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Research methods--quantitative, qualitative, and more: overview.

• Quantitative Research
• Qualitative Research
• Data Science Methods (Machine Learning, AI, Big Data)
• Text Mining and Computational Text Analysis
• Evidence Synthesis/Systematic Reviews
• Get Data, Get Help!

About Research Methods

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

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

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

Suggestions for changes and additions to this guide are welcome! 

START HERE: SAGE Research Methods

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

• SAGE Research Methods
• Little Green Books  (Quantitative Methods)
• Little Blue Books  (Qualitative Methods)
• Dictionaries and Encyclopedias  
• Case studies of real research projects
• Sample datasets for hands-on practice
• Streaming video--see methods come to life
• Methodspace- -a community for researchers
• SAGE Research Methods Course Mapping

Library Data Services at UC Berkeley

Library Data Services Program and Digital Scholarship Services

The LDSP offers a variety of services and tools !  From this link, check out pages for each of the following topics:  discovering data, managing data, collecting data, GIS data, text data mining, publishing data, digital scholarship, open science, and the Research Data Management Program.

Be sure also to check out the visual guide to where to seek assistance on campus with any research question you may have!

Library GIS Services

Other Data Services at Berkeley

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

General Research Methods Resources

Here are some general resources for assistance:

• Assistance from ICPSR (must create an account to access): Getting Help with Data , and Resources for Students
• Wiley Stats Ref for background information on statistics topics
• Survey Documentation and Analysis (SDA) .  Program for easy web-based analysis of survey data.

Consultants

• D-Lab/Data Science Discovery Consultants Request help with your research project from peer consultants.
• Research data (RDM) consulting Meet with RDM consultants before designing the data security, storage, and sharing aspects of your qualitative project.
• Statistics Department Consulting Services A service in which advanced graduate students, under faculty supervision, are available to consult during specified hours in the Fall and Spring semesters.

Related Resourcex

• IRB / CPHS Qualitative research projects with human subjects often require that you go through an ethics review.
• OURS (Office of Undergraduate Research and Scholarships) OURS supports undergraduates who want to embark on research projects and assistantships. In particular, check out their "Getting Started in Research" workshops
• Sponsored Projects Sponsored projects works with researchers applying for major external grants.
• Next: Quantitative Research >>
• Last Updated: Apr 25, 2024 11:09 AM
• URL: https://guides.lib.berkeley.edu/researchmethods

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• Knowledge Base
• Methodology

Research Design | Step-by-Step Guide with Examples

Published on 5 May 2022 by Shona McCombes . Revised on 20 March 2023.

A research design is a strategy for answering your research question  using empirical data. Creating a research design means making decisions about:

• Your overall aims and approach
• The type of research design you’ll use
• Your sampling methods or criteria for selecting subjects
• Your data collection methods
• The procedures you’ll follow to collect data
• Your data analysis methods

A well-planned research design helps ensure that your methods match your research aims and that you use the right kind of analysis for your data.

Table of contents

Step 1: consider your aims and approach, step 2: choose a type of research design, step 3: identify your population and sampling method, step 4: choose your data collection methods, step 5: plan your data collection procedures, step 6: decide on your data analysis strategies, frequently asked questions.

• Introduction

Before you can start designing your research, you should already have a clear idea of the research question you want to investigate.

There are many different ways you could go about answering this question. Your research design choices should be driven by your aims and priorities – start by thinking carefully about what you want to achieve.

The first choice you need to make is whether you’ll take a qualitative or quantitative approach.

Qualitative research designs tend to be more flexible and inductive , allowing you to adjust your approach based on what you find throughout the research process.

Quantitative research designs tend to be more fixed and deductive , with variables and hypotheses clearly defined in advance of data collection.

It’s also possible to use a mixed methods design that integrates aspects of both approaches. By combining qualitative and quantitative insights, you can gain a more complete picture of the problem you’re studying and strengthen the credibility of your conclusions.

Practical and ethical considerations when designing research

As well as scientific considerations, you need to think practically when designing your research. If your research involves people or animals, you also need to consider research ethics .

• How much time do you have to collect data and write up the research?
• Will you be able to gain access to the data you need (e.g., by travelling to a specific location or contacting specific people)?
• Do you have the necessary research skills (e.g., statistical analysis or interview techniques)?
• Will you need ethical approval ?

At each stage of the research design process, make sure that your choices are practically feasible.

Prevent plagiarism, run a free check.

Within both qualitative and quantitative approaches, there are several types of research design to choose from. Each type provides a framework for the overall shape of your research.

Types of quantitative research designs

Quantitative designs can be split into four main types. Experimental and   quasi-experimental designs allow you to test cause-and-effect relationships, while descriptive and correlational designs allow you to measure variables and describe relationships between them.

With descriptive and correlational designs, you can get a clear picture of characteristics, trends, and relationships as they exist in the real world. However, you can’t draw conclusions about cause and effect (because correlation doesn’t imply causation ).

Experiments are the strongest way to test cause-and-effect relationships without the risk of other variables influencing the results. However, their controlled conditions may not always reflect how things work in the real world. They’re often also more difficult and expensive to implement.

Types of qualitative research designs

Qualitative designs are less strictly defined. This approach is about gaining a rich, detailed understanding of a specific context or phenomenon, and you can often be more creative and flexible in designing your research.

The table below shows some common types of qualitative design. They often have similar approaches in terms of data collection, but focus on different aspects when analysing the data.

Your research design should clearly define who or what your research will focus on, and how you’ll go about choosing your participants or subjects.

In research, a population is the entire group that you want to draw conclusions about, while a sample is the smaller group of individuals you’ll actually collect data from.

Defining the population

A population can be made up of anything you want to study – plants, animals, organisations, texts, countries, etc. In the social sciences, it most often refers to a group of people.

For example, will you focus on people from a specific demographic, region, or background? Are you interested in people with a certain job or medical condition, or users of a particular product?

The more precisely you define your population, the easier it will be to gather a representative sample.

Sampling methods

Even with a narrowly defined population, it’s rarely possible to collect data from every individual. Instead, you’ll collect data from a sample.

To select a sample, there are two main approaches: probability sampling and non-probability sampling . The sampling method you use affects how confidently you can generalise your results to the population as a whole.

Probability sampling is the most statistically valid option, but it’s often difficult to achieve unless you’re dealing with a very small and accessible population.

For practical reasons, many studies use non-probability sampling, but it’s important to be aware of the limitations and carefully consider potential biases. You should always make an effort to gather a sample that’s as representative as possible of the population.

Case selection in qualitative research

In some types of qualitative designs, sampling may not be relevant.

For example, in an ethnography or a case study, your aim is to deeply understand a specific context, not to generalise to a population. Instead of sampling, you may simply aim to collect as much data as possible about the context you are studying.

In these types of design, you still have to carefully consider your choice of case or community. You should have a clear rationale for why this particular case is suitable for answering your research question.

For example, you might choose a case study that reveals an unusual or neglected aspect of your research problem, or you might choose several very similar or very different cases in order to compare them.

Data collection methods are ways of directly measuring variables and gathering information. They allow you to gain first-hand knowledge and original insights into your research problem.

You can choose just one data collection method, or use several methods in the same study.

