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• Descriptive Research | Definition, Types, Methods & Examples

Descriptive Research | Definition, Types, Methods & Examples

Published on May 15, 2019 by Shona McCombes . Revised on June 22, 2023.

Descriptive research aims to accurately and systematically describe a population, situation or phenomenon. It can answer what , where , when and how   questions , but not why questions.

A descriptive research design can use a wide variety of research methods  to investigate one or more variables . Unlike in experimental research , the researcher does not control or manipulate any of the variables, but only observes and measures them.

Table of contents

When to use a descriptive research design, descriptive research methods, other interesting articles.

Descriptive research is an appropriate choice when the research aim is to identify characteristics, frequencies, trends, and categories.

It is useful when not much is known yet about the topic or problem. Before you can research why something happens, you need to understand how, when and where it happens.

Descriptive research question examples

• How has the Amsterdam housing market changed over the past 20 years?
• Do customers of company X prefer product X or product Y?
• What are the main genetic, behavioural and morphological differences between European wildcats and domestic cats?
• What are the most popular online news sources among under-18s?
• How prevalent is disease A in population B?

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Descriptive research is usually defined as a type of quantitative research , though qualitative research can also be used for descriptive purposes. The research design should be carefully developed to ensure that the results are valid and reliable .

Survey research allows you to gather large volumes of data that can be analyzed for frequencies, averages and patterns. Common uses of surveys include:

• Describing the demographics of a country or region
• Gauging public opinion on political and social topics
• Evaluating satisfaction with a company’s products or an organization’s services

Observations

Observations allow you to gather data on behaviours and phenomena without having to rely on the honesty and accuracy of respondents. This method is often used by psychological, social and market researchers to understand how people act in real-life situations.

Observation of physical entities and phenomena is also an important part of research in the natural sciences. Before you can develop testable hypotheses , models or theories, it’s necessary to observe and systematically describe the subject under investigation.

Case studies

A case study can be used to describe the characteristics of a specific subject (such as a person, group, event or organization). Instead of gathering a large volume of data to identify patterns across time or location, case studies gather detailed data to identify the characteristics of a narrowly defined subject.

Rather than aiming to describe generalizable facts, case studies often focus on unusual or interesting cases that challenge assumptions, add complexity, or reveal something new about a research problem .

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Normal distribution
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Ecological validity

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

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Home » Descriptive Research Design – Types, Methods and Examples

Descriptive Research Design – Types, Methods and Examples

Table of Contents

Descriptive Research Design

Definition:

Descriptive research design is a type of research methodology that aims to describe or document the characteristics, behaviors, attitudes, opinions, or perceptions of a group or population being studied.

Descriptive research design does not attempt to establish cause-and-effect relationships between variables or make predictions about future outcomes. Instead, it focuses on providing a detailed and accurate representation of the data collected, which can be useful for generating hypotheses, exploring trends, and identifying patterns in the data.

Types of Descriptive Research Design

Types of Descriptive Research Design are as follows:

Cross-sectional Study

This involves collecting data at a single point in time from a sample or population to describe their characteristics or behaviors. For example, a researcher may conduct a cross-sectional study to investigate the prevalence of certain health conditions among a population, or to describe the attitudes and beliefs of a particular group.

Longitudinal Study

This involves collecting data over an extended period of time, often through repeated observations or surveys of the same group or population. Longitudinal studies can be used to track changes in attitudes, behaviors, or outcomes over time, or to investigate the effects of interventions or treatments.

This involves an in-depth examination of a single individual, group, or situation to gain a detailed understanding of its characteristics or dynamics. Case studies are often used in psychology, sociology, and business to explore complex phenomena or to generate hypotheses for further research.

Survey Research

This involves collecting data from a sample or population through standardized questionnaires or interviews. Surveys can be used to describe attitudes, opinions, behaviors, or demographic characteristics of a group, and can be conducted in person, by phone, or online.

Observational Research

This involves observing and documenting the behavior or interactions of individuals or groups in a natural or controlled setting. Observational studies can be used to describe social, cultural, or environmental phenomena, or to investigate the effects of interventions or treatments.

Correlational Research

This involves examining the relationships between two or more variables to describe their patterns or associations. Correlational studies can be used to identify potential causal relationships or to explore the strength and direction of relationships between variables.

Data Analysis Methods

Descriptive research design data analysis methods depend on the type of data collected and the research question being addressed. Here are some common methods of data analysis for descriptive research:

Descriptive Statistics

This method involves analyzing data to summarize and describe the key features of a sample or population. Descriptive statistics can include measures of central tendency (e.g., mean, median, mode) and measures of variability (e.g., range, standard deviation).

Cross-tabulation

This method involves analyzing data by creating a table that shows the frequency of two or more variables together. Cross-tabulation can help identify patterns or relationships between variables.

Content Analysis

This method involves analyzing qualitative data (e.g., text, images, audio) to identify themes, patterns, or trends. Content analysis can be used to describe the characteristics of a sample or population, or to identify factors that influence attitudes or behaviors.

Qualitative Coding

This method involves analyzing qualitative data by assigning codes to segments of data based on their meaning or content. Qualitative coding can be used to identify common themes, patterns, or categories within the data.

Visualization

This method involves creating graphs or charts to represent data visually. Visualization can help identify patterns or relationships between variables and make it easier to communicate findings to others.

Comparative Analysis

This method involves comparing data across different groups or time periods to identify similarities and differences. Comparative analysis can help describe changes in attitudes or behaviors over time or differences between subgroups within a population.

Applications of Descriptive Research Design

Descriptive research design has numerous applications in various fields. Some of the common applications of descriptive research design are:

• Market research: Descriptive research design is widely used in market research to understand consumer preferences, behavior, and attitudes. This helps companies to develop new products and services, improve marketing strategies, and increase customer satisfaction.
• Health research: Descriptive research design is used in health research to describe the prevalence and distribution of a disease or health condition in a population. This helps healthcare providers to develop prevention and treatment strategies.
• Educational research: Descriptive research design is used in educational research to describe the performance of students, schools, or educational programs. This helps educators to improve teaching methods and develop effective educational programs.
• Social science research: Descriptive research design is used in social science research to describe social phenomena such as cultural norms, values, and beliefs. This helps researchers to understand social behavior and develop effective policies.
• Public opinion research: Descriptive research design is used in public opinion research to understand the opinions and attitudes of the general public on various issues. This helps policymakers to develop effective policies that are aligned with public opinion.
• Environmental research: Descriptive research design is used in environmental research to describe the environmental conditions of a particular region or ecosystem. This helps policymakers and environmentalists to develop effective conservation and preservation strategies.

Descriptive Research Design Examples

Here are some real-time examples of descriptive research designs:

• A restaurant chain wants to understand the demographics and attitudes of its customers. They conduct a survey asking customers about their age, gender, income, frequency of visits, favorite menu items, and overall satisfaction. The survey data is analyzed using descriptive statistics and cross-tabulation to describe the characteristics of their customer base.
• A medical researcher wants to describe the prevalence and risk factors of a particular disease in a population. They conduct a cross-sectional study in which they collect data from a sample of individuals using a standardized questionnaire. The data is analyzed using descriptive statistics and cross-tabulation to identify patterns in the prevalence and risk factors of the disease.
• An education researcher wants to describe the learning outcomes of students in a particular school district. They collect test scores from a representative sample of students in the district and use descriptive statistics to calculate the mean, median, and standard deviation of the scores. They also create visualizations such as histograms and box plots to show the distribution of scores.
• A marketing team wants to understand the attitudes and behaviors of consumers towards a new product. They conduct a series of focus groups and use qualitative coding to identify common themes and patterns in the data. They also create visualizations such as word clouds to show the most frequently mentioned topics.
• An environmental scientist wants to describe the biodiversity of a particular ecosystem. They conduct an observational study in which they collect data on the species and abundance of plants and animals in the ecosystem. The data is analyzed using descriptive statistics to describe the diversity and richness of the ecosystem.

How to Conduct Descriptive Research Design

To conduct a descriptive research design, you can follow these general steps:

• Define your research question: Clearly define the research question or problem that you want to address. Your research question should be specific and focused to guide your data collection and analysis.
• Choose your research method: Select the most appropriate research method for your research question. As discussed earlier, common research methods for descriptive research include surveys, case studies, observational studies, cross-sectional studies, and longitudinal studies.
• Design your study: Plan the details of your study, including the sampling strategy, data collection methods, and data analysis plan. Determine the sample size and sampling method, decide on the data collection tools (such as questionnaires, interviews, or observations), and outline your data analysis plan.
• Collect data: Collect data from your sample or population using the data collection tools you have chosen. Ensure that you follow ethical guidelines for research and obtain informed consent from participants.
• Analyze data: Use appropriate statistical or qualitative analysis methods to analyze your data. As discussed earlier, common data analysis methods for descriptive research include descriptive statistics, cross-tabulation, content analysis, qualitative coding, visualization, and comparative analysis.
• I nterpret results: Interpret your findings in light of your research question and objectives. Identify patterns, trends, and relationships in the data, and describe the characteristics of your sample or population.
• Draw conclusions and report results: Draw conclusions based on your analysis and interpretation of the data. Report your results in a clear and concise manner, using appropriate tables, graphs, or figures to present your findings. Ensure that your report follows accepted research standards and guidelines.

When to Use Descriptive Research Design

Descriptive research design is used in situations where the researcher wants to describe a population or phenomenon in detail. It is used to gather information about the current status or condition of a group or phenomenon without making any causal inferences. Descriptive research design is useful in the following situations:

• Exploratory research: Descriptive research design is often used in exploratory research to gain an initial understanding of a phenomenon or population.
• Identifying trends: Descriptive research design can be used to identify trends or patterns in a population, such as changes in consumer behavior or attitudes over time.
• Market research: Descriptive research design is commonly used in market research to understand consumer preferences, behavior, and attitudes.
• Health research: Descriptive research design is useful in health research to describe the prevalence and distribution of a disease or health condition in a population.
• Social science research: Descriptive research design is used in social science research to describe social phenomena such as cultural norms, values, and beliefs.
• Educational research: Descriptive research design is used in educational research to describe the performance of students, schools, or educational programs.

Purpose of Descriptive Research Design

The main purpose of descriptive research design is to describe and measure the characteristics of a population or phenomenon in a systematic and objective manner. It involves collecting data that describe the current status or condition of the population or phenomenon of interest, without manipulating or altering any variables.

The purpose of descriptive research design can be summarized as follows:

• To provide an accurate description of a population or phenomenon: Descriptive research design aims to provide a comprehensive and accurate description of a population or phenomenon of interest. This can help researchers to develop a better understanding of the characteristics of the population or phenomenon.
• To identify trends and patterns: Descriptive research design can help researchers to identify trends and patterns in the data, such as changes in behavior or attitudes over time. This can be useful for making predictions and developing strategies.
• To generate hypotheses: Descriptive research design can be used to generate hypotheses or research questions that can be tested in future studies. For example, if a descriptive study finds a correlation between two variables, this could lead to the development of a hypothesis about the causal relationship between the variables.
• To establish a baseline: Descriptive research design can establish a baseline or starting point for future research. This can be useful for comparing data from different time periods or populations.

Characteristics of Descriptive Research Design

Descriptive research design has several key characteristics that distinguish it from other research designs. Some of the main characteristics of descriptive research design are:

• Objective : Descriptive research design is objective in nature, which means that it focuses on collecting factual and accurate data without any personal bias. The researcher aims to report the data objectively without any personal interpretation.
• Non-experimental: Descriptive research design is non-experimental, which means that the researcher does not manipulate any variables. The researcher simply observes and records the behavior or characteristics of the population or phenomenon of interest.
• Quantitative : Descriptive research design is quantitative in nature, which means that it involves collecting numerical data that can be analyzed using statistical techniques. This helps to provide a more precise and accurate description of the population or phenomenon.
• Cross-sectional: Descriptive research design is often cross-sectional, which means that the data is collected at a single point in time. This can be useful for understanding the current state of the population or phenomenon, but it may not provide information about changes over time.
• Large sample size: Descriptive research design typically involves a large sample size, which helps to ensure that the data is representative of the population of interest. A large sample size also helps to increase the reliability and validity of the data.
• Systematic and structured: Descriptive research design involves a systematic and structured approach to data collection, which helps to ensure that the data is accurate and reliable. This involves using standardized procedures for data collection, such as surveys, questionnaires, or observation checklists.

Advantages of Descriptive Research Design

Descriptive research design has several advantages that make it a popular choice for researchers. Some of the main advantages of descriptive research design are:

• Provides an accurate description: Descriptive research design is focused on accurately describing the characteristics of a population or phenomenon. This can help researchers to develop a better understanding of the subject of interest.
• Easy to conduct: Descriptive research design is relatively easy to conduct and requires minimal resources compared to other research designs. It can be conducted quickly and efficiently, and data can be collected through surveys, questionnaires, or observations.
• Useful for generating hypotheses: Descriptive research design can be used to generate hypotheses or research questions that can be tested in future studies. For example, if a descriptive study finds a correlation between two variables, this could lead to the development of a hypothesis about the causal relationship between the variables.
• Large sample size : Descriptive research design typically involves a large sample size, which helps to ensure that the data is representative of the population of interest. A large sample size also helps to increase the reliability and validity of the data.
• Can be used to monitor changes : Descriptive research design can be used to monitor changes over time in a population or phenomenon. This can be useful for identifying trends and patterns, and for making predictions about future behavior or attitudes.
• Can be used in a variety of fields : Descriptive research design can be used in a variety of fields, including social sciences, healthcare, business, and education.

Limitation of Descriptive Research Design

Descriptive research design also has some limitations that researchers should consider before using this design. Some of the main limitations of descriptive research design are:

• Cannot establish cause and effect: Descriptive research design cannot establish cause and effect relationships between variables. It only provides a description of the characteristics of the population or phenomenon of interest.
• Limited generalizability: The results of a descriptive study may not be generalizable to other populations or situations. This is because descriptive research design often involves a specific sample or situation, which may not be representative of the broader population.
• Potential for bias: Descriptive research design can be subject to bias, particularly if the researcher is not objective in their data collection or interpretation. This can lead to inaccurate or incomplete descriptions of the population or phenomenon of interest.
• Limited depth: Descriptive research design may provide a superficial description of the population or phenomenon of interest. It does not delve into the underlying causes or mechanisms behind the observed behavior or characteristics.
• Limited utility for theory development: Descriptive research design may not be useful for developing theories about the relationship between variables. It only provides a description of the variables themselves.
• Relies on self-report data: Descriptive research design often relies on self-report data, such as surveys or questionnaires. This type of data may be subject to biases, such as social desirability bias or recall bias.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Descriptive research: what it is and how to use it.

8 min read Understanding the who, what and where of a situation or target group is an essential part of effective research and making informed business decisions.

For example you might want to understand what percentage of CEOs have a bachelor’s degree or higher. Or you might want to understand what percentage of low income families receive government support – or what kind of support they receive.

Descriptive research is what will be used in these types of studies.

In this guide we’ll look through the main issues relating to descriptive research to give you a better understanding of what it is, and how and why you can use it.

Free eBook: 2024 global market research trends report

What is descriptive research?

Descriptive research is a research method used to try and determine the characteristics of a population or particular phenomenon.

Using descriptive research you can identify patterns in the characteristics of a group to essentially establish everything you need to understand apart from why something has happened.

Market researchers use descriptive research for a range of commercial purposes to guide key decisions.

For example you could use descriptive research to understand fashion trends in a given city when planning your clothing collection for the year. Using descriptive research you can conduct in depth analysis on the demographic makeup of your target area and use the data analysis to establish buying patterns.

Conducting descriptive research wouldn’t, however, tell you why shoppers are buying a particular type of fashion item.

Descriptive research design

Descriptive research design uses a range of both qualitative research and quantitative data (although quantitative research is the primary research method) to gather information to make accurate predictions about a particular problem or hypothesis.

As a survey method, descriptive research designs will help researchers identify characteristics in their target market or particular population.

These characteristics in the population sample can be identified, observed and measured to guide decisions.

Descriptive research characteristics

While there are a number of descriptive research methods you can deploy for data collection, descriptive research does have a number of predictable characteristics.

Here are a few of the things to consider:

Measure data trends with statistical outcomes

Descriptive research is often popular for survey research because it generates answers in a statistical form, which makes it easy for researchers to carry out a simple statistical analysis to interpret what the data is saying.

