empirical vs imperical research

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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.

LEARN ABOUT: Level of Analysis

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?

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.

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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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Empirical Research: Defining, Identifying, & Finding

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

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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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Home » Education » Difference Between Conceptual and Empirical Research

Difference Between Conceptual and Empirical Research

The main difference between conceptual and empirical research is that conceptual research involves abstract ideas and concepts, whereas empirical research involves research based on observation, experiments and verifiable evidence.

Conceptual research and empirical research are two ways of doing scientific research. These are two opposing types of research frameworks since conceptual research doesn’t involve any experiments and empirical research does.

Key Areas Covered

1. What is Empirical Research     – Definition, Characteristics, Uses 2. What is Empirical Research     – Definition, Characteristics, Uses 3. What is the Difference Between Conceptual and Empirical Research     – Comparison of Key Differences

Conceptual Research, Empirical Research, Research

What is Conceptual Research?

Conceptual research is a type of research that is generally related to abstract ideas or concepts. It doesn’t particularly involve any practical experimentation. However, this type of research typically involves observing and analyzing information already present on a given topic. Philosophical research is a generally good example for conceptual research.

Conceptual research can be used to solve real-world problems. Conceptual frameworks, which are analytical tools researchers use in their studies, are based on conceptual research. Furthermore, these frameworks help to make conceptual distinctions and organize ideas researchers need for research purposes.

Figure 2: Conceptual Framework

In simple words, a conceptual framework is the researcher’s synthesis of the literature (previous research studies) on how to explain a particular phenomenon. It explains the actions required in the course of the study based on the researcher’s observations on the subject of research as well as the knowledge gathered from previous studies.

What is Empirical Research?

Empirical research is basically a research that uses empirical evidence. Empirical evidence refers to evidence verifiable by observation or experience rather than theory or pure logic. Thus, empirical research is research studies with conclusions based on empirical evidence. Moreover, empirical research studies are observable and measurable.

Empirical evidence can be gathered through qualitative research studies or quantitative research studies . Qualitative research methods gather non-numerical or non-statistical data. Thus, this type of studies helps to understand the underlying reasons, opinions, and motivations behind something as well as to uncover trends in thought and opinions. Quantitative research studies, on the other hand, gather statistical data. These have the ability to quantify behaviours, opinions, or other defined variables. Moreover, a researcher can even use a combination of quantitative and qualitative methods to find answers to his research questions .

Figure 2: Empirical Research Cycle

A.D. de Groot, a famous psychologist, came up with a cycle (figure 2) to explain the process of the empirical research process. Moreover, this cycle has five steps, each as important as the other. These steps include observation, induction, deduction, testing and evaluation.

Conceptual research is a type of research that is generally related to abstract ideas or concepts whereas empirical research is any research study where conclusions of the study are drawn from evidence verifiable by observation or experience rather than theory or pure logic.

Conceptual research involves abstract idea and concepts; however, it doesn’t involve any practical experiments. Empirical research, on the other hand, involves phenomena that are observable and measurable.

Type of Studies

Philosophical research studies are examples of conceptual research studies, whereas empirical research includes both quantitative and qualitative studies.

The main difference between conceptual and empirical research is that conceptual research involves abstract ideas and concepts whereas empirical research involves research based on observation, experiments and verifiable evidence.

1.“Empirical Research: Definition, Methods, Types and Examples.” QuestionPro, 14 Dec. 2018, Available here . 2. “Empirical Research.” Wikipedia, Wikimedia Foundation, 15 Sept. 2019, Available here . 3.“Conceptual Research: Definition, Framework, Example and Advantages.” QuestionPro, 18 Sept. 2018, Available here. 4. Patrick. “Conceptual Framework: A Step-by-Step Guide on How to Make One.” SimplyEducate.Me, 4 Dec. 2018, Available here .

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1. “APM Conceptual Framework” By LarryDragich – Created for a Technical Management Counsel meeting Previously published: First published in APM Digest in March (CC BY-SA 3.0) via Commons Wikimedia 2. “Empirical Cycle” By Empirical_Cycle.png: TesseUndDaanderivative work: Beao (talk) – Empirical_Cycle.png (CC BY 3.0) via Commons Wikimedia

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Conceptual Research vs. Empirical Research

What's the difference.

Conceptual research and empirical research are two distinct approaches to conducting research. Conceptual research focuses on exploring and developing theories, concepts, and ideas. It involves analyzing existing literature, theories, and concepts to gain a deeper understanding of a particular topic. Conceptual research is often used in the early stages of research to generate hypotheses and develop a theoretical framework. On the other hand, empirical research involves collecting and analyzing data to test hypotheses and answer research questions. It relies on observation, measurement, and experimentation to gather evidence and draw conclusions. Empirical research is more focused on obtaining concrete and measurable results, often through surveys, experiments, or observations. Both approaches are valuable in research, with conceptual research providing a foundation for empirical research and empirical research validating or refuting conceptual theories.

Further Detail

Introduction.

Research is a fundamental aspect of any field of study, providing a systematic approach to acquiring knowledge and understanding. In the realm of research, two primary methodologies are commonly employed: conceptual research and empirical research. While both approaches aim to contribute to the body of knowledge, they differ significantly in their attributes, methodologies, and outcomes. This article aims to explore and compare the attributes of conceptual research and empirical research, shedding light on their unique characteristics and applications.

Conceptual Research

Conceptual research, also known as theoretical research, focuses on the exploration and development of theories, concepts, and ideas. It is primarily concerned with abstract and hypothetical constructs, aiming to enhance understanding and generate new insights. Conceptual research often involves a comprehensive review of existing literature, analyzing and synthesizing various theories and concepts to propose new frameworks or models.

One of the key attributes of conceptual research is its reliance on deductive reasoning. Researchers start with a set of existing theories or concepts and use logical reasoning to derive new hypotheses or frameworks. This deductive approach allows researchers to build upon existing knowledge and propose innovative ideas. Conceptual research is often exploratory in nature, seeking to expand the boundaries of knowledge and provide a foundation for further empirical investigations.

Conceptual research is particularly valuable in fields where empirical data may be limited or difficult to obtain. It allows researchers to explore complex phenomena, develop theoretical frameworks, and generate hypotheses that can later be tested through empirical research. By focusing on abstract concepts and theories, conceptual research provides a theoretical foundation for empirical investigations, guiding researchers in their quest for empirical evidence.

Furthermore, conceptual research plays a crucial role in the development of new disciplines or interdisciplinary fields. It helps establish a common language and theoretical framework, facilitating communication and collaboration among researchers from different backgrounds. By synthesizing existing knowledge and proposing new concepts, conceptual research lays the groundwork for empirical studies and contributes to the overall advancement of knowledge.

Empirical Research

Empirical research, in contrast to conceptual research, is concerned with the collection and analysis of observable data. It aims to test hypotheses, validate theories, and provide evidence-based conclusions. Empirical research relies on the systematic collection of data through various methods, such as surveys, experiments, observations, or interviews. The data collected is then analyzed using statistical or qualitative techniques to draw meaningful conclusions.

One of the primary attributes of empirical research is its inductive reasoning approach. Researchers start with specific observations or data and use them to develop general theories or conclusions. This inductive approach allows researchers to derive broader implications from specific instances, providing a basis for generalization. Empirical research is often hypothesis-driven, seeking to test and validate theories or hypotheses through the collection and analysis of data.

Empirical research is highly valued for its ability to provide concrete evidence and support or refute existing theories. It allows researchers to investigate real-world phenomena, understand cause-and-effect relationships, and make informed decisions based on empirical evidence. By relying on observable data, empirical research enhances the credibility and reliability of research findings, contributing to the overall body of knowledge in a field.

Moreover, empirical research is particularly useful in applied fields, where practical implications and real-world applications are of utmost importance. It allows researchers to evaluate the effectiveness of interventions, assess the impact of policies, or measure the outcomes of specific actions. Empirical research provides valuable insights that can inform decision-making processes, guide policy development, and drive evidence-based practices.

Comparing Conceptual Research and Empirical Research

While conceptual research and empirical research differ in their methodologies and approaches, they are both essential components of the research process. Conceptual research focuses on the development of theories and concepts, providing a theoretical foundation for empirical investigations. Empirical research, on the other hand, relies on the collection and analysis of observable data to test and validate theories.

Conceptual research is often exploratory and aims to expand the boundaries of knowledge. It is valuable in fields where empirical data may be limited or difficult to obtain. By synthesizing existing theories and proposing new frameworks, conceptual research provides a theoretical basis for empirical studies. It helps researchers develop hypotheses and guides their quest for empirical evidence.

Empirical research, on the other hand, is hypothesis-driven and seeks to provide concrete evidence and support or refute existing theories. It allows researchers to investigate real-world phenomena, understand cause-and-effect relationships, and make informed decisions based on empirical evidence. Empirical research is particularly useful in applied fields, where practical implications and real-world applications are of utmost importance.

Despite their differences, conceptual research and empirical research are not mutually exclusive. In fact, they often complement each other in the research process. Conceptual research provides the theoretical foundation and guidance for empirical investigations, while empirical research validates and refines existing theories or concepts. The iterative nature of research often involves a continuous cycle of conceptual and empirical research, with each informing and influencing the other.

Both conceptual research and empirical research contribute to the advancement of knowledge in their respective fields. Conceptual research expands theoretical frameworks, proposes new concepts, and lays the groundwork for empirical investigations. Empirical research, on the other hand, provides concrete evidence, validates theories, and informs practical applications. Together, they form a symbiotic relationship, driving progress and innovation in various disciplines.

Conceptual research and empirical research are two distinct methodologies employed in the pursuit of knowledge and understanding. While conceptual research focuses on the development of theories and concepts, empirical research relies on the collection and analysis of observable data. Both approaches have their unique attributes, methodologies, and applications.

Conceptual research plays a crucial role in expanding theoretical frameworks, proposing new concepts, and providing a foundation for empirical investigations. It is particularly valuable in fields where empirical data may be limited or difficult to obtain. On the other hand, empirical research provides concrete evidence, validates theories, and informs practical applications. It is highly valued in applied fields, where evidence-based decision-making is essential.