Survey methods

Surveys allow you to collect data about opinions, behaviours, experiences, and characteristics by asking people directly. There are two main survey methods to choose from: questionnaires and interviews.

Observation methods

Observations allow you to collect data unobtrusively, observing characteristics, behaviours, or social interactions without relying on self-reporting.

Observations may be conducted in real time, taking notes as you observe, or you might make audiovisual recordings for later analysis. They can be qualitative or quantitative.

Other methods of data collection

There are many other ways you might collect data depending on your field and topic.

If you’re not sure which methods will work best for your research design, try reading some papers in your field to see what data collection methods they used.

Secondary data

If you don’t have the time or resources to collect data from the population you’re interested in, you can also choose to use secondary data that other researchers already collected – for example, datasets from government surveys or previous studies on your topic.

With this raw data, you can do your own analysis to answer new research questions that weren’t addressed by the original study.

Using secondary data can expand the scope of your research, as you may be able to access much larger and more varied samples than you could collect yourself.

However, it also means you don’t have any control over which variables to measure or how to measure them, so the conclusions you can draw may be limited.

As well as deciding on your methods, you need to plan exactly how you’ll use these methods to collect data that’s consistent, accurate, and unbiased.

Planning systematic procedures is especially important in quantitative research, where you need to precisely define your variables and ensure your measurements are reliable and valid.

Operationalisation

Some variables, like height or age, are easily measured. But often you’ll be dealing with more abstract concepts, like satisfaction, anxiety, or competence. Operationalisation means turning these fuzzy ideas into measurable indicators.

If you’re using observations , which events or actions will you count?

If you’re using surveys , which questions will you ask and what range of responses will be offered?

You may also choose to use or adapt existing materials designed to measure the concept you’re interested in – for example, questionnaires or inventories whose reliability and validity has already been established.

Reliability and validity

Reliability means your results can be consistently reproduced , while validity means that you’re actually measuring the concept you’re interested in.

For valid and reliable results, your measurement materials should be thoroughly researched and carefully designed. Plan your procedures to make sure you carry out the same steps in the same way for each participant.

If you’re developing a new questionnaire or other instrument to measure a specific concept, running a pilot study allows you to check its validity and reliability in advance.

Sampling procedures

As well as choosing an appropriate sampling method, you need a concrete plan for how you’ll actually contact and recruit your selected sample.

That means making decisions about things like:

• How many participants do you need for an adequate sample size?
• What inclusion and exclusion criteria will you use to identify eligible participants?
• How will you contact your sample – by mail, online, by phone, or in person?

If you’re using a probability sampling method, it’s important that everyone who is randomly selected actually participates in the study. How will you ensure a high response rate?

If you’re using a non-probability method, how will you avoid bias and ensure a representative sample?

Data management

It’s also important to create a data management plan for organising and storing your data.

Will you need to transcribe interviews or perform data entry for observations? You should anonymise and safeguard any sensitive data, and make sure it’s backed up regularly.

Keeping your data well organised will save time when it comes to analysing them. It can also help other researchers validate and add to your findings.

On their own, raw data can’t answer your research question. The last step of designing your research is planning how you’ll analyse the data.

Quantitative data analysis

In quantitative research, you’ll most likely use some form of statistical analysis . With statistics, you can summarise your sample data, make estimates, and test hypotheses.

Using descriptive statistics , you can summarise your sample data in terms of:

• The distribution of the data (e.g., the frequency of each score on a test)
• The central tendency of the data (e.g., the mean to describe the average score)
• The variability of the data (e.g., the standard deviation to describe how spread out the scores are)

The specific calculations you can do depend on the level of measurement of your variables.

Using inferential statistics , you can:

• Make estimates about the population based on your sample data.
• Test hypotheses about a relationship between variables.

Regression and correlation tests look for associations between two or more variables, while comparison tests (such as t tests and ANOVAs ) look for differences in the outcomes of different groups.

Your choice of statistical test depends on various aspects of your research design, including the types of variables you’re dealing with and the distribution of your data.

Qualitative data analysis

In qualitative research, your data will usually be very dense with information and ideas. Instead of summing it up in numbers, you’ll need to comb through the data in detail, interpret its meanings, identify patterns, and extract the parts that are most relevant to your research question.

Two of the most common approaches to doing this are thematic analysis and discourse analysis .

There are many other ways of analysing qualitative data depending on the aims of your research. To get a sense of potential approaches, try reading some qualitative research papers in your field.

A sample is a subset of individuals from a larger population. Sampling means selecting the group that you will actually collect data from in your research.

For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

Statistical sampling allows you to test a hypothesis about the characteristics of a population. There are various sampling methods you can use to ensure that your sample is representative of the population as a whole.

Operationalisation means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioural avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalise the variables that you want to measure.

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts, and meanings, use qualitative methods .
• If you want to analyse a large amount of readily available data, use secondary data. If you want data specific to your purposes with control over how they are generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

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Home Market Research

What is Research: Definition, Methods, Types & Examples

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

Content Index

What is Research?

What are the characteristics of research.

• Comparative analysis chart

Qualitative methods

Quantitative methods, 8 tips for conducting accurate research.

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

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

Research is conducted with a purpose to:

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

What is the purpose of research?

There are three main purposes:

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

LEARN ABOUT: Descriptive Analysis

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

LEARN ABOUT: Best Data Collection Tools

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

Here is a comparative analysis chart for a better understanding:

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

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

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

Types of research methods and Examples

Research methods are broadly classified as Qualitative and Quantitative .

Both methods have distinctive properties and data collection methods .

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

Types of qualitative methods include:

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

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

Types of quantitative methods include:

• Survey research
• Descriptive research
• Correlational research

LEARN MORE: Descriptive Research vs Correlational Research

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

It is essential to ensure that your data is:

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

Gather insights

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

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

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NIH conducts clinical research trials for many diseases and conditions, including cancer , Alzheimer’s disease , allergy and infectious diseases , and neurological disorders . To search for other diseases and conditions, you can visit ClinicalTrials.gov.

ClinicalTrials.gov [ How to Use Search ] This is a searchable registry and results database of federally and privately supported clinical trials conducted in the United States and around the world. ClinicalTrials.gov gives you information about a trial's purpose, who may participate, locations, and phone numbers for more details. This information should be used in conjunction with advice from health care professionals.

Listing a study does not mean it has been evaluated by the U.S. Federal Government. Read the disclaimer on ClinicalTrials.gov for details.

Before participating in a study, talk to your health care provider and learn about the risks and potential benefits.

At the NIH Clinical Center in Bethesda, Maryland

Search NIH Clinical Research Studies The NIH maintains an online database of clinical research studies taking place at its Clinical Center, which is located on the NIH campus in Bethesda, Maryland. Studies are conducted by most of the institutes and centers across the NIH. The Clinical Center hosts a wide range of studies from rare diseases to chronic health conditions, as well as studies for healthy volunteers. Visitors can search by diagnosis, sign, symptom or other key words.

Join a National Registry of Research Volunteers

ResearchMatch This is an NIH-funded initiative to connect 1) people who are trying to find research studies, and 2) researchers seeking people to participate in their studies. It is a free, secure registry to make it easier for the public to volunteer and to become involved in clinical research studies that contribute to improved health in the future.

