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September 8, 2021

Explaining How Research Works

Understanding Research infographic

We’ve heard “follow the science” a lot during the pandemic. But it seems science has taken us on a long and winding road filled with twists and turns, even changing directions at times. That’s led some people to feel they can’t trust science. But when what we know changes, it often means science is working.

Expaling How Research Works Infographic en español

Explaining the scientific process may be one way that science communicators can help maintain public trust in science. Placing research in the bigger context of its field and where it fits into the scientific process can help people better understand and interpret new findings as they emerge. A single study usually uncovers only a piece of a larger puzzle.

Questions about how the world works are often investigated on many different levels. For example, scientists can look at the different atoms in a molecule, cells in a tissue, or how different tissues or systems affect each other. Researchers often must choose one or a finite number of ways to investigate a question. It can take many different studies using different approaches to start piecing the whole picture together.

Sometimes it might seem like research results contradict each other. But often, studies are just looking at different aspects of the same problem. Researchers can also investigate a question using different techniques or timeframes. That may lead them to arrive at different conclusions from the same data.

Using the data available at the time of their study, scientists develop different explanations, or models. New information may mean that a novel model needs to be developed to account for it. The models that prevail are those that can withstand the test of time and incorporate new information. Science is a constantly evolving and self-correcting process.

Scientists gain more confidence about a model through the scientific process. They replicate each other’s work. They present at conferences. And papers undergo peer review, in which experts in the field review the work before it can be published in scientific journals. This helps ensure that the study is up to current scientific standards and maintains a level of integrity. Peer reviewers may find problems with the experiments or think different experiments are needed to justify the conclusions. They might even offer new ways to interpret the data.

It’s important for science communicators to consider which stage a study is at in the scientific process when deciding whether to cover it. Some studies are posted on preprint servers for other scientists to start weighing in on and haven’t yet been fully vetted. Results that haven't yet been subjected to scientific scrutiny should be reported on with care and context to avoid confusion or frustration from readers.

We’ve developed a one-page guide, "How Research Works: Understanding the Process of Science" to help communicators put the process of science into perspective. We hope it can serve as a useful resource to help explain why science changes—and why it’s important to expect that change. Please take a look and share your thoughts with us by sending an email to  [email protected].

Below are some additional resources:

  • Discoveries in Basic Science: A Perfectly Imperfect Process
  • When Clinical Research Is in the News
  • What is Basic Science and Why is it Important?
  • ​ What is a Research Organism?
  • What Are Clinical Trials and Studies?
  • Basic Research – Digital Media Kit
  • Decoding Science: How Does Science Know What It Knows? (NAS)
  • Can Science Help People Make Decisions ? (NAS)

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Home Market Research

What is Research: Definition, Methods, Types & Examples

What is Research

The search for knowledge is closely linked to the object of study; that is, to the reconstruction of the facts that will provide an explanation to an observed event and that at first sight can be considered as a problem. It is very human to seek answers and satisfy our curiosity. Let’s talk about research.

Content Index

What is Research?

What are the characteristics of research.

  • Comparative analysis chart

Qualitative methods

Quantitative methods, 8 tips for conducting accurate research.

Research is the careful consideration of study regarding a particular concern or research problem using scientific methods. According to the American sociologist Earl Robert Babbie, “research is a systematic inquiry to describe, explain, predict, and control the observed phenomenon. It involves inductive and deductive methods.”

Inductive methods analyze an observed event, while deductive methods verify the observed event. Inductive approaches are associated with qualitative research , and deductive methods are more commonly associated with quantitative analysis .

Research is conducted with a purpose to:

  • Identify potential and new customers
  • Understand existing customers
  • Set pragmatic goals
  • Develop productive market strategies
  • Address business challenges
  • Put together a business expansion plan
  • Identify new business opportunities
  • Good research follows a systematic approach to capture accurate data. Researchers need to practice ethics and a code of conduct while making observations or drawing conclusions.
  • The analysis is based on logical reasoning and involves both inductive and deductive methods.
  • Real-time data and knowledge is derived from actual observations in natural settings.
  • There is an in-depth analysis of all data collected so that there are no anomalies associated with it.
  • It creates a path for generating new questions. Existing data helps create more research opportunities.
  • It is analytical and uses all the available data so that there is no ambiguity in inference.
  • Accuracy is one of the most critical aspects of research. The information must be accurate and correct. For example, laboratories provide a controlled environment to collect data. Accuracy is measured in the instruments used, the calibrations of instruments or tools, and the experiment’s final result.

What is the purpose of research?

There are three main purposes:

  • Exploratory: As the name suggests, researchers conduct exploratory studies to explore a group of questions. The answers and analytics may not offer a conclusion to the perceived problem. It is undertaken to handle new problem areas that haven’t been explored before. This exploratory data analysis process lays the foundation for more conclusive data collection and analysis.

LEARN ABOUT: Descriptive Analysis

  • Descriptive: It focuses on expanding knowledge on current issues through a process of data collection. Descriptive research describe the behavior of a sample population. Only one variable is required to conduct the study. The three primary purposes of descriptive studies are describing, explaining, and validating the findings. For example, a study conducted to know if top-level management leaders in the 21st century possess the moral right to receive a considerable sum of money from the company profit.

LEARN ABOUT: Best Data Collection Tools

  • Explanatory: Causal research or explanatory research is conducted to understand the impact of specific changes in existing standard procedures. Running experiments is the most popular form. For example, a study that is conducted to understand the effect of rebranding on customer loyalty.

Here is a comparative analysis chart for a better understanding:

 
Approach used Unstructured Structured Highly structured
Conducted throughAsking questions Asking questions By using hypotheses.
TimeEarly stages of decision making Later stages of decision makingLater stages of decision making

It begins by asking the right questions and choosing an appropriate method to investigate the problem. After collecting answers to your questions, you can analyze the findings or observations to draw reasonable conclusions.

When it comes to customers and market studies, the more thorough your questions, the better the analysis. You get essential insights into brand perception and product needs by thoroughly collecting customer data through surveys and questionnaires . You can use this data to make smart decisions about your marketing strategies to position your business effectively.

To make sense of your study and get insights faster, it helps to use a research repository as a single source of truth in your organization and manage your research data in one centralized data repository .

Types of research methods and Examples

what is research

Research methods are broadly classified as Qualitative and Quantitative .

Both methods have distinctive properties and data collection methods .

Qualitative research is a method that collects data using conversational methods, usually open-ended questions . The responses collected are essentially non-numerical. This method helps a researcher understand what participants think and why they think in a particular way.

Types of qualitative methods include:

  • One-to-one Interview
  • Focus Groups
  • Ethnographic studies
  • Text Analysis

Quantitative methods deal with numbers and measurable forms . It uses a systematic way of investigating events or data. It answers questions to justify relationships with measurable variables to either explain, predict, or control a phenomenon.

Types of quantitative methods include:

  • Survey research
  • Descriptive research
  • Correlational research

LEARN MORE: Descriptive Research vs Correlational Research

Remember, it is only valuable and useful when it is valid, accurate, and reliable. Incorrect results can lead to customer churn and a decrease in sales.

It is essential to ensure that your data is:

  • Valid – founded, logical, rigorous, and impartial.
  • Accurate – free of errors and including required details.
  • Reliable – other people who investigate in the same way can produce similar results.
  • Timely – current and collected within an appropriate time frame.
  • Complete – includes all the data you need to support your business decisions.

Gather insights

What is a research - tips

  • Identify the main trends and issues, opportunities, and problems you observe. Write a sentence describing each one.
  • Keep track of the frequency with which each of the main findings appears.
  • Make a list of your findings from the most common to the least common.
  • Evaluate a list of the strengths, weaknesses, opportunities, and threats identified in a SWOT analysis .
  • Prepare conclusions and recommendations about your study.
  • Act on your strategies
  • Look for gaps in the information, and consider doing additional inquiry if necessary
  • Plan to review the results and consider efficient methods to analyze and interpret results.

Review your goals before making any conclusions about your study. Remember how the process you have completed and the data you have gathered help answer your questions. Ask yourself if what your analysis revealed facilitates the identification of your conclusions and recommendations.

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What is Research? Definition, Types, Methods, and Examples

Academic research is a methodical way of exploring new ideas or understanding things we already know. It involves gathering and studying information to answer questions or test ideas and requires careful thinking and persistence to reach meaningful conclusions. Let’s try to understand what research is.   

Table of Contents

Why is research important?    

Whether it’s doing experiments, analyzing data, or studying old documents, research helps us learn more about the world. Without it, we rely on guesswork and hearsay, often leading to mistakes and misconceptions. By using systematic methods, research helps us see things clearly, free from biases. (1)   

What is the purpose of research?  

In the real world, academic research is also a key driver of innovation. It brings many benefits, such as creating valuable opportunities and fostering partnerships between academia and industry. By turning research into products and services, science makes meaningful improvements to people’s lives and boosts the economy. (2)(3)  

What are the characteristics of research?    

The research process collects accurate information systematically. Logic is used to analyze the collected data and find insights. Checking the collected data thoroughly ensures accuracy. Research also leads to new questions using existing data.   

Accuracy is key in research, which requires precise data collection and analysis. In scientific research, laboratories ensure accuracy by carefully calibrating instruments and controlling experiments. Every step is checked to maintain integrity, from instruments to final results. Accuracy gives reliable insights, which in turn help advance knowledge.   

Types of research    

The different forms of research serve distinct purposes in expanding knowledge and understanding:    

  • Exploratory research ventures into uncharted territories, exploring new questions or problem areas without aiming for conclusive answers. For instance, a study may delve into unexplored market segments to better understand consumer behaviour patterns.   
  • Descriptive research delves into current issues by collecting and analyzing data to describe the behaviour of a sample population. For instance, a survey may investigate millennials’ spending habits to gain insights into their purchasing behaviours.   
  • Explanatory research, also known as causal research, seeks to understand the impact of specific changes in existing procedures. An example might be a study examining how changes in drug dosage over some time improve patients’ health.   
  • Correlational research examines connections between two sets of data to uncover meaningful relationships. For instance, a study may analyze the relationship between advertising spending and sales revenue.   
  • Theoretical research deepens existing knowledge without attempting to solve specific problems. For example, a study may explore theoretical frameworks to understand the underlying principles of human behaviour.   
  • Applied research focuses on real-world issues and aims to provide practical solutions. An example could be a study investigating the effectiveness of a new teaching method in improving student performance in schools.  (4)

Types of research methods

  • Qualitative Method: Qualitative research gathers non-numerical data through interactions with participants. Methods include one-to-one interviews, focus groups, ethnographic studies, text analysis, and case studies. For example, a researcher interviews cancer patients to understand how different treatments impact their lives emotionally.    
  • Quantitative Method: Quantitative methods deal with numbers and measurable data to understand relationships between variables. They use systematic methods to investigate events and aim to explain or predict outcomes. For example, Researchers study how exercise affects heart health by measuring variables like heart rate and blood pressure in a large group before and after an exercise program. (5)  

Basic steps involved in the research process    

Here are the basic steps to help you understand the research process:   

  • Choose your topic: Decide the specific subject or area that you want to study and investigate. This decision is the foundation of your research journey.   
  • Find information: Look for information related to your research topic. You can search in journals, books, online, or ask experts for help.   
  • Assess your sources: Make sure the information you find is reliable and trustworthy. Check the author’s credentials and the publication date.   
  • Take notes: Write down important information from your sources that you can use in your research.   
  • Write your paper: Use your notes to write your research paper. Broadly, start with an introduction, then write the body of your paper, and finish with a conclusion.   
  • Cite your sources: Give credit to the sources you used by including citations in your paper.   
  • Proofread: Check your paper thoroughly for any errors in spelling, grammar, or punctuation before you submit it. (6)

How to ensure research accuracy?  

