research types in medicine

Research Types Explained: Basic, Clinical, Translational

“Research” is a broad stroke of a word, the verbal equivalent of painting a wall instead of a masterpiece. There are important distinctions among the three principal types of medical research — basic, clinical and translational.

Whereas basic research is looking at questions related to how nature works, translational research aims to take what’s learned in basic research and apply that in the development of solutions to medical problems. Clinical research, then, takes those solutions and studies them in clinical trials. Together, they form a continuous research loop that transforms ideas into action in the form of new treatments and tests, and advances cutting-edge developments from the lab bench to the patient’s bedside and back again.

Basic Research

When it comes to science, the “basic” in basic research describes something that’s an essential starting point. “If you think of it in terms of construction, you can’t put up a beautiful, elegant house without first putting in a foundation,” says David Frank, MD , Associate Professor of Medicine, Medical Oncology, at Dana-Farber Cancer Institute. “In science, if you don’t first understand the basic research, then you can’t move on to advanced applications.”

Basic medical research is usually conducted by scientists with a PhD in such fields as biology and chemistry, among many others. They study the core building blocks of life — DNA, cells, proteins, molecules, etc. — to answer fundamental questions about their structures and how they work.

For example, oncologists now know that mutations in DNA enable the unchecked growth of cells in cancer. A scientist conducting basic research might ask: How does DNA work in a healthy cell? How do mutations occur? Where along the DNA sequence do mutations happen? And why?

“Basic research is fundamentally curiosity-driven research,” says Milka Kostic, Program Director, Chemical Biology at Dana-Farber Cancer Institute. “Think of that moment when an apple fell on Isaac Newton’s head. He thought to himself, ‘Why did that happen?’ and then went on to try to find the answer. That’s basic research.”

Clinical Research

Clinical research explores whether new treatments, medications and diagnostic techniques are safe and effective in patients. Physicians administer these to patients in rigorously controlled clinical trials, so that they can accurately and precisely monitor patients’ progress and evaluate the treatment’s efficacy, or measurable benefit.

“In clinical research, we’re trying to define the best treatment for a patient with a given condition,” Frank says. “We’re asking such questions as: Will this new treatment extend the life of a patient with a given type of cancer? Could this supportive medication diminish nausea, diarrhea or other side effects? Could this diagnostic test help physicians detect cancer earlier or distinguish between fast- and slow-growing cancers?”

Successful clinical researchers must draw on not only their medical training but also their knowledge of such areas as statistics, controls and regulatory compliance.

Translational Research

It’s neither practical nor safe to transition directly from studying individual cells to testing on patients. Translational research provides that crucial pivot point. It bridges the gap between basic and clinical research by bringing together a number of specialists to refine and advance the application of a discovery. “Biomedical science is so complex, and there’s so much knowledge available.” Frank says. “It’s through collaboration that advances are made.”

For example, let’s say a basic researcher has identified a gene that looks like a promising candidate for targeted therapy. Translational researchers would then evaluate thousands, if not millions, of potential compounds for the ideal combination that could be developed into a medicine to achieve the desired effect. They’d refine and test the compound on intermediate models, in laboratory and animal models. Then they would analyze those test results to determine proper dosage, side effects and other safety considerations before moving to first-in-human clinical trials. It’s the complex interplay of chemistry, biology, oncology, biostatistics, genomics, pharmacology and other specialties that makes such a translational study a success.

Collaboration and technology have been the twin drivers of recent quantum leaps in the quality and quantity of translational research. “Now, using modern molecular techniques,” Frank says, “we can learn so much from a tissue sample from a patient that we couldn’t before.”

Translational research provides a crucial pivot point after clinical trials as well. Investigators explore how the trial’s resulting treatment or guidelines can be implemented by physicians in their practice. And the clinical outcomes might also motivate basic researchers to reevaluate their original assumptions.

“Translational research is a two-way street,” Kostic says. “There is always conversation flowing in both directions. It’s a loop, a continuous cycle, with one research result inspiring another.”

Learn more about research at Dana-Farber .

Types of Study Design

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Introduction

Study designs are frameworks used in medical research to gather data and explore a specific research question .

Choosing an appropriate study design is one of many essential considerations before conducting research to minimise bias and yield valid results .

This guide provides a summary of study designs commonly used in medical research, their characteristics, advantages and disadvantages.

Case-report and case-series

A case report is a detailed description of a patient’s medical history, diagnosis, treatment, and outcome. A case report typically documents unusual or rare cases or reports  new or unexpected clinical findings .

A case series is a similar study that involves a group of patients sharing a similar disease or condition. A case series involves a comprehensive review of medical records for each patient to identify common features or disease patterns. Case series help better understand a disease’s presentation, diagnosis, and treatment.

While a case report focuses on a single patient, a case series involves a group of patients to provide a broader perspective on a specific disease. Both case reports and case series are important tools for understanding rare or unusual diseases .

Advantages of case series and case reports include:

• Able to describe rare or poorly understood conditions or diseases
• Helpful in generating hypotheses and identifying patterns or trends in patient populations
• Can be conducted relatively quickly and at a lower cost compared to other research designs

Disadvantages

Disadvantages of case series and case reports include:

• Prone to selection bias , meaning that the patients included in the series may not be representative of the general population
• Lack a control group, which makes it difficult to conclude  the effectiveness of different treatments or interventions
• They are descriptive and cannot establish causality or control for confounding factors

Cross-sectional study

A cross-sectional study aims to measure the prevalence or frequency of a disease in a population at a specific point in time. In other words, it provides a “ snapshot ” of the population at a single moment in time.

Cross-sectional studies are unique from other study designs in that they collect data on the exposure and the outcome of interest from a sample of individuals in the population. This type of data is used to investigate the distribution of health-related conditions and behaviours in different populations, which is especially useful for guiding the development of public health interventions .

Example of a cross-sectional study

A cross-sectional study might investigate the prevalence of hypertension (the outcome) in a sample of adults in a particular region. The researchers would measure blood pressure levels in each participant and gather information on other factors that could influence blood pressure, such as age, sex, weight, and lifestyle habits (exposure).

Advantages of cross-sectional studies include:

• Relatively quick and inexpensive to conduct compared to other study designs, such as cohort or case-control studies
• They can provide a snapshot of the prevalence and distribution of a particular health condition in a population
• They can help to identify patterns and associations between exposure and outcome variables, which can be used to generate hypotheses for further research

Disadvantages of cross-sectional studies include:

• They cannot establish causality , as they do not follow participants over time and cannot determine the temporal sequence between exposure and outcome
• Prone to selection bias , as the sample may not represent the entire population being studied
• They cannot account for confounding variables , which may affect the relationship between the exposure and outcome of interest

Case-control study

A case-control study compares people who have developed a disease of interest ( cases ) with people who have not developed the disease ( controls ) to identify potential risk factors associated with the disease.

Once cases and controls have been identified, researchers then collect information about related risk factors , such as age, sex, lifestyle factors, or environmental exposures, from individuals. By comparing the prevalence of risk factors between the cases and the controls, researchers can determine the association between the risk factors and the disease.

Example of a case-control study

A case-control study design might involve comparing a group of individuals with lung cancer (cases) to a group of individuals without lung cancer (controls) to assess the association between smoking (risk factor) and the development of lung cancer.

Advantages of case-control studies include:

• Useful for studying rare diseases , as they allow researchers to selectively recruit cases with the disease of interest
• Useful for investigating potential risk factors for a disease, as the researchers can collect data on many different factors from both cases and controls
• Can be helpful in situations where it is not ethical or practical to manipulate exposure levels or randomise study participants

Disadvantages of case-control studies include:

• Prone to selection bias , as the controls may not be representative of the general population or may have different underlying risk factors than the cases
• Cannot establish causality , as they can only identify associations between factors and disease
• May be limited by the availability of suitable controls , as finding appropriate controls who have similar characteristics to the cases can be challenging

Cohort study

A cohort study follows a group of individuals (a cohort) over time to investigate the relationship between an exposure or risk factor and a particular outcome or health condition. Cohort studies can be further classified into prospective or retrospective cohort studies.

Prospective cohort study

A prospective cohort study is a study in which the researchers select a group of individuals who do not have a particular disease or outcome of interest at the start of the study.

They then follow this cohort over time to track the number of patients who develop the outcome . Before the start of the study, information on exposure(s) of interest may also be collected.

Example of a prospective cohort study

A prospective cohort study might follow a group of individuals who have never smoked and measure their exposure to tobacco smoke over time to investigate the relationship between smoking and lung cancer .

Retrospective cohort study

In contrast, a retrospective cohort study is a study in which the researchers select a group of individuals who have already been exposed to something (e.g. smoking) and look back in time (for example, through patient charts) to see if they developed the outcome (e.g. lung cancer ).

The key difference in retrospective cohort studies is that data on exposure and outcome are collected after the outcome has occurred.

Example of a retrospective cohort study

A retrospective cohort study might look at the medical records of smokers and see if they developed a particular adverse event such as lung cancer.

Advantages of cohort studies include:

• Generally considered to be the most appropriate study design for investigating the temporal relationship between exposure and outcome
• Can provide estimates of incidence and relative risk , which are useful for quantifying the strength of the association between exposure and outcome
• Can be used to investigate multiple outcomes or endpoints associated with a particular exposure, which can help to identify unexpected effects or outcomes

Disadvantages of cohort studies include:

• Can be expensive and time-consuming to conduct, particularly for long-term follow-up
• May suffer from selection bias , as the sample may not be representative of the entire population being studied
• May suffer from attrition bias , as participants may drop out or be lost to follow-up over time

Meta-analysis

A meta-analysis is a type of study that involves extracting outcome data from all relevant studies in the literature and combining the results of multiple studies to produce an overall estimate of the effect size of an intervention or exposure.

Meta-analysis is often conducted alongside a systematic review and can be considered a study of studies . By doing this, researchers provide a more comprehensive and reliable estimate of the overall effect size and their confidence interval (a measure of precision).

Meta-analyses can be conducted for a wide range of research questions , including evaluating the effectiveness of medical interventions, identifying risk factors for disease, or assessing the accuracy of diagnostic tests. They are particularly useful when the results of individual studies are inconsistent or when the sample sizes of individual studies are small, as a meta-analysis can provide a more precise estimate of the true effect size.

When conducting a meta-analysis, researchers must carefully assess the risk of bias in each study to enhance the validity of the meta-analysis. Many aspects of research studies are prone to bias , such as the methodology and the reporting of results. Where studies exhibit a high risk of bias, authors may opt to exclude the study from the analysis or perform a subgroup or sensitivity analysis.

Advantages of a meta-analysis include:

• Combine the results of multiple studies, resulting in a larger sample size and increased statistical power, to provide a more comprehensive and precise estimate of the effect size of an intervention or outcome
• Can help to identify sources of heterogeneity or variability in the results of individual studies by exploring the influence of different study characteristics or subgroups
• Can help to resolve conflicting results or controversies in the literature by providing a more robust estimate of the effect size

Disadvantages of a meta-analysis include:

• Susceptible to publication bias , where studies with statistically significant or positive results are more likely to be published than studies with nonsignificant or negative results. This bias can lead to an overestimation of the treatment effect in a meta-analysis
• May not be appropriate if the studies included are too heterogeneous , as this can make it difficult to draw meaningful conclusions from the pooled results
• Depend on the quality and completeness of the data available from the individual studies and may be limited by the lack of data on certain outcomes or subgroups

Ecological study

An ecological study assesses the relationship between outcome and exposure at a population level or among groups of people rather than studying individuals directly.

The main goal of an ecological study is to observe and analyse patterns or trends at the population level and to identify potential associations or correlations between environmental factors or exposures and health outcomes.

Ecological studies focus on collecting data on population health outcomes , such as disease or mortality rates, and environmental factors or exposures, such as air pollution, temperature, or socioeconomic status.

Example of an ecological study

An ecological study might be used when comparing smoking rates and lung cancer incidence across different countries.

Advantages of an ecological study include:

• Provide insights into how social, economic, and environmental factors may impact health outcomes in real-world settings , which can inform public health policies and interventions
• Cost-effective and efficient, often using existing data or readily available data, such as data from national or regional databases

Disadvantages of an ecological study include:

• Ecological fallacy occurs when conclusions about individual-level associations are drawn from population-level differences
• Ecological studies rely on population-level (i.e. aggregate) rather than individual-level data; they cannot establish causal relationships between exposures and outcomes, as the studies do not account for differences or confounders at the individual level

Randomised controlled trial

A randomised controlled trial (RCT) is an important study design commonly used in medical research to determine the effectiveness of a treatment or intervention . It is considered the gold standard in research design because it allows researchers to draw cause-and-effect conclusions about the effects of an intervention.

In an RCT, participants are randomly assigned to two or more groups. One group receives the intervention being tested, such as a new drug or a specific medical procedure. In contrast, the other group is a control group and receives either no intervention or a placebo .

Randomisation ensures that each participant has an equal chance of being assigned to either group, thereby minimising selection bias . To reduce bias, an RCT often uses a technique called blinding , in which study participants, researchers, or analysts are kept unaware of participant assignment during the study. The participants are then followed over time, and outcome measures are collected and compared to determine if there is any statistical difference between the intervention and control groups.

Example of a randomised controlled trial

An RCT might be employed to evaluate the effectiveness of a new smoking cessation program in helping individuals quit smoking compared to the existing standard of care.

Advantages of an RCT include:

• Considered the most reliable study design for establishing causal relationships between interventions and outcomes and determining the effectiveness of interventions
• Randomisation of participants to intervention and control groups ensures that the groups are similar at the outset, reducing the risk of selection bias and enhancing internal validity
• Using a control group allows researchers to compare with the group that received the intervention while controlling for confounding factors

Disadvantages of an RCT include:

• Can raise ethical concerns ; for example, it may be considered unethical to withhold an intervention from a control group, especially if the intervention is known to be effective
• Can be expensive and time-consuming to conduct, requiring resources for participant recruitment, randomisation, data collection, and analysis
• Often have strict inclusion and exclusion criteria , which may limit the generalisability of the findings to broader populations
• May not always be feasible or practical for certain research questions, especially in rare diseases or when studying long-term outcomes

Dr Chris Jefferies

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• Rothman KJ, Greenland S, Lash T. Modern Epidemiology. 3 rd ed. Philadelphia: Lippincott Williams & Wilkins; 2008.

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Evidence-Based Medicine: Types of Studies

• What is Evidence-Based Practice?
• Question Types and Corresponding Resources
• Types of Studies
• Practice Guidelines
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Experimental vs. Observational Studies

An observational study is a study in which the investigator cannot control the assignment of treatment to subjects because the participants or conditions are not directly assigned by the researcher.

• Examines predetermined treatments, interventions, policies, and their effects
• Four main types: case series , case-control studies , cross-sectional studies , and cohort studies

In an experimental study , the investigators directly manipulate or assign participants to different interventions or environments

Experimental studies that involve humans are called clinical trials . They fall into two categories: those with controls, and those without controls.

