occupational Health Psychology
• Research on Infection Control
• Research on Cancer
• Research on Mathematical Science
• Research on Environmental Science
• Research on Genetics
• Research on Climate Change
• Research on Economics

Student Research

• Thesis for B.S. in Computer Science & Engineering  
• Thesis for B.S. in Geography
• Thesis for B.S. in Architecture
• Thesis for Master of Science in Electrical Engineering & Computer Science
• Thesis for Master of Science in Artificial Intelligence
• Thesis for Master of Science in Food Science and Nutrition
• Dissertation for Ph.D. in Marketing  
• Dissertation for Ph.D. in Social Work
• Dissertation for Ph.D. in Urban Planning

Since ancient times until today, empirical research remains one of the most useful tools in man’s collective endeavor to unlock life’s mysteries. Using meaningful experience and observable evidence, this type of research will continue helping validate myriad hypotheses, test theoretical models, and advance various fields of specialization.

With new forms of deadly diseases and other problems continuing to plague man’s existence, finding effective medical interventions and relevant solutions had never been more important. This is among the reasons why empirical research had assumed a more prominent role in today’s society.

This article was able to discuss the different empirical research methods, the steps for conducting empirical research, the empirical research cycle, and notable examples. All of these contribute to supporting the larger societal cause to help understand how the world really works and make it a better place. Furthermore, being factually accurate is a big part of the criteria of good research , and it serves as the heart of empirical research.

Key Insights

• Definition of Empirical Research: Empirical research is based on verifiable evidence derived from observation and experimentation, aiming to understand how the world works.
• Origins: The concept of empirical research dates back to ancient Greek medical practitioners who relied on observed phenomena rather than dogmatic principles.
• Types and Methods: Empirical research can be qualitative (e.g., interviews, case studies) or quantitative (e.g., surveys, experiments), depending on the nature of the data collected and the research question.
• Empirical Research Cycle: Consists of observation, induction, deduction, testing, and evaluation, forming a systematic approach to generating and testing hypotheses.
• Steps in Conducting Empirical Research: Includes establishing objectives, reviewing literature, framing hypotheses, designing methodology, collecting data, analyzing data, and making conclusions.
• Advantages: Empirical research validates previous findings, enhances internal validity, allows for high control over variables, and is fact-based, making it authentic and competent.
• Disadvantages: Data collection can be challenging and time-consuming, especially in longitudinal studies, and interpreting statistical significance can be problematic.
• Applications: Used across various fields such as IT, infectious diseases, occupational health, environmental science, and economics. It is also prevalent in student research for theses and dissertations.
• What is the primary goal of empirical research? The primary goal of empirical research is to generate knowledge about how the world works by relying on verifiable evidence obtained through observation and experimentation.
• How does empirical research differ from theoretical research? Empirical research is based on observable and measurable evidence, while theoretical research involves abstract ideas and concepts without necessarily relying on real-world data.
• What are the main types of empirical research methods? The main types of empirical research methods are qualitative (e.g., interviews, case studies, focus groups) and quantitative (e.g., surveys, experiments, cross-sectional studies).
• Why is the empirical research cycle important? The empirical research cycle is important because it provides a structured and systematic approach to generating and testing hypotheses, ensuring that the research is thorough and reliable.
• What are the steps involved in conducting empirical research? The steps involved in conducting empirical research include establishing the research objective, reviewing relevant literature, framing hypotheses, defining research design and methodology, collecting data, analyzing data, and making conclusions.
• What are the advantages of empirical research? The advantages of empirical research include validating previous findings, enhancing internal validity, allowing for high control over variables, and being based on facts and experiences, making the research authentic and competent.
• What are some common challenges in conducting empirical research? Common challenges in conducting empirical research include difficulties in data collection, time-consuming processes, obtaining permissions for certain methods, high costs, and potential misinterpretation of statistical significance.
• In which fields is empirical research commonly used? Empirical research is commonly used in fields such as information technology, infectious diseases, occupational health, environmental science, economics, and various academic disciplines for student theses and dissertations.
• Can empirical research use both qualitative and quantitative methods? Yes, empirical research can use both qualitative and quantitative methods, often combining them to provide a comprehensive understanding of the research problem.
• What role does empirical research play in modern society? Empirical research plays a crucial role in modern society by validating hypotheses, testing theoretical models, and advancing knowledge across various fields, ultimately contributing to solving complex problems and improving the quality of life.
• Abbott, B., Abbott, R., Abbott, T., Abernathy, M., & Acernese, F. (2016). Observation of Gravitational Waves from a Binary Black Hole Merger. Physical Review Letters, 116 (6), 061102. https://doi.org/10.1103/PhysRevLett.116.061102
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• What is empirical research: Methods, types & examples

Defne Çobanoğlu

Having opinions on matters based on observation is okay sometimes. Same as having theories on the subject you want to solve. However, some theories need to be tested. Just like Robert Oppenheimer says, “Theory will take you only so far .” 

In that case, when you have your research question ready and you want to make sure it is correct, the next step would be experimentation. Because only then you can test your ideas and collect tangible information. Now, let us start with the empirical research definition:

• What is empirical research?

Empirical research is a research type where the aim of the study is based on finding concrete and provable evidence . The researcher using this method to draw conclusions can use both quantitative and qualitative methods. Different than theoretical research, empirical research uses scientific experimentation and investigation. 

Using experimentation makes sense when you need to have tangible evidence to act on whatever you are planning to do. As the researcher, you can be a marketer who is planning on creating a new ad for the target audience, or you can be an educator who wants the best for the students. No matter how big or small, data gathered from the real world using this research helps break down the question at hand. 

• When to use empirical research?

Empirical research methods are used when the researcher needs to gather data analysis on direct, observable, and measurable data. Research findings are a great way to make grounded ideas. Here are some situations when one may need to do empirical research:

1. When quantitative or qualitative data is needed

There are times when a researcher, marketer, or producer needs to gather data on specific research questions to make an informed decision. And the concrete data gathered in the research process gives a good starting point.

2. When you need to test a hypothesis

When you have a hypothesis on a subject, you can test the hypothesis through observation or experiment. Making a planned study is a great way to collect information and test whether or not your hypothesis is correct.

3. When you want to establish causality

Experimental research is a good way to explore whether or not there is any correlation between two variables. Researchers usually establish causality by changing a variable and observing if the independent variable changes accordingly.

• Types of empirical research

The aim of empirical research is to collect information about a subject from the people by doing experimentation and other data collection methods. However, the methods and data collected are divided into two groups: one collects numerical data, and the other one collects opinion-like data. Let us see the difference between these two types:

Quantitative research

Quantitative research methods are used to collect data in a numerical way. Therefore, the results gathered by these methods will be numbers, statistics, charts, etc. The results can be used to quantify behaviors, opinions, and other variables. Quantitative research methods are surveys, questionnaires, and experimental research.

Qualitiative research

Qualitative research methods are not used to collect numerical answers, instead, they are used to collect the participants’ reasons, opinions, and other meaningful aspects. Qualitative research methods include case studies, observations, interviews, focus groups, and text analysis.

• 5 steps to conduct empirical research

Necessary steps for empirical research

When you want to collect direct and concrete data on a subject, empirical research is a great way to go. And, just like every other project and research, it is best to have a clear structure in mind. This is even more important in studies that may take a long time, such as experiments that take years. Let us look at a clear plan on how to do empirical research:

1. Define the research question

The very first step of every study is to have the question you will explore ready. Because you do not want to change your mind in the middle of the study after investing and spending time on the experimentation.

2. Go through relevant literature

This is the step where you sit down and do a desk research where you gather relevant data and see if other researchers have tried to explore similar research questions. If so, you can see how well they were able to answer the question or what kind of difficulties they faced during the research process.

3. Decide on the methodology

Once you are done going through the relevant literature, you can decide on which method or methods you can use. The appropriate methods are observation, experimentation, surveys, interviews, focus groups, etc.

4. Do data analysis

When you get to this step, it means you have successfully gathered enough data to make a data analysis. Now, all you need to do is look at the data you collected and make an informed analysis.

5. Conclusion

This is the last step, where you are finished with the experimentation and data analysis process. Now, it is time to decide what to do with this information. You can publish a paper and make informed decisions about whatever your goal is.

• Empirical research methodologies

Some essential methodologies to conduct empirical research

The aim of this type of research is to explore brand-new evidence and facts. Therefore, the methods should be primary and gathered in real life, directly from the people. There is more than one method for this goal, and it is up to the researcher to use which one(s). Let us see the methods of empirical research: 

• Observation

The method of observation is a great way to collect information on people without the effect of interference. The researcher can choose the appropriate area, time, or situation and observe the people and their interactions with one another. The researcher can be just an outside observer or can be a participant as an observer or a full participant.

• Experimentation

The experimentation process can be done in the real world by intervening in some elements to unify the environment for all participants. This method can also be done in a laboratory environment. The experimentation process is good for being able to change the variables according to the aim of the study.

The case study method is done by making an in-depth analysis of already existing cases. When the parameters and variables are similar to the research question at hand, it is wise to go through what was researched before.

• Focus groups

The case study method is done by using a group of individuals or multiple groups and using their opinions, characteristics, and responses. The scientists gather the data from this group and generalize it to the whole population.

Surveys are an effective way to gather data directly from people. It is a systematic approach to collecting information. If it is done in an online setting as an online survey , it would be even easier to reach out to people and ask their opinions in open-ended or close-ended questions.

Interviews are similar to surveys as you are using questions to collect information and opinions of the people. Unlike a survey, this process is done face-to-face, as a phone call, or as a video call.

• Advantages of empirical research

Empirical research is effective for many reasons, and helps researchers from numerous fields. Here are some advantages of empirical research to have in mind for your next research:

• Empirical research improves the internal validity of the study.
• Empirical evidence gathered from the study is used to authenticate the research question.
• Collecting provable evidence is important for the success of the study.
• The researcher is able to make informed decisions based on the data collected using empirical research.
• Disadvantages of empirical research

After learning about the positive aspects of empirical research, it is time to mention the negative aspects. Because this type may not be suitable for everyone and the researcher should be mindful of the disadvantages of empirical research. Here are the disadvantages of empirical research:

• As it is similar to other research types, a case study where experimentation is included will be time-consuming no matter what. It has more steps and variables than concluding a secondary research.
• There are a lot of variables that need to be controlled and considered. Therefore, it may be a challenging task to be mindful of all the details.
• Doing evidence-based research can be expensive if you need to complete it on a large scale.
• When you are conducting an experiment, you may need some waivers and permissions.
• Frequently asked questions about empirical research

Empirical research is one of the many research types, and there may be some questions in mind about its similarities and differences to other research types.