Ensuring accuracy in research is a mix of several essential steps:    

  • Clarify goals: Start by defining clear objectives for your research. Identify your research question, hypothesis, and variables of interest. This clarity will help guide your data collection and analysis methods, ensuring that your research stays focused and purposeful.   
  • Use reliable data: Select trustworthy sources for your information, whether they are primary data collected by you or secondary data obtained from other sources. For example, if you’re studying climate change, use data from reputable scientific organizations with transparent methodologies.   
  • Validate data: Validate your data to ensure it meets the standards of your research project. Check for errors, outliers, and inconsistencies at different stages, such as during data collection, entry, cleaning, or analysis.    
  • Document processes: Documenting your data collection and analysis processes is essential for transparency and reproducibility. Record details such as data collection methods, cleaning procedures, and analysis techniques used. This documentation not only helps you keep track of your research but also enables others to understand and replicate your work.   
  • Review results: Finally, review and verify your research findings to confirm their accuracy and reliability. Double-check your analyses, cross-reference your data, and seek feedback from peers or supervisors. (7) 

Research is crucial for better understanding our world and for social and economic growth. By following ethical guidelines and ensuring accuracy, researchers play a critical role in driving this progress, whether through exploring new topics or deepening existing knowledge.   

References:  

  • Why is Research Important – Introductory Psychology – Washington State University  
  • The Role Of Scientific Research In Driving Business Innovation – Forbes  
  • Innovation – Royal Society  
  • Types of Research – Definition & Methods – Bachelor Print  
  • What Is Qualitative vs. Quantitative Study? – National University  
  • Basic Steps in the Research Process – North Hennepin Community College  
  • Best Practices for Ensuring Data Accuracy in Research – LinkedIn  

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What is Scientific Research and How Can it be Done?

Scientific researches are studies that should be systematically planned before performing them. In this review, classification and description of scientific studies, planning stage randomisation and bias are explained.

Research conducted for the purpose of contributing towards science by the systematic collection, interpretation and evaluation of data and that, too, in a planned manner is called scientific research: a researcher is the one who conducts this research. The results obtained from a small group through scientific studies are socialised, and new information is revealed with respect to diagnosis, treatment and reliability of applications. The purpose of this review is to provide information about the definition, classification and methodology of scientific research.

Before beginning the scientific research, the researcher should determine the subject, do planning and specify the methodology. In the Declaration of Helsinki, it is stated that ‘the primary purpose of medical researches on volunteers is to understand the reasons, development and effects of diseases and develop protective, diagnostic and therapeutic interventions (method, operation and therapies). Even the best proven interventions should be evaluated continuously by investigations with regard to reliability, effectiveness, efficiency, accessibility and quality’ ( 1 ).

The questions, methods of response to questions and difficulties in scientific research may vary, but the design and structure are generally the same ( 2 ).

Classification of Scientific Research

Scientific research can be classified in several ways. Classification can be made according to the data collection techniques based on causality, relationship with time and the medium through which they are applied.

  • Observational
  • Experimental
  • Descriptive
  • Retrospective
  • Prospective
  • Cross-sectional
  • Social descriptive research ( 3 )

Another method is to classify the research according to its descriptive or analytical features. This review is written according to this classification method.

I. Descriptive research

  • Case series
  • Surveillance studies

II. Analytical research

  • Observational studies: cohort, case control and cross- sectional research
  • Interventional research: quasi-experimental and clinical research
  • Case Report: it is the most common type of descriptive study. It is the examination of a single case having a different quality in the society, e.g. conducting general anaesthesia in a pregnant patient with mucopolysaccharidosis.
  • Case Series: it is the description of repetitive cases having common features. For instance; case series involving interscapular pain related to neuraxial labour analgesia. Interestingly, malignant hyperthermia cases are not accepted as case series since they are rarely seen during historical development.
  • Surveillance Studies: these are the results obtained from the databases that follow and record a health problem for a certain time, e.g. the surveillance of cross-infections during anaesthesia in the intensive care unit.

Moreover, some studies may be experimental. After the researcher intervenes, the researcher waits for the result, observes and obtains data. Experimental studies are, more often, in the form of clinical trials or laboratory animal trials ( 2 ).

Analytical observational research can be classified as cohort, case-control and cross-sectional studies.

Firstly, the participants are controlled with regard to the disease under investigation. Patients are excluded from the study. Healthy participants are evaluated with regard to the exposure to the effect. Then, the group (cohort) is followed-up for a sufficient period of time with respect to the occurrence of disease, and the progress of disease is studied. The risk of the healthy participants getting sick is considered an incident. In cohort studies, the risk of disease between the groups exposed and not exposed to the effect is calculated and rated. This rate is called relative risk. Relative risk indicates the strength of exposure to the effect on the disease.

Cohort research may be observational and experimental. The follow-up of patients prospectively is called a prospective cohort study . The results are obtained after the research starts. The researcher’s following-up of cohort subjects from a certain point towards the past is called a retrospective cohort study . Prospective cohort studies are more valuable than retrospective cohort studies: this is because in the former, the researcher observes and records the data. The researcher plans the study before the research and determines what data will be used. On the other hand, in retrospective studies, the research is made on recorded data: no new data can be added.

In fact, retrospective and prospective studies are not observational. They determine the relationship between the date on which the researcher has begun the study and the disease development period. The most critical disadvantage of this type of research is that if the follow-up period is long, participants may leave the study at their own behest or due to physical conditions. Cohort studies that begin after exposure and before disease development are called ambidirectional studies . Public healthcare studies generally fall within this group, e.g. lung cancer development in smokers.

  • Case-Control Studies: these studies are retrospective cohort studies. They examine the cause and effect relationship from the effect to the cause. The detection or determination of data depends on the information recorded in the past. The researcher has no control over the data ( 2 ).

Cross-sectional studies are advantageous since they can be concluded relatively quickly. It may be difficult to obtain a reliable result from such studies for rare diseases ( 2 ).

Cross-sectional studies are characterised by timing. In such studies, the exposure and result are simultaneously evaluated. While cross-sectional studies are restrictedly used in studies involving anaesthesia (since the process of exposure is limited), they can be used in studies conducted in intensive care units.

  • Quasi-Experimental Research: they are conducted in cases in which a quick result is requested and the participants or research areas cannot be randomised, e.g. giving hand-wash training and comparing the frequency of nosocomial infections before and after hand wash.
  • Clinical Research: they are prospective studies carried out with a control group for the purpose of comparing the effect and value of an intervention in a clinical case. Clinical study and research have the same meaning. Drugs, invasive interventions, medical devices and operations, diets, physical therapy and diagnostic tools are relevant in this context ( 6 ).

Clinical studies are conducted by a responsible researcher, generally a physician. In the research team, there may be other healthcare staff besides physicians. Clinical studies may be financed by healthcare institutes, drug companies, academic medical centres, volunteer groups, physicians, healthcare service providers and other individuals. They may be conducted in several places including hospitals, universities, physicians’ offices and community clinics based on the researcher’s requirements. The participants are made aware of the duration of the study before their inclusion. Clinical studies should include the evaluation of recommendations (drug, device and surgical) for the treatment of a disease, syndrome or a comparison of one or more applications; finding different ways for recognition of a disease or case and prevention of their recurrence ( 7 ).

Clinical Research

In this review, clinical research is explained in more detail since it is the most valuable study in scientific research.

Clinical research starts with forming a hypothesis. A hypothesis can be defined as a claim put forward about the value of a population parameter based on sampling. There are two types of hypotheses in statistics.

  • H 0 hypothesis is called a control or null hypothesis. It is the hypothesis put forward in research, which implies that there is no difference between the groups under consideration. If this hypothesis is rejected at the end of the study, it indicates that a difference exists between the two treatments under consideration.
  • H 1 hypothesis is called an alternative hypothesis. It is hypothesised against a null hypothesis, which implies that a difference exists between the groups under consideration. For example, consider the following hypothesis: drug A has an analgesic effect. Control or null hypothesis (H 0 ): there is no difference between drug A and placebo with regard to the analgesic effect. The alternative hypothesis (H 1 ) is applicable if a difference exists between drug A and placebo with regard to the analgesic effect.

The planning phase comes after the determination of a hypothesis. A clinical research plan is called a protocol . In a protocol, the reasons for research, number and qualities of participants, tests to be applied, study duration and what information to be gathered from the participants should be found and conformity criteria should be developed.

The selection of participant groups to be included in the study is important. Inclusion and exclusion criteria of the study for the participants should be determined. Inclusion criteria should be defined in the form of demographic characteristics (age, gender, etc.) of the participant group and the exclusion criteria as the diseases that may influence the study, age ranges, cases involving pregnancy and lactation, continuously used drugs and participants’ cooperation.

The next stage is methodology. Methodology can be grouped under subheadings, namely, the calculation of number of subjects, blinding (masking), randomisation, selection of operation to be applied, use of placebo and criteria for stopping and changing the treatment.

I. Calculation of the Number of Subjects

The entire source from which the data are obtained is called a universe or population . A small group selected from a certain universe based on certain rules and which is accepted to highly represent the universe from which it is selected is called a sample and the characteristics of the population from which the data are collected are called variables. If data is collected from the entire population, such an instance is called a parameter . Conducting a study on the sample rather than the entire population is easier and less costly. Many factors influence the determination of the sample size. Firstly, the type of variable should be determined. Variables are classified as categorical (qualitative, non-numerical) or numerical (quantitative). Individuals in categorical variables are classified according to their characteristics. Categorical variables are indicated as nominal and ordinal (ordered). In nominal variables, the application of a category depends on the researcher’s preference. For instance, a female participant can be considered first and then the male participant, or vice versa. An ordinal (ordered) variable is ordered from small to large or vice versa (e.g. ordering obese patients based on their weights-from the lightest to the heaviest or vice versa). A categorical variable may have more than one characteristic: such variables are called binary or dichotomous (e.g. a participant may be both female and obese).

If the variable has numerical (quantitative) characteristics and these characteristics cannot be categorised, then it is called a numerical variable. Numerical variables are either discrete or continuous. For example, the number of operations with spinal anaesthesia represents a discrete variable. The haemoglobin value or height represents a continuous variable.

Statistical analyses that need to be employed depend on the type of variable. The determination of variables is necessary for selecting the statistical method as well as software in SPSS. While categorical variables are presented as numbers and percentages, numerical variables are represented using measures such as mean and standard deviation. It may be necessary to use mean in categorising some cases such as the following: even though the variable is categorical (qualitative, non-numerical) when Visual Analogue Scale (VAS) is used (since a numerical value is obtained), it is classified as a numerical variable: such variables are averaged.