• Controlled trials - studies in which the experimental drug or procedure is compared with another drug or procedure
• Uncontrolled trials - studies in which the investigators' experience with the experimental drug or procedure is described, but the treatment is not compared with another treatment

Definitions taken from: Dawson B, Trapp R.G. (2004). Chapter 2. Study Designs in Medical Research. In Dawson B, Trapp R.G. (Eds), Basic & Clinical Biostatistics, 4e . Retrieved September 15, 2014 from  https://accessmedicine.mhmedical.com/book.aspx?bookid=2724

Levels of Evidence Pyramid

Levels of Evidence Pyramid created by Andy Puro, September 2014

Additional Study Design Resources

Study Design 101 : Himmelfarb's tutorial on study types and how to find them

Study Designs  (Centre for Evidence Based Medicine, University of Oxford)

Learn about Clinical Studies  (ClinicalTrials.gov, National Institutes of Health)

Study Designs Guide  (Deakin University)

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• Clinical Trials: What Patients Need to Know

What Are the Different Types of Clinical Research?

Different types of clinical research are used depending on what the researchers are studying. Below are descriptions of some different kinds of clinical research.

Treatment Research generally involves an intervention such as medication, psychotherapy, new devices, or new approaches to surgery or radiation therapy. 

Prevention Research looks for better ways to prevent disorders from developing or returning. Different kinds of prevention research may study medicines, vitamins, vaccines, minerals, or lifestyle changes. 

Diagnostic Research refers to the practice of looking for better ways to identify a particular disorder or condition. 

Screening Research aims to find the best ways to detect certain disorders or health conditions. 

Quality of Life Research explores ways to improve comfort and the quality of life for individuals with a chronic illness. 

Genetic studies aim to improve the prediction of disorders by identifying and understanding how genes and illnesses may be related. Research in this area may explore ways in which a person’s genes make him or her more or less likely to develop a disorder. This may lead to development of tailor-made treatments based on a patient’s genetic make-up. 

Epidemiological studies seek to identify the patterns, causes, and control of disorders in groups of people. 

An important note: some clinical research is “outpatient,” meaning that participants do not stay overnight at the hospital. Some is “inpatient,” meaning that participants will need to stay for at least one night in the hospital or research center. Be sure to ask the researchers what their study requires. 

Phases of clinical trials: when clinical research is used to evaluate medications and devices Clinical trials are a kind of clinical research designed to evaluate and test new interventions such as psychotherapy or medications. Clinical trials are often conducted in four phases. The trials at each phase have a different purpose and help scientists answer different questions. 

Phase I trials Researchers test an experimental drug or treatment in a small group of people for the first time. The researchers evaluate the treatment’s safety, determine a safe dosage range, and identify side effects. 

Phase II trials The experimental drug or treatment is given to a larger group of people to see if it is effective and to further evaluate its safety.

Phase III trials The experimental study drug or treatment is given to large groups of people. Researchers confirm its effectiveness, monitor side effects, compare it to commonly used treatments, and collect information that will allow the experimental drug or treatment to be used safely. 

Phase IV trials Post-marketing studies, which are conducted after a treatment is approved for use by the FDA, provide additional information including the treatment or drug’s risks, benefits, and best use.

Examples of other kinds of clinical research Many people believe that all clinical research involves testing of new medications or devices. This is not true, however. Some studies do not involve testing medications and a person’s regular medications may not need to be changed. Healthy volunteers are also needed so that researchers can compare their results to results of people with the illness being studied. Some examples of other kinds of research include the following: 

A long-term study that involves psychological tests or brain scans

A genetic study that involves blood tests but no changes in medication

A study of family history that involves talking to family members to learn about people’s medical needs and history.

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Understanding Clinical Trials

Clinical research: what is it.

Your doctor may have said that you are eligible for a clinical trial, or you may have seen an ad for a clinical research study. What is clinical research, and is it right for you?

Clinical research is the comprehensive study of the safety and effectiveness of the most promising advances in patient care. Clinical research is different than laboratory research. It involves people who volunteer to help us better understand medicine and health. Lab research generally does not involve people — although it helps us learn which new ideas may help people.

Every drug, device, tool, diagnostic test, technique and technology used in medicine today was once tested in volunteers who took part in clinical research studies.

At Johns Hopkins Medicine, we believe that clinical research is key to improve care for people in our community and around the world. Once you understand more about clinical research, you may appreciate why it’s important to participate — for yourself and the community.

What Are the Types of Clinical Research?

There are two main kinds of clinical research:

Observational Studies

Observational studies are studies that aim to identify and analyze patterns in medical data or in biological samples, such as tissue or blood provided by study participants.

Clinical Trials

Clinical trials, which are also called interventional studies, test the safety and effectiveness of medical interventions — such as medications, procedures and tools — in living people.

Clinical research studies need people of every age, health status, race, gender, ethnicity and cultural background to participate. This will increase the chances that scientists and clinicians will develop treatments and procedures that are likely to be safe and work well in all people. Potential volunteers are carefully screened to ensure that they meet all of the requirements for any study before they begin. Most of the reasons people are not included in studies is because of concerns about safety.

Both healthy people and those with diagnosed medical conditions can take part in clinical research. Participation is always completely voluntary, and participants can leave a study at any time for any reason.

“The only way medical advancements can be made is if people volunteer to participate in clinical research. The research participant is just as necessary as the researcher in this partnership to advance health care.” Liz Martinez, Johns Hopkins Medicine Research Participant Advocate

Types of Research Studies

Within the two main kinds of clinical research, there are many types of studies. They vary based on the study goals, participants and other factors.

Biospecimen studies

Healthy volunteer studies.

Clinical trials study the safety and effectiveness of interventions and procedures on people’s health. Interventions may include medications, radiation, foods or behaviors, such as exercise. Usually, the treatments in clinical trials are studied in a laboratory and sometimes in animals before they are studied in humans. The goal of clinical trials is to find new and better ways of preventing, diagnosing and treating disease. They are used to test:

Drugs or medicines

New types of surgery

Medical devices

New ways of using current treatments

New ways of changing health behaviors

New ways to improve quality of life for sick patients

 Goals of Clinical Trials

Because every clinical trial is designed to answer one or more medical questions, different trials have different goals. Those goals include:

Treatment trials

Prevention trials, screening trials, phases of a clinical trial.

In general, a new drug needs to go through a series of four types of clinical trials. This helps researchers show that the medication is safe and effective. As a study moves through each phase, researchers learn more about a medication, including its risks and benefits.

Is the medication safe and what is the right dose?   Phase one trials involve small numbers of participants, often normal volunteers.

Does the new medication work and what are the side effects?   Phase two trials test the treatment or procedure on a larger number of participants. These participants usually have the condition or disease that the treatment is intended to remedy.

Is the new medication more effective than existing treatments?  Phase three trials have even more people enrolled. Some may get a placebo (a substance that has no medical effect) or an already approved treatment, so that the new medication can be compared to that treatment.

Is the new medication effective and safe over the long term?   Phase four happens after the treatment or procedure has been approved. Information about patients who are receiving the treatment is gathered and studied to see if any new information is seen when given to a large number of patients.

“Johns Hopkins has a comprehensive system overseeing research that is audited by the FDA and the Association for Accreditation of Human Research Protection Programs to make certain all research participants voluntarily agreed to join a study and their safety was maximized.” Gail Daumit, M.D., M.H.S., Vice Dean for Clinical Investigation, Johns Hopkins University School of Medicine

Is It Safe to Participate in Clinical Research?

There are several steps in place to protect volunteers who take part in clinical research studies. Clinical Research is regulated by the federal government. In addition, the institutional review board (IRB) and Human Subjects Research Protection Program at each study location have many safeguards built in to each study to protect the safety and privacy of participants.

Clinical researchers are required by law to follow the safety rules outlined by each study's protocol. A protocol is a detailed plan of what researchers will do in during the study.

In the U.S., every study site's IRB — which is made up of both medical experts and members of the general public — must approve all clinical research. IRB members also review plans for all clinical studies. And, they make sure that research participants are protected from as much risk as possible.

Earning Your Trust

This was not always the case. Many people of color are wary of joining clinical research because of previous poor treatment of underrepresented minorities throughout the U.S. This includes medical research performed on enslaved people without their consent, or not giving treatment to Black men who participated in the Tuskegee Study of Untreated Syphilis in the Negro Male. Since the 1970s, numerous regulations have been in place to protect the rights of study participants.

Many clinical research studies are also supervised by a data and safety monitoring committee. This is a group made up of experts in the area being studied. These biomedical professionals regularly monitor clinical studies as they progress. If they discover or suspect any problems with a study, they immediately stop the trial. In addition, Johns Hopkins Medicine’s Research Participant Advocacy Group focuses on improving the experience of people who participate in clinical research.

Clinical research participants with concerns about anything related to the study they are taking part in should contact Johns Hopkins Medicine’s IRB or our Research Participant Advocacy Group .

Learn More About Clinical Research at Johns Hopkins Medicine

For information about clinical trial opportunities at Johns Hopkins Medicine, visit our trials site.

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Types of Study

Introduction to Types of Medical Research

Evidence-based medicine may be defined as the systematic, quantitative and preferentially experimental approach to obtaining medical information. This information is obtained through medical research. Medical research encompasses a wide range of study techniques that can be used to understand diseases, uncover their causative factors and validate the treatments we have available for them. Each type of study technique comes with advantages as well as their own particular disadvantages. This article will introduce the different types of study commonly used within medical research and discuss their particular traits. The diagram below provides an overview of how the different types of study methodology relate to one another.

Primary vs. Secondary Research

Medical research can be classified as either primary or secondary research. Primary research involves performing studies and collecting raw data. Secondary research involves evaluating or synthesising data collected during primary research.

Observational vs. Experimental Research

An observational study is a study in which the investigator does not seek to control any of the variables nor the assignment of intervention to subjects. These decisions are usually made by the patient and their doctor. Examples include cohort, case-control, case-series and cross-sectional studies.

An experimental study involves direct manipulation or assignment of participants to different interventions or environments. Clinical experimental studies are known as clinical trials.

Prospective vs. Retrospective

In prospective studies , individuals are followed over a period of time and data is collected when their characteristics or circumstances change. Studies usually relate the outcome of interest to suspected risk factors. For these prospective studies, the outcome of interest should commonly occur to ensure statistical significance. Prospective studies allow precise estimation of the relative risk of an outcome based upon exposure.

In retrospective studies , individuals are sampled and information is collected about their past. These studies usually establish an outcome of interest and examine exposures to suspected risk or protective factors. Data is typically gathered from interviews or medical notes. The nature of retrospective studies makes them more susceptible to bias. Retrospective studies allow calculation of the odds ratio (this is an estimate of the relative risk) for uncommon outcomes. Retrospective studies are advantageous for studying rare diseases since prospective studies are unfeasible due to the large study sizes needed to reach statistical significance.

Randomised vs. Non-Randomised

Randomised studies involve the random allocation of individuals to intervention groups in order to minimise confounding variables. Allocation does not take into account any similarities or differences in the individuals. It usually involves use of a random number generator.

Non-randomised studies involve allocation of people to different interventions using methods which are not random.

Single-Blinded vs. Double Blinded vs. Triple-Blinded

Blinding is important to reduce bias and ensure a study’s internal validity. It prevents participants and researchers from affecting the outcomes of a study in a conscious or subconscious manner.

• Single-blind study – only the participants are blinded.
• Double-blind study – both participants and experimenters are blinded.
• Triple-blind study – participants, experimenters and researchers analysing the data are blinded.

The Levels of Evidence

Not all evidence is created equal with some forms of study technique thought to be superior in design. Studies which employ superior designs are felt to carry more weight when interpreting their conclusions. The result is the creation of a hierarchy based upon study technique. This has been outlined in the diagram below.

The ordering of evidence in this manner may be seen as simplistic because it does not take into account the methodological merit of individual study designs. Furthermore, the quality of systematic review evidence will depend largely upon the type of study included within the analysis and meta-analysis results can vary wildly depending upon the statistical methods employed. In the final instance, systematic reviews should be considered a lens through which evidence can be viewed.

Brief Description of Study Types

In this section we will cover the basics of the following study designs.

• Meta-Analysis
• Systematic Review
• Randomised Control Trial
• Cohort Study
• Case Control Series
• Case Report/Series

For further information on each of these study designs and how to perform them, have a look at the Equator Network .

Meta-Analysis - Secondary Research

Definition: A meta-analysis is a statistical procedure for systematically combining numerical (quantitative) data from multiple independent studies in the published literature. These data are assessed and used to derive conclusions about that body of research. It is a subset of systematic reviews (see below).

Uses: Meta-analyses can be used to provide more precise estimates than those given by any individual study included within the analysis. They may also answer questions not posed by individual studies or identify and examine the heterogeneity between the individual studies (including statistical significance where conflicting results are reported). Examples of alternative questions include providing a more complex analysis of harms/benefits or the examination of subgroups where individual study numbers were not large enough.

Brief Methodology: The Cochrane collaboration has developed a protocol which provides structure for literature search, analytic and diagnostic methods for evaluating the output of meta-analyses. These can be viewed within their handbook . Additional guidance can be found by using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). This is an evidence-based minimum set of items (checklist) for reporting in systematic reviews and meta-analyses.

• Provides greater statistical power and increased volume of data for more precise estimates.
• Hypothesis testing and biases within publications can be examined.
• Inconsistencies within research can be resolved.
• Provides better estimate of relationships.

Disadvantages

• It is difficult and time consuming to identify the correct studies.
• Not all studies may be appropriate for inclusion.
• An incomplete set of studies may have been analysed.
• Requires advanced statistical capabilities.
• Heterogeneity of methods used in studies may lead to erroneous inferences.

Systematic Review - Secondary Research

Definition: A systematic review is a detailed, systematic and transparent means of considering all published and unpublished material which fits within a prespecified eligibility criteria. The included material can be of varying study designs. Those materials which are judged to be methodologically sound are combined in either a quantitative or qualitative manner to answer a pre-defined research question. Meta-analyses are not required but many systematic reviews will include a meta-analysis.

Uses: Systematic reviews are used to deliver a meticulous summary of the available primary research in response to a research question.

Brief Methodology: Systematic reviews should have a clear set of objectives, predefined eligibility criteria, a reproducible methodology, a systemic search method, an assessment of the validity of the findings of included studies and a systematic presentation and synthesis of the attributes and findings from the studies used.

• Addresses a specific question.
• Explicit and bias limiting methods.
• More reliable and accurate than individual studies.
• Less costly than organising a new study.
• Requires less time than a new study.
• Results can be generalised and extrapolated into the general population.
• Time consuming.
• There may be difficulties combining different studies.
• May be composed of inadequate primary studies.
• May be poorly designed and executed.
• May mis-interpret results.

Randomised Controlled Trial - Primary Research, Experimental, Prospective

Definition: A randomised control trial involves one or more new treatments where participants are randomly assigned into an experimental or control group. The various groups are then followed up to see if there is any difference in the specified outcome. The results and subsequent analysis are used to evaluating the effectiveness of the intervention.

Uses: Randomised controlled trials are used to establish the effectiveness of a new intervention or treatment.

Brief Methodology: Interventions might include a medication or procedure. Control groups will either get a placebo treatment or receive the current ‘gold standard’ treatment. Randomisation seeks to evenly distribute baseline characteristics in order to reduce the effect of confounding variables. This process is usually performed using mathematical techniques.

The CONSORT (Consolidated Standards of Reporting Trials) Statement can be used as an evidence-based minimum set of recommendations (checklist) for reporting randomised trials. The Cochrane Library has formed a highly concentrated source of reports of randomised controlled trials which can be found within their CENTRAL (Cochrane Central Register of Controlled Trials) database.