Is empirical research qualitative or quantitative?

The data collected by empirical research can be qualitative, quantitative, or a mix of both. It is up to the aim of researcher to what kind of data is needed and searched for.

Is empirical research the same as quantitative research?

As quantitative research heavily relies on data collection methods of observation and experimentation, it is, in nature, an empirical study. Some professors may even use the terms interchangeably. However, that does not mean that empirical research is only a quantitative one.

What is the difference between theoretical and empirical research?

Empirical studies are based on data collection to prove theories or answer questions, and it is done by using methods such as observation and experimentation. Therefore, empirical research relies on finding evidence that backs up theories. On the other hand, theoretical research relies on theorizing on empirical research data and trying to make connections and correlations.

What is the difference between conceptual and empirical research?

Conceptual research is about thoughts and ideas and does not involve any kind of experimentation. Empirical research, on the other hand, works with provable data and hard evidence.

What is the difference between empirical vs applied research?

Some scientists may use these two terms interchangeably however, there is a difference between them. Applied research involves applying theories to solve real-life problems. On the other hand, empirical research involves the obtaining and analysis of data to test hypotheses and theories.

• Final words

Empirical research is a good means when the goal of your study is to find concrete data to go with. You may need to do empirical research when you need to test a theory, establish causality, or need qualitative/quantitative data. For example, you are a scientist and want to know if certain colors have an effect on people’s moods, or you are a marketer and want to test your theory on ad places on websites. 

In both scenarios, you can collect information by using empirical research methods and make informed decisions afterward. These are just the two of empirical research examples. This research type can be applied to many areas of work life and social sciences. Lastly, for all your research needs, you can visit forms.app to use its many useful features and over 1000 form and survey templates!

Defne is a content writer at forms.app. She is also a translator specializing in literary translation. Defne loves reading, writing, and translating professionally and as a hobby. Her expertise lies in survey research, research methodologies, content writing, and translation.

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Empirical research in the social sciences and education.

• What is Empirical Research and How to Read It
• Finding Empirical Research in Library Databases
• Designing Empirical Research
• Ethics, Cultural Responsiveness, and Anti-Racism in Research
• Citing, Writing, and Presenting Your Work

Contact the Librarian at your campus for more help!

Introduction: What is Empirical Research?

Empirical research is based on observed and measured phenomena and derives knowledge from actual experience rather than from theory or belief. 

How do you know if a study is empirical? Read the subheadings within the article, book, or report and look for a description of the research "methodology."  Ask yourself: Could I recreate this study and test these results?

Key characteristics to look for:

• Specific research questions to be answered
• Definition of the population, behavior, or phenomena being studied
• Description of the process used to study this population or phenomena, including selection criteria, controls, and testing instruments (such as surveys)

Another hint: some scholarly journals use a specific layout, called the "IMRaD" format, to communicate empirical research findings. Such articles typically have 4 components:

• Introduction: sometimes called "literature review" -- what is currently known about the topic -- usually includes a theoretical framework and/or discussion of previous studies
• Methodology: sometimes called "research design" -- how to recreate the study -- usually describes the population, research process, and analytical tools used in the present study
• Results: sometimes called "findings" -- what was learned through the study -- usually appears as statistical data or as substantial quotations from research participants
• Discussion: sometimes called "conclusion" or "implications" -- why the study is important -- usually describes how the research results influence professional practices or future studies

Reading and Evaluating Scholarly Materials

Reading research can be a challenge. However, the tutorials and videos below can help. They explain what scholarly articles look like, how to read them, and how to evaluate them:

• CRAAP Checklist A frequently-used checklist that helps you examine the currency, relevance, authority, accuracy, and purpose of an information source.
• IF I APPLY A newer model of evaluating sources which encourages you to think about your own biases as a reader, as well as concerns about the item you are reading.
• Credo Video: How to Read Scholarly Materials (4 min.)
• Credo Tutorial: How to Read Scholarly Materials
• Credo Tutorial: Evaluating Information
• Credo Video: Evaluating Statistics (4 min.)
• Credo Tutorial: Evaluating for Diverse Points of View
• Next: Finding Empirical Research in Library Databases >>
• Last Updated: Aug 13, 2024 3:16 PM
• URL: https://guides.libraries.psu.edu/emp

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• Research Guides

Empirical Research: Defining, Identifying, & Finding

Defining empirical research, what is empirical research, quantitative or qualitative.

• Introduction
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Calfee & Chambliss (2005)  (UofM login required) describe empirical research as a "systematic approach for answering certain types of questions."  Those questions are answered "[t]hrough the collection of evidence under carefully defined and replicable conditions" (p. 43). 

The evidence collected during empirical research is often referred to as "data." 

Characteristics of Empirical Research

Emerald Publishing's guide to conducting empirical research identifies a number of common elements to empirical research: 

• A  research question , which will determine research objectives.
• A particular and planned  design  for the research, which will depend on the question and which will find ways of answering it with appropriate use of resources.
• The gathering of  primary data , which is then analysed.
• A particular  methodology  for collecting and analysing the data, such as an experiment or survey.
• The limitation of the data to a particular group, area or time scale, known as a sample [emphasis added]: for example, a specific number of employees of a particular company type, or all users of a library over a given time scale. The sample should be somehow representative of a wider population.
• The ability to  recreate  the study and test the results. This is known as  reliability .
• The ability to  generalize  from the findings to a larger sample and to other situations.

If you see these elements in a research article, you can feel confident that you have found empirical research. Emerald's guide goes into more detail on each element. 

Empirical research methodologies can be described as quantitative, qualitative, or a mix of both (usually called mixed-methods).

Ruane (2016)  (UofM login required) gets at the basic differences in approach between quantitative and qualitative research:

• Quantitative research  -- an approach to documenting reality that relies heavily on numbers both for the measurement of variables and for data analysis (p. 33).
• Qualitative research  -- an approach to documenting reality that relies on words and images as the primary data source (p. 33).

Both quantitative and qualitative methods are empirical . If you can recognize that a research study is quantitative or qualitative study, then you have also recognized that it is empirical study. 

Below are information on the characteristics of quantitative and qualitative research. This video from Scribbr also offers a good overall introduction to the two approaches to research methodology: 

Characteristics of Quantitative Research 

Researchers test hypotheses, or theories, based in assumptions about causality, i.e. we expect variable X to cause variable Y. Variables have to be controlled as much as possible to ensure validity. The results explain the relationship between the variables. Measures are based in pre-defined instruments.

Examples: experimental or quasi-experimental design, pretest & post-test, survey or questionnaire with closed-ended questions. Studies that identify factors that influence an outcomes, the utility of an intervention, or understanding predictors of outcomes. 

Characteristics of Qualitative Research

Researchers explore “meaning individuals or groups ascribe to social or human problems (Creswell & Creswell, 2018, p3).” Questions and procedures emerge rather than being prescribed. Complexity, nuance, and individual meaning are valued. Research is both inductive and deductive. Data sources are multiple and varied, i.e. interviews, observations, documents, photographs, etc. The researcher is a key instrument and must be reflective of their background, culture, and experiences as influential of the research.

Examples: open question interviews and surveys, focus groups, case studies, grounded theory, ethnography, discourse analysis, narrative, phenomenology, participatory action research.

Calfee, R. C. & Chambliss, M. (2005). The design of empirical research. In J. Flood, D. Lapp, J. R. Squire, & J. Jensen (Eds.),  Methods of research on teaching the English language arts: The methodology chapters from the handbook of research on teaching the English language arts (pp. 43-78). Routledge.  http://ezproxy.memphis.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=125955&site=eds-live&scope=site .

Creswell, J. W., & Creswell, J. D. (2018).  Research design: Qualitative, quantitative, and mixed methods approaches  (5th ed.). Thousand Oaks: Sage.

How to... conduct empirical research . (n.d.). Emerald Publishing.  https://www.emeraldgrouppublishing.com/how-to/research-methods/conduct-empirical-research .

Scribbr. (2019). Quantitative vs. qualitative: The differences explained  [video]. YouTube.  https://www.youtube.com/watch?v=a-XtVF7Bofg .

Ruane, J. M. (2016).  Introducing social research methods : Essentials for getting the edge . Wiley-Blackwell.  http://ezproxy.memphis.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=1107215&site=eds-live&scope=site .  

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Methodology or method? A critical review of qualitative case study reports

Despite on-going debate about credibility, and reported limitations in comparison to other approaches, case study is an increasingly popular approach among qualitative researchers. We critically analysed the methodological descriptions of published case studies. Three high-impact qualitative methods journals were searched to locate case studies published in the past 5 years; 34 were selected for analysis. Articles were categorized as health and health services ( n= 12), social sciences and anthropology ( n= 7), or methods ( n= 15) case studies. The articles were reviewed using an adapted version of established criteria to determine whether adequate methodological justification was present, and if study aims, methods, and reported findings were consistent with a qualitative case study approach. Findings were grouped into five themes outlining key methodological issues: case study methodology or method, case of something particular and case selection, contextually bound case study, researcher and case interactions and triangulation, and study design inconsistent with methodology reported. Improved reporting of case studies by qualitative researchers will advance the methodology for the benefit of researchers and practitioners.

Case study research is an increasingly popular approach among qualitative researchers (Thomas, 2011 ). Several prominent authors have contributed to methodological developments, which has increased the popularity of case study approaches across disciplines (Creswell, 2013b ; Denzin & Lincoln, 2011b ; Merriam, 2009 ; Ragin & Becker, 1992 ; Stake, 1995 ; Yin, 2009 ). Current qualitative case study approaches are shaped by paradigm, study design, and selection of methods, and, as a result, case studies in the published literature vary. Differences between published case studies can make it difficult for researchers to define and understand case study as a methodology.

Experienced qualitative researchers have identified case study research as a stand-alone qualitative approach (Denzin & Lincoln, 2011b ). Case study research has a level of flexibility that is not readily offered by other qualitative approaches such as grounded theory or phenomenology. Case studies are designed to suit the case and research question and published case studies demonstrate wide diversity in study design. There are two popular case study approaches in qualitative research. The first, proposed by Stake ( 1995 ) and Merriam ( 2009 ), is situated in a social constructivist paradigm, whereas the second, by Yin ( 2012 ), Flyvbjerg ( 2011 ), and Eisenhardt ( 1989 ), approaches case study from a post-positivist viewpoint. Scholarship from both schools of inquiry has contributed to the popularity of case study and development of theoretical frameworks and principles that characterize the methodology.