Despite their differences, conceptual research and empirical research are not mutually exclusive. They often work in tandem, with conceptual research guiding the development of hypotheses and theoretical frameworks, and empirical research validating and refining these theories through the collection and analysis of data. Together, they contribute to the overall advancement of knowledge and understanding in various disciplines.

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

Key characteristics of empirical research include:

• Specific research questions to be answered;
• Definitions of the population, behavior, or phenomena being studied;
• Description of the methodology or research design used to study this population or phenomena, including selection criteria, controls, and testing instruments (such as surveys);
• Two basic research processes or methods in empirical research: quantitative methods and qualitative methods (see the rest of the guide for more about these methods).

(based on the original from the Connelly LIbrary of LaSalle University)

Empirical Research: Qualitative vs. Quantitative

Learn about common types of journal articles that use APA Style, including empirical studies; meta-analyses; literature reviews; and replication, theoretical, and methodological articles.

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Quantitative Research

A quantitative research project is characterized by having a population about which the researcher wants to draw conclusions, but it is not possible to collect data on the entire population.

• For an observational study, it is necessary to select a proper, statistical random sample and to use methods of statistical inference to draw conclusions about the population. 
• For an experimental study, it is necessary to have a random assignment of subjects to experimental and control groups in order to use methods of statistical inference.

Statistical methods are used in all three stages of a quantitative research project.

For observational studies, the data are collected using statistical sampling theory. Then, the sample data are analyzed using descriptive statistical analysis. Finally, generalizations are made from the sample data to the entire population using statistical inference.

For experimental studies, the subjects are allocated to experimental and control group using randomizing methods. Then, the experimental data are analyzed using descriptive statistical analysis. Finally, just as for observational data, generalizations are made to a larger population.

Iversen, G. (2004). Quantitative research . In M. Lewis-Beck, A. Bryman, & T. Liao (Eds.), Encyclopedia of social science research methods . (pp. 897-898). Thousand Oaks, CA: SAGE Publications, Inc.

Qualitative Research

What makes a work deserving of the label qualitative research is the demonstrable effort to produce richly and relevantly detailed descriptions and particularized interpretations of people and the social, linguistic, material, and other practices and events that shape and are shaped by them.

Qualitative research typically includes, but is not limited to, discerning the perspectives of these people, or what is often referred to as the actor’s point of view. Although both philosophically and methodologically a highly diverse entity, qualitative research is marked by certain defining imperatives that include its case (as opposed to its variable) orientation, sensitivity to cultural and historical context, and reflexivity. 

In its many guises, qualitative research is a form of empirical inquiry that typically entails some form of purposive sampling for information-rich cases; in-depth interviews and open-ended interviews, lengthy participant/field observations, and/or document or artifact study; and techniques for analysis and interpretation of data that move beyond the data generated and their surface appearances. 

Sandelowski, M. (2004).  Qualitative research . In M. Lewis-Beck, A. Bryman, & T. Liao (Eds.),  Encyclopedia of social science research methods . (pp. 893-894). Thousand Oaks, CA: SAGE Publications, Inc.

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Empirical Research: A Comprehensive Guide for Academics 

Empirical research relies on gathering and studying real, observable data. The term ’empirical’ comes from the Greek word ’empeirikos,’ meaning ‘experienced’ or ‘based on experience.’ So, what is empirical research? Instead of using theories or opinions, empirical research depends on real data obtained through direct observation or experimentation. 

Why Empirical Research?

Empirical research plays a key role in checking or improving current theories, providing a systematic way to grow knowledge across different areas. By focusing on objectivity, it makes research findings more trustworthy, which is critical in research fields like medicine, psychology, economics, and public policy. In the end, the strengths of empirical research lie in deepening our awareness of the world and improving our capacity to tackle problems wisely. 1,2  

Qualitative and Quantitative Methods

There are two main types of empirical research methods – qualitative and quantitative. 3,4 Qualitative research delves into intricate phenomena using non-numerical data, such as interviews or observations, to offer in-depth insights into human experiences. In contrast, quantitative research analyzes numerical data to spot patterns and relationships, aiming for objectivity and the ability to apply findings to a wider context. 

Steps for Conducting Empirical Research

When it comes to conducting research, there are some simple steps that researchers can follow. 5,6  

• Create Research Hypothesis:  Clearly state the specific question you want to answer or the hypothesis you want to explore in your study. 
• Examine Existing Research:  Read and study existing research on your topic. Understand what’s already known, identify existing gaps in knowledge, and create a framework for your own study based on what you learn. 
• Plan Your Study:  Decide how you’ll conduct your research—whether through qualitative methods, quantitative methods, or a mix of both. Choose suitable techniques like surveys, experiments, interviews, or observations based on your research question. 
• Develop Research Instruments:  Create reliable research collection tools, such as surveys or questionnaires, to help you collate data. Ensure these tools are well-designed and effective. 
• Collect Data:  Systematically gather the information you need for your research according to your study design and protocols using the chosen research methods. 
• Data Analysis:  Analyze the collected data using suitable statistical or qualitative methods that align with your research question and objectives. 
• Interpret Results:  Understand and explain the significance of your analysis results in the context of your research question or hypothesis. 
• Draw Conclusions:  Summarize your findings and draw conclusions based on the evidence. Acknowledge any study limitations and propose areas for future research. 

Advantages of Empirical Research

Empirical research is valuable because it stays objective by relying on observable data, lessening the impact of personal biases. This objectivity boosts the trustworthiness of research findings. Also, using precise quantitative methods helps in accurate measurement and statistical analysis. This precision ensures researchers can draw reliable conclusions from numerical data, strengthening our understanding of the studied phenomena. 4  

Disadvantages of Empirical Research

While empirical research has notable strengths, researchers must also be aware of its limitations when deciding on the right research method for their study.4 One significant drawback of empirical research is the risk of oversimplifying complex phenomena, especially when relying solely on quantitative methods. These methods may struggle to capture the richness and nuances present in certain social, cultural, or psychological contexts. Another challenge is the potential for confounding variables or biases during data collection, impacting result accuracy.  

Tips for Empirical Writing

In empirical research, the writing is usually done in research papers, articles, or reports. The empirical writing follows a set structure, and each section has a specific role. Here are some tips for your empirical writing. 7   

• Define Your Objectives:  When you write about your research, start by making your goals clear. Explain what you want to find out or prove in a simple and direct way. This helps guide your research and lets others know what you have set out to achieve. 
• Be Specific in Your Literature Review:  In the part where you talk about what others have studied before you, focus on research that directly relates to your research question. Keep it short and pick studies that help explain why your research is important. This part sets the stage for your work. 
• Explain Your Methods Clearly : When you talk about how you did your research (Methods), explain it in detail. Be clear about your research plan, who took part, and what you did; this helps others understand and trust your study. Also, be honest about any rules you follow to make sure your study is ethical and reproducible. 
• Share Your Results Clearly : After doing your empirical research, share what you found in a simple way. Use tables or graphs to make it easier for your audience to understand your research. Also, talk about any numbers you found and clearly state if they are important or not. Ensure that others can see why your research findings matter. 
• Talk About What Your Findings Mean:  In the part where you discuss your research results, explain what they mean. Discuss why your findings are important and if they connect to what others have found before. Be honest about any problems with your study and suggest ideas for more research in the future. 
• Wrap It Up Clearly:  Finally, end your empirical research paper by summarizing what you found and why it’s important. Remind everyone why your study matters. Keep your writing clear and fix any mistakes before you share it. Ask someone you trust to read it and give you feedback before you finish. 

References:  

• Empirical Research in the Social Sciences and Education, Penn State University Libraries. Available online at  https://guides.libraries.psu.edu/emp  
• How to conduct empirical research, Emerald Publishing. Available online at  https://www.emeraldgrouppublishing.com/how-to/research-methods/conduct-empirical-research  
• Empirical Research: Quantitative & Qualitative, Arrendale Library, Piedmont University. Available online at  https://library.piedmont.edu/empirical-research  
• Bouchrika, I.  What Is Empirical Research? Definition, Types & Samples  in 2024. Research.com, January 2024. Available online at  https://research.com/research/what-is-empirical-research  
• Quantitative and Empirical Research vs. Other Types of Research. California State University, April 2023. Available online at  https://libguides.csusb.edu/quantitative  
• Empirical Research, Definitions, Methods, Types and Examples, Studocu.com website. Available online at  https://www.studocu.com/row/document/uganda-christian-university/it-research-methods/emperical-research-definitions-methods-types-and-examples/55333816  
• Writing an Empirical Paper in APA Style. Psychology Writing Center, University of Washington. Available online at  https://psych.uw.edu/storage/writing_center/APApaper.pdf  

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• What is a Literature Review? How to Write It (with Examples)
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• Ethical Research Practices For Research with Human Subjects

Ethics in Science: Importance, Principles & Guidelines 

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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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By incorporating Appinio into your data collection toolkit, you can unlock a world of possibilities and elevate the impact of your empirical research. Ready to revolutionize your approach to data collection?

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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.

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?

Introducing Appinio , the real-time market research platform revolutionizing how companies gather consumer insights for their empirical research endeavors. With Appinio, you can conduct your own market research in minutes, gaining valuable data to fuel your data-driven decisions.

Appinio is more than just a market research platform; it's a catalyst for transforming the way you approach empirical research, making it exciting, intuitive, and seamlessly integrated into your decision-making process.

Here's why Appinio is the go-to solution for empirical research:

• From Questions to Insights in Minutes : With Appinio's streamlined process, you can go from formulating your research questions to obtaining actionable insights in a matter of minutes, saving you time and effort.
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Research Methods

• Getting Started
• Literature Review Research

Research Design

• Research Design By Discipline
• SAGE Research Methods
• Teaching with SAGE Research Methods

Quantitative vs. Qualitative Research: The Differences Explained

From Scribbr 

Empirical Research

What is empirical research.

"Empirical research is research that is based on observation and measurement of phenomena, as directly experienced by the researcher. The data thus gathered may be compared against a theory or hypothesis, but the results are still based on real life experience. The data gathered is all primary data, although secondary data from a literature review may form the theoretical background."

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. 