Clinical research is carried out on the sample and generalised to the population. Accordingly, the number of samples should be correctly determined. Different sample size formulas are used on the basis of the statistical method to be used. When the sample size increases, error probability decreases. The sample size is calculated based on the primary hypothesis. The determination of a sample size before beginning the research specifies the power of the study. Power analysis enables the acquisition of realistic results in the research, and it is used for comparing two or more clinical research methods.

Because of the difference in the formulas used in calculating power analysis and number of samples for clinical research, it facilitates the use of computer programs for making calculations.

It is necessary to know certain parameters in order to calculate the number of samples by power analysis.

  • Type-I (α) and type-II (β) error levels
  • Difference between groups (d-difference) and effect size (ES)
  • Distribution ratio of groups
  • Direction of research hypothesis (H1)

a. Type-I (α) and Type-II (β) Error (β) Levels

Two types of errors can be made while accepting or rejecting H 0 hypothesis in a hypothesis test. Type-I error (α) level is the probability of finding a difference at the end of the research when there is no difference between the two applications. In other words, it is the rejection of the hypothesis when H 0 is actually correct and it is known as α error or p value. For instance, when the size is determined, type-I error level is accepted as 0.05 or 0.01.

Another error that can be made during a hypothesis test is a type-II error. It is the acceptance of a wrongly hypothesised H 0 hypothesis. In fact, it is the probability of failing to find a difference when there is a difference between the two applications. The power of a test is the ability of that test to find a difference that actually exists. Therefore, it is related to the type-II error level.

Since the type-II error risk is expressed as β, the power of the test is defined as 1–β. When a type-II error is 0.20, the power of the test is 0.80. Type-I (α) and type-II (β) errors can be intentional. The reason to intentionally make such an error is the necessity to look at the events from the opposite perspective.

b. Difference between Groups and ES

ES is defined as the state in which statistical difference also has clinically significance: ES≥0.5 is desirable. The difference between groups is the absolute difference between the groups compared in clinical research.

c. Allocation Ratio of Groups

The allocation ratio of groups is effective in determining the number of samples. If the number of samples is desired to be determined at the lowest level, the rate should be kept as 1/1.

d. Direction of Hypothesis (H1)

The direction of hypothesis in clinical research may be one-sided or two-sided. While one-sided hypotheses hypothesis test differences in the direction of size, two-sided hypotheses hypothesis test differences without direction. The power of the test in two-sided hypotheses is lower than one-sided hypotheses.

After these four variables are determined, they are entered in the appropriate computer program and the number of samples is calculated. Statistical packaged software programs such as Statistica, NCSS and G-Power may be used for power analysis and calculating the number of samples. When the samples size is calculated, if there is a decrease in α, difference between groups, ES and number of samples, then the standard deviation increases and power decreases. The power in two-sided hypothesis is lower. It is ethically appropriate to consider the determination of sample size, particularly in animal experiments, at the beginning of the study. The phase of the study is also important in the determination of number of subjects to be included in drug studies. Usually, phase-I studies are used to determine the safety profile of a drug or product, and they are generally conducted on a few healthy volunteers. If no unacceptable toxicity is detected during phase-I studies, phase-II studies may be carried out. Phase-II studies are proof-of-concept studies conducted on a larger number (100–500) of volunteer patients. When the effectiveness of the drug or product is evident in phase-II studies, phase-III studies can be initiated. These are randomised, double-blinded, placebo or standard treatment-controlled studies. Volunteer patients are periodically followed-up with respect to the effectiveness and side effects of the drug. It can generally last 1–4 years and is valuable during licensing and releasing the drug to the general market. Then, phase-IV studies begin in which long-term safety is investigated (indication, dose, mode of application, safety, effectiveness, etc.) on thousands of volunteer patients.

II. Blinding (Masking) and Randomisation Methods

When the methodology of clinical research is prepared, precautions should be taken to prevent taking sides. For this reason, techniques such as randomisation and blinding (masking) are used. Comparative studies are the most ideal ones in clinical research.

Blinding Method

A case in which the treatments applied to participants of clinical research should be kept unknown is called the blinding method . If the participant does not know what it receives, it is called a single-blind study; if even the researcher does not know, it is called a double-blind study. When there is a probability of knowing which drug is given in the order of application, when uninformed staff administers the drug, it is called in-house blinding. In case the study drug is known in its pharmaceutical form, a double-dummy blinding test is conducted. Intravenous drug is given to one group and a placebo tablet is given to the comparison group; then, the placebo tablet is given to the group that received the intravenous drug and intravenous drug in addition to placebo tablet is given to the comparison group. In this manner, each group receives both the intravenous and tablet forms of the drug. In case a third party interested in the study is involved and it also does not know about the drug (along with the statistician), it is called third-party blinding.

Randomisation Method

The selection of patients for the study groups should be random. Randomisation methods are used for such selection, which prevent conscious or unconscious manipulations in the selection of patients ( 8 ).

No factor pertaining to the patient should provide preference of one treatment to the other during randomisation. This characteristic is the most important difference separating randomised clinical studies from prospective and synchronous studies with experimental groups. Randomisation strengthens the study design and enables the determination of reliable scientific knowledge ( 2 ).

The easiest method is simple randomisation, e.g. determination of the type of anaesthesia to be administered to a patient by tossing a coin. In this method, when the number of samples is kept high, a balanced distribution is created. When the number of samples is low, there will be an imbalance between the groups. In this case, stratification and blocking have to be added to randomisation. Stratification is the classification of patients one or more times according to prognostic features determined by the researcher and blocking is the selection of a certain number of patients for each stratification process. The number of stratification processes should be determined at the beginning of the study.

As the number of stratification processes increases, performing the study and balancing the groups become difficult. For this reason, stratification characteristics and limitations should be effectively determined at the beginning of the study. It is not mandatory for the stratifications to have equal intervals. Despite all the precautions, an imbalance might occur between the groups before beginning the research. In such circumstances, post-stratification or restandardisation may be conducted according to the prognostic factors.

The main characteristic of applying blinding (masking) and randomisation is the prevention of bias. Therefore, it is worthwhile to comprehensively examine bias at this stage.

Bias and Chicanery

While conducting clinical research, errors can be introduced voluntarily or involuntarily at a number of stages, such as design, population selection, calculating the number of samples, non-compliance with study protocol, data entry and selection of statistical method. Bias is taking sides of individuals in line with their own decisions, views and ideological preferences ( 9 ). In order for an error to lead to bias, it has to be a systematic error. Systematic errors in controlled studies generally cause the results of one group to move in a different direction as compared to the other. It has to be understood that scientific research is generally prone to errors. However, random errors (or, in other words, ‘the luck factor’-in which bias is unintended-do not lead to bias ( 10 ).

Another issue, which is different from bias, is chicanery. It is defined as voluntarily changing the interventions, results and data of patients in an unethical manner or copying data from other studies. Comparatively, bias may not be done consciously.

In case unexpected results or outliers are found while the study is analysed, if possible, such data should be re-included into the study since the complete exclusion of data from a study endangers its reliability. In such a case, evaluation needs to be made with and without outliers. It is insignificant if no difference is found. However, if there is a difference, the results with outliers are re-evaluated. If there is no error, then the outlier is included in the study (as the outlier may be a result). It should be noted that re-evaluation of data in anaesthesiology is not possible.

Statistical evaluation methods should be determined at the design stage so as not to encounter unexpected results in clinical research. The data should be evaluated before the end of the study and without entering into details in research that are time-consuming and involve several samples. This is called an interim analysis . The date of interim analysis should be determined at the beginning of the study. The purpose of making interim analysis is to prevent unnecessary cost and effort since it may be necessary to conclude the research after the interim analysis, e.g. studies in which there is no possibility to validate the hypothesis at the end or the occurrence of different side effects of the drug to be used. The accuracy of the hypothesis and number of samples are compared. Statistical significance levels in interim analysis are very important. If the data level is significant, the hypothesis is validated even if the result turns out to be insignificant after the date of the analysis.

Another important point to be considered is the necessity to conclude the participants’ treatment within the period specified in the study protocol. When the result of the study is achieved earlier and unexpected situations develop, the treatment is concluded earlier. Moreover, the participant may quit the study at its own behest, may die or unpredictable situations (e.g. pregnancy) may develop. The participant can also quit the study whenever it wants, even if the study has not ended ( 7 ).

In case the results of a study are contrary to already known or expected results, the expected quality level of the study suggesting the contradiction may be higher than the studies supporting what is known in that subject. This type of bias is called confirmation bias. The presence of well-known mechanisms and logical inference from them may create problems in the evaluation of data. This is called plausibility bias.

Another type of bias is expectation bias. If a result different from the known results has been achieved and it is against the editor’s will, it can be challenged. Bias may be introduced during the publication of studies, such as publishing only positive results, selection of study results in a way to support a view or prevention of their publication. Some editors may only publish research that extols only the positive results or results that they desire.

Bias may be introduced for advertisement or economic reasons. Economic pressure may be applied on the editor, particularly in the cases of studies involving drugs and new medical devices. This is called commercial bias.

In recent years, before beginning a study, it has been recommended to record it on the Web site www.clinicaltrials.gov for the purpose of facilitating systematic interpretation and analysis in scientific research, informing other researchers, preventing bias, provision of writing in a standard format, enhancing contribution of research results to the general literature and enabling early intervention of an institution for support. This Web site is a service of the US National Institutes of Health.

The last stage in the methodology of clinical studies is the selection of intervention to be conducted. Placebo use assumes an important place in interventions. In Latin, placebo means ‘I will be fine’. In medical literature, it refers to substances that are not curative, do not have active ingredients and have various pharmaceutical forms. Although placebos do not have active drug characteristic, they have shown effective analgesic characteristics, particularly in algology applications; further, its use prevents bias in comparative studies. If a placebo has a positive impact on a participant, it is called the placebo effect ; on the contrary, if it has a negative impact, it is called the nocebo effect . Another type of therapy that can be used in clinical research is sham application. Although a researcher does not cure the patient, the researcher may compare those who receive therapy and undergo sham. It has been seen that sham therapies also exhibit a placebo effect. In particular, sham therapies are used in acupuncture applications ( 11 ). While placebo is a substance, sham is a type of clinical application.

Ethically, the patient has to receive appropriate therapy. For this reason, if its use prevents effective treatment, it causes great problem with regard to patient health and legalities.

Before medical research is conducted with human subjects, predictable risks, drawbacks and benefits must be evaluated for individuals or groups participating in the study. Precautions must be taken for reducing the risk to a minimum level. The risks during the study should be followed, evaluated and recorded by the researcher ( 1 ).

After the methodology for a clinical study is determined, dealing with the ‘Ethics Committee’ forms the next stage. The purpose of the ethics committee is to protect the rights, safety and well-being of volunteers taking part in the clinical research, considering the scientific method and concerns of society. The ethics committee examines the studies presented in time, comprehensively and independently, with regard to ethics and science; in line with the Declaration of Helsinki and following national and international standards concerning ‘Good Clinical Practice’. The method to be followed in the formation of the ethics committee should be developed without any kind of prejudice and to examine the applications with regard to ethics and science within the framework of the ethics committee, Regulation on Clinical Trials and Good Clinical Practice ( www.iku.com ). The necessary documents to be presented to the ethics committee are research protocol, volunteer consent form, budget contract, Declaration of Helsinki, curriculum vitae of researchers, similar or explanatory literature samples, supporting institution approval certificate and patient follow-up form.