The diversity of case studies reported in the published literature, and on-going debates about credibility and the use of case study in qualitative research practice, suggests that differences in perspectives on case study methodology may prevent researchers from developing a mutual understanding of practice and rigour. In addition, discussion about case study limitations has led some authors to query whether case study is indeed a methodology (Luck, Jackson, & Usher, 2006 ; Meyer, 2001 ; Thomas, 2010 ; Tight, 2010 ). Methodological discussion of qualitative case study research is timely, and a review is required to analyse and understand how this methodology is applied in the qualitative research literature. The aims of this study were to review methodological descriptions of published qualitative case studies, to review how the case study methodological approach was applied, and to identify issues that need to be addressed by researchers, editors, and reviewers. An outline of the current definitions of case study and an overview of the issues proposed in the qualitative methodological literature are provided to set the scene for the review.

Definitions of qualitative case study research

Case study research is an investigation and analysis of a single or collective case, intended to capture the complexity of the object of study (Stake, 1995 ). Qualitative case study research, as described by Stake ( 1995 ), draws together “naturalistic, holistic, ethnographic, phenomenological, and biographic research methods” in a bricoleur design, or in his words, “a palette of methods” (Stake, 1995 , pp. xi–xii). Case study methodology maintains deep connections to core values and intentions and is “particularistic, descriptive and heuristic” (Merriam, 2009 , p. 46).

As a study design, case study is defined by interest in individual cases rather than the methods of inquiry used. The selection of methods is informed by researcher and case intuition and makes use of naturally occurring sources of knowledge, such as people or observations of interactions that occur in the physical space (Stake, 1998 ). Thomas ( 2011 ) suggested that “analytical eclecticism” is a defining factor (p. 512). Multiple data collection and analysis methods are adopted to further develop and understand the case, shaped by context and emergent data (Stake, 1995 ). This qualitative approach “explores a real-life, contemporary bounded system (a case ) or multiple bounded systems (cases) over time, through detailed, in-depth data collection involving multiple sources of information … and reports a case description and case themes ” (Creswell, 2013b , p. 97). Case study research has been defined by the unit of analysis, the process of study, and the outcome or end product, all essentially the case (Merriam, 2009 ).

The case is an object to be studied for an identified reason that is peculiar or particular. Classification of the case and case selection procedures informs development of the study design and clarifies the research question. Stake ( 1995 ) proposed three types of cases and study design frameworks. These include the intrinsic case, the instrumental case, and the collective instrumental case. The intrinsic case is used to understand the particulars of a single case, rather than what it represents. An instrumental case study provides insight on an issue or is used to refine theory. The case is selected to advance understanding of the object of interest. A collective refers to an instrumental case which is studied as multiple, nested cases, observed in unison, parallel, or sequential order. More than one case can be simultaneously studied; however, each case study is a concentrated, single inquiry, studied holistically in its own entirety (Stake, 1995 , 1998 ).

Researchers who use case study are urged to seek out what is common and what is particular about the case. This involves careful and in-depth consideration of the nature of the case, historical background, physical setting, and other institutional and political contextual factors (Stake, 1998 ). An interpretive or social constructivist approach to qualitative case study research supports a transactional method of inquiry, where the researcher has a personal interaction with the case. The case is developed in a relationship between the researcher and informants, and presented to engage the reader, inviting them to join in this interaction and in case discovery (Stake, 1995 ). A postpositivist approach to case study involves developing a clear case study protocol with careful consideration of validity and potential bias, which might involve an exploratory or pilot phase, and ensures that all elements of the case are measured and adequately described (Yin, 2009 , 2012 ).

Current methodological issues in qualitative case study research

The future of qualitative research will be influenced and constructed by the way research is conducted, and by what is reviewed and published in academic journals (Morse, 2011 ). If case study research is to further develop as a principal qualitative methodological approach, and make a valued contribution to the field of qualitative inquiry, issues related to methodological credibility must be considered. Researchers are required to demonstrate rigour through adequate descriptions of methodological foundations. Case studies published without sufficient detail for the reader to understand the study design, and without rationale for key methodological decisions, may lead to research being interpreted as lacking in quality or credibility (Hallberg, 2013 ; Morse, 2011 ).

There is a level of artistic license that is embraced by qualitative researchers and distinguishes practice, which nurtures creativity, innovation, and reflexivity (Denzin & Lincoln, 2011b ; Morse, 2009 ). Qualitative research is “inherently multimethod” (Denzin & Lincoln, 2011a , p. 5); however, with this creative freedom, it is important for researchers to provide adequate description for methodological justification (Meyer, 2001 ). This includes paradigm and theoretical perspectives that have influenced study design. Without adequate description, study design might not be understood by the reader, and can appear to be dishonest or inaccurate. Reviewers and readers might be confused by the inconsistent or inappropriate terms used to describe case study research approach and methods, and be distracted from important study findings (Sandelowski, 2000 ). This issue extends beyond case study research, and others have noted inconsistencies in reporting of methodology and method by qualitative researchers. Sandelowski ( 2000 , 2010 ) argued for accurate identification of qualitative description as a research approach. She recommended that the selected methodology should be harmonious with the study design, and be reflected in methods and analysis techniques. Similarly, Webb and Kevern ( 2000 ) uncovered inconsistencies in qualitative nursing research with focus group methods, recommending that methodological procedures must cite seminal authors and be applied with respect to the selected theoretical framework. Incorrect labelling using case study might stem from the flexibility in case study design and non-directional character relative to other approaches (Rosenberg & Yates, 2007 ). Methodological integrity is required in design of qualitative studies, including case study, to ensure study rigour and to enhance credibility of the field (Morse, 2011 ).

Case study has been unnecessarily devalued by comparisons with statistical methods (Eisenhardt, 1989 ; Flyvbjerg, 2006 , 2011 ; Jensen & Rodgers, 2001 ; Piekkari, Welch, & Paavilainen, 2009 ; Tight, 2010 ; Yin, 1999 ). It is reputed to be the “the weak sibling” in comparison to other, more rigorous, approaches (Yin, 2009 , p. xiii). Case study is not an inherently comparative approach to research. The objective is not statistical research, and the aim is not to produce outcomes that are generalizable to all populations (Thomas, 2011 ). Comparisons between case study and statistical research do little to advance this qualitative approach, and fail to recognize its inherent value, which can be better understood from the interpretive or social constructionist viewpoint of other authors (Merriam, 2009 ; Stake, 1995 ). Building on discussions relating to “fuzzy” (Bassey, 2001 ), or naturalistic generalizations (Stake, 1978 ), or transference of concepts and theories (Ayres, Kavanaugh, & Knafl, 2003 ; Morse et al., 2011 ) would have more relevance.

Case study research has been used as a catch-all design to justify or add weight to fundamental qualitative descriptive studies that do not fit with other traditional frameworks (Merriam, 2009 ). A case study has been a “convenient label for our research—when we ‘can't think of anything ‘better”—in an attempt to give it [qualitative methodology] some added respectability” (Tight, 2010 , p. 337). Qualitative case study research is a pliable approach (Merriam, 2009 ; Meyer, 2001 ; Stake, 1995 ), and has been likened to a “curious methodological limbo” (Gerring, 2004 , p. 341) or “paradigmatic bridge” (Luck et al., 2006 , p. 104), that is on the borderline between postpositivist and constructionist interpretations. This has resulted in inconsistency in application, which indicates that flexibility comes with limitations (Meyer, 2001 ), and the open nature of case study research might be off-putting to novice researchers (Thomas, 2011 ). The development of a well-(in)formed theoretical framework to guide a case study should improve consistency, rigour, and trust in studies published in qualitative research journals (Meyer, 2001 ).

Assessment of rigour

The purpose of this study was to analyse the methodological descriptions of case studies published in qualitative methods journals. To do this we needed to develop a suitable framework, which used existing, established criteria for appraising qualitative case study research rigour (Creswell, 2013b ; Merriam, 2009 ; Stake, 1995 ). A number of qualitative authors have developed concepts and criteria that are used to determine whether a study is rigorous (Denzin & Lincoln, 2011b ; Lincoln, 1995 ; Sandelowski & Barroso, 2002 ). The criteria proposed by Stake ( 1995 ) provide a framework for readers and reviewers to make judgements regarding case study quality, and identify key characteristics essential for good methodological rigour. Although each of the factors listed in Stake's criteria could enhance the quality of a qualitative research report, in Table I we present an adapted criteria used in this study, which integrates more recent work by Merriam ( 2009 ) and Creswell ( 2013b ). Stake's ( 1995 ) original criteria were separated into two categories. The first list of general criteria is “relevant for all qualitative research.” The second list, “high relevance to qualitative case study research,” was the criteria that we decided had higher relevance to case study research. This second list was the main criteria used to assess the methodological descriptions of the case studies reviewed. The complete table has been preserved so that the reader can determine how the original criteria were adapted.

Framework for assessing quality in qualitative case study research.

Adapted from Stake ( 1995 , p. 131).

Study design

The critical review method described by Grant and Booth ( 2009 ) was used, which is appropriate for the assessment of research quality, and is used for literature analysis to inform research and practice. This type of review goes beyond the mapping and description of scoping or rapid reviews, to include “analysis and conceptual innovation” (Grant & Booth, 2009 , p. 93). A critical review is used to develop existing, or produce new, hypotheses or models. This is different to systematic reviews that answer clinical questions. It is used to evaluate existing research and competing ideas, to provide a “launch pad” for conceptual development and “subsequent testing” (Grant & Booth, 2009 , p. 93).

Qualitative methods journals were located by a search of the 2011 ISI Journal Citation Reports in Social Science, via the database Web of Knowledge (see m.webofknowledge.com). No “qualitative research methods” category existed in the citation reports; therefore, a search of all categories was performed using the term “qualitative.” In Table II , we present the qualitative methods journals located, ranked by impact factor. The highest ranked journals were selected for searching. We acknowledge that the impact factor ranking system might not be the best measure of journal quality (Cheek, Garnham, & Quan, 2006 ); however, this was the most appropriate and accessible method available.

International Journal of Qualitative Studies on Health and Well-being.