Descriptive research design is ideal for further research

Because the data collection for descriptive research produces statistical outcomes, it can also be used as secondary data for another research study.

Plus, the data collected from descriptive research can be subjected to other types of data analysis .

Uncontrolled variables

A key component of the descriptive research method is that it uses random variables that are not controlled by the researchers. This is because descriptive research aims to understand the natural behavior of the research subject.

It’s carried out in a natural environment

Descriptive research is often carried out in a natural environment. This is because researchers aim to gather data in a natural setting to avoid swaying respondents.

Data can be gathered using survey questions or online surveys.

For example, if you want to understand the fashion trends we mentioned earlier, you would set up a study in which a researcher observes people in the respondent’s natural environment to understand their habits and preferences.

Descriptive research allows for cross sectional study

Because of the nature of descriptive research design and the randomness of the sample group being observed, descriptive research is ideal for cross sectional studies – essentially the demographics of the group can vary widely and your aim is to gain insights from within the group.

This can be highly beneficial when you’re looking to understand the behaviors or preferences of a wider population.

Descriptive research advantages

There are many advantages to using descriptive research, some of them include:

Cost effectiveness

Because the elements needed for descriptive research design are not specific or highly targeted (and occur within the respondent’s natural environment) this type of study is relatively cheap to carry out.

Multiple types of data can be collected

A big advantage of this research type, is that you can use it to collect both quantitative and qualitative data. This means you can use the stats gathered to easily identify underlying patterns in your respondents’ behavior.

Descriptive research disadvantages

Potential reliability issues.

When conducting descriptive research it’s important that the initial survey questions are properly formulated.

If not, it could make the answers unreliable and risk the credibility of your study.

Potential limitations

As we’ve mentioned, descriptive research design is ideal for understanding the what, who or where of a situation or phenomenon.

However, it can’t help you understand the cause or effect of the behavior. This means you’ll need to conduct further research to get a more complete picture of a situation.

Descriptive research methods

Because descriptive research methods include a range of quantitative and qualitative research, there are several research methods you can use.

Use case studies

Case studies in descriptive research involve conducting in-depth and detailed studies in which researchers get a specific person or case to answer questions.

Case studies shouldn’t be used to generate results, rather it should be used to build or establish hypothesis that you can expand into further market research .

For example you could gather detailed data about a specific business phenomenon, and then use this deeper understanding of that specific case.

Use observational methods

This type of study uses qualitative observations to understand human behavior within a particular group.

By understanding how the different demographics respond within your sample you can identify patterns and trends.

As an observational method, descriptive research will not tell you the cause of any particular behaviors, but that could be established with further research.

Use survey research

Surveys are one of the most cost effective ways to gather descriptive data.

An online survey or questionnaire can be used in descriptive studies to gather quantitative information about a particular problem.

Survey research is ideal if you’re using descriptive research as your primary research.

Descriptive research examples

Descriptive research is used for a number of commercial purposes or when organizations need to understand the behaviors or opinions of a population.

One of the biggest examples of descriptive research that is used in every democratic country, is during elections.

Using descriptive research, researchers will use surveys to understand who voters are more likely to choose out of the parties or candidates available.

Using the data provided, researchers can analyze the data to understand what the election result will be.

In a commercial setting, retailers often use descriptive research to figure out trends in shopping and buying decisions.

By gathering information on the habits of shoppers, retailers can get a better understanding of the purchases being made.

Another example that is widely used around the world, is the national census that takes place to understand the population.

The research will provide a more accurate picture of a population’s demographic makeup and help to understand changes over time in areas like population age, health and education level.

Where Qualtrics helps with descriptive research

Whatever type of research you want to carry out, there’s a survey type that will work.

Qualtrics can help you determine the appropriate method and ensure you design a study that will deliver the insights you need.

Our experts can help you with your market research needs , ensuring you get the most out of Qualtrics market research software to design, launch and analyze your data to guide better, more accurate decisions for your organization.

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• What is descriptive research?

Last updated

5 February 2023

Reviewed by

Cathy Heath

Descriptive research is a common investigatory model used by researchers in various fields, including social sciences, linguistics, and academia.

Read on to understand the characteristics of descriptive research and explore its underlying techniques, processes, and procedures.

Analyze your descriptive research

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Descriptive research is an exploratory research method. It enables researchers to precisely and methodically describe a population, circumstance, or phenomenon.

As the name suggests, descriptive research describes the characteristics of the group, situation, or phenomenon being studied without manipulating variables or testing hypotheses . This can be reported using surveys , observational studies, and case studies. You can use both quantitative and qualitative methods to compile the data.

Besides making observations and then comparing and analyzing them, descriptive studies often develop knowledge concepts and provide solutions to critical issues. It always aims to answer how the event occurred, when it occurred, where it occurred, and what the problem or phenomenon is.

• Characteristics of descriptive research

The following are some of the characteristics of descriptive research:

Quantitativeness

Descriptive research can be quantitative as it gathers quantifiable data to statistically analyze a population sample. These numbers can show patterns, connections, and trends over time and can be discovered using surveys, polls, and experiments.

Qualitativeness

Descriptive research can also be qualitative. It gives meaning and context to the numbers supplied by quantitative descriptive research .

Researchers can use tools like interviews, focus groups, and ethnographic studies to illustrate why things are what they are and help characterize the research problem. This is because it’s more explanatory than exploratory or experimental research.

Uncontrolled variables

Descriptive research differs from experimental research in that researchers cannot manipulate the variables. They are recognized, scrutinized, and quantified instead. This is one of its most prominent features.

Cross-sectional studies

Descriptive research is a cross-sectional study because it examines several areas of the same group. It involves obtaining data on multiple variables at the personal level during a certain period. It’s helpful when trying to understand a larger community’s habits or preferences.

Carried out in a natural environment

Descriptive studies are usually carried out in the participants’ everyday environment, which allows researchers to avoid influencing responders by collecting data in a natural setting. You can use online surveys or survey questions to collect data or observe.

Basis for further research

You can further dissect descriptive research’s outcomes and use them for different types of investigation. The outcomes also serve as a foundation for subsequent investigations and can guide future studies. For example, you can use the data obtained in descriptive research to help determine future research designs.

• Descriptive research methods

There are three basic approaches for gathering data in descriptive research: observational, case study, and survey.

You can use surveys to gather data in descriptive research. This involves gathering information from many people using a questionnaire and interview .

Surveys remain the dominant research tool for descriptive research design. Researchers can conduct various investigations and collect multiple types of data (quantitative and qualitative) using surveys with diverse designs.

You can conduct surveys over the phone, online, or in person. Your survey might be a brief interview or conversation with a set of prepared questions intended to obtain quick information from the primary source.

Observation

This descriptive research method involves observing and gathering data on a population or phenomena without manipulating variables. It is employed in psychology, market research , and other social science studies to track and understand human behavior.

Observation is an essential component of descriptive research. It entails gathering data and analyzing it to see whether there is a relationship between the two variables in the study. This strategy usually allows for both qualitative and quantitative data analysis.

Case studies

A case study can outline a specific topic’s traits. The topic might be a person, group, event, or organization.

It involves using a subset of a larger group as a sample to characterize the features of that larger group.

You can generalize knowledge gained from studying a case study to benefit a broader audience.

This approach entails carefully examining a particular group, person, or event over time. You can learn something new about the study topic by using a small group to better understand the dynamics of the entire group.

• Types of descriptive research

There are several types of descriptive study. The most well-known include cross-sectional studies, census surveys, sample surveys, case reports, and comparison studies.

Case reports and case series

In the healthcare and medical fields, a case report is used to explain a patient’s circumstances when suffering from an uncommon illness or displaying certain symptoms. Case reports and case series are both collections of related cases. They have aided the advancement of medical knowledge on countless occasions.

The normative component is an addition to the descriptive survey. In the descriptive–normative survey, you compare the study’s results to the norm.

Descriptive survey

This descriptive type of research employs surveys to collect information on various topics. This data aims to determine the degree to which certain conditions may be attained.

You can extrapolate or generalize the information you obtain from sample surveys to the larger group being researched.

Correlative survey

Correlative surveys help establish if there is a positive, negative, or neutral connection between two variables.

Performing census surveys involves gathering relevant data on several aspects of a given population. These units include individuals, families, organizations, objects, characteristics, and properties.

During descriptive research, you gather different degrees of interest over time from a specific population. Cross-sectional studies provide a glimpse of a phenomenon’s prevalence and features in a population. There are no ethical challenges with them and they are quite simple and inexpensive to carry out.

Comparative studies

These surveys compare the two subjects’ conditions or characteristics. The subjects may include research variables, organizations, plans, and people.

Comparison points, assumption of similarities, and criteria of comparison are three important variables that affect how well and accurately comparative studies are conducted.

For instance, descriptive research can help determine how many CEOs hold a bachelor’s degree and what proportion of low-income households receive government help.

• Pros and cons

The primary advantage of descriptive research designs is that researchers can create a reliable and beneficial database for additional study. To conduct any inquiry, you need access to reliable information sources that can give you a firm understanding of a situation.

Quantitative studies are time- and resource-intensive, so knowing the hypotheses viable for testing is crucial. The basic overview of descriptive research provides helpful hints as to which variables are worth quantitatively examining. This is why it’s employed as a precursor to quantitative research designs.

Some experts view this research as untrustworthy and unscientific. However, there is no way to assess the findings because you don’t manipulate any variables statistically.

Cause-and-effect correlations also can’t be established through descriptive investigations. Additionally, observational study findings cannot be replicated, which prevents a review of the findings and their replication.

The absence of statistical and in-depth analysis and the rather superficial character of the investigative procedure are drawbacks of this research approach.

• Descriptive research examples and applications

Several descriptive research examples are emphasized based on their types, purposes, and applications. Research questions often begin with “What is …” These studies help find solutions to practical issues in social science, physical science, and education.

Here are some examples and applications of descriptive research:

Determining consumer perception and behavior

Organizations use descriptive research designs to determine how various demographic groups react to a certain product or service.

For example, a business looking to sell to its target market should research the market’s behavior first. When researching human behavior in response to a cause or event, the researcher pays attention to the traits, actions, and responses before drawing a conclusion.

Scientific classification

Scientific descriptive research enables the classification of organisms and their traits and constituents.

Measuring data trends

A descriptive study design’s statistical capabilities allow researchers to track data trends over time. It’s frequently used to determine the study target’s current circumstances and underlying patterns.

Conduct comparison

Organizations can use a descriptive research approach to learn how various demographics react to a certain product or service. For example, you can study how the target market responds to a competitor’s product and use that information to infer their behavior.

• Bottom line

A descriptive research design is suitable for exploring certain topics and serving as a prelude to larger quantitative investigations. It provides a comprehensive understanding of the “what” of the group or thing you’re investigating.

This research type acts as the cornerstone of other research methodologies . It is distinctive because it can use quantitative and qualitative research approaches at the same time.

What is descriptive research design?

Descriptive research design aims to systematically obtain information to describe a phenomenon, situation, or population. More specifically, it helps answer the what, when, where, and how questions regarding the research problem rather than the why.

How does descriptive research compare to qualitative research?

Despite certain parallels, descriptive research concentrates on describing phenomena, while qualitative research aims to understand people better.

How do you analyze descriptive research data?

Data analysis involves using various methodologies, enabling the researcher to evaluate and provide results regarding validity and reliability.

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Bridging the Gap: Overcome these 7 flaws in descriptive research design

Descriptive research design is a powerful tool used by scientists and researchers to gather information about a particular group or phenomenon. This type of research provides a detailed and accurate picture of the characteristics and behaviors of a particular population or subject. By observing and collecting data on a given topic, descriptive research helps researchers gain a deeper understanding of a specific issue and provides valuable insights that can inform future studies.

In this blog, we will explore the definition, characteristics, and common flaws in descriptive research design, and provide tips on how to avoid these pitfalls to produce high-quality results. Whether you are a seasoned researcher or a student just starting, understanding the fundamentals of descriptive research design is essential to conducting successful scientific studies.

Table of Contents

What Is Descriptive Research Design?

The descriptive research design involves observing and collecting data on a given topic without attempting to infer cause-and-effect relationships. The goal of descriptive research is to provide a comprehensive and accurate picture of the population or phenomenon being studied and to describe the relationships, patterns, and trends that exist within the data.

Descriptive research methods can include surveys, observational studies , and case studies, and the data collected can be qualitative or quantitative . The findings from descriptive research provide valuable insights and inform future research, but do not establish cause-and-effect relationships.

Importance of Descriptive Research in Scientific Studies

1. understanding of a population or phenomenon.

Descriptive research provides a comprehensive picture of the characteristics and behaviors of a particular population or phenomenon, allowing researchers to gain a deeper understanding of the topic.

2. Baseline Information

The information gathered through descriptive research can serve as a baseline for future research and provide a foundation for further studies.

3. Informative Data

Descriptive research can provide valuable information and insights into a particular topic, which can inform future research, policy decisions, and programs.

4. Sampling Validation

Descriptive research can be used to validate sampling methods and to help researchers determine the best approach for their study.

5. Cost Effective

Descriptive research is often less expensive and less time-consuming than other research methods , making it a cost-effective way to gather information about a particular population or phenomenon.

6. Easy to Replicate

Descriptive research is straightforward to replicate, making it a reliable way to gather and compare information from multiple sources.

Key Characteristics of Descriptive Research Design

The primary purpose of descriptive research is to describe the characteristics, behaviors, and attributes of a particular population or phenomenon.

2. Participants and Sampling

Descriptive research studies a particular population or sample that is representative of the larger population being studied. Furthermore, sampling methods can include convenience, stratified, or random sampling.

3. Data Collection Techniques

Descriptive research typically involves the collection of both qualitative and quantitative data through methods such as surveys, observational studies, case studies, or focus groups.

4. Data Analysis

Descriptive research data is analyzed to identify patterns, relationships, and trends within the data. Statistical techniques , such as frequency distributions and descriptive statistics, are commonly used to summarize and describe the data.

5. Focus on Description

Descriptive research is focused on describing and summarizing the characteristics of a particular population or phenomenon. It does not make causal inferences.

6. Non-Experimental

Descriptive research is non-experimental, meaning that the researcher does not manipulate variables or control conditions. The researcher simply observes and collects data on the population or phenomenon being studied.

When Can a Researcher Conduct Descriptive Research?

A researcher can conduct descriptive research in the following situations:

• To better understand a particular population or phenomenon
• To describe the relationships between variables
• To describe patterns and trends
• To validate sampling methods and determine the best approach for a study
• To compare data from multiple sources.

Types of Descriptive Research Design

1. survey research.

Surveys are a type of descriptive research that involves collecting data through self-administered or interviewer-administered questionnaires. Additionally, they can be administered in-person, by mail, or online, and can collect both qualitative and quantitative data.

2. Observational Research

Observational research involves observing and collecting data on a particular population or phenomenon without manipulating variables or controlling conditions. It can be conducted in naturalistic settings or controlled laboratory settings.

3. Case Study Research

Case study research is a type of descriptive research that focuses on a single individual, group, or event. It involves collecting detailed information on the subject through a variety of methods, including interviews, observations, and examination of documents.

4. Focus Group Research

Focus group research involves bringing together a small group of people to discuss a particular topic or product. Furthermore, the group is usually moderated by a researcher and the discussion is recorded for later analysis.

5. Ethnographic Research

Ethnographic research involves conducting detailed observations of a particular culture or community. It is often used to gain a deep understanding of the beliefs, behaviors, and practices of a particular group.

Advantages of Descriptive Research Design

1. provides a comprehensive understanding.

Descriptive research provides a comprehensive picture of the characteristics, behaviors, and attributes of a particular population or phenomenon, which can be useful in informing future research and policy decisions.

2. Non-invasive

Descriptive research is non-invasive and does not manipulate variables or control conditions, making it a suitable method for sensitive or ethical concerns.

3. Flexibility

Descriptive research allows for a wide range of data collection methods , including surveys, observational studies, case studies, and focus groups, making it a flexible and versatile research method.

4. Cost-effective

Descriptive research is often less expensive and less time-consuming than other research methods. Moreover, it gives a cost-effective option to many researchers.