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

• Quantitative vs. Qualitative
• Data Collection Methods
• Analyzing Data

When collecting and analyzing data,  quantitative research  deals with numbers and statistics, while  qualitative research  deals with words and meanings. Both are important for gaining different kinds of knowledge.

Quantitative research

Common quantitative methods include experiments, observations recorded as numbers, and surveys with closed-ended questions.

Qualitative research

Common qualitative methods include interviews with open-ended questions, observations described in words, and literature reviews that explore concepts and theories.

Streefkerk, R. (2022, February 7). Qualitative vs. quantitative research: Differences, examples & methods. Scibbr. https://www.scribbr.com/methodology/qualitative-quantitative-research/ 

Quantitative and qualitative data can be collected using various methods. It is important to use a  data collection  method that will help answer your research question(s).

Many data collection methods can be either qualitative or quantitative. For example, in surveys, observations or  case studies , your data can be represented as numbers (e.g. using rating scales or counting frequencies) or as words (e.g. with open-ended questions or descriptions of what you observe).

However, some methods are more commonly used in one type or the other.

Quantitative data collection methods

• Surveys :  List of closed or multiple choice questions that is distributed to a  sample  (online, in person, or over the phone).
• Experiments :  Situation in which  variables  are controlled and manipulated to establish cause-and-effect relationships.
• Observations:  Observing subjects in a natural environment where variables can’t be controlled.

Qualitative data collection methods

• Interviews : Asking open-ended questions verbally to respondents.
• Focus groups:  Discussion among a group of people about a topic to gather opinions that can be used for further research.
• Ethnography : Participating in a community or organization for an extended period of time to closely observe culture and behavior.
• Literature review :  Survey of published works by other authors.

When to use qualitative vs. quantitative research

A rule of thumb for deciding whether to use qualitative or quantitative data is:

• Use quantitative research if you want to  confirm or test something  (a theory or hypothesis)
• Use qualitative research if you want to  understand something  (concepts, thoughts, experiences)

For most  research topics  you can choose a qualitative, quantitative or  mixed methods approach . Which type you choose depends on, among other things, whether you’re taking an  inductive vs. deductive research approach ; your  research question(s) ; whether you’re doing  experimental ,  correlational , or  descriptive research ; and practical considerations such as time, money, availability of data, and access to respondents.

Streefkerk, R. (2022, February 7).  Qualitative vs. quantitative research: Differences, examples & methods.  Scibbr. https://www.scribbr.com/methodology/qualitative-quantitative-research/ 

Qualitative or quantitative data by itself can’t prove or demonstrate anything, but has to be analyzed to show its meaning in relation to the research questions. The method of analysis differs for each type of data.

Analyzing quantitative data

Quantitative data is based on numbers. Simple math or more advanced  statistical analysis  is used to discover commonalities or patterns in the data. The results are often reported in graphs and tables.

Applications such as Excel, SPSS, or R can be used to calculate things like:

• Average scores
• The number of times a particular answer was given
• The  correlation or causation  between two or more variables
• The  reliability and validity  of the results

Analyzing qualitative data

Qualitative data is more difficult to analyze than quantitative data. It consists of text, images or videos instead of numbers.

Some common approaches to analyzing qualitative data include:

• Qualitative content analysis : Tracking the occurrence, position and meaning of words or phrases
• Thematic analysis : Closely examining the data to identify the main themes and patterns
• Discourse analysis : Studying how communication works in social contexts

Comparison of Research Processes

Creswell, J. W., & Creswell, J. D. (2018).  Research design : qualitative, quantitative, and mixed methods approaches  (Fifth). SAGE Publications.

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Penn State University Libraries

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.)
• Next: Finding Empirical Research in Library Databases >>
• Last Updated: Feb 18, 2024 8:33 PM
• URL: https://guides.libraries.psu.edu/emp

Conceptual Vs. Empirical Research: Which Is Better?

Scientific research is often divided into two classes: conceptual research and empirical research. There used to be distinct ways of doing research and a researcher would proudly claim to be one or the other, praising his method and scorning the alternative. Today the distinction is not so clear.

What is Conceptual Research?

Conceptual research focuses on the concept or theory that explains or describes the phenomenon being studied. What causes disease? How can we describe the motions of the planets? What are the building blocks of matter? The conceptual researcher sits at his desk with pen in hand and tries to solve these problems by thinking about them. He does no experiments but may make use of observations by others, since this is the mass of data that he is trying to make sense of. Until fairly recently, conceptual research methodology was considered the most honorable form of research—it required using the brain, not the hands. Researchers such as the alchemists who did experiments were considered little better than blacksmiths—“filthy empiricists.”

What is Empirical Research?

For all of their lofty status, conceptual researchers regularly produced theories that were wrong. Aristotle taught that large cannonballs fell to earth faster than small ones, and many generations of professors repeated his teachings until Galileo proved them wrong. Galileo was an empiricist of the best sort, one who performed original experiments not merely to destroy old theories but to provide the basis for new theories. A reaction against the ivory tower theoreticians culminated in those who claimed to have no use for theory, arguing that empirical acquisition of knowledge was the only way to the truth. A pure empiricist would simply graph data and see if he got a straight line relation between variables. If so, he had a good “empirical” relationship that would make useful predictions. The theory behind the correlation was irrelevant.

The Scientific Method: A Bit of Both

The modern scientific method is really a combination of empirical and conceptual research. Using known experimental data a scientist formulates a working hypothesis to explain some aspect of nature. He then performs new experiments designed to test predictions of the theory, to support it or disprove it. Einstein is often cited as an example of a conceptual researcher, but he based his theories on experimental observations and proposed experiments, real and thought, which would test his theories. On the other hand, Edison is often considered an empiricist, the “Edisonian method” being a by-word for trial and error. But Edison appreciated the work of theorists and hired some of the best. Random screening of myriad possibilities is still valuable: pharmaceutical companies looking for new drugs do this, sometimes with great success. Personally, I tend to be a semi-empiricist. In graduate school I used the Hammett linear free-energy relation (a semi-empirical equation) to gain insight into chemical transition states. So I don’t debate on “conceptual vs. empirical research.” There is a range of possibilities between both the forms, all of which have their uses.

Excellent explanations in a simple language.

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Albert Einstein did theoretical work–he had no laboratory, Put simply, through new conceptual models, he re-interpreted the findings of others and expressed them mathematically.

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BY 499 - Senior Seminar

• Library Catalog(s)
• Searching Tips and Source Evaluation
• Article Databases
• Writing Style - APA
• Empirical v. Non-Empirical Research
• Poster Design
• How Did We Do?

Subject Guide

Biology Articles

Primary Databases

Featuring thousands of full-text journals, this collection of scholarly trade and popular articles offers information on a broad range of important areas including: anthropology, biology, chemistry, ethnic & multicultural studies, law, mathematics, music, psychology, women's studies, and many other fields. Part of the Database Offerings in GALILEO, Georgia’s Virtual Library

ProQuest Research Library™ provides access to more than 5,060 titles —over 3,600 in full text— on a wide range of popular academic subjects. The database features a diversified mix of scholarly journals, trade publications, magazines, and newspapers.  Part of the Database Offerings in GALILEO, Georgia’s Virtual Library

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This database contains more than 820 leading full-text journals covering relevant aspects of the scientific and technical community. In addition to full text, Science & Technology Collection™ offers indexing and abstracts for more than 1,750 journals. Topics include aeronautics, astrophysics, biology, chemistry, computer technology, geology, aviation, physics, archaeology, marine sciences and materials science. Part of the Database Offerings in GALILEO, Georgia’s Virtual Library

A leading full-text scientific database covering the life and health sciences.

How to Make a Poster

• Designing Conference Posters & Poster Templates

Empirical Versus Non-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)
• Author(s) present a new set of findings from original research after conducting an original experiment
• Firsthand collection of data

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 or variables to be researched, research process, and analytical tools
• 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

Here are some common characteristics of review articles:

• Author(s) analyze and summarize existing research
• Author(s) did NOT do original research. They are summarizing work of others.
• Often focus on a general topic (such as breast cancer treatment) and bring together all relevant, useful articles on that topic in one review article.
• Do not contain sections such as Methods (and Materials), Results because they did not do any original research!

Fermentation and quality of yellow pigments from golden brown rice solid culture by a selected Monascus mutant.

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Quantitative and Empirical Research vs. Other Types of Research: Quantitative Research

• Quantitative Research
• Other Types of Research
• What are Scholarly Journals?

     P rofessors often want you to use scholarly journal articles for your assignments.

     Sometimes, they will require you to use scholarly journal articles that contain quantitative research .

DEFINITIONS

QUANTITATIVE

     Quantitative research looks at factors that can actually be measured in some way, in other words, quantified . It produces numerical results that can be analyzed statistically.

     Quantitative research commonly involves experimentation, surveys, or questionnaires in the context of a large, randomly selected group.

     The term  empirical research  is often used as a synonym for quantitative research, but strictly speaking, empirical research is simply any form of research based upon direct observation. It might also be quantitative, but it might not.

PLEASE NOTE: Some professors use these two terms interchangeably.  When this occurs, they are usually referring to articles that fit the quantitative description above.

HINT: Don't use the words "quantitative" or "empirical" in your keyword searches.  They usually do not appear in article titles, abstracts, or subject words.  Instead, check the articles you find to see if some sort of numerical measuring and statistical analysis is present along with the characteristics listed on the right.

CHARACTERISTICS OF QUANTITATIVE RESEARCH

      W atch for these features when determining if an article has quantitative research. They may appear in the abstract, or you may need to skim the text of the article to find them.

• Introduction : a statement of background or purpose (what was being studied and why). May review prior studies on the same topic.
• Description of the design and/or method of the study (the experimental group or sample , control, variables, number of test subjects, test conditions, etc.)
• Results , or report of the findings (in numeric form as tables, charts, or graphs, etc., often with statistical analysis)
• Conclusions that can be drawn from the results (may be labeled  discussion or significance )
• Footnotes and/or a bibliography
• Author credentials (degrees earned, where they work, etc.)  