This page last reviewed on November 6, 2018

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Module 1: Introduction: What is Research?

Learning Objectives

By the end of this module, you will be able to:

• Explain how the scientific method is used to develop new knowledge
• Describe why it is important to follow a research plan

The Scientific Method consists of observing the world around you and creating a  hypothesis  about relationships in the world. A hypothesis is an informed and educated prediction or explanation about something. Part of the research process involves testing the  hypothesis , and then examining the results of these tests as they relate to both the hypothesis and the world around you. When a researcher forms a hypothesis, this acts like a map through the research study. It tells the researcher which factors are important to study and how they might be related to each other or caused by a  manipulation  that the researcher introduces (e.g. a program, treatment or change in the environment). With this map, the researcher can interpret the information he/she collects and can make sound conclusions about the results.

Research can be done with human beings, animals, plants, other organisms and inorganic matter. When research is done with human beings and animals, it must follow specific rules about the treatment of humans and animals that have been created by the U.S. Federal Government. This ensures that humans and animals are treated with dignity and respect, and that the research causes minimal harm.

No matter what topic is being studied, the value of the research depends on how well it is designed and done. Therefore, one of the most important considerations in doing good research is to follow the design or plan that is developed by an experienced researcher who is called the  Principal Investigator  (PI). The PI is in charge of all aspects of the research and creates what is called a  protocol  (the research plan) that all people doing the research must follow. By doing so, the PI and the public can be sure that the results of the research are real and useful to other scientists.

Module 1: Discussion Questions

• How is a hypothesis like a road map?
• Who is ultimately responsible for the design and conduct of a research study?
• How does following the research protocol contribute to informing public health practices?

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About Clinical Studies

Research: it's all about patients.

Mayo's mission is about the patient, the patient comes first. So the mission and research here, is to advance how we can best help the patient, how to make sure the patient comes first in care. So in many ways, it's a cycle. It can start with as simple as an idea, worked on in a laboratory, brought to the patient bedside, and if everything goes right, and let's say it's helpful or beneficial, then brought on as a standard approach. And I think that is one of the unique characteristics of Mayo's approach to research, that patient-centeredness. That really helps to put it in its own spotlight.

At Mayo Clinic, the needs of the patient come first. Part of this commitment involves conducting medical research with the goal of helping patients live longer, healthier lives.

Through clinical studies, which involve people who volunteer to participate in them, researchers can better understand how to diagnose, treat and prevent diseases or conditions.

Types of clinical studies

• Observational study. A type of study in which people are observed or certain outcomes are measured. No attempt is made by the researcher to affect the outcome — for example, no treatment is given by the researcher.
• Clinical trial (interventional study). During clinical trials, researchers learn if a new test or treatment works and is safe. Treatments studied in clinical trials might be new drugs or new combinations of drugs, new surgical procedures or devices, or new ways to use existing treatments. Find out more about the five phases of non-cancer clinical trials on ClinicalTrials.gov or the National Cancer Institute phases of cancer trials .
• Medical records research. Medical records research involves the use of information collected from medical records. By studying the medical records of large groups of people over long periods of time, researchers can see how diseases progress and which treatments and surgeries work best. Find out more about Minnesota research authorization .

Clinical studies may differ from standard medical care

A health care provider diagnoses and treats existing illnesses or conditions based on current clinical practice guidelines and available, approved treatments.

But researchers are constantly looking for new and better ways to prevent and treat disease. In their laboratories, they explore ideas and test hypotheses through discovery science. Some of these ideas move into formal clinical trials.

During clinical studies, researchers formally and scientifically gather new knowledge and possibly translate these findings into improved patient care.

Before clinical trials begin

This video demonstrates how discovery science works, what happens in the research lab before clinical studies begin, and how a discovery is transformed into a potential therapy ready to be tested in trials with human participants:

How clinical trials work

Trace the clinical trial journey from a discovery research idea to a viable translatable treatment for patients:

See a glossary of terms related to clinical studies, clinical trials and medical research on ClinicalTrials.gov.

Watch a video about clinical studies to help you prepare to participate.

Let's Talk About Clinical Research

Narrator: This presentation is a brief introduction to the terms, purposes, benefits and risks of clinical research.

If you have questions about the content of this program, talk with your health care provider.

What is clinical research?

Clinical research is a process to find new and better ways to understand, detect, control and treat health conditions. The scientific method is used to find answers to difficult health-related questions.

Ways to participate

There are many ways to participate in clinical research at Mayo Clinic. Three common ways are by volunteering to be in a study, by giving permission to have your medical record reviewed for research purposes, and by allowing your blood or tissue samples to be studied.

Types of clinical research

There are many types of clinical research:

• Prevention studies look at ways to stop diseases from occurring or from recurring after successful treatment.
• Screening studies compare detection methods for common conditions.
• Diagnostic studies test methods for early identification of disease in those with symptoms.
• Treatment studies test new combinations of drugs and new approaches to surgery, radiation therapy and complementary medicine.
• The role of inheritance or genetic studies may be independent or part of other research.
• Quality of life studies explore ways to manage symptoms of chronic illness or side effects of treatment.
• Medical records studies review information from large groups of people.

Clinical research volunteers

Participants in clinical research volunteer to take part. Participants may be healthy, at high risk for developing a disease, or already diagnosed with a disease or illness. When a study is offered, individuals may choose whether or not to participate. If they choose to participate, they may leave the study at any time.

Research terms

You will hear many terms describing clinical research. These include research study, experiment, medical research and clinical trial.

Clinical trial

A clinical trial is research to answer specific questions about new therapies or new ways of using known treatments. Clinical trials take place in phases. For a treatment to become standard, it usually goes through two or three clinical trial phases. The early phases look at treatment safety. Later phases continue to look at safety and also determine the effectiveness of the treatment.

Phase I clinical trial

A small number of people participate in a phase I clinical trial. The goals are to determine safe dosages and methods of treatment delivery. This may be the first time the drug or intervention is used with people.

Phase II clinical trial

Phase II clinical trials have more participants. The goals are to evaluate the effectiveness of the treatment and to monitor side effects. Side effects are monitored in all the phases, but this is a special focus of phase II.

Phase III clinical trial

Phase III clinical trials have the largest number of participants and may take place in multiple health care centers. The goal of a phase III clinical trial is to compare the new treatment to the standard treatment. Sometimes the standard treatment is no treatment.

Phase IV clinical trial

A phase IV clinical trial may be conducted after U.S. Food and Drug Administration approval. The goal is to further assess the long-term safety and effectiveness of a therapy. Smaller numbers of participants may be enrolled if the disease is rare. Larger numbers will be enrolled for common diseases, such as diabetes or heart disease.

Clinical research sponsors

Mayo Clinic funds clinical research at facilities in Rochester, Minnesota; Jacksonville, Florida; and Arizona, and in the Mayo Clinic Health System. Clinical research is conducted in partnership with other medical centers throughout the world. Other sponsors of research at Mayo Clinic include the National Institutes of Health, device or pharmaceutical companies, foundations and organizations.

Clinical research at Mayo Clinic

Dr. Hugh Smith, former chair of Mayo Clinic Board of Governors, stated, "Our commitment to research is based on our knowledge that medicine must be constantly moving forward, that we need to continue our efforts to better understand disease and bring the latest medical knowledge to our practice and to our patients."