5. Easy to Replicate

Descriptive research is easy to replicate, making it a reliable way to gather and compare information from multiple sources.

6. Informs Future Research

The insights gained from a descriptive research can inform future research and inform policy decisions and programs.

Disadvantages of Descriptive Research Design

1. limited scope.

Descriptive research only provides a snapshot of the current situation and cannot establish cause-and-effect relationships.

2. Dependence on Existing Data

Descriptive research relies on existing data, which may not always be comprehensive or accurate.

3. Lack of Control

Researchers have no control over the variables in descriptive research, which can limit the conclusions that can be drawn.

The researcher’s own biases and preconceptions can influence the interpretation of the data.

5. Lack of Generalizability

Descriptive research findings may not be applicable to other populations or situations.

6. Lack of Depth

Descriptive research provides a surface-level understanding of a phenomenon, rather than a deep understanding.

7. Time-consuming

Descriptive research often requires a large amount of data collection and analysis, which can be time-consuming and resource-intensive.

7 Ways to Avoid Common Flaws While Designing Descriptive Research

1. Clearly define the research question

A clearly defined research question is the foundation of any research study, and it is important to ensure that the question is both specific and relevant to the topic being studied.

2. Choose the appropriate research design

Choosing the appropriate research design for a study is crucial to the success of the study. Moreover, researchers should choose a design that best fits the research question and the type of data needed to answer it.

3. Select a representative sample

Selecting a representative sample is important to ensure that the findings of the study are generalizable to the population being studied. Researchers should use a sampling method that provides a random and representative sample of the population.

4. Use valid and reliable data collection methods

Using valid and reliable data collection methods is important to ensure that the data collected is accurate and can be used to answer the research question. Researchers should choose methods that are appropriate for the study and that can be administered consistently and systematically.

5. Minimize bias

Bias can significantly impact the validity and reliability of research findings.  Furthermore, it is important to minimize bias in all aspects of the study, from the selection of participants to the analysis of data.

6. Ensure adequate sample size

An adequate sample size is important to ensure that the results of the study are statistically significant and can be generalized to the population being studied.

7. Use appropriate data analysis techniques

The appropriate data analysis technique depends on the type of data collected and the research question being asked. Researchers should choose techniques that are appropriate for the data and the question being asked.

Have you worked on descriptive research designs? How was your experience creating a descriptive design? What challenges did you face? Do write to us or leave a comment below and share your insights on descriptive research designs!

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• Descriptive Research Design | Definition, Methods & Examples

Descriptive Research Design | Definition, Methods & Examples

Published on 5 May 2022 by Shona McCombes . Revised on 10 October 2022.

Descriptive research aims to accurately and systematically describe a population, situation or phenomenon. It can answer what , where , when , and how   questions , but not why questions.

A descriptive research design can use a wide variety of research methods  to investigate one or more variables . Unlike in experimental research , the researcher does not control or manipulate any of the variables, but only observes and measures them.

Table of contents

When to use a descriptive research design, descriptive research methods.

Descriptive research is an appropriate choice when the research aim is to identify characteristics, frequencies, trends, and categories.

It is useful when not much is known yet about the topic or problem. Before you can research why something happens, you need to understand how, when, and where it happens.

• How has the London housing market changed over the past 20 years?
• Do customers of company X prefer product Y or product Z?
• What are the main genetic, behavioural, and morphological differences between European wildcats and domestic cats?
• What are the most popular online news sources among under-18s?
• How prevalent is disease A in population B?

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Descriptive research is usually defined as a type of quantitative research , though qualitative research can also be used for descriptive purposes. The research design should be carefully developed to ensure that the results are valid and reliable .

Survey research allows you to gather large volumes of data that can be analysed for frequencies, averages, and patterns. Common uses of surveys include:

• Describing the demographics of a country or region
• Gauging public opinion on political and social topics
• Evaluating satisfaction with a company’s products or an organisation’s services

Observations

Observations allow you to gather data on behaviours and phenomena without having to rely on the honesty and accuracy of respondents. This method is often used by psychological, social, and market researchers to understand how people act in real-life situations.

Observation of physical entities and phenomena is also an important part of research in the natural sciences. Before you can develop testable hypotheses , models, or theories, it’s necessary to observe and systematically describe the subject under investigation.

Case studies

A case study can be used to describe the characteristics of a specific subject (such as a person, group, event, or organisation). Instead of gathering a large volume of data to identify patterns across time or location, case studies gather detailed data to identify the characteristics of a narrowly defined subject.

Rather than aiming to describe generalisable facts, case studies often focus on unusual or interesting cases that challenge assumptions, add complexity, or reveal something new about a research problem .

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Home Market Research

Descriptive Research: Definition, Characteristics, Methods + Examples

Suppose an apparel brand wants to understand the fashion purchasing trends among New York’s buyers, then it must conduct a demographic survey of the specific region, gather population data, and then conduct descriptive research on this demographic segment.

The study will then uncover details on “what is the purchasing pattern of New York buyers,” but will not cover any investigative information about “ why ” the patterns exist. Because for the apparel brand trying to break into this market, understanding the nature of their market is the study’s main goal. Let’s talk about it.

What is descriptive research?

Descriptive research is a research method describing the characteristics of the population or phenomenon studied. This descriptive methodology focuses more on the “what” of the research subject than the “why” of the research subject.

The method primarily focuses on describing the nature of a demographic segment without focusing on “why” a particular phenomenon occurs. In other words, it “describes” the research subject without covering “why” it happens.

Characteristics of descriptive research

The term descriptive research then refers to research questions, the design of the study, and data analysis conducted on that topic. We call it an observational research method because none of the research study variables are influenced in any capacity.

Some distinctive characteristics of descriptive research are:

• Quantitative research: It is a quantitative research method that attempts to collect quantifiable information for statistical analysis of the population sample. It is a popular market research tool that allows us to collect and describe the demographic segment’s nature.
• Uncontrolled variables: In it, none of the variables are influenced in any way. This uses observational methods to conduct the research. Hence, the nature of the variables or their behavior is not in the hands of the researcher.
• Cross-sectional studies: It is generally a cross-sectional study where different sections belonging to the same group are studied.
• The basis for further research: Researchers further research the data collected and analyzed from descriptive research using different research techniques. The data can also help point towards the types of research methods used for the subsequent research.

Applications of descriptive research with examples

A descriptive research method can be used in multiple ways and for various reasons. Before getting into any survey , though, the survey goals and survey design are crucial. Despite following these steps, there is no way to know if one will meet the research outcome. How to use descriptive research? To understand the end objective of research goals, below are some ways organizations currently use descriptive research today:

• Define respondent characteristics: The aim of using close-ended questions is to draw concrete conclusions about the respondents. This could be the need to derive patterns, traits, and behaviors of the respondents. It could also be to understand from a respondent their attitude, or opinion about the phenomenon. For example, understand millennials and the hours per week they spend browsing the internet. All this information helps the organization researching to make informed business decisions.
• Measure data trends: Researchers measure data trends over time with a descriptive research design’s statistical capabilities. Consider if an apparel company researches different demographics like age groups from 24-35 and 36-45 on a new range launch of autumn wear. If one of those groups doesn’t take too well to the new launch, it provides insight into what clothes are like and what is not. The brand drops the clothes and apparel that customers don’t like.
• Conduct comparisons: Organizations also use a descriptive research design to understand how different groups respond to a specific product or service. For example, an apparel brand creates a survey asking general questions that measure the brand’s image. The same study also asks demographic questions like age, income, gender, geographical location, geographic segmentation , etc. This consumer research helps the organization understand what aspects of the brand appeal to the population and what aspects do not. It also helps make product or marketing fixes or even create a new product line to cater to high-growth potential groups.
• Validate existing conditions: Researchers widely use descriptive research to help ascertain the research object’s prevailing conditions and underlying patterns. Due to the non-invasive research method and the use of quantitative observation and some aspects of qualitative observation , researchers observe each variable and conduct an in-depth analysis . Researchers also use it to validate any existing conditions that may be prevalent in a population.
• Conduct research at different times: The analysis can be conducted at different periods to ascertain any similarities or differences. This also allows any number of variables to be evaluated. For verification, studies on prevailing conditions can also be repeated to draw trends.

Advantages of descriptive research

Some of the significant advantages of descriptive research are:

• Data collection: A researcher can conduct descriptive research using specific methods like observational method, case study method, and survey method. Between these three, all primary data collection methods are covered, which provides a lot of information. This can be used for future research or even for developing a hypothesis for your research object.
• Varied: Since the data collected is qualitative and quantitative, it gives a holistic understanding of a research topic. The information is varied, diverse, and thorough.
• Natural environment: Descriptive research allows for the research to be conducted in the respondent’s natural environment, which ensures that high-quality and honest data is collected.
• Quick to perform and cheap: As the sample size is generally large in descriptive research, the data collection is quick to conduct and is inexpensive.

Descriptive research methods

There are three distinctive methods to conduct descriptive research. They are:

Observational method

The observational method is the most effective method to conduct this research, and researchers make use of both quantitative and qualitative observations.

A quantitative observation is the objective collection of data primarily focused on numbers and values. It suggests “associated with, of or depicted in terms of a quantity.” Results of quantitative observation are derived using statistical and numerical analysis methods. It implies observation of any entity associated with a numeric value such as age, shape, weight, volume, scale, etc. For example, the researcher can track if current customers will refer the brand using a simple Net Promoter Score question .

Qualitative observation doesn’t involve measurements or numbers but instead just monitoring characteristics. In this case, the researcher observes the respondents from a distance. Since the respondents are in a comfortable environment, the characteristics observed are natural and effective. In a descriptive research design, the researcher can choose to be either a complete observer, an observer as a participant, a participant as an observer, or a full participant. For example, in a supermarket, a researcher can from afar monitor and track the customers’ selection and purchasing trends. This offers a more in-depth insight into the purchasing experience of the customer.

Case study method

Case studies involve in-depth research and study of individuals or groups. Case studies lead to a hypothesis and widen a further scope of studying a phenomenon. However, case studies should not be used to determine cause and effect as they can’t make accurate predictions because there could be a bias on the researcher’s part. The other reason why case studies are not a reliable way of conducting descriptive research is that there could be an atypical respondent in the survey. Describing them leads to weak generalizations and moving away from external validity.

Survey research

In survey research, respondents answer through surveys or questionnaires or polls . They are a popular market research tool to collect feedback from respondents. A study to gather useful data should have the right survey questions. It should be a balanced mix of open-ended questions and close ended-questions . The survey method can be conducted online or offline, making it the go-to option for descriptive research where the sample size is enormous.

Examples of descriptive research

Some examples of descriptive research are:

• A specialty food group launching a new range of barbecue rubs would like to understand what flavors of rubs are favored by different people. To understand the preferred flavor palette, they conduct this type of research study using various methods like observational methods in supermarkets. By also surveying while collecting in-depth demographic information, offers insights about the preference of different markets. This can also help tailor make the rubs and spreads to various preferred meats in that demographic. Conducting this type of research helps the organization tweak their business model and amplify marketing in core markets.
• Another example of where this research can be used is if a school district wishes to evaluate teachers’ attitudes about using technology in the classroom. By conducting surveys and observing their comfortableness using technology through observational methods, the researcher can gauge what they can help understand if a full-fledged implementation can face an issue. This also helps in understanding if the students are impacted in any way with this change.

Some other research problems and research questions that can lead to descriptive research are:

• Market researchers want to observe the habits of consumers.
• A company wants to evaluate the morale of its staff.
• A school district wants to understand if students will access online lessons rather than textbooks.
• To understand if its wellness questionnaire programs enhance the overall health of the employees.

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Child Care and Early Education Research Connections

Descriptive research studies.

Descriptive research is a type of research that is used to describe the characteristics of a population. It collects data that are used to answer a wide range of what, when, and how questions pertaining to a particular population or group. For example, descriptive studies might be used to answer questions such as: What percentage of Head Start teachers have a bachelor's degree or higher? What is the average reading ability of 5-year-olds when they first enter kindergarten? What kinds of math activities are used in early childhood programs? When do children first receive regular child care from someone other than their parents? When are children with developmental disabilities first diagnosed and when do they first receive services? What factors do programs consider when making decisions about the type of assessments that will be used to assess the skills of the children in their programs? How do the types of services children receive from their early childhood program change as children age?

Descriptive research does not answer questions about why a certain phenomenon occurs or what the causes are. Answers to such questions are best obtained from  randomized and quasi-experimental studies . However, data from descriptive studies can be used to examine the relationships (correlations) among variables. While the findings from correlational analyses are not evidence of causality, they can help to distinguish variables that may be important in explaining a phenomenon from those that are not. Thus, descriptive research is often used to generate hypotheses that should be tested using more rigorous designs.

A variety of data collection methods may be used alone or in combination to answer the types of questions guiding descriptive research. Some of the more common methods include surveys, interviews, observations, case studies, and portfolios. The data collected through these methods can be either quantitative or qualitative. Quantitative data are typically analyzed and presenting using  descriptive statistics . Using quantitative data, researchers may describe the characteristics of a sample or population in terms of percentages (e.g., percentage of population that belong to different racial/ethnic groups, percentage of low-income families that receive different government services) or averages (e.g., average household income, average scores of reading, mathematics and language assessments). Quantitative data, such as narrative data collected as part of a case study, may be used to organize, classify, and used to identify patterns of behaviors, attitudes, and other characteristics of groups.

Descriptive studies have an important role in early care and education research. Studies such as the  National Survey of Early Care and Education  and the  National Household Education Surveys Program  have greatly increased our knowledge of the supply of and demand for child care in the U.S. The  Head Start Family and Child Experiences Survey  and the  Early Childhood Longitudinal Study Program  have provided researchers, policy makers and practitioners with rich information about school readiness skills of children in the U.S.

Each of the methods used to collect descriptive data have their own strengths and limitations. The following are some of the strengths and limitations of descriptive research studies in general.

Study participants are questioned or observed in a natural setting (e.g., their homes, child care or educational settings).

Study data can be used to identify the prevalence of particular problems and the need for new or additional services to address these problems.

Descriptive research may identify areas in need of additional research and relationships between variables that require future study. Descriptive research is often referred to as "hypothesis generating research."

Depending on the data collection method used, descriptive studies can generate rich datasets on large and diverse samples.

Limitations:

Descriptive studies cannot be used to establish cause and effect relationships.

Respondents may not be truthful when answering survey questions or may give socially desirable responses.

The choice and wording of questions on a questionnaire may influence the descriptive findings.

Depending on the type and size of sample, the findings may not be generalizable or produce an accurate description of the population of interest.

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Descriptive Research Design

• September 29, 2021

Voxco’s Descriptive Research guide helps uncover the how, when, what, and where questions in a research problem

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When conducting a study, researchers generally try to find an explanation for the existence of a phenomenon. They want to understand “why” the phenomenon occurred. 

However, before identifying why a phenomenon occurred, it is integral to answer other questions first. You need to have answers to the “what,” “when,” “how,” and “where” before you can understand the “why.” This is where descriptive research comes in.

The descriptive research design involves using a range of qualitative and quantitative research methods to collect data that aids in accurately describing a research problem.

What is Descriptive Research Design?

Descriptive research design is a type of research design that aims to systematically obtain information to describe a phenomenon, situation, or population. More specifically, it helps answer the what, when, where, and how questions regarding the research problem rather than the why. 

A researcher can conduct this research using various methodologies. It predominantly employs quantitative data, although qualitative data is sometimes used for descriptive purposes. 

It is important to note that in the descriptive research method, the researcher does not control or manipulate any variables, unlike in experimental research. Instead, the variables are only identified, observed, and measured. 

Surveys and observation are the most used method to conduct this research design. You can leverage online survey tools or offline survey tools to gather data as per your research objective.

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What are the Characteristics of Descriptive Research Design?

Let’s take a look at the defining characteristics of the descriptive research design:

1. Quantitative in nature 

Descriptive research involves the collection of quantifiable and systematic data that can be used for the statistical analysis of the research problem. 

2. Uncontrolled variables

One of the most prominent characteristics of descriptive research is that, unlike in experimental research, the variables are not controlled or manipulated. Instead, they are simply identified, observed, and measured.

3. A basis for further research

The data collected in descriptive research provides a base for further research as it helps obtain a comprehensive understanding of the research question so that it can be answered appropriately. 