Search strategy

In March 2013, searches of the journals, Qualitative Health Research , Qualitative Research , and Qualitative Inquiry were completed to retrieve studies with “case study” in the abstract field. The search was limited to the past 5 years (1 January 2008 to 1 March 2013). The objective was to locate published qualitative case studies suitable for assessment using the adapted criterion. Viewpoints, commentaries, and other article types were excluded from review. Title and abstracts of the 45 retrieved articles were read by the first author, who identified 34 empirical case studies for review. All authors reviewed the 34 studies to confirm selection and categorization. In Table III , we present the 34 case studies grouped by journal, and categorized by research topic, including health sciences, social sciences and anthropology, and methods research. There was a discrepancy in categorization of one article on pedagogy and a new teaching method published in Qualitative Inquiry (Jorrín-Abellán, Rubia-Avi, Anguita-Martínez, Gómez-Sánchez, & Martínez-Mones, 2008 ). Consensus was to allocate to the methods category.

Outcomes of search of qualitative methods journals.

In Table III , the number of studies located, and final numbers selected for review have been reported. Qualitative Health Research published the most empirical case studies ( n= 16). In the health category, there were 12 case studies of health conditions, health services, and health policy issues, all published in Qualitative Health Research . Seven case studies were categorized as social sciences and anthropology research, which combined case study with biography and ethnography methodologies. All three journals published case studies on methods research to illustrate a data collection or analysis technique, methodological procedure, or related issue.

The methodological descriptions of 34 case studies were critically reviewed using the adapted criteria. All articles reviewed contained a description of study methods; however, the length, amount of detail, and position of the description in the article varied. Few studies provided an accurate description and rationale for using a qualitative case study approach. In the 34 case studies reviewed, three described a theoretical framework informed by Stake ( 1995 ), two by Yin ( 2009 ), and three provided a mixed framework informed by various authors, which might have included both Yin and Stake. Few studies described their case study design, or included a rationale that explained why they excluded or added further procedures, and whether this was to enhance the study design, or to better suit the research question. In 26 of the studies no reference was provided to principal case study authors. From reviewing the description of methods, few authors provided a description or justification of case study methodology that demonstrated how their study was informed by the methodological literature that exists on this approach.

The methodological descriptions of each study were reviewed using the adapted criteria, and the following issues were identified: case study methodology or method; case of something particular and case selection; contextually bound case study; researcher and case interactions and triangulation; and, study design inconsistent with methodology. An outline of how the issues were developed from the critical review is provided, followed by a discussion of how these relate to the current methodological literature.

Case study methodology or method

A third of the case studies reviewed appeared to use a case report method, not case study methodology as described by principal authors (Creswell, 2013b ; Merriam, 2009 ; Stake, 1995 ; Yin, 2009 ). Case studies were identified as a case report because of missing methodological detail and by review of the study aims and purpose. These reports presented data for small samples of no more than three people, places or phenomenon. Four studies, or “case reports” were single cases selected retrospectively from larger studies (Bronken, Kirkevold, Martinsen, & Kvigne, 2012 ; Coltart & Henwood, 2012 ; Hooghe, Neimeyer, & Rober, 2012 ; Roscigno et al., 2012 ). Case reports were not a case of something, instead were a case demonstration or an example presented in a report. These reports presented outcomes, and reported on how the case could be generalized. Descriptions focussed on the phenomena, rather than the case itself, and did not appear to study the case in its entirety.

Case reports had minimal in-text references to case study methodology, and were informed by other qualitative traditions or secondary sources (Adamson & Holloway, 2012 ; Buzzanell & D'Enbeau, 2009 ; Nagar-Ron & Motzafi-Haller, 2011 ). This does not suggest that case study methodology cannot be multimethod, however, methodology should be consistent in design, be clearly described (Meyer, 2001 ; Stake, 1995 ), and maintain focus on the case (Creswell, 2013b ).

To demonstrate how case reports were identified, three examples are provided. The first, Yeh ( 2013 ) described their study as, “the examination of the emergence of vegetarianism in Victorian England serves as a case study to reveal the relationships between boundaries and entities” (p. 306). The findings were a historical case report, which resulted from an ethnographic study of vegetarianism. Cunsolo Willox, Harper, Edge, ‘My Word’: Storytelling and Digital Media Lab, and Rigolet Inuit Community Government (2013) used “a case study that illustrates the usage of digital storytelling within an Inuit community” (p. 130). This case study reported how digital storytelling can be used with indigenous communities as a participatory method to illuminate the benefits of this method for other studies. This “case study was conducted in the Inuit community” but did not include the Inuit community in case analysis (Cunsolo Willox et al., 2013 , p. 130). Bronken et al. ( 2012 ) provided a single case report to demonstrate issues observed in a larger clinical study of aphasia and stroke, without adequate case description or analysis.

Case study of something particular and case selection

Case selection is a precursor to case analysis, which needs to be presented as a convincing argument (Merriam, 2009 ). Descriptions of the case were often not adequate to ascertain why the case was selected, or whether it was a particular exemplar or outlier (Thomas, 2011 ). In a number of case studies in the health and social science categories, it was not explicit whether the case was of something particular, or peculiar to their discipline or field (Adamson & Holloway, 2012 ; Bronken et al., 2012 ; Colón-Emeric et al., 2010 ; Jackson, Botelho, Welch, Joseph, & Tennstedt, 2012 ; Mawn et al., 2010 ; Snyder-Young, 2011 ). There were exceptions in the methods category ( Table III ), where cases were selected by researchers to report on a new or innovative method. The cases emerged through heuristic study, and were reported to be particular, relative to the existing methods literature (Ajodhia-Andrews & Berman, 2009 ; Buckley & Waring, 2013 ; Cunsolo Willox et al., 2013 ; De Haene, Grietens, & Verschueren, 2010 ; Gratton & O'Donnell, 2011 ; Sumsion, 2013 ; Wimpenny & Savin-Baden, 2012 ).

Case selection processes were sometimes insufficient to understand why the case was selected from the global population of cases, or what study of this case would contribute to knowledge as compared with other possible cases (Adamson & Holloway, 2012 ; Bronken et al., 2012 ; Colón-Emeric et al., 2010 ; Jackson et al., 2012 ; Mawn et al., 2010 ). In two studies, local cases were selected (Barone, 2010 ; Fourie & Theron, 2012 ) because the researcher was familiar with and had access to the case. Possible limitations of a convenience sample were not acknowledged. Purposeful sampling was used to recruit participants within the case of one study, but not of the case itself (Gallagher et al., 2013 ). Random sampling was completed for case selection in two studies (Colón-Emeric et al., 2010 ; Jackson et al., 2012 ), which has limited meaning in interpretive qualitative research.

To demonstrate how researchers provided a good justification for the selection of case study approaches, four examples are provided. The first, cases of residential care homes, were selected because of reported occurrences of mistreatment, which included residents being locked in rooms at night (Rytterström, Unosson, & Arman, 2013 ). Roscigno et al. ( 2012 ) selected cases of parents who were admitted for early hospitalization in neonatal intensive care with a threatened preterm delivery before 26 weeks. Hooghe et al. ( 2012 ) used random sampling to select 20 couples that had experienced the death of a child; however, the case study was of one couple and a particular metaphor described only by them. The final example, Coltart and Henwood ( 2012 ), provided a detailed account of how they selected two cases from a sample of 46 fathers based on personal characteristics and beliefs. They described how the analysis of the two cases would contribute to their larger study on first time fathers and parenting.

Contextually bound case study

The limits or boundaries of the case are a defining factor of case study methodology (Merriam, 2009 ; Ragin & Becker, 1992 ; Stake, 1995 ; Yin, 2009 ). Adequate contextual description is required to understand the setting or context in which the case is revealed. In the health category, case studies were used to illustrate a clinical phenomenon or issue such as compliance and health behaviour (Colón-Emeric et al., 2010 ; D'Enbeau, Buzzanell, & Duckworth, 2010 ; Gallagher et al., 2013 ; Hooghe et al., 2012 ; Jackson et al., 2012 ; Roscigno et al., 2012 ). In these case studies, contextual boundaries, such as physical and institutional descriptions, were not sufficient to understand the case as a holistic system, for example, the general practitioner (GP) clinic in Gallagher et al. ( 2013 ), or the nursing home in Colón-Emeric et al. ( 2010 ). Similarly, in the social science and methods categories, attention was paid to some components of the case context, but not others, missing important information required to understand the case as a holistic system (Alexander, Moreira, & Kumar, 2012 ; Buzzanell & D'Enbeau, 2009 ; Nairn & Panelli, 2009 ; Wimpenny & Savin-Baden, 2012 ).

In two studies, vicarious experience or vignettes (Nairn & Panelli, 2009 ) and images (Jorrín-Abellán et al., 2008 ) were effective to support description of context, and might have been a useful addition for other case studies. Missing contextual boundaries suggests that the case might not be adequately defined. Additional information, such as the physical, institutional, political, and community context, would improve understanding of the case (Stake, 1998 ). In Boxes 1 and 2 , we present brief synopses of two studies that were reviewed, which demonstrated a well bounded case. In Box 1 , Ledderer ( 2011 ) used a qualitative case study design informed by Stake's tradition. In Box 2 , Gillard, Witt, and Watts ( 2011 ) were informed by Yin's tradition. By providing a brief outline of the case studies in Boxes 1 and 2 , we demonstrate how effective case boundaries can be constructed and reported, which may be of particular interest to prospective case study researchers.

Article synopsis of case study research using Stake's tradition

Ledderer ( 2011 ) used a qualitative case study research design, informed by modern ethnography. The study is bounded to 10 general practice clinics in Denmark, who had received federal funding to implement preventative care services based on a Motivational Interviewing intervention. The researcher question focussed on “why is it so difficult to create change in medical practice?” (Ledderer, 2011 , p. 27). The study context was adequately described, providing detail on the general practitioner (GP) clinics and relevant political and economic influences. Methodological decisions are described in first person narrative, providing insight on researcher perspectives and interaction with the case. Forty-four interviews were conducted, which focussed on how GPs conducted consultations, and the form, nature and content, rather than asking their opinion or experience (Ledderer, 2011 , p. 30). The duration and intensity of researcher immersion in the case enhanced depth of description and trustworthiness of study findings. Analysis was consistent with Stake's tradition, and the researcher provided examples of inquiry techniques used to challenge assumptions about emerging themes. Several other seminal qualitative works were cited. The themes and typology constructed are rich in narrative data and storytelling by clinic staff, demonstrating individual clinic experiences as well as shared meanings and understandings about changing from a biomedical to psychological approach to preventative health intervention. Conclusions make note of social and cultural meanings and lessons learned, which might not have been uncovered using a different methodology.