SAMPLE QUANTITATIVE RESEARCH ARTICLES

• Relations Between Trait Impulsivity, Behavioral Impulsivity, Physiological Arousal, and Risky Sexual Behavior Among Young Men
• Nocturnal Heart Rate Variability in Patients Treated with Cognitive–Behavioral Therapy for Insomnia.
• Characterisation of Mainstream and Passive Vapors Emitted by Selected Electronic Cigarettes

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• Last Updated: Apr 6, 2023 8:16 AM
• URL: https://libguides.csusb.edu/quantitative

• Connelly Library

Qualitative and Quantitative Research

What is "empirical research".

• empirical research
• Locating Articles in Cinahl and PsycInfo
• Locating Articles in PubMed
• Getting the Articles

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
• 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
• << Previous: Home
• Next: Locating Articles in Cinahl and PsycInfo >>

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• Meriam Library

SWRK 330 - Social Work Research Methods

• Literature Reviews and Empirical Research
• Databases and Search Tips
• Article Citations
• Scholarly Journal Evaulation
• Statistical Sources
• Books and eBooks

What is a Literature Review?

Empirical research.

• Annotated Bibliographies

A literature review  summarizes and discusses previous publications  on a topic.

It should also:

explore past research and its strengths and weaknesses.

be used to validate the target and methods you have chosen for your proposed research.

consist of books and scholarly journals that provide research examples of populations or settings similar to your own, as well as community resources to document the need for your proposed research.

The literature review does not present new  primary  scholarship. 

be completed in the correct citation format requested by your professor  (see the  C itations Tab)

Access Purdue  OWL's Social Work Literature Review Guidelines here .  

Empirical Research  is  research  that is based on experimentation or observation, i.e. Evidence. Such  research  is often conducted to answer a specific question or to test a hypothesis (educated guess).

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?

These are some key features to look for when identifying empirical research.

NOTE:  Not all of these features will be in every empirical research article, some may be excluded, use this only as a guide.

• Statement of methodology
• Research questions are clear and measurable
• Individuals, group, subjects which are being studied are identified/defined
• Data is presented regarding the findings
• Controls or instruments such as surveys or tests were conducted
• There is a literature review
• There is discussion of the results included
• Citations/references are included

See also Empirical Research Guide

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Empirical & Descriptive Articles: Empirical vs. Descriptive

• Empirical vs. Descriptive
• Locating Empirical Articles
• Understanding Findings

Empirical & Descriptive

Empirical articles are articles that report research findings from an original study.

Empirical Articles:

• Articles that report research findings from an original study
• Always contain a “Methods” section
• Usually discusses a sample
• Tells the reader how the research was done
• May contain statistics or words to describe findings
• Can be found in databases/search engines and academic journals
• Used for research papers that need to be evidence-based & to learn about new research studies

Descriptive Articles

Descriptive articles  are articles that describe a topic and sometimes have a literature review but do not include a research study. They may use other researcher’s findings to create a new way of looking at an issue.

Descriptive Articles:

• Use other researcher findings to create a new way of looking at an issue
• May contain statistics from other research
• May have “literature review”, findings, and/or “conclusions sections
• Can be found in databases/search engines, Academic Journals, & magazines
• Use for general information gathering & research papers
• Next: Locating Empirical Articles >>
• Last Updated: Jun 13, 2023 10:18 AM
• URL: https://southern.libguides.com/empirical

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Developing a Research Question

15 Normative Versus Empirical Statements

When it comes to research questions, there are two concepts that are very important to sociologists: normative and empirical statements. Normative statements are judgmental, whereas empirical statements are informative and facts based. Let us look at two statements. Can you pick out which one is normative and which one is empirical?

• Canada has one of the best science programs in the world.
• In 2015, Canada ranked 4th overall in science education performance of 15-year-old high school students in a study conducted by the Organization for Education Cooperation and Development (OECD, 2015).

If you concluded that the first statement is normative and the second is empirical, you are exactly right.  While normative statements can underly an empirical statement, as demonstrated above, sociologists are focused on answering empirical questions—those that can be answered by real experience in the real world.

An Introduction to Research Methods in Sociology Copyright © 2019 by Valerie A. Sheppard is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Conceptual Research Vs Empirical Research?

Conceptual research.

Conceptual research is a technique wherein investigation is conducted by watching and analyzing already present data on a given point. Conceptual research does not include any viable tests. It is related to unique concepts or thoughts. Philosophers have long utilized conceptual research to create modern speculations or decipher existing hypotheses in a diverse light.

It doesn’t include viable experimentation, but the instep depends on analyzing accessible data on a given theme. Conceptual research has been broadly utilized within logic to create modern hypotheses, counter existing speculations, or distinctively decipher existing hypotheses. 

Today, conceptual research is utilized to answer business questions and fathom real-world problems. Researchers utilize explanatory apparatuses called conceptual systems to form conceptual refinements and organize thoughts required for investigation purposes.

Conceptual Research Framework

A conceptual research framework is built utilizing existing writing and studies from which inferences can be drawn. A conceptual research system constitutes a researcher’s combination of past research and related work and clarifies the phenomenon. The study is conducted to diminish the existing information gap on a specific theme and make important and dependable data available. 

The following steps can be taken to make a conceptual research framework:

Explain a topic for research

The primary step is to characterize the subject of your research. Most analysts will choose a topic relating to their field of expertise.

Collect and Organize relevant research

As conceptual research depends on pre-existing studies and writing, analysts must collect all important data relating to their point. It’s imperative to utilize dependable sources and information from scientific journals or investigate well-presumed papers. As conceptual research does not utilize experimentation and tests, the significance of analyzing dependable, fact-based information is reinforced.

Distinguish factors for the research

The other step is to choose important factors for their research. These factors will be the measuring sticks by which inductions will be drawn. They provide modern scope to inquire about and offer to help identify how distinctive factors may influence the subject of research.

Make the Framework 

The last step is to make the research framework by utilizing significant writing, factors, and other significant material. 

Advantages of Conceptual Research

It requires few resources compared to other types of market research where practical experimentation is required. This spares time and assets.

It is helpful as this form of investigation only requires the assessment of existing writing. 

Disadvantages of Conceptual Research

Speculations based on existing writing instead of experimentation and perception draw conclusions that are less fact-based and may not essentially be considered dependable.

Often, we see philosophical hypotheses being countered or changed since their conclusions or inferences are drawn from existing writings instead of practical experimentation. 

Empirical Research:

Empirical research is based on observed and established phenomena and determines information from real involvement instead of hypothesis or conviction. It derives knowledge from actual experiences. How do you know a study is empirical? Pay attention to the subheadings inside the article, book, or report and examine them to seek a depiction of the investigating “strategy.” Inquire yourself: Could I recreate this study and test these results?

Key characteristics to see for: 

• Specific research questions to be answered 
• Definition of the population, behavior, or wonders being studied 
• Description of the methods used to consider the population of the area of phenomena, including various aspects like choice criteria, controls, and testing instruments.

Empirical Research Framework:

Since empirical research is based on perception and capturing experiences, it is critical to arrange the steps to experiment and how to examine it. This will empower the analyst to resolve issues or obstacles amid the test.

• Define your purpose for this research:

This is often the step where the analyst must answer questions like what precisely I need to discover? What is the issue articulation? Are there any issues regarding the accessibility of knowledge, data, time, or assets? Will this research be more useful than what it’ll cost? Before going ahead, an analyst should characterize his reason for the investigation and plan to carry out assist tasks.

• Supporting theories and relevant literature:

The analyst should discover if some hypotheses can be connected to his research issue. He must figure out if any hypothesis can offer assistance in supporting his discoveries. All kinds of significant writing will offer assistance to the analyst to discover if others have researched this before. The analyst will also need to set up presumptions and also discover if there’s any history concerning his investigation issue

• Creation of Hypothesis and measurement:

Before starting the proper research related to his subject, he must give himself a working theory or figure out the probable result. The researcher has to set up factors, choose the environment for the research and find out how he can relate between the variables. The researcher will also need to characterize the units of estimations, tolerable degree for mistakes, and discover in the event that the estimation chosen will be approved by others.

• Methodology and data collection:

In this step, the analyst has to characterize a strategy for conducting his investigation. He must set up tests to gather the information that can empower him to propose the theory. The analyst will choose whether to require a test or non-test strategy for conducting the research. The research design will shift depending on the field in which the research is being conducted. Finally, the analyst will discover parameters that will influence the legitimacy of the research plan. The information collected will need to be done by choosing appropriate tests depending on the inquire-about address. To carry out the inquiry, he can utilize one of the numerous testing strategies. Once information collection is complete, the analyst will have experimental information which must be examined.

• Data Analysis and result:

Data analysis can be tried in two ways, qualitatively and quantitatively. The analyst will need to discover what subjective strategy or quantitative strategy will be required or will require a combination of both. Depending on the examination of his information, he will know if his speculation is backed or rejected. Analyzing this information is the foremost vital portion to bolster his speculation.

A report will need to be made with the discoveries of the research. The analyst can deliver the hypotheses and writing that support his investigation. He can make recommendations or suggestions to assist research on his subject

Advantages of empirical research

• Empirical research points to discover the meaning behind a specific phenomenon. In other words, it looks for answers to how and why something works the way it is. 
• By recognizing why something happens, it is conceivable to imitate or avoid comparative events. 
• The adaptability of the research permits the analysts to alter certain perspectives of the research and alter them to new objectives. 
• It is more dependable since it speaks to a real-life involvement and not fair theories. 
• Data collected through experimental research may be less biased since the analyst is there amid the collection handle. In contrast, it is incomprehensible to confirm the precision of the information in non-empirical research.

Disadvantages of empirical research

• It can be time-consuming depending on the research subject that you have chosen. 
• It isn’t a cost-effective way of information collection in most cases because of the viable costly strategies of information gathering. Additionally, it may require traveling between numerous locations. 
• Lack of proof and research subjects may not surrender the required result. A little test estimate avoids generalization since it may not be enough to speak to the target audience.
• It isn’t easy to induce data on touchy points. Additionally, analysts may require participants’ consent to utilize the data

Difference Between Conceptual and Empirical Research

Conceptual research and empirical research are two ways of doing logical research. These are two restricting investigation systems since conceptual research doesn’t include any tests, and empirical investigation does.

Conceptual research includes unique thoughts and ideas; as it may, it doesn’t include any experiments and tests. Empirical research, on the other hand, includes phenomena that are observable and can be measured.