• You can make direct comparisons between treatments.
• Effective randomisation removes selection bias.
• Randomisation reduces the impact of confounding factors and makes groups comparable with both known and unknown factors.
• Results can be reliably analysed with statistical tools.
• Blinding can be applied to reduce performance bias.
• Prospective design minimises recall error and selection bias.
• It is expensive and takes time.
• Participants must volunteer and so may not be representative of the whole population.
• Studies will have to be powered sufficiently to make significant outcomes.
• There is the risk of participants being lost to follow up.
• Ethical limitations. For example, informed consent is impossible to obtain, or some intervention arms would be ethically impossible.
• Results may not mimic realise and generalisability to the real world may be difficult.

Cohort Studies - Primary Research, Observational, Predominantly Prospective

Definition: Groups of disease-free individuals are identified, and baseline measurements are taken for a variety of variables (risk factors) that might be relevant to the development of the outcome of interest. These individuals are then followed over time to determine whether they develop the outcome of interest. Cohort studies are usually prospective but can be performed retrospectively with data collected for other purposes.

Uses: Cohort studies measure incidence rates and the relative risk for developing the outcome of interest for each measured variable. They are able to distinguish between cause and effect due to the temporal relationship between risk factor exposure and outcome occurrence.

Brief Methodology: In prospective cohort studies the risk exposure information is collected at the start of the study and new cases of disease identified from that point onwards. In retrospective cohort studies the exposure status was measured in the past and disease identification has already begun. Both methods enable calculation of the relative risk.

The STROBE (STrengthening the Reporting of OBservational studies in Epidemiology) statement (checklist) can be used to ensure observational studies are adequately described in research publications. This checklist has been designed for cohort studies, case-control studies and cross-sectional studies.

• It is cheaper and easier to implement than a randomised controlled trial.
• It is able to distinguish between cause and effect.
• Multiple outcomes can be studied.
• It may uncover unanticipated associations with the outcome.
• The efficiency of prospective cohort studies increases as the incidence of any particular outcome increases.
• Patients can be lost to follow up thereby introducing attrition bias.
• Subject selection can introduce bias due to an imbalance of patient characteristics.
• It is prone to change of methods over time.
• Confounding variables can be difficult to remove.
• It is difficult to blind researchers.
• Requires large numbers of patients.
• The outcome of interest can take a long time to occur.

Case Control Studies - Primary Research, Observational, Retrospective

Definition: A study that compares patients who have an outcome of interest (the disease in question) with those who do not. Case control studies are almost always retrospective. The researcher looks back in time to identify which individuals were exposed to a risk factor or treatment and thus the relation it has with the presence or absence of disease.

Uses: Good for studying rare diseases and outcomes. They can also be used where there is a long latent period between an exposure and disease occurrence. They are often used to generate hypotheses that can then be studied using other means.

Brief Methodology: Individuals with the outcome of interest (the disease in question) are selected (cases). A second group of similar individuals without the outcome of interest is constructed (controls). The researcher then looks at historical factors to identify if some exposures are found more commonly in the cases than the controls. If this is the case, a link can be established between the exposure and the outcome of interest. This produces an odds ratio that can be used to approximate the relative risk for each variable studied.

Case Report/Series - Primary Research, Observational, Retrospective

Definition: An article that describes and interprets an individual case or cases. It is often written as a detailed story.

Brief Methodology: An interesting case is identified, and the patient should be described in detail. Include the following: their age, sex, ethnicity, race, employment status, social situation, medical history, diagnosis, prognosis, previous treatments, diagnostic tests, medications, current intervention and the clinical and functional assessment.

Uses: Describe unique cases that cannot be explained by known diseases or syndromes. They may show an important variation from a known disease. They may show unexpected events that yield new information. They may include patients with two or more unexpected diseases or disorders.

• Stats Direct
• Cochrane Handbook
• CONSORT Statement: Cosolidated Standards of Reporting Trials
• PRISMA Statement: Preferred Reporting Items for Systematic Reviews and Meta-Analyses
• STROBE Statement: Strengthening the Reporting of Observational Studies in Epidemiology
• Equator Network: Enhancing the Quality and Transparency of Health Research
• Open MD: Medical Research
• Deutsches Ärzteblatt International: Types of Study in Medical Research
• Himmelfarb: Types of Studies
• Georgia State University: Literature Reviews: Types of Clinical Study Designs
• Deutsches Ärzteblatt International: Systematic Literature Reviews and Meta-Analyses
• Emergency Medicine Journal: Randomised Controlled Trials and Their Principles

Also in Research

Writing your First Research Article

The Anatomy of a Research Article

P-Values and Confidence Intervals

Introduction to Descriptive Statistics

Introduction to Inferential Statistics

Diagnostic Tables

Relative Risk and Odds Ratio

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Major Types of Research for Medicine & Health

Basic sciences research.

Basic research asks fundamental questions about how life works. Scientists study cells, genes, proteins, and other building blocks of life. What they find can lead to better ways to predict, prevent, diagnose, and treat disease. more about Basic Science Research

Clinical research is research conducted with human subjects, or material of human origin, in which the researcher directly interacts with human subjects. Clinical researchers at the National Human Genome Research Institute (NHGRI) are developing advanced methods for studying the fundamental mechanisms of inherited and acquired genetic disorders. FAQs about Clinical Research

Epidemiological Research

The basic epidemiological study designs are cross-sectional, case-control, and cohort studies. Cross-sectional studies provide a snapshot of a population by determining both exposures and outcomes at one time point. Cohort studies identify the study groups based on the exposure and, then, the researchers follow up study participants to measure outcomes. Case-control studies identify the study groups based on the outcome, and the researchers retrospectively collect the exposure of interest. F rom: Introduction to Epidemiological Studies

Mixed Methods Research

• Glossary of Key Terms From Colorado State University: Members of the Research Methods Seminar (E600) taught by Mike Palmquist in the 1990s and 2000s. (1994-2022). Glossary of Key Terms. Writing@CSU. Colorado State University. https://writing.colostate.edu/guides/guide.cfm?guideid=90
• Mixed Methods in Health Sciences Research Sage Research Methods
• Mixed Methods Research : A guide to the Field From Sate Research Methods Conceptual Framework for the Field of Mixed Methods Research Welcome to the field of mixed methods research! We begin this book by considering the
• NIH Mixed Methods Research Pprovides guidance to NIH investigators on how to rigorously develop and evaluate mixed methods research applications. Pursuant to this, the team developed a report of “best practices” following three major objectives.
• SAGE Mixed Methods Research An Overview of Mixed Methods Research

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• Hypothesis Testing Penn State University tutorial
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• GOHy Worksheet - Minimal experiemental design Worksheet for experimental design development

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Types of studies and research design

Affiliation.

• 1 Department of Anesthesiology, Max Smart Super Specialty Hospital, New Delhi, India.
• PMID: 27729687
• PMCID: PMC5037941
• DOI: 10.4103/0019-5049.190616

Medical research has evolved, from individual expert described opinions and techniques, to scientifically designed methodology-based studies. Evidence-based medicine (EBM) was established to re-evaluate medical facts and remove various myths in clinical practice. Research methodology is now protocol based with predefined steps. Studies were classified based on the method of collection and evaluation of data. Clinical study methodology now needs to comply to strict ethical, moral, truth, and transparency standards, ensuring that no conflict of interest is involved. A medical research pyramid has been designed to grade the quality of evidence and help physicians determine the value of the research. Randomised controlled trials (RCTs) have become gold standards for quality research. EBM now scales systemic reviews and meta-analyses at a level higher than RCTs to overcome deficiencies in the randomised trials due to errors in methodology and analyses.

Keywords: Clinical trials; evidence-based medicine; medical research; meta-analysis.

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Types of Research – Explained with Examples

• By DiscoverPhDs
• October 2, 2020

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.

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.

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.

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.

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.

A concept paper is a short document written by a researcher before starting their research project, explaining what the study is about, why it is needed and the methods that will be used.

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A science investigatory project is a science-based research project or study that is performed by school children in a classroom, exhibition or science fair.

Is it really possible to do a PhD while working? The answer is ‘yes’, but it comes with several ‘buts’. Read our post to find out if it’s for you.

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Types of Primary Medical Research

Medical research may be classified as either primary or secondary research. Primary research entails conducting studies and collecting raw data. Secondary research evaluates or synthesizes data collected during primary research.

Primary medical research is categorized into three main fields: laboratorial, clinical, and epidemiological. Laboratory scientists analyze the fundamentals of diseases and treatments. Clinical researchers collaborate with participants to test new and established forms of treatment. Epidemiologists focus on populations to identify the cause and distribution of diseases.

Basic/Laboratory Research

Laboratory, or basic, research involves scientific investigation and experimentation in a controlled environment to establish or confirm an understanding of chemical interactions, genetic material, cells, and biologic agents—more specifically, the agent’s relationships, behaviors, or properties. Basic science forms the knowledge-base and foundation upon which other types of research are built. Laboratory scientists investigate specific hypotheses which contribute to the development of new medical treatments.

An advantage of this type of research is that scientists can control the variables within a laboratory setting. Such a high level of control is often not possible outside of the laboratory. This leads to greater internal validity of a hypothesis and allows the testing of various aspects of disease and potential treatments. The key to laboratory research is to establish at least one independent variable, while holding all others constant. The standardized conditions of a laboratory setting also support the development of new medical imaging and diagnostic tools.

Applied research aims to solve problems such as treating a particular disease that is under investigation. There a number of different study types within applied research, including:

• Animal studies: Animals are often induced to have a particular disease model so that the disease and potential treatments can be better understood for use with humans.
• Biochemistry: Focuses upon the chemical processes that occur within the body; biochemistry also explores the metabolic basis of disease.
• Cell study: Examines how cells develop and each cell type’s potential role in disease or treatment.
• Genomics: Explores how all genes interact to influence the growth, health, and potential disease development of an organism/human.
• Pharmacogenetics: Pharmacogenetics seeks to better understand the influence genes have upon how a patient might respond to any treatments they may receive. 3

Theoretical

Clinical Research

Clinical research is conducted to improve the understanding, treatment, or prevention of disease. Clinical studies examine individuals within a selected patient population. This type of research is usually interventional, but may also be observational or preventional. In order to categorize clinical research, it is useful to look at two factors: 1) the timing of the data collection (whether the study is retrospective or prospective) and 2) the study design (e.g. case-control, cohort). 4 Study integrity is improved through randomization, blinding, and statistical analysis. Researchers often test the efficacy and safety of drugs in clinical drug studies. Many clinical trials have a pharmacological basis. In addition, clinical studies may examine surgical, physical, or psychological procedures as well as new or conventional uses for medical devices. Researchers may perform diagnostic, retrospective, or case series observational studies to diagnose, treat, and monitor patients.

Treatments, dosages, and population can be exactly specified to control or minimize internal differences aside from the treatment.

Interventional/Clinical Trials

Clinical trials are defined by phases, with the first phase (Phase I) being the introduction of a new drug in to the human population. Before Phase I, animal testing will have been undertaken. 5 Phase I is conducted to assess the safety and maximum dosage that a majority or a significant portion of patients are able to tolerate. The following list describes the key elements of each clinical trial phase . 7

• Phase I: This is the initial step in any drug development, a Phase I clinical trial includes a small number of people (usually 20-100) to determine the safety of a drug and the appropriate dosage.
• Phase II: After success at Phase I, Phase II trials include larger groups of individuals (~100-300) and work to determine both efficacy as well as potential adverse reactions.
• Phase III: At this stage, larger numbers of individuals (~300-3,000) with a specific condition are included within the trial. Trials seek to establish intervention effectiveness in treating a condition under normal use and to establish more robust safety and side effect data.
• Phase IV: Following approval for public use, Phase IV trials are undertaken to understand the long-term impact of an intervention. At this stage, the drug may also be tested on “at-risk” populations, such as the elderly, to make sure that it is safe for a broader population.

Observational

In observational studies, the researcher does not seek to control any variables. Instead, the researcher observes participants (often retrospectively) over a specified period of time. In contrast to controlled and randomized interventional studies, treatment decisions are left to the doctor and patient. Comparisons may be made between individuals given two different types of therapy or having different prognostic variables (e.g. a particular condition). Diagnostic studies evaluate the accuracy of a diagnostic test or method in predicting or identifying a specific condition. Once a number of studies have undertaken an analysis of a single variable, a secondary analysis can take place either via a meta-analysis or literature review in order to see if there is consistency across study results.

Epidemiological Research

Epidemiologists investigate the causes, distribution, and historical changes in the frequency of disease. For example, researchers have looked for trends in cancer or flu outbreaks to determine their cause and ways to prevent or reduce the spread either of these types of disease. These studies can be interventional, but are usually observational due to ethical, social, political, and health risk factors.

Interventional

• Intervention Study: These studies explore changes in health or disease outcomes after the introduction of a specific intervention. For example, the effect of adding fluoride to drinking water was studied through interventional epidemiologic studies in the United States in the 1940s. Another study undertaken in the U.S. sought to assess how a diet high in fruit and vegetables and low in red meat and processed food might impact sodium levels of individuals when compared with a traditional American diet. 6
• Cohort (Follow-up) Study: Observational studies can include many thousands of individuals and because of this, they can be time-consuming and expensive to undertake. To overcome some of these costs, researchers may choose to focus upon a particular group of people (known as a cohort) and explore the health of this group in relation to specific variables. For example, studies have sought to understand how different levels of exercise improve health outcomes.
• Case control: Particularly useful when seeking to explore rare diseases because the population with the disease has already been identified. The group of individuals identified with the disease is then compared to individuals without the disease with the purpose of exploring how the health outcomes differ between the two groups.
• Cross-sectional: Used to explore the levels of disease within a population (prevalence). Cross-sectional studies provide a snapshot of what is happening within a particular population at one period of time.
• Ecological: Tend to analyze data from previously published sources in order to explore the health of populations and the potential causes of ill health.
• Monitoring/Surveillance: Many countries record and survey populations in order to fully understand the health of their populations.
• Description with registry data: In the United States, cancer registries collect data about the numbers of cases of site-specific cancers each year. This information can then be used to explore rates of cancer at a local level to examine whether incidence and prevalence are changing over time.
• Röhrig, B., du Prel, J.-B., Wachtlin, D. & Blettner, M. Types of study in medical research: part 3 of a series on evaluation of scientific publications. Dtsch Arztebl Int 106, 262–268 (2009).
• Haidich, A. B. Meta-analysis in medical research. Hippokratia 14, 29–37 (2010).
• Ma, Q. & Lu, A. Y. H. Pharmacogenetics, pharmacogenomics, and individualized medicine. Pharmacol. Rev. 63, 437–459 (2011).
• Sessler, D. I. & Imrey, P. B. Clinical Research Methodology 1: Study Designs and Methodologic Sources of Error. Anesth. Analg. 121, 1034–1042 (2015).
• Umscheid, C. A., Margolis, D. J. & Grossman, C. E. Key concepts of clinical trials: a narrative review. Postgrad Med 123, 194–204 (2011).
• Svetkey, L. P. et al. The DASH Diet, Sodium Intake and Blood Pressure Trial (DASH-Sodium). Journal of the American Dietetic Association 99, S96–S104 (1999).
• U.S. Food & Drug Administration. The Drug Development Process.

Contributors

Vanessa Gordon-Dseugo, MPH, PhD; Grace Satterfield, MS

Published: January 17, 2019 Revised: September 2, 2020

Participating in Health Research Studies

• What is Health Research?
• Is Health Research Safe?
• Is Health Research Right for Me?

