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empirical research is also known as

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Empirical Research: Definition, Methods, Types and Examples

What is Empirical Research

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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.

LEARN ABOUT: Best Data Collection Tools

Step #5: Data Analysis and result

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

Step #6: Conclusion

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

Empirical research methodology cycle

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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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!

Ellysa Cahoy

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

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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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Introduction to Empirical Research

Databases for finding empirical research, guided search, google scholar, examples of empirical research, sources and further reading.

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  • Introductory Video This video covers what empirical research is, what kinds of questions and methods empirical researchers use, and some tips for finding empirical research articles in your discipline.

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  • Guided Search: Finding Empirical Research Articles This is a hands-on tutorial that will allow you to use your own search terms to find resources.

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  • Study on radiation transfer in human skin for cosmetics
  • Long-Term Mobile Phone Use and the Risk of Vestibular Schwannoma: A Danish Nationwide Cohort Study
  • Emissions Impacts and Benefits of Plug-In Hybrid Electric Vehicles and Vehicle-to-Grid Services
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  • Endocrine disrupters and human health: could oestrogenic chemicals in body care cosmetics adversely affect breast cancer incidence in women?

empirical research is also known as

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Empirical Research: What is empirical research?

What is empirical research.

  • How do I find empirical research in databases?
  • What does empirical research look like?
  • How is empirical research conducted?
  • What is Empirical Research?
  • How do I Find Empirical Research in Databases?
  • How is Empirical Research Conducted?

Ask a Librarian

Contact the reference desk.

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

What about when research is not empirical?

Many humanities scholars do not use empirical methods. if you are looking for empirical articles in one of these subject areas, try including keywords like:.

  • quantitative
  • qualitative

Also, look for opportunities to narrow your search to scholarly, academic, or peer-reviewed journals articles in the database.

Adapted from " Research Methods: Finding Empirical Articles " by Jill Anderson at Georgia State University Library.

See the complete A-Z databases list for more resources

The primary content of this guide was originally created by  Ellysa  Cahoy at Penn State Libraries .

  • Next: How do I find empirical research in databases? >>
  • Last Updated: Apr 12, 2024 8:07 AM
  • URL: https://geiselguides.anselm.edu/Empirical-Research

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According to the APA , empirical research is defined as the following: "Study based on facts, systematic observation, or experiment, rather than theory or general philosophical principle." Empirical research articles are generally located in scholarly, peer-reviewed journals and often follow a specific layout known as IMRaD: 1) Introduction - This provides a theoretical framework and might discuss previous studies related to the topic at hand. 2) Methodology - This describes the analytical tools used, research process, and the populations included. 3) Results - Sometimes this is referred to as findings, and it typically includes statistical data.  4) Discussion - This can also be known as the conclusion to the study, this usually describes what was learned and how the results can impact future practices.

In addition to IMRaD, it's important to see a conclusion and references that can back up the author's claims.

Characteristics to look for

In addition to the IMRaD format mentioned above, empirical research articles contain several key characteristics for identification purposes:

  • The length of empirical research is often substantial, usually eight to thirty pages long.
  • You should see data of some kind, this includes graphs, charts, or some kind of statistical analysis.
  • There is always a bibliography found at the end of the article.

Publications

Empirical research articles can be found in scholarly or academic journals. These types of journals are often referred to as "peer-reviewed" publications; this means qualified members of an academic discipline review and evaluate an academic paper's suitability in order to be published. 

The CRAAP Checklist should be utilized to help you examine the currency, relevancy, authority, accuracy, and purpose of an information resource. This checklist was developed by California State University's Meriam Library . 

This page has been adapted from the Sociology Research Guide: Identify Empirical Articles at Cal State Fullerton Pollak Library.

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Encyclopedia of Psychology and Religion pp 782–783 Cite as

Empirical Research

  • Emeka Thaddues Njoku 3  
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The term “empirical” entails gathered data based on experience, observations, or experimentation. In empirical research, knowledge is developed from factual experience as opposed to theoretical assumption and usually involved the use of data sources like datasets or fieldwork, but can also be based on observations within a laboratory setting. Testing hypothesis or answering definite questions is a primary feature of empirical research. Empirical research, in other words, involves the process of employing working hypothesis that are tested through experimentation or observation. Hence, empirical research is a method of uncovering empirical evidence.

Through the process of gathering valid empirical data, scientists from a variety of fields, ranging from the social to the natural sciences, have to carefully design their methods. This helps to ensure quality and accuracy of data collection and treatment. However, any error in empirical data collection process could inevitably render such...

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Bibliography

Bhattacherjee, A. (2012). Social science research: Principles, methods, and practices. Textbooks Collection . Book 3.

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Comte, A., & Bridges, J. H. (Tr.) (1865). A general view of positivism . Trubner and Co. (reissued by Cambridge University Press, 2009).

Dilworth, C. B. (1982). Empirical research in the literature class. English Journal, 71 (3), 95–97.

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Heisenberg, W. (1971). Positivism, metaphysics and religion. In R. N. Nanshen (Ed.), Werner Heisenberg – Physics and beyond – Encounters and conversations , World Perspectives. 42. Translator: Arnold J. Pomerans. New York: Harper and Row.

Hossain, F. M. A. (2014). A critical analysis of empiricism. Open Journal of Philosophy, 2014 (4), 225–230.

Kant, I. (1783). Prolegomena to any future metaphysic (trans: Bennett, J.). Early Modern Texts. www.earlymoderntexts.com

Koch, S. (1992). Psychology’s Bridgman vs. Bridgman’s Bridgman: An essay in reconstruction. Theory and Psychology, 2 (3), 261–290.

Matin, A. (1968). An outline of philosophy . Dhaka: Mullick Brothers.

Mcleod, S. (2008). Psychology as science. http://www.simplypsychology.org/science-psychology.html

Popper, K. (1963). Conjectures and refutations: The growth of scientific knowledge . London: Routledge.

Simmel, G. (1908). The problem areas of sociology in Kurt H. Wolf: The sociology of Georg Simmel . London: The Free Press.

Weber, M. (1991). The nature of social action. In W. G. Runciman (Ed.), Weber: Selections in translation . Cambridge: Cambridge University Press.

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Njoku, E.T. (2020). Empirical Research. In: Leeming, D.A. (eds) Encyclopedia of Psychology and Religion. Springer, Cham. https://doi.org/10.1007/978-3-030-24348-7_200051

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Empirical Research: Defining, Identifying, & Finding

Identifying empirical research.

  • Defining Empirical Research

Finding the Characteristics of Empirical Research in an Article

The abstract.

  • Introduction
  • Database Tools
  • Search Terms
  • Image Descriptions

Once you know the characteristics of empirical research , the next question is how to find those characteristics when reading a scholarly, peer-reviewed journal article. Knowing the basic structure of an article will help you identify those characteristics quickly. 

The IMRaD Layout

Many scholarly, peer-reviewed journal articles, especially empirical articles, are structured according to the IMRaD layout. IMRaD stands for "Introduction, Methods, Results, and Discussion." These are the major sections of the article, and each part has an important role: 

  • Introduction: explains the research project and why it is needed. 
  • Methods: details how the research was conducted. 
  • Results: provides the data from the research.
  • Discussion: explains the importance of the results. 

While an IMRaD article will have these sections, it may use different names for these sections or split them into subsections. 

While just because an article is structured in an IMRaD layout is not enough to say it is empirical, specific characteristics of empirical research are more likely to be in certain sections , so knowing them will help you find the characteristics more quickly. Click the link for each section to learn what empirical research characteristics are in that section and common alternative names for those sections: 

Use this video for a quick overview of the sections of an academic article: 

Journal articles will also have an abstract which summarizes the article. That summary often includes simplified information from different IMRaD sections, which can give you a good sense of whether the research is empirical. Most library databases and other academic search tools will show you the abstract in your search results, making it the first place you can look for evidence that an article is empirical. 

There are two types of abstracts: structured and unstructured. 

Structured Abstracts

Structured abstracts   are organized and labeled in a way that replicates the IMRaD format. If you know what characteristics of empirical research are located in a particular IMRaD section, you can skim that section of the structured abstract to look for them. 