• Type of Studies:

Philosophical research studies are cases of conceptual research, while empirical research incorporates both quantitative and subjective studies.

The major difference between conceptual and empirical investigation is that conceptual research involves unique thoughts and ideas, though experimental investigation includes investigation based on perception, tests, and unquestionable evidence.

References:

• Empirical Research: Advantages, Drawbacks, and Differences with Non-Empirical Research. In Voicedocs . Retrieved from https://voicedocs.com/en/blog/empirical-research-advantages-drawbacks-and-differences-non-empirical-research
• Empirical Research: Definition, Methods, Types and Examples. In QuestionPro . Retrieved from https://www.questionpro.com/blog/empirical-research/
• Conceptual vs. empirical research: which is better? In Enago Academy . Retrieved from https://www.enago.com/academy/conceptual-vs-empirical-research-which-is-better/

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The Vagueness of Integrating the Empirical and the Normative: Researchers’ Views on Doing Empirical Bioethics

• Original Research
• Open access
• Published: 08 November 2023

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• T. Wangmo   ORCID: orcid.org/0000-0003-0857-0510 1 ,
• V. Provoost 2 &
• E. Mihailov 3  

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The integration of normative analysis with empirical data often remains unclear despite the availability of many empirical bioethics methodologies. This paper sought bioethics scholars’ experiences and reflections of doing empirical bioethics research to feed these practical insights into the debate on methods. We interviewed twenty-six participants who revealed their process of integrating the normative and the empirical. From the analysis of the data, we first used the themes to identify the methodological content. That is, we show participants’ use of familiar methods explained as “back-and-forth” methods (reflective equilibrium), followed by dialogical methods where collaboration was seen as a better way of doing integration. Thereafter, we highlight methods that were deemed as inherent integration approaches, where the normative and the empirical were intertwined from the start of the research project. Second, we used the themes to express not only how we interpreted what was said but also how things were said. In this, we describe an air of uncertainty and overall vagueness that surrounded the above methods. We conclude that the indeterminacy of integration methods is a double-edged sword. It allows for flexibility but also risks obscuring a lack of understanding of the theoretical-methodological underpinnings of empirical bioethics research methods.

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Introduction

Empirical bioethics is an interdisciplinary activity that centres around the integration of empirical findings with normative (philosophical) analysis (Ives, Dunn, and Cribb 2017 ). Mertz and colleagues ( 2014 ) posited that “empirical research in EE [empirical ethics] is not an end in itself, but a required step towards a normative conclusion or statement with regard to empirical analysis, leading to a combination of empirical research with ethical analysis and argument” (p. 1). Thegrowth of this field is often attributed to a dissatisfaction with a purely philosophical approach, perceived as being insufficient to address bioethical issues (Hedgecoe 2004 ; Hoffmaster 2018 ) and hence a belief that an empirically informed bioethics is better suited to deal with the complexity of human practices. A consensus paper put forward by European empirical ethics scholars aimed to reach standards of practice for those working in and wanting to do empirical bioethics (Ives, et al. 2018 ). Concerning integration, the standards included the need to (1) clearly state how the theoretical position was chosen for integration, (2) explain and justify how the method of integration was carried out, and (3) be transparent in informing how the method of integration was executed.

Despite consensus that empirical research is relevant to bioethical argument (Mihailov, et al. 2022 ; Musschenga 2005 ; Sulmasy and Sugarman 2010 ; Rost and Mihailov 2021 ), integrating empirical research with normative analysis remains challenging. An often and long discussed way of integration is the (wide) reflective equilibrium (Daniels 1979 ), which has been tailored to serve empirical bioethics projects by several scholars (Ives and Draper 2009 ; Van Thiel and Van Delden 2010 ; de Vries and van Leeuwen 2010 ). Briefly, (wide) reflective equilibrium is a two-way dialogue between ethical principles/values/judgement and practice (empirical data). It is carried out by the researcher, “the thinker.” In this process, the thinker goes back and forth between the normative underpinnings and empirical facts (data available from the study or other sources) until he or she can produce moral coherence (an “equilibrium”).

A systematic review of integrative empirical bioethics identified thirty-two methodologies (Davies, et al. 2015 ). Amongst others, these include (wide) reflective equilibrium (Ives 2014 ; Van Thiel and Van Delden 2010 ; de Vries and van Leeuwen 2010 ), dialogical empirical ethics (Widdershoven, Abma, and Molewijk 2009 ; Abma, et al. 2010 ), reflexive balancing (Ives 2014 ), integrative empirical ethics (Molewijk, et al. 2003 ), hermeneutical approach to bioethics (Rehmann-Sutter, Porz, and Scully 2012 ), symbiotic ethics (Frith 2012 ), and grounded moral analysis (Dunn, et al. 2012 ). Davies and colleagues ( 2015 ) categorized the identified methodologies into, inter alia, (1) dialogical, where there is a reliance on a dialogue between the stakeholders (e.g., researchers and participants) to reach a shared understanding of the analysis and the conclusion (e.g., inter-ethics); (2) consultative, which comprises analysis of the data by the researcher, who is the external thinker and works independently to develop a normative conclusion (e.g., reflexive balancing, reflective equilibrium), and (3) those that combine the two (e.g., hermeneutics).

The wide variety of integration methodologies available illustrates considerable uncertainty about the particular aims, content, and domain of application (Davies, et al. 2015 ; Wangmo and Provoost 2017 ). Furthermore, the steps that guide the integration process are often unspecific (Davies, et al. 2015 ; Huxtable and Ives 2019 ). For example, if an ethicist acts as facilitator and applies ethical theory to enrich the dialogical process for decision-making in concrete situations (Abma, et al. 2010 ), one may wonder whether the application of ethical theories was up to the subjective appreciation of the ethicist. In reflective equilibrium, there are pressing issues of how much weight should be given to empirical data and ethical theory. The existing methodologies thus risk being frustratingly vague and insufficiently determinate in practical contexts (Arras 2009 ; Dunn, et al. 2008 ). All in all, the multiplicity of methodological paths and their lack of clarity gives rise to a debate about appropriate methodologies (Hedgecoe 2004 ; Ives and Draper 2009 ; Ives, Dunn, and Cribb 2017 ).

In a survey of bioethics scholars in twelve European countries, Wangmo and Provoost ( 2017 ), found that one-third of the respondents (total respondents N = 200) attempted to integrate the normative with the empirical. Their findings indicate that not everyone in the field of bioethics did or intended to engage in this kind of interdisciplinary work. A reason could be the methodological diversity and complications pointed to above. It is of importance to further clarify and, where necessary, develop (new) integration methodologies that address the needs in the field. In this explorative qualitative study, we set out to investigate how researchers perform the integration of empirical data with normative analysis and how they evaluate that process. Our hope is to learn from the experiences and reflections of researchers who engaged in empirical bioethics research and to feed these insights from practice into the debate on methods.

Sampling and Study Participants

To form our participant sample pool, we conducted a systematic search of peer-reviewed publications in two databases—PubMed and SCOPUS—and used the following key terms: “Empirical Bioethics” OR “Empirical Ethics” OR “Interdisciplinary Ethics” OR “Interdisciplinary Empirical Ethics” OR “empirical-normative” OR “normative-empirical” OR “Empirical research in Bioethics.” The literature search resulted in 334 results, from which we removed 143 results because they were duplicates or did not match our inclusion criteria. A sample pool of 191 papers were left. A separate Google Scholar search using the same terms lead to thirteen extra papers, resulting in a total sample pool of 204 papers.

Starting from this sample pool, we first aimed for a maximum variation sample of scholars according to the type of paper they had authored. Therefore, the 204 results were categorized into three groups: (a) Empirical: ninety-four; (b) Methodological: seventy-four; and (c) Empirical-Argumentative: thirty-six. Empirical papers were those that used purely empirical social science methodology. The methodological papers were those that discussed and/or used empirical bioethics research. Empirical-argumentative papers were those that produced empirical results along with an attempt to use them in an argumentative manner to make certain claims. These three categories were ordered alphabetically to allow simple random selection of the first authors of those included publications. Secondly, we also purposefully selected papers to aim for a balanced distribution of male versus female scholars. We carried out two rounds of selection which identified first authors of eighty-five publications who were invited to participate in our study. A total of twenty-four scholars agreed to participate. We interviewed two additional participants who were referred to us by a participant. See table 1 for participant information.

Data Collection

All selected first authors received an email from EM informing them about the study, its purpose, the researchers, and the voluntary nature of the study. All non-responders received one reminder. No incentive was given to participate in the study. The interviews were carried out using Zoom in light of the pandemic and because our participants were from different countries. The interviews were completed between April 2020 and January 2021 and were on average sixty minutes long (range forty-five to ninety minutes).

To structure the discussion, we used an interview guide composed of three sections. The first part of the interview was geared towards generally understanding the type of research carried out by the participants. Therefore, this part of the interview was not limited to the research presented in the paper via which they were selected. The second part aimed at their attitudes towards the purpose of empirical research in bioethics, using a series of eight statements to which they were invited to respond (Mihailov, et al. 2022 ). The third section sought participants’ experiences of doing empirical bioethics (i.e., integration), the advantages and challenges to carrying out empirical bioethics study, and their views on the empirical turn in bioethics. During the data collection process, the research team met twice to discuss the interview guide based on reading two of the first four interviews. This resulted in minor adjustments to the interview guide. For the interview guide and further information on the study method, please refer to the first paper from this project (Mihailov, et al. 2022 ).

Data Analysis

Audio recordings were transcribed verbatim. All anonymized transcripts were imported into qualitative data analysis software, MAXQDA. Two authors (EM and TW) carefully read and coded several interviews independently and discussed the coding process and code labels used for the entire data corpus. This pre-coding followed a thematic analysis (TA) framework (Braun and Clark, 2006 ; Guest, et al. 2012 ) in light of its fit with the explorative nature of the overall project. Thereafter, a more specific analysis of the data related to integration methods took place in order to meet the aim of this paper.