Types of Health Research

Behavioral studies.

These are studies that test how people act in different ways.

Clinical Trials

These are studies of a drug, surgery, or medical device in healthy volunteers or people who have a specific disease. See below for more information.

Community-Based Participatory Research (CBPR)

This is research that engages community partners as equal participants in the research.

Genetic Studies

These are studies to find the role of genes in different diseases.

Observational Studies

These are studies in which a group of people is observed for many years.

Physiological Studies

These are studies to better understand how the human body functions.

Prevention Studies

These are studies that test ways to prevent specific conditions or diseases.

Public Health Research

This type of research can be one or a combination of the types of research mentioned above. Public health research tries to improve the health and well-being of people from a  population-level  perspective.

More Information about Clinical Trials

Clinical trials are often done in a "randomized" way. These are sometimes called RCTs for "randomized clinical trials." In an RCT, some people will be chosen at random to receive a treatment or intervention, such as a new drug. The rest of the participants will be given a "placebo," such as a sugar pill. In other cases, when two interventions are being compared, one group will receive one of the interventions and the other group will be given a different one. Some clinical trials are also "blinded." This means that both the volunteers and the doctors do not know if people are taking the new medicine or the placebo. Only at the end of the study will this be revealed. Since people are chosen at random (similar to a coin toss) in an RCT, people who receive the treatment should be no different than those who do not. For instance, there should be an equal number of males who receive treatment compared with those who do not. This helps reduce bias due to something like gender in a study.

New drugs are first developed in research labs, and then tested in animals. Only then are clinical studies done in humans. Clinical trials of new drugs are done in different phases:

• Phase I  studies test a new drug for the first time in a small group of people (about 20-80) to see if it safe, to find the right dose, and to know the side effects.
• Phase II  studies are done in more people (about 100-300) to see how well the new drug treats a disease.
• Phase III  studies are done in large groups of people (about 1000 to 3000) to see if the new drug works well, has side effects, and how it compares to other drugs.
• Phase IV  studies are done after the treatment is approved by the U.S. Food and Drug Administration (FDA).
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Qualitative Research

Qualitative research is used to explore and understand people's beliefs, experiences, attitudes, behaviour and interactions. It generates descriptive, non-numerical data.  Qualitative research methods include:

• Documents - the study of documentary accounts of events, such as minutes of meetings
• Passive observation - the systematic watching and recording of behaviour  
• Participant observation – here, the researcher also occupies a role or part in the setting, in addition to observing
• In-depth interview - a face-to-face conversation to explore issues or topics in detail
• Focus group - method of group interview which explicitly includes and uses the group interaction to generate data.

Quantitative Research

Quantitative research is used to generate numerical data or data that can be converted into numbers. Study types that are used in the health and medical field include:  

• Case report or case series - a report on one or more individual patients.  There is no "control group" so this study type is considered to have low statistical validity
• Case control study - this studies patients with a particular outcome (cases) and control patients without the outcome. Is useful in aetiology (causation) research but prone to causation error
• Cohort study – identifies and follows two groups (cohorts) of patients, one having received the intervention being studied, and and one having not. Useful in both aetiology and prognosis research. Because the groups are not randomised, they may differ in ways other than in the variable under study
• Randomised Controlled Trial (RCT) - a clinical trial in which participants are randomly allocated to a test treatment and a control. This is considered the “gold standard” in testing the efficacy of an intervention. RCTs include methodologies - randomisation and blinding - that reduce the potential for bias and provide good evidence for cause and effect.

Mixed Methods

Please note that a research study does not have to be exclusively quantitative or qualitative. Many studies will use a combination of both types of research.

In the Dictionary of Statistics and Methodology , Mixed-Method Research is defined as:

"Inquiry that combines two or more methods. This particular term usually refers to mixing that crosses the quantitative-qualitative boundary. However, that boundary is not necessarily the most difficult one to cross. For example, mixing surveys and experiments (both quantitative methods) may require more effort for many researchers than combining surveys and focus groups (the first quantitative and the second qualitative)."

Mixed method research. (1999). In Vogt, P. W. (Ed.). Dictionary of statistics & methodology (2nd ed.).

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Home » Research – Types, Methods and Examples

Research – Types, Methods and Examples

Table of Contents

Definition:

Research refers to the process of investigating a particular topic or question in order to discover new information , develop new insights, or confirm or refute existing knowledge. It involves a systematic and rigorous approach to collecting, analyzing, and interpreting data, and requires careful planning and attention to detail.

History of Research

The history of research can be traced back to ancient times when early humans observed and experimented with the natural world around them. Over time, research evolved and became more systematic as people sought to better understand the world and solve problems.

In ancient civilizations such as those in Greece, Egypt, and China, scholars pursued knowledge through observation, experimentation, and the development of theories. They explored various fields, including medicine, astronomy, and mathematics.

During the Middle Ages, research was often conducted by religious scholars who sought to reconcile scientific discoveries with their faith. The Renaissance brought about a renewed interest in science and the scientific method, and the Enlightenment period marked a major shift towards empirical observation and experimentation as the primary means of acquiring knowledge.

The 19th and 20th centuries saw significant advancements in research, with the development of new scientific disciplines and fields such as psychology, sociology, and computer science. Advances in technology and communication also greatly facilitated research efforts.

Today, research is conducted in a wide range of fields and is a critical component of many industries, including healthcare, technology, and academia. The process of research continues to evolve as new methods and technologies emerge, but the fundamental principles of observation, experimentation, and hypothesis testing remain at its core.

Types of Research

Types of Research are as follows:

• Applied Research : This type of research aims to solve practical problems or answer specific questions, often in a real-world context.
• Basic Research : This type of research aims to increase our understanding of a phenomenon or process, often without immediate practical applications.
• Experimental Research : This type of research involves manipulating one or more variables to determine their effects on another variable, while controlling all other variables.
• Descriptive Research : This type of research aims to describe and measure phenomena or characteristics, without attempting to manipulate or control any variables.
• Correlational Research: This type of research examines the relationships between two or more variables, without manipulating any variables.
• Qualitative Research : This type of research focuses on exploring and understanding the meaning and experience of individuals or groups, often through methods such as interviews, focus groups, and observation.
• Quantitative Research : This type of research uses numerical data and statistical analysis to draw conclusions about phenomena or populations.
• Action Research: This type of research is often used in education, healthcare, and other fields, and involves collaborating with practitioners or participants to identify and solve problems in real-world settings.
• Mixed Methods Research : This type of research combines both quantitative and qualitative research methods to gain a more comprehensive understanding of a phenomenon or problem.
• Case Study Research: This type of research involves in-depth examination of a specific individual, group, or situation, often using multiple data sources.
• Longitudinal Research: This type of research follows a group of individuals over an extended period of time, often to study changes in behavior, attitudes, or health outcomes.
• Cross-Sectional Research : This type of research examines a population at a single point in time, often to study differences or similarities among individuals or groups.
• Survey Research: This type of research uses questionnaires or interviews to gather information from a sample of individuals about their attitudes, beliefs, behaviors, or experiences.
• Ethnographic Research : This type of research involves immersion in a cultural group or community to understand their way of life, beliefs, values, and practices.
• Historical Research : This type of research investigates events or phenomena from the past using primary sources, such as archival records, newspapers, and diaries.
• Content Analysis Research : This type of research involves analyzing written, spoken, or visual material to identify patterns, themes, or messages.
• Participatory Research : This type of research involves collaboration between researchers and participants throughout the research process, often to promote empowerment, social justice, or community development.
• Comparative Research: This type of research compares two or more groups or phenomena to identify similarities and differences, often across different countries or cultures.
• Exploratory Research : This type of research is used to gain a preliminary understanding of a topic or phenomenon, often in the absence of prior research or theories.
• Explanatory Research: This type of research aims to identify the causes or reasons behind a particular phenomenon, often through the testing of theories or hypotheses.
• Evaluative Research: This type of research assesses the effectiveness or impact of an intervention, program, or policy, often through the use of outcome measures.
• Simulation Research : This type of research involves creating a model or simulation of a phenomenon or process, often to predict outcomes or test theories.

Data Collection Methods

• Surveys : Surveys are used to collect data from a sample of individuals using questionnaires or interviews. Surveys can be conducted face-to-face, by phone, mail, email, or online.
• Experiments : Experiments involve manipulating one or more variables to measure their effects on another variable, while controlling for other factors. Experiments can be conducted in a laboratory or in a natural setting.
• Case studies : Case studies involve in-depth analysis of a single case, such as an individual, group, organization, or event. Case studies can use a variety of data collection methods, including interviews, observation, and document analysis.
• Observational research : Observational research involves observing and recording the behavior of individuals or groups in a natural setting. Observational research can be conducted covertly or overtly.
• Content analysis : Content analysis involves analyzing written, spoken, or visual material to identify patterns, themes, or messages. Content analysis can be used to study media, social media, or other forms of communication.
• Ethnography : Ethnography involves immersion in a cultural group or community to understand their way of life, beliefs, values, and practices. Ethnographic research can use a range of data collection methods, including observation, interviews, and document analysis.
• Secondary data analysis : Secondary data analysis involves using existing data from sources such as government agencies, research institutions, or commercial organizations. Secondary data can be used to answer research questions, without collecting new data.
• Focus groups: Focus groups involve gathering a small group of people together to discuss a topic or issue. The discussions are usually guided by a moderator who asks questions and encourages discussion.
• Interviews : Interviews involve one-on-one conversations between a researcher and a participant. Interviews can be structured, semi-structured, or unstructured, and can be conducted in person, by phone, or online.
• Document analysis : Document analysis involves collecting and analyzing written documents, such as reports, memos, and emails. Document analysis can be used to study organizational communication, policy documents, and other forms of written material.

Data Analysis Methods

Data Analysis Methods in Research are as follows:

• Descriptive statistics : Descriptive statistics involve summarizing and describing the characteristics of a dataset, such as mean, median, mode, standard deviation, and frequency distributions.
• Inferential statistics: Inferential statistics involve making inferences or predictions about a population based on a sample of data, using methods such as hypothesis testing, confidence intervals, and regression analysis.
• Qualitative analysis: Qualitative analysis involves analyzing non-numerical data, such as text, images, or audio, to identify patterns, themes, or meanings. Qualitative analysis can be used to study subjective experiences, social norms, and cultural practices.
• Content analysis: Content analysis involves analyzing written, spoken, or visual material to identify patterns, themes, or messages. Content analysis can be used to study media, social media, or other forms of communication.
• Grounded theory: Grounded theory involves developing a theory or model based on empirical data, using methods such as constant comparison, memo writing, and theoretical sampling.
• Discourse analysis : Discourse analysis involves analyzing language use, including the structure, function, and meaning of words and phrases, to understand how language reflects and shapes social relationships and power dynamics.
• Network analysis: Network analysis involves analyzing the structure and dynamics of social networks, including the relationships between individuals and groups, to understand social processes and outcomes.

Research Methodology

Research methodology refers to the overall approach and strategy used to conduct a research study. It involves the systematic planning, design, and execution of research to answer specific research questions or test hypotheses. The main components of research methodology include:

• Research design : Research design refers to the overall plan and structure of the study, including the type of study (e.g., observational, experimental), the sampling strategy, and the data collection and analysis methods.
• Sampling strategy: Sampling strategy refers to the method used to select a representative sample of participants or units from the population of interest. The choice of sampling strategy will depend on the research question and the nature of the population being studied.
• Data collection methods : Data collection methods refer to the techniques used to collect data from study participants or sources, such as surveys, interviews, observations, or secondary data sources.
• Data analysis methods: Data analysis methods refer to the techniques used to analyze and interpret the data collected in the study, such as descriptive statistics, inferential statistics, qualitative analysis, or content analysis.
• Ethical considerations: Ethical considerations refer to the principles and guidelines that govern the treatment of human participants or the use of sensitive data in the research study.
• Validity and reliability : Validity and reliability refer to the extent to which the study measures what it is intended to measure and the degree to which the study produces consistent and accurate results.

Applications of Research

Research has a wide range of applications across various fields and industries. Some of the key applications of research include:

• Advancing scientific knowledge : Research plays a critical role in advancing our understanding of the world around us. Through research, scientists are able to discover new knowledge, uncover patterns and relationships, and develop new theories and models.
• Improving healthcare: Research is instrumental in advancing medical knowledge and developing new treatments and therapies. Clinical trials and studies help to identify the effectiveness and safety of new drugs and medical devices, while basic research helps to uncover the underlying causes of diseases and conditions.
• Enhancing education: Research helps to improve the quality of education by identifying effective teaching methods, developing new educational tools and technologies, and assessing the impact of various educational interventions.
• Driving innovation: Research is a key driver of innovation, helping to develop new products, services, and technologies. By conducting research, businesses and organizations can identify new market opportunities, gain a competitive advantage, and improve their operations.
• Informing public policy : Research plays an important role in informing public policy decisions. Policy makers rely on research to develop evidence-based policies that address societal challenges, such as healthcare, education, and environmental issues.
• Understanding human behavior : Research helps us to better understand human behavior, including social, cognitive, and emotional processes. This understanding can be applied in a variety of settings, such as marketing, organizational management, and public policy.

Importance of Research

Research plays a crucial role in advancing human knowledge and understanding in various fields of study. It is the foundation upon which new discoveries, innovations, and technologies are built. Here are some of the key reasons why research is essential:

• Advancing knowledge: Research helps to expand our understanding of the world around us, including the natural world, social structures, and human behavior.
• Problem-solving: Research can help to identify problems, develop solutions, and assess the effectiveness of interventions in various fields, including medicine, engineering, and social sciences.
• Innovation : Research is the driving force behind the development of new technologies, products, and processes. It helps to identify new possibilities and opportunities for improvement.
• Evidence-based decision making: Research provides the evidence needed to make informed decisions in various fields, including policy making, business, and healthcare.
• Education and training : Research provides the foundation for education and training in various fields, helping to prepare individuals for careers and advancing their knowledge.
• Economic growth: Research can drive economic growth by facilitating the development of new technologies and innovations, creating new markets and job opportunities.

When to use Research

Research is typically used when seeking to answer questions or solve problems that require a systematic approach to gathering and analyzing information. Here are some examples of when research may be appropriate:

• To explore a new area of knowledge : Research can be used to investigate a new area of knowledge and gain a better understanding of a topic.
• To identify problems and find solutions: Research can be used to identify problems and develop solutions to address them.
• To evaluate the effectiveness of programs or interventions : Research can be used to evaluate the effectiveness of programs or interventions in various fields, such as healthcare, education, and social services.
• To inform policy decisions: Research can be used to provide evidence to inform policy decisions in areas such as economics, politics, and environmental issues.
• To develop new products or technologies : Research can be used to develop new products or technologies and improve existing ones.
• To understand human behavior : Research can be used to better understand human behavior and social structures, such as in psychology, sociology, and anthropology.

Characteristics of Research

The following are some of the characteristics of research:

• Purpose : Research is conducted to address a specific problem or question and to generate new knowledge or insights.
• Systematic : Research is conducted in a systematic and organized manner, following a set of procedures and guidelines.
• Empirical : Research is based on evidence and data, rather than personal opinion or intuition.
• Objective: Research is conducted with an objective and impartial perspective, avoiding biases and personal beliefs.
• Rigorous : Research involves a rigorous and critical examination of the evidence and data, using reliable and valid methods of data collection and analysis.
• Logical : Research is based on logical and rational thinking, following a well-defined and logical structure.
• Generalizable : Research findings are often generalized to broader populations or contexts, based on a representative sample of the population.
• Replicable : Research is conducted in a way that allows others to replicate the study and obtain similar results.
• Ethical : Research is conducted in an ethical manner, following established ethical guidelines and principles, to ensure the protection of participants’ rights and well-being.
• Cumulative : Research builds on previous studies and contributes to the overall body of knowledge in a particular field.