Example of a structured abstract.  Long description available through "Image description" link.

[ Image description ] 

Unstructured Abstracts

Unstructured abstracts   do not label the parts of the summary and are generally a single block paragraph. You will not be able to skim through an unstructured abstract for empirical research characteristics as easily, but some of those characteristics will still be there. Often the unstructured abstract will include some version of the research question and simplified descriptions of the design, methodology, and sample. 

Example of an unstructured abstract. Long description available through "Image description" link.

[ Image description ]

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What is Empirical Research? Definition, Methods, Examples

Appinio Research · 09.02.2024 · 35min read

What is Empirical Research Definition Methods Examples

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.

To streamline your process and gather insights with precision and efficiency, consider leveraging innovative tools like Appinio . With Appinio's intuitive platform, you can harness the power of real-time consumer data to inform your research decisions effectively. Whether you're conducting surveys, interviews, or observations, Appinio empowers you to define your target audience, collect data from diverse demographics, and analyze results seamlessly.

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 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.

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Empirical Research

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Definition of Empirical Research

Research employing empirical evidence is known as empirical research, which entails observing and measuring events as the investigator personally witnesses them. It obtains information from practical exposure instead of concept or assumption since it is built on observed and measurable events.

Sociological Explanation

The actual sociological study bases its explanations of social phenomena on empirical information about social formations and their constituents. The methodologies used to perform and analyze empirical research might be qualitative or quantitative.

It is a research technique that relies on independently verified data to produce research findings. This research uses a scientific inquiry to compare the experimental probabilities of the study variables, in contrast to theoretical work, which relies on assumptions about the research variables.

Instead of being based on theoretical propositions, knowledge is generated via accurate and verifiable experience in an empirical study. This kind of research often uses datasets or fieldwork, but it may also be based on empirical evidence made inside an experimental group in a culture or community.

Theodor W. Adorno’s article, “Sociology and Empirical Research”, originally appeared in 1957 and contained his critique of the 1950s’ sociology and empirical social science research.

According to empirical research, entrepreneurs are not a homogenous group, which further indicates that they include the self-employed, small employers, industrialists, and owner-directors.

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1.3: Scientific Research

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Given that theories and observations are the two pillars of science, scientific research operates at two levels: a theoretical level and an empirical level. The theoretical level is concerned with developing abstract concepts about a natural or social phenomenon and relationships between those concepts (i.e., build “theories”), while the empirical level is concerned with testing the theoretical concepts and relationships to see how well they reflect our observations of reality, with the goal of ultimately building better theories. Over time, a theory becomes more and more refined (i.e., fits the observed reality better), and the science gains maturity. Scientific research involves continually moving back and forth between theory and observations. Both theory and observations are essential components of scientific research. For instance, relying solely on observations for making inferences and ignoring theory is not considered valid scientific research.

Depending on a researcher’s training and interest, scientific inquiry may take one of two possible forms: inductive or deductive. In inductive research , the goal of a researcher is to infer theoretical concepts and patterns from observed data. In deductive research , the goal of the researcher is to test concepts and patterns known from theory using new empirical data. Hence, inductive research is also called theory-building research, and deductive research is theory-testing research. Note here that the goal of theory-testing is not just to test a theory, but possibly to refine, improve, and extend it. Figure 1.1 depicts the complementary nature of inductive and deductive research. Note that inductive and deductive research are two halves of the research cycle that constantly iterates between theory and observations. You cannot do inductive or deductive research if you are not familiar with both the theory and data components of research. Naturally, a complete researcher is one who can traverse the entire research cycle and can handle both inductive and deductive research.

It is important to understand that theory-building (inductive research) and theorytesting (deductive research) are both critical for the advancement of science. Elegant theories are not valuable if they do not match with reality. Likewise, mountains of data are also useless until they can contribute to the construction to meaningful theories. Rather than viewing these two processes in a circular relationship, as shown in Figure 1.1, perhaps they can be better viewed as a helix, with each iteration between theory and data contributing to better explanations of the phenomenon of interest and better theories. Though both inductive and deductive research are important for the advancement of science, it appears that inductive (theory-building) research is more valuable when there are few prior theories or explanations, while deductive (theory-testing) research is more productive when there are many competing theories of the same phenomenon and researchers are interested in knowing which theory works best and under what circumstances.

clipboard_e50495fa785569896bb101e5c53e9d6f8.png

Theory building and theory testing are particularly difficult in the social sciences, given the imprecise nature of the theoretical concepts, inadequate tools to measure them, and the presence of many unaccounted factors that can also influence the phenomenon of interest. It is also very difficult to refute theories that do not work. For instance, Karl Marx’s theory of communism as an effective means of economic production withstood for decades, before it was finally discredited as being inferior to capitalism in promoting economic growth and social welfare. Erstwhile communist economies like the Soviet Union and China eventually moved toward more capitalistic economies characterized by profit-maximizing private enterprises. However, the recent collapse of the mortgage and financial industries in the United States demonstrates that capitalism also has its flaws and is not as effective in fostering economic growth and social welfare as previously presumed. Unlike theories in the natural sciences, social science theories are rarely perfect, which provides numerous opportunities for researchers to improve those theories or build their own alternative theories.

Conducting scientific research, therefore, requires two sets of skills – theoretical and methodological – needed to operate in the theoretical and empirical levels respectively. Methodological skills ("know-how") are relatively standard, invariant across disciplines, and easily acquired through doctoral programs. However, theoretical skills ("know-what") is considerably harder to master, requires years of observation and reflection, and are tacit skills that cannot be “taught” but rather learned though experience. All of the greatest scientists in the history of mankind, such as Galileo, Newton, Einstein, Neils Bohr, Adam Smith, Charles Darwin, and Herbert Simon, were master theoreticians, and they are remembered for the theories they postulated that transformed the course of science. Methodological skills are needed to be an ordinary researcher, but theoretical skills are needed to be an extraordinary researcher!

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Introduction: What is Empirical Research?

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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 is also known as

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

Introduction, what is empirical research, attribution.

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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

Portions of this guide were built using suggestions from other libraries, including Penn State and Utah State University libraries.

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empirical research is also known as

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What is Empirical research?

In empirical study, conclusions of the study are drawn from concrete empirical evidence. This evidence is also referred to as “verifiable” evidence. This evidence is gathered either through quantitative market research or qualitative market research methods.

An example of empirical analysis  would be if a researcher was interested in finding out whether listening to happy music promotes prosocial behaviour. An experiment could be conducted where one group of the audience is exposed to happy music and the other is not exposed to music at all. The participants could be given an opportunity to either help a stranger with something or not. The results are then evaluated to find whether happy music increases prosaically behavior or not.

Empirical Research

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What is an Empirical Study?

The origin of empirical methods starts from the quote “I will not believe it unless I see it myself.” Empirical observation emerged during the renaissance with medieval science. The word empirical is derived from the Greek word ‘empeirikos’ meaning ‘experienced’.

The word empirical, in today’s day and age, refers to collecting empirical data through methods of observation, experience, or by specific scientific instruments. All of these methods are dependent on observation and experiments which are used to collect data and test the same for arriving at conclusions. Online survey tools are an extremely effective technique which can be used for empirical methods.

Types and methodologies of empirical research

Empirical study uses qualitative or quantitative methods to conduct research and analyze results. 

  • Quantitative research: Quantitative research is referred to as the process of collecting as well as analyzing numerical data. It is generally used to find patterns, averages, predictions, as well as cause-effect relationships between the variables being studied. It is also used to generalize the results of a particular study to the population in consideration.

Empirical Research 2

  • Qualitative research: Qualitative research can be defined as a method used for market research which aims at obtaining data through open-ended questions and conversations with the intended consumers. This method aims at establishing not only “what” people think but “how” they come to that opinion as well as “why” they think so.

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Empirical Research 3

The empirical data that is collected from either of these methods has to be analyzed. Empirical evidence is analyzed using qualitative or quantitative methods. These methods are used to answer empirical questions that are clearly defined. The type of research design used by the researcher depends on the field and the nature of the problem. Some researchers use a combination of quantitative and qualitative methods to answer the questions set for the research.

Quantitative research methods

Quantitative research methods help in the analysis of the empirical evidence that has been gathered. By using these methods researchers can find support for their hypotheses.