4. Cross-sectional studies

The descriptive research method is generally carried out through cross-sectional studies. A cross-sectional study is a type of observational study that involves gathering information on various variables at the individual level at a given point in time.

Example of Descriptive Research Design

To gain a deeper understanding of the descriptive method of research, let’s consider the following descriptive design research example: 

Company XYZ is a girls’ shoe brand catering to girls, specifically between the ages of 4 to 14. 

They want to start selling shoes for boys of the same age group as well and therefore want to gather information on the kind of shoes boys want to wear. They decide to conduct market research & choose the observational method to learn about different shoes boys wear nowadays. 

Naturalistic observation can be conducted by observing boys’ shoes in schools, malls, playgrounds, and other public spaces. 

This will help company XYZ identify the kind of shoe boys wear nowadays so that they can create the kind of products that will appeal to this audience.

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Why use Descriptive Research Design?

A descriptive approach to research allows researchers to thoroughly investigate the background of a research problem before further research can be carried out. It can be used in social science research to explore and document the nature and scope of a problem, to identify trends and patterns, and to provide a basis for subsequent research. 

The findings of descriptive research can help inform decision-making, policy development, and program planning.

There are many different contexts in which the use of a descriptive research design is beneficial. Here are some important uses of descriptive research design:

1. To measure data trends 

The descriptive method of research can be used to measure changes in variables over a period of time, allowing trends to be identified and analyzed. 

2. To compare variables

Descriptive research can be used to compare different variables and how different demographics respond to different variables. 

3. To define the characteristics of subjects

It can also be used to determine the different characteristics of the subjects. This can include characteristics such as opinions, traits, behavior, etc. 

4. To verify or validate existing conditions 

Descriptive research can prove to be a useful tool when trying to test the validity of an existing condition as it involves conducting an in-depth analysis of every variable before drawing conclusions.

What Are Some Examples of Descriptive Research Questions?

Here are some examples of descriptive research questions that can be addressed using a descriptive research design include:

• What are the demographic characteristics of a particular population?
• What is the prevalence of a particular health condition or risk factor?
• What are the attitudes and beliefs of a particular group towards a particular issue?
• What are the behaviors and experiences of individuals who have been exposed to a particular intervention or treatment?

What Are the Advantages of Descriptive Research Design?

The following are a few advantages of using a descriptive research design: 

1. Multiple methods of data collection

Research can use a wide range of methods for data collection, such as case studies, observational, and survey methods. They can also decide how they want to collect the data, online, offline, or via phone. 

2. Fast and cost-effective

As the descriptive research design often employs the use of surveys, data can be collected from a very large sample size quickly and cost-effectively. 

Researchers aiming to conduct market research using this research design should leverage integrated market research software . It will enable them to conduct product, customer, brand, and market research using suitable channels. 

3. Comprehensive

Descriptive research often uses quantitative and qualitative research in amalgamation, providing a more holistic understanding of the research topic. 

4. External validity

Results obtained through the descriptive method of research often have high external validity as research is conducted in the respondent’s natural environment and no variables are manipulated.

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What Are the Disadvantages of Descriptive Research Design?

The following are a few disadvantages of using a descriptive research design:

1. Cannot test or verify the research question

The descriptive method of research cannot be used to test or verify the research problem as the data collected does not help explain the cause of the phenomena being studied. 

2. Lack of reliability

If the research problem isn’t formulated well, then the data collected may not be entirely reliable. This also makes it more tedious to carry out a credible investigation. 

3. Risk of untrue responses

Descriptive research relies on the responses of people, especially when conducted using surveys. There may be instances when people provide false responses, compromising the validity of the data collected and the research results. 

4. Risk of sampling error

The descriptive research method generally employs random sampling while selecting a sample group. The randomness may lead to sampling error if the sample group isn’t representative of the larger population. Sampling error would lead to unreliable and inaccurate results.

What Are the Different Methods of Descriptive Research Design?

There are three most important descriptive research design methods:

In survey research, questionnaires or polls are used to collect information on a specific topic from respondents. Surveys should involve a mix of closed-ended and open-ended questions, as both have their own advantages. 

Online survey tools allow multiple data collection channels such as email, website, and SMS surveys. 

They are also popularly used in market research to collect customer feedback to optimize products and strategies and improve customer experience (CX). Some popular market research surveys are Net Promoter Score® (NPS®) surveys , brand tracking surveys , and conjoint analysis surveys . 

2. Case Studies 

The case study method involves the in-depth research of individuals or groups of individuals. Case studies involve gathering detailed data on a narrowly defined subject rather than gathering a large volume of data to identify correlations and patterns. 

Therefore, this method is often used to describe a specific subject’s different characteristics rather than generalizable facts. 

Case studies allow researchers to create hypotheses that can widen the scope of evaluation while studying the phenomenon. However, it is important to note that case studies cannot be used to outline the cause-and-effect relationship between variables as they cannot make accurate predictions due to the risk of researcher bias.

3. Observations method

In this method, researchers observe respondents in their natural environment, from a distance, and therefore do not influence the variables being studied. This allows them to gather information on the behaviors and characteristics being studied without having to rely on respondents for honest and accurate responses. 

The observational method is considered the most effective method for carrying out descriptive research. It involves the collection of both qualitative and quantitative data. You can leverage offline survey tools to gather data digitally, even without the Internet. 

Quantitative observation should be related to or understood in terms of quantity and can be analyzed with the use of statistical data analysis methods. A few examples of quantitative observations include age, weight, height, etc. 

Qualitative observations, on the other hand, involve monitoring variables whose values do not need to be related to numerical measurements. 

When employing this research method, the researcher can choose to be a complete observer, an observer as a participant, a participant as an observer, or a full participant. 

The observational method is generally used in psychological, social, and market research to obtain data that explains how people behave in real-life settings.

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What Are the Types of Descriptive Research Design Surveys?

The following are the different types of descriptive survey studies:

1. Census survey

A census survey is a kind of survey where information is gathered from all units of a population. Data collected through a census study is highly generalizable to the population as all or most units of the population are sampled. 

2. Sample survey 

A sample survey involves gathering information from a small subgroup of the entire population. When selecting a sample, the aim is to select a group of individuals representing the target population so that the data collected can be generalized to the larger population. Sample groups allow research to be conducted in a fast and cost-effective way. 

3. Cross-sectional survey 

In this type of survey, standardized data is collected from a cross-section of the pre-determined population at a given point in time. There are two main types of cross-sectional surveys ; those with a single variable and those with two or more variables. 

4. Longitudinal survey

Longitudinal surveys are used in longitudinal studies where the same variables are observed over a long period of time. This allows researchers to investigate the status of variables at different points in time. There are three main types of longitudinal studies ; trend, panel, and cohort.

5. Comparative survey

Comparative surveys are used to compare the status of two or more variables. The variables are compared using specific criteria that must be delineated as criterion variables. 

6. Evaluative survey

An evaluative survey is generally used to evaluate a program, policy, or curriculum. It involves gathering information that can be used to rate the effectiveness and worthwhileness of a program or policy, or institution. 

7. Documentary survey

A documentary survey involves gathering and analyzing information using pre-existing data that is already available. This data can be research papers, review articles, books, official records, etc. In documentary studies, the researcher evaluates the available literature on the research topic.

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How to Conduct a Descriptive Research Design

Use the following steps to conduct a study using the descriptive method of research:

Step-1: Outline the research objective

The first step is to identify and outline the objectives of your research and then translate these objectives into criteria of investigation. You must clearly identify the different issues and questions in the context of which the knowledge of the situation must be surveyed. 

This must be framed in the form of objectives. Once you’ve clearly stated your criteria and objectives, you must also specify the nature of the data that must be gathered. 

Step-2: Determine the tools and techniques to be used for data collection

In this step, you must determine the tools you will employ for the data collection process. Some examples of different tools that can be used are interviews, questionnaires, observation schedules, reaction scales, etc. 

In this stage, you will have to identify which tools and techniques are relevant and valid to your study. Leverage robust survey software that offers you multiple channels, thus enabling you to utilize various channels to gather insights. 

Step-3: Define​​ the target population and sample group

In the fourth step, you will have to outline your target population. The target population is the group of individuals that you are examining in your research study. Additionally, unless you are conducting a census study and collecting data from the entire population, you must select a sample group.

You can also use an audience panel to accelerate your research. A survey panel gives you access to diverse respondents so you can create your ideal panel. 

Additional read: Types of sampling methods .

Step-4: Select a method for data collection

In the data collection stage, you must have a clear plan of how your data will be collected. This involves clearly outlining the type of data you require, the tools that will be used to gather it, the level of training required by researchers to collect the data, the time required for data collection and fieldwork, and so on. 

As you collect data, keep your research question and objectives in mind and aim to gather authentic and objective data without personal bias. 

Step-5: Analyse the data collected

Once you’ve collected your data, you reach the sixth stage of descriptive research: data analysis. In this stage, you will have to evaluate all the data collected from all your different sources, quantify and qualify them, and then categorize them component-wise. 

If you are working with quantitative and qualitative data, you must employ a range of different quantitative and qualitative analysis techniques to analyze the data collected. 

Leverage survey analytics software that allows you to run statistical analysis and observe data on a live dashboard.  

Step-6: Write the report

The final step of survey research involves writing the report. As survey research involves working with extensive data, it is important to keep the focus of the investigation in mind. The report must be precise and objective-oriented.

Why Use Voxco for Descriptive Research Design?

Voxco being an omnichannel survey software , can be a valuable tool in descriptive research design. It can provide its users with a convenient and efficient means of collecting data from a large number of respondents. 

It allows researchers to design and distribute surveys to a targeted sample of participants, collect data in a standardized format, and analyze the results.

Here are some ways in which Voxco helps with descriptive research design:

• Customizable surveys: Voxco lets its users design surveys with a range of question types and themes. 
• Ease of distribution: With a range of distribution integration, Voxco makes it easy for users to distribute surveys easily via email, SMS, social media, etc. It helps the surveys reach a larger number of respondents. 
• Data analysis: Voxco not only helps researchers gather survey data but also analyzes the survey feedback, which allows researchers to get actionable insights on a visual dashboard. 

Overall, Voxco survey software is an effective tool for conducting descriptive research design, as it provides a streamlined and efficient way to gather, measure, and analyze survey data.

Wondering what will be the cost of conducting a survey using Voxco?

This sums up our article on descriptive research design. This research method helps uncover the hidden element of a customer’s behavior. It helps you create a foundation for your research by helping you create an outline of your research subject.

Begin your descriptive research with a free step-by-step guide to descriptive research

What is descriptive research?

Descriptive research design is a type of research methodology that researchers mostly use to analyze and document the behaviors and characteristics of a particular group of people. It gives a detailed analysis of a situation to explore the relation between two variables.

What is descriptive research study used for?

A descriptive research study is a type of observational research and is used for exploring and documenting the nature and scope of a problem, identifying its trends and patterns, and providing a basis for subsequent research. The outcome of a descriptive study is helpful in making decisions, developing policies, and planning social programs.

It is primarily concerned with describing the current state of a given phenomenon rather than explaining why it exists or how it came to be.

Why is descriptive research design used?

Descriptive research design can be used for a variety of reasons, including

• To describe and document a phenomenon of a particular population
• To identify patterns and trends
• To generate hypotheses for further research
• To inform decision-making and policy development

What is an example of a descriptive method?

A case study that examines the experiences of a small business run by women can be an example of a descriptive method of research. Let’s 

For instance, a researcher may conduct a case study of a small business solely run by women that have successfully implemented sustainable business practices in their food cloth manufacturing business. 

The case study could involve interviews with the owners of the business, observation of their business practices, and analysis of their financial data to document the costs and benefits of sustainability initiatives.

The researchers can then use the findings of the case study to provide a detailed account of the business’s approach to sustainability and to identify best practices that could be applied to other businesses.

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Descriptive Research 101: Definition, Methods and Examples

Parvathi vijayamohan.

18 October 2023

Table Of Contents

• Descriptive Research 101: The Definitive Guide

What is Descriptive Research?

Key characteristics of descriptive research.

• Descriptive Research Methods: The 3 You Need to Know!

Observation

Case studies, 7 types of descriptive research, descriptive research: examples to build your next study, tips to excel at descriptive research.

Imagine you are a detective called to a crime scene. Your job is to study the scene and report whatever you find: whether that’s the half-smoked cigarette on the table or the large “RACHE” written in blood on the wall. That, in a nutshell, is  descriptive research .

Researchers often need to do descriptive research on a problem before they attempt to solve it. So in this guide, we’ll take you through:

• What is descriptive research + characteristics
• Descriptive research methods
• Types of descriptive research
• Descriptive research examples
• Tips to excel at the descriptive method

Click to jump to the section that interests you.

Definition: As its name says, descriptive research  describes  the characteristics of the problem, phenomenon, situation, or group under study.

So the goal of all descriptive studies is to  explore  the background, details, and existing patterns in the problem to fully understand it. In other words, preliminary research.

However, descriptive research can be both  preliminary and conclusive . You can use the data from a descriptive study to make reports and get insights for further planning.

What descriptive research isn’t: Descriptive research finds the  what/when/where  of a problem, not the  why/how .

Because of this, we can’t use the descriptive method to explore cause-and-effect relationships where one variable (like a person’s job role) affects another variable (like their monthly income).

• Answers the “what,” “when,” and “where”  of a research problem. For this reason, it is popularly used in  market research ,  awareness surveys , and  opinion polls .
• Sets the stage  for a research problem. As an early part of the research process, descriptive studies help you dive deeper into the topic.
• Opens the door  for further research. You can use descriptive data as the basis for more profound research, analysis and studies.
• Qualitative and quantitative . It is possible to get a balanced mix of numerical responses and open-ended answers from the descriptive method.
• No control or interference with the variables . The researcher simply observes and reports on them. However, specific research software has  filters  that allow her to zoom in on one variable.
• Done in natural settings . You can get the best results from descriptive research by talking to people, surveying them, or observing them in a suitable environment. For example, suppose you are a website beta testing an app feature. In that case, descriptive research invites users to try the feature, tracking their behavior and then asking their opinions .
• Can be applied to many research methods and areas. Examples include healthcare, SaaS, psychology, political studies, education, and pop culture.

Descriptive Research Methods: The Top Three You Need to Know!

In short, survey research is a brief interview or conversation with a set of prepared questions about a topic.

So you create a questionnaire, share it, and analyze the data you collect for further action. Learn about the differences between surveys and questionnaires  here .

You can access free survey templates , over 20+ question types , and pass data to 1,500+ applications with survey software, like SurveySparrow . It enables you to create surveys, share them and capture data with very little effort.

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• Surveys can be hyper-local, regional, or global, depending on your objectives.
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The observational method is a type of descriptive research in which you, the researcher, observe ongoing behavior.

Now, there are several (non-creepy) ways you can observe someone. In fact, observational research has three main approaches:

• Covert observation: In true spy fashion, the researcher mixes in with the group undetected or observes from a distance.
• Overt observation : The researcher identifies himself as a researcher – “The name’s Bond. J. Bond.” – and explains the purpose of the study.
• Participatory observation : The researcher participates in what he is observing to understand his topic better.
• Observation is one of the most accurate ways to get data on a subject’s behavior in a natural setting.
• You don’t need to rely on people’s willingness to share information.
• Observation is a universal method that can be applied to any area of research.

In the case study method, you do a detailed study of a specific group, person, or event over a period.

This brings us to a frequently asked question: “What’s the difference between case studies and longitudinal studies?”

A case study will go  very in-depth into the subject with one-on-one interviews, observations, and archival research. They are also qualitative, though sometimes they will use numbers and stats.

An example of longitudinal research would be a study of the health of night shift employees vs. general shift employees over a decade. An example of a case study would involve in-depth interviews with Casey, an assistant director of nursing who’s handled the night shift at the hospital for ten years now.

• Due to the focus on a few people, case studies can give you a tremendous amount of information.
• Because of the time and effort involved, a case study engages both researchers and participants.
• Case studies are helpful for ethically investigating unusual, complex, or challenging subjects. An example would be a study of the habits of long-term cocaine users.

1. Case Study: Airbnb’s Growth Strategy

In an excellent case study, Tam Al Saad, Principal Consultant, Strategy + Growth at Webprofits, deep dives into how Airbnb attracted and retained 150 million users .