The first author created and analysed a data set pertaining to participants’ experience, opinions, and their use of particular methods of integrating the normative and the empirical. Themes and sub-themes were developed based on authors’ discussion of the data related to the integration process. Using these themes and sub-themes, TW drafted the study results in a detailed and descriptive way for the co-authors (VP and EM) to gain the richness and depth of this specific content. After several rounds of iterations and discussions among the authors (process described in the next paragraph), we agreed on the result interpretations as presented in the next section.

Briefly, our analytical approach combines TA with a hermeneutics of faith or empathy and a hermeneutics of suspicion. Such approach has been used in other studies (Huxley et al. 2011 ). Whereas a hermeneutics of faith aims at better understanding what the participant described, a hermeneutics of suspicion aims to find out hidden or latent meanings. Our team integrated two types of hermeneutics that were reflected in the researcher roles: a hermeneutics of faith or empathy (EM, the interviewer and TW, the first author), a hermeneutics of suspicion (VP) and a mixture of both (TW). Integrating various analytic roles in one team has the advantage that different readings of the data can be used to challenge each other’s views, whilst still keeping track of those different interpretations. In the results section, these layers of interpretation are interwoven. We start with interpretations close to the participants’ accounts (the first two themes predominantly resulted from a hermeneutics of faith, where we also added critical notes at the end). As the results section progresses, critical interpretations that go beyond the data surface are given more weight (hermeneutics of suspicion). At the same time, we simultaneously keep underlining the scholars’ experiences in their own terms. We present data as block-quotes to support our analysis. Shorter expressions of the participants are given in the text using italic print between quotation marks.

Ethics Approval

The study was approved by the Research Ethics Commission of the University of Bucharest. All participants provided their informed consent to participate in this study and to record their interviews.

We identified four themes related directly to our research question. The first theme “the back-and forth methods” relays the scholars’ accounts of using a reflective equilibrium method or similar. The second theme “collaboration as doing integration” deals with dialogical methods and the views of scholars who thought that collaboration was a better way of organizing integration. In reporting these two themes, we also illustrate the inherently vague manner in which the participants discussed their use of integration methods. Both theme labels were also chosen to reflect the simplified way several of the scholars conveyed their integration process. Thereafter, we continue with two additional themes, where we focus in on these accounts of participants’ chosen methods and how they were used. For this, we first present the theme “Integration as inherently ingrained from the start of the project; but is it integration?” In this theme, we start by critically looking at participants’ process of how the integration is done. Finally, we move further to unpack the ambiguity with which some participants spoke of engaging with these methods. In the theme “the integration method as a particular opaque intelligence” we highlight participants’ plea for creativity and flexibility. Here we note that although the participants are making a good point, this plea may at the same time reveal hesitance and uncertainty in talking about how they chose and applied the method they used.

Theme 1: The “back-and-forth” methods

Several participants described their method as cyclical and included terms like “back-and-forth” between the conceptual framework and the empirical data. They alluded to their method as reflective equilibrium. Here, the participants noted that their research begins with a conceptual understanding of the ethical issues relevant for the topic or question. This was followed by the collection of empirical data based on the ethical concern teased out from conceptual work and going back to the conceptual to evaluate how it must be changed or adapted. Important in this backward and forward process was the notion of “ revising ” the theory and that this was an iterative process.

While doing the back-and-forth method of integration, one participant distinguished the normative and the empirical work, with the former being the core and the empirical elements being used to shape the normative concept. This reflective equilibrium method was also seen as a way of trying to understand why practice and theory are different; hence, it includes the need to go back-and-forth iteratively between what is happening in practice and why it does or does not conform to what is set out in theory.

My approach would be to start with the normative bit. Do(ing) research around that area. Have that firmly consolidated. With that, I could develop the empirical research bit: method, structure, instrument, population, whatever ... the design of the empirical bit. But probably that—the ongoing findings from this empirical bit, empirical research—would be continuously informing the normative bit that I already had then. And—as I mentioned before—for the output and the final outcomes, I think that probably starts by seeing how the empirical changed the shape of this normative “stone” [laughs]. (P18, SSE) I think it’s kind of a reflective equilibrium thing going on and ... if it turns out that people who are on the front lines making certain kinds of moral decisions systematically think about a case a certain way, and that’s different, you know, they are sensitive to factors that maybe my theory thinks shouldn’t be important, it’s not obvious what should happen. Maybe I need to update my theory …. Or it might be that I come up with an account of why it is that they are systematically wrong, that their intuitions are corrupted in some way, or they’re responsive to factors that shouldn’t be normatively relevant. (P9, EE)

The iterative process was also seen as something that cannot be set into stone since one may have to go through several rounds of going backward and forward. Thus, a participant said that although this method is in essence a simple one, it cannot be recipe-like. This method was described as a creative process, explicitly set apart from empirical methods that follow a strict and preset schedule.

You know, this isn’t like science, where, you know, you have this type of data, do this statistical step, and follow x, y, z .... It is a creative process. You do your conceptual work; you look at the data. “No, that doesn’t work. Something’s not right. Doesn’t fit.” You go back to your concepts, reorganize them, look at your data again and other information you might have. So, it’s this iterative process of interpreting, reinterpreting data—you might have to go and seek more information, you know, if there’s certain gaps in what you ... to solve certain dilemmas you come up with. But yeah, I mean, it’s that simple. You just ... look at your data, try to ... gain meaning from that data and then conceptualize it and keep going backwards and forwards. (P7, ERB)

Within the participants’ accounts of doing such “back-and-forth” integration work, we were surprised by how often their descriptions expressed hesitance and uncertainty. This vagueness becomes clearest in this part of the discussions where an actual method of doing empirical bioethics was described. It was evident in the use of language such as “it’s kind of a […] thing,” and “a bit of . ” Also, the participants used expressions such as “trying” and “we reflect a bit and balance a bit” when explaining how they used the method. These wording suggest a lack of confidence towards their own role in the methodological process.

I think basically my advice is some kind of evaluation of judgement is a normative one, philosophical normative one, but I try to use empirical [data] as in some kind of understanding, or I try to apply those normative into the practice, and also when the real or the empirical data, empirical knowledge, has some different implication or different meaning, then I could go back for my normative one. So, it’s kind of the reflective equilibrium thing. (P25, ERB) So, what we normally say is that we use a bit of the method of reflective equilibrium, trying to combine all kinds of considerations [of the people you are studying or the issue of the study], and norms and values and principles and professional norms and individual norms. And try to mix those and weigh those and come to an equilibrium. (P19, ERB)

Theme 2: Collaboration as doing integration without a distinct integration method

Some participants said that integration can be done through collaboration, in which two or more researchers with different skills (normative analysis and empirical method) would come together to formulate the research question and conduct the study. Participants reporting this mode of integration used a dialogical encounter. It was advised that the researchers with different backgrounds should know each other’s trade and work closely together, although in some ways also staying distinct. Calling for collaboration, one participant felt that although each researcher within their respective disciplines needs their own methods, there is no particular need for a standardized overarching method.

Well, first of all it’s an interdisciplinary work. So, you need the methodology, and you need the experts in their fields. For the empirical part you really need experienced social scientists, who know how to do empirical research in a valid manner. And for the normative part you need philosophers and people who are used ... are familiar with how to approach a normative question. And I think what is also important is that they know from each other and their different methodology and work. … So, integration sounds a little bit as if all things come together ... kind of a ménage. But there ... I see it more as staying distinct but working very closely and interactively together. But still with different methodology and [remaining] aware that they are different. (P20, ERB)

One participant explained this collaborative integration as a communicative process where the normative conclusions drawn are the result of discussions with the study participants, stakeholders, and even journal readers and other audiences. This participant’s collaboration method made a clear differentiation between the empirical and the theoretical parts. That is, the empirical phase stops after finishing the data collection and the (first-level) interpretation of those collected data. Thereafter, the empirical results are taken through a process of discussions with different stakeholders, a collaborative process that in theory is unending as it continues even after the publication of the study findings.

So, we were very interested in how they [their participants] narrate what they experience, and we saw, that [they] have typical […] narratives, with which they identify. […] That was the empirical approach and then at the end there was another [approach] between the results from the empirical part and the more theoretical or bioethical discussion, where we had regular interactions with the two parts of our team and some of the members, myself included, per parts of the empirical theme and of the theoretical theme and so we had this exchange of perspective and that led then to the publications. It’s a communication process. I think bioethics is always a conversation, also when we just write up papers, we are in a conversation, just one step in a conversation. So, your question how to integrate, is how to proceed in more comprehensive conversation with the audience, the readers of our papers, we are addressing. (P4, EE)

What these participants relayed is that the integration occurred through the process of collaboration. In these accounts, there is no specific integration method used during this collaboration and no plea for an overarching method of integration. Another way of stakeholder collaboration leading to integration was described as dialogical encounter during workshops. Here the key idea was that the research team along with their invited experts deliberate on the aggregate findings and reach a consensus as to what could be the key message of the overall work. Here again, we notice how no specific method (used during such collaboration) was brought forward.

Yeah. We tend to do a little bit of reflection ourselves on the data to come up with a conceptual map or model or policy recommendations and then we try to iterate that with the group, because we realize that, you know, we have a responsibility together. Right? And so balancing our ideas offered people ... it’s a good way of assessing whether ... when we are making the shift from what the “is” is to perhaps what the “ought” should be. Having different perspectives there is important. And we do that and depending on the project, sometimes we built in a formal consensus process, another time we just want to test our ideas to see how they ... If other people endorse them or can make some suggestions to improve them. (P3, ERB) I think ... I don’t think we need one [a specific method]. I really, I don’t. I don’t actually think we need one. Because a lot of people do a lot of good work—either empirically or normatively—and there are people who get along and so ... I think that is the empiricist and the normative […] and I also very hate to “pick” ... I think we have a lot of people who do both really well. But what I WISH ... is that instead of looking for a recipe to be able to integrate ... that people with different expertise would just work together more often. (P15, ERB)

Overall, we saw a similar vagueness in their description of the “how” of integration. For example, in the quote above, the participant talks of “balancing” that is done among the invited stakeholders as part of their discussion. It remains unclear how exactly such collaboration occurs and how to confirm the value of the outcomes reached. Also in this quote, we note the language of indeterminacy we described above (e.g., “try to iterate” ).

Theme 3: Integration as inherently ingrained from the start of the project; but is it integration?