  • Survey research: Survey research is the most common and widely used tool for quantitative research. Surveys are used to gather data by asking relevant questions to the respondents who are thought to have the relevant information we are seeking to acquire. Generally, a formal list of questionnaires is prepared which is circulated to the respondents and they can self-report their thoughts. Researchers use a non-disguised approach so that the participants of the survey know exactly what they are answering. In general, respondents are asked questions regarding their demographic details, and the opinion that the researcher is interested in studying. Surveys can be conducted through online polls, paper-pencil questionnaires, web-intercept surveys, etc. 

For example: In market research, customers are deemed as the most important part of the organisation. It is a known fact that satisfied customers will help your organisation grow directly by remaining loyal to your company and also by becoming an advocate for your brand. Researchers can use customer satisfaction survey templates to assess their brand’s value and how likely their customers are to recommend their brand to others.

  • Experimental research : This is one of the most recommended and reliant research methods in natural as well as social sciences. As the name suggests, experimental research (also known as experimentation) is usually based on one of more theories as its driving principle or rationale. In this method, the theory which is under study has not yet proven, it is merely a speculation. Thus, an experiment is performed in order to either prove or disprove the theory. If the results of the experiment are in line with the prediction made by the theory, then the theory is supported. If not, then the theory is refuted. 

For instance, if a researcher wants to study whether their dandruff protection product is successful in curing dandruff, and the only difference between the two groups under study is the product of interest (one group uses the product while group 2 uses a placebo), then dandruff could be considered as the dependent variable and the product curing it would be called an independent variable. Now, the independent variable, here, is “manipulated” in the sense that one group is exposed to it and one is not. All things being constant, if the product cures dandruff in group 1 as opposed to the group that is using a placebo, the experimental research findings are successful. This will help in establishing a cause and effect relationship, the product is “causing” the treatment (“effect”) of dandruff.

  • Correlational research : A correlation refers to an association or a relationship between two entities. A correlational research studies how one entity impacts the other and what are the changes that are observed when either one of them changes.  correlation coefficient ranges from -1 to +1. A correlation coefficient of +1 indicates a perfect positive correlation whereas a correlation coefficient of -1 indicates a perfect negative correlation between two variables. A correlation coefficient of 0 indicates that there is no relationship between the variables under study.

Some examples of correlational research questions: 

  • What is the relationship between gender and the purchase of a particular product under study?
  • The relationship between stress and burnout in employees of an organisation.
  • The relationship between choosing to work from home and the level of corona-phobia in employees.
  • Longitudinal study : Longitudinal surveys, on the other hand, involve studying variables for a long period of time and observing the changes in them from time to time. Here, the data is collected from the respondents at the beginning of the study, and then the researcher collects data at different time intervals until the end of the study. Longitudinal surveys are more popularly used in medicinal science to understand and evaluate the effects of medicines, or vaccines, in the long-run on participants. Because longitudinal surveys take place for several years, researchers can establish the sequence of events that may affect the variable under study.

For example: If researchers want to understand how smoking affects the development of cancer in later stages of life, they would choose participants who are different from other observable variables but similar in one: smoking. In this case, researchers would observe the participants who started smoking from adolescence into later adulthood and examine the changes in their body that are caused due to smoking. They can see how smoking has influenced the immunity of participants, their reaction to stress, and other variables relevant to the researcher. Over time, researchers can also observe the effects of quitting smoking if some participants decide to quit smoking later in their life. This will help researchers understand the interaction between health and smoking in more detail.

  • Cross sectional: In cross-sectional surveys, the study takes place at a single point in time. Hence, cross-sectional surveys do not entail the manipulation of the variables under study, and are limited in that way. Cross-sectional surveys allow researchers to study various characteristics, such as the demographic structure of the consumers, their interests, and attitudes, all at once. It aims to provide information about the population at the current moment in time. For example, cross-sectional surveys will tell us how the consumer is responding and feeling about the product at the present moment. It does not study the other variables that may affect the consumers’ reactions to the product in the future.

For example: Let us consider a researcher who is aiming to study developmental psychology. He/she may select groups of people who are of different ages but study them at one point in time. In this way, the difference between the groups will be attributed to their age differences instead of other variables that may happen over time.

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Qualitative research methods

A qualitative approach is more appropriate when tackling some research questions. This is especially true if the researcher wishes to observe the behaviors of the target audience in-depth. The results here are in descriptive form. Qualitative research is not predictive in nature. It enables researchers to build and support their theories to advance future potential quantitative research. Qualitative research methods are used to come up with conclusions to support the theory or hypothesis under study.

  • Case study: Case studies have evolved to become a valuable method for qualitative research. It is used for explaining a case of an organization or an entity. This is one of the simplest ways of conducting research because it involves an exhaustive understanding of the data collected and the interpretation of the same. 

For example: For example; let’s assume that a researcher is interested in understanding how to effectively solve the problems of turnover in organizations. While exploring, he came across an organization that had high rates of turnover and was able to solve the problem by the end of the year. The researcher can study this case in detail and come up with methods that increased the chances of success for this organization.

  • Observational method :  When doing qualitative research, maintaining the existing records can be a valuable source of information in the future. This data can be used in new research and also provide insights for the same. Observation is one of the common aspects that is used in every method we described above. It can be systematic or naturalistic. Qualitative observation of respondents’ answers, or their behaviors in particular settings can yield enriching insights. Hence, observation in qualitative research is used to gather information about relevant characteristics that the researcher is interested in studying.

For instance, if a smartphone brand wants to see how customers react to its products in a showroom, observers may be hired to note the same. The observers can use the recorded observations to evaluate and draw inferences about the customers.

  • One-on-one interview : Interviewing people of interest is one of the most common practices in qualitative research. Here, there is an in-depth personal interview carried out either face-to-face or through online mediums with one respondent at a time. This is a conversational method of gathering information and it invites the researcher with an opportunity to get a detailed response from the respondent.

For example: A one-on-one interview with an environmentalist will help to gather data on the current climate crisis in the world. 

  • Focus groups :  Another most commonly used method in qualitative research apart from interviewing people is focus group. In this method, data is usually conducted once a researcher includes a limited number of consumers (usually ranging from 6 to 10) from the target market and forms a group. 

For example: Let’s assume a researcher wants to explore what are qualities consumers value when buying a laptop. This could be the display quality, battery life, brand value, or even the color. The researcher can make a focus group of people who buy laptops regularly and understand the dynamics a consumer considers when buying electronic devices.

  • Text analysis : In text analysis, researchers analyze the social life of the respondents in the study and aim to decode the actions and the words of the respondents. Hence, text analysis is distinct from other qualitative research methods as it focuses on the social life of the respondents. In the last decade or so, text analysis has become increasingly popular due to the analysis of what consumers share on social media platforms in the form of blogs, images, and other texts. 

For example: Companies ask their customers to give detailed feedback on how satisfied they are with their customer support team. This data helps them make appropriate decisions to improve their team.

Sometimes researchers use a combination of methods to answer the questions. This is especially true when researchers tackle complex subject matters.

Exploratory Research Guide

Conducting exploratory research seems tricky but an effective guide can help.

Steps for conducting empirical research

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

Step #1: Define the purpose of the research

The very first step is for the researcher to identify the area of research and the problem can be addressed by finding out ways to solve it. The researcher should come up with various questions regarding what is the problem, who will benefit from the research, how should they go about the process, etc. The researchers should explore the purpose of the research in detail.

Step #2 : Supporting theories and relevant literature

After exploring and finding out the purpose of the research, the researcher must aim to find if there are existing theories that have addressed this before. The researcher has to figure out whether any previous studies can help them support their research. During this stage of empirical study, the researcher should aim at finding all relevant literature that will help them understand the problem at hand. The researcher should also come up with his/her own set of assumptions or problem statements that they wish to explore. 

Step #3: Creation of Hypothesis and measurement

If the researcher is aiming to solve a problem the problem has not been resolved efficiently in previous research, then the researcher creates his/her own problem statement. This problem statement, also called hypothesis, will be based on the questions that the researcher came up with while identifying the area of concern. The researcher can also form a hypothesis on the basis of prior research they found and studied during the literature review phase of the study.