This fits with the term "translational research," meaning what is learned in the laboratory goes quickly to the patient's bedside and what is learned at the bedside is taken back to the laboratory.

Ethics and safety of clinical research

All clinical research conducted at Mayo Clinic is reviewed and approved by Mayo's Institutional Review Board. Multiple specialized committees and colleagues may also provide review of the research. Federal rules help ensure that clinical research is conducted in a safe and ethical manner.

Institutional review board

An institutional review board (IRB) reviews all clinical research proposals. The goal is to protect the welfare and safety of human subjects. The IRB continues its review as research is conducted.

Consent process

Participants sign a consent form to ensure that they understand key facts about a study. Such facts include that participation is voluntary and they may withdraw at any time. The consent form is an informational document, not a contract.

Study activities

Staff from the study team describe the research activities during the consent process. The research may include X-rays, blood tests, counseling or medications.

Study design

During the consent process, you may hear different phrases related to study design. Randomized means you will be assigned to a group by chance, much like a flip of a coin. In a single-blinded study, participants do not know which treatment they are receiving. In a double-blinded study, neither the participant nor the research team knows which treatment is being administered.

Some studies use an inactive substance called a placebo.

Multisite studies allow individuals from many different locations or health care centers to participate.

Remuneration

If the consent form states remuneration is provided, you will be paid for your time and participation in the study.

Some studies may involve additional cost. To address costs in a study, carefully review the consent form and discuss questions with the research team and your insurance company. Medicare may cover routine care costs that are part of clinical trials. Medicaid programs in some states may also provide routine care cost coverage, as well.

When considering participation in a research study, carefully look at the benefits and risks. Benefits may include earlier access to new clinical approaches and regular attention from a research team. Research participation often helps others in the future.

Risks/inconveniences

Risks may include side effects. The research treatment may be no better than the standard treatment. More visits, if required in the study, may be inconvenient.

Weigh your risks and benefits

Consider your situation as you weigh the risks and benefits of participation prior to enrolling and during the study. You may stop participation in the study at any time.

Ask questions

Stay informed while participating in research:

• Write down questions you want answered.
• If you do not understand, say so.
• If you have concerns, speak up.

Website resources are available. The first website lists clinical research at Mayo Clinic. The second website, provided by the National Institutes of Health, lists studies occurring in the United States and throughout the world.

Additional information about clinical research may be found at the Mayo Clinic Barbara Woodward Lips Patient Education Center and the Stephen and Barbara Slaggie Family Cancer Education Center.

Clinical studies questions

• Phone: 800-664-4542 (toll-free)
• Contact form

Cancer-related clinical studies questions

• Phone: 855-776-0015 (toll-free)

International patient clinical studies questions

• Phone: 507-284-8884
• Email: [email protected]

Clinical Studies in Depth

Learning all you can about clinical studies helps you prepare to participate.

• Institutional Review Board

The Institutional Review Board protects the rights, privacy, and welfare of participants in research programs conducted by Mayo Clinic and its associated faculty, professional staff, and students.

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Ozempic Cuts Risk of Chronic Kidney Disease Complications, Study Finds

A major clinical trial showed such promising results that the drug’s maker halted it early.

• Share full article

By Dani Blum

Dani Blum has reported on Ozempic and similar drugs since 2022.

Semaglutide, the compound in the blockbuster drugs Ozempic and Wegovy , dramatically reduced the risk of kidney complications, heart issues and death in people with Type 2 diabetes and chronic kidney disease in a major clinical trial, the results of which were published on Friday. The findings could transform how doctors treat some of the sickest patients with chronic kidney disease, which affects more than one in seven adults in the United States but has no cure.

“Those of us who really care about kidney patients spent our whole careers wanting something better,” said Dr. Katherine Tuttle, a professor of medicine at the University of Washington School of Medicine and an author of the study. “And this is as good as it gets.” The research was presented at a European Renal Association meeting in Stockholm on Friday and simultaneously published in The New England Journal of Medicine .

The trial, funded by Ozempic maker Novo Nordisk, was so successful that the company stopped it early . Dr. Martin Holst Lange, Novo Nordisk’s executive vice president of development, said that the company would ask the Food and Drug Administration to update Ozempic’s label to say it can also be used to reduce the progression of chronic kidney disease or complications in people with Type 2 diabetes.

Diabetes is a leading cause of chronic kidney disease, which occurs when the kidneys don’t function as well as they should. In advanced stages, the kidneys are so damaged that they cannot properly filter blood. This can cause fluid and waste to build up in the blood, which can exacerbate high blood pressure and raise the risk of heart disease and stroke, said Dr. Subramaniam Pennathur, the chief of the nephrology division at Michigan Medicine.

The study included 3,533 people with kidney disease and Type 2 diabetes, about half of whom took a weekly injection of semaglutide, and half of whom took a weekly placebo shot.

Researchers followed up with participants after a median period of around three and a half years and found that those who took semaglutide had a 24 percent lower likelihood of having a major kidney disease event, like losing at least half of their kidney function, or needing dialysis or a kidney transplant. There were 331 such events among the semaglutide group, compared with 410 in the placebo group.

People who received semaglutide were much less likely to die from cardiovascular issues, or from any cause at all, and had slower rates of kidney decline.

Kidney damage often occurs gradually, and people typically do not show symptoms until the disease is in advanced stages. Doctors try to slow the decline of kidney function with existing medications and lifestyle modifications, said Dr. Melanie Hoenig, a nephrologist at Beth Israel Deaconess Medical Center who was not involved with the study. But even with treatment, the disease can progress to the point that patients need dialysis, a treatment that removes waste and excess fluids from the blood, or kidney transplants.

The participants in the study were extremely sick — the severe complications seen in some study participants are more likely to occur in people the later stages of chronic kidney disease, said Dr. George Bakris, a professor of medicine at the University of Chicago Medicine and an author of the study. Most participants in the trial were already taking medication for chronic kidney disease.

For people with advanced kidney disease, in particular, the findings are promising. “We can help people live longer,” said Dr. Vlado Perkovic, a nephrologist and renal researcher at the University of New South Wales, Sydney, and another author of the study.

While the data shows clear benefits, even the researchers studying drugs like Ozempic aren’t sure how, exactly, they help the kidneys. One leading theory is that semaglutide may reduce inflammation, which exacerbates kidney disease.

And the results come with several caveats: Roughly two-thirds of the participants were men and around two-thirds were white — a limitation of the study, the authors noted, because chronic kidney disease disproportionately affects Black and Indigenous patients. The trial participants taking semaglutide were more likely to stop the drug because of gastrointestinal issues, which are common side effects of Ozempic.

Doctors said they wanted to know whether the drug might benefit patients who have kidney disease but not diabetes, and some also had questions about the potential long-term risks of taking semaglutide.

Still, the results are the latest data to show that semaglutide can do more than treat diabetes or drive weight loss. In March, the F.D.A. authorized Wegovy for reducing the risk of cardiovascular issues in some patients. And scientists are examining semaglutide and tirzepatide, the compound in the rival drugs Mounjaro and Zepbound, for a range of other conditions , including sleep apnea and liver disease.

If the F.D.A. approves the new use, it could drive even more demand for Ozempic, which has faced recurrent shortages .

