research type vs research design

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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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Home » Research Design – Types, Methods and Examples

Research Design – Types, Methods and Examples

Table of Contents

Research design is the framework or blueprint that guides the collection, measurement, and analysis of data in a study. It provides a structured approach to answering research questions, ensuring that the study’s goals are met in an organized, reliable, and valid manner. Research design is crucial as it directly impacts the study’s quality, credibility, and findings.

Research Design

Research design is a systematic plan outlining how a study is conducted, including methods of data collection, procedures, and tools for analysis. It aligns the research question with the appropriate methods, ensuring that the study remains focused, feasible, and ethically sound.

Purpose of Research Design :

Provides a structured approach for data collection and analysis.
Ensures consistency in the research process.
Enhances the reliability and validity of findings.
Minimizes bias by defining clear procedures and controls.

Types of Research Design

Research designs are typically classified into three main types: qualitative , quantitative , and mixed methods . Each type serves different purposes and is selected based on the nature of the research question, objectives, and resources.

1. Qualitative Research Design

Definition : Qualitative research focuses on exploring complex phenomena, understanding individual experiences, and generating insights into social or human behavior. It often involves non-numerical data, such as interviews, observations, and textual analysis.
Case Study : In-depth analysis of a specific individual, group, or event.
Ethnography : Study of cultural groups and practices within their natural setting.
Grounded Theory : Development of a theory based on observed data.
Phenomenology : Exploration of lived experiences and perceptions.
Example : A case study on how remote work impacts employee well-being by conducting interviews with employees from various industries to gather personal insights and themes.

2. Quantitative Research Design

Definition : Quantitative research is focused on quantifying variables and using statistical analysis to test hypotheses. It often involves large samples, standardized data collection tools, and numerical data.
Descriptive : Provides a summary of characteristics or behaviors within a population (e.g., surveys, cross-sectional studies).
Correlational : Examines relationships between two or more variables without manipulating them.
Experimental : Involves manipulation of variables to establish cause-and-effect relationships.
Quasi-Experimental : Similar to experimental design but lacks random assignment.
Example : An experimental study investigating the effect of a new teaching method on student test scores, with one group using the new method and a control group using traditional methods.

3. Mixed-Methods Research Design

Definition : Mixed-methods design combines both qualitative and quantitative approaches in a single study, providing a more comprehensive analysis of the research question.
Explanatory Sequential Design : Quantitative data is collected and analyzed first, followed by qualitative data to explain or expand on the quantitative findings.
Exploratory Sequential Design : Qualitative data is collected first to explore a phenomenon, followed by quantitative data to confirm or generalize findings.
Convergent Design : Both qualitative and quantitative data are collected simultaneously and compared to produce integrated insights.
Example : A study on customer satisfaction, first surveying customers to get quantitative data and then conducting follow-up interviews to explore specific customer feedback in detail.

Methods in Research Design

Various methods are used within research designs to collect and analyze data. Each method is selected based on the research question, data type, and study objectives.

1. Survey and Questionnaire

Definition : Surveys and questionnaires are tools for collecting standardized data from large samples. They are often used in descriptive and correlational studies.
Develop questions related to the research objectives.
Distribute to participants via online platforms, paper forms, or face-to-face interviews.
Analyze results using statistical software for quantitative insights.
Example : A survey assessing consumer satisfaction with a new product by collecting data on factors such as ease of use, design, and performance.

2. Interview

Definition : Interviews are qualitative methods that gather in-depth information through direct questioning. They can be structured, semi-structured, or unstructured.
Design interview questions that align with the research goals.
Conduct interviews in person, via phone, or virtually, recording responses for analysis.
Use thematic or content analysis to interpret findings.
Example : Conducting semi-structured interviews with educators to explore their experiences with online teaching during the COVID-19 pandemic.

3. Observation

Definition : Observation involves recording behaviors, actions, or events as they occur naturally. It is often used in ethnographic and case study designs.
Choose between participant (researcher actively engages) or non-participant observation.
Develop an observation checklist or guide for consistency.
Record findings, often through field notes or video, and analyze for patterns.
Example : Observing interactions in a classroom setting to study student engagement with different teaching methods.

4. Experiment

Definition : Experiments involve manipulating variables to examine cause-and-effect relationships. They are commonly used in scientific and clinical research.
Randomly assign participants to control and experimental groups.
Manipulate the independent variable and measure changes in the dependent variable.
Use statistical analysis to interpret results.
Example : A laboratory experiment testing the effectiveness of a new drug on blood pressure by comparing outcomes in treated and untreated groups.

5. Case Study

Definition : A case study is an in-depth investigation of an individual, group, organization, or event to explore underlying principles and patterns.
Select a case that represents the phenomenon of interest.
Use various data sources, including interviews, documents, and observations.
Analyze for unique insights and apply findings to broader contexts.
Example : A case study on the strategies a small business used to survive during an economic recession.

Examples of Research Design Applications

Design : Quantitative, using a survey.
Goal : To understand consumer preferences for eco-friendly packaging.
Method : Survey distributed to a random sample of consumers asking about purchasing behaviors and attitudes toward sustainability.
Design : Experimental, quantitative.
Goal : To study the effect of sleep deprivation on cognitive performance.
Method : Participants are randomly assigned to sleep-deprived and control groups, with cognitive performance measured using standardized tests.
Design : Convergent mixed-methods.
Goal : To evaluate the effectiveness of a new curriculum on student learning.
Method : Collect quantitative data from student test scores and qualitative data from teacher interviews to provide a comprehensive evaluation.
Design : Qualitative, ethnography.
Goal : To study cultural practices in rural communities.
Method : The researcher spends an extended period within the community, observing daily activities and conducting informal interviews.

Tips for Choosing the Right Research Design

Align with Research Question : Choose a design that directly addresses the research question and allows for valid answers.
Consider Data Type : Decide whether the research requires quantitative (numerical) or qualitative (textual or observational) data.
Assess Feasibility : Take into account time, resources, and access to participants when selecting a design.
Ensure Ethical Compliance : Make sure the design is ethically sound, with informed consent and confidentiality for participants.
Anticipate Limitations : Be aware of potential limitations in each design type and how they might affect your findings.

Challenges in Research Design

Sample Selection Bias : Choosing a non-representative sample can lead to biased results and impact the study’s validity.
Data Collection Constraints : Limitations in resources or participant access may affect data quality.
Ethical Concerns : Research involving vulnerable populations or sensitive topics requires careful ethical consideration.
External Validity : Some designs, like case studies, may have limited generalizability beyond the studied context.

Research design is a critical component of the research process, as it determines how a study is structured, conducted, and analyzed. By choosing the appropriate design—whether qualitative, quantitative, or mixed methods—researchers ensure that they answer their questions effectively, producing credible, reliable, and valid results. A solid research design aligns with the study’s objectives, considers resources and ethical issues, and anticipates limitations to provide meaningful contributions to knowledge.

Creswell, J. W., & Creswell, J. D. (2018). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches . SAGE Publications.
Trochim, W. M., & Donnelly, J. P. (2008). The Research Methods Knowledge Base . Cengage Learning.
Saunders, M., Lewis, P., & Thornhill, A. (2019). Research Methods for Business Students . Pearson Education.
Yin, R. K. (2017). Case Study Research and Applications: Design and Methods . SAGE Publications.

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