Step #4: Methodology, research design and empirical data collection

Here the researcher has to define the strategies to be used for conducting the research. They can set up experiments in collecting data that can help them come up with probable hypotheses. On the basis of the hypotheses, researchers can decide whether they will require experimental or non-experimental methods for the conduction of the research. The research design will depend upon the field in which the research is to be conducted. The researchers will need to find parameters that can affect the validity of the research design. Researchers also need to choose appropriate methods of data collection, which in turn depends on the research question. There are many sampling methods that can be used by the researcher. Once, the data is collected, it has to be analysed.

Step #5: Data Analysis and result

Data can be analyzed either qualitatively and quantitatively. Researchers will need to decide which method they will employ depending upon the nature of the empirical data collected. Researchers can also use a combination of both for their study. On the basis of the analysis, the hypothesis will either be supported or rejected. Data analysis is the most important aspect of empirical observation.

Step #6: Conclusion

The researcher will have to collate the findings and make a report based on the empirical observations. The researcher can use previous theories and literature to support their hypothesis and lineage of findings. The researcher can also make recommendations for future research on similar issues.

Advantages of Empirical research

The advantages of empirical study are highlighted below:

  • Used for authentication. Empirical study is used to authenticate previous findings of experiments and empirical observations. This research methodology makes the conducted study more authentic and accurate. 
  • Empirical approach is useful for understanding dynamic changes. Due to the detailed process of literature review, empirical analysis is used in helping researchers understand dynamic changes in the field. It also enables them to strategies accordingly.
  • Provides a level of control . Empirical approach empowers researchers to demonstrate a level of control by allowing them to control multiple variables under study.
  • Empirical methods Increase internal validity . The high level of control in the research process makes an empirical method demonstrate high internal validity.

Disadvantages of Empirical research

Empirical approach is not without its limitations. Some of them include:

  • Time consuming . Empirical studies are time consuming because it requires researchers to collect data through multiple sources. It also requires them to assess various parameters involved in the research. 
  • Empirical approach is Expensive. The researcher may have to conduct the research at different locations or environments which may be expensive.
  • Difficult to acquire consent/permission. Sometimes empirical studies may be difficult to conduct due to the rules that are to be followed when conducting it.
  • Data collection in the empirical approach can be a problem. Since empirical data has to be collected from different methods and sources, it can pose a problem to the researchers.

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Why is there a need for empirical research?

Because most people today only believe in their experiences, empirical observation is increasingly becoming important. It is used to validate various hypotheses or refute them in the face of evidence. It also increases human knowledge and advances scientific progression. 

For instance, empirical analysis is used by pharmaceutical companies to test specific drugs. This is done by administering the drug on an experimental group, while giving a placebo to the control group. This is done to prove theories about the proposed drug and check its efficacy. This is the most crucial way in which leading evidence for various drugs have been found for many years. 

Empirical methods are used not just in medical science, but also in history, social science, market research, etc.

In today’s world it has become critical to conduct empirical analysis in order to support hypotheses and gather knowledge in several fields. The methods under empirical studies mentioned above help researchers to carry out research.

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Writing the Experimental Report: Overview, Introductions, and Literature Reviews

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Experimental reports (also known as "lab reports") are reports of empirical research conducted by their authors. You should think of an experimental report as a "story" of your research in which you lead your readers through your experiment. As you are telling this story, you are crafting an argument about both the validity and reliability of your research, what your results mean, and how they fit into other previous work.

These next two sections provide an overview of the experimental report in APA format. Always check with your instructor, advisor, or journal editor for specific formatting guidelines.

General-specific-general format

Experimental reports follow a general to specific to general pattern. Your report will start off broadly in your introduction and discussion of the literature; the report narrows as it leads up to your specific hypotheses, methods, and results. Your discussion transitions from talking about your specific results to more general ramifications, future work, and trends relating to your research.

Experimental reports in APA format have a title page. Title page formatting is as follows:

  • A running head and page number in the upper right corner (right aligned)
  • A definition of running head in IN ALL CAPS below the running head (left aligned)
  • Vertically and horizontally centered paper title, followed by author and affiliation

Please see our sample APA title page .

Crafting your story

Before you begin to write, carefully consider your purpose in writing: what is it that you discovered, would like to share, or would like to argue? You can see report writing as crafting a story about your research and your findings. Consider the following.

  • What is the story you would like to tell?
  • What literature best speaks to that story?
  • How do your results tell the story?
  • How can you discuss the story in broad terms?

During each section of your paper, you should be focusing on your story. Consider how each sentence, each paragraph, and each section contributes to your overall purpose in writing. Here is a description of one student's process.

Briel is writing an experimental report on her results from her experimental psychology lab class. She was interested in looking at the role gender plays in persuading individuals to take financial risks. After her data analysis, she finds that men are more easily persuaded by women to take financial risks and that men are generally willing to take more financial risks.

When Briel begins to write, she focuses her introduction on financial risk taking and gender, focusing on male behaviors. She then presents relevant literature on financial risk taking and gender that help illuminate her own study, but also help demonstrate the need for her own work. Her introduction ends with a study overview that directly leads from the literature review. Because she has already broadly introduced her study through her introduction and literature review, her readers can anticipate where she is going when she gets to her study overview. Her methods and results continue that story. Finally, her discussion concludes that story, discussing her findings, implications of her work, and the need for more research in the area of gender and financial risk taking.

The abstract gives a concise summary of the contents of the report.

  • Abstracts should be brief (about 100 words)
  • Abstracts should be self-contained and provide a complete picture of what the study is about
  • Abstracts should be organized just like your experimental report—introduction, literature review, methods, results and discussion
  • Abstracts should be written last during your drafting stage

Introduction

The introduction in an experimental article should follow a general to specific pattern, where you first introduce the problem generally and then provide a short overview of your own study. The introduction includes three parts: opening statements, literature review, and study overview.

Opening statements: Define the problem broadly in plain English and then lead into the literature review (this is the "general" part of the introduction). Your opening statements should already be setting the stage for the story you are going to tell.

Literature review: Discusses literature (previous studies) relevant to your current study in a concise manner. Keep your story in mind as you organize your lit review and as you choose what literature to include. The following are tips when writing your literature review.

  • You should discuss studies that are directly related to your problem at hand and that logically lead to your own hypotheses.
  • You do not need to provide a complete historical overview nor provide literature that is peripheral to your own study.
  • Studies should be presented based on themes or concepts relevant to your research, not in a chronological format.
  • You should also consider what gap in the literature your own research fills. What hasn't been examined? What does your work do that others have not?

Study overview: The literature review should lead directly into the last section of the introduction—your study overview. Your short overview should provide your hypotheses and briefly describe your method. The study overview functions as a transition to your methods section.

You should always give good, descriptive names to your hypotheses that you use consistently throughout your study. When you number hypotheses, readers must go back to your introduction to find them, which makes your piece more difficult to read. Using descriptive names reminds readers what your hypotheses were and allows for better overall flow.

In our example above, Briel had three different hypotheses based on previous literature. Her first hypothesis, the "masculine risk-taking hypothesis" was that men would be more willing to take financial risks overall. She clearly named her hypothesis in the study overview, and then referred back to it in her results and discussion sections.

Thais and Sanford (2000) recommend the following organization for introductions.

  • Provide an introduction to your topic
  • Provide a very concise overview of the literature
  • State your hypotheses and how they connect to the literature
  • Provide an overview of the methods for investigation used in your research

Bem (2006) provides the following rules of thumb for writing introductions.

  • Write in plain English
  • Take the time and space to introduce readers to your problem step-by-step; do not plunge them into the middle of the problem without an introduction
  • Use examples to illustrate difficult or unfamiliar theories or concepts. The more complicated the concept or theory, the more important it is to have clear examples
  • Open with a discussion about people and their behavior, not about psychologists and their research
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Q. How do I find an empirical research article?

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Answered By: Robert Miller Last Updated: Jan 05, 2024     Views: 340

What is an empirical article?

Characteristics of an empirical article

How do I find empirical articles?

Further details

Empirical research articles are also known as experimental or primary research articles.