“What Airbnb offers isn’t a cheap place to sleep when you’re on holiday; it’s the opportunity to experience your destination as a local would. It’s the chance to meet the locals, experience the markets, and find non-touristy places.

Sure, you can visit the Louvre, see Buckingham Palace, and climb the Empire State Building, but you can do it as if it were your hometown while staying in a place that has character and feels like a home.” – Tam al Saad, Principal Consultant, Strategy + Growth at Webprofits

2. Observation – Better Tech Experiences for the Elderly

We often think that our elders are so hopeless with technology. But we’re not getting any younger either, and tech is changing at a hair trigger! This article by Annemieke Hendricks shares a wonderful example where researchers compare the levels of technological familiarity between age groups and how that influences usage.

“It is generally assumed that older adults have difficulty using modern electronic devices, such as mobile telephones or computers. Because this age group is growing in most countries, changing products and processes to adapt to their needs is increasingly more important. “ – Annemieke Hendricks, Marketing Communication Specialist, Noldus

3. Surveys – Decoding Sleep with SurveySparrow

SRI International (formerly Stanford Research Institute) – an independent, non-profit research center – wanted to investigate the impact of stress on an adolescent’s sleep. To get those insights, two actions were essential: tracking sleep patterns through wearable devices and sending surveys at a pre-set time –  the pre-sleep period.

“With SurveySparrow’s recurring surveys feature, SRI was able to share engaging surveys with their participants exactly at the time they wanted and at the frequency they preferred.”

Read more about this project : How SRI International decoded sleep patterns with SurveySparrow

1: Answer the six Ws –

• Who should we consider?
• What information do we need?
• When should we collect the information?
• Where should we collect the information?
• Why are we obtaining the information?
• Way to collect the information

#2: Introduce and explain your methodological approach

#3: Describe your methods of data collection and/or selection.

#4: Describe your methods of analysis.

#5: Explain the reasoning behind your choices.

#6: Collect data.

#7: Analyze the data. Use software to speed up the process and reduce overthinking and human error.

#8: Report your conclusions and how you drew the results.

Wrapping Up

That’s all, folks!

Growth Marketer at SurveySparrow

Fledgling growth marketer. Cloud watcher. Aunty to a naughty beagle.

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• Descriptive Research Designs: Types, Examples & Methods

One of the components of research is getting enough information about the research problem—the what, how, when and where answers, which is why descriptive research is an important type of research. It is very useful when conducting research whose aim is to identify characteristics, frequencies, trends, correlations, and categories.

This research method takes a problem with little to no relevant information and gives it a befitting description using qualitative and quantitative research method s. Descriptive research aims to accurately describe a research problem.

In the subsequent sections, we will be explaining what descriptive research means, its types, examples, and data collection methods.

What is Descriptive Research?

Descriptive research is a type of research that describes a population, situation, or phenomenon that is being studied. It focuses on answering the how, what, when, and where questions If a research problem, rather than the why.

This is mainly because it is important to have a proper understanding of what a research problem is about before investigating why it exists in the first place. 

For example, an investor considering an investment in the ever-changing Amsterdam housing market needs to understand what the current state of the market is, how it changes (increasing or decreasing), and when it changes (time of the year) before asking for the why. This is where descriptive research comes in.

What Are The Types of Descriptive Research?

Descriptive research is classified into different types according to the kind of approach that is used in conducting descriptive research. The different types of descriptive research are highlighted below:

• Descriptive-survey

Descriptive survey research uses surveys to gather data about varying subjects. This data aims to know the extent to which different conditions can be obtained among these subjects.

For example, a researcher wants to determine the qualification of employed professionals in Maryland. He uses a survey as his research instrument , and each item on the survey related to qualifications is subjected to a Yes/No answer. 

This way, the researcher can describe the qualifications possessed by the employed demographics of this community. 

• Descriptive-normative survey

This is an extension of the descriptive survey, with the addition being the normative element. In the descriptive-normative survey, the results of the study should be compared with the norm.

For example, an organization that wishes to test the skills of its employees by a team may have them take a skills test. The skills tests are the evaluation tool in this case, and the result of this test is compared with the norm of each role.

If the score of the team is one standard deviation above the mean, it is very satisfactory, if within the mean, satisfactory, and one standard deviation below the mean is unsatisfactory.

• Descriptive-status

This is a quantitative description technique that seeks to answer questions about real-life situations. For example, a researcher researching the income of the employees in a company, and the relationship with their performance.

A survey will be carried out to gather enough data about the income of the employees, then their performance will be evaluated and compared to their income. This will help determine whether a higher income means better performance and low income means lower performance or vice versa.

• Descriptive-analysis

The descriptive-analysis method of research describes a subject by further analyzing it, which in this case involves dividing it into 2 parts. For example, the HR personnel of a company that wishes to analyze the job role of each employee of the company may divide the employees into the people that work at the Headquarters in the US and those that work from Oslo, Norway office.

A questionnaire is devised to analyze the job role of employees with similar salaries and who work in similar positions.

• Descriptive classification

This method is employed in biological sciences for the classification of plants and animals. A researcher who wishes to classify the sea animals into different species will collect samples from various search stations, then classify them accordingly.

• Descriptive-comparative

In descriptive-comparative research, the researcher considers 2 variables that are not manipulated, and establish a formal procedure to conclude that one is better than the other. For example, an examination body wants to determine the better method of conducting tests between paper-based and computer-based tests.

A random sample of potential participants of the test may be asked to use the 2 different methods, and factors like failure rates, time factors, and others will be evaluated to arrive at the best method.

• Correlative Survey

Correlative surveys are used to determine whether the relationship between 2 variables is positive, negative, or neutral. That is, if 2 variables say X and Y are directly proportional, inversely proportional or are not related to each other.

Examples of Descriptive Research

There are different examples of descriptive research, that may be highlighted from its types, uses, and applications. However, we will be restricting ourselves to only 3 distinct examples in this article.

• Comparing Student Performance:

An academic institution may wish 2 compare the performance of its junior high school students in English language and Mathematics. This may be used to classify students based on 2 major groups, with one group going ahead to study while courses, while the other study courses in the Arts & Humanities field.

Students who are more proficient in mathematics will be encouraged to go into STEM and vice versa. Institutions may also use this data to identify students’ weak points and work on ways to assist them.

• Scientific Classification

During the major scientific classification of plants, animals, and periodic table elements, the characteristics and components of each subject are evaluated and used to determine how they are classified.

For example, living things may be classified into kingdom Plantae or kingdom animal is depending on their nature. Further classification may group animals into mammals, pieces, vertebrae, invertebrae, etc. 

All these classifications are made a result of descriptive research which describes what they are.

• Human Behavior

When studying human behaviour based on a factor or event, the researcher observes the characteristics, behaviour, and reaction, then use it to conclude. A company willing to sell to its target market needs to first study the behaviour of the market.

This may be done by observing how its target reacts to a competitor’s product, then use it to determine their behaviour.

What are the Characteristics of Descriptive Research?  

The characteristics of descriptive research can be highlighted from its definition, applications, data collection methods, and examples. Some characteristics of descriptive research are:

• Quantitativeness

Descriptive research uses a quantitative research method by collecting quantifiable information to be used for statistical analysis of the population sample. This is very common when dealing with research in the physical sciences.

• Qualitativeness

It can also be carried out using the qualitative research method, to properly describe the research problem. This is because descriptive research is more explanatory than exploratory or experimental.

• Uncontrolled variables

In descriptive research, researchers cannot control the variables like they do in experimental research.

• The basis for further research

The results of descriptive research can be further analyzed and used in other research methods. It can also inform the next line of research, including the research method that should be used.

This is because it provides basic information about the research problem, which may give birth to other questions like why a particular thing is the way it is.

Why Use Descriptive Research Design?  

Descriptive research can be used to investigate the background of a research problem and get the required information needed to carry out further research. It is used in multiple ways by different organizations, and especially when getting the required information about their target audience.

• Define subject characteristics :

It is used to determine the characteristics of the subjects, including their traits, behaviour, opinion, etc. This information may be gathered with the use of surveys, which are shared with the respondents who in this case, are the research subjects.

For example, a survey evaluating the number of hours millennials in a community spends on the internet weekly, will help a service provider make informed business decisions regarding the market potential of the community.

• Measure Data Trends

It helps to measure the changes in data over some time through statistical methods. Consider the case of individuals who want to invest in stock markets, so they evaluate the changes in prices of the available stocks to make a decision investment decision.

Brokerage companies are however the ones who carry out the descriptive research process, while individuals can view the data trends and make decisions.

Descriptive research is also used to compare how different demographics respond to certain variables. For example, an organization may study how people with different income levels react to the launch of a new Apple phone.

This kind of research may take a survey that will help determine which group of individuals are purchasing the new Apple phone. Do the low-income earners also purchase the phone, or only the high-income earners do?

Further research using another technique will explain why low-income earners are purchasing the phone even though they can barely afford it. This will help inform strategies that will lure other low-income earners and increase company sales.

• Validate existing conditions

When you are not sure about the validity of an existing condition, you can use descriptive research to ascertain the underlying patterns of the research object. This is because descriptive research methods make an in-depth analysis of each variable before making conclusions.

• Conducted Overtime

Descriptive research is conducted over some time to ascertain the changes observed at each point in time. The higher the number of times it is conducted, the more authentic the conclusion will be.

What are the Disadvantages of Descriptive Research?  

• Response and Non-response Bias

Respondents may either decide not to respond to questions or give incorrect responses if they feel the questions are too confidential. When researchers use observational methods, respondents may also decide to behave in a particular manner because they feel they are being watched.

• The researcher may decide to influence the result of the research due to personal opinion or bias towards a particular subject. For example, a stockbroker who also has a business of his own may try to lure investors into investing in his own company by manipulating results.
• A case-study or sample taken from a large population is not representative of the whole population.
• Limited scope:The scope of descriptive research is limited to the what of research, with no information on why thereby limiting the scope of the research.

What are the Data Collection Methods in Descriptive Research?  

There are 3 main data collection methods in descriptive research, namely; observational method, case study method, and survey research.

1. Observational Method

The observational method allows researchers to collect data based on their view of the behaviour and characteristics of the respondent, with the respondents themselves not directly having an input. It is often used in market research, psychology, and some other social science research to understand human behaviour.

It is also an important aspect of physical scientific research, with it being one of the most effective methods of conducting descriptive research . This process can be said to be either quantitative or qualitative.

Quantitative observation involved the objective collection of numerical data , whose results can be analyzed using numerical and statistical methods. 

Qualitative observation, on the other hand, involves the monitoring of characteristics and not the measurement of numbers. The researcher makes his observation from a distance, records it, and is used to inform conclusions.

2. Case Study Method

A case study is a sample group (an individual, a group of people, organizations, events, etc.) whose characteristics are used to describe the characteristics of a larger group in which the case study is a subgroup. The information gathered from investigating a case study may be generalized to serve the larger group.

This generalization, may, however, be risky because case studies are not sufficient to make accurate predictions about larger groups. Case studies are a poor case of generalization.

3. Survey Research

This is a very popular data collection method in research designs. In survey research, researchers create a survey or questionnaire and distribute it to respondents who give answers.

Generally, it is used to obtain quick information directly from the primary source and also conducting rigorous quantitative and qualitative research. In some cases, survey research uses a blend of both qualitative and quantitative strategies.

Survey research can be carried out both online and offline using the following methods

• Online Surveys: This is a cheap method of carrying out surveys and getting enough responses. It can be carried out using Formplus, an online survey builder. Formplus has amazing tools and features that will help increase response rates.
• Offline Surveys: This includes paper forms, mobile offline forms , and SMS-based forms.

What Are The Differences Between Descriptive and Correlational Research?  

Before going into the differences between descriptive and correlation research, we need to have a proper understanding of what correlation research is about. Therefore, we will be giving a summary of the correlation research below.

Correlational research is a type of descriptive research, which is used to measure the relationship between 2 variables, with the researcher having no control over them. It aims to find whether there is; positive correlation (both variables change in the same direction), negative correlation (the variables change in the opposite direction), or zero correlation (there is no relationship between the variables).

Correlational research may be used in 2 situations;

(i) when trying to find out if there is a relationship between two variables, and

(ii) when a causal relationship is suspected between two variables, but it is impractical or unethical to conduct experimental research that manipulates one of the variables. 

Below are some of the differences between correlational and descriptive research:

• Definitions :

Descriptive research aims is a type of research that provides an in-depth understanding of the study population, while correlational research is the type of research that measures the relationship between 2 variables. 

• Characteristics :

Descriptive research provides descriptive data explaining what the research subject is about, while correlation research explores the relationship between data and not their description.

• Predictions :

 Predictions cannot be made in descriptive research while correlation research accommodates the possibility of making predictions.

Descriptive Research vs. Causal Research

Descriptive research and causal research are both research methodologies, however, one focuses on a subject’s behaviors while the latter focuses on a relationship’s cause-and-effect. To buttress the above point, descriptive research aims to describe and document the characteristics, behaviors, or phenomena of a particular or specific population or situation. 

It focuses on providing an accurate and detailed account of an already existing state of affairs between variables. Descriptive research answers the questions of “what,” “where,” “when,” and “how” without attempting to establish any causal relationships or explain any underlying factors that might have caused the behavior.

Causal research, on the other hand, seeks to determine cause-and-effect relationships between variables. It aims to point out the factors that influence or cause a particular result or behavior. Causal research involves manipulating variables, controlling conditions or a subgroup, and observing the resulting effects. The primary objective of causal research is to establish a cause-effect relationship and provide insights into why certain phenomena happen the way they do.

Descriptive Research vs. Analytical Research

Descriptive research provides a detailed and comprehensive account of a specific situation or phenomenon. It focuses on describing and summarizing data without making inferences or attempting to explain underlying factors or the cause of the factor. 

It is primarily concerned with providing an accurate and objective representation of the subject of research. While analytical research goes beyond the description of the phenomena and seeks to analyze and interpret data to discover if there are patterns, relationships, or any underlying factors. 

It examines the data critically, applies statistical techniques or other analytical methods, and draws conclusions based on the discovery. Analytical research also aims to explore the relationships between variables and understand the underlying mechanisms or processes involved.

Descriptive Research vs. Exploratory Research

Descriptive research is a research method that focuses on providing a detailed and accurate account of a specific situation, group, or phenomenon. This type of research describes the characteristics, behaviors, or relationships within the given context without looking for an underlying cause. 

Descriptive research typically involves collecting and analyzing quantitative or qualitative data to generate descriptive statistics or narratives. Exploratory research differs from descriptive research because it aims to explore and gain firsthand insights or knowledge into a relatively unexplored or poorly understood topic. 

It focuses on generating ideas, hypotheses, or theories rather than providing definitive answers. Exploratory research is often conducted at the early stages of a research project to gather preliminary information and identify key variables or factors for further investigation. It involves open-ended interviews, observations, or small-scale surveys to gather qualitative data.

Read More – Exploratory Research: What are its Method & Examples?

Descriptive Research vs. Experimental Research

Descriptive research aims to describe and document the characteristics, behaviors, or phenomena of a particular population or situation. It focuses on providing an accurate and detailed account of the existing state of affairs. 

Descriptive research typically involves collecting data through surveys, observations, or existing records and analyzing the data to generate descriptive statistics or narratives. It does not involve manipulating variables or establishing cause-and-effect relationships.

Experimental research, on the other hand, involves manipulating variables and controlling conditions to investigate cause-and-effect relationships. It aims to establish causal relationships by introducing an intervention or treatment and observing the resulting effects. 

Experimental research typically involves randomly assigning participants to different groups, such as control and experimental groups, and measuring the outcomes. It allows researchers to control for confounding variables and draw causal conclusions.

Related – Experimental vs Non-Experimental Research: 15 Key Differences

Descriptive Research vs. Explanatory Research

Descriptive research focuses on providing a detailed and accurate account of a specific situation, group, or phenomenon. It aims to describe the characteristics, behaviors, or relationships within the given context. 

Descriptive research is primarily concerned with providing an objective representation of the subject of study without explaining underlying causes or mechanisms. Explanatory research seeks to explain the relationships between variables and uncover the underlying causes or mechanisms. 

It goes beyond description and aims to understand the reasons or factors that influence a particular outcome or behavior. Explanatory research involves analyzing data, conducting statistical analyses, and developing theories or models to explain the observed relationships.