Advantages of Research

Research has several advantages, including:

• Generates new knowledge: Research is conducted to generate new knowledge and understanding of a particular topic or phenomenon, which can be used to inform policy, practice, and decision-making.
• Provides evidence-based solutions : Research provides evidence-based solutions to problems and issues, which can be used to develop effective interventions and strategies.
• Improves quality : Research can improve the quality of products, services, and programs by identifying areas for improvement and developing solutions to address them.
• Enhances credibility : Research enhances the credibility of an organization or individual by providing evidence to support claims and assertions.
• Enables innovation: Research can lead to innovation by identifying new ideas, approaches, and technologies.
• Informs decision-making : Research provides information that can inform decision-making, helping individuals and organizations make more informed and effective choices.
• Facilitates progress: Research can facilitate progress by identifying challenges and opportunities and developing solutions to address them.
• Enhances understanding: Research can enhance understanding of complex issues and phenomena, helping individuals and organizations navigate challenges and opportunities more effectively.
• Promotes accountability : Research promotes accountability by providing a basis for evaluating the effectiveness of policies, programs, and interventions.
• Fosters collaboration: Research can foster collaboration by bringing together individuals and organizations with diverse perspectives and expertise to address complex issues and problems.

Limitations of Research

Some Limitations of Research are as follows:

• Cost : Research can be expensive, particularly when large-scale studies are required. This can limit the number of studies that can be conducted and the amount of data that can be collected.
• Time : Research can be time-consuming, particularly when longitudinal studies are required. This can limit the speed at which research findings can be generated and disseminated.
• Sample size: The size of the sample used in research can limit the generalizability of the findings to larger populations.
• Bias : Research can be affected by bias, both in the design and implementation of the study, as well as in the analysis and interpretation of the data.
• Ethics : Research can present ethical challenges, particularly when human or animal subjects are involved. This can limit the types of research that can be conducted and the methods that can be used.
• Data quality: The quality of the data collected in research can be affected by a range of factors, including the reliability and validity of the measures used, as well as the accuracy of the data entry and analysis.
• Subjectivity : Research can be subjective, particularly when qualitative methods are used. This can limit the objectivity and reliability of the findings.
• Accessibility : Research findings may not be accessible to all stakeholders, particularly those who are not part of the academic or research community.
• Interpretation : Research findings can be open to interpretation, particularly when the data is complex or contradictory. This can limit the ability of researchers to draw firm conclusions.
• Unforeseen events : Unexpected events, such as changes in the environment or the emergence of new technologies, can limit the relevance and applicability of research findings.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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COLUMBIA UNIVERSITY IN THE CITY OF NEW YORK

Chief Admin Research Officer

• Columbia University Medical Center
• Opening on: Aug 20 2024
• Job Type: Officer of Administration
• Regular/Temporary: Regular
• Hours Per Week: 35
• Salary Range: $240,000 - $280,000

Position Summary

The Department of Medicine (DoM) is seeking a Chief Administrative Research Officer (CARO) to lead the development of a high-quality and successful research enterprise. As a senior executive, the CARO oversees and supports the administration of DoM’s research portfolio, aligning with the department’s business plan to create effective technical solution teams (i.e., pre- and post-award cores). This role involves designing and implementing programs, methods, tools, platforms, practices, and other activities to support the department’s research enterprise and engaging with university administrators, faculty researchers, and collaborative partners in basic, applied, and advanced research.

Reporting to the Department Administrator/COO, the CARO will lead the Research Administration team and be financially responsible for the department’s overall research portfolio. The CARO will collaborate closely with departmental and division leadership, the grants management team, principal investigators, and other University and external stakeholders to ensure compliance with Department of Medicine, Columbia University, Federal, and sponsor-specific requirements.

Responsibilities

• Develop and execute a research strategy that aligns with the Department’s strategic plan.
• Create and implement an action plan for enhancing research-related processes, workflows, and infrastructure to build technically capable and competitive teams for research funding and compliance.
• Serve as a catalyst for change in research administration and compliance activities.
• Oversee the financial performance of the Department’s research portfolio, ensuring full recovery of indirect costs and maximizing direct cost spend.
• Monitor and report on the Department’s sponsored research portfolio, including overall and categorical grant support, unfunded and over-the-cap salary, and the number and types of awards.
• Work with Division and Finance teams to monitor department-funded research, including start-up and retention packages.
• Partner with departmental directors, especially the Director of Budget and Finance, to achieve departmental goals.
• Manage a staff of grants management professionals, ensuring their development, training, and performance.
• Collaborate with Division Administrators to supervise staff and with Human Resources for recruitment.
• Develop project-specific and summary financial reports for the team.
• Manage and monitor the Research Administration budget.
• Provide leadership and expertise in sponsored research management.
• Foster a collegial atmosphere that supports the recruitment, retention, and development of a diverse and inclusive team, developing succession plans for future leaders.
• Engage in the preparation of atypical grant proposals (e.g., program project grants, cooperative agreements).
• Lead the development of new research initiatives and training programs.
• Resolve contractual issues and disputes.
• Serve on the Department’s research committee and the Innovation Nucleation Fund (INF) committee, administering the INF program.
• Act as a subject matter expert in sponsored projects administration, including research compliance, procurement, financial reporting, sub-award monitoring, and program-related audit functions.
• Provide guidance on purchasing policies, compliance matters, and best practices to Principal Investigators and project key personnel.
• Ensure compliance with all rules and regulations and keep relevant staff informed of updates.
• Maintain and develop relationships with University offices, departments, and external agencies.
• Serve as the primary contact for University offices and external funding agencies regarding research administration.
• Perform other duties and projects as assigned.

Minimum Qualifications

• Requires bachelor’s degree or equivalent in education and experience, plus six years of related experience.
• Master’s degree would substitute in part for experience
• Exceptional written, oral, and interpersonal skills with success in strategic and operational messaging.
• Ability to work collaboratively, manage multiple priorities and projects effectively.
• Experience in research, program or project administration, and collaborative work.
• Ability to work under tight deadlines, be self-reliant, a problem solver, results-oriented, and capable of making decisions in a dynamic environment while anticipating future needs.
• Strong negotiation and problem-solving skills.
• Ability to develop strong working relationships with multiple constituencies and foster a culture of collaboration.
• Commitment to diversity, equity, and inclusion (DEI), demonstrating cultural awareness and promoting DEI efforts.
• Proven track record in driving results and business and financial management, including budget management, outcome measurement, and improvement.
• Ability to create a people-first culture that values teamwork and recognizes the importance of individuals to the organization.

Preferred Qualifications

• Leadership experience with 5-10 years in program/academic leadership, financial, administrative, and sponsored projects management in an academic medical center.
• Knowledge of Federal grants portals (e.g., NSF Fastlane, Research.gov, Grants.gov Workspace, eRA Commons ASSIST).
• Educational or practical experience in biological science or a related field.
• Experience in managing a team and working collaboratively with peers.
• Knowledge of CUMC systems and research regulations (federal, state, local), NIH, and other sponsors.

Other Requirements

Successful completion of applicable compliance and systems training requirements.

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What are some new research projects in the field of ‘smart’ insulin? | Explained Premium

The research will be conducted at universities in the united states, australia, and china. .

Published - August 21, 2024 11:34 am IST

Image used for representation only. | Photo Credit: Tanvi Manhas/Chennai

The story so far: The Type 1 Diabetes Grand Challenge, a partnership between the Steve Morgan Foundation, Diabetes UK and JDRF, on Monday, August 12, 2024, announced grants of over £2.7 million for new research in the development of next-generation insulins to manage type 1 diabetes. The funding will accelerate research of insulins that imitate how healthy pancreas work, the initiative said.

What is type 1 diabetes?

Type 1 diabetes is a chronic condition characterised by deficient insulin production and requires frequent insulin administration, mostly daily or sometimes even multiple times a day. Without insulin, glucose continues to build up in the bloodstream, causing high blood sugar levels. The insulin hormone helps regulate blood sugar by allowing glucose to enter cells to be used up for manufacturing energy.

More about the grants

The funding will be provided to six new international research projects focused on developing the next-generation, or novel, insulins. The research will be conducted at universities in the United States, Australia, and China.

“The funded six new research projects address major shortcomings in insulin therapy. Potentially minimising the risk of hypoglycaemia through an insulin-glucagon combination would ease one of the major concerns associated with insulin therapy today. Therefore, these research projects, if successful might do no less than heralding a new era in insulin therapy,” Tim Heise, Vice Chair of Novel Insulins Scientific Advisory Panel of the Type 1 Diabetes Grand Challenge, said.

According to the Type 1 Diabetes Grand Challenge, four of the newly-funded projects are related to glucose responsive insulins (GRIs), which can respond to changing blood glucose levels.

GRIs activate only when there is a certain amount of glucose in the bloodstream and become inactive when it drops below a stipulated point. This is expected to prevent both hyperglycaemia (high blood glucose) and hypoglycaemia (low blood glucose).

Another research project focuses on developing a short-acting insulin. Among the currently available insulins, there is a delay between the administration of the drug and its action on blood glucose – even with the fastest acting variants. This can cause a spike in blood glucose levels before insulin can lower it, thus endangering the person.

The last funded project focuses on combining insulin with glucagon.

Also read: ‘Insulin’ homoeopathic tablets under CDSCO lens

Glucagon is also secreted by pancreas, and it increases blood sugar levels to prevent it from dropping below a critical level. The project relies on the concept that having both insulin and glucagon in one formulation can stabilise blood sugar levels.

GRI projects

The four GRI projects are being researched at Monash University, Australia, Wayne State University, U.S., Jinhua Institute of Zhejiang University in China, and University of Notre Dame, U.S.

The Monash University project involves development of a second generation of nano sugar-insulin system, based on advanced nanotechnology. In the first-generation experiment of this insulin delivery system, insulin and a glucose-sensing molecule in tiny particles called nano sugars are injected under the skin. These nano sugars react to very small changes in blood glucose and release insulin only when glucose levels are outside a range, without any intervention from the patient. The aim of this experiment is to reduce the number of times people with type 1 have to inject insulin.

Researchers at the Wayne University are working to develop a “smart insulin” which can detect changes in blood glucose levels and respond by releasing the right amount of insulin at the right time. Chemical engineer Zhiqiang Cao’s team plans to develop a smarter insulin which is “more” sensitive to changing glucose levels, because some novel insulins are not as powerful as the currently available ones, resulting in higher doses to obtain a similar impact on blood glucose levels.

The third project, conducted by researchers at the Jinhua Institute of Zhejiang University in China, involves novel insulins that respond immediately to rising blood glucose levels. This novel insulin forms a reservoir of insulin under the skin once it is injected, and can therefore be used either daily or weekly. The experiment uses an insulin/polymer complex as the starting point and adds a safe glucose-sensing molecule to it. In the project, the team will improve the GRI and ensure all components work together effectively. The next step will be to make sure the GRI releases insulin properly from the reservoir, especially when blood glucose levels are high.

Researchers at the University of Notre Dame, U.S, developed a smart insulin delivery system that uses tiny particles called nanocomplexes, which contain insulin. These nanocomplexes can also be injected under the skin to create a reservoir to automatically release insulin if blood sugar rises. The project will be developed further and tested in pigs exposed to relevant real-life scenarios.

Ultrafast insulin

Scientists at the Stanford University, U.S. are working on developing and testing an ultrafast-acting insulin that’s only active when needed and could reduce the risk of blood glucose highs and lows in people with type 1 diabetes.

The current fast-acting insulins are a group of six molecules which need to be separated to form single insulin molecules to regulate blood sugar. Sometimes, even these single molecules cluster into pairs, hindering the blood sugar regulation. The new research will focus on designing an insulin molecule that doesn’t cluster so that it acts in the bloodstream quickly. The design is based on insulin molecules found in the venom from the cone snail, a type of underwater snail that uses insulin as a weapon.

Insulin + glucagon

A team of researchers at the Indiana University, U.S. will combine insulin and glucagon in their project, to prevent the highs and lows in blood glucose. The molecules has been tested in rats with type 1 diabetes and found that it can reduce the risk of hypoglycemia both at mealtimes and throughout the day. The experiment will also test the stability of the molecule and explore different ways to manufacture it.

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Drugmaker says weight-loss drug reduced Type 2 diabetes risk by 94%

Eli Lilly, maker of the weight-loss drug Zepbound, released new data indicating that weekly injections of the drug reduced the risk of progression to Type 2 diabetes by 94% among adults with prediabetes and obesity, or who were overweight, compared to a placebo.

The data comes as new research found a nearly 19% increase in cases of Type 2 diabetes in the U.S. between 2012 and 2022.

Additionally, patients who had a weekly injection of 15 milligrams of the tirzepatide-based drug had an average reduction of 22.9% of their body weight. Those on a placebo lost about 2.1% of their body weight.

The findings come after over three years of study by the drug manufacturer. Previously, 72-week findings were published in the New England Journal of Medicine in 2022.

"Obesity is a chronic disease that puts nearly 900 million adults worldwide at an increased risk of other complications such as type 2 diabetes," said Dr. Jeff Emmick, senior vice president of product development at Eli Lilly. "Tirzepatide reduced the risk of developing type 2 diabetes by 94% and resulted in sustained weight loss over the three-year treatment period. These data reinforce the potential clinical benefits of long-term therapy for people living with obesity and pre-diabetes."

RELATED STORY | Amid rise in childhood diabetes, man describes how to 'thrive' with disease

Dr. Jayne Morgan, president of medical affairs at Hello Heart, said the new data was "very significant."

"They really were looking at whether or not they could prevent people from transitioning or progressing from prediabetes, meaning you don't yet have diabetes but your glucose or sugar levels are higher than normal but they don't meet the criteria for diabetes. So how do we prevent these people from progressing to diabetes?" she said. "They gave 1,032 people this medication over a period of three years and they were able to prevent the progression of diabetes by 94% in this group of people."

Eli Lilly acknowledged that a 17-week off-treatment follow-up showed that some participants had developed diabetes and gained some, but not all, of their weight back after stopping the injections. Morgan suggested that in order to reap the benefits of this medication, a person might need to remain on the drug indefinitely.

"As we continue next-gen medications moving towards perhaps oral formulations or pills, moving away from these injections, we are hopeful that perhaps we can see some of that ground be regained, but currently these would be lifetime maintenance medications just like taking insulin or taking your blood pressure medication, something that would be maintained for life," she said.

RELATED STORY | New research finds nearly 19% increase in cases of Type 2 diabetes over a decade

Eli Lilly says that Zepbound uses hormone receptors to help people who are considered obese or overweight lose weight and keep it off.

However, these weight-loss drugs do have side effects. Eli Lilly noted that Zepbound can potentially cause numerous adverse gastrointestinal reactions.

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Red and processed meat consumption associated with higher type 2 diabetes risk

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Meat consumption, particularly consumption of processed meat and unprocessed red meat, is associated with a higher type 2 diabetes risk, an analysis of data from almost two million participants has found.