Article synopsis of case study research using Yin's tradition

Gillard et al. ( 2011 ) study of camps for adolescents living with HIV/AIDs provided a good example of Yin's interpretive case study approach. The context of the case is bounded by the three summer camps of which the researchers had prior professional involvement. A case study protocol was developed that used multiple methods to gather information at three data collection points coinciding with three youth camps (Teen Forum, Discover Camp, and Camp Strong). Gillard and colleagues followed Yin's ( 2009 ) principles, using a consistent data protocol that enhanced cross-case analysis. Data described the young people, the camp physical environment, camp schedule, objectives and outcomes, and the staff of three youth camps. The findings provided a detailed description of the context, with less detail of individual participants, including insight into researcher's interpretations and methodological decisions throughout the data collection and analysis process. Findings provided the reader with a sense of “being there,” and are discovered through constant comparison of the case with the research issues; the case is the unit of analysis. There is evidence of researcher immersion in the case, and Gillard reports spending significant time in the field in a naturalistic and integrated youth mentor role.

This case study is not intended to have a significant impact on broader health policy, although does have implications for health professionals working with adolescents. Study conclusions will inform future camps for young people with chronic disease, and practitioners are able to compare similarities between this case and their own practice (for knowledge translation). No limitations of this article were reported. Limitations related to publication of this case study were that it was 20 pages long and used three tables to provide sufficient description of the camp and program components, and relationships with the research issue.

Researcher and case interactions and triangulation

Researcher and case interactions and transactions are a defining feature of case study methodology (Stake, 1995 ). Narrative stories, vignettes, and thick description are used to provoke vicarious experience and a sense of being there with the researcher in their interaction with the case. Few of the case studies reviewed provided details of the researcher's relationship with the case, researcher–case interactions, and how these influenced the development of the case study (Buzzanell & D'Enbeau, 2009 ; D'Enbeau et al., 2010 ; Gallagher et al., 2013 ; Gillard et al., 2011 ; Ledderer, 2011 ; Nagar-Ron & Motzafi-Haller, 2011 ). The role and position of the researcher needed to be self-examined and understood by readers, to understand how this influenced interactions with participants, and to determine what triangulation is needed (Merriam, 2009 ; Stake, 1995 ).

Gillard et al. ( 2011 ) provided a good example of triangulation, comparing data sources in a table (p. 1513). Triangulation of sources was used to reveal as much depth as possible in the study by Nagar-Ron and Motzafi-Haller ( 2011 ), while also enhancing confirmation validity. There were several case studies that would have benefited from improved range and use of data sources, and descriptions of researcher–case interactions (Ajodhia-Andrews & Berman, 2009 ; Bronken et al., 2012 ; Fincham, Scourfield, & Langer, 2008 ; Fourie & Theron, 2012 ; Hooghe et al., 2012 ; Snyder-Young, 2011 ; Yeh, 2013 ).

Study design inconsistent with methodology

Good, rigorous case studies require a strong methodological justification (Meyer, 2001 ) and a logical and coherent argument that defines paradigm, methodological position, and selection of study methods (Denzin & Lincoln, 2011b ). Methodological justification was insufficient in several of the studies reviewed (Barone, 2010 ; Bronken et al., 2012 ; Hooghe et al., 2012 ; Mawn et al., 2010 ; Roscigno et al., 2012 ; Yeh, 2013 ). This was judged by the absence, or inadequate or inconsistent reference to case study methodology in-text.

In six studies, the methodological justification provided did not relate to case study. There were common issues identified. Secondary sources were used as primary methodological references indicating that study design might not have been theoretically sound (Colón-Emeric et al., 2010 ; Coltart & Henwood, 2012 ; Roscigno et al., 2012 ; Snyder-Young, 2011 ). Authors and sources cited in methodological descriptions were inconsistent with the actual study design and practices used (Fourie & Theron, 2012 ; Hooghe et al., 2012 ; Jorrín-Abellán et al., 2008 ; Mawn et al., 2010 ; Rytterström et al., 2013 ; Wimpenny & Savin-Baden, 2012 ). This occurred when researchers cited Stake or Yin, or both (Mawn et al., 2010 ; Rytterström et al., 2013 ), although did not follow their paradigmatic or methodological approach. In 26 studies there were no citations for a case study methodological approach.

The findings of this study have highlighted a number of issues for researchers. A considerable number of case studies reviewed were missing key elements that define qualitative case study methodology and the tradition cited. A significant number of studies did not provide a clear methodological description or justification relevant to case study. Case studies in health and social sciences did not provide sufficient information for the reader to understand case selection, and why this case was chosen above others. The context of the cases were not described in adequate detail to understand all relevant elements of the case context, which indicated that cases may have not been contextually bounded. There were inconsistencies between reported methodology, study design, and paradigmatic approach in case studies reviewed, which made it difficult to understand the study methodology and theoretical foundations. These issues have implications for methodological integrity and honesty when reporting study design, which are values of the qualitative research tradition and are ethical requirements (Wager & Kleinert, 2010a ). Poorly described methodological descriptions may lead the reader to misinterpret or discredit study findings, which limits the impact of the study, and, as a collective, hinders advancements in the broader qualitative research field.

The issues highlighted in our review build on current debates in the case study literature, and queries about the value of this methodology. Case study research can be situated within different paradigms or designed with an array of methods. In order to maintain the creativity and flexibility that is valued in this methodology, clearer descriptions of paradigm and theoretical position and methods should be provided so that study findings are not undervalued or discredited. Case study research is an interdisciplinary practice, which means that clear methodological descriptions might be more important for this approach than other methodologies that are predominantly driven by fewer disciplines (Creswell, 2013b ).

Authors frequently omit elements of methodologies and include others to strengthen study design, and we do not propose a rigid or purist ideology in this paper. On the contrary, we encourage new ideas about using case study, together with adequate reporting, which will advance the value and practice of case study. The implications of unclear methodological descriptions in the studies reviewed were that study design appeared to be inconsistent with reported methodology, and key elements required for making judgements of rigour were missing. It was not clear whether the deviations from methodological tradition were made by researchers to strengthen the study design, or because of misinterpretations. Morse ( 2011 ) recommended that innovations and deviations from practice are best made by experienced researchers, and that a novice might be unaware of the issues involved with making these changes. To perpetuate the tradition of case study research, applications in the published literature should have consistencies with traditional methodological constructions, and deviations should be described with a rationale that is inherent in study conduct and findings. Providing methodological descriptions that demonstrate a strong theoretical foundation and coherent study design will add credibility to the study, while ensuring the intrinsic meaning of case study is maintained.

The value of this review is that it contributes to discussion of whether case study is a methodology or method. We propose possible reasons why researchers might make this misinterpretation. Researchers may interchange the terms methods and methodology, and conduct research without adequate attention to epistemology and historical tradition (Carter & Little, 2007 ; Sandelowski, 2010 ). If the rich meaning that naming a qualitative methodology brings to the study is not recognized, a case study might appear to be inconsistent with the traditional approaches described by principal authors (Creswell, 2013a ; Merriam, 2009 ; Stake, 1995 ; Yin, 2009 ). If case studies are not methodologically and theoretically situated, then they might appear to be a case report.

Case reports are promoted by university and medical journals as a method of reporting on medical or scientific cases; guidelines for case reports are publicly available on websites ( http://www.hopkinsmedicine.org/institutional_review_board/guidelines_policies/guidelines/case_report.html ). The various case report guidelines provide a general criteria for case reports, which describes that this form of report does not meet the criteria of research, is used for retrospective analysis of up to three clinical cases, and is primarily illustrative and for educational purposes. Case reports can be published in academic journals, but do not require approval from a human research ethics committee. Traditionally, case reports describe a single case, to explain how and what occurred in a selected setting, for example, to illustrate a new phenomenon that has emerged from a larger study. A case report is not necessarily particular or the study of a case in its entirety, and the larger study would usually be guided by a different research methodology.

This description of a case report is similar to what was provided in some studies reviewed. This form of report lacks methodological grounding and qualities of research rigour. The case report has publication value in demonstrating an example and for dissemination of knowledge (Flanagan, 1999 ). However, case reports have different meaning and purpose to case study, which needs to be distinguished. Findings of our review suggest that the medical understanding of a case report has been confused with qualitative case study approaches.

In this review, a number of case studies did not have methodological descriptions that included key characteristics of case study listed in the adapted criteria, and several issues have been discussed. There have been calls for improvements in publication quality of qualitative research (Morse, 2011 ), and for improvements in peer review of submitted manuscripts (Carter & Little, 2007 ; Jasper, Vaismoradi, Bondas, & Turunen, 2013 ). The challenging nature of editor and reviewers responsibilities are acknowledged in the literature (Hames, 2013 ; Wager & Kleinert, 2010b ); however, review of case study methodology should be prioritized because of disputes on methodological value.

Authors using case study approaches are recommended to describe their theoretical framework and methods clearly, and to seek and follow specialist methodological advice when needed (Wager & Kleinert, 2010a ). Adequate page space for case study description would contribute to better publications (Gillard et al., 2011 ). Capitalizing on the ability to publish complementary resources should be considered.

Limitations of the review

There is a level of subjectivity involved in this type of review and this should be considered when interpreting study findings. Qualitative methods journals were selected because the aims and scope of these journals are to publish studies that contribute to methodological discussion and development of qualitative research. Generalist health and social science journals were excluded that might have contained good quality case studies. Journals in business or education were also excluded, although a review of case studies in international business journals has been published elsewhere (Piekkari et al., 2009 ).

The criteria used to assess the quality of the case studies were a set of qualitative indicators. A numerical or ranking system might have resulted in different results. Stake's ( 1995 ) criteria have been referenced elsewhere, and was deemed the best available (Creswell, 2013b ; Crowe et al., 2011 ). Not all qualitative studies are reported in a consistent way and some authors choose to report findings in a narrative form in comparison to a typical biomedical report style (Sandelowski & Barroso, 2002 ), if misinterpretations were made this may have affected the review.

Case study research is an increasingly popular approach among qualitative researchers, which provides methodological flexibility through the incorporation of different paradigmatic positions, study designs, and methods. However, whereas flexibility can be an advantage, a myriad of different interpretations has resulted in critics questioning the use of case study as a methodology. Using an adaptation of established criteria, we aimed to identify and assess the methodological descriptions of case studies in high impact, qualitative methods journals. Few articles were identified that applied qualitative case study approaches as described by experts in case study design. There were inconsistencies in methodology and study design, which indicated that researchers were confused whether case study was a methodology or a method. Commonly, there appeared to be confusion between case studies and case reports. Without clear understanding and application of the principles and key elements of case study methodology, there is a risk that the flexibility of the approach will result in haphazard reporting, and will limit its global application as a valuable, theoretically supported methodology that can be rigorously applied across disciplines and fields.