Empirical articles are written by scientists reporting on an experiment or similar research that they conducted.

You'll find empirical articles in scholarly journals (also known as academic or peer-reviewed journals) within the library databases.

An empirical article will almost always be written in technical, specialized language, intended for an audience of experts rather than the general public (the writing will "sound" scientific). Often, you'll see quantitative (numerical) data arranged in tables or charts. And an empirical article will almost always have a specific structure following (more or less) these headings within the article:

  • The author summarizes her article
  • The author discusses the general background of her research topic; often, she will present a literature review, that is, summarize what other experts have written on this particular research topic
  • The author describes the study she designed and conducted
  • The author presents the data she gathered during her experiment
  • The author offers ideas about the importance and implications of her research findings, and speculates on future directions that similar research might take
  • The author gives a References list of sources she used in her paper

A reasonable keyword search on almost any scientific, medical, or technical topic, for example:

  • trauma AND "therapy animals"
  • "climate change" AND "polar ice"

will bring up many empirical articles in the following databases, which, being science-oriented, contain almost exclusively empirical articles. So just review the characteristics of an empirical article above, and you should be able to find them in library databases such as:

  • Academic Search Ultimate
  • Science Direct
  • APA PsycArticles
  • APA PsycInfo

In other databases, such Business Source Ultimate or Environment Complete , if you limit your search to "scholarly" only (sometimes labeled "academic" or "peer-reviewed" only), then many of your results will probably be empirical articles. Again, review an article to see if it matches the characteristics outlined above .

  • Finding Experimental (Empirical) Research Articles (psychology)
  • Primary Research Articles (general science)
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Experimental (Empirical) Research Articles

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How Can I Find Experimental (Empirical) Articles?

Many of the recommended databases in this research guide contain scholarly experimental articles (also known as empirical articles or research studies or primary research). Search in databases like: 

  • APA PsycInfo ​
  • ScienceDirect

Because those databases are rich in scholarly experimental articles, any well-structured search that you enter will retrieve experimental/empirical articles. These searches, for example, will retrieve many experimental/empirical articles:

  • caffeine AND "reaction time"
  • aging AND ("cognitive function" OR "cognitive ability")
  • "child development" AND play

Experimental (Empirical) Articles: How Will I Know One When I See One?

Scholarly experimental articles  to conduct and publish an experiment, an author or team of authors designs an experiment, gathers data, then analyzes the data and discusses the results of the experiment. a published experiment or research study will therefore  look  very different from other types of articles (newspaper stories, magazine articles, essays, etc.) found in our library databases..

In fact, newspapers, magazines, and websites written by journalists report on psychology research all the time, summarizing published experiments in non-technical language for the general public. Although that kind of article can be interesting to read (and can even lead you to look up the original experiment published by the researchers themselves),  to write a research paper about a psychology topic, you should, generally, use experimental articles written by researchers. The following guidelines will help you recognize an experimental article, written by the researchers themselves and published in a scholarly journal.

Structure of a Experimental Article Typically, an experimental article has the following sections:

  • The author summarizes her article
  • The author discusses the general background of her research topic; often, she will present a literature review, that is, summarize what other experts have written on this particular research topic
  • The author describes the experiment she designed and conducted
  • The author presents the data she gathered during her experiment
  • The author offers ideas about the importance and implications of her research findings, and speculates on future directions that similar research might take
  • The author gives a References list of sources she used in her paper

Look for articles structured in that way--they will be experimental/empirical articles. ​

Also, experimental/empirical articles are written in very formal, technical language (even the titles of the articles sound complicated!) and will usually contain numerical data presented in tables. 

As noted above, when you search in a database like APA PsycInfo, it's really easy to find experimental/empirical articles, once you know what you're looking for. Just in case, though, here is a shortcut that might help:

First, do your keyword search, for example:

search menu in APA PsycInfo

In the results screen, on the left-hand side, scroll down until you see "Methodology." You can use that menu to refine your search by limiting the articles to empirical studies only:

Methodology menu in APA PsycInfo

You can learn learn more about advanced search techniques in APA PsycInfo here . 

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  • http://orcid.org/0000-0002-8129-8376 Jane Ferguson 1 ,
  • http://orcid.org/0000-0001-9325-3362 Gemma Stringer 2 ,
  • http://orcid.org/0000-0002-0696-480X Kieran Walshe 2 ,
  • http://orcid.org/0000-0002-2972-7911 Thomas Allen 3 , 4 ,
  • http://orcid.org/0000-0003-1621-8648 Christos Grigoroglou 3 ,
  • http://orcid.org/0000-0002-2958-915X Darren M Ashcroft 5 ,
  • http://orcid.org/0000-0001-6450-5815 Evangelos Kontopantelis 6 , 7
  • 1 Health Services Management Centre, School of Social Policy , University of Birmingham , Birmingham , UK
  • 2 Alliance Manchester Business School , University of Manchester , Manchester , UK
  • 3 Manchester Centre for Health Economics, Division of Population Health, Health Services Research and Primary Care , University of Manchester , Manchester , UK
  • 4 Danish Centre for Health Economics , University of Southern Denmark , Odense , Denmark
  • 5 NIHR Greater Manchester Patient Safety Research Collaboration (PSRC), Division of Pharmacy and Optometry, Faculty of Biology Medicine and Health , University of Manchester , Manchester , UK
  • 6 Division of Informatics, Imaging and Data Sciences , University of Manchester , Manchester , UK
  • 7 NIHR School for Primary Care Research, Centre for Primary Care, Division of Population Health, Health Services Research and Primary Care , University of Manchester , Manchester , UK
  • Correspondence to Dr Jane Ferguson, Health Services Management Centre, University of Birmingham, Birmingham, UK; j.ferguson.1{at}bham.ac.uk

Background The use of temporary doctors, known as locums, has been common practice for managing staffing shortages and maintaining service delivery internationally. However, there has been little empirical research on the implications of locum working for quality and safety. This study aimed to investigate the implications of locum working for quality and safety.

Methods Qualitative semi-structured interviews and focus groups were conducted with 130 participants, including locums, patients, permanently employed doctors, nurses and other healthcare professionals with governance and recruitment responsibilities for locums across primary and secondary healthcare organisations in the English NHS. Data were collected between March 2021 and April 2022. Data were analysed using reflexive thematic analysis and abductive analysis.

Results Participants described the implications of locum working for quality and safety across five themes: (1) ‘familiarity’ with an organisation and its patients and staff was essential to delivering safe care; (2) ‘balance and stability’ of services reliant on locums were seen as at risk of destabilisation and lacking leadership for quality improvement; (3) ‘discrimination and exclusion’ experienced by locums had negative implications for morale, retention and patient outcomes; (4) ‘defensive practice’ by locums as a result of perceptions of increased vulnerability and decreased support; (5) clinical governance arrangements, which often did not adequately cover locum doctors.

Conclusion Locum working and how locums were integrated into organisations posed some significant challenges and opportunities for patient safety and quality of care. Organisations should take stock of how they work with the locum workforce to improve not only quality and safety but also locum experience and retention.

  • Health services research
  • Patient safety
  • Qualitative research
  • Quality improvement

Data availability statement

No data are available.

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See:  https://creativecommons.org/licenses/by/4.0/ .

https://doi.org/10.1136/bmjqs-2023-016699

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WHAT IS ALREADY KNOWN ON THIS TOPIC

Despite longstanding policy concerns about the implications of locum working for quality and safety, there has been little empirical research. Understanding how organisations engage, support and work with locums and how locum doctors integrate and interact with the complex and changing systems in which they work is essential if quality and safety are to be improved.

WHAT THIS STUDY ADDS

This qualitative study examines the perspectives of locums, patients and people who work with locums to identify the implications of temporary medical working for quality and safety.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

Organisations should examine how they engage, support and work with locums. Organisations and locums need to reflect on whether their practices support a collective approach to patient safety and quality of care.