Our research supports recommendations to limit the consumption of processed meat and unprocessed red meat to reduce type 2 diabetes cases in the population Nita Forouhi

The findings are published today in The Lancet Diabetes and Endocrinology .

Global meat production has increased rapidly in recent decades and meat consumption exceeds dietary guidelines in many countries.  Earlier research indicated that higher intakes of processed meat and unprocessed red meat are associated with an elevated risk of type 2 diabetes, but the results have been variable and not conclusive.

Poultry such as chicken, turkey, or duck is often considered to be an alternative to processed meat or unprocessed red meat, but fewer studies have examined the association between poultry consumption and type 2 diabetes.

To determine the association between consumption of processed meat, unprocessed red meat and poultry and type 2 diabetes, a team led by researchers at the University of Cambridge used the global InterConnect project to analyse data from 31 study cohorts in 20 countries. Their extensive analysis took into account factors such as age, gender, health-related behaviours, energy intake and body mass index.

The researchers found that the habitual consumption of 50 grams of processed meat a day - equivalent to 2 slices of ham - is associated with a 15% higher risk of developing type 2 diabetes in the next 10 years. The consumption of 100 grams of unprocessed red meat a day - equivalent to a small steak - was associated with a 10% higher risk of type 2 diabetes.

Habitual consumption of 100 grams of poultry a day was associated with an 8% higher risk, but when further analyses were conducted to test the findings under different scenarios the association for poultry consumption became weaker, whereas the associations with type 2 diabetes for each of processed meat and unprocessed meat persisted.

Professor Nita Forouhi of the Medical Research Council (MRC) Epidemiology Unit at the University of Cambridge, and a senior author on the paper, said: “Our research provides the most comprehensive evidence to date of an association between eating processed meat and unprocessed red meat and a higher future risk of type 2 diabetes. It supports recommendations to limit the consumption of processed meat and unprocessed red meat to reduce type 2 diabetes cases in the population.

“While our findings provide more comprehensive evidence on the association between poultry consumption and type 2 diabetes than was previously available, the link remains uncertain and needs to be investigated further.”

InterConnect uses an approach that allows researchers to analyse individual participant data from diverse studies, rather than being limited to published results. This enabled the authors to include as many as 31 studies in this analysis, 18 of which had not previously published findings on the link between meat consumption and type 2 diabetes. By including this previously unpublished study data the authors considerably expanded the evidence base and reduced the potential for bias from the exclusion of existing research.

Lead author Dr Chunxiao Li, also of the MRC Epidemiology Unit, said: “Previous meta-analysis involved pooling together of already published results from studies on the link between meat consumption and type 2 diabetes, but our analysis examined data from individual participants in each study. This meant that we could harmonise the key data collected across studies, such as the meat intake information and the development of type 2 diabetes.

“Using harmonised data also meant we could more easily account for different factors, such as lifestyle or health behaviours, that may affect the association between meat consumption and diabetes.”

Professor Nick Wareham, Director of the MRC Epidemiology Unit, and a senior author on the paper said: “InterConnect enables us to study the risk factors for obesity and type 2 diabetes across populations in many different countries and continents around the world, helping to include populations that are under-represented in traditional meta-analyses.

“Most research studies on meat and type 2 diabetes have been conducted in USA and Europe, with some in East Asia. This research included additional studies from the Middle East, Latin America and South Asia, and highlighted the need for investment in research in these regions and in Africa.”

InterConnect was initially funded by the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no 602068.

Reference Li, C et al. Meat consumption and incident type 2 diabetes: a federated meta-analysis of 1·97 million adults with 100,000 incident cases from 31 cohorts in 20 countries. Lancet Diabetes Endocrinol.; 20 August 2024

Adapted form a press release from the MRC Epidemiology Unit

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Methodology for clinical research

Aysha karim kiani.

1 Allama Iqbal Open University, Islamabad, Pakistan

2 MAGI EUREGIO, Bolzano, Italy

ZAKIRA NAUREEN

3 Department of Biological Sciences and chemistry, University of Nizwa, Oman

DEREK PHEBY

4 Society and Health, Buckinghamshire New University, High Wycombe, UK

GARY HENEHAN

5 School of Food Science and Environmental Health, Technological University of Dublin, Dublin, Ireland

RICHARD BROWN

6 Department of Psychology and Neuroscience, Dalhousie University, Halifax, Nova Scotia, Canada

PAUL SIEVING

7 Department of Ophthalmology, Center for Ocular Regenerative Therapy, School of Medicine, University of California at Davis, Sacramento, CA, USA

PETER SYKORA

8 Department of Philosophy and Applied Philosophy, University of St. Cyril and Methodius, Trnava, Slovakia

ROBERT MARKS

9 Department of Biotechnology Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel

BENEDETTO FALSINI

10 Institute of Ophthalmology, Università Cattolica del Sacro Cuore, Fondazione Policlinico Universitario A. Gemelli-IRCCS, Rome, Italy

NATALE CAPODICASA

11 MAGI BALKANS, Tirana, Albania

STANISLAV MIERTUS

12 Department of Biotechnology, University of SS. Cyril and Methodius, Trnava, Slovakia

13 International Centre for Applied Research and Sustainable Technology, Bratislava, Slovakia

LORENZO LORUSSO

14 UOC Neurology and Stroke Unit, ASST Lecco, Merate, Italy

DANIELE DONDOSSOLA

15 Center for Preclincal Research and General and Liver Transplant Surgery Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy

16 Department of Pathophysiology and Transplantation, Università degli Studi di Milano, Milan, Italy

GIANLUCA MARTINO TARTAGLIA

17 Department of Biomedical, Surgical and Dental Sciences, University of Milan, Milan, Italy

18 UOC Maxillo-Facial Surgery and Dentistry, Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, Milan, Italy

MAHMUT CERKEZ ERGOREN

19 Department of Medical Genetics, Faculty of Medicine, Near East University, Nicosia, Cyprus

MUNIS DUNDAR

20 Department of Medical Genetics, Erciyes University Medical Faculty, Kayseri, Turkey

SANDRO MICHELINI

21 Vascular Diagnostics and Rehabilitation Service, Marino Hospital, ASL Roma 6, Marino, Italy

DANIELE MALACARNE

22 MAGI’S LAB, Rovereto (TN), Italy

GABRIELE BONETTI

Kevin donato, maria chiara medori, tommaso beccari.

23 Department of Pharmaceutical Sciences, University of Perugia, Perugia, Italy

MICHELE SAMAJA

24 MAGI GROUP, San Felice del Benaco (BS), Italy

STEPHEN THADDEUS CONNELLY

25 San Francisco Veterans Affairs Health Care System, Department of Oral & Maxillofacial Surgery, University of California, San Francisco, CA, USA

DONALD MARTIN

26 Univ. Grenoble Alpes, CNRS, Grenoble INP, TIMC-IMAG, SyNaBi, Grenoble, France

ASSUNTA MORRESI

27 Department of Chemistry, Biology and Biotechnology, University of Perugia, Perugia, Italy

ARIOLA BACU

28 Department of Biotechnology, University of Tirana, Tirana, Albania

KAREN L. HERBST

29 Total Lipedema Care, Beverly Hills California and Tucson Arizona, USA

MYKHAYLO KAPUSTIN

30 Federation of the Jewish Communities of Slovakia

LIBORIO STUPPIA

31 Department of Psychological, Health and Territorial Sciences, School of Medicine and Health Sciences, University "G. d'Annunzio", Chieti, Italy

LUDOVICA LUMER

32 Department of Anatomy and Developmental Biology, University College London, London, UK

GIAMPIETRO FARRONATO

Matteo bertelli.

33 MAGISNAT, Peachtree Corners (GA), USA

A clinical research requires a systematic approach with diligent planning, execution and sampling in order to obtain reliable and validated results, as well as an understanding of each research methodology is essential for researchers. Indeed, selecting an inappropriate study type, an error that cannot be corrected after the beginning of a study, results in flawed methodology. The results of clinical research studies enhance the repertoire of knowledge regarding a disease pathogenicity, an existing or newly discovered medication, surgical or diagnostic procedure or medical device. Medical research can be divided into primary and secondary research, where primary research involves conducting studies and collecting raw data, which is then analysed and evaluated in secondary research. The successful deployment of clinical research methodology depends upon several factors. These include the type of study, the objectives, the population, study design, methodology/techniques and the sampling and statistical procedures used. Among the different types of clinical studies, we can recognize descriptive or analytical studies, which can be further categorized in observational and experimental. Finally, also pre-clinical studies are of outmost importance, representing the steppingstone of clinical trials. It is therefore important to understand the types of method for clinical research. Thus, this review focused on various aspects of the methodology and describes the crucial steps of the conceptual and executive stages.

How to cite this article: Kiani AK, Naureen Z, Pheby D, Henehan G, Brown R, Sieving P, Sykora P, Marks R, Falsini B, Capodicasa N, Miertus S, Lorusso L, Dondossola D, Tartaglia GM, Ergoren MC, Dundar M, Michelini S, Malacarne D, Bonetti G, Donato K, Medori MC, Beccari T, Samaja M, Connelly ST, Martin D, Morresi A, Bacu A, Herbst KL, Kapustin M, Stuppia L, Lumer L, Farronato G, Bertelli M. Methodology for clinical research. J Prev Med Hyg 2022;63(suppl.3):E267-E278. https://doi.org/10.15167/2421-4248/jpmh2022.63.2S3.30

Introduction

According to epistemologists, who study the nature, origin and scope of knowledge, epistemic justification, the rationality of belief and related issues [ 1 ], there are six ways to obtain knowledge:

• authoritarianism;
• rationalism and empiricism;
• pragmatism;
• scepticism.

Rationalism and empiricism, pragmatism and scepticism may be within the scope of the scientific method, whereas authoritarianism and mysticism are clearly pseudoscience or anti-science [ 2 ]. Science is characterized by systematic observation and experimentation, inductive and deductive reasoning, and the formation and testing of hypotheses and theories. The details of how these are carried out can vary greatly, but these characteristics are sufficient to distinguish scientific activity from non-science [ 3-8 ]

The choice and selection of a particular methodology depends on factors such as the hypothesis to investigate, the research question or statement of the problem, the objectives, the nature of the study, the study population and controls, intervention and variables [ 9-12 ]. The reliability and validity of the results therefore depend on an overall study design having well-defined objectives, reproducible methodology, diligent data collection and analysis to minimise errors and bias, and efficient reporting of the findings [ 9 , 12 ]. Selecting an appropriate methodology is therefore essential to obtain valid results, and an understanding of research methodology is essential for researchers.

Medical research can be broadly categorised into primary and secondary research. Primary research involves conducting studies and collecting raw data that is then analysed and evaluated in secondary research [ 13 ]. Primary research can be further classified into three types as shown in Figure 1 : basic or laboratory studies, also known as preclinical studies, clinical research, and epidemiological research. Both clinical and epidemiological research involve observational and experimental methods. Clinical research investigates the effects of specific interventions on individuals, while epidemiological research studies the causes and distribution of disease or mortality in human populations, especially the effects of exposure to single or multiple environmental agents [ 14 ]. Similar in essence, clinical research methods differ somewhat, depending on the type of study. Type is an integral element of study design and depends on the research question to answer. It should be specified before the start of any study [ 15 ]. Selecting an inappropriate study type results in flawed methodology, and if it occurs after commencement of the study, it is an error that cannot corrected.

Types of primary medical research.

Stages of clinical research

A clinical research project consists broadly of two stages: planning and action [ 16 ].

PLANNING STAGE

The planning stage consists of all the preliminary paperwork and search of the literature done before starting actual research. It includes identifying the problem, reviewing the literature, developing a research question, formulating a hypothesis, determining the type of study, selecting a study design, identifying the target/study population, and seeking informed consent to participation. It also includes establishing collaborations with experts and determining the overall feasibility of the proposed work [ 9 , 16 ].

Before beginning the scientific investigation, the researchers should decide the data collection strategy, sampling techniques and statistical analysis. After choosing a working hypothesis and reformulating it as null and alternative hypotheses, the next step is to decide the type of study required to answer the research question and an appropriate method to implement it.

ACTION STAGE

This stage includes the actionable research, implementation of the method in coherence with the theoretical concept, randomisation, blinding, application of sampling techniques, data collection and statistical analysis [ 10 , 11 ].

Classification of clinical research

Depending on the study design, clinical research can in principle be categorised as either quantitative or qualitative [ 9 ]. Further classification of clinical research methods may be based on data collection techniques and the direction of causality being investigated, as illustrated for example by time relationships. Clinical research can be classified as either descriptive or analytical, as illustrated in Figure 2 [ 9 , 12 , 17-20 ].

Classification of clinical research.

DESCRIPTIVE RESEARCH

Descriptive studies record and report unusual or new events, e.g. the prevalence of a disease or syndrome in a family, and correlate the events with possible explanations. This type of research is neither randomized nor pre-designed, and is presented as a case report, case series or surveillance study.

Case Reports

These are reports of individual patients with particular clinical characteristics. Such reports present baseline characteristics recorded and evaluated for single patients, compared with population values. Sometimes these studies may consist of observations recorded for administration of a certain treatment to an individual. They are essentially hypothesis generating, opening the way for more rigorous studies of an experimental nature [ 12 ].

Case series

Case series may include examination of successive clinical cases having common characteristics. They may, for example, present observations from patients exposed to a particular drug or group of drugs at regular intervals, and may include former histories of patients having similar outcomes, to detect possible cause-effect relationships.

Surveillance studies

This type of study involves continuous monitoring of disease occurrence in a population. Information related to a health problem of interest is collected in databases, analysed over a time period and inferences are made based on observed correlations.

ANALYTICAL/EXPLANATORY STUDIES

The most significant difference between descriptive and analytical studies is the presence in the latter of control groups that enable comparative evaluations to be made. Analytical clinical studies can be further classified into experimental (intervention) studies and observational (non-intervention) studies.

Observational studies

Observational studies are non-intervention studies in which patients are prescribed a specified therapy based on diagnosis and therapeutic need. They include therapeutic, prognostic, observational drug studies, secondary data analyses, case series and single case reports, and may be retrospective, prospective or ambidirectional [ 21 ]. In non-intervention studies, “knowledge from the treatment of persons with drugs in accordance with the instructions for use specified in their registration is analysed using epidemiological methods” [ 21 ]. “Diagnosis, treatment and monitoring are not performed according to a previously specified study protocol, but exclusively according to medical practice” [ 21 ].

Observational studies involve collecting data pertaining to study participants in their natural or real-world environments. They are usually diagnostic and prognostic studies, with a cross-sectional approach to data collection. The comparative-effectiveness study is the hallmark of non-experimental research [ 22 ], and involves comparison of comparable groups to interpret outcome effects. Such studies are also known as benchmarking-controlled trials because of the element of peer comparison [ 22 ].

Observational studies can be broadly categorised into individual and aggregate studies.

Aggregate observation studies

Individual level data aggregated by geographic area, year or any other parameter is termed aggregate data. Aggregate studies are conducted to record observations on pandemics and epidemics of communicable diseases and their treatment regimens, for example aggregate data on COVID-19 in a particular country, or the occurrence and effective treatment of malaria and its relapse in a particular geographical area. Data pertaining to non-communicable diseases is also aggregated in the same way to generate insights into the distribution of diseases in specified populations, as for example in cancer registries [ 23 , 24 ].