Descriptive Research vs. Inferential Research

Descriptive research focuses on describing and summarizing data without making inferences or generalizations beyond the specific sample or population being studied. It aims to provide an accurate and objective representation of the subject of study. 

Descriptive research typically involves analyzing data to generate descriptive statistics, such as means, frequencies, or percentages, to describe the characteristics or behaviors observed.

Inferential research, however, involves making inferences or generalizations about a larger population based on a smaller sample. 

It aims to draw conclusions about the population characteristics or relationships by analyzing the sample data. Inferential research uses statistical techniques to estimate population parameters, test hypotheses, and determine the level of confidence or significance in the findings.

Related – Inferential Statistics: Definition, Types + Examples

Conclusion  

The uniqueness of descriptive research partly lies in its ability to explore both quantitative and qualitative research methods. Therefore, when conducting descriptive research, researchers have the opportunity to use a wide variety of techniques that aids the research process.

Descriptive research explores research problems in-depth, beyond the surface level thereby giving a detailed description of the research subject. That way, it can aid further research in the field, including other research methods .

It is also very useful in solving real-life problems in various fields of social science, physical science, and education.

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Descriptive Research Design and Its Myriad Uses

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Table of Contents

The design of a research study can be of two broad types—observational or interventional. In interventional studies, at least one variable can be controlled by the researcher. For example, drug trials that examine the efficacy of novel medicines are interventional studies. Observational studies, on the other hand, simply examine and describe uncontrollable variables¹ .   

What is descriptive research design?¹

Descriptive design is one of the simplest forms of observational study design. It can either quantify the distribution of certain variables (quantitative descriptive research) or simply report the qualities of these variables without quantifying them (qualitative descriptive research).   

When can descriptive research design be used?¹

It is useful when you wish to examine the occurrence of a phenomenon, delineate trends or patterns within the phenomenon, or describe the relationship between variables. As such, descriptive design is great for¹ :  

• A survey conducted to measure the changes in the levels of customer satisfaction among shoppers in the US is the perfect example of quantitative descriptive research.  
• Conversely, a case report detailing the experiences and perspectives of individuals living with a particular rare disease is a good example of qualitative descriptive research.  
• Cross-sectional studies : Descriptive research is ideal for cross-sectional studies that capture a snapshot of a population at a specific point in time. This approach can be used to observe the variations in risk factors and diseases in a population. Take the following examples:   
• In quantitative descriptive research: A study that measures the prevalence of heart disease among college students in the current academic year.  
• In qualitative descriptive research: A cross-sectional study exploring the cultural perceptions of mental health across different communities.  
• Ecological studies : Descriptive research design is also well-suited for studies that seek to understand relationships between variables and outcomes in specific populations. For example:  
• A study that measures the relationship between the number of police personnel and homicides in India can use quantitative descriptive research design  
• A study describing the impact of deforestation on indigenous communities’ cultural practices and beliefs can use qualitative descriptive research design.  
• Focus group discussion reports : Descriptive research can help in capturing diverse perspectives and understanding the nuances of participants’ experiences.   
• First, an example of quantitative descriptive research: A study that uses two focus groups to explore the perceptions of mental health among immigrants in London.  
• Next, an example of qualitative descriptive research: A focus group report analyzing the themes and emotions associated with different advertising campaigns.  

Benefits of descriptive research design¹  

• Easy to conduct: Due to its simplicity, descriptive research design can be employed by researchers of all experience levels.  
• Economical: Descriptive research design is not resource intensive. It is a budget-friendly approach to studying many phenomena without costly equipment.   
• Provides comprehensive and useful information: Descriptive research is a more thorough approach that can capture many different aspects of a phenomena, facilitating a wholistic understanding.  
• Aids planning of major projects or future research: As a tool for preliminary exploration, descriptive research guides can guide strategic decision-making and guide major projects.  

The Bottom Line  

Descriptive research plays a crucial role in improving our lives. Surveys help create better policies and cross-sectional studies help us understand problems affecting different populations including diseases. Used in the right context, descriptive research can advance knowledge and inform decision making¹ .  

We, at Elsevier Language Services, understand the value of your descriptive research, as well as the importance of communicating it correctly. If you have a manuscript based on a descriptive study, our experienced editors can help improve its myriad aspects. By improving the logical flow, tone, and accuracy of your writing, we ensure that your descriptive research gets published in a top tier journal and makes maximum impact in academia and beyond. Contact us for a comprehensive list of services!   

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References 

• Aggarwal, R., & Ranganathan, P. (2019). Study designs: Part 2 – Descriptive studies. Perspectives in Clinical Research , 10 (1), 34. https://doi.org/10.4103/picr.picr_154_18 .  

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Descriptive Research

Descriptive research can be explained as a statement of affairs as they are at present with the researcher having no control over variable. Moreover, “descriptive studies may be characterised as simply the attempt to determine, describe or identify what is, while analytical research attempts to establish why it is that way or how it came to be” [1] . Three main purposes of descriptive studies can be explained as describing, explaining and validating research findings. This type of research is popular with non-quantified topic.

Descriptive research is “aimed at casting light on current issues or problems through a process of data collection that enables them to describe the situation more completely than was possible without employing this method.” [2] To put it simply, descriptive studies are used to describe various aspects of the phenomenon. In its popular format, descriptive research is used to describe characteristics and/or behaviour of sample population. It is an effective method to get information that can be used to develop hypotheses and propose associations.

Importantly, these types of studies do not focus on reasons for the occurrence of the phenomenon. In other words, descriptive research focuses on the question “What?”, but it is not concerned with the question “Why?”

Descriptive studies have the following characteristics:

1. While descriptive research can employ a number of variables, only one variable is required to conduct a descriptive study.

2. Descriptive studies are closely associated with observational studies, but they are not limited with observation data collection method. Case studies and  surveys can also be specified as popular data collection methods used with descriptive studies.

3. Findings of descriptive researches create a scope for further research. When a descriptive study answers to the question “What?”, a further research can be conducted to find an answer to “Why?” question.

Examples of Descriptive Research

Research questions in descriptive studies typically start with ‘What is…”. Examples of research questions in descriptive studies may include the following:

• What are the most effective intangible employee motivation tools in hospitality industry in the 21 st century?
• What is the impact of viral marketing on consumer behaviour in consumer amongst university students in Canada?
• Do corporate leaders of multinational companies in the 21 st century possess moral rights to receive multi-million bonuses?
• What are the main distinctive traits of organisational culture of McDonald’s USA?
• What is the impact of the global financial crisis of 2007 – 2009 on fitness industry in the UK?

Advantages of Descriptive Research

• Effective to analyse non-quantified topics and issues
• The possibility to observe the phenomenon in a completely natural and unchanged natural environment
• The opportunity to integrate the qualitative and quantitative methods of data collection. Accordingly, research findings can be comprehensive.
• Less time-consuming than quantitative experiments
• Practical use of research findings for decision-making

Disadvantages of Descriptive Research

• Descriptive studies cannot test or verify the research problem statistically
• Research results may reflect certain level of bias due to the absence of statistical tests
• The majority of descriptive studies are not ‘repeatable’ due to their observational nature
• Descriptive studies are not helpful in identifying cause behind described phenomenon

My e-book,  The Ultimate Guide to Writing a Dissertation in Business Studies: a step by step assistance  contains discussions of theory and application of research designs. The e-book also explains all stages of the  research process  starting from the  selection of the research area  to writing personal reflection. Important elements of dissertations such as  research philosophy ,  research approach ,  methods of data collection ,  data analysis  and  sampling  are explained in this e-book in simple words.

John Dudovskiy

[1] Ethridge, D.E. (2004) “Research Methodology in Applied Economics” John Wiley & Sons, p.24

[2] Fox, W. & Bayat, M.S. (2007) “A Guide to Managing Research” Juta Publications, p.45

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Descriptive Research Design

Descriptive research design is a scientific method which involves observing and describing the behavior of a subject without influencing it in any way.

This article is a part of the guide:

• Research Designs
• Quantitative and Qualitative Research
• Literature Review
• Quantitative Research Design

Browse Full Outline

• 1 Research Designs
• 2.1 Pilot Study
• 2.2 Quantitative Research Design
• 2.3 Qualitative Research Design
• 2.4 Quantitative and Qualitative Research
• 3.1 Case Study
• 3.2 Naturalistic Observation
• 3.3 Survey Research Design
• 3.4 Observational Study
• 4.1 Case-Control Study
• 4.2 Cohort Study
• 4.3 Longitudinal Study
• 4.4 Cross Sectional Study
• 4.5 Correlational Study
• 5.1 Field Experiments
• 5.2 Quasi-Experimental Design
• 5.3 Identical Twins Study
• 6.1 Experimental Design
• 6.2 True Experimental Design
• 6.3 Double Blind Experiment
• 6.4 Factorial Design
• 7.1 Literature Review
• 7.2 Systematic Reviews
• 7.3 Meta Analysis

Many scientific disciplines, especially social science and psychology, use this method to obtain a general overview of the subject.

Some subjects cannot be observed in any other way; for example, a social case study of an individual subject is a descriptive research design and allows observation without affecting normal behavior.

It is also useful where it is not possible to test and measure the large number of samples needed for more quantitative types of experimentation .

These types of experiments are often used by anthropologists, psychologists and social scientists to observe natural behaviors without affecting them in any way. It is also used by market researchers to judge the habits of customers, or by companies wishing to judge the morale of staff.

The results from a descriptive research can in no way be used as a definitive answer or to disprove a hypothesis but, if the limitations are understood, they can still be a useful tool in many areas of scientific research.

The subject is being observed in a completely natural and unchanged natural environment. A good example of this would be an anthropologist who wanted to study a tribe without affecting their normal behavior in any way. True experiments , whilst giving analyzable data, often adversely influence the normal behavior of the subject.

Descriptive research is often used as a pre-cursor to quantitative research designs, the general overview giving some valuable pointers as to what variables are worth testing quantitatively. Quantitative experiments are often expensive and time-consuming so it is often good sense to get an idea of what hypotheses are worth testing .

Disadvantages

Because there are no variables manipulated , there is no way to statistically analyze the results. Many scientists regard this type of study as very unreliable and ‘unscientific’.

In addition, the results of observational studies are not repeatable , and so there can be no replication of the experiment and reviewing of the results.

Descriptive research design is a valid method for researching specific subjects and as a precursor to more quantitative studies. Whilst there are some valid concerns about the statistical validity , as long as the limitations are understood by the researcher, this type of study is an invaluable scientific tool.

Whilst the results are always open to question and to different interpretations, there is no doubt that they are preferable to performing no research at all.

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Martyn Shuttleworth (Sep 26, 2008). Descriptive Research Design. Retrieved Apr 05, 2024 from Explorable.com: https://explorable.com/descriptive-research-design

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• Section 2: Home
• Developing the Quantitative Research Design
• Qualitative Descriptive Design

Overview of Descriptive Design

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A descriptive design is a flexible, exploratory approach to qualitative research. Descriptive design is referred to in the literature by other labels including generic, general, basic, traditional, interpretive, and pragmatic. Descriptive design as an acceptable research design for dissertation and other robust scholarly research has received varying degrees of acceptance within the academic community. However, descriptive design has been gaining momentum since the early 2000’s as a suitable design for studies that do not fall into the more mainstream genres of qualitative research (ie. Case study, phenomenology, ethnography, narrative inquiry and grounded theory). In contrast to other qualitative designs, descriptive design is not aligned to specific methods (for example, bracketing in phenomenology, bounded systems in case study, or constant comparative analysis in grounded theory). Rather, descriptive design “borrows” methods appropriate to the proposed study from other designs. 

Arguments supporting the flexible nature of descriptive designs describe it as being preferable to forcing a research approach into a design that is not quite appropriate for the nature of the intended study. However, descriptive design has also been criticized for this mixing of methods as well as for the limited literature describing it. The descriptive design can be the foundation for a rigorous study within the ADE program. Because of the flexibility of the methods used, a descriptive design provides the researcher with the opportunity to choose methods best suited to a practice-based research purpose.   

• Example Descriptive Design in an Applied Doctorate

Sources of Data in Descriptive Design

Because of the exploratory nature of descriptive design, the triangulation of multiple sources of data are often used for additional insight into the phenomenon. Sources of data that can be used in descriptive studies are similar to those that may be used in other qualitative designs and include interviews, focus groups, documents, artifacts, and observations.

The following video provides additional considerations for triangulation in qualitative designs including descriptive design: Triangulation: Pairing Thematic and Content Analysis

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Characteristics of Qualitative Descriptive Studies: A Systematic Review

MSN, CRNP, Doctoral Candidate, University of Pennsylvania School of Nursing

Justine S. Sefcik

MS, RN, Doctoral Candidate, University of Pennsylvania School of Nursing

Christine Bradway

PhD, CRNP, FAAN, Associate Professor of Gerontological Nursing, University of Pennsylvania School of Nursing

Qualitative description (QD) is a term that is widely used to describe qualitative studies of health care and nursing-related phenomena. However, limited discussions regarding QD are found in the existing literature. In this systematic review, we identified characteristics of methods and findings reported in research articles published in 2014 whose authors identified the work as QD. After searching and screening, data were extracted from the sample of 55 QD articles and examined to characterize research objectives, design justification, theoretical/philosophical frameworks, sampling and sample size, data collection and sources, data analysis, and presentation of findings. In this review, three primary findings were identified. First, despite inconsistencies, most articles included characteristics consistent with limited, available QD definitions and descriptions. Next, flexibility or variability of methods was common and desirable for obtaining rich data and achieving understanding of a phenomenon. Finally, justification for how a QD approach was chosen and why it would be an appropriate fit for a particular study was limited in the sample and, therefore, in need of increased attention. Based on these findings, recommendations include encouragement to researchers to provide as many details as possible regarding the methods of their QD study so that readers can determine whether the methods used were reasonable and effective in producing useful findings.

Qualitative description (QD) is a label used in qualitative research for studies which are descriptive in nature, particularly for examining health care and nursing-related phenomena ( Polit & Beck, 2009 , 2014 ). QD is a widely cited research tradition and has been identified as important and appropriate for research questions focused on discovering the who, what, and where of events or experiences and gaining insights from informants regarding a poorly understood phenomenon. It is also the label of choice when a straight description of a phenomenon is desired or information is sought to develop and refine questionnaires or interventions ( Neergaard et al., 2009 ; Sullivan-Bolyai et al., 2005 ).

Despite many strengths and frequent citations of its use, limited discussions regarding QD are found in qualitative research textbooks and publications. To the best of our knowledge, only seven articles include specific guidance on how to design, implement, analyze, or report the results of a QD study ( Milne & Oberle, 2005 ; Neergaard, Olesen, Andersen, & Sondergaard, 2009 ; Sandelowski, 2000 , 2010 ; Sullivan-Bolyai, Bova, & Harper, 2005 ; Vaismoradi, Turunen, & Bondas, 2013 ; Willis, Sullivan-Bolyai, Knafl, & Zichi-Cohen, 2016 ). Furthermore, little is known about characteristics of QD as reported in journal-published, nursing-related, qualitative studies. Therefore, the purpose of this systematic review was to describe specific characteristics of methods and findings of studies reported in journal articles (published in 2014) self-labeled as QD. In this review, we did not have a goal to judge whether QD was done correctly but rather to report on the features of the methods and findings.

Features of QD

Several QD design features and techniques have been described in the literature. First, researchers generally draw from a naturalistic perspective and examine a phenomenon in its natural state ( Sandelowski, 2000 ). Second, QD has been described as less theoretical compared to other qualitative approaches ( Neergaard et al., 2009 ), facilitating flexibility in commitment to a theory or framework when designing and conducting a study ( Sandelowski, 2000 , 2010 ). For example, researchers may or may not decide to begin with a theory of the targeted phenomenon and do not need to stay committed to a theory or framework if their investigations take them down another path ( Sandelowski, 2010 ). Third, data collection strategies typically involve individual and/or focus group interviews with minimal to semi-structured interview guides ( Neergaard et al., 2009 ; Sandelowski, 2000 ). Fourth, researchers commonly employ purposeful sampling techniques such as maximum variation sampling which has been described as being useful for obtaining broad insights and rich information ( Neergaard et al., 2009 ; Sandelowski, 2000 ). Fifth, content analysis (and in many cases, supplemented by descriptive quantitative data to describe the study sample) is considered a primary strategy for data analysis ( Neergaard et al., 2009 ; Sandelowski, 2000 ). In some instances thematic analysis may also be used to analyze data; however, experts suggest care should be taken that this type of analysis is not confused with content analysis ( Vaismoradi et al., 2013 ). These data analysis approaches allow researchers to stay close to the data and as such, interpretation is of low-inference ( Neergaard et al., 2009 ), meaning that different researchers will agree more readily on the same findings even if they do not choose to present the findings in the same way ( Sandelowski, 2000 ). Finally, representation of study findings in published reports is expected to be straightforward, including comprehensive descriptive summaries and accurate details of the data collected, and presented in a way that makes sense to the reader ( Neergaard et al., 2009 ; Sandelowski, 2000 ).