Conflict of interest and funding

The authors have not received any funding or benefits from industry or elsewhere to conduct this study.

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Economic burden of patients with leading cancers in China: a cost-of-illness study

• Ziting Wu 1 , 2 , 3   na1 ,
• Yiwen Yu 4 , 5   na1 ,
• Feng Xie 6 , 7 ,
• Qiushi Chen 8 ,
• Zhong Cao 9 ,
• Simiao Chen 4 , 10 &
• Gordon G. Liu 1 , 2 , 3  

BMC Health Services Research volume  24 , Article number:  1135 ( 2024 ) Cite this article

Metrics details

China accounts for 24% of newly diagnosed cancer cases and 30% of cancer-related deaths worldwide. Comprehensive analyses of the economic burden on patients across different cancer treatment phases, based on empirical data, are lacking. This study aims to estimate the financial burden borne by patients and analyze the cost compositions of the leading cancers with the highest number of new cases in China.

This cross-sectional cost-of-illness study analyzed patients diagnosed with lung, breast, colorectal, esophageal, liver, or gastric cancer, identified through electronic health records (EHRs) from 84 hospitals across 17 provinces in China. Patients completed any one of the initial treatment phase, follow-up phase, and relapse/metastasis phase were recruited by trained attending physicians through a stratified sampling procedure to ensure enough cases for each cancer progression stage and cancer treatment phase. Direct and indirect costs by treatment phase were collected from the EHRs and self-reported surveys. We estimated per case cost for each type of cancer, and employed subgroup analyses and multiple linear regression models to explore cost drivers.

We recruited a total of 13,745 cancer patients across three treatment phases. The relapse/metastasis phase incurred the highest per case costs, varying from $8,890 to $14,572, while the follow-up phase was the least costly, ranging from $1,840 to $4,431. Being in the relapse/metastasis phase and having an advanced clinical stage of cancer at diagnosis were associated with significantly higher cost, while patients with low socioeconomic status borne lower costs.

Conclusions

There were substantial financial burden on patients with six leading cancers in China. Health policymakers should emphasize comprehensive healthcare coverage for marginalized populations such as the uninsured, less educated, and those living in underdeveloped regions.

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Cancer is the second leading cause of death globally, responsible for nearly 10 million deaths in 2020, accounting for nearly one in every six deaths [ 1 ]. Also, China accounted for 24% of newly diagnosed cases and 30% of cancer-related deaths worldwide [ 2 ]. The burden of cancer has been increasing in recent decades in China [ 3 ]. At the individual level, patients pay substantially high out-of-pocket expenses on cancer treatments which may lead to catastrophic impact on the entire family [ 4 ]. Cancer also imposes a substantial economic burden at the societal level. A previous modeling study found that China accounted for 24.1% of the global economic burden of cancer from 2020 to 2050, but the direct impact on patients and their families is less frequently highlighted [ 5 ].

Numerous studies have examined the economic burden borne by patients. For example, in the US, the out-of-pocket costs of thyroid cancer diagnosis and treatment ranged from $1,425 to $17,000 [ 6 ]. Globally, studies reported the average costs of metastatic colorectal cancer ranged from $12,346 to $293,461 [ 7 ], and the direct medical costs of lung cancer ranged from $4,484 to $45,364, reflecting significant financial demands on patients [ 8 ]. In China, nationwide studies have found that the overall average expenditure per case for esophageal cancer, liver cancer, colorectal cancer, lung cancer ranged from $3,000~$10,000 [ 9 , 10 , 11 , 12 , 13 ]. Another study reported the average costs for lung cancer, liver cancer, esophageal cancer, and stomach cancer between 1996 and 2006 as $1,418, $1,333, $1,307, and $1,411, respectively, again emphasizing the financial challenges faced by patients [ 14 ].

Despite these findings, significant variations in cost estimates among current studies likely arise due to differences in cancer types, clinical stages, and time frames considered. Moreover, these studies were mainly focused on direct medical cost [ 6 , 7 ], without accounting for the full spectrum of costs incurred by patients across different treatment phases [ 6 , 7 , 8 , 15 , 16 , 17 ]. Additionally, much of the cost data in China has been collected through patient self-reports, which raises concerns about the validity and reliability of these figures. Comprehensive data on patient-incurred costs, considering various cancer types, treatment phases, and clinical stages are currently unavailable. This lack of robust data limits our understanding of the true economic burden borne by patients and hinders efforts to develop effective financial support strategies [ 18 ].

To address these gaps, we conducted a cross-sectional study in 2021 ~ 2022 to estimate the comprehensive costs of cancer borne by patients in China. We focused on costs across different treatment phases for the six leading cancers, providing a clearer picture of the financial impact on patients and their families.

Study design and data collection

We adopted a societal perspective to evaluate the economic burden borne by individuals diagnosed with the six cancers with the highest number of new cases in China in 2020: lung (815,563 cases), colorectal (555,477 cases), gastric (478,508 cases), breast (416,371 cases), liver (410,038 cases), and esophageal (324,422 cases) cancer [ 19 ]. Our study aimed to capture financial strain on patients through a national survey conducted across hospitals in 17 provinces (North: Beijing, Shanxi, Inner Mongolia, Hebei; East: Shandong, Jiangxi, Jiangsu, Zhejiang, Anhui; Middle: Henan, Hubei, Hunan; West: Sichuan, Chongqing; South: Guangdong, Hainan, Guangxi). Please refer to Supplementary Table 1 for more details of the survey sites and the hospitals. Trained attending physicians recruited patients through a stratified sampling procedure to ensure enough cases for each cancer progression stage and cancer treatment phase. The cancer treatment phases were illustrated in Fig.  1 and the details of the sample sizes were in Supplementary Table 2 [ 20 ].

Diagram of Cancer Treatment Phases Division

Eligible patients must have completed one of the following phases between November 1, 2021, and December 31, 2022: (I) the initial treatment phase, which includes surgical interventions (Ia) or non-surgical treatment interventions (Ib). Phase Ib encompasses more conservative strategies, such as radiotherapy, chemotherapy, palliative care, and traditional Chinese medicine, used when surgery is not applicable; (II) the follow-up phase, defined as the 5-year period following initial treatment, where patients who experienced no cancer relapse or metastasis for more than 5 years are considered cancer-free; and (III) the relapse/metastasis phase, during which patients experience cancer progression, relapse, or metastasis. Given the varying and often lengthy treatment durations, this approach allowed us to capture the full spectrum of patient-incurred cancer-related costs through a cross-sectional survey.

In addition to completing one of these phases, patients had to meet the following inclusion criteria: 1) they were diagnosed with one of the six cancers as the primary tumor; 2) they received treatment in the participating hospitals, with complete diagnostic and treatment information available; and 3) their medical expenses were fully documented. Patients were excluded if they had more than one primary cancer.

The socio-demographic characteristics and clinical information—including hospital location, hospital type (general or specialized), age at diagnosis, gender, education level, marital status, health insurance status, diagnostic methods, diagnosis records, treatment phases, and clinical stages—were collected through Electronic Health Records (EHRs) from the participating hospitals and supplemented by a self-reported questionnaire survey (refer to Supplementary Methods for the self-reported questionnaires). The EHRs comprise both outpatient (OPD) and inpatient (IPD) data. In the OPD, we validated diagnoses using three key factors: diagnosis codes, primary diagnosis code, and primary diagnosis name. The codes used in both OPD and IPD are based on the International Classification of Diseases, Tenth Revision (ICD-10) (Supplementary Table 3 ). The validation process involves the following steps: first, we verified the primary diagnosis corresponds to the cancer of interest by checking the primary diagnosis code within the diagnosis codes. Next, we selected cases where the diagnosis codes corresponded accurately with the diagnosis name. The validation method for IPD closely followed that of the OPD data. The key factors are the discharge diagnosis codes, primary discharge diagnosis code, and primary discharge diagnosis name. The process ensured that the primary discharge diagnosis code was included within the discharge diagnosis codes and matched the cancer of interest, while also aligning with the discharge diagnosis name.

We employed a bottom-up micro-costing approach [ 21 ] to quantify service and resource utilization from a societal perspective. Total costs were categorized into direct medical costs, direct non-medical costs, and indirect costs. Direct medical costs encompassed the total consumption of healthcare services, such as diagnosis costs, inpatient hospitalization stays, outpatient visits, prescription medications, emergency department visits, and nursing services, during the treatment phases. These costs were extracted from the EHRs. Costs incurred outside the participating hospitals, along with direct non-medical costs and indirect costs, were collected through a self-reported questionnaire survey administered by trained attending physicians or project field workers. Direct non-medical costs included expenses for transportation, relocation, and nutrition during the treatment process that patients usually need to pay out of pocket. Indirect costs in this study were defined as the loss of income for both patients and their informal caregivers due to absenteeism measured using the product of daily wages and days of absenteeism. The human capital approach was chosen over the friction cost approach, given the focus on the economic burden borne by patients from a societal perspective [ 22 , 23 ]. Additionally, we differentiated cancer-related costs data from non-cancer visits by two ways. First, we included cases where the primary diagnosis in OPD or the primary discharge diagnosis in IPD was the cancer of interest. Second, to appropriately allocate a portion of the direct medical costs for comorbid conditions or complications, we measured the excess costs associated with comorbidities or complications using multiple regression analyses. Specifically, the logarithmic value of direct medical costs were regressed on binary indicators identifying the diagnosis of any comorbidities or complications, while controlling for factors such as age at diagnosis, sex, regional residence, education level, marital status, health insurance status, diagnosis method, treatment phases, and clinical stages.

A three-tiered quality control process was implemented to ensure the validity and reliability of cost data collected outside designated hospitals. The first level involved data collectors validated the data from the self-report form by cross-referencing it with the EHRs. The second- and third-levels involved the research supervisors from the hospitals and the National Cancer Center, who conducted further rounds of quality control and data verification.

All costs have been adjusted to 2022 currency values using the Consumer Price Index (CPI) in China and then converted to US dollars using the 2022 annual average exchange rate of 6.73 [ 24 , 25 ].

Statistical analysis

We reported descriptive statistics on the per-case economic burden of cancer across three main treatment phases, including the mean, standard deviation, median, and interquartile ranges for all cost types: direct medical costs, direct non-medical costs, indirect costs, and total costs. We also calculated the proportion of direct medical costs in total costs.