Individual observation studies

Individual studies are based on disaggregated individual results and involve analysis to estimate differences between subgroups. In individual observational studies, subjects are observed individually and then gathered in groups based on outcomes or exposures or both. Based on grouping criteria, individual observational studies may take the form of case-control, cohort or cross-sectional studies.

Individual observational studies that involve grouping of subjects based on selected outcomes are termed case-control studies. In these studies, the exposure experience of the case group (subjects with the outcome of interest) is compared with that of the control group (subjects without the outcome), for instance occurrence or non-occurrence of renal failure in diabetic patients or heart attacks in hypertensive patients. The design of such studies is retrospective and evaluates possible associations between exposures and outcome. They are quick and inexpensive to perform, and the results are expressed as odds ratios (OR) and risk ratio/relative risk. Case control studies enable multiple exposure variables to be examined for a given outcome, but they do not allow correlation of sequential causes and effects with the outcome [ 12 ].

In this type of study subjects are grouped based on exposure. Cohort studies enable multiple outcomes to be studied for a given exposure. The exposure is well-defined, but the outcome may vary, thus providing an opportunity to monitor many outcomes of a single exposure [ 12 ]. Cohort studies can be retrospective, where the cohorts are defined on the basis of a past exposure, or prospective, where the cohorts are defined by a current exposure.

In retrospective cohort observational studies, the researchers look back in time at archived or self-reported data in order to compare outcomes in exposed and non-exposed patients. The two groups are identified retrospectively and studied prospectively. This type of study is quick and inexpensive [ 25 , 26 ], but is prone to recall-bias [ 27 ].

A prospective cohort study is a longitudinal cohort study in which cohorts differing in exposure to the factors being studied are followed up at predetermined time intervals to determine the effect on outcomes. This type of study helps to determine associations between a particular exposure and outcomes. For rare outcomes, large numbers of subjects and long follow-up periods are required, so such studies tend to be very expensive. In addition, if randomization and blinding are not conducted properly, the chances of bias and confounders increases [ 26 ].

Cross-sectional studies have transverse study design and involve concurrent assessment of exposures and outcomes without any follow-up. These studies are essentially based on surveys, and are therefore appropriate for determining prevalence but cannot shed light on causation [ 12 , 26 ].

Experimental studies

Experimental studies are intervention studies, and include preclinical trials on animals as well as clinical trials in humans. In these studies, the effect of an intervention is compared with that of another intervention or a placebo. Interventions studied may include, for example, use of medical devices, surgical, physical or psychotherapeutic procedures, psychosocial interventions, rehabilitation measures, acupuncture, physiotherapy training or diet [ 1 , 14 ]. Experimental studies mostly aim to compare outcomes of treatment procedures in a group of patients exhibiting minimal internal differences. To avoid bias, patients are randomly allocated to treatment and control groups. Different countries have different procedures and legal and ethical requirements governing the conduct of such studies. For instance, the United Kingdom Medicines and Medical Devices Act 2021 requires that studies using medical devices be registered by the relevant authorities. In the European Union, interventional studies must be conducted in accordance with the binding rules of Good Clinical Practice (GCP) [ 28 ]. In Germany, vaccine studies are considered to be intervention studies and are conducted as clinical studies according to the AMG [ 13 ]. Likewise, drug studies must seek approval from ethical committees. Informed consent must be obtained from the patient and an ethically defensible control group included. The control group is given another treatment regimen and/or placebo and should enable the central questions of the study to be answered [ 28 ].

Some experimental studies in biomedical research may focus on possible biomarkers, such as enzymes or genes, on evaluation of imaging techniques, such as magnetic resonance imaging and computed tomography, or on techniques such as gene sequencing in order to find correlations between genotypes and phenotypes. The development of statistical tests and mathematical models may also be regarded as experimental studies. Generally, the design of biomedical studies should be based on their purpose and objectives [ 13 ].

Design of experimental studies

The design of an experimental study depends on the type of information sought, the objectives of the study and the ultimate application. Designs can be characterized by interventions on selected groups of the study population under controlled environmental conditions compared with a control group without any interventions. The main designs employed in experimental studies are randomised controlled trials and non-randomised clinical trials, also known as quasi-experimental studies [ 9 , 12 , 26 ].

Non-randomized studies

In non-randomised studies, the study population is selected on the basis of pre-determined selection criteria; it is not randomized with respect to treatment(s) but is prescribed treatment based on the course of the disease. In many experimental studies involving surgical intervention which is only appropriate for particular patient groups, randomization is either not possible or not ethical. Generally, phase IV of a clinical trial has non-randomized design. Non-randomised studies can be further categorised as:

The investigator assigns exposure to the intervention as in a randomized controlled trial, but the subjects are not randomized [ 12 ].

These are large scale studies of therapeutic interventions, for example the efficacy of COVID-19 vaccines in combatting COVID-19. Many samples are required to determine efficacy, particularly when the incidence of a particular disease in the population is low [ 26 ].

In these trials, treatments are allocated to a community group. For instance, the effect of fluoridation of water was tested by exposing some communities to fluoride and comparing outcomes with those in unexposed communities.

Randomized controlled trials

Randomised controlled trials (RCTs) are trials in which the subjects are randomly assigned to experimental and control groups. The experimental group is given the treatment that is being tested and the control group is given an alternative treatment or a placebo or no treatment at all. Most experimental clinical studies are RCTs, and the subjects are either healthy volunteers or patients. After a new drug passes a pre-clinical trial, it is tested via RCTs. Various aspects of the RCT require careful consideration before the trial begins, for example study design, patient population, control group selection, randomization, sampling, blinding or open labelling of treatments and outcomes [ 12 , 26 ].

Study design is an important prerequisite for the success of the study. Randomised controlled trials commonly use parallel group design, matched pairs and cross-over designs [ 29 ].

This design requires large number of subjects/patients who are enrolled, followed up and observed for outcomes on a parallel basis over a period of time.

In this design, patients are matched for different variables. Matched subjects are assigned at random to intervention or control groups. Although this type of design is difficult to conduct, it helps overcome the influence of confounding variables on outcomes.

This design is used for drugs having reversible and transient effects. The effects of two interventions, administered sequentially, are assessed. The number of patients required is smaller than for the other designs [ 29 ].

In RCTs, the patient population is selected on the basis of predetermined selection criteria. This selection is carried out to avoid confounding variables and should be based on predefined inclusion and exclusion criteria. Withdrawal criteria, indicating the circumstances under which subjects should be withdrawn from the trial, should also be predefined.

The criteria for selection of subjects (patients or healthy volunteers) are based on age, body mass index, gender, ethnicity, prognostic factors and diagnostic admission criteria. They are used to select the subjects and then randomly assign them to various treatments for comparison of outcomes [ 26 , 30 ].

These are criteria for excluding subjects from a particular trial, for example severity of disease, concurrent medication, allergies, underlying health conditions and many more [ 30 ].

• Withdrawal criteria

These indicate situations in which the trial is terminated for particular subjects and specify how and when the subjects should be withdrawn from the study. When subjects are withdrawn, they are no longer subject to follow-up.

Perhaps the most important factor in any scientific research is identification and determination of a control group. Without successful deployment of a control group, a study cannot be authentic. Randomised controlled trials can include placebo, no-treatment, historical or active controls [ 26 ].

A placebo is a fake or inert version of the drug under evaluation, with no pharmacological effect. Placebos help overcome any psychological impact of drug dispensing on disease progression, allowing the investigator to estimate the effectiveness of a treatment free from confounding psychological factors. However, placebo controls in drug research and sham surgery are ethically controversial, especially in cases where an effective treatment exists.

This is the least preferred type of control, where subjects are not given anything by way of treatment, not even a placebo. Such controls serve as a neutral reference group for the experimental groups receiving the treatment under investigation. This approach avoids bias due to psychological factors that may influence outcomes.

In some studies, concurrent controls are dispensed with and only historical control data is used. This is done specifically for studies involving rare diseases with high mortality. In such circumstances, withholding treatment from a control group would raise very considerable ethical implications [ 9 ]. Historical controls are controls used in previous studies. They help reduce the overall cost of the study, making drug developers more likely to invest. Historical controls also make enrolment in rare disease trials more feasible by reducing the number of patients required.

Randomization is the optimal method of allocating subjects to the therapy arms of a trial. Random assignment of subjects to the treatment and control groups ensures equal distribution of all variables and confounding factors, such as genetic variabilities, risk factors and comorbidities, in all groups, thereby alleviating bias. Randomization is intended to ensure comparability between the groups, and it reduces the chance of allocating a specific therapy to patients with a particularly favourable prognosis. Randomization is carried out using random number tables, mathematical algorithms for pseudorandom number generation, physical randomization devices such as coins and cards, or sophisticated devices such as electronic random number indicator equipment [ 9-12 , 26 ].

The main randomization techniques used in RCTs are simple randomization, cluster randomization and stratified randomization [ 31 ].

Randomization involving a single sequence of random assignments is known as simple randomization. It randomizes patients selected on the basis of selection criteria to various treatment groups.

Cluster-randomized trials are used to compare treatments that are allocated to clusters (groups) of subjects, rather than to individuals. Groups of patients matching the selection criteria are randomly assigned to the group receiving the treatment or to a control group. Randomised controlled trials are used to evaluate complex interventions.

This is a two-step procedure. As the name indicates, the subjects entering the clinical trial are first grouped in strata (groups) based on clinical features that might affect the outcome of their condition, and then undergo intra-group randomization to assign them to various treatment groups.

Sampling is the process of selecting a sample population from the target population. Sampling allows information to be obtained about the target population based on statistical analysis of a subset of the population, without any need to investigate the characteristics of every individual in the target population [ 32 ]. Sampling techniques are broadly categorised into probability and non-probability sampling, as shown in Figure 3 .

Sampling methods in clinical research.

In this sampling technique, every element of the population has an equal chance of being selected. This helps create a sample truly representative of a given population [ 22 ]. Types of probability sampling techniques are:

Simple random sampling

In this type of sampling every experimental unit has an equal chance of being selected during sampling.

Systematic sampling

This sampling is used where a complete and up-to-date sampling frame is available. The first experimental unit is selected randomly, while the rest are selected randomly based on a predesigned pattern.

Stratified sampling

In this method the study population is divided into strata according to age, gender etc. and then sampling is carried out from these strata.

Cluster sampling

In this method the study population is divided into clusters and these clusters rather than individuals are taken as sampling units. The clusters are then randomly selected for inclusion in the study.

Multistage sampling

Multistage random sampling is conducted at several stages within population clusters. This sampling method is usually applied to large nationwide surveys.

Multiphase sampling

The sampling is conducted in two or more phases. In the first phase some data is collected from the whole sample and in the second, data is collected from a subset of the original sample.

In this type of sampling technique, not all experimental units get an equal chance of being selected [ 22 ]. A non-representative sample which does not produce generalizable results is a possible result. Different types of non-probability sampling are:

Convenience sampling

This sampling is based on the convenience of the investigator.

Purposive/judgemental/selective/subjective sampling

This type is based on the judgement of the investigator.

Quota sampling

This method of sampling is used in studies involving interviews and is based on the judgment of the interviewers, depending on characteristics such as sex and physical status.

Blinding is defined as “concealing or masking the assignment of subjects to a study group from the participants of the study, i.e., patients/subjects, observers and researchers”. Randomised clinical trials may be blinded or non-blinded [ 9 , 12 , 26 ].

Non-blinded experiments are also known as open-label studies. In this type of study, all participating patients, physicians, observers and researchers know the treatment used. This may result in bias, but is unavoidable where hiding a treatment raises ethical concerns. For instance, it is unethical to hide the treatment regime from patients with cancer, AIDS or organ failure. Patients may also be allowed to select the drug brand themselves.

In these experiments the blinding is done at the start of the experiment. Blinding can be single, double or triple.

Single-blind trials

The subjects (patients or healthy volunteers) do not know whether they are in the intervention or the placebo group.

Double-blind trials

Neither the subjects nor the researcher knows who has been assigned to the control and the test groups. Only the observer knows to which group the subjects have been assigned.

Triple-blind trials

In triple blind RCTs, personal or intentional bias is eliminated by none of the study participants (subjects, observer, researcher) knowing the label or nature of the treatment administered.

The information identifying treatment and subjects in double- and triple-blind experiments is held by another party and only made available to the researcher at the end of the trial.

Prospective, randomized, open-label, blinded-endpoint (PROBE) trials

Randomized controlled trials can be conducted as PROBE trials in which patients are randomly assigned to different treatment regimens and both patients and researchers are aware of the treatments administered. The PROBE trial is much easier to conduct than double- or triple-blind or doubled-blind placebo-controlled design, as it enables trials to be performed in conditions that resemble real-world practice. It is also economical and simplifies patient enrolment. However, it imposes certain conditions to avoid the bias associated with open label trials. PROBE designs are endpoint blinded, as the observer is unaware of the treatment being used. Since the subjects and researchers know the treatments, potential bias can be avoided by using so-called hard endpoints as primary endpoints. However, the results obtained by PROBE are less reliable than those obtained by double- or triple-blind studies [ 33 ].

Another important prelude to a successful clinical study is the selection of treatment dosage, form, frequency, route of administration and concurrent medications for the test and active control groups. A drug may be available in various doses and in forms such as tablet, capsule or injectable. Since these factors affect the plasma concentrations and effects of the drug, and ultimately the outcome; all these factors, except dose and frequency, are maintained constant throughout the study. If necessary, the dose and frequency of the drug may be changed gradually and sequentially. If the treatments involve more than one drug, their pharmacokinetic and pharmacodynamic interactions are kept under observation while determining dosage, in order to avoid any influence of these interactions on outcomes [ 9 , 12 , 33 ]. Another important consideration in treatment selection is patient compliance, since non-compliance may have adverse effects on outcome.

Since the objectives of a clinical study indicate the possible outcomes, this is borne in mind in selecting the methods of monitoring and the data required for recording the outcomes of interest. In clinical experiments, outcomes are assessed in terms of efficacy endpoints, i.e. primary endpoints and surrogate or secondary endpoints. Primary endpoints are measures specified by the researcher at the start of the study in order to verify or refute the hypothesis, whereas surrogate endpoints are specified before commencement of the study but can be modified during its course. For instance, in an experiment estimating the efficacy of an antihypertensive drug, the primary endpoint would be to see whether or not the treatment reduces cardiovascular events, while a surrogate endpoint could be its ability to reduce blood pressure [ 26 ]. Many primary and secondary endpoints are prespecified before beginning a study. However, the main primary endpoint is the quality of life afforded by a particular treatment for individuals in the study group.

Bias is distortion of outcomes due to introduction of errors, voluntarily or involuntarily, at different stages of the research, e.g. the stages of design, population selection, calculation of number of samples, data entry and statistical analysis. Several types of bias can occur during clinical research ( Tab. I ).

Types of bias in clinical research.

Chicanery involves deliberate unethical changes to interventions, results and the data of patients. Copying data from other sources is also classified as chicanery.

Confounders

Confounders are factors, other than those being studied, that can affect an outcome parameter. These factors are not directly relevant to the research question but may possibly alter the outcomes [ 10 , 11 ]. For example, while studying the effect of hypertension on renal failure, diabetes could be a confounder as it also affects kidney function. It is therefore essential to take all potential confounders into consideration when designing a study. If known, confounders can be controlled for by selection constraints or statistical adjustments, such as stratification and mathematical modelling, during study design. Various strategies are used during data analysis to adjust for confounders; these include stratified analysis using the Mantel-Haenszel method, a matched design approach, data restriction and model fitting using regression techniques [ 34 ].