It is also important to acknowledge that variations in methods or techniques may be appropriate across QD studies ( Sandelowski, 2010 ). For example, when consistent with the study goals, decisions may be made to use techniques from other qualitative traditions, such as employing a constant comparative analytic approach typically associated with grounded theory ( Sandelowski, 2000 ).

Search Strategy and Study Screening

The PubMed electronic database was searched for articles written in English and published from January 1, 2014 to December 31, 2014, using the terms, “qualitative descriptive study,” “qualitative descriptive design,” and “qualitative description,” combined with “nursing.” This specific publication year, “2014,” was chosen because it was the most recent full year at the time of beginning this systematic review. As we did not intend to identify trends in QD approaches over time, it seemed reasonable to focus on the nursing QD studies published in a certain year. The inclusion criterion for this review was data-based, nursing-related, research articles in which authors used the terms QD, qualitative descriptive study, or qualitative descriptive design in their titles or abstracts as well as in the main texts of the publication.

All articles yielded through an initial search in PubMed were exported into EndNote X7 ( Thomson Reuters, 2014 ), a reference management software, and duplicates were removed. Next, titles and abstracts were reviewed to determine if the publication met inclusion criteria; all articles meeting inclusion criteria were then read independently in full by two authors (HK and JS) to determine if the terms – QD or qualitative descriptive study/design – were clearly stated in the main texts. Any articles in which researchers did not specifically state these key terms in the main text were then excluded, even if the terms had been used in the study title or abstract. In one article, for example, although “qualitative descriptive study” was reported in the published abstract, the researchers reported a “qualitative exploratory design” in the main text of the article ( Sundqvist & Carlsson, 2014 ); therefore, this article was excluded from our review. Despite the possibility that there may be other QD studies published in 2014 that were not labeled as such, to facilitate our screening process we only included articles where the researchers clearly used our search terms for their approach. Finally, the two authors compared, discussed, and reconciled their lists of articles with a third author (CB).

Study Selection

Initially, although the year 2014 was specifically requested, 95 articles were identified (due to ahead of print/Epub) and exported into the EndNote program. Three duplicate publications were removed and the 20 articles with final publication dates of 2015 were also excluded. The remaining 72 articles were then screened by examining titles, abstracts, and full-texts. Based on our inclusion criteria, 15 (of 72) were then excluded because QD or QD design/study was not identified in the main text. We then re-examined the remaining 57 articles and excluded two additional articles that did not meet inclusion criteria (e.g., QD was only reported as an analytic approach in the data analysis section). The remaining 55 publications met inclusion criteria and comprised the sample for our systematic review (see Figure 1 ).

Flow Diagram of Study Selection

Of the 55 publications, 23 originated from North America (17 in the United States; 6 in Canada), 12 from Asia, 11 from Europe, 7 from Australia and New Zealand, and 2 from South America. Eleven studies were part of larger research projects and two of them were reported as part of larger mixed-methods studies. Four were described as a secondary analysis.

Quality Appraisal Process

Following the identification of the 55 publications, two authors (HK and JS) independently examined each article using the Critical Appraisal Skills Programme (CASP) qualitative checklist ( CASP, 2013 ). The CASP was chosen to determine the general adequacy (or rigor) of the qualitative studies included in this review as the CASP criteria are generic and intend to be applied to qualitative studies in general. In addition, the CASP was useful because we were able to examine the internal consistency between study aims and methods and between study aims and findings as well as the usefulness of findings ( CASP, 2013 ). The CASP consists of 10 main questions with several sub-questions to consider when making a decision about the main question ( CASP, 2013 ). The first two questions have reviewers examine the clarity of study aims and appropriateness of using qualitative research to achieve the aims. With the next eight questions, reviewers assess study design, sampling, data collection, and analysis as well as the clarity of the study’s results statement and the value of the research. We used the seven questions and 17 sub-questions related to methods and statement of findings to evaluate the articles. The results of this process are presented in Table 1 .

CASP Questions and Quality Appraisal Results (N = 55)

Note . The CASP questions are adapted from “10 questions to help you make sense of qualitative research,” by Critical Appraisal Skills Programme, 2013, retrieved from http://media.wix.com/ugd/dded87_29c5b002d99342f788c6ac670e49f274.pdf . Its license can be found at http://creativecommons.org/licenses/by-nc-sa/3.0/

Once articles were assessed by the two authors independently, all three authors discussed and reconciled our assessment. No articles were excluded based on CASP results; rather, results were used to depict the general adequacy (or rigor) of all 55 articles meeting inclusion criteria for our systematic review. In addition, the CASP was included to enhance our examination of the relationship between the methods and the usefulness of the findings documented in each of the QD articles included in this review.

Process for Data Extraction and Analysis

To further assess each of the 55 articles, data were extracted on: (a) research objectives, (b) design justification, (c) theoretical or philosophical framework, (d) sampling and sample size, (e) data collection and data sources, (f) data analysis, and (g) presentation of findings (see Table 2 ). We discussed extracted data and identified common and unique features in the articles included in our systematic review. Findings are described in detail below and in Table 3 .

Elements for Data Extraction

Data Extraction and Analysis Results

Note . NR = not reported

Quality Appraisal Results

Justification for use of a QD design was evident in close to half (47.3%) of the 55 publications. While most researchers clearly described recruitment strategies (80%) and data collection methods (100%), justification for how the study setting was selected was only identified in 38.2% of the articles and almost 75% of the articles did not include any reason for the choice of data collection methods (e.g., focus-group interviews). In the vast majority (90.9%) of the articles, researchers did not explain their involvement and positionality during the process of recruitment and data collection or during data analysis (63.6%). Ethical standards were reported in greater than 89% of all articles and most articles included an in-depth description of data analysis (83.6%) and development of categories or themes (92.7%). Finally, all researchers clearly stated their findings in relation to research questions/objectives. Researchers of 83.3% of the articles discussed the credibility of their findings (see Table 1 ).

Research Objectives

In statements of study objectives and/or questions, the most frequently used verbs were “explore” ( n = 22) and “describe” ( n = 17). Researchers also used “identify” ( n = 3), “understand” ( n = 4), or “investigate” ( n = 2). Most articles focused on participants’ experiences related to certain phenomena ( n = 18), facilitators/challenges/factors/reasons ( n = 14), perceptions about specific care/nursing practice/interventions ( n = 11), and knowledge/attitudes/beliefs ( n = 3).

Design Justification

A total of 30 articles included references for QD. The most frequently cited references ( n = 23) were “Whatever happened to qualitative description?” ( Sandelowski, 2000 ) and “What’s in a name? Qualitative description revisited” ( Sandelowski, 2010 ). Other references cited included “Qualitative description – the poor cousin of health research?” ( Neergaard et al., 2009 ), “Reaching the parts other methods cannot reach: an introduction to qualitative methods in health and health services research” ( Pope & Mays, 1995 ), and general research textbooks ( Polit & Beck, 2004 , 2012 ).

In 26 articles (and not necessarily the same as those citing specific references to QD), researchers provided a rationale for selecting QD. Most researchers chose QD because this approach aims to produce a straight description and comprehensive summary of the phenomenon of interest using participants’ language and staying close to the data (or using low inference).

Authors of two articles distinctly stated a QD design, yet also acknowledged grounded-theory or phenomenological overtones by adopting some techniques from these qualitative traditions ( Michael, O'Callaghan, Baird, Hiscock, & Clayton, 2014 ; Peacock, Hammond-Collins, & Forbes, 2014 ). For example, Michael et al. (2014 , p. 1066) reported:

The research used a qualitative descriptive design with grounded theory overtones ( Sandelowski, 2000 ). We sought to provide a comprehensive summary of participants’ views through theoretical sampling; multiple data sources (focus groups [FGs] and interviews); inductive, cyclic, and constant comparative analysis; and condensation of data into thematic representations ( Corbin & Strauss, 1990 , 2008 ).

Authors of four additional articles included language suggestive of a grounded-theory or phenomenological tradition, e.g., by employing a constant comparison technique or translating themes stated in participants’ language into the primary language of the researchers during data analysis ( Asemani et al., 2014 ; Li, Lee, Chen, Jeng, & Chen, 2014 ; Ma, 2014 ; Soule, 2014 ). Additionally, Li et al. (2014) specifically reported use of a grounded-theory approach.

Theoretical or Philosophical Framework

In most (n = 48) articles, researchers did not specify any theoretical or philosophical framework. Of those articles in which a framework or philosophical stance was included, the authors of five articles described the framework as guiding the development of an interview guide ( Al-Zadjali, Keller, Larkey, & Evans, 2014 ; DeBruyn, Ochoa-Marin, & Semenic, 2014 ; Fantasia, Sutherland, Fontenot, & Ierardi, 2014 ; Ma, 2014 ; Wiens, Babenko-Mould, & Iwasiw, 2014 ). In two articles, data analysis was described as including key concepts of a framework being used as pre-determined codes or categories ( Al-Zadjali et al., 2014 ; Wiens et al., 2014 ). Oosterveld-Vlug et al. (2014) and Zhang, Shan, and Jiang (2014) discussed a conceptual model and underlying philosophy in detail in the background or discussion section, although the model and philosophy were not described as being used in developing interview questions or analyzing data.

Sampling and Sample Size

In 38 of the 55 articles, researchers reported ‘purposeful sampling’ or some derivation of purposeful sampling such as convenience ( n = 10), maximum variation ( n = 8), snowball ( n = 3), and theoretical sampling ( n = 1). In three instances ( Asemani et al., 2014 ; Chan & Lopez, 2014 ; Soule, 2014 ), multiple sampling strategies were described, for example, a combination of snowball, convenience, and maximum variation sampling. In articles where maximum variation sampling was employed, “variation” referred to seeking diversity in participants’ demographics ( n = 7; e.g., age, gender, and education level), while one article did not include details regarding how their maximum variation sampling strategy was operationalized ( Marcinowicz, Abramowicz, Zarzycka, Abramowicz, & Konstantynowicz, 2014 ). Authors of 17 articles did not specify their sampling techniques.

Sample sizes ranged from 8 to 1,932 with nine studies in the 8–10 participant range and 24 studies in the 11–20 participant range. The participant range of 21–30 and 31–50 was reported in eight articles each. Six studies included more than 50 participants. Two of these articles depicted quite large sample sizes (N=253, Hart & Mareno, 2014 ; N=1,932, Lyndon et al., 2014 ) and the authors of these articles described the use of survey instruments and analysis of responses to open-ended questions. This was in contrast to studies with smaller sample sizes where individual interviews and focus groups were more commonly employed.

Data Collection and Data Sources

In a majority of studies, researchers collected data through individual ( n = 39) and/or focus-group ( n = 14) interviews that were semistructured. Most researchers reported that interviews were audiotaped ( n = 51) and interview guides were described as the primary data collection tool in 29 of the 51 studies. In some cases, researchers also described additional data sources, for example, taking memos or field notes during participant observation sessions or as a way to reflect their thoughts about interviews ( n = 10). Written responses to open-ended questions in survey questionnaires were another type of data source in a small number of studies ( n = 4).

Data Analysis

The analysis strategy most commonly used in the QD studies included in this review was qualitative content analysis ( n = 30). Among the studies where this technique was used, most researchers described an inductive approach; researchers of two studies analyzed data both inductively and deductively. Thematic analysis was adopted in 14 studies and the constant comparison technique in 10 studies. In nine studies, researchers employed multiple techniques to analyze data including qualitative content analysis with constant comparison ( Asemani et al., 2014 ; DeBruyn et al., 2014 ; Holland, Christensen, Shone, Kearney, & Kitzman, 2014 ; Li et al., 2014 ) and thematic analysis with constant comparison ( Johansson, Hildingsson, & Fenwick, 2014 ; Oosterveld-Vlug et al., 2014 ). In addition, five teams conducted descriptive statistical analysis using both quantitative and qualitative data and counting the frequencies of codes/themes ( Ewens, Chapman, Tulloch, & Hendricks, 2014 ; Miller, 2014 ; Santos, Sandelowski, & Gualda, 2014 ; Villar, Celdran, Faba, & Serrat, 2014 ) or targeted events through video monitoring ( Martorella, Boitor, Michaud, & Gelinas, 2014 ). Tseng, Chen, and Wang (2014) cited Thorne, Reimer Kirkham, and O’Flynn-Magee (2004)’s interpretive description as the inductive analytic approach. In five out of 55 articles, researchers did not specifically name their analysis strategies, despite including descriptions about procedural aspects of data analysis. Researchers of 20 studies reported that data saturation for their themes was achieved.

Presentation of Findings

Researchers described participants’ experiences of health care, interventions, or illnesses in 18 articles and presented straightforward, focused, detailed descriptions of facilitators, challenges, factors, reasons, and causes in 15 articles. Participants’ perceptions of specific care, interventions, or programs were described in detail in 11 articles. All researchers presented their findings with extensive descriptions including themes or categories. In 25 of 55 articles, figures or tables were also presented to illustrate or summarize the findings. In addition, the authors of three articles summarized, organized, and described their data using key concepts of conceptual models ( Al-Zadjali et al., 2014 ; Oosterveld-Vlug et al., 2014 ; Wiens et al., 2014 ). Martorella et al. (2014) assessed acceptability and feasibility of hand massage therapy and arranged their findings in relation to pre-determined indicators of acceptability and feasibility. In one longitudinal QD study ( Kneck, Fagerberg, Eriksson, & Lundman, 2014 ), the researchers presented the findings as several key patterns of learning for persons living with diabetes; in another longitudinal QD study ( Stegenga & Macpherson, 2014 ), findings were presented as processes and themes regarding patients’ identity work across the cancer trajectory. In another two studies, the researchers described and compared themes or categories from two different perspectives, such as patients and nurses ( Canzan, Heilemann, Saiani, Mortari, & Ambrosi, 2014 ) or parents and children ( Marcinowicz et al., 2014 ). Additionally, Ma (2014) reported themes using both participants’ language and the researcher’s language.

In this systematic review, we examined and reported specific characteristics of methods and findings reported in journal articles self-identified as QD and published during one calendar year. To accomplish this we identified 55 articles that met inclusion criteria, performed a quality appraisal following CASP guidelines, and extracted and analyzed data focusing on QD features. In general, three primary findings emerged. First, despite inconsistencies, most QD publications had the characteristics that were originally observed by Sandelowski (2000) and summarized by other limited available QD literature. Next, there are no clear boundaries in methods used in the QD studies included in this review; in a number of studies, researchers adopted and combined techniques originating from other qualitative traditions to obtain rich data and increase their understanding of the phenomenon under investigation. Finally, justification for how QD was chosen and why it would be an appropriate fit for a particular study is an area in need of increased attention.

In general, the overall characteristics were consistent with design features of QD studies described in the literature ( Neergaard et al., 2009 ; Sandelowski, 2000 , 2010 ; Vaismoradi et al., 2013 ). For example, many authors reported that study objectives were to describe or explore participants’ experiences and factors related to certain phenomena, events, or interventions. In most cases, these authors cited Sandelowski (2000) as a reference for this particular characteristic. It was rare that theoretical or philosophical frameworks were identified, which also is consistent with descriptions of QD. In most studies, researchers used purposeful sampling and its derivative sampling techniques, collected data through interviews, and analyzed data using qualitative content analysis or thematic analysis. Moreover, all researchers presented focused or comprehensive, descriptive summaries of data including themes or categories answering their research questions. These characteristics do not indicate that there are correct ways to do QD studies; rather, they demonstrate how others designed and produced QD studies.