Introduction

Temporary doctors, often known as locums, are a vital resource that enable healthcare organisations to deliver care by flexing capacity and covering staffing gaps. In the United Kingdom, all doctors, other than those in their first year of training after qualifying, can work as a locum. Locum work can vary from very short-term (a single shift) to longer-term assignments (weeks, months or even sometimes years). Locums find work through various platforms, including locum agencies, online job platforms, professional networks or word of mouth. Locum agencies typically have some governance responsibilities (such as compliance with regulations and licensing requirements), but the extent of these responsibilities varies and the NHS in England has no oversight over how recruitment agencies operate. Despite concerns among policymakers, healthcare providers, professional associations and professional regulators about the implications of locum working for quality and safety and cost, 1–3 there is limited robust empirical research to evidence or support those concerns.

The workforce retention crisis is a significant challenge in healthcare internationally 4–6 and persistent understaffing poses a serious risk to patient safety. 7 8 In the UK, high doctor turnover has been linked to poorer service and health outcomes 9 and has led NHS trusts and general practices (GPs) to be ‘overly reliant’ 3 on temporary staff to fill rota gaps. 10 11 Expenditure on temporary staff in the NHS in England increased from £3.45 billion to £5.2 billion between 2021 and 2022. 3 12 The NHS Long Term Workforce Plan aims to reduce reliance on temporary staff and make substantive employment the most cost-effective and attractive option. 3 However, with the vacancy rate in the NHS projected to increase, 13 locums are likely to continue to be essential to maintaining service provision, especially in shortage specialities such as psychiatry. 14

An obvious implication of locum working is a reduced likelihood of organisational and team integration, 15 familiarity and a shared understanding of ‘the way things are done around here’. 16 Locums are likely to be less familiar with teams and other contextual factors relevant to providing safe and effective care 17 and more likely to be situated on the periphery of organisational structures, teams and governance systems 1 18 Teamwork represents a powerful process to improve patient care, 19 20 and trust, shared understanding, communication and collaboration have been associated with better patient outcomes. 21 22 The ability of healthcare teams to develop and maintain team situational awareness, or a shared perception, comprehension and subsequent projection of what is going on in complex and changing clinical environments, has been described as crucial for patient safety. 23 24 Through participation and working together, 25 teams gain an understanding of the roles, skills and competencies of others to demonstrate ‘collective competence’, 26 27 which is critical for healthcare delivery, 28 29 and existing research on locums suggests a need for better integration into teams to improve quality and safety. 30 31

Context matters for patient safety and quality improvement, 32 33 yet the limited evidence 17 relating to locums practice is largely ‘acontextual’ and tends to ignore the role of the organisation in the integration of temporary staff, focusing instead on the potential risks locums present as individual clinicians, 17 30 which is perhaps unsurprising given the liminal space locums occupy. In the UK, responsibility for the quality and safety of healthcare services is shared primarily between organisations and the individual professionals working within them. 34 Organisations are responsible for creating systems and environments that promote and protect clinical governance and enable all doctors to meet their professional obligations, while doctors are expected to participate in the systems and processes put in place by regulators and organisations to protect and improve patient care. 35 However, NHS trusts and primary care organisations procure the services of locum doctors without assuming the responsibilities normally associated with an employer–employee relationship 30 and locums often struggle to participate in teams and governance systems that were designed for doctors working in conventional employment relationships. 18 36

There is longstanding debate about the role of individual accountability in patient safety and how responsibility is distributed between organisations and individuals. 37 A systems approach reasons that adverse events are likely to occur as a result of system failures rather than individual failures, 38 and patients are protected from mistakes by well designed systems and environments that promote safety cultures. 39 But locums are often positioned at the periphery of these systems, 30 and doctors who are new to and also peripheral to organisations, and organisations who are inexperienced with and unsupportive of locums are unlikely to be able to perform optimally. 40

The aim of this research was to provide evidence on how locum working arrangements impact quality and safety and the implications of locum working for patients, locums and health service organisations in primary and secondary care in the English NHS. Locum doctors are an essential and growing part of the healthcare workforce 1 who have been largely ignored in healthcare workforce research. This research addresses a gap in the empirical evidence base on how locum doctor working arrangements affect quality and safety, and provides, for the first time, an in-depth exploration that includes perspectives from patients, locums and the people they work with.

Study design and setting

A qualitative semi-structured interview and focus group study was conducted with locums, people working with locums, and patients with experience of being treated by locums. Participants were purposively sampled through 11 organisations, including NHS trusts, primary care practices, statutory NHS bodies and locum agencies. Locum doctor participants were recruited through these organisations, locum recruitment agencies and networks. We used purposive, snowball and convenience sampling, drawing on intelligence from stakeholders, including our project advisory group, to identify and recruit organisations and participants. Patient participants were recruited through patient and contributor forums. The forum involved active partnership between patients and researchers in the research process to develop research which is relevant and useful to patient and public needs. Participant demographics were monitored to ensure representation across a broad range of roles in primary and secondary care and to increase diversity in terms of gender and ethnicity (see table 1 ).

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Characteristics of study participants

Data collection

Three semi-structured interview and focus group guides were developed for use with locums, people working with locums and patients with experience of being treated by locums (as shown in online supplemental files 1-3 ). Our previous review of the literature relating to quality and safety and locum work 17 informed the schedules as well as the initial coding and thematic development. Schedules were also refined and informed by our patient and public involvement (PPI) forum and our project advisory group. Each schedule was intended to explore locum doctor working arrangements with a particular focus on understanding how locum doctor working may affect the safety and quality of care and what strategies or systems organisations and individuals used to assure or improve quality and safety. The topic guides for locums and people working with locums also covered governance and support, the impact of the COVID pandemic and policies and initiatives used to support locums.

Supplemental material

Interviews and focus groups were transcribed verbatim by a professional transcription company and organised into codes and themes using the software package NVivo. 41 Reflexive thematic analysis (RTA) 42 was used and involved familiarisation with the data by reading and re-reading the transcripts and field notes; coding the dataset and collating all relevant data extracts; generating initial themes by examining the codes and collated data to identify significant broader patterns of meaning across the dataset; reviewing themes by questioning whether themes answered the research question and told a convincing story of the data and combining, splitting and discarding themes as necessary; defining and naming themes by developing a detailed analysis of each theme; and finally the analytical write up which positioned the analysis in relation to existing literature. 43 RTA acknowledges the active role of researchers in knowledge production and the researcher’s subjectivity as the analytic resource. 42 RTA recognises interpretive variability between researchers based on differences in their knowledge and skills, theoretical assumptions and differences in how they responded to the dataset is acknowledged and expected. 42 The research team worked reflexively discussing their personal biases and their potential impact on the research at regular meetings throughout the data collection and analysis period. Our PPI forum were also involved in data collection and analysis, and offered a form of triangulation to enhance rigour, challenge and alternative interpretations of the findings. 44 Analysis adopted a constructionist epistemology, in that while we acknowledged the importance of recurrence in generating themes, meaning and meaningfulness were the central criteria in the coding process. 42

After themes were developed, an abductive approach was taken to position findings against a background of existing theory and knowledge. 17 30 This provided a way of constructing empirically based theorisations without confining theory to predefined concepts. 45 This approach integrated inductive data-driven coding with deductive theory-driven interpretation; aiming to find a middle ground between inductive and deductive methods and the most logical solution and useful explanation for phenomena. 45

We conducted 130 interviews with 88 participants who worked in healthcare and 42 patients took part in focus groups and one-to-one interviews. Participants included locums, permanently employed doctors; nurses and other health professionals; medical directors/clinical leaders; responsible officers (ROs are accountable for local clinical governance processes and focus on the performance of doctors) and appraisers; leads for medical staffing and clinical governance and practice managers (see table 2 ). Three experienced qualitative researchers (JF, GS and KW) and two members of the PPI forum (MM and MS) carried out five focus groups with 30 patients, and JF and GS carried out 12 one-to-one interviews. Data were collected between March 2021 and April 2022 during the COVID pandemic using video conferencing software (n=126) or over the phone (n=4) at a time convenient to participants. Interviews and focus groups ranged in length from 23 to 171 min, with the average interview being 59 min.

Healthcare organisations and participant roles

Thematic framework

Our findings are presented under five broad and interrelated themes that examine how locum work relates to and impacts quality and safety: ‘familiarity’ with an organisation and its patients and staff; ‘balance and stability’ in services with lots of locums; ‘discrimination and exclusion’ towards locums and their effects; ‘defensive practice’ by locums; and the positioning of locums outside clinical governance arrangements.