Several scholars did not consider it necessary to use a specific method of integration. They reported that, for them, the normative and empirical parts of a study are interwoven within the different phases of the research process. According to these participants, the normative and empirical cannot be teased out. This is because these are inherently linked from the start of the study, with the research question and the research project being, in and of itself, normatively oriented. The empirical and the normative are constantly informing one another: “ you cannot separate the normative from the empirical. When doing empirical work, you already do a lot of normative work as well. So yeah it’s for me it’s integrated anyway” (P12, EE). Adding to the above quote, the same participant stated, “ No, it’s always both [normative and empirical], you cannot separate actually. But it also depends on what you understand as normative analysis of course .”

However, some scholars who felt that they were also doing this type of integration in empirical bioethics, to our view, are mistaken. This is because they were either (1) describing what looked to be purely theoretical research activities or (2) presenting what looked to be purely empirical activities as both empirical and normative. For instance, one participant argued that the normative and the empirical are not distinguishable in that there is no separation between the normative and empirical. This scholar talked about a feature of this approach, where “ no data is gathered ” as it was a process of doing philosophical work in context. The claim was that the entire research is situated in the world of “oughts,” thereby making it possible to come to an “ought” statement without having to trouble oneself with the is-ought gap. What this scholar sees as “integration” looks like context-sensitive normative argumentation.

So, the integration account is basically the production of a certain kind of an argument in a certain kind of context. And that’s why the integration that I defend, I guess, is, it’s so, it’s about normative reasoning of a certain kind, taking place in a certain kind of context, in situ. Which is why I resist the idea of, as seeing descriptive and normative phases. If you take that view, you’re basically saying something I think more profoundly about how, that data can produce an understanding of the ethics or something like that or that data can profoundly impact on our political positions. I don’t think that’s what the data is doing, insofar as what data is doing on my account on integration, it’s much more about how we can make better, how we can make arguments that have a particular kind of fall. (P6, EE)

A few other participants’ empirical bioethics work seemed to us as merely descriptive-oriented research activities on ethically relevant topics. One participant stated how the normative and empirical are not distinguishable and that somehow the analysis process is when normative thinking takes place. In this, however, no normative undertaking of the data was evident. Within their descriptions, we also found statements that conveyed vagueness in how this process of integrating the empirical and the normative was done. For instance, a participant regarded several parts of the research process, interpreting and discussing the research data, as normative in nature because it could not be disentangled from normative presuppositions.

Yeah. So, the way I do data analysis is by listening to the audio of interviews and also reading transcripts. And so ... often by the time I’ve gotten to the point of analysis I already have ... interpretative themes … So, it really is an integrated theoretical and empirical process. (P16, SSE). I wouldn’t know how to distinguish the empirical and the normative because ... what you can do empirically is deeply dependent on ... normative ... presuppositions. Ehm ... and then of course, what you actually do when you ask people for responses, and when you do ... your statistical analysis, I mean that’s not […] that’s only partly normative in the epistemic sense, but not in the moral sense. Ehm so, that’s obviously empirical then. But again—as soon as you start interpreting and discussing the empirical results—you’re back in the normative arena so, that really goes hand in hand. (P23, TE)

In another example, participants explained how in a descriptive type of study on an ethical topic, the normative work still played a role by referring to a thematic map that was based on normative concepts. However, one could claim that by describing the normative part as doing “ an empirical analysis in an ethically relevant way” they actually place this research activity fully within the empirical domain.

I mean, the normative and the empirical, what I actually, I’m not so much concerned with that question, even though that may be a little bit, um, bit weird. Um, I often think a little bit different, I think like what can I contribute for the empirical and what can I contribute from the applied ethics, perspective so to say. It doesn’t necessarily have to be normative, um, it just needs to be in the realm of ethics so to say, so again if I talk about [ethical topic of the participant’s research], I, I’m also just interested in what do they [researchers] think is their [values on the ethical topic], how do they frame their [value on the ethical topic], and by asking them about [the ethical topic] I ask them about their actions, what they do, why they do it, what is their normative basis, all those things, and by that I already ensure the ethical debate, to some degree. (P5, ERB) If you are doing the interviews, I would say, this is more the point where you are on the empirical parts …. Though I would still say, it’s very helpful to have the normative background assisting, when you are doing the interviews and hearing out what are the normative interesting things that people say. So, still it is not completely gone, the normative background. When you are analysing the data, then I would say, you have the empirical part for one, because you have to do this in an empirically solid manner, but you also have the normative part included, because you want to analyse the data not just in a sociological way, but you want to analyse this in an ethically relevant way. (P2, EE)

Theme 4: The integration method as a particular opaque intelligence

Within this theme, we illustrate how the vagueness in the methods used was more explicitly brought forward as a feature of these methods. Participants who have done empirical bioethics or sought to do it described how one can go from one step to the next to reach the normative conclusion. Their use of terminologies to describe this vague process pointed to something mysterious: an “ opaque A.I. ” and a “ big leap .” The process was seen as something that was difficult to explain. One participant claimed it could not be put into precise methodological rules. We pointed to this argument above when we reported the case participants made against recipe-like methods. Here, the participant explicitly raised the view that this process remains open to post-hoc justification.

What does integration really mean? How do you articulate this—kind of—magic box, where data goes in and then you come out conclusions?. It’s a particular opaque A.I., where you—kind of—plug in the data and this conclusion comes out. … And, that’s not a transparent process, we don’t know how our brains work, we don’t know how we make connections. So all we can do is perhaps be transparent about the steps we’re taking to get the information, be reflexive about how we use information, and then articulate the reasons for our conclusions. But I think—as I said earlier—there will always tend to be post-hoc justifications. (P22, EE) And then the big leap ... and the big leap is probably the one that you are curious about. The big leap toward what is the good thing to do. … But yet again, I have always thought that that methods [reflective equilibrium] falls short in giving clear sight of the black box, of the end, of the conclusion, ... I don’t have an answer whether or not we really get a clear view what happens when we take the “jump” from what we see, what we think, towards what we think would be the right thing to do, what we ought to do. (P19, ERB).

Accounts where we saw this vagueness presented as a feature of the method also expressed a need for a creative process that would require some flexibility. In the same line another participant noted: “ I feel that if we did have a recipe for integration, it would almost be sad ... people might feel that they are finding the ‘holy grail,’ but then you limiting yourself to just one way of thinking” (P15, ERB). Several participants underscored the need for flexibility and not to be restricted by too many rules. They said that much of empirical bioethics seeks to integrate work from two disciplines that have indeterminate processes, i.e., qualitative research and theoretical ethics. They thus emphasized the challenges of articulating two methods that are themselves opaque into one that is not.

And I think qualitative researchers have been ... struggling with this for a long time, and I think a lot of what we’re doing now mirrors the difficulties that qualitative researchers have been having—particularly in medicine—where they’re being challenged to explain a method. … And we have to explain method, but you can’t explain how your brain got there. With empirical bioethics, we’re working with qualitative research AND we’re working with ... theoretical ethics, so it’s doubly challenging to articulate two uhm very opaque processes. (P22, EE)

In 2015, Davies and colleagues summarized thirty-two empirical bioethics integrative methodologies that combine normative analysis and empirical data obtained using social-science research. Following this, scholars have discussed the integration of the normative and life sciences research (Mertz and Schildmann 2018 ), using critical realism in empirical bioethics (McKeown 2017 ), and integrating experimental philosophical bioethics and normative ethics (Earp, et al. 2020 ; Mihailov, et al. 2021 ). In line with the systematic review of empirical bioethics methodologies’ two broad categories of dialogical and consultative processes of integration (Davies, et al. 2015 ), our participants indicated two familiar approaches. The first one is based on a reflective equilibrium–type process, and the other, an interdisciplinary collaboration between and among different stakeholders.

In addition, several participants suggested integration was inherent with the normative and empirical intertwined within the overall research process. Our participants’ accounts of inherent integration shared some similarities with, for example, moral case analysis (Dunn, et al. 2012 ), integrated empirical ethics (Molewijk, et al. 2003 ), and dialogical empirical ethics (Landeweer, et al. 2017 ; Widdershoven, et al. 2009 ). The shared similarities were in the sense that there were no separate normative and empirical parts to be distinguished in a project and that the project itself was normatively oriented. However, we should be critical of this view. The mere fact the empirical and the normative is inseparably intertwined throughout a research process does not mean (1) that these claims cannot be conceptually separated and (2) that such a method is free of methodological concerns. For instance, there would still be the need to specify what moral principles demand in a particular situation, decide which ethical theory to use, or make normative judgements with the help of empirical data (Frith 2012 ; Salloch, et al. 2015 ). Apart from that, several of these “inherently integrated” methods lacked a clear normative side and the enterprises described seemed purely empirical. Upon closer analysis, one could interpret some of the accounts of “integration was always inherently present” as a way of avoiding looking into the black box.

Furthermore, within these “inherently integrated” approaches, a few scholars described their descriptive research on ethical issues as empirical bioethics. Based on the available definition of empirical bioethics (Ives, Dunn, and Cribb 2017 ; Mertz, et al. 2014 ) and the standards offered by Ives and colleagues ( 2018 ), the works of these participants would thus not count as empirical bioethics. This is because there was no evidence of any integration happening. In our opinion, this mismatch between the practice of some scholars and what is “agreed” to in the literature as empirical bioethics may be pointing to the fact that empirical work in bioethics is in essence heterogeneous (Ives, Dunn, and Cribb 2017 ; Mertz, et al. 2014 ). For one, it is possible that scholars look at their projects as fitting an empirical bioethics because they start from research questions relating to the normative and because their projects, even with purely descriptive parts (and papers), are aimed to eventually lead to normative conclusions. But also in that case, we need to be clear about the nature of such particular (sub)projects and about the absence of integration efforts in these parts. Second, it is possible that scholars have different perspectives on the matter than the one expressed in the standards paper (Ives, et al. 2018 ). In that case as well, these must be brought out in the open. Third, some scholars may simply be mistaken when they consider their projects to be empirical bioethics. Their mistaken belief might be based on the idea that the empirical findings were at some point integrated in normative reasoning, which results in a normative claim. This simply might not be the case. This then, more than anything, would point to the need for transparency about and agreement on the use of methods. A heterogeneity of approaches in the field should be applauded. However, for all of them, we need to be able to identify where and how the integration happens. In the remaining part of this discussion, we focus on the overall vague manner in which our participants talked about their methods and what that implies for the field of empirical bioethics.