Only one sister/brother, mother, father, son/daughter and wife/husband can take charge in the same ethics committee. A rector, vice rector, dean, deputy dean, provincial healthcare director and chief physician cannot be members of the ethics committee.

Members of the ethics committee can work as researchers or coordinators in clinical research. However, during research meetings in which members of the ethics committee are researchers or coordinators, they must leave the session and they cannot sign-off on decisions. If the number of members in the ethics committee for a particular research is so high that it is impossible to take a decision, the clinical research is presented to another ethics committee in the same province. If there is no ethics committee in the same province, an ethics committee in the closest settlement is found.

Thereafter, researchers need to inform the participants using an informed consent form. This form should explain the content of clinical study, potential benefits of the study, alternatives and risks (if any). It should be easy, comprehensible, conforming to spelling rules and written in plain language understandable by the participant.

This form assists the participants in taking a decision regarding participation in the study. It should aim to protect the participants. The participant should be included in the study only after it signs the informed consent form; the participant can quit the study whenever required, even when the study has not ended ( 7 ).

Peer-review: Externally peer-reviewed.

Author Contributions: Concept - C.Ö.Ç., A.D.; Design - C.Ö.Ç.; Supervision - A.D.; Resource - C.Ö.Ç., A.D.; Materials - C.Ö.Ç., A.D.; Analysis and/or Interpretation - C.Ö.Ç., A.D.; Literature Search - C.Ö.Ç.; Writing Manuscript - C.Ö.Ç.; Critical Review - A.D.; Other - C.Ö.Ç., A.D.

Conflict of Interest: No conflict of interest was declared by the authors.

Financial Disclosure: The authors declared that this study has received no financial support.

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About Research Methods

This guide provides an overview of research methods, how to choose and use them, and supports and resources at UC Berkeley. 

As Patten and Newhart note in the book Understanding Research Methods , "Research methods are the building blocks of the scientific enterprise. They are the "how" for building systematic knowledge. The accumulation of knowledge through research is by its nature a collective endeavor. Each well-designed study provides evidence that may support, amend, refute, or deepen the understanding of existing knowledge...Decisions are important throughout the practice of research and are designed to help researchers collect evidence that includes the full spectrum of the phenomenon under study, to maintain logical rules, and to mitigate or account for possible sources of bias. In many ways, learning research methods is learning how to see and make these decisions."

The choice of methods varies by discipline, by the kind of phenomenon being studied and the data being used to study it, by the technology available, and more.  This guide is an introduction, but if you don't see what you need here, always contact your subject librarian, and/or take a look to see if there's a library research guide that will answer your question. 

Suggestions for changes and additions to this guide are welcome! 

START HERE: SAGE Research Methods

Without question, the most comprehensive resource available from the library is SAGE Research Methods.  HERE IS THE ONLINE GUIDE  to this one-stop shopping collection, and some helpful links are below:

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D-Lab Supports Berkeley faculty, staff, and graduate students with research in data intensive social science, including a wide range of training and workshop offerings Dryad Dryad is a simple self-service tool for researchers to use in publishing their datasets. It provides tools for the effective publication of and access to research data. Geospatial Innovation Facility (GIF) Provides leadership and training across a broad array of integrated mapping technologies on campu Research Data Management A UC Berkeley guide and consulting service for research data management issues

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Research Method

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Research Process – Steps, Examples and Tips

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Research Process

Research Process

Definition:

Research Process is a systematic and structured approach that involves the collection, analysis, and interpretation of data or information to answer a specific research question or solve a particular problem.

Research Process Steps

Research Process Steps are as follows:

Identify the Research Question or Problem

This is the first step in the research process. It involves identifying a problem or question that needs to be addressed. The research question should be specific, relevant, and focused on a particular area of interest.

Conduct a Literature Review

Once the research question has been identified, the next step is to conduct a literature review. This involves reviewing existing research and literature on the topic to identify any gaps in knowledge or areas where further research is needed. A literature review helps to provide a theoretical framework for the research and also ensures that the research is not duplicating previous work.

Formulate a Hypothesis or Research Objectives

Based on the research question and literature review, the researcher can formulate a hypothesis or research objectives. A hypothesis is a statement that can be tested to determine its validity, while research objectives are specific goals that the researcher aims to achieve through the research.

Design a Research Plan and Methodology

This step involves designing a research plan and methodology that will enable the researcher to collect and analyze data to test the hypothesis or achieve the research objectives. The research plan should include details on the sample size, data collection methods, and data analysis techniques that will be used.

Collect and Analyze Data

This step involves collecting and analyzing data according to the research plan and methodology. Data can be collected through various methods, including surveys, interviews, observations, or experiments. The data analysis process involves cleaning and organizing the data, applying statistical and analytical techniques to the data, and interpreting the results.

Interpret the Findings and Draw Conclusions

After analyzing the data, the researcher must interpret the findings and draw conclusions. This involves assessing the validity and reliability of the results and determining whether the hypothesis was supported or not. The researcher must also consider any limitations of the research and discuss the implications of the findings.

Communicate the Results

Finally, the researcher must communicate the results of the research through a research report, presentation, or publication. The research report should provide a detailed account of the research process, including the research question, literature review, research methodology, data analysis, findings, and conclusions. The report should also include recommendations for further research in the area.

Review and Revise

The research process is an iterative one, and it is important to review and revise the research plan and methodology as necessary. Researchers should assess the quality of their data and methods, reflect on their findings, and consider areas for improvement.

Ethical Considerations

Throughout the research process, ethical considerations must be taken into account. This includes ensuring that the research design protects the welfare of research participants, obtaining informed consent, maintaining confidentiality and privacy, and avoiding any potential harm to participants or their communities.

Dissemination and Application

The final step in the research process is to disseminate the findings and apply the research to real-world settings. Researchers can share their findings through academic publications, presentations at conferences, or media coverage. The research can be used to inform policy decisions, develop interventions, or improve practice in the relevant field.

Research Process Example

Following is a Research Process Example:

Research Question : What are the effects of a plant-based diet on athletic performance in high school athletes?

Step 1: Background Research Conduct a literature review to gain a better understanding of the existing research on the topic. Read academic articles and research studies related to plant-based diets, athletic performance, and high school athletes.

Step 2: Develop a Hypothesis Based on the literature review, develop a hypothesis that a plant-based diet positively affects athletic performance in high school athletes.

Step 3: Design the Study Design a study to test the hypothesis. Decide on the study population, sample size, and research methods. For this study, you could use a survey to collect data on dietary habits and athletic performance from a sample of high school athletes who follow a plant-based diet and a sample of high school athletes who do not follow a plant-based diet.

Step 4: Collect Data Distribute the survey to the selected sample and collect data on dietary habits and athletic performance.

Step 5: Analyze Data Use statistical analysis to compare the data from the two samples and determine if there is a significant difference in athletic performance between those who follow a plant-based diet and those who do not.

Step 6 : Interpret Results Interpret the results of the analysis in the context of the research question and hypothesis. Discuss any limitations or potential biases in the study design.

Step 7: Draw Conclusions Based on the results, draw conclusions about whether a plant-based diet has a significant effect on athletic performance in high school athletes. If the hypothesis is supported by the data, discuss potential implications and future research directions.

Step 8: Communicate Findings Communicate the findings of the study in a clear and concise manner. Use appropriate language, visuals, and formats to ensure that the findings are understood and valued.

Applications of Research Process

The research process has numerous applications across a wide range of fields and industries. Some examples of applications of the research process include:

  • Scientific research: The research process is widely used in scientific research to investigate phenomena in the natural world and develop new theories or technologies. This includes fields such as biology, chemistry, physics, and environmental science.
  • Social sciences : The research process is commonly used in social sciences to study human behavior, social structures, and institutions. This includes fields such as sociology, psychology, anthropology, and economics.
  • Education: The research process is used in education to study learning processes, curriculum design, and teaching methodologies. This includes research on student achievement, teacher effectiveness, and educational policy.
  • Healthcare: The research process is used in healthcare to investigate medical conditions, develop new treatments, and evaluate healthcare interventions. This includes fields such as medicine, nursing, and public health.
  • Business and industry : The research process is used in business and industry to study consumer behavior, market trends, and develop new products or services. This includes market research, product development, and customer satisfaction research.
  • Government and policy : The research process is used in government and policy to evaluate the effectiveness of policies and programs, and to inform policy decisions. This includes research on social welfare, crime prevention, and environmental policy.

Purpose of Research Process

The purpose of the research process is to systematically and scientifically investigate a problem or question in order to generate new knowledge or solve a problem. The research process enables researchers to:

  • Identify gaps in existing knowledge: By conducting a thorough literature review, researchers can identify gaps in existing knowledge and develop research questions that address these gaps.
  • Collect and analyze data : The research process provides a structured approach to collecting and analyzing data. Researchers can use a variety of research methods, including surveys, experiments, and interviews, to collect data that is valid and reliable.
  • Test hypotheses : The research process allows researchers to test hypotheses and make evidence-based conclusions. Through the systematic analysis of data, researchers can draw conclusions about the relationships between variables and develop new theories or models.
  • Solve problems: The research process can be used to solve practical problems and improve real-world outcomes. For example, researchers can develop interventions to address health or social problems, evaluate the effectiveness of policies or programs, and improve organizational processes.
  • Generate new knowledge : The research process is a key way to generate new knowledge and advance understanding in a given field. By conducting rigorous and well-designed research, researchers can make significant contributions to their field and help to shape future research.

Tips for Research Process

Here are some tips for the research process:

  • Start with a clear research question : A well-defined research question is the foundation of a successful research project. It should be specific, relevant, and achievable within the given time frame and resources.
  • Conduct a thorough literature review: A comprehensive literature review will help you to identify gaps in existing knowledge, build on previous research, and avoid duplication. It will also provide a theoretical framework for your research.
  • Choose appropriate research methods: Select research methods that are appropriate for your research question, objectives, and sample size. Ensure that your methods are valid, reliable, and ethical.
  • Be organized and systematic: Keep detailed notes throughout the research process, including your research plan, methodology, data collection, and analysis. This will help you to stay organized and ensure that you don’t miss any important details.
  • Analyze data rigorously: Use appropriate statistical and analytical techniques to analyze your data. Ensure that your analysis is valid, reliable, and transparent.
  • I nterpret results carefully : Interpret your results in the context of your research question and objectives. Consider any limitations or potential biases in your research design, and be cautious in drawing conclusions.
  • Communicate effectively: Communicate your research findings clearly and effectively to your target audience. Use appropriate language, visuals, and formats to ensure that your findings are understood and valued.
  • Collaborate and seek feedback : Collaborate with other researchers, experts, or stakeholders in your field. Seek feedback on your research design, methods, and findings to ensure that they are relevant, meaningful, and impactful.