“I think it’s a game changer,” Dr. Hoenig said, “if I can get it for my patients.”

Dani Blum is a health reporter for The Times. More about Dani Blum

A Close Look at Weight-Loss Drugs

Reduced Disease Complications: Semaglutide, the compound in Ozempic and Wegovy, dramatically reduced the risk of kidney complications , heart issues and death in people with Type 2 diabetes and chronic kidney disease in a major clinical trial.

Supplement Stores: GNC and the Vitamin Shoppe are redesigning displays and taking other steps  to appeal to people who are taking or are interested in drugs like Ozempic and Wegovy.

Senate Investigation: A Senate committee is investigating the prices that Novo Nordisk charges  for Ozempic and Wegovy, which are highly effective at treating diabetes and obesity but carry steep price tags.

A Company Remakes Itself: Novo Nordisk’s factories work nonstop turning out Ozempic and Wegovy , but the Danish company has far bigger ambitions.

Transforming a Small Danish Town: In Kalundborg, population under 17,000, Novo Nordisk is making huge investments to increase production  of Ozempic and Wegovy.

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Is College Worth It?

As economic outcomes for young adults with and without degrees have improved, americans hold mixed views on the value of college, table of contents.

• Labor force trends and economic outcomes for young adults
• Economic outcomes for young men
• Economic outcomes for young women
• Wealth trends for households headed by a young adult
• The importance of a four-year college degree
• Getting a high-paying job without a college degree
• Do Americans think their education prepared them for the workplace?
• Is college worth the cost?
• Acknowledgments
• The American Trends Panel survey methodology
• Current Population Survey methodology
• Survey of Consumer Finances methodology

Pew Research Center conducted this study to better understand public views on the importance of a four-year college degree. The study also explores key trends in the economic outcomes of young adults among those who have and have not completed a four-year college degree.

The analysis in this report is based on three data sources. The labor force, earnings, hours, household income and poverty characteristics come from the U.S. Census Bureau’s Annual Social and Economic Supplement of the Current Population Survey. The findings on net worth are based on the Federal Reserve’s Survey of Consumer Finances.

The data on public views on the value of a college degree was collected as part of a Center survey of 5,203 U.S. adults conducted Nov. 27 to Dec. 3, 2023. Everyone who took part in the survey is a member of Pew Research Center’s American Trends Panel (ATP), an online survey panel that is recruited through national, random sampling of residential addresses. Address-based sampling ensures that nearly all U.S. adults have a chance of selection. The survey is weighted to be representative of the U.S. adult population by gender, race, ethnicity, partisan affiliation, education and other categories. Read more about the ATP’s methodology .

Here are the questions used for this report , along with responses, and the survey’s methodology .

Young adults refers to Americans ages 25 to 34.

Noncollege adults include those who have some college education as well as those who graduated from high school but did not attend college. Adults who have not completed high school are not included in the analysis of noncollege adults. About 6% of young adults have not completed high school. Trends in some labor market outcomes for those who have not finished high school are impacted by changes in the foreign-born share of the U.S. population. The Census data used in this analysis did not collect information on nativity before 1994.

Some college includes those with an associate degree and those who attended college but did not obtain a degree.

The some college or less population refers to adults who have some college education, those with a high school diploma only and those who did not graduate high school.

A full-time, full-year worker works at least 50 weeks per year and usually 35 hours a week or more.

The labor force includes all who are employed and those who are unemployed but looking for work.

The labor force participation rate is the share of a population that is in the labor force.

Young adults living independently refers to those who are not living in the home of either of their parents.

Household income is the sum of incomes received by all members of the household ages 15 and older. Income is the sum of earnings from work, capital income such as interest and dividends, rental income, retirement income, and transfer income (such as government assistance) before payments for such things as personal income taxes, Social Security and Medicare taxes, union dues, etc. Non-cash transfers such as food stamps, health benefits, subsidized housing and energy assistance are not included. As household income is pretax, it does not include stimulus payments or tax credits for earned income and children/dependent care.

Net worth, or wealth, is the difference between the value of what a household owns (assets) and what it owes (debts).

All references to party affiliation include those who lean toward that party. Republicans include those who identify as Republicans and those who say they lean toward the Republican Party. Democrats include those who identify as Democrats and those who say they lean toward the Democratic Party.

At a time when many Americans are questioning the value of a four-year college degree, economic outcomes for young adults without a degree are improving.

After decades of falling wages, young U.S. workers (ages 25 to 34) without a bachelor’s degree have seen their earnings increase over the past 10 years. Their overall wealth has gone up too, and fewer are living in poverty today.

Things have also improved for young college graduates over this period. As a result, the gap in earnings between young adults with and without a college degree has not narrowed.

The public has mixed views on the importance of having a college degree, and many have doubts about whether the cost is worth it, according to a new Pew Research Center survey.

• Only one-in-four U.S. adults say it’s extremely or very important to have a four-year college degree in order to get a well-paying job in today’s economy. About a third (35%) say a college degree is somewhat important, while 40% say it’s not too or not at all important.
• Roughly half (49%) say it’s less important to have a four-year college degree today in order to get a well-paying job than it was 20 years ago; 32% say it’s more important, and 17% say it’s about as important as it was 20 years ago.
• Only 22% say the cost of getting a four-year college degree today is worth it even if someone has to take out loans. Some 47% say the cost is worth it only if someone doesn’t have to take out loans. And 29% say the cost is not worth it.

These findings come amid rising tuition costs and mounting student debt . Views on the cost of college differ by Americans’ level of education. But even among four-year college graduates, only about a third (32%) say college is worth the cost even if someone has to take out loans – though they are more likely than those without a degree to say this.

Four-year college graduates (58%) are much more likely than those without a college degree (26%) to say their education was extremely or very useful in giving them the skills and knowledge they needed to get a well-paying job. (This finding excludes the 9% of respondents who said this question did not apply to them.)

Views on the importance of college differ widely by partisanship. Republicans and Republican-leaning independents are more likely than Democrats and Democratic leaners to say:

• It’s not too or not at all important to have a four-year college degree in order to get a well-paying job (50% of Republicans vs. 30% of Democrats)
• A college degree is less important now than it was 20 years ago (57% vs. 43%)
• It’s extremely or very likely someone without a four-year college degree can get a well-paying job (42% vs. 26%)

At the same time that the public is expressing doubts about the value of college, a new Center analysis of government data finds young adults without a college degree are doing better on some key measures than they have in recent years.

A narrow majority of workers ages 25 to 34 do not have a four-year college degree (54% in 2023). Earnings for these young workers mostly trended downward from the mid-1970s until roughly a decade ago.

Outcomes have been especially poor for young men without a college degree. Other research has shown that this group saw falling labor force participation and sagging earnings starting in the early 1970s , but the last decade has marked a turning point.

This analysis looks at young men and young women separately because of their different experiences in the labor force.

Trends for young men

• Labor force participation: The share of young men without a college degree who were working or looking for work dropped steadily from 1970 until about 2014. Our new analysis suggests things have stabilized somewhat for this group over the past decade. Meanwhile, labor force participation among young men with a four-year degree has remained mostly flat.
• Full-time, full-year employment: The share of employed young men without a college degree who are working full time and year-round has varied somewhat over the years – trending downward during recessions. It’s risen significantly since the Great Recession of 2007-09, with the exception of a sharp dip in 2021 due to the COVID-19 pandemic. For employed young men with a college degree, the share working full time, full year has remained more stable over the years.

