meaning of study in research

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

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

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Why is research important?

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

What is the purpose of research?

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

What are the characteristics of research?

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

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

Types of research

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

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

Types of research methods

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

Basic steps involved in the research process

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

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

How to ensure research accuracy?

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

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

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

References:

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

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Study designs: Part 1 – An overview and classification

Priya ranganathan, rakesh aggarwal.

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Address for correspondence: Dr. Priya Ranganathan, Department of Anaesthesiology, Tata Memorial Centre, Ernest Borges Road, Parel, Mumbai - 400 012, Maharashtra, India. E-mail: [email protected]

This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.

There are several types of research study designs, each with its inherent strengths and flaws. The study design used to answer a particular research question depends on the nature of the question and the availability of resources. In this article, which is the first part of a series on “study designs,” we provide an overview of research study designs and their classification. The subsequent articles will focus on individual designs.

Keywords: Epidemiologic methods, research design, research methodology

INTRODUCTION

Research study design is a framework, or the set of methods and procedures used to collect and analyze data on variables specified in a particular research problem.

Research study designs are of many types, each with its advantages and limitations. The type of study design used to answer a particular research question is determined by the nature of question, the goal of research, and the availability of resources. Since the design of a study can affect the validity of its results, it is important to understand the different types of study designs and their strengths and limitations.

There are some terms that are used frequently while classifying study designs which are described in the following sections.

A variable represents a measurable attribute that varies across study units, for example, individual participants in a study, or at times even when measured in an individual person over time. Some examples of variables include age, sex, weight, height, health status, alive/dead, diseased/healthy, annual income, smoking yes/no, and treated/untreated.

Exposure (or intervention) and outcome variables

A large proportion of research studies assess the relationship between two variables. Here, the question is whether one variable is associated with or responsible for change in the value of the other variable. Exposure (or intervention) refers to the risk factor whose effect is being studied. It is also referred to as the independent or the predictor variable. The outcome (or predicted or dependent) variable develops as a consequence of the exposure (or intervention). Typically, the term “exposure” is used when the “causative” variable is naturally determined (as in observational studies – examples include age, sex, smoking, and educational status), and the term “intervention” is preferred where the researcher assigns some or all participants to receive a particular treatment for the purpose of the study (experimental studies – e.g., administration of a drug). If a drug had been started in some individuals but not in the others, before the study started, this counts as exposure, and not as intervention – since the drug was not started specifically for the study.

Observational versus interventional (or experimental) studies

Observational studies are those where the researcher is documenting a naturally occurring relationship between the exposure and the outcome that he/she is studying. The researcher does not do any active intervention in any individual, and the exposure has already been decided naturally or by some other factor. For example, looking at the incidence of lung cancer in smokers versus nonsmokers, or comparing the antenatal dietary habits of mothers with normal and low-birth babies. In these studies, the investigator did not play any role in determining the smoking or dietary habit in individuals.

For an exposure to determine the outcome, it must precede the latter. Any variable that occurs simultaneously with or following the outcome cannot be causative, and hence is not considered as an “exposure.”

Observational studies can be either descriptive (nonanalytical) or analytical (inferential) – this is discussed later in this article.

Interventional studies are experiments where the researcher actively performs an intervention in some or all members of a group of participants. This intervention could take many forms – for example, administration of a drug or vaccine, performance of a diagnostic or therapeutic procedure, and introduction of an educational tool. For example, a study could randomly assign persons to receive aspirin or placebo for a specific duration and assess the effect on the risk of developing cerebrovascular events.

Descriptive versus analytical studies

Descriptive (or nonanalytical) studies, as the name suggests, merely try to describe the data on one or more characteristics of a group of individuals. These do not try to answer questions or establish relationships between variables. Examples of descriptive studies include case reports, case series, and cross-sectional surveys (please note that cross-sectional surveys may be analytical studies as well – this will be discussed in the next article in this series). Examples of descriptive studies include a survey of dietary habits among pregnant women or a case series of patients with an unusual reaction to a drug.

Analytical studies attempt to test a hypothesis and establish causal relationships between variables. In these studies, the researcher assesses the effect of an exposure (or intervention) on an outcome. As described earlier, analytical studies can be observational (if the exposure is naturally determined) or interventional (if the researcher actively administers the intervention).

Directionality of study designs

Based on the direction of inquiry, study designs may be classified as forward-direction or backward-direction. In forward-direction studies, the researcher starts with determining the exposure to a risk factor and then assesses whether the outcome occurs at a future time point. This design is known as a cohort study. For example, a researcher can follow a group of smokers and a group of nonsmokers to determine the incidence of lung cancer in each. In backward-direction studies, the researcher begins by determining whether the outcome is present (cases vs. noncases [also called controls]) and then traces the presence of prior exposure to a risk factor. These are known as case–control studies. For example, a researcher identifies a group of normal-weight babies and a group of low-birth weight babies and then asks the mothers about their dietary habits during the index pregnancy.

Prospective versus retrospective study designs

The terms “prospective” and “retrospective” refer to the timing of the research in relation to the development of the outcome. In retrospective studies, the outcome of interest has already occurred (or not occurred – e.g., in controls) in each individual by the time s/he is enrolled, and the data are collected either from records or by asking participants to recall exposures. There is no follow-up of participants. By contrast, in prospective studies, the outcome (and sometimes even the exposure or intervention) has not occurred when the study starts and participants are followed up over a period of time to determine the occurrence of outcomes. Typically, most cohort studies are prospective studies (though there may be retrospective cohorts), whereas case–control studies are retrospective studies. An interventional study has to be, by definition, a prospective study since the investigator determines the exposure for each study participant and then follows them to observe outcomes.

The terms “prospective” versus “retrospective” studies can be confusing. Let us think of an investigator who starts a case–control study. To him/her, the process of enrolling cases and controls over a period of several months appears prospective. Hence, the use of these terms is best avoided. Or, at the very least, one must be clear that the terms relate to work flow for each individual study participant, and not to the study as a whole.

Classification of study designs

Figure 1 depicts a simple classification of research study designs. The Centre for Evidence-based Medicine has put forward a useful three-point algorithm which can help determine the design of a research study from its methods section:[ 1 ]

Classification of research study designs

Does the study describe the characteristics of a sample or does it attempt to analyze (or draw inferences about) the relationship between two variables? – If no, then it is a descriptive study, and if yes, it is an analytical (inferential) study

If analytical, did the investigator determine the exposure? – If no, it is an observational study, and if yes, it is an experimental study

If observational, when was the outcome determined? – at the start of the study (case–control study), at the end of a period of follow-up (cohort study), or simultaneously (cross sectional).

In the next few pieces in the series, we will discuss various study designs in greater detail.

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1. Centre for Evidence-Based Medicine. Study Designs. 2016. [Last accessed on 2018 Sep 04]. Available from: https://www.cebm.net/2014/04/study-designs/
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In brief: what types of studies are there.

Last Update: March 25, 2020 ; 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 causal relationship. That means finding out whether a certain effect is actually due to the medication being tested. 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 disc 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.

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 2004; 129: T7-T10. [ PubMed : 17530597 ]
Schäfer T. Kritische Bewertung von Studien zur Ätiologie. In: Kunz R, Ollenschläger G, Raspe H, Jonitz G, Donner-Banzhoff N (Ed). 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 2020 Mar 25].