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Research: Meaning and Purpose

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  • Kazi Abusaleh 4 &
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The objective of the chapter is to provide the conceptual framework of the research and research process and draw the importance of research in social sciences. Various books and research papers were reviewed to write the chapter. The chapter defines ‘research’ as a deliberate and systematic scientific investigation into a phenomenon to explore, analyse, and predict about the issues or circumstances, and characterizes ‘research’ as a systematic and scientific mode of inquiry, a way to testify the existing knowledge and theories, and a well-designed process to answer questions in a reliable and unbiased way. This chapter, however, categorizes research into eight types under four headings, explains six steps to carry out a research work scientifically, and finally sketches the importance of research in social sciences.

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  • October 2, 2020

Types of Research Design

Types of Research

Research is about using established methods to investigate a problem or question in detail with the aim of generating new knowledge about it.

It is a vital tool for scientific advancement because it allows researchers to prove or refute hypotheses based on clearly defined parameters, environments and assumptions. Due to this, it enables us to confidently contribute to knowledge as it allows research to be verified and replicated.

Knowing the types of research and what each of them focuses on will allow you to better plan your project, utilises the most appropriate methodologies and techniques and better communicate your findings to other researchers and supervisors.

Classification of Types of Research

There are various types of research that are classified according to their objective, depth of study, analysed data, time required to study the phenomenon and other factors. It’s important to note that a research project will not be limited to one type of research, but will likely use several.

According to its Purpose

Theoretical research.

Theoretical research, also referred to as pure or basic research, focuses on generating knowledge , regardless of its practical application. Here, data collection is used to generate new general concepts for a better understanding of a particular field or to answer a theoretical research question.

Results of this kind are usually oriented towards the formulation of theories and are usually based on documentary analysis, the development of mathematical formulas and the reflection of high-level researchers.

Applied Research

Here, the goal is to find strategies that can be used to address a specific research problem. Applied research draws on theory to generate practical scientific knowledge, and its use is very common in STEM fields such as engineering, computer science and medicine.

This type of research is subdivided into two types:

  • Technological applied research : looks towards improving efficiency in a particular productive sector through the improvement of processes or machinery related to said productive processes.
  • Scientific applied research : has predictive purposes. Through this type of research design, we can measure certain variables to predict behaviours useful to the goods and services sector, such as consumption patterns and viability of commercial projects.

Methodology Research

According to your Depth of Scope

Exploratory research.

Exploratory research is used for the preliminary investigation of a subject that is not yet well understood or sufficiently researched. It serves to establish a frame of reference and a hypothesis from which an in-depth study can be developed that will enable conclusive results to be generated.

Because exploratory research is based on the study of little-studied phenomena, it relies less on theory and more on the collection of data to identify patterns that explain these phenomena.

Descriptive Research

The primary objective of descriptive research is to define the characteristics of a particular phenomenon without necessarily investigating the causes that produce it.

In this type of research, the researcher must take particular care not to intervene in the observed object or phenomenon, as its behaviour may change if an external factor is involved.

Explanatory Research

Explanatory research is the most common type of research method and is responsible for establishing cause-and-effect relationships that allow generalisations to be extended to similar realities. It is closely related to descriptive research, although it provides additional information about the observed object and its interactions with the environment.

Correlational Research

The purpose of this type of scientific research is to identify the relationship between two or more variables. A correlational study aims to determine whether a variable changes, how much the other elements of the observed system change.

According to the Type of Data Used

Qualitative research.

Qualitative methods are often used in the social sciences to collect, compare and interpret information, has a linguistic-semiotic basis and is used in techniques such as discourse analysis, interviews, surveys, records and participant observations.

In order to use statistical methods to validate their results, the observations collected must be evaluated numerically. Qualitative research, however, tends to be subjective, since not all data can be fully controlled. Therefore, this type of research design is better suited to extracting meaning from an event or phenomenon (the ‘why’) than its cause (the ‘how’).

Quantitative Research

Quantitative research study delves into a phenomena through quantitative data collection and using mathematical, statistical and computer-aided tools to measure them . This allows generalised conclusions to be projected over time.

Types of Research Methodology

According to the Degree of Manipulation of Variables

Experimental research.

It is about designing or replicating a phenomenon whose variables are manipulated under strictly controlled conditions in order to identify or discover its effect on another independent variable or object. The phenomenon to be studied is measured through study and control groups, and according to the guidelines of the scientific method.

Non-Experimental Research

Also known as an observational study, it focuses on the analysis of a phenomenon in its natural context. As such, the researcher does not intervene directly, but limits their involvement to measuring the variables required for the study. Due to its observational nature, it is often used in descriptive research.

Quasi-Experimental Research

It controls only some variables of the phenomenon under investigation and is therefore not entirely experimental. In this case, the study and the focus group cannot be randomly selected, but are chosen from existing groups or populations . This is to ensure the collected data is relevant and that the knowledge, perspectives and opinions of the population can be incorporated into the study.

According to the Type of Inference

Deductive investigation.

In this type of research, reality is explained by general laws that point to certain conclusions; conclusions are expected to be part of the premise of the research problem and considered correct if the premise is valid and the inductive method is applied correctly.

Inductive Research

In this type of research, knowledge is generated from an observation to achieve a generalisation. It is based on the collection of specific data to develop new theories.

Hypothetical-Deductive Investigation

It is based on observing reality to make a hypothesis, then use deduction to obtain a conclusion and finally verify or reject it through experience.

Descriptive Research Design

According to the Time in Which it is Carried Out

Longitudinal study (also referred to as diachronic research).

It is the monitoring of the same event, individual or group over a defined period of time. It aims to track changes in a number of variables and see how they evolve over time. It is often used in medical, psychological and social areas .

Cross-Sectional Study (also referred to as Synchronous Research)

Cross-sectional research design is used to observe phenomena, an individual or a group of research subjects at a given time.

According to The Sources of Information

Primary research.

This fundamental research type is defined by the fact that the data is collected directly from the source, that is, it consists of primary, first-hand information.

Secondary research

Unlike primary research, secondary research is developed with information from secondary sources, which are generally based on scientific literature and other documents compiled by another researcher.

Action Research Methods

According to How the Data is Obtained

Documentary (cabinet).

Documentary research, or secondary sources, is based on a systematic review of existing sources of information on a particular subject. This type of scientific research is commonly used when undertaking literature reviews or producing a case study.

Field research study involves the direct collection of information at the location where the observed phenomenon occurs.

From Laboratory

Laboratory research is carried out in a controlled environment in order to isolate a dependent variable and establish its relationship with other variables through scientific methods.

Mixed-Method: Documentary, Field and/or Laboratory

Mixed research methodologies combine results from both secondary (documentary) sources and primary sources through field or laboratory research.

What is Scientific Misconduct?

Scientific misconduct can be described as a deviation from the accepted standards of scientific research, study and publication ethics.

What are the consequences of Self-Plagiarism?

Self-plagiarism is when you try and pass off work that you’ve previously done as something that is completely new.

Purpose of Research - What is Research

The purpose of research is to enhance society by advancing knowledge through developing scientific theories, concepts and ideas – find out more on what this involves.

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The role of research at universities: why it matters.

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(Photo by William B. Plowman/Getty Images)

Teaching and learning, research and discovery, synthesis and creativity, understanding and engagement, service and outreach. There are many “core elements” to the mission of a great university. Teaching would seem the most obvious, but for those outside of the university, “research” (taken to include scientific research, scholarship more broadly, as well as creative activity) may be the least well understood. This creates misunderstanding of how universities invest resources, especially those deriving from undergraduate tuition and state (or other public) support, and the misperception that those resources are being diverted away from what is believed should be the core (and sole) focus, teaching. This has led to a loss of trust, confidence, and willingness to continue to invest or otherwise support (especially our public) universities.

Why are universities engaged in the conduct of research? Who pays? Who benefits? And why does it all matter? Good questions. Let’s get to some straightforward answers. Because the academic research enterprise really is not that difficult to explain, and its impacts are profound.

So let’s demystify university-based research. And in doing so, hopefully we can begin building both better understanding and a better relationship between the public and higher education, both of which are essential to the future of US higher education.   

Why are universities engaged in the conduct of research?

Universities engage in research as part of their missions around learning and discovery. This, in turn, contributes directly and indirectly to their primary mission of teaching. Universities and many colleges (the exception being those dedicated exclusively to undergraduate teaching) have as part of their mission the pursuit of scholarship. This can come in the form of fundamental or applied research (both are most common in the STEM fields, broadly defined), research-based scholarship or what often is called “scholarly activity” (most common in the social sciences and humanities), or creative activity (most common in the arts). Increasingly, these simple categorizations are being blurred, for all good reasons and to the good of the discovery of new knowledge and greater understanding of complex (transdisciplinary) challenges and the creation of increasingly interrelated fields needed to address them.

It goes without saying that the advancement of knowledge (discovery, innovation, creation) is essential to any civilization. Our nation’s research universities represent some of the most concentrated communities of scholars, facilities, and collective expertise engaged in these activities. But more importantly, this is where higher education is delivered, where students develop breadth and depth of knowledge in foundational and advanced subjects, where the skills for knowledge acquisition and understanding (including contextualization, interpretation, and inference) are honed, and where students are educated, trained, and otherwise prepared for successful careers. Part of that training and preparation derives from exposure to faculty who are engaged at the leading-edge of their fields, through their research and scholarly work. The best faculty, the teacher-scholars, seamlessly weave their teaching and research efforts together, to their mutual benefit, and in a way that excites and engages their students. In this way, the next generation of scholars (academic or otherwise) is trained, research and discovery continue to advance inter-generationally, and the cycle is perpetuated.

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University research can be expensive, particularly in laboratory-intensive fields. But the responsibility for much (indeed most) of the cost of conducting research falls to the faculty member. Faculty who are engaged in research write grants for funding (e.g., from federal and state agencies, foundations, and private companies) to support their work and the work of their students and staff. In some cases, the universities do need to invest heavily in equipment, facilities, and personnel to support select research activities. But they do so judiciously, with an eye toward both their mission, their strategic priorities, and their available resources.

Medical research, and medical education more broadly, is expensive and often requires substantial institutional investment beyond what can be covered by clinical operations or externally funded research. But universities with medical schools/medical centers have determined that the value to their educational and training missions as well as to their communities justifies the investment. And most would agree that university-based medical centers are of significant value to their communities, often providing best-in-class treatment and care in midsize and smaller communities at a level more often seen in larger metropolitan areas.

Research in the STEM fields (broadly defined) can also be expensive. Scientific (including medical) and engineering research often involves specialized facilities or pieces of equipment, advanced computing capabilities, materials requiring controlled handling and storage, and so forth. But much of this work is funded, in large part, by federal agencies such as the National Science Foundation, National Institutes of Health, US Department of Energy, US Department of Agriculture, and many others.

Research in the social sciences is often (not always) less expensive, requiring smaller amount of grant funding. As mentioned previously, however, it is now becoming common to have physical, natural, and social scientist teams pursuing large grant funding. This is an exciting and very promising trend for many reasons, not the least of which is the nature of the complex problems being studied.