• Median annual earnings: Since 2014, earnings have risen for young men with some college education and for those whose highest attainment is a high school diploma. Even so, earnings for these groups remain below where they were in the early 1970s. Earnings for young men with a bachelor’s degree have also trended up, for the most part, over the past 10 years.
• Poverty: Among young men without a college degree who are living independently from their parents, the share in poverty has fallen significantly over the last decade. For example, 12% of young men with a high school diploma were living in poverty in 2023, down from a peak of 17% in 2011. The share of young men with a four-year college degree who are in poverty has also fallen and remains below that of noncollege young men.

Trends for young women

• Labor force participation: The shares of young women with and without a college degree in the labor force grew steadily from 1970 to about 1990. Among those without a college degree, the share fell after 2000, and the drop-off was especially sharp for young women with a high school diploma. Since 2014, labor force participation for both groups of young women has increased.
• Full-time, full-year employment: The shares of employed young women working full time and year-round, regardless of their educational attainment, have steadily increased over the decades. There was a decline during and after the Great Recession and again (briefly) in 2021 due to the pandemic. Today, the shares of women working full time, full year are the highest they’ve ever been across education levels.

• Median annual earnings: Median earnings for young women without a college degree were relatively flat from 1970 until about a decade ago. These women did not experience the steady decline in earnings that noncollege young men did over this period. By contrast, earnings have grown over the decades for young women with a college degree. In the past 10 years, earnings for women both with and without a college degree have risen.
• Poverty: As is the case for young men without a college degree, the share of noncollege young women living in poverty has fallen substantially over the past decade. In 2014, 31% of women with a high school diploma who lived independently from their parents were in poverty. By 2023, that share had fallen to 21%. Young women with a college degree remain much less likely to be in poverty than their counterparts with less education.

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From businesses and banks to colleges and churches: americans’ views of u.s. institutions, fewer young men are in college, especially at 4-year schools, key facts about u.s. latinos with graduate degrees, private, selective colleges are most likely to use race, ethnicity as a factor in admissions decisions, most popular, report materials.

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The HPV vaccine prevents head and neck cancers in men, study suggests

The HPV vaccine is linked to a drastic reduction in head and neck cancers in adolescent boys and men, new research finds. 

HPV, or human papillomavirus, is a sexually transmitted infection responsible for virtually all cases of cervical cancer . But the virus is also linked to a number of other cancers , including penile, anal and vaginal cancers. 

It also accounts for the majority — up to 70% — of head and neck cancers , which affect the throat and mouth. Men are about twice as likely to develop these cancers than women, according to the National Cancer Institute.

The HPV vaccine, initially approved for adolescent girls, protects against strains of the virus linked to cervical cancer and has been found to significantly reduce rates of the cancer . But there’s growing evidence that the vaccine also protects against other HPV-related cancers.

“We want males to be thinking about HPV vaccination not just as something that protects female patients, but also male patients,” said Jefferson DeKloe, a research fellow in the department of otolaryngology at Thomas Jefferson University, who specializes in head and neck surgery and who co-authored the research.

The findings will be presented next week at the American Society of Clinical Oncology conference and have not yet been published in a peer-reviewed journal. 

Prior research showed a downward trend in oral infections with HPV strains known to cause cancer. That was a promising sign, said Dr. Glenn J. Hanna, a medical oncologist at the Dana-Farber Cancer Institute’s Center for Head and Neck Oncology, who was not involved in the new research.

“If we can lower the infection rate, we would hope that we would see what we are seeing now, a decline in cancer rates,” Hanna said. “This is an important evolution of the story.” 

The new study analyzed health records from a national database that included nearly 3.5 million people in the United States ages 9 to 39 who had received any vaccination — HPV or otherwise — from 2010 through 2023. About 1.5 million were male, half of whom had been vaccinated against cancer-causing strains of HPV. Nearly 1 million were females who had been vaccinated against HPV. 

The researchers compared the rates of HPV-linked cancers — including head and neck, anal, penile, and cervical cancers — in people who had received the HPV vaccine to those who hadn’t. They found being vaccinated reduced the overall risk of HPV-related cancers in males by 54%, a decrease driven primarily by a drop in head and neck cancers. Females were about 30% less likely to develop any type of HPV-related cancer, including cervical cancer. 

Most cases of head and neck cancer are in people older than 50. Since the U.S. is only about a decade into widespread HPV vaccination in both males and females, the vaccinated generation hasn’t reached this age yet. HPV typically infects younger people and takes decades for chronic infection to lead to cancer.

“These are the early results of a larger phenomenon we are going to watch play out over the next 20 or 30 years,” DeKloe said, noting that experts don’t expect to see the full effect HPV vaccination has on cancer rates until the largely vaccinated generation is older. 

A second study, which will also be presented at the ASCO conference next week and is not yet published in a peer-reviewed journal, found that HPV vaccination rates have been on the rise in the U.S. from 2011 through early 2020, including in all racial and ethnic groups.

HPV vaccination wasn’t recommended for males until 2011, five years after the Centers for Disease Control and Prevention recommended the vaccine series for girls. The HPV vaccine is now recommended for all adolescents starting as young as age 9, but can also be given to adults up to age 45. 

In the new study, which included children and young adults ages 9 to 26, the increase was largely driven by growing HPV vaccine uptake among males. Although overall HPV vaccination rates among males still lag behind females — about 36% compared to about 50% of those in the 9 to 26 age group — these rates are accelerating. 

“The gap is narrowing between males and females and eventually I would hope that they would meet up,” said Dr. Danh Nguyen, a resident physician at University of Texas Southwestern Medical Center, who led the research. 

Although vaccination efforts have focused on adolescents, adults should also consider getting vaccinated if they weren’t when they were younger, said Dr. Nancy Lee, service chief of head and neck radiation oncology at Memorial Sloan Kettering Cancer Center in New York City, who was not involved with either study. 

“If you are in your 20s or 30s, you can still get the vaccination. Even if you are 45, there is no reason you cannot get vaccinated because we have a population that lives a long time,” Lee said. 

Nguyen said it’s important that conversations about HPV vaccination continue to focus on the prevention of all cancers, including head and neck cancers that are more prevalent in men, rather than solely on cervical cancer prevention.

Hanna said stigma around HPV being a sexually transmitted infection has made discussions around vaccinating adolescents a sticky subject in the past, but that clear data showing the impact vaccination rates have on HPV-related cancers is shifting the narrative. 

“HPV vaccination is cancer prevention,” Hanna said. “The bottom line is that we are preventing cancers broadly by getting people vaccinated younger.”

Kaitlin Sullivan is a contributor for NBCNews.com who has worked with NBC News Investigations. She reports on health, science and the environment and is a graduate of the Craig Newmark Graduate School of Journalism at City University of New York.

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In brief: what types of studies are there.

Last Update: September 8, 2016 ; Next update: 2024.

There are various types of scientific studies such as experiments and comparative analyses, observational studies, surveys, or interviews. The choice of study type will mainly depend on the research question being asked.