Bias, chicanery and confounders can be avoided by randomization and blinding. The randomized controlled and blinded clinical trial with case number planning is therefore accepted as the gold standard for evaluating the efficacy and safety of drugs and therapeutic regimes [ 35 ].

The results of a clinical trial are said to be valid if the differences observed between the study and control groups are real and not influenced by bias or confounders (internal validity) and are applicable to a broader population (external validity). Placebo-controlled, double-blinded, randomised clinical trials have high internal validity, while external validity can be increased by broadening the eligibility criteria for enrolling subjects [ 36 ].

Preclinical studies for the development of biomedical products

Pre-clinical (or laboratory) studies form the basis of clinical trials. To reduce the time for, and to improve the chances of approval of a new drug, the choice of an appropriate preclinical model is of utmost importance. Preclinical studies evaluate the pharmacodynamics, pharmacokinetics and toxicology of a drug in in vitro and in vivo settings. Clinical trials are conducted when preclinical studies have demonstrated the efficacy and safety of a new drug. The results of clinical trials can improve preclinical studies and vice versa . Nonetheless, only a small fraction of drugs that pass the preclinical evaluation criteria are selected for clinical trials, and only a few are approved for use in humans, so optimization of standard preclinical procedures to mimic the complexity of human disease mechanisms is urgently needed [ 37 ].

In summary, preclinical studies involve the use of various in vivo and in vitro models and computer designs to evaluate the efficacy and safety of a new drug.

IN VITRO MODELS (CELL STUDIES)

Advances in cell culture technology have made it possible to test new drugs on cell lines grown in vitro. These studies may involve testing of drugs on human or animal cancer cells [ 38 ].

IN VIVO MODELS (ANIMAL STUDIES)

Drugs that prove effective in vitro are then tested in vivo in live animals to ensure their safety in living systems. Animal models, and their critical validation, are of great importance in minimizing unpredicted adverse effects of a drug in clinical trial phases. Animal models are carefully selected on the basis of their advantages and limitations and on the objectives of the study, in order to mimic pathophysiological conditions in humans [ 38 ]. The validity of animal models is increased by following the relevant guidelines and standards in designing a study. Three types of models are used in preclinical studies:

Homologous models

Homologous models are animals which have the same causes, symptoms, and treatments of a particular disease that humans would have.

Isomorphic models

These animals have same symptoms and treatments of a particular disease as humans, but the cause may be different.

Predictive models

These models are only like humans in some aspects of a particular disease; however they provide useful information about the mechanisms of disease features.

IN SILICO MODELS (COMPUTER STUDIES)

In silico models are based on computer simulations that complement or precede in vitro and in vivo studies. They predict how a drug might behave in these subsequent studies. In-silico studies require expertise in biochemistry, molecular biology, cheminformatics, and bioinformatics [ 38 ].

Pre-clinical studies provide useful information about the behaviour and safety of drugs. However, drugs do not necessarily behave in the same way in humans as they do in animal models. For example, human subjects and mice models differ sharply in absorption, processing, and excretion of certain drugs. Unexpected side-effects may therefore occur in humans that do not occur in animal models. Drugs which show promising outcomes in preclinical studies are then approved for testing in human subjects by regulatory authorities such as the Food and Drug Administration (FDA) in the US [ 37 , 38 ].

Design, performance, and monitoring of clinical trials

Once preclinical studies on a new drug are completed and promising results are achieved, the next stage in biomedical research is testing the safety, efficacy and reproducibility of the drug’s action on humans through clinical trials. Clinical trials are considered to be a safe and dependable method of evaluating the efficacy of a treatment. Clinical trials may be therapeutic or preventive [ 37-39 ].

THERAPEUTIC TRIALS

These trials are conducted to test experimental treatments, combinations of new or existing drugs, and new surgical interventions.

PREVENTIVE TRIALS

These trials test the efficacy of interventions (drugs, vaccines) in preventing diseases and their outcomes.

In general, clinical trials aim to enhance the repertoire of information related to an intervention or lifestyle regime that might prove beneficial for patient management or treatment. They are designed to develop and test new diagnostic methods or treatments and their effects on humans, or new uses of existing diagnostic methods or treatment. They also help identify the most cost-effective and risk-free diagnostic methods or treatments. Randomized controlled trials are conducted to compare the safety and efficacy of two or more interventions in humans, and can often be based on clinical equipoise. Their phases [ 26 ] are shown in Table II .

Phases of a randomized controlled trial of a drug.

Good clinical practice: guidelines and requirements

Clinical trials are the gold standard for evaluating the superiority or similarity of new drugs or surgical procedures with respect to existing ones. As clinical trials involve testing on humans, their design and conduct require careful planning, diligent execution and enormous resources to comply with regulations set by the regulatory authorities so that robust results can be attained. The good clinical practice (GCP) guidelines published by the International Council of Harmonization (ICH) is an international ethical standard that ensures that the design, conduct, performance, monitoring, auditing, recording, analysis and reporting of clinical trials takes place according to established values. It also ensures the reliability and precision of reported data, and protects the rights, integrity and privacy of subjects participating in a trial [ 28 , 31 ]. Protection of the safety, wellbeing and rights of human subjects participating in a clinical trial is consistent with the principles of the Declaration of Helsinki [ 40 ] and with the ethical principles formulated by the World Medical Association [ 41 ]. The requirements for conducting clinical trials in the European Union, including GCP and good manufacturing practice and their respective inspections, are implemented in the Clinical Trial Directive (Directive 2001/20/EC) and the Good Clinical Practice Directive (Directive 2005/28/EC) [ 31 ].

The responsibility for GCP lies with all participants in the trial, from the site staff to the subjects and the ethical and monitoring committees. The roles and responsibilities of GCP participants are shown in Table III .

Clinical trial participants and their role in good clinical practice.

The planning and execution of clinical research is of vital importance for the advancement of medical science. The validity of clinical research findings depends on a variety of factors, such as study design, sampling techniques and statistical analysis. Choosing an appropriate study design requires detailed knowledge of the types of clinical study, the situations where they are applied and the possible outcomes, so that a methodology befitting the hypothesis is adopted. Careful implementation of study design eliminates the chances of bias, provides quality assurance of the data collected and increases the validity of the results, adding value to the findings. Successful preclinical studies, basic research and pilot scale intervention studies pave the way for more sophisticated clinical trials. Randomised, double-blind clinical trials with case number planning are accepted as the gold standard for evaluating the efficacy and safety of drugs and therapeutic regimes and in evaluating the superiority or similarity of new drugs or surgical procedures to existing ones. As clinical trials involve testing on humans, their design and conduct require careful planning, diligent execution and enormous resources to comply with the rules set by the regulatory authorities, necessary to achieve robust results.

Acknowledgements

This research was funded by the Provincia Autonoma di Bolzano in the framework of LP 15/2020 (dgp 3174/2021).

Conflicts of interest statement

Authors declare no conflict of interest.

Author's contributions

MB: study conception, editing and critical revision of the manuscript; AKK, DP, GH, RB, Paul S, Peter S, RM, BF, NC, SM, LL, DD, GMT, MCE, MD, SM, Daniele M, GB, KD, MCM, TB, MS, STC, Donald M, AM, AB, KLH, MK, LS, LL, GF: literature search, editing and critical revision of the manuscript. All authors have read and approved the final manuscript.

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How much does your phone's blue light really delay your sleep? Relax, it's just 2.7 minutes

by Chelsea Reynolds, The Conversation

It's one of the most pervasive messages about technology and sleep. We're told bright, blue light from screens prevents us falling asleep easily. We're told to avoid scrolling on our phones before bedtime or while in bed . We're sold glasses to help filter out blue light. We put our phones on "night mode" to minimize exposure to blue light.

But what does the science actually tell us about the impact of bright, blue light and sleep? When our group of sleep experts from Sweden, Australia and Israel compared scientific studies that directly tested this, we found the overall impact was close to meaningless. Sleep was disrupted, on average, by less than three minutes.

We showed the message that blue light from screens stops you from falling asleep is essentially a myth, albeit a very convincing one.

Instead, we found a more nuanced picture of technology and sleep.

What we did

We gathered evidence from 73 independent studies with a total of 113,370 participants of all ages examining various factors that connect technology use and sleep.

We did indeed find a link between technology use and sleep, but not necessarily what you'd think.

We found that sometimes technology use can lead to poor sleep and sometimes poor sleep can lead to more technology use. In other words, the relationship between technology and sleep is complex and can go both ways.

How is technology supposed to harm sleep?

Technology is proposed to harm our sleep in a number of ways. But here's what we found when we looked at the evidence:

Bright screen light—across 11 experimental studies, people who used a bright screen emitting blue light before bedtime fell asleep an average of only 2.7 minutes later. In some studies, people slept better after using a bright screen. When we were invited to write about this evidence further, we showed there is still no meaningful impact of bright screen light on other sleep characteristics including the total amount or quality of sleep

Arousal is a measure of whether people become more alert depending on what they're doing on their device. Across seven studies, people who engaged in more alerting or "exciting" content (for example, video games) lost an average of only about 3.5 minutes of sleep compared to those who engaged in something less exciting (for example, TV). This tells us the content of technology alone doesn't affect sleep as much as we think

• We found sleep disruption at night (for example, being awoken by text messages) and sleep displacement (using technology past the time that we could be sleeping) can lead to sleep loss. So while technology use was linked to less sleep in these instances, this was unrelated to being exposed to bright, blue light from screens before bedtime.

Which factors encourage more technology use?

Research we reviewed suggests people tend to use more technology at bedtime for two main reasons:

• to "fill the time" when they're not yet sleepy . This is common for teenagers , who have a biological shift in their sleep patterns that leads to later sleep times, independent of technology use.
• to calm down negative emotions and thoughts at bedtime, for apparent stress reduction and to provide comfort.

There are also a few things that might make people more vulnerable to using technology late into the night and losing sleep.

We found people who are risk-takers or who lose track of time easily may turn off devices later and sacrifice sleep. Fear of missing out and social pressures can also encourage young people in particular to stay up later on technology.

What helps us use technology sensibly?

Last of all, we looked at protective factors, ones that can help people use technology more sensibly before bed.

The two main things we found that helped were self-control , which helps resist the short-term rewards of clicking and scrolling, and having a parent or loved one to help set bedtimes .

Why do we blame blue light?

The blue light theory involves melatonin, a hormone that regulates sleep. During the day, we are exposed to bright, natural light that contains a high amount of blue light. This bright, blue light activates certain cells at the back of our eyes, which send signals to our brain that it's time to be alert. But as light decreases at night, our brain starts to produce melatonin, making us feel sleepy.

It's logical to think that artificial light from devices could interfere with the production of melatonin and so affect our sleep. But studies show it would require light levels of about 1,000–2,000 lux (a measure of the intensity of light) to have a significant impact.

Device screens emit only about 80–100 lux . At the other end of the scale, natural sunlight on a sunny day provides about 100,000 lux .

What's the take-home message?

We know that bright light does affect sleep and alertness. However, our research indicates the light from devices such as smartphones and laptops is nowhere near bright or blue enough to disrupt sleep.

There are many factors that can affect sleep, and bright, blue screen light likely isn't one of them.

The take-home message is to understand your own sleep needs and how technology affects you. Maybe reading an e-book or scrolling on socials is fine for you, or maybe you're too often putting the phone down way too late. Listen to your body and when you feel sleepy, turn off your device.

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Eating Red And Processed Meat—And Even Chicken—Could Increase Risk Of Diabetes, Research Finds

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Consuming meat, particularly red and processed meat, and even poultry like chicken and turkey may increase the risk of developing type 2 diabetes in the future, according to a new study published on Tuesday, adding to growing evidence linking meat and ultra-processed foods to health issues including heart disease, cancer, depression, anxiety and even premature death.

Red meat is associated with a higher risk of type 2 diabetes, researchers found.

Consuming processed meat and unprocessed red meat regularly is associated with a higher risk of developing type 2 diabetes, according to peer reviewed published in The Lancet Diabetes and Endocrinology medical journal.

While previous research has indicated eating more processed meat and unprocessed red meat is linked to a higher risk of type 2 diabetes, the researchers said results have been inconclusive and variable, which has led to confusing and often polarizing debates over whether the foods are safe to eat and, if so, in what quantities.

To assess the link between meat and the risk of type 2 diabetes, the team, led by researchers at the University of Cambridge, analyzed existing data from nearly 2 million people across 31 study groups in 20 countries to see whether their eating habits were associated with a risk of type 2 diabetes when accounting for other factors like age, gender, energy intake, body mass index and health-related behaviors.

Habitually eating 50 grams of processed meat a day—roughly equivalent to two slices of ham—was associated with a 15% higher risk of developing type 2 diabetes in the next 10 years, the researchers found, and consuming 100 grams of unprocessed red meat a day—the equivalent of a small steak—was associated with a 10% higher risk.

Nita Forouhi, a professor of population health and nutrition at the University of Cambridge and a senior author on the paper, said the research “provides the most comprehensive evidence to date” of a link between eating red and processed meat and a higher future risk of type 2 diabetes.

“It supports recommendations to limit the consumption of processed meat and unprocessed red meat to reduce type 2 diabetes cases in the population,” added Forouhi.

Is It Safe To Eat Other Meat Like Chicken And Turkey?

Poultry such as chicken, turkey and duck is often touted as a healthier protein source to red and processed meats. The idea is supported by research, which indicates lower risks for many of the health issues linked to red and processed meat consumption like cancer , heart disease and diabetes , but the issue is a comparative one and it does not mean eating poultry is without risk. Research increasingly indicates regular poultry meat consumption is linked to harmful health effects like gastro-oesophageal reflux disease, gallbladder disease and diabetes. Research on this association is more limited, the researchers noted, taking the opportunity to investigate the potential link as well. They found habitual consumption of 100 grams of poultry a day was associated with an 8% higher risk of developing type 2 diabetes over the next 10 years. However, Forouhi warned the evidence linking poultry consumption and diabetes was much weaker than that for red and processed meat when subjected to further analytical scrutiny. “While our findings provide more comprehensive evidence on the association between poultry consumption and type 2 diabetes than was previously available, the link remains uncertain and needs to be investigated further,” Forouhi said.

Surprising Fact

While often considered a “white meat” alongside poultry like chicken, experts and regulators say pork is a “red meat” like beef, veal and lamb. The U.S. Department of Agriculture says the distinction is determined by the amount of the oxygen-carrying protein myoglobin is in the meat, which determines the color of the meat. Pork is considered red meat because it contains more myoglobin than chicken or fish.

What To Watch For

Growing evidence on the negative health associations of eating different meats has ignited campaigns to limit the consumption of red and processed meat, and sometimes meat in general, as a matter of public health and to reduce the burden of diseases like diabetes. In recent years, this health-driven messaging has been joined by a more climate-focused approach, urging people to limit meat consumption as part of reducing their carbon footprint and tackling the climate crisis. Research has also increasingly identified potential health problems like heart disease and early death linked to ultraprocessed foods, including plant-based ultraprocessed foods .

What We Don’t Know

Most research between food consumption and various health risks are observational in nature. This means causal relationships are very hard to determine. More research—much of which would be difficult or impossible to conduct in humans—is needed to establish causal claims like reducing red meat intake will reduce the risk of developing diabetes.

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