Research in the arts and humanities typically requires the least amount of funding as it rarely requires the expensive items listed previously. Funding from such organizations as the National Endowment for the Arts, National Endowment for the Humanities, and private foundations may be able to support significant scholarship and creation of new knowledge or works through much more modest grants than would be required in the natural or physical sciences, for example.

Philanthropy may also be directed toward the support of research and scholarly activity at universities. Support from individual donors, family foundations, private or corporate foundations may be directed to support students, faculty, labs or other facilities, research programs, galleries, centers, and institutes.

Who benefits?

Students, both undergraduate and graduate, benefit from studying in an environment rich with research and discovery. Besides what the faculty can bring back to the classroom, there are opportunities to engage with faculty as part of their research teams and even conduct independent research under their supervision, often for credit. There are opportunities to learn about and learn on state-of-the-art equipment, in state-of-the-art laboratories, and from those working on the leading edge in a discipline. There are opportunities to co-author, present at conferences, make important connections, and explore post-graduate pathways.

The broader university benefits from active research programs. Research on timely and important topics attracts attention, which in turn leads to greater institutional visibility and reputation. As a university becomes known for its research in certain fields, they become magnets for students, faculty, grants, media coverage, and even philanthropy. Strength in research helps to define a university’s “brand” in the national and international marketplace, impacting everything from student recruitment, to faculty retention, to attracting new investments.

The community, region, and state benefits from the research activity of the university. This is especially true for public research universities. Research also contributes directly to economic development, clinical, commercial, and business opportunities. Resources brought into the university through grants and contracts support faculty, staff, and student salaries, often adding additional jobs, contributing directly to the tax base. Research universities, through their expertise, reputation, and facilities, can attract new businesses into their communities or states. They can also launch and incubate startup companies, or license and sell their technologies to other companies. Research universities often host meeting and conferences which creates revenue for local hotels, restaurants, event centers, and more. And as mentioned previously, university medical centers provide high-quality medical care, often in midsize communities that wouldn’t otherwise have such outstanding services and state-of-the-art facilities.

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And finally, why does this all matter?

Research is essential to advancing society, strengthening the economy, driving innovation, and addressing the vexing and challenging problems we face as a people, place, and planet. It’s through research, scholarship, and discovery that we learn about our history and ourselves, understand the present context in which we live, and plan for and secure our future.

Research universities are vibrant, exciting, and inspiring places to learn and to work. They offer opportunities for students that few other institutions can match – whether small liberal arts colleges, mid-size teaching universities, or community colleges – and while not right for every learner or every educator, they are right for many, if not most. The advantages simply cannot be ignored. Neither can the importance or the need for these institutions. They need not be for everyone, and everyone need not find their way to study or work at our research universities, and we stipulate that there are many outstanding options to meet and support different learning styles and provide different environments for teaching and learning. But it’s critically important that we continue to support, protect, and respect research universities for all they do for their students, their communities and states, our standing in the global scientific community, our economy, and our nation.

David Rosowsky

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Research: People Still Want to Work. They Just Want Control Over Their Time.

  • Stephanie Tepper
  • Neil Lewis, Jr.

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It’s a strong predictor for how satisfied they are with their work — and their lives.

To better understand the role that control over one’s time plays in job and life satisfaction, the authors analyzed survey data from a nationally representative sample. They found: 1) People who had greater control over their time had the highest job satisfaction and overall satisfaction with their lives, 2) Those who felt a sense of time scarcity had less satisfaction with their jobs and were less satisfied with their lives, 3) The number of hours people worked was not related to how satisfied people were with their jobs, and 4) For those who had more control over their time, feeling time scarcity did not undermine their job satisfaction as much as it did for those who had less control over their time. Employers should therefore create and tailor flexible work policies to meet diverse employee needs, fostering satisfaction and retention.

Workers — particularly those considered “ knowledge workers ” who are able to do most if not all of their work with a laptop and an internet connection — have been fighting for the right to maintain control over their time for years. While working from home in 2020 and 2021, they demonstrated to their bosses that they are able to maintain, or in some cases even increase , their productivity while working flexibly. Their bosses, on the other hand, have been pulling them in the opposite direction; executives and managers have been fighting to get workers back into the offices that companies are paying a lot of money to lease. This struggle has affected workers and companies alike. Workers quit en masse during a period that became known as “ the Great Resignation ,” and employers who instituted return-to-office mandates have struggled to hire and retain top talent . Now, especially with Gen Z making up an increasing share of the working population and the conversations around hybrid work and returning to the office stagnating, demands for increased flexibility in work arrangements are still top of mind for many employees and job seekers.

  • ST Stephanie Tepper is a behavioral scientist who studies behavioral and policy interventions to reduce economic inequality and promote economic opportunity. She is an Associate Fellow at the U.S. Office of Evaluation Sciences and a Postdoctoral Scholar at Jeb E. Brooks School of Public Policy at Cornell University.
  • NL Dr. Neil Lewis Jr is a behavioral scientist who studies the motivational, behavioral, and equity implications of social interventions and policies. He is a Nancy and Peter Meinig Family Investigator in the Life Sciences at Cornell University and Weill Cornell Medicine, where he is also associate professor of communication, medicine, and public policy.

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Reporting by Anna Tong in San Francisco and Katie Paul in New York; editing by Ken Li and Claudia Parsons

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Thomson Reuters

Anna Tong is a correspondent for Reuters based in San Francisco, where she reports on the technology industry. She joined Reuters in 2023 after working at the San Francisco Standard as a data editor. Tong previously worked at technology startups as a product manager and at Google where she worked in user insights and helped run a call center. Tong graduated from Harvard University.

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Brandon Marc Finn

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Brandon Marc Finn is an assistant research scientist in the Urban Sustainability Research Group and is a core faculty member of the Center for Sustainable Systems. His interdisciplinary research focuses on urbanization, informality, and mining, and his current work investigates the unintended consequences of decarbonization. In the Democratic Republic of Congo, Brandon is researching the interplays between artisanal and industrial mining practices in the 'first-mile' of the global cobalt and copper supply chain. In Ghana, he is assessing how informality defines the 'last-mile' of global electronic waste supply chains. Brandon’s other work is concerned with urban informality in relation to climate change mitigation and just transitions, where he argues that informality lies at the heart of sustainable development.

Publications

Finn, B.M., 2024. Informality at the heart of sustainable development. Dialogues in Human Geography, p.20438206241240216.

Finn, B.M. and Bandauko, E., 2024. Dwindling funds and increased responsibilities: Decentralization, unfunded mandates, and Harare's infrastructure crisis. Habitat International, 148, p.103087.

Finn, B.M. and Cobbinah, P.B., 2023. African urbanisation at the confluence of informality and climate change. Urban Studies, 60(3), pp.405-424.

Finn, B.M., 2023. The structure of informality: The Zambian copperbelt and the informal/formal dialectic. Dialogues in Human Geography, p.20438206231168883.

Current research projects include:

1. Copper and cobalt mining in the Democratic Republic of Congo

2. Mixed-methods research on industrial and artisanal mining supply chains

3. Electronic waste and urbanization in Accra, Ghana

PhD Urban Planning, Harvard University

MSc Urban Studies, University College London

BSocSci Environmental and Geographical Sciences, University of Cape Town

Veronika Lubeck (MS ’24): Meet the future of Geospatial Data Sciences

In 2021, Veronika Lubeck (MS ’24) graduated from Santa Clara University with an environmental science degree. With an interest in data and statistical analysis, Lubeck...

Preventive antibiotics may help curb the STI epidemic, experts say

A pharmacist holds a bottle of the antibiotic doxycycline hyclate in Sacramento, Calif.

Instead of simply treating sexually transmitted infections with antibiotics, a new public-health movement seeks to use one such medication to prevent STIs in the first place. Promising research into variations on this method has raised hopes, but also concerns about whether this method might also contribute to another public health crisis: drug-resistant infections. 

One thing is clear: The nation is in dire need of game changers to battle the STI epidemic, as gonorrhea, chlamydia and syphilis have largely soared during the past decade.

Syphilis, which public health experts thought as recently as the 1990s could possibly be eliminated, has seen especially worrying increases among pregnant women in particular. Congenital syphilis — when a mother passes the infection to her baby — can be fatal or lead to severe birth defects.

Enter doxycycline: a common, well-tolerated antibiotic long used for multiple purposes, including treating acne.

Last month, the Centers for Disease Control and Prevention issued guidelines for the use of doxycycline after sex — as post-exposure prophylaxis, or doxyPEP — to lower the risk of bacterial STIs among gay and bisexual men and transgender women. The recommendation was limited to this population because a recent clinical trial of doxyPEP among cisgender women failed to demonstrate any benefit. Men who have sex with men also have a disproportionately high STI rate.

The CDC endorsement followed three randomized controlled trials finding that providing doxycycline to gay and bisexual men and trans women and instructing them to take one 200-milligram dose within 72 of sex lowered their risk of chlamydia and syphilis by more than 70% and gonorrhea by about 50%. Further research of the gay community’s use of doxyPEP in San Francisco has been similarly promising. 

“It’s too early to know whether doxyPEP will reverse years of increasing STIs,” said Dr. Jonathan Mermin, the CDC’s STI-prevention director. “However, there is considerable enthusiasm in the community and by many providers.”

Now, two new studies have helped expand the conversation about doxycycline, to ask whether taking just 100 mg of the antibiotic daily — as pre-exposure prophylaxis, or doxy PrEP — might afford a more optimal balance of risks versus benefits for some people.

Findings from these studies , conducted among HIV-positive gay and bisexual men in Toronto and Vancouver, British Columbia, and in female sex workers in Tokyo, will be presented at the 25th International HIV Conference in Munich, Germany, which runs July 22-26. 

“I have had some patients prefer the once-a-day, adding the pill to their daily medication routine and not worrying about when or how to take it after sex,” Dr. Jeffrey Klausner, a professor of infectious disease at the University of Southern California, said of the doxyPrEP protocol. “Other patients prefer the single dose after sex — simple and easy.”

Klausner was not involved in the new studies, but he was the lead author of the first-ever doxyPrEP study , of a small group of gay and bisexual men in Los Angeles. Published in 2015, it found that those in the doxyPrEP group were less likely to be diagnosed with STIs than those provided financial incentives to remain STI free.

The main concern about prescribing doxycycline for prevention is that it might drive the emergence of drug-resistant infections, like staph. Gonorrhea is the only of the three STIs with documented acquisition of  such resistance. But while doxycycline is proven effective at preventing gonorrhea, it isn’t generally used to treat that infection.

On the flip side, by reducing STI rates, doxycycline can lessen the need for other antibiotics to treat such infections — thus lowering the potential that those drugs can drive drug resistance.

The new double-blind Canadian study of doxyPrEP enrolled 52 gay and bisexual men and evenly randomized them to receive doxycycline or a placebo. After one year, the doxyPrEP group had a 68% to 92% lower diagnosis rate of each of the three STIs — a comparable result to the recent doxyPEP study.

There was essentially no difference in drug-resistance among staph infections between the two groups, albeit from a very small number of samples. 