When making decisions, patients and doctors need reliable answers to a number of questions. Depending on the medical condition and patient's personal situation, the following questions may be asked:

• What is the cause of the condition?
• What is the natural course of the disease if left untreated?
• What will change because of the treatment?
• How many other people have the same condition?
• How do other people cope with it?

Each of these questions can best be answered by a different type of study.

In order to get reliable results, a study has to be carefully planned right from the start. One thing that is especially important to consider is which type of study is best suited to the research question. A study protocol should be written and complete documentation of the study's process should also be done. This is vital in order for other scientists to be able to reproduce and check the results afterwards.

The main types of studies are randomized controlled trials (RCTs), cohort studies, case-control studies and qualitative studies.

• Randomized controlled trials

If you want to know how effective a treatment or diagnostic test is, randomized trials provide the most reliable answers. Because the effect of the treatment is often compared with "no treatment" (or a different treatment), they can also show what happens if you opt to not have the treatment or diagnostic test.

When planning this type of study, a research question is stipulated first. This involves deciding what exactly should be tested and in what group of people. In order to be able to reliably assess how effective the treatment is, the following things also need to be determined before the study is started:

• How long the study should last
• How many participants are needed
• How the effect of the treatment should be measured

For instance, a medication used to treat menopause symptoms needs to be tested on a different group of people than a flu medicine. And a study on treatment for a stuffy nose may be much shorter than a study on a drug taken to prevent strokes .

“Randomized” means divided into groups by chance. In RCTs participants are randomly assigned to one of two or more groups. Then one group receives the new drug A, for example, while the other group receives the conventional drug B or a placebo (dummy drug). Things like the appearance and taste of the drug and the placebo should be as similar as possible. Ideally, the assignment to the various groups is done "double blinded," meaning that neither the participants nor their doctors know who is in which group.

The assignment to groups has to be random in order to make sure that only the effects of the medications are compared, and no other factors influence the results. If doctors decided themselves which patients should receive which treatment, they might – for instance – give the more promising drug to patients who have better chances of recovery. This would distort the results. Random allocation ensures that differences between the results of the two groups at the end of the study are actually due to the treatment and not something else.

Randomized controlled trials provide the best results when trying to find out if there is a cause-and-effect relationship. RCTs can answer questions such as these:

• Is the new drug A better than the standard treatment for medical condition X?
• Does regular physical activity speed up recovery after a slipped disk when compared to passive waiting?
• Cohort studies

A cohort is a group of people who are observed frequently over a period of many years – for instance, to determine how often a certain disease occurs. In a cohort study, two (or more) groups that are exposed to different things are compared with each other: For example, one group might smoke while the other doesn't. Or one group may be exposed to a hazardous substance at work, while the comparison group isn't. The researchers then observe how the health of the people in both groups develops over the course of several years, whether they become ill, and how many of them pass away. Cohort studies often include people who are healthy at the start of the study. Cohort studies can have a prospective (forward-looking) design or a retrospective (backward-looking) design. In a prospective study, the result that the researchers are interested in (such as a specific illness) has not yet occurred by the time the study starts. But the outcomes that they want to measure and other possible influential factors can be precisely defined beforehand. In a retrospective study, the result (the illness) has already occurred before the study starts, and the researchers look at the patient's history to find risk factors.

Cohort studies are especially useful if you want to find out how common a medical condition is and which factors increase the risk of developing it. They can answer questions such as:

• How does high blood pressure affect heart health?
• Does smoking increase your risk of lung cancer?

For example, one famous long-term cohort study observed a group of 40,000 British doctors, many of whom smoked. It tracked how many doctors died over the years, and what they died of. The study showed that smoking caused a lot of deaths, and that people who smoked more were more likely to get ill and die.

• Case-control studies

Case-control studies compare people who have a certain medical condition with people who do not have the medical condition, but who are otherwise as similar as possible, for example in terms of their sex and age. Then the two groups are interviewed, or their medical files are analyzed, to find anything that might be risk factors for the disease. So case-control studies are generally retrospective.

Case-control studies are one way to gain knowledge about rare diseases. They are also not as expensive or time-consuming as RCTs or cohort studies. But it is often difficult to tell which people are the most similar to each other and should therefore be compared with each other. Because the researchers usually ask about past events, they are dependent on the participants’ memories. But the people they interview might no longer remember whether they were, for instance, exposed to certain risk factors in the past.

Still, case-control studies can help to investigate the causes of a specific disease, and answer questions like these:

• Do HPV infections increase the risk of cervical cancer ?
• Is the risk of sudden infant death syndrome (“cot death”) increased by parents smoking at home?

Cohort studies and case-control studies are types of "observational studies."

• Cross-sectional studies

Many people will be familiar with this kind of study. The classic type of cross-sectional study is the survey: A representative group of people – usually a random sample – are interviewed or examined in order to find out their opinions or facts. Because this data is collected only once, cross-sectional studies are relatively quick and inexpensive. They can provide information on things like the prevalence of a particular disease (how common it is). But they can't tell us anything about the cause of a disease or what the best treatment might be.

Cross-sectional studies can answer questions such as these:

• How tall are German men and women at age 20?
• How many people have cancer screening?
• Qualitative studies

This type of study helps us understand, for instance, what it is like for people to live with a certain disease. Unlike other kinds of research, qualitative research does not rely on numbers and data. Instead, it is based on information collected by talking to people who have a particular medical condition and people close to them. Written documents and observations are used too. The information that is obtained is then analyzed and interpreted using a number of methods.

Qualitative studies can answer questions such as these:

• How do women experience a Cesarean section?
• What aspects of treatment are especially important to men who have prostate cancer ?
• How reliable are the different types of studies?

Each type of study has its advantages and disadvantages. It is always important to find out the following: Did the researchers select a study type that will actually allow them to find the answers they are looking for? You can’t use a survey to find out what is causing a particular disease, for instance.

It is really only possible to draw reliable conclusions about cause and effect by using randomized controlled trials. Other types of studies usually only allow us to establish correlations (relationships where it isn’t clear whether one thing is causing the other). For instance, data from a cohort study may show that people who eat more red meat develop bowel cancer more often than people who don't. This might suggest that eating red meat can increase your risk of getting bowel cancer. But people who eat a lot of red meat might also smoke more, drink more alcohol, or tend to be overweight. The influence of these and other possible risk factors can only be determined by comparing two equal-sized groups made up of randomly assigned participants.

That is why randomized controlled trials are usually the only suitable way to find out how effective a treatment is. Systematic reviews, which summarize multiple RCTs , are even better. In order to be good-quality, though, all studies and systematic reviews need to be designed properly and eliminate as many potential sources of error as possible.

• German Network for Evidence-based Medicine. Glossar: Qualitative Forschung.  Berlin: DNEbM; 2011. 
• Greenhalgh T. Einführung in die Evidence-based Medicine: kritische Beurteilung klinischer Studien als Basis einer rationalen Medizin. Bern: Huber; 2003. 
• Institute for Quality and Efficiency in Health Care (IQWiG, Germany). General methods . Version 5.0. Cologne: IQWiG; 2017.
• Klug SJ, Bender R, Blettner M, Lange S. Wichtige epidemiologische Studientypen. Dtsch Med Wochenschr 2007; 132:e45-e47. [ PubMed : 17530597 ]
• Schäfer T. Kritische Bewertung von Studien zur Ätiologie. In: Kunz R, Ollenschläger G, Raspe H, Jonitz G, Donner-Banzhoff N (eds.). Lehrbuch evidenzbasierte Medizin in Klinik und Praxis. Cologne: Deutscher Ärzte-Verlag; 2007.