Vagueness of Integration Methods Used

Reflective equilibrium, broadly construed, is a deliberative process that seeks coherence between attitudes, beliefs, and competing ethical principles (Daniels 2020 ). A standard objection against reflective equilibrium methodology is that it is insufficiently determinate in practical contexts to be action-guiding or to help decide between conflicting views (Arras 2009 ; Paulo 2020 ; Raz 1982 ). The iterative process of going back-and-forth between the normative and the empirical to come to a coherent account, similarly, is fraught with indeterminate indications. The way study participants relayed their approaches and explained their practices underscored the vagueness they felt. It further showed the difficulties even scholars with expertise in using these methods had in illustrating the “how” in an exact manner.

Such vagueness was also evident in collaboration methods of integration reported by our study participants. This collaboration involves an iterative and deliberative process of sharing information and engaging with different perspectives (Rehmann-Sutter, et al. 2012 ). It requires ongoing dialogue between social scientists and bioethicists. Their practical know-how guides the conclusion about the normative significance of empirical data. Even though the experience and implicit know-how of the experts can be rich in content and varied, how the communication process is done and who decides the outcome often remains indeterminate. This was noted in the voices of our participants.

The difficulty in clearly explaining the “how” of the integration process is something that researchers who have carried out an integration or wished to do so are likely to be familiar with. Several scholars have pointed to this unclear process as well (Ives and Draper 2009 ; Mertz and Schildmann 2018 ; Strong, et al. 2010 ). One explanation for this finding may be that, given the numerous tailored versions of the reflective equilibrium methodology for empirical bioethics (de Vries and van Leeuwen 2010 ; Ives 2014 , Ives and Draper 2009 ; Van Thiel and Van Delden 2010 ; Savulescu, et al. 2021 ), there may be confusion surrounding how to make a choice and how to implement it in practice. As noted earlier, there are many available empirical bioethics methodologies (Davies, et al. 2015 ), and it has been suggested that each researcher could be using his or her own version (Wangmo and Provoost 2017 ). This situation, to us, points in two directions. First, it may convey a general need to remain flexible and open to creativeness, key components of the normative reasoning that is central to the integration method. We may thus have to stop looking for a method that is akin to empirical standards, especially those of quantitative methods, and recognize that the empirical and normative integration is in many ways a normative enterprise, which does not follow an exact method. Second, the wide variation of approaches makes it even clearer that we need to seek more methodological clarity on the overarching level. This is where the debate on standards (Ives, et al. 2018 ), for instance, has been an added value. It allows for heterogeneity while at the same time striving to create more clarity. In fact, we point out that the integration methods are inherently indeterminate and that this is a good thing. That said, an acceptance of the indeterminate character of this integration does not absolve us from the need to identify the foundations of what we are doing in a theoretical-methodological way.

The study findings confirm the image of an indeterminate process. As research on this topic is developing, it is ever more clear that the scholars involved come from a wide variation of disciplines. This is another argument as to why this indeterminate character is indispensable. The findings thus substantiate what has already been written about the indeterminate status of the methods used in empirical bioethics (Arras 2009 ; Davies, et al. 201 5 ; Dunn, et al. 2008 ; Huxtable and Ives 2019 ), despite efforts to delimit and standardize empirical bioethics work (Mertz, et al. 2014 ; Ives, et al. 2018 ). One way of reading the vagueness we encountered is the scholars’ struggle to explain their own integration process, and perhaps even a lack of full comprehension of that process. Another interpretation is one that is in line with the wish for creativity and flexibility, and a level of indeterminacy in the methods we look for, namely an expression of leaving things open. Creativity can be a medicine against the belief that precise and transparent standards can account for such a “maze of interactions” (Feyerabend 2010 ) between experts with fertile know-hows. Too much standardization misses how particular research situations inspire novel ways of seeing the ethical relevance of empirical data. We should nevertheless be aware that the indeterminate nature of any integrative methodology makes it subject to risks of post-hoc rationalizations and motivated reasoning (Ives and Dunn 2010 ; Mihailov 2016 ). In the end, demands for creativity—however valid—should go hand in hand with demands for a thorough theoretical foundation as well as practical understanding of the method at hand.

The Normative Nature of Integrative Methodologies

Reflective equilibrium is a deliberation method that helps us come to a conclusion about what we ought to do (Daniels 1996 ; Rawls 1951 , 1971 ). If we describe the integration process only in terms of going back-and-forth between data and theory, or in terms of collaboration between different experts, we risk obscuring the normative nature of using empirical data to help elaborate ethical prescriptions, which is the goal of doing such an integration (Ives and Draper 2009 ; Mertz, et al. 2014 ). Researchers often talk about integration as if it is a process half empirical and half normative or something that just needs normative reasoning alongside empirical data. But the very act of integration is normative in nature. While facts are essential for addressing bioethical issues, the task of integration ultimately depends on normative assumptions about the normative weight of moral intuitions.

Our data show that many of our participants rely on a reflective equilibrium characterized in their explanations mostly by moving back-and-forth between empirical results about moral attitudes and intuitions. Although the cyclical thinking is an important part of reflective equilibrium, there is more to it. Often, however, our participants did not move beyond this aspect. Ideas of coherence between moral intuitions and moral principles, and the fundamental willingness to adjust moral principles in light of what we discover were rarely touched upon. Perhaps what we see here is that several study participants embarked on an intuitive account of a—sometimes simplified—reflective equilibrium inspired methodology. At least in the interviews, it was not shown that they were fully aware of theoretical commitments to coherence, giving normative weight to moral intuitions, and screening them for bias.

The need to clarify the essential normative nature of integration appeals to normatively trained bioethicists, who may be in a better position to debate and assess how empirical input should be integrated into normative recommendations. We are not claiming that bioethics should be the arena of philosophers. Empirical research in bioethics is widespread (Borry, et al. 2006 ; Wangmo, et al. 2018 ), and scholarly perceptions about who belongs in the field are no longer exclusivist. There is thus a need to look at empirical bioethics projects in a broader way, including studies where empirical data are gathered but not used directly as part of a normative argumentation. Such empirical data may thus contribute to a larger body of work aimed at reaching normative conclusions. They can include, for example, empirical studies that explore stakeholders’ views relating to bioethical matters and explain how people arrive at certain reasoning patterns or studies that reveal the lived experience of stakeholders and explore how moral questions are experienced in practice (Mihailov, et al. 2022 ). To our view, despite the central role of normative know-how to integration, this does not mean that integration efforts need to be exclusively the work of ethicists or that empirical researchers will be unable to engage in it.

Limitations

Our findings are, first and foremost, not generalizable, as they are based on an exploratory qualitative study design. The data come from a small non-representative sample of researchers. Other scholars, with different or greater experience in using particular (interdisciplinary) integration methods may have different opinions. They could perhaps have provided us with more concrete information about the way they carried out such integration. Also, only one of our participants described him/herself as a normative researcher. It would have been interesting to have more participants who were normatively oriented to include their views on how empirical data can be of use to the adaptation or formation of normative recommendations. Second, we asked scholars to tell us the process they use in integrating the normative and the empirical. This is a challenge task in and of itself. Not only did the scholars have limited time for the interview, but also it is generally difficult to explain how exactly this process pans out post-hoc. We thus acknowledge that we presented the participants with questions which were in no way easy for them to address in a single conversation. Because we wanted to focus on the scholars’ own reports, we did not confront them with approaches adopted by others in as systematic way. We did not also engage in a critical assessment of the reported method at the time of the interview. It would be interesting for further research to include such an approach and, for instance, study this using focus group methods. Using confrontation with other approaches or other views could offer the opportunity for a more critical reflection. For this paper, however, we opted to enrich the ongoing debate first and foremost with the accounts of the scholars. Third, we underline that a minority of our participants had already published methodological papers related to empirical bioethics as evident from the EBE sample. We did not ask the scholars to discuss the method that they have written about or most liked, nor did we ask them to discuss the paper that led to their identification for this study. During the interviews, however, we sought to address acquiescence and social desirability by using Socratic questioning and probing, to provide time for participants to explain their method of integration.

Conclusion: Ambiguity Waiting to Be Disentangled

We set out to find more about the “how” of the integration methods used by scholars in empirical bioethics. Our hope was to provide input for the ongoing debate on methods and perhaps even some practical support for those considering empirical bioethics projects. Although we shed some light onto the way integration methods were used by different bioethics scholars, we especially bring forth the vagueness and uncertainties in their accounts. The main challenge was not the heterogeneity of methods but rather the indeterminate nature of integration methodologies. On a practical level, this finding may express the need for flexibility and variation in approaches rather than a need for recipe-like instructions. Such a clear-cut method will likely neither be possible nor appreciated. Philosopher of science Paul Feyerabend once said that methodological rules “are ambiguous in the way certain drawings are ambiguous” ( 2001 , 39). The ambiguity of integration methods does not make them less appealing, just as the ambiguity of drawings does not make them less beautiful. Therefore, we may be wiser to accept some degree of indeterminacy, while simultaneously striving for clarity and transparency in terms of the theoretical-methodological underpinnings.

Data Availability

Anonymized data relevant to evaluate the results presented in this paper can be made available upon request. 

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Acknowledgements

We sincerely acknowledge the two anonymous reviewers for their insightful comments and for how they constructively challenged the discussion of the study findings.

The authors thank the study participants for their time and sharing their views. The study was supported by the Swiss National Science Foundation, IZSEZ0_190015.

Open access funding provided by University of Basel

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Wangmo, T., Provoost, V. & Mihailov, E. The Vagueness of Integrating the Empirical and the Normative: Researchers’ Views on Doing Empirical Bioethics. Bioethical Inquiry (2023). https://doi.org/10.1007/s11673-023-10286-z

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Received : 02 January 2023

Accepted : 20 July 2023

Published : 08 November 2023

DOI : https://doi.org/10.1007/s11673-023-10286-z

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