Familiarity: knowing who, where and how

Locums described often working in unfamiliar environments, sometimes with minimal induction and varying levels of support. Unfamiliarity, lack of access to or other restrictions on computer systems, policies, procedures and buildings meant that locums were not always able to do their job safely, productively or effectively.

That’s probably the biggest sort of safety aspect that sticks in my mind, is that it is unbelievably frustrating to have to learn a whole new set of patients from day to day … when I was signed up to four different hospitals, plus the locum agencies, I very quickly realised that not only is it the fact that you don’t know the patients from day to day, if you’re chopping and changing site the whole time, then store cupboards are laid out differently, ways of contacting relevant staff members are different, you’ve got to recognise what code to put in to bleep someone that’s different at every single site. (Interview 23, locum, secondary care)

Locum working sometimes created extra work for permanent staff who were responsible for inducting, training and supervising locums. The amount of additional workload was dependent on contextual factors, such as the experience of the locum, organisational support and length of placement, access to systems and what terms and conditions locums or organisations had negotiated. Locum reliance on permanent staff meant that care could be delayed, partially completed or not completed at all, which sometimes caused resentment.

Some of the things that we don’t … like, for example, procedures of limited clinical value that we don’t refer in for, they won’t know about those in our areas … So they’ll do referrals that we then will get pulled on. They’ll maybe prescribe medications that are not first line medications within our own formulary. So we see quite a bit of that, you know, there’s quite a lot of tidying up to be done afterwards or work. They generate that. So whilst we meet the patient numbers, they create a lot of work for the rest of the team. (Interview 3, practice manager, primary care)

Locums mitigated risks related to working in unfamiliar environments by avoiding organisations considered chaotic or unsafe, working below their grade to avoid having responsibility in unfamiliar organisations where they may not be supported or included in the team or working in a limited number of organisations to increase familiarity.

Most locums take jobs, locum work below their grade. So a person who’s at a registrar level would take a locum work as an SHO (senior house officer), because they don't know the trust that well. (Interview 55, locum, secondary care)

However, lack of familiarity and discontinuity could at times be beneficial for patients and organisations as fresh perspectives offered by locums led to different routes of treatment or management, and could alter organisational cultures or practices.

So that [locum] doctor, through that line of questioning and not having any sort of prior history … ordered the right tests and didn’t feel constrained in that practice about what tests that they could order. And someone subsequently … because when you get referred to hospital, the consultant said that that doctor was very much on the ball. And, of course, that’s a change to lifelong medication. And literally within a month of the medication kicking in, it transformed my life. (Focus group A, patient 1)

Balance and stability

The balance between locum and permanent staff had implications for quality and safety, organisational leadership, long-term planning and governance. Locums were often employed to deliver immediate services and consequently were less likely to be involved in team and organisational development. Locums recognised that having ‘an NHS run by locums’ was detrimental to quality and safety, and some avoided organisations that were locum dependent for this reason. Well functioning established teams were regarded as better able to incorporate a small number of locums without being significantly impacted.

Locum work, my view on it is they’re there to fill a gap. They shouldn’t be relied upon to deliver a service Monday to Friday, day in, day out, week in, week out. And unfortunately my trust see it as that, though, that’s my worry that they feel they’re not just plugging a gap, they’re almost as a workforce … (Interview 84, lead GP, primary and secondary care)

Departments that were disproportionately locum dependent were often perceived to lack clinical leadership and direction. An absence of consistent medical leadership meant that quality improvement was slower or less likely to happen, and trusting relationships between staff were harder to establish.

If you get a department that is disproportionately locum dependent, then it stagnates, it doesn't progress. Things like implementation of new NICE guidance, for example, that sort of thing tends not to happen or happen less well, less quickly. (Interview 30, responsible officer, secondary care)

Discrimination and exclusion

Most locums described negative behaviours and attitudes from staff and some patients, which impacted their involvement, inclusion and experiences in organisations. Negative attitudes and behaviours towards locums could affect turnover, locum well-being, team dynamics and potentially patient safety. Perceived disparities between pay, workload, competence and organisational and team commitment between locums and permanent staff could be sources of resentment and influenced how locums were treated and viewed. This compromised staff communication and reduced the sharing of important patient information.

I guess like any temporary post really, you struggle to invest in them, don't necessarily see them as being part of the team. Not very positive about them, particularly junior staff, particularly in the acute trusts. We'd have locums refusing to come back because of the treatment of the midwives. (Interview 86, clinical lead, secondary care)

Negative perceptions of competency and safety meant that locums were often stigmatised, marginalised and excluded. The identity of locum intersected and overlapped with other identities and was described as ‘layering up’ with ethnicity and gender to further exacerbate discrimination.

Oh, doctors coming over from Germany. There was one locum … that administered a dose of something and the patient died, and then there’s this whole layer of extra negativity attached to locum doctors in general because of what one doctor did, and that doctor happened to be someone from a different ethnicity … As a UK born and qualified doctor I can see that those overseas get it but I can also see that I have experienced that as well. So yeah, it can layer up with the whole locum thing. (Interview 59, locum GP, primary care)

A sense of othering and being seen as less was particularly evident during the COVID pandemic when resources were limited. Some locums described how they were not afforded the same protections as permanent members of staff and were sometimes expected to take on riskier work.

I’ve worked in another practice where, because they live on locums and they live on ad hoc locums, you’re a piece of dirt under the shoe. You don’t get gloves, you didn’t have aprons, you didn’t have a face visor, you didn’t have safety specs, you have to ask for a mask. Not only are you not treated as a service provider, you’re not treated as a colleague, someone with knowledge. (Interview 44, locum GP)

Defensive practice by locums

Locums recognised that they were likely to be scapegoated if things went wrong, and some locums described being more likely to practice defensively. Defensive practice has been defined as deviation from standard practice to avoid litigation, complaints or criticism. 46 Participants reported instances of defensive practice which involved providing services (eg, tests, referrals) or avoiding high-risk decisions, usually to reduce the risk of adverse outcomes such as patient complaints or potential termination of contract at short notice. Locums described practicing defensively because they were attempting to practice as safely as possible in complex unfamiliar environments where they were professionally isolated and perceived negatively. Permanent members of staff could perceive that locums practiced defensively because they lacked confidence in their abilities. The diversion of resources away from more clinically relevant activities placed additional burden on teams, who were already facing significant workload challenges.

Being risk averse and practising defensive medicine usually means more tests, more referrals, whereas holding risk tends to be disadvantageous for you as a locum because what’s the benefit to you of not doing that. You’re benefiting the system by rationing resource, the patient won’t thank you. (Interview 35, locum GP)

Locums described avoiding making decisions when risks to employment or medical licenses were perceived as high. Locums felt they were more vulnerable to criticisms of their clinical competence and disempowered to make decisions. Others felt that some locums were simply avoiding work and evaded responsibility for patients by pushing work onto others or into the future.

You don’t interfere, very simple. Over time locums have learned that if you interfere, if you participate in the team, you participate in patient care, [and this] is when you get into trouble … Well most of the locums that I know will just say, okay, there’s already somebody else who’s made a decision, it’s not my job to make a decision, I just follow through. If things go wrong, call the senior person and be done with it, that’s the end of my role. Actually doing something to protect a patient is not important for a locum because the risk is too high. (Interview 55, locum, secondary care)

Locums fall outside clinical governance arrangements

Governance practices in relation to locums varied widely and were not generally regarded as being as robust in comparison to permanently employed doctors. Responsibility for involving locum doctors in performance feedback, supervision, educational opportunities, appraisal and quality improvement was unclear. While some organisations included locums in their governance activities, others regarded locum work as transactional; where the locum was there to provide a finite service and the organisation assumed no responsibilities for their performance, development or oversight. There were concerns that governance structures were modelled on and designed for permanently employed doctors and did not work for locums. When deficits in performance were undetected or unaddressed, doctor performance and patient safety could be jeopardised.