In the Japanese study, 40 women in the commercial sex trade saw their STI infection rate decline by two thirds, from about 225 diagnoses per 100 cumulative years of follow-up before receiving doxyPrEP to a rate of about 80 diagnoses afterward. Once the women were prescribed daily doxycycline, syphilis vanished among them. Chlamydia declined by about two thirds, but this shift was only marginally statistically significant. There was no significant change in gonorrhea.

The study authors found no change in signs of drug resistance in two infections: bacterial vaginosis and Candida vaginitis.

Nearly three quarters of the women reported reduced anxiety about contracting STIs.

“It is important to emphasize that these are both small studies,” Dr. Christoph Spinner, local co-chair for the forthcoming HIV conference and chief medical information officer at University Hospital rechts der Isar in Munich, said at a recent press briefing. “Also, the one from Canada is a pilot study, and the one from Japan had no control group.”

A more enthusiastic Klausner reflected on the results of the study of gay men and said that they “are compelling and support the idea that people should have choice” in their STI prevention tools. “Current guidelines might need to be further updated.”

Dr. Troy Grennan, the physician lead for the provincial HIV/STI program at the BC Centre for Disease Control in Vancouver and the lead author of the study in gay men, said his findings support the nationwide trial in Canada that his research team launched a year ago comparing doxyPEP with doxyPrEP. The study has enrolled about 150 of a planned 560 participants. 

“The generic blanket statement of saying that doxyPEP is better because it’s less drug — we can’t assume that is the bottom line,” he said.

For one thing, some people may have sexual partners frequently enough that it makes more sense to take doxycycline daily as PrEP — both because at half the dose of doxyPEP, doxyPrEP actually adds up to less overall use for them. Also, consistent rather than intermittent exposure to antibiotics may lower the risk of the emergence of drug resistance in pathogens.

And for some people, especially those who already take daily medications, such as pills to treat or prevent HIV, it’s easier to remember to take a daily pill than to schedule doses based on the timing of recent sexual encounters.

As for the worry of promoting drug resistance, “The trend hasn’t really been convincing one way or another,” Grennan said. Research seeking to address this question is ongoing. 

Like Klausner, Grennan touted the benefits of choice in STI prevention tools among those at risk.

“One size does not fit all,” he said.

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Benjamin Ryan is independent journalist specializing in science and LGBTQ coverage. He contributes to NBC News, The New York Times, The Guardian and Thomson Reuters Foundation and has also written for The Washington Post, The Nation, The Atlantic and New York.

Frequently asked questions

What is a research project.

A research project is an academic, scientific, or professional undertaking to answer a research question . Research projects can take many forms, such as qualitative or quantitative , descriptive , longitudinal , experimental , or correlational . What kind of research approach you choose will depend on your topic.

Frequently asked questions: Writing a research paper

The best way to remember the difference between a research plan and a research proposal is that they have fundamentally different audiences. A research plan helps you, the researcher, organize your thoughts. On the other hand, a dissertation proposal or research proposal aims to convince others (e.g., a supervisor, a funding body, or a dissertation committee) that your research topic is relevant and worthy of being conducted.

Formulating a main research question can be a difficult task. Overall, your question should contribute to solving the problem that you have defined in your problem statement .

However, it should also fulfill criteria in three main areas:

  • Researchability
  • Feasibility and specificity
  • Relevance and originality

Research questions anchor your whole project, so it’s important to spend some time refining them.

In general, they should be:

  • Focused and researchable
  • Answerable using credible sources
  • Complex and arguable
  • Feasible and specific
  • Relevant and original

All research questions should be:

  • Focused on a single problem or issue
  • Researchable using primary and/or secondary sources
  • Feasible to answer within the timeframe and practical constraints
  • Specific enough to answer thoroughly
  • Complex enough to develop the answer over the space of a paper or thesis
  • Relevant to your field of study and/or society more broadly

Writing Strong Research Questions

A research aim is a broad statement indicating the general purpose of your research project. It should appear in your introduction at the end of your problem statement , before your research objectives.

Research objectives are more specific than your research aim. They indicate the specific ways you’ll address the overarching aim.

Once you’ve decided on your research objectives , you need to explain them in your paper, at the end of your problem statement .

Keep your research objectives clear and concise, and use appropriate verbs to accurately convey the work that you will carry out for each one.

I will compare …

Your research objectives indicate how you’ll try to address your research problem and should be specific:

Research objectives describe what you intend your research project to accomplish.

They summarize the approach and purpose of the project and help to focus your research.

Your objectives should appear in the introduction of your research paper , at the end of your problem statement .

The main guidelines for formatting a paper in Chicago style are to:

  • Use a standard font like 12 pt Times New Roman
  • Use 1 inch margins or larger
  • Apply double line spacing
  • Indent every new paragraph ½ inch
  • Include a title page
  • Place page numbers in the top right or bottom center
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  • Published: 08 July 2024

Pathogenicity and transmissibility of bovine H5N1 influenza virus

  • Amie J. Eisfeld 1   na1 ,
  • Asim Biswas 1   na1 ,
  • Lizheng Guan 1   na1 ,
  • Chunyang Gu 1   na1 ,
  • Tadashi Maemura 1   na1 ,
  • Sanja Trifkovic 1 ,
  • Tong Wang 1 ,
  • Lavanya Babujee 1 ,
  • Randall Dahn 1 ,
  • Peter J. Halfmann   ORCID: orcid.org/0000-0002-1648-1625 1 ,
  • Tera Barnhardt 2 ,
  • Gabriele Neumann 1 ,
  • Yasuo Suzuki 3 ,
  • Alexis Thompson   ORCID: orcid.org/0000-0003-4405-5313 4 ,
  • Amy K. Swinford 5 ,
  • Kiril M. Dimitrov   ORCID: orcid.org/0000-0002-5525-4492 5 ,
  • Keith Poulsen 6 &
  • Yoshihiro Kawaoka   ORCID: orcid.org/0000-0001-5061-8296 1 , 7 , 8 , 9  

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  • Influenza virus
  • Viral pathogenesis
  • Viral transmission

Highly pathogenic H5N1 avian influenza (HPAI H5N1) viruses occasionally infect, but typically do not transmit, in mammals. In the Spring of 2024, an unprecedented outbreak of HPAI H5N1 in bovine herds occurred in the US, with virus spread within and between herds, infections in poultry and cats, and spillover into humans, collectively indicating an increased public health risk 1-4 . Here, we characterized an HPAI H5N1 virus isolated from infected cow milk in mice and ferrets. Like other HPAI H5N1 viruses, the bovine H5N1 virus spread systemically, including to the mammary glands of both species; however, this tropism was also observed for an older HPAI H5N1 virus isolate. Importantly, bovine HPAI H5N1 virus bound to sialic acids expressed in human upper airways and inefficiently transmitted to exposed ferrets (one of four exposed ferrets seroconverted without virus detection). Bovine HPAI H5N1 virus thus possesses features that may facilitate infection and transmission in mammals.

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These authors contributed equally: Amie J. Eisfeld, Asim Biswas, Lizheng Guan, Chunyang Gu, Tadashi Maemura

Authors and Affiliations

Influenza Research Institute, Dept. of Pathobiological Sciences, University of Wisconsin-Madison, Madison, WI, USA

Amie J. Eisfeld, Asim Biswas, Lizheng Guan, Chunyang Gu, Tadashi Maemura, Sanja Trifkovic, Tong Wang, Lavanya Babujee, Randall Dahn, Peter J. Halfmann, Gabriele Neumann & Yoshihiro Kawaoka

Heritage Vet Partners, Johnson, KS, USA

Tera Barnhardt

Department of Biochemistry, School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan

Yasuo Suzuki

Texas A&M Veterinary Medical Diagnostic Laboratory, Canyon, TX, USA

Alexis Thompson

Texas A&M Veterinary Medical Diagnostic Laboratory, College Station, TX, USA

Amy K. Swinford & Kiril M. Dimitrov

Wisconsin Veterinary Diagnostic Laboratory, University of Wisconsin-Madison, Madison, WI, USA

Keith Poulsen

Department of Virology, Institute of Medical Science, University of Tokyo, Tokyo, Japan

Yoshihiro Kawaoka

The University of Tokyo Pandemic Preparedness, Infection and Advanced research center (UTOPIA), University of Tokyo, Tokyo, Japan

The Research Center for Global Viral Diseases, National Center for Global Health and Medicine Research Institute, Tokyo, Japan

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Correspondence to Yoshihiro Kawaoka .

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Eisfeld, A.J., Biswas, A., Guan, L. et al. Pathogenicity and transmissibility of bovine H5N1 influenza virus. Nature (2024). https://doi.org/10.1038/s41586-024-07766-6

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DOI : https://doi.org/10.1038/s41586-024-07766-6

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ChatGPT: Disruptive or Constructive?

Thursday, Jul 18, 2024 • Jeremiah Valentine : [email protected]

What is Chat GPT?

ChatGPT is a popular emerging technology using Artificial Intelligence. GPT stands for Generative Pre-trained Transformer, which describes an AI program that looks for patterns in language and data learning to predict the next word in a sentence or the next paragraph in an essay. The website has a friendly interface that allows users to interact with AI in a n efficient conversational tone . ChatGPT provides another opportunity for students, instructors, researchers, workers, and others to find practical solutions to everyday and complicated problems.

At the root of this conversation is Artificial Intelligence. I plan to explore applicable uses of AI and ChatGPT in the classroom , entrepreneurial potential uses, and applications in industry .

A person types on a laptop.

   

Everyday Uses of Artificial Intelligence

The use of Artificial I ntelligence varies based on the user and their end goal. While many individuals will use certain programs or websites to meet specific objectives , many companies and apps have begun to utilize this emerging technology to better meet their customer's needs.

Duolingo is a popular foreign language learning application that I use to supplement my Spanish studies . The app uses Artificial Intelligence to assess users' knowledge and understanding as they interact with the program , thus streamlining users learning outcomes.

As another example, Khan Academy is a free online resource that helps teachers and students learn any level of math or other grade school topics for free. They have created Khanmigo , using AI. The model acts as a tutor that helps work through a problem while not directly providing the answer. It can assist in writing an essay or solving a complex math problem step by step.

These everyday applications continue a trend of companies implementing this new technolog y into students and teachers' lives . . This new AI technology also allows business professionals to enhance aspects of their processes.

Entrepreneurs, A.I. and the Advantages

While AI already provides companies and organizations with new ways to interact with and better support their customers, AI could also provide emerging industries and entrepreneurs with new paths to business success. 

According to Entrpreneur.com, most businesses currently use AI for customer service purposes , however , AI could also help entrepreneurs create effective spreadsheets cataloging useful data with accuracy that can be incredibly specific or broad. Specifically with customer service, AI can quickly find what a customer needs and solve their problems efficiently. It could also analyze how effective marketing campaigns are influencing customers’ purchases.

As I researched for more information about this topic, I found an article in The Journal of Business Venturing Insights published in March 2023, sharing different techniques business students can use ChatGPT as an asset to generate entrepreneurial business pitches. The article titled “ The Artificially Intelligent Entrepreneur” written by Cole Short, an Assistant Professor of Strategy at Pepperdine University, and Jeremy C. Short, a UTA alumni and Professor at the University of North Texas at Denton, showcased different elevator pitch scenarios.