Given that the economic burden may vary by age, treatment type, and health insurance coverage [ 6 , 15 ], we also investigated potential cost drivers. Subgroup analyses and multiple linear models with log transformation were used to analyze the cost drivers of medical expenditure for cancer. We presented the coefficient estimates for factors such as age at diagnosis, sex, regional residence, education level, marital status, health insurance status (considering five major insurance categories per the latest national policies) [ 26 ], diagnosis method, comorbidities, complications, cancer types, treatment phases, and clinical stages [ 27 ]. These coefficients indicate how the costs for each subgroup change in relation to the reference group.

All analyses were performed using R version 4.0.1 (R Foundation for Statistical Computing, Vienna, Austria). Two-sided P value < 0.05 was considered statistically significant.

The self-report survey achieved a 85.0% response rate. We recruited a total of 13,745 cancer patients across the three treatment phases (Table  1 ). Among them, 2,866 (20.9%) were diagnosed with lung cancer, 2,808 (20.4%) with breast cancer, 2,420 (17.6%) with colorectal cancer, 2,039 (14.8%) with gastric cancer, 1,906 (13.9%) with liver cancer, and 1,706 (12.4%) with esophageal cancer. Patients were recruited from hospitals across the north, east, middle, west, and south regions of China, with roughly half of the patients treated in general hospitals and the other half in specialized hospitals. The mean ages at diagnosis ranged from 60 to 65 years, except for breast cancer patients, who had a younger mean age of 53 years. Across most cancer types, except for breast cancer, the proportion of male patients was higher than that of female patients (28.7%~45.7%). More than half of the patients in the surgical-related treatment phase were diagnosed at early clinical stages (Stage I/II), while over 50% of patients in the systemic treatment and relapse/metastasis phases were at advanced clinical stages (Stage III/IV), with the exception of breast cancer patients. Additional demographic details are provided in Supplementary Table 4 .

Table  2  and Fig.  2 show the per-case costs borne by patients at different treatment phases for each cancer type, along with a detailed breakdowns (with cancer staging information provided in Supplementary Fig.  1 ). The relapse/metastasis phase incurred the highest median costs for patients, ranging from $8,890 (Interquartile range: 4,939 to 15,428) to $14,572 (6,953 to 26,914), followed by the initial treatment phase, with costs ranging from $6,359 (4,187 to 10,533) to $13,704 (9,294 to 19,784). The follow-up phase had the lowest median costs, ranging from $1,840 (911 to 4,390) to $4,431 (2,235 to 11,230). Among surgical-related treatments, gastric cancer patients faced the highest median total costs ($13,398; 8,885 to 17,763), while breast cancer patients incurred the highest total costs during the non-surgical treatment phase ($9,531; 4,488 to 18,577) and the relapse/metastasis phase ($14,572; 6,953 to 26,914). Liver cancer patients faced the highest total costs during the follow-up phase ($4,431; 2,235 to 11,230). Notably, the mean direct medical expenses accounted for the largest share of the total costs, ranging from 52.6 to 87.7% across all cancer types (Table  2 ).

The median of per case costs of six cancers by treatment phases in China (in US dollars at constant 2022 prices)

Subgroup analysis (Table  3 ) reveals significant variations in the economic burden on patients across different geographic regions, hospital types, diagnostic methods, treatment phases, and clinical stages. Generally, patients hospitalized in specialized hospitals (predominantly oncology hospitals in this study), those diagnosed through physical examinations, and those in the relapse/metastasis phase incurred higher treatment costs.

The associations between cost drivers and direct medical expenses are shown in Supplementary Fig.  2 . Geographically, patients hospitalized in eastern and southern China incurred 13% (95% CI: 7–19%) and 14% (95% CI: 7–22%) higher medical costs, respectively, compared to those in northern regions, while patients in western regions had 24% (95% CI: 18–30%) lower costs. Patients treated in specialized hospitals faced 30% (95% CI: 26–35%) higher costs than those in general hospitals. Among demographic characteristics, patients younger than 45 years, those with higher levels of education, those who were divorced, and those with Urban Employee Basic Medical Insurance (UEBMI) coverage incurred significantly higher direct medical costs. For example, across all cancer types, direct medical costs for patients under the age of 45 were 10% higher (95% CI: 3–17%) than for individuals aged 55 to 64. Similarly, direct medical costs were 9% higher (95% CI: 1–16%) for patients with primary education, 15% higher (95% CI: 7–22%) for those with secondary education, and 14% higher (95% CI: 4–23%) for those with post-secondary education compared to those with no schooling. Divorced patients incurred 20% greater direct medical costs (95% CI: 5–35%) than married patients. Individuals with UEBMI coverage had medical expenses that were 55% (95% CI: 47–63%) higher than those who were uninsured and 19% (95% CI: 15–24%) higher than those with Urban and Rural Residents’ Basic Medical Insurance (URRBMI). In terms of disease characteristics, cancer complications were associated with a 17% increase in costs (95% CI: 10–24%) across all cancer types. Patients identified through screenings incurred 22% more costs (95% CI: 9–35%) than those diagnosed from symptoms. Costs increased with clinical stage: Stage II, III, and IV diagnoses led to 9% (95% CI: 4–14%), 26% (95% CI: 21–31%), and 32% (95% CI: 26–38%) higher direct medical costs, respectively, compared to Stage I.

Table  4 indicates the population attributable fraction of costs of complications and the cancer-related per case direct medical costs for the six cancer types. We found the existence of complications was associated with 30% (95% CI: 14– 46%), 22% (95% CI: 3– 41%), and 38% (95% CI: 21 – 54%) increase of direct medical costs for lung cancer, breast cancer, and esophageal cancer, respectively. The population attributable fraction percentage of costs associated with complication is no higher than 5.9% for all cancer types. We did not find statistically significant differences for the estimates of comorbidities on direct medical costs.

This study is the first to present a comprehensive analysis that estimated the economic burden on patients with leading cancers in China. We assessed the per-case financial burden on patients across three main treatment phases. Notably, patients in the relapse/metastasis phase faced the highest costs, ranging from $8,890 to $14,572. Additionally, our findings highlight that hospital location, hospital type, clinical stage at diagnosis, and patient demographics significantly influence the financial burden on individuals undergoing cancer treatment.

Previous studies on the cost of illness in China [ 9 , 10 , 11 , 12 , 13 ] have documented direct medical costs ranging from $3,000 to $10,000. In contrast, studies from other regions globally [ 7 , 8 , 28 , 29 ] report medical expenses ranging from $1,000 to $45,000. In our study, the medical expenditures by cancer patients for initial treatment had a median range of $4,685 to $12,024 and a mean of $8,622 to $14,366. These findings are close to those of the cost-of-illness studies in China. Some discrepancies in cost estimates compared to studies from other countries [ 30 ] are largely due to variations that likely arise from differences in economic contexts, healthcare systems, and market disparities across regions [ 31 ].

Furthermore, Sorensen et al. [ 32 ] found that treatment-related costs, including both active treatment and supportive care, accounted for 75% of total expenditures, a finding that aligns closely with our results. In our study, the surgical-related and relapse/metastasis phases consistently emerged as the most expensive for patients [ 31 ]. This insight helps identify the most financially demanding phases in the cancer treatment course and suggests a need to rethink medical reimbursement strategies for different treatment stages. It also underscores the importance of preventing cancer relapse/metastasis to substantially lower medical costs. Moreover, we found that individuals detected through screening incurred higher initial costs than those diagnosed based on symptoms. This is because participants detected by screening tend to undergo more examinations to reach a definitive diagnosis, leading to increased expenses. However, screening programs are intended to lead to earlier detection of disease and better prognoses, which can be cost-effective in the long term by potentially reducing the costs of advanced disease treatment. Additionally, the increase in health expenditures may result from the intended effects of screening, as patients with better health awareness—who participate in screenings—are more likely to invest more in their medical care [ 33 ].

Our study also identified several factors associated with higher costs for patients. Generally, we found that in different treatment phases, the highest-cost cancer varies, reflecting the differences in disease or therapy characteristics. Thus, tailored medical or social policies are needed for various cancer types taking the treatment phases into consideration. Patients treated in specialized hospitals incurred higher costs, which may be attributed to more advanced treatments, specialized staff, and state-of-the-art equipment available in these institutions, offering more comprehensive and personalized care. A more advanced clinical stage at diagnosis was also a significant driver of higher costs. This finding underscores the importance of early diagnosis and treatment to not only improve patient outcomes but also reduce the financial burden on patients [ 34 ].

Our findings also revealed lower medical costs among marginalized populations, which likely reflect financial hardship and underutilization of healthcare services. A study in China reported disparities in cancer diagnosis rates between rural and urban areas, suggesting that residents in rural areas may not receive timely or adequate cancer prevention and treatment services [ 35 ]. These findings emphasize the existence of inequalities in healthcare access, financing, and outcomes across different population groups [ 36 ]. This highlights the need for targeted policies to ensure equitable access to healthcare, particularly for underserved populations.

There are a few limitations in this study. Firstly, the non-randomized sampling method may affect the representativeness of the study sample. To address this, we implemented a stratified sampling procedure to mitigate this issue, ensuring the sample retains a degree of representativeness. Secondly, the cross-sectional nature of this study means that we observed the treatment course within a specific time frame, potentially underestimating the lifelong economic burden on patients. While longitudinal studies would provide more comprehensive data, they are currently difficult to conduct. Thirdly, we only covered 17 out of the 34 provincial administrations in China. Data in some remote areas like Xinjiang and Tibet were missing in this study and should be taken into consideration in further studies. Fourthly, our primary analysis did not specifically differentiate between cancer-related and non-cancer-related costs. However, the relatively low population attributable fraction of costs (no higher than 5.9%) further supports the notion that our results primarily reflected the economic burden caused by cancer-related medical services. This suggests that the main results of this study were indeed indicative of the financial impact related to cancer, as well as the burden faced by cancer patients. Finally, the generalizability of this study to other countries is closely related to whether the local cancer treatment methods and technological levels are similar to those in China.

The six leading cancers in China impose a substantial financial burden on patients. Key factors influencing these costs include patient demographics, disease stage at diagnosis, and geographic location. The relapse/metastasis treatment phase and advanced clinical staging at diagnosis are associated with significantly higher costs, underscoring the critical importance of early diagnosis and consistent follow-up care to mitigate financial strain on patients. Additionally, patients with lower levels of education, those without UEBMI, and those residing in less developed regions face greater financial challenges due to insufficient healthcare provision. These findings highlight the need for targeted policy interventions to reduce the economic burden on vulnerable patient populations and ensure equitable access to cancer care across different regions and socioeconomic groups.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Electronic health records

Consumer Price Index

Urban Employee Basic Medical Insurance

Urban and Rural Residents’ Basic Medical Insurance

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Acknowledgements

We thank the Cancer Hospital, the Chinese Academy of Medical Sciences, Peking Union Medical College, and all the hospitals involved for database support and study management. Most importantly, we thank the participants from the selected hospitals for their contributions that made this study possible.