IQWiG health information is written with the aim of helping people understand the advantages and disadvantages of the main treatment options and health care services.

Because IQWiG is a German institute, some of the information provided here is specific to the German health care system. The suitability of any of the described options in an individual case can be determined by talking to a doctor. informedhealth.org can provide support for talks with doctors and other medical professionals, but cannot replace them. We do not offer individual consultations.

Our information is based on the results of good-quality studies. It is written by a team of health care professionals, scientists and editors, and reviewed by external experts. You can find a detailed description of how our health information is produced and updated in our methods.

• Cite this Page InformedHealth.org [Internet]. Cologne, Germany: Institute for Quality and Efficiency in Health Care (IQWiG); 2006-. In brief: What types of studies are there? [Updated 2016 Sep 8].

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Groundbreaking Research Shows Ancient Egyptians Were Conducting Cancer Surgery Over 4,000 Years Ago

By putting an ancient skull under the microscope, scientists are proving that cancer research is about 1,000 years older than previously thought

Julia Binswanger

Daily Correspondent

A new study published in the journal Frontiers in Medicine is radically changing ideas about early cancer studies.

Researchers examining an over 4,000-year-old Egyptian skull have found that ancient doctors may have used surgical intervention to treat brain cancer.

"What we found is the first evidence of a surgical intervention directly related to cancer," Edgard Camarós , paleopathologist at the University of Santiago de Compostela in Spain and co-author of the research paper, tells Live Science ’s Emily Cooke. "This is where modern medicine starts."

The skull, part of the University of Cambridge 's Duckworth Collection , dates from between 2687 and 2345 B.C.E. and belonged to a 30 to 35-year-old man. Since the mid-19th century, experts have been examining the Egyptian man’s cranial remains.

Studying cancer in the ancient world can be tricky because the disease often presents in the soft tissue, and experts do not have access to a patient’s medical history. Previous research on the skull showed that the man had suffered from one large brain tumor and 30 small metastasized lesions.

Through microscope and microtomography scans, Camarós and his team found cut marks on the skull’s edges right where the cancerous lesions appeared. They concluded that a sharp metal tool was responsible for the incisions. Thus, ancient doctors were not only aware of the cancer, they were likely looking to learn more about it through surgical intervention.

“When we first observed the cut marks under the microscope, we could not believe what was in front of us,” says Tatiana Tondini , a researcher at the University of Tübingen and study co-author, in a statement.

“There was an uncomfortable silence in the room, because we knew what we had just discovered,” Camarós tells the New York Times ’ Jordan Pearson.

Before the study was published, researchers believed that the oldest description of cancer came from the Edwin Smith Papyrus , an ancient Egyptian medical text from around 1600 B.C.E. The new research changes the timeline on the first cancer treatments in human history, moving the date up about 1,000 years earlier.

Still, the researchers do not know whether doctors cut into the skull while the patient was still living or shortly after his death for a cancer-related autopsy.

“If those cut marks were done with that person alive, we’re talking about some kind of treatment directly related to the cancer,” Camarós tells CNN . He adds that either way, “it’s amazing to think that they performed a surgical intervention.”

The researchers also found other evidence of ancient Egyptian medicine.

The team looked at the skull of a woman over 50 years old who lived between 664 and 343 B.C.E. The woman had two lesions related to a traumatic head injury that had healed. In turn, experts believe that someone attacked her with a sharp weapon and she likely survived with the help of medical treatment. Her skull also had a cancer-related lesion, but there weren’t signs she received treatment for it.

With this new evidence, Camarós and his team are wondering if other ancient societies studied cancer as well. 

He tells Live Science , "If we know that more than 4,000 years ago, ancient Egyptians were trying to understand cancer at a surgical level, we are absolutely convinced that this is just the beginning of something that started many, many thousands of years ago."

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Julia Binswanger is a freelance arts and culture reporter based in Chicago. Her work has been featured in WBEZ,  Chicago magazine,  Rebellious magazine and  PC magazine. 

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AI risks harming scientific research, study warns

The Royal Society warns that results can be unreliable or untrustworthy, and poor at solving real world problems

Overdependence on ‘opaque’ AI systems in research could make scientific findings less reliable and less useful in the real world, a report by the Royal Society has found.

The complexity and ‘black box’ nature of sophisticated machine learning models mean their outputs can't always be explained by the researchers using them.

This, researchers warned, can make them unreliable or untrustworthy, and limits their usefulness in terms of solving real world challenges.

"This report captures how the rapid adoption of AI across scientific disciplines is transforming research and enabling leaps in understanding that would not have been thinkable a decade ago," said Professor Alison Noble, vice president of the Royal Society and chair of the report’s working group.

"While AI systems are useful, they are not perfect. We should think of them almost like a scientific peer; they can offer valuable insights, but you would expect to be able to verify them yourself – and that isn’t always the case with current AI studies."

Challenges identified by the report include reproducibility, in which other researchers can't replicate experiments carried out using AI tools; interdisciplinarity, where limited collaboration between AI and non-AI disciplines can lead to a less rigorous uptake of AI across domains; and the environmental costs of the high energy consumption required to operate large compute infrastructure.

The report warned there are other factors too - such as pressure on scientific researchers to be ‘good at AI’ rather than ‘good at science’. Changing incentives across the scientific ecosystem, the report suggested, are pushing them to use advanced AI techniques at the expense of more conventional methodologies.

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However, the report also details the opportunities for the use of AI in scientific research, used particularly in fields such as medicine, materials science, robotics , agriculture, genetics, and computer science .

The main techniques include artificial neural networks, deep learning , natural language processing (NLP), and image recognition.

The report noted that while China and the US lead on, respectively, the number and value of patents filed, the UK is well positioned for growth. While it ranks tenth globally on patents, the UK holds second place in Europe behind Germany, and has a 14.7% share of the AI life sciences market.

"Science is constantly enjoying the introduction of disruptive new methodologies, from the microscope to computers, but adoption can be limited by things like cost, availability of the technology, and skills," said Dr Peter Dayan, director of the Max Planck Institute for Biological Cybernetics and a member of the working group.

"Now machine learning is set to transform vast swathes of research, we need to ask what that requires in terms of access. The report's recommendations look at how we can achieve that confluence of high-quality data, processing power and researcher skills in a suitably equitable manner."

This involves establishing ‘open science’, environmental, and ethical frameworks for AI-based research to help make sure that findings are accurate, reproducible and support the public good.

There should also be investment in ‘CERN-style’ regional and cross-sector AI infrastructure, to ensure all scientific disciplines can access the computing power and data resources to conduct rigorous research and maintain the competitiveness of non-industry researchers.

Finally, the report recommends, scientific researchers should be encouraged to become more AI-literate, and they should collaborate with developers to make sure their tools are accessible and usable.

Emma Woollacott is a freelance journalist writing for publications including the BBC, Private Eye, Forbes, Raconteur and specialist technology titles.

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