Students and entrepreneurs study CEOs who have impacted an industry dynamically; the CEO's mentality is an asset . I had the opportunity to question Dr. Jeremy Short on how he arrived at the initial question of using AI as a CEO archetype business consultant. An archetype is a symbol, term, or pattern of behavior which others have replicated or emulated.

He responded, “ We used this existing framework and selected a CEO from each archetype and used ChatGPT to create elevator pitches, social media pitches, and crowdfunding pitches. The strength of ChatGPT is based largely on the creativity of the prompt, which is where we aim as authors.”

An empty classroom sits unused.

CEO Archetypes and Prompt Engineering

ChatGPT allows the user to understand the archetypes of successful CEOs and collaborate with entrepreneurial styles. These archetypes are accessible options to consult with AI. Let ’ s break down different CEO archetypes students used during this study:

Creator CEOs are typically serial entrepreneurs and serve during the growth stages of developing new businesses. These individuals are risk takers recognizing opportunities that others don ’ t see. Elon Musk, CEO of Tesla, SpaceX, and Twitter is the creator archetype.

Transformer CEOs are created by climbing the ladder of a successful business and adding new ideas . They have a firm understanding of the company's culture and work to dramatically change the company, separating it from missteps in the past. Indra Nooyi CEO of PepsiCo is the transformer archetype.

Savior CEOs rescue businesses on the verge of failure with disciplined actions, unique experience and insights they forge a successful path forward for declining businesses. Lisa Su, CEO of AMD is the savior archetype.

ChatGPT was prompted to write an elevator pitch in the style of the previously listed CEOs. 

The response for Elon Musk included language about “ building” a product with “ cutting-edge technology.” 

Indra Nooyi ’s response included phrases like “ the world is changing” and making “ a positive impact in the world.” 

Lisa Su's response produced a pitch speaking about being “ accountable, tough and disciplined” with an emphasis on “ a strong focus on efficiency and performance.”

However, I believe these positions can help entrepreneurs develop their own successful business practices; creating a product your former employer could use to gain an advantage over the competition is disruptive. B uying a company on the brink of bankruptcy that has been mismanaged is a scenario entrepreneurs have explored and practiced .

Prompt engineering is the description of a task AI can accomplish , with instructions embedded in the input. Using prompt engineering, users can fine-tune their input to achieve a desired output incorporating a task description to guide the AI model. 

Conversation around ChatGPT and Artificial Intelligence

I asked Dr. Short about how students could use this technology as an asset that guides their learning and, additionally, how instructors can use this as well. He spoke about an assignment he is currently using in his classes. “ Chat GPT might be valuable in helping create a recipe for material that students can then refine. For example, in my social entrepreneurship class students create crowdfunding campaigns for either DonorsChoose , a platform that caters to public school teachers or GoFundMe , a service which allows a variety of project types to a larger userbase . I plan on students using ChatGPT to create a ‘rough draft’ to show me so I can see how they refine their responses for their particular campaigns this upcoming fall.” Th is approach allows students to take advantage of popular technology in a constructive way.

The journal article provided some notable conclusions about ChatGPT , i ncluding “ quality control is essential when using automated tools; a hallmark of success for large language models is their vast associative memory, this strength can also be a weakness. Specifically, models such as OpenAI’s GPT-3.5 and GPT-4 are capable of confidently generating “ hallucinated” output that appears correct but, it is incorrect or completely fabricated. ChatGPT serves as an emerging tool that can efficiently and flexibly produce a range of narrative content for entrepreneurs and serve to inspire future research at the intersection of entrepreneurship and AI.” ChatGPT ’s limitations and potential applications are continually being explored.

Industry Application

After researching various applications of AI, I spoke with Dr. George Benson, Professor and Department Chair of the Department of Management at The University of Texas at Arlington, about AI and ChatGPT from an industry perspective. His research focuses on Artificial Intelligence with Human Resource Management .

Dr. Benson told me that Artificial Intelligence is being invested heavily by human resource departments who are looking to automate hiring practices. Specifically, he mentioned “ HR is using this as a market opportunity. AI is a useful tool to sift through potential applicants by scanning their resumes for qualifications and experiences. Allowing professionals to hire applicants faster.”

This application allows the technology to handle low-level tasks, but the results generated are being handed to a human to review and act on. He spoke about the potential of A.I. “ There are a lot of unknowns, but the technology is new and getting better.” Looking towards the future, technology is already being applied in different ways . These applications are being explored in the classrooms of UTA as well.

A group of Alumni discuss rankings in a conference room.

Exploration of AI at UTA

The College of Business conduct ed a survey to understand the faculty’s attitude towards A I in the classroom. It was a part of the “Teaching with Chat GPT” workshop on Friday February 9 th , which focus ed on how to integrate Chat GPT and other AI platforms into teaching . 

Dr. Kevin Carr, a Clinical Assistant Professor of Marketing at UTA, was a part of the workshop ; he currently teaches Advanced Business Communication . I talked to him about the purpose of the workshop and what he hopes to gain from the group's sessions. 

Dr. Carr explained "The point of the workshop is designed to give faculty ideas for instruction and to develop classroom activities to work with students . Our goal for th e workshop is to introduce Artificial Intelligence as a teaching tool for faculty, including showing what AI can do potentially in the classroom. We are going to be very open to faculty’s direction, in terms of ongoing discu ssions and meetings.”

Personal Take

Artificial Intelligence or Chat GPT , in my view, is another useful tool in the toolbox of technology. It will take the air out of certain industries, and it will change jobs, yet every major technological advancement has the potential to do so. The automobile was considered radical, the use of plastic, computers in the workplace, and alternative energy have been impactful on society. 

Alternative energy was headlined as the end of oil use. The automobile changed the way cities were formed and led to the creation of a national highway system. Society has always found a way to adapt and overcome major technological innovations, artificial intelligence is not any different.

AI is the technology of tomorrow. It reminds me of something Dr. George Benson said , “ It's cool software that is a sophisticated search engine.” Google, one of the most popular search engines, reshaped the internet, as you search for resources, it is a natural starting point. AI and ChatGPT are an evolution, for students it is a tremendous resource consulting a CEO archetype, creating business pitches, and most importantly shaping the future .

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Changing Partisan Coalitions in a Politically Divided Nation

1. the partisanship and ideology of american voters, table of contents.

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The partisan identification of registered voters is now evenly split between the two major parties: 49% of registered voters are Democrats or lean to the Democratic Party, and a nearly identical share – 48% – are Republicans or lean to the Republican Party.

Trend chart over time showing that 49% of registered voters are Democrats or lean to the Democratic Party, and 48% are Republicans or lean to the Republican Party. Four years ago, Democrats had a 5 percentage point advantage.

The partisan balance has tightened in recent years following a clear edge in Democratic Party affiliation during the last administration.

  • Four years ago, in the run-up to the 2020 election, Democrats had a 5 percentage point advantage over the GOP (51% vs. 46%).

The share of voters who are in the Democratic coalition reached 55% in 2008. For much of the last three decades of Pew Research Center surveys, the partisan composition of registered voters has been more closely divided.

About two-thirds of registered voters identify as a partisan, and they are roughly evenly split between those who say they are Republicans (32% of voters) and those who say they are Democrats (33%). Roughly a third instead say they are independents or something else (35%), with most of these voters leaning toward one of the parties. Partisan leaners often share the same political views and behaviors as those who directly identify with the party they favor.

Bart charts over time showing that as of 2023, about two-thirds of registered voters identify as a partisan and are split between those who say they are Republicans (32%) and those who say they are Democrats (33%). Roughly a third instead say they are independents or something else (35%), with most of these voters leaning toward one of the parties. The share of voters who identify as independent or something else is somewhat higher than in the late 1990s and early 2000s.

The share of voters who identify as independent or something else is somewhat higher than in the late 1990s and early 2000s. As a result, there are more “leaners” today than in the past. Currently, 15% of voters lean toward the Republican Party and 16% lean toward the Democratic Party. By comparison, in 1994, 27% of voters leaned toward either the GOP (15%) or the Democratic Party (12%).

While the electorate overall is nearly equally divided between those who align with the Republican and Democratic parties, a greater share of registered voters say they are both ideologically conservative and associate with the Republican Party (33%) than say they are liberal and align with the Democratic Party (23%).

Bar charts by party and ideology showing that as of 2023, 33% of registered voters say they are both ideologically conservative and associate with the Republican Party, 14% identify as moderates or liberals and are Republicans or Republican leaners, 25% associate with the Democratic Party and describe their views as either conservative or moderate, and 23% are liberal and align with the Democratic Party.

A quarter of voters associate with the Democratic Party and describe their views as either conservative or moderate, and 14% identify as moderates or liberals and are Republicans or Republican leaners.

The partisan and ideological composition of voters is relatively unchanged over the last five years.

(As a result of significant mode differences in measures of ideology between telephone and online surveys, there is not directly comparable data on ideology prior to 2019.)

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    Research is the careful consideration of study regarding a particular concern or research problem using scientific methods. According to the American sociologist Earl Robert Babbie, "research is a systematic inquiry to describe, explain, predict, and control the observed phenomenon. It involves inductive and deductive methods.".

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    Research methods are specific procedures for collecting and analyzing data. Developing your research methods is an integral part of your research design. When planning your methods, there are two key decisions you will make. First, decide how you will collect data. Your methods depend on what type of data you need to answer your research question:

  7. A Beginner's Guide to Starting the Research Process

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    Brandon Marc Finn is an assistant research scientist in the Urban Sustainability Research Group and is a core faculty member of the Center for Sustainable Systems. His interdisciplinary research focuses on urbanization, informality, and mining, and his current work investigates the unintended consequences of decarbonization. In the Democratic Republic of Congo, Brandon is researching the ...

  26. Preventive antibiotics may help curb the STI epidemic, experts say

    New research finds that taking an antibiotic after sex, or even taking a smaller dose daily, substantially reduces the risk of sexually transmitted infections. IE 11 is not supported.

  27. What is a research project?

    A research project is an academic, scientific, or professional undertaking to answer a research question. Research projects can take many forms, such as qualitative or quantitative, descriptive, longitudinal, experimental, or correlational. What kind of research approach you choose will depend on your topic.

  28. Pathogenicity and transmissibility of bovine H5N1 influenza virus

    The Research Center for Global Viral Diseases, National Center for Global Health and Medicine Research Institute, Tokyo, Japan. Yoshihiro Kawaoka. Authors. Amie J. Eisfeld. View author publications.

  29. ChatGPT: Disruptive or Constructive?

    ChatGPT is a popular emerging technology using Artificial Intelligence. GPT stands for Generative Pre-trained Transformer, which describes an AI program that looks for patterns in language and data learning to predict the next word in a sentence or the next paragraph in an essay. The website has a friendly interface that allows users to interact with AI in a n efficient conversational tone.

  30. 1. The partisanship and ideology of American voters

    The partisan identification of registered voters is now evenly split between the two major parties: 49% of registered voters are Democrats or lean to the Democratic Party, and a nearly identical share - 48% - are Republicans or lean to the Republican Party. The partisan balance has tightened in recent years following a clear edge in Democratic Party affiliation during the last administration.