This work was supported by the China National Cancer Center, the Chinese Academy of Medical Sciences, Peking Union Medical College. The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

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Ziting Wu and Yiwen Yu contributed equally to this work.

Authors and Affiliations

National School of Development, Peking University, Beijing, 100871, China

Ziting Wu & Gordon G. Liu

Institute for Global Health and Development, Peking University, Beijing, 100871, China

PKU China Center for Health Economic Research, Peking University, Beijing, 100871, China

School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China

Yiwen Yu & Simiao Chen

Office of Cancer Screening, National Clinical Research Center for Cancer/Cancer Hospital, National Cancer Center, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China

Department of Health Research Methods, Evidence, and Impact, Faculty of Health Sciences, McMaster University, Hamilton, Canada

Centre for Health Economics and Policy Analysis, McMaster University, Hamilton, Canada

The Harold and Inge Marcus Department of Industrial and Manufacturing Engineering, The Pennsylvania State University, University Park, PA, USA

Qiushi Chen

State Key Lab of Intelligent Technologies and Systems, Beijing National Research Center for Information Science and Technology, Department of Automation, Tsinghua University, Beijing, China

Heidelberg Institute of Global Health, Faculty of Medicine and University Hospital, Heidelberg University, Heidelberg, Germany

Simiao Chen

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Contributions

Concept and design: Y.Y., F.X, G.G.L.Acquisition of data: Y.Y.Analysis and interpretation of data: Z.W., Y.Y.Drafting of the manuscript: Z.W., Y.Y.Critical revision of the paper for important intellectual content: Z.W., Y.Y., F. X., Q. C., C.Z., S. C., G.G.L.Obtaining funding: Y.Y., G.G.L.Administrative, technical, or logistic support: Z.W., Y.Y., G.G.L.Supervision: F.X, G.G.L. All authors reviewed the manuscript.

Corresponding authors

Correspondence to Yiwen Yu or Gordon G. Liu .

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This study was approved by the ethics committees of the China National Cancer Center/Cancer Hospital, the Chinese Academy of Medical Sciences, Peking Union Medical College, and all hospitals involved (NO. 15-071/998), and was conducted in accordance with the Declaration of Helsinki. All patients provided written informed consent.

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Wu, Z., Yu, Y., Xie, F. et al. Economic burden of patients with leading cancers in China: a cost-of-illness study. BMC Health Serv Res 24 , 1135 (2024). https://doi.org/10.1186/s12913-024-11514-x

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DOI : https://doi.org/10.1186/s12913-024-11514-x

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Impact of environmental regulation on the resilience of marine economy: a case study of 11 coastal provinces and cities in china.

1. Introduction

2. theoretical analysis and research hypothesis, 2.1. the direct effect of environmental regulations on the resilience of the marine economy, 2.2. heterogeneity of the impact of different environmental regulations on the resilience of the marine economy, 2.3. spatial spillover effects of environmental regulation on the resilience of the marine economy, 2.4. the intermediary effect of marine industrial structure upgrading, 3. methods and data, 3.1. variable selection, 3.1.1. core explanatory variables, 3.1.2. explained variables, 3.1.3. intermediate variable, 3.1.4. control variables, 3.2. model construction, 3.2.1. construction of benchmark regression model, 3.2.2. construction of spatial metrology model.

• Construction of spatial weight matrix

3.2.3. Construction of Mediation Effect Model

3.3. data explanation, 4. empirical analysis and results, 4.1. baseline regression results, 4.2. the spatial spillover effect of environmental regulation on the resilience of the marine economy, 4.2.1. spatial autocorrelation test, 4.2.2. selection of spatial metrology model, 4.2.3. spatial effect analysis, 4.3. mechanism analysis, 5. robustness test, 5.1. robustness test considering different spatial weight matrices, 5.2. robustness test of baseline regression, 5.2.1. replace core explanatory variables, 5.2.2. replace the explained variable, 5.2.3. lag one stage, 5.2.4. replace the mediator variable, 6. conclusions and suggestions, 6.1. research conclusions, 6.2. suggestions, 7. limitations, author contributions, institutional review board statement, informed consent statement, data availability statement, acknowledgments, conflicts of interest.

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Zhang, L.; Xu, Z.; Chen, Y.; Liu, Z.; Yu, H. Impact of Environmental Regulation on the Resilience of Marine Economy: A Case Study of 11 Coastal Provinces and Cities in China. Sustainability 2024 , 16 , 8288. https://doi.org/10.3390/su16198288

Zhang L, Xu Z, Chen Y, Liu Z, Yu H. Impact of Environmental Regulation on the Resilience of Marine Economy: A Case Study of 11 Coastal Provinces and Cities in China. Sustainability . 2024; 16(19):8288. https://doi.org/10.3390/su16198288

Zhang, Lanting, Zilin Xu, Yifan Chen, Zhe Liu, and Huijuan Yu. 2024. "Impact of Environmental Regulation on the Resilience of Marine Economy: A Case Study of 11 Coastal Provinces and Cities in China" Sustainability 16, no. 19: 8288. https://doi.org/10.3390/su16198288

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Evaluation of sediment transport estimates using Sediment Routing Analysis (SRA) model: study case of Rawa Pening Lake

• Original Article
• Published: 26 September 2024

Cite this article

• Hanggar Ganara Mawandha   ORCID: orcid.org/0009-0001-9093-0775 1 ,
• M. Eka Bimantara Putra 2 ,
• Issiami Nursafa 1 ,
• Krisnadi Cahyo Yuliardi 1 ,
• Lalu Marhayani Kesuma 3 &
• Dewi Shinta Rulisyani 4  

This study investigates sediment transport dynamics and the effectiveness of sediment control structures in Rawa Pening Lake and its sub-catchments using Sediment Routing Analysis (SRA) model. By analyzing sediment characteristics ranging from mud to gravel, the research highlights significant sedimentation rates that have led to an average loss of 12.65 million cubic meters in the lake’s effective storage volume. Both quasi-unsteady and unsteady sediment transport models were employed, with the unsteady model demonstrating superior predictive capabilities. The empirical Ackers-White (A-W) equation surpassed the Meyer-Peter and Muller (M-P&M) equation, particularly in accurately representing the sediment characteristics and transport processes in Rawa Pening. This superiority is evidenced by a closer alignment between the A-W model’s predictions and observed bathymetric measurements. The use of HEC-RAS software facilitated detailed simulations under various flow conditions, emphasizing the role of hydraulic parameters and topographic data in model accuracy. Sediment routing simulations reveal that while check dams effectively reduce sediment concentration, diversion structures, particularly Div-2, achieve up to a 91% reduction in sediment loads entering the lake. This highlights the critical importance of selecting appropriate sediment control structures based on their design and hydraulic conditions to optimize sediment management. Using SRA modelling developed in this study, the accuracy and robustness of the sediment deposition zone and the appropriate sediment control structures for practical engineering applications could be defined.

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Data availability

Raw data were generated at Land and Water Resource Engineering Laboratory, Department of Agricultural and Biosystem Engineering, UGM. Derived data supporting the findings of this study are available from the corresponding author, H.G.M., on request.

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Acknowledgements

The authors express their gratitude to the relevant parties at the Central River Region Pemali Juana of the Ministry of Public Works and Public Housing for their support and cooperation in providing the necessary data for this study. Additionally, the authors acknowledge the financial support provided by the Directorate of Research and Community Services Universitas Gadjah Mada through the Doctoral Competency Improvement Program Universitas Gadjah Mada Number 7743/UN1.P.II/Dit-Lit/PT.01.03/2023.

This work was supported by the Central River Region Pemali Juana of the Ministry of Public Works and Public Housing and funded by Directorate of Research and Community Services Universitas Gadjah Mada through the Doctoral Competency Improvement Program Universitas Gadjah Mada (Grant numbers 7743/UN1.P.II/Dit-Lit/PT.01.03/2023).

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Conceptualization, H.G.M., L.M.K., and D.S.R.; methodology, H.G.M., L.M.K., and D.S.R.; software, H.G.M. and M.E.B.P.; validation, H.G.M. and M.E.B.P. formal analysis, H.G.M., M.E.B.P., I.N., K.C.Y.; investigation, H.G.M., M.E.B.P., and L.M.K.; writing—original draft preparation, H.G.M. and I.N.; writing—review and editing, H.G.M. and I.N.; funding acquisition, H.G.M. All authors have read and agreed to the published version of the manuscript.

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Mawandha, H.G., Putra, M.E.B., Nursafa, I. et al. Evaluation of sediment transport estimates using Sediment Routing Analysis (SRA) model: study case of Rawa Pening Lake. Model. Earth Syst. Environ. (2024). https://doi.org/10.1007/s40808-024-02163-4

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DOI : https://doi.org/10.1007/s40808-024-02163-4

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Computer Science > Robotics

Title: gait switching and enhanced stabilization of walking robots with deep learning-based reachability: a case study on two-link walker.

Abstract: Learning-based approaches have recently shown notable success in legged locomotion. However, these approaches often lack accountability, necessitating empirical tests to determine their effectiveness. In this work, we are interested in designing a learning-based locomotion controller whose stability can be examined and guaranteed. This can be achieved by verifying regions of attraction (RoAs) of legged robots to their stable walking gaits. This is a non-trivial problem for legged robots due to their hybrid dynamics. Although previous work has shown the utility of Hamilton-Jacobi (HJ) reachability to solve this problem, its practicality was limited by its poor scalability. The core contribution of our work is the employment of a deep learning-based HJ reachability solution to the hybrid legged robot dynamics, which overcomes the previous work's limitation. With the learned reachability solution, first, we can estimate a library of RoAs for various gaits. Second, we can design a one-step predictive controller that effectively stabilizes to an individual gait within the verified RoA. Finally, we can devise a strategy that switches gaits, in response to external perturbations, whose feasibility is guided by the RoA analysis. We demonstrate our method in a two-link walker simulation, whose mathematical model is well established. Our method achieves improved stability than previous model-based methods, while ensuring transparency that was not present in the existing learning-based approaches.

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