I think it’s a remote world. It’s like a cloud, you know, it’s like the cloud. We talk about the cloud when it comes to storing information. And I think locum world is a bit like that … And I don’t know the doctors anywhere like as much as I did when I was an RO in the NHS, I knew them all personally. If I used to have a problem, I used to get them in my office there and then, chat it all through, sort it. Can’t do that in locum world, it might take me four days to get hold of the doctor, some of them won’t respond immediately … They don’t know me and I don’t know them. (Interview 51, responsible officer, locum agency)

The absence of typical recruitment processes (involving meeting a doctor, carrying out an interview and following up on references) meant that healthcare organisations were reliant on partial information from locum agencies, which made it difficult to determine competency, scope of practice and suitability for a role. However, staff shortages and a requirement to meet safe staffing ratios meant that organisational leaders had little recourse of action if they were unsure about a doctor’s capability, which caused anxiety and frustration. This suggests that the provision of healthcare superseded ensuring safety standards and necessitated accepting one of two objectionable alternatives; accepting gaps in staffing that may jeopardise patient safety or accepting unknown doctors; each of which may compromise patient safety.

If a locum turns up and I have serious doubts about their ability to do the job to the required standard, I don’t have any recourse … And therefore I’m in a position where either I accept this locum or I don’t. There’s not much in the way of middle ground. Not accepting them is a really unpalatable choice because if I say look, I’m sorry, I don’t think you’re up to this, I think you should go home, that leaves me with a gap. (Interview 30, consultant and responsible officer, secondary care)

Similar governance and information sharing problems were described by locum agencies and NHS organisations; both described difficulties in gathering and sharing feedback. When concerns were raised, participants were often uncertain as to what happened to the information they provided and whether it was shared or acted on. Locums often did not get to hear about concerns raised about them, meaning learning opportunities were missed.

It would give you more confidence if you heard back. And sometimes I'll pick up the phone and you try to do the best you can to make sure this information gets passed on. But I just have this nagging doubt that I'm not always convinced it does. (Interview 30, responsible officer, secondary care)

There was also a perception from some locum agency responsible officers that while most locum doctors were excellent, there were some locums who were isolated and in need of organisational and professional support.

You have to accept that whilst within the agency world, 80 per cent of the doctors we place are excellent, and have no problems, and do a great job, perhaps 20 per cent are those that have shaken down to that 20 per cent in the agency world, because they’ve not succeeded in the NHS, they’ve not got a substantive place, they are lost souls. And they are less able to cope with the vicissitudes of busy clinical life and professional life within a large organisation such as the NHS. (Interview 47, responsible officer, locum agency)

Our findings provide some profound and concerning insights for patient safety and quality of care. The ways in which locums were recruited, inducted, deployed and integrated, and supported by organisations undoubtedly affected quality and safety. Our findings indicate that regardless of their level of experience, it was unlikely that locum doctors would be able to function optimally in unfamiliar environments; and organisations who had poor supportive infrastructure and governance mechanisms for locums were less likely to deliver high-quality safe services.

Locums were often regarded as organisational outsiders—positioned at the periphery of the team and the organisation. The implications of transience and peripheral participation were weaker relationships with organisations, teams, peers and patients, leading some to suggest locum working is better suited to experienced doctors. 47 Consistent with previous research, 48 frequent variation in process, systems and equipment, combined with disruption in relationships and a lack of mutual awareness of team skills and competencies, decreased collective competence, placed additional burden on the wider healthcare team and reduced patient safety. As others have found in research on safe staffing and nursing, 49 temporary staff are not effective substitutes for staff who regularly work in the organisation. Safe medical staffing is not just achieved by filling rota gaps, but also team composition and doctors’ familiarity with the team and organisation must be taken into account. Regulatory agencies should consider locum usage in their inspections and perhaps be particularly concerned when organisations have ‘services run on locums’.

Our research found, as others have, 18 that organisations and doctors sometimes struggled to meet their governance obligations and that governance activities differed based on contractual status and organisational policies and norms, with systems being less robust for locums. This research has highlighted that much still needs to be done to develop governance systems that promote and protect the interests of patients and create an environment which supports locum doctors in meeting their professional obligations.

More positively, locum doctors are a potentially valuable source of information about safety concerns, faulty systems or poor conduct. 50 Locums move between organisations, have broad systems knowledge and are perhaps better placed to identify some quality and safety issues than permanent doctors. However, findings indicate opportunities for shared learning were often missed. Locums recognised their precarity and vulnerability when offering second opinions, sharing improvement ideas or voicing safety concerns; meaning opinions were not always offered and concerns were not always raised. Failure to voice concerns is a persistent problem in healthcare, 51 and locums may be even less inclined to offer potentially valuable information about safety concerns because of their perceptions of unsupportive organisational climates.

Our findings shed light on how temporary doctors fit into the enduring debate 37 around how responsibility between organisational systems and individual professionals is distributed. Locums appear to represent a subsection of the medical profession for whom the wider paradigm shift from a focus on individual blame to a systems approach 52 appeared not to have been made. Locums were often not regarded as a part of the organisation, and therefore the system, and not afforded the same protections as permanent staff when things went wrong. Blaming locums when things go wrong and punishing or sanctioning individuals who make errors in contexts that were not designed to incorporate temporary workers may divert attention from understanding inadequately designed, poorly functioning systems, or indeed the individual practice of other doctors. While we should take into account systemic factors that impede locums from performing safely, we should expect high standards of healthcare professionals, be cognisant of individual agency and recognise the distinction between blaming someone and holding them responsible. 53

Strengths and limitations

This large qualitative study explores locum working and quality and safety in an under-researched, yet growing area of the medical workforce. However, sites were all based in England, which means caution should be taken when extrapolating findings. Similar research in other countries and contexts to understand more about locum doctor working and quality and safety is therefore important. It is possible that our sample may have been skewed towards locums, healthcare professionals and patients who had more negative perceptions and experiences, although accounts resonate with previous research 30 and patient perspectives were generally positive. Our data were collected during the COVID pandemic, which may have affected findings as there was a reduction in locum working during that time 10 11 ; it also meant we were unable to carry out observations, which would have strengthened our findings and mitigated some of the inherent limitations of interviews, such as recall bias. We used both one-to-one interviews and focus groups in data collection. Although flexibility in data collection meant that participants had the option to take part in an interview or a focus group, these methods are used for different reasons and produce different data. There may have been differences in what participants disclosed depending on the method

Our findings show that the way in which doctors who worked on a temporary basis were integrated into organisations posed some significant challenges and opportunities for patient safety and quality of care, and that both organisations and locums had a part to play in improvement. Doctors working as locums are a heterogeneous group with differing backgrounds, experiences, skills and capabilities that likely reflect the variability seen in the wider population of doctors. Locums are working in the same pressured and imperfect systems as other health workers; it is vital that systemic problems are not mistaken for problems about individuals and important to recognise that a locum is not a type of doctor but a way of working. Our findings are a call to action for organisations to take stock of how they engage, support and work with locums, and asks both locums and organisations to reflect on whether their practices support a collective approach to patient safety and quality of care.

Ethics statements

Patient consent for publication.

Not applicable.

Ethics approval

This study involves human participants and was approved by the Health Research Authority North West—Haydock Research Ethics Committee 20/NW/0386. Participants gave informed consent to participate in the study before taking part.

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Supplementary materials

Supplementary data.

This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

  • Data supplement 1
  • Data supplement 2
  • Data supplement 3
  • Data supplement 4

Twitter @janefergo, @@kieran_walshe

Contributors JF, KW, DA, TA and EK conceived the study. Recruitment was led by JF and supported by GS. JF, GS and KW conducted the interviews, reviewed and analysed the transcripts, and JF wrote the first version of the manuscript. Two members of the patient and public involvement (PPI) forum also assisted with focus groups. JF conducted data analysis with input from KW and GS, the PPI forum, and review by all authors. JF and KW were involved in initial critical review and revision of the manuscript, followed by all authors. All authors read and approved the final version of the manuscript. JF is the guarantor.

Funding This study was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR128349), and the NIHR Greater Manchester Patient Safety Research Collaboration (PSRC). The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care.

Competing interests None declared.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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  • Editorial Locums: threat or opportunity Richard Lilford BMJ Quality & Safety 2024; - Published Online First: 16 Apr 2024. doi: 10.1136/bmjqs-2023-016951

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