In several studies, researchers combined techniques that originated from other qualitative traditions for sampling, data collection, and analysis. This flexibility or variability, a key feature of recently published QD studies, may indicate that there are no clear boundaries in designing QD studies. Sandelowski (2010) articulated: “in the actual world of research practice, methods bleed into each other; they are so much messier than textbook depictions” (p. 81). Hammersley (2007) also observed:

“We are not so much faced with a set of clearly differentiated qualitative approaches as with a complex landscape of variable practice in which the inhabitants use a range of labels (‘ethnography’, ‘discourse analysis’, ‘life history work’, narrative study’, ……, and so on) in diverse and open-ended ways in order to characterize their orientation, and probably do this somewhat differently across audiences and occasions” (p. 293).

This concept of having no clear boundaries in methods when designing a QD study should enable researchers to obtain rich data and produce a comprehensive summary of data through various data collection and analysis approaches to answer their research questions. For example, using an ethnographical approach (e.g., participant observation) in data collection for a QD study may facilitate an in-depth description of participants’ nonverbal expressions and interactions with others and their environment as well as situations or events in which researchers are interested ( Kawulich, 2005 ). One example found in our review is that Adams et al. (2014) explored family members’ responses to nursing communication strategies for patients in intensive care units (ICUs). In this study, researchers conducted interviews with family members, observed interactions between healthcare providers, patients, and family members in ICUs, attended ICU rounds and family meetings, and took field notes about their observations and reflections. Accordingly, the variability in methods provided Adams and colleagues (2014) with many different aspects of data that were then used to complement participants’ interviews (i.e., data triangulation). Moreover, by using a constant comparison technique in addition to qualitative content analysis or thematic analysis in QD studies, researchers compare each case with others looking for similarities and differences as well as reasoning why differences exist, to generate more general understanding of phenomena of interest ( Thorne, 2000 ). In fact, this constant comparison analysis is compatible with qualitative content analysis and thematic analysis and we found several examples of using this approach in studies we reviewed ( Asemani et al., 2014 ; DeBruyn et al., 2014 ; Holland et al., 2014 ; Johansson et al., 2014 ; Li et al., 2014 ; Oosterveld-Vlug et al., 2014 ).

However, this flexibility or variability in methods of QD studies may cause readers’ as well as researchers’ confusion in designing and often labeling qualitative studies ( Neergaard et al., 2009 ). Especially, it could be difficult for scholars unfamiliar with qualitative studies to differentiate QD studies with “hues, tones, and textures” of qualitative traditions ( Sandelowski, 2000 , p. 337) from grounded theory, phenomenological, and ethnographical research. In fact, the major difference is in the presentation of the findings (or outcomes of qualitative research) ( Neergaard et al., 2009 ; Sandelowski, 2000 ). The final products of grounded theory, phenomenological, and ethnographical research are a generation of a theory, a description of the meaning or essence of people’s lived experience, and an in-depth, narrative description about certain culture, respectively, through researchers’ intensive/deep interpretations, reflections, and/or transformation of data ( Streubert & Carpenter, 2011 ). In contrast, QD studies result in “a rich, straight description” of experiences, perceptions, or events using language from the collected data ( Neergaard et al., 2009 ) through low-inference (or data-near) interpretations during data analysis ( Sandelowski, 2000 , 2010 ). This feature is consistent with our finding regarding presentation of findings: in all QD articles included in this systematic review, the researchers presented focused or comprehensive, descriptive summaries to their research questions.

Finally, an explanation or justification of why a QD approach was chosen or appropriate for the study aims was not found in more than half of studies in the sample. While other qualitative approaches, including grounded theory, phenomenology, ethnography, and narrative analysis, are used to better understand people’s thoughts, behaviors, and situations regarding certain phenomena ( Sullivan-Bolyai et al., 2005 ), as noted above, the results will likely read differently than those for a QD study ( Carter & Little, 2007 ). Therefore, it is important that researchers accurately label and justify their choices of approach, particularly for studies focused on participants’ experiences, which could be addressed with other qualitative traditions. Justifying one’s research epistemology, methodology, and methods allows readers to evaluate these choices for internal consistency, provides context to assist in understanding the findings, and contributes to the transparency of choices, all of which enhance the rigor of the study ( Carter & Little, 2007 ; Wu, Thompson, Aroian, McQuaid, & Deatrick, 2016 ).

Use of the CASP tool drew our attention to the credibility and usefulness of the findings of the QD studies included in this review. Although justification for study design and methods was lacking in many articles, most authors reported techniques of recruitment, data collection, and analysis that appeared. Internal consistencies among study objectives, methods, and findings were achieved in most studies, increasing readers’ confidence that the findings of these studies are credible and useful in understanding under-explored phenomenon of interest.

In summary, our findings support the notion that many scholars employ QD and include a variety of commonly observed characteristics in their study design and subsequent publications. Based on our review, we found that QD as a scholarly approach allows flexibility as research questions and study findings emerge. We encourage authors to provide as many details as possible regarding how QD was chosen for a particular study as well as details regarding methods to facilitate readers’ understanding and evaluation of the study design and rigor. We acknowledge the challenge of strict word limitation with submissions to print journals; potential solutions include collaboration with journal editors and staff to consider creative use of charts or tables, or using more citations and less text in background sections so that methods sections are robust.

Limitations

Several limitations of this review deserve mention. First, only articles where researchers explicitly stated in the main body of the article that a QD design was employed were included. In contrast, articles labeled as QD in only the title or abstract, or without their research design named were not examined due to the lack of certainty that the researchers actually carried out a QD study. As a result, we may have excluded some studies where a QD design was followed. Second, only one database was searched and therefore we did not identify or describe potential studies following a QD approach that were published in non-PubMed databases. Third, our review is limited by reliance on what was included in the published version of a study. In some cases, this may have been a result of word limits or specific styles imposed by journals, or inconsistent reporting preferences of authors and may have limited our ability to appraise the general adequacy with the CASP tool and examine specific characteristics of these studies.

Conclusions

A systematic review was conducted by examining QD research articles focused on nursing-related phenomena and published in one calendar year. Current patterns include some characteristics of QD studies consistent with the previous observations described in the literature, a focus on the flexibility or variability of methods in QD studies, and a need for increased explanations of why QD was an appropriate label for a particular study. Based on these findings, recommendations include encouragement to authors to provide as many details as possible regarding the methods of their QD study. In this way, readers can thoroughly consider and examine if the methods used were effective and reasonable in producing credible and useful findings.

Acknowledgments

This work was supported in part by the John A. Hartford Foundation’s National Hartford Centers of Gerontological Nursing Excellence Award Program.

Hyejin Kim is a Ruth L. Kirschstein NRSA Predoctoral Fellow (F31NR015702) and 2013–2015 National Hartford Centers of Gerontological Nursing Excellence Patricia G. Archbold Scholar. Justine Sefcik is a Ruth L. Kirschstein Predoctoral Fellow (F31NR015693) through the National Institutes of Health, National Institute of Nursing Research.

Conflict of Interest Statement

The Authors declare that there is no conflict of interest.

Contributor Information

Hyejin Kim, MSN, CRNP, Doctoral Candidate, University of Pennsylvania School of Nursing.

Justine S. Sefcik, MS, RN, Doctoral Candidate, University of Pennsylvania School of Nursing.

Christine Bradway, PhD, CRNP, FAAN, Associate Professor of Gerontological Nursing, University of Pennsylvania School of Nursing.

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• Open access
• Published: 01 April 2024

Midwives’ lived experiences of caring for women with mobility disabilities during pregnancy, labour and puerperium in Eswatini: a qualitative study

• Annie M. Temane 1 ,
• Fortunate N. Magagula 2 &
• Anna G. W. Nolte 1  

BMC Women's Health volume  24 , Article number:  207 ( 2024 ) Cite this article

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Metrics details

Midwives encounter various difficulties while aiming to achieve excellence in providing maternity care to women with mobility disabilities. The study aimed to explore and describe midwives’ experiences of caring for women with mobility disabilities during pregnancy, labour and puerperium in Eswatini.

A qualitative, exploratory, descriptive, contextual research design with a phenomenological approach was followed. Twelve midwives working in maternal health facilities in the Hhohho and Manzini regions in Eswatini were interviewed. Purposive sampling was used to select midwives to participate in the research. In-depth phenomenological interviews were conducted, and Giorgi’s descriptive phenomenological method was used for data analysis.

Three themes emerged from the data analysis: midwives experienced physical and emotional strain in providing maternity care to women with mobility disabilities, they experienced frustration due to the lack of equipment to meet the needs of women with mobility disabilities, and they faced challenges in providing support and holistic care to women with mobility disabilities during pregnancy, labour and puerperium.

Conclusions

Midwives experienced challenges caring for women with mobility disabilities during pregnancy, labour and the puerperium in Eswatini. There is a need to develop and empower midwives with the knowledge and skill to implement guidelines and enact protocols. Moreover, equipment and infrastructure are required to facilitate support and holistic maternity care for women with mobility disabilities.

Peer Review reports

Globally, few studies have focused on midwives’ views of providing maternity care to women with mobility disabilities during pregnancy, labour and the puerperium [ 1 ]. In The Disabled World [ 2 ], the World Health Organisation (WHO) defines ‘disability’ as an umbrella term covering impairments, activity limitations, and participation restrictions. Furthermore, the WHO defines an ‘impairment’ as a problem in bodily function or structure; an ‘activity limitation’ as a difficulty encountered by an individual in executing a task or action; and ‘participation restriction’ as a problem experienced by an individual in various life situations [ 2 ]. In this study, mobility disabilities refer to an impairment in the functioning of the upper and lower extremities as experienced by women during pregnancy, labour and the puerperium.

Midwives, as frontline workers in the delivery of maternity care [ 3 ] responsible for the lives of the mother and the baby, are accountable for providing competent and holistic care for women during pregnancy, labour and puerperium. As part of healthcare provision, midwives play an important role in ensuring that every woman, including women with mobility disabilities, receives the best maternity care during pregnancy, labour and puerperium. Moridi et al. [ 4 ] state that women with mobility disabilities are entitled to feel safe, respected and well cared for by midwives, who must be sufficiently prepared to care for these women.

According to the Global Population Report, [ 5 ] more than one billion people have some form of disability. Eswatini is classified as a middle-income setting in the southern African region, measuring 17 000 square kilometres with a population of 1 093 238. Of the population, 76.2% reside in rural areas (833 472), and 23.8% (259 766) reside in urban areas [ 6 ]. The economy is largely agricultural as most industries manufacture agricultural products [ 7 ]. Of the Eswatini population, 146 554 (13%) live with disabilities, with most being women (87 258; 16%), 22,871 (14.1%) and 26,270 (14.3%) of them reside in the Hhohho and Manzini regions respectively [ 8 ]. 15% (125 545) of people with disabilities live in rural areas, and 85% of the disabled population is unemployed [ 8 ], which means most of these individuals are economically disadvantaged. Furthermore, according to the Eswatini Central Statistics Office, 8 26.5% of people with disabilities have a mobility (walking) disability, with 63.5% of these being women.

Midwives may encounter difficulties while aiming to achieve excellence in providing maternity care to women with mobility disabilities in what may be challenging circumstances [ 9 ]. The WHO [ 10 ] claims people with disabilities do not receive the health services they need and are thus likely to find healthcare providers have inadequate skills. Lawler et al. [ 11 ] argue that ineffective interactions and poor communication with women needing care, particularly among health professionals engaged in providing maternity services, limit these women’s opportunities to participate in decision-making processes during pregnancy, childbirth, and postpartum care. According to the University of Johannesburg, [ 12 ] the midwife, together with the mother, have to engage collaboratively in order to come up with opportunities to promote health while removing any challenges that could impede the achievement thereof.

Walsh-Gallagher et al. [ 13 ] postulate that healthcare professionals tend to view women with disabilities as liabilities and regard them as high risk; they often exclude them from the individualised plan of care, which leads to an increase in these women’s fears about their maternity care. These challenges frequently result in health disparities and prevent women with mobility disabilities from receiving optimal maternity care. By exploring midwives’ experiences of this phenomenon, guidelines for support can be developed to extend available knowledge on maternity care for women with mobility disabilities during pregnancy, labour and puerperium.

Study design

The aim of the study was to explore and describe midwives’ experiences of caring for women with mobility disabilities during pregnancy, labour and puerperium in the Hhohho and Manzini regions of Eswatini. A qualitative, [ 14 ] exploratory, [ 15 ] descriptive, [ 16 ] contextual [ 17 ] research design with a phenomenological approach [ 18 ] was applied for this study to gain insight and understanding of the research phenomenon [ 19 ]. The phenomenon under study was midwives’ lived experiences caring for women with mobility disabilities during pregnancy, labour and puerperium. The participants were approached face-to-face to participate in the study. The researchers followed the Consolidated Criteria for Reporting Qualitative Research (COREQ) to report on this qualitative study [ 20 ].

The setting for the study was the Hhohho and Manzini regions of Eswatini. The researcher collected data at the site where participants experienced the phenomenon, as emphasised by Yildiz, [ 21 ] within the context in which they were comfortable to be interviewed [ 22 ]. This setting included maternal health facilities in hospitals and public health units.

Population and sampling

The study’s population comprised midwives working in maternal health facilities in hospitals and public health units, that is, one referral hospital and one public health unit in the Hhohho region and two referral hospitals and one public health unit in the Manzini region of Eswatini. Purposive sampling was used to select midwives to participate in the study; [ 16 ] 12 midwives from both regions were included. The midwives were between the ages of 35 and 55, and all midwives were black in race and identified as females. The years of experience in the field ranged between 5 and 15 years. The criteria for inclusion were midwives who had provided maternity care to women with mobility disabilities during pregnancy, labour and puerperium for a period of not more than two to three years, willing to participate in the study. The sample size was determined by repetitions of key statements about the research phenomenon during data collection, termed data saturation [ 23 ]. None of the participants refused to participate in the study.

Table  1 summarises the participants’ demographic characteristics.

Data collection

In-depth phenomenological, face-to-face, individual interviews were conducted to collect data [ 17 ]. The researcher who was a Midwifery lecturer held a Master’s Degree in Maternal and Neonatal science at the time of the study requested approval from the Unit manager to seek permission from the midwives to take part in the study. The midwives were given an information letter which included objectives of the study and the reasons for conducting the study. After recruiting midwives and obtaining their written consent to participate in the study and permission to audio-record the interviews, the researcher set up appointments with them for the interviews, and the data collection process commenced. The central question posed to participants was: How was it for you to care for a woman with a mobility disability during pregnancy, labour and puerperium? A pilot of the tool was performed on the first participant who met the inclusion criteria and possessed the same characteristics as those of the study sample. The pre-testing question yielded positive results, the participant responded to the question asked and there was no need to rephrase it or further test it.

The interviews were conducted from March 2019 to July 2019 and lasted 30–45 min. The researcher conducted interviews until the data became redundant and repetitive, reflecting that saturation had been reached, in congruence with Fouché et al. [ 25 ] In addition, field notes were recorded in a notebook after each in-depth phenomenological interview. No repeat interviews were held. The researcher ensured bracketing by omitting any perceptions from her past experiences that were likely to influence her interpretation of the research findings.

Data analysis

Before data analysis commenced, data were organised in computer files after being transcribed and translated into narrative form. Data from each participant were coded and stored in the relevant file and kept in a safe place; only the researcher could access the information. Back-up copies were made of all the data, and the master copies were stored in a safe to which only the researcher had access.

Data collection and analysis occurred concurrently. The researcher was guided by Giorgi et al.’s [ 26 ] five-step method of data analysis. This entailed the researcher reading all the transcribed data and the entire ‘naïve description’ provided by the participants during the interviews. The demarcation of ‘meaning units’ within narratives followed. In addition, the researcher marked where meaning shifts occurred and transformed meaning units into descriptive expressions. The researcher laid out the general structure of midwives’ experiences. Moreover, an independent coder was provided with the raw data (after signing a confidentiality agreement) to analyse the findings. The researcher and independent coder analysed the data separately and met for a consensus discussion. Both agreed on all the units of analysis, with an inter-coder reliability of 100%.

Measures of trustworthiness

The research was informed by Guba and Lincoln’s [ 27 ] model in relation to credibility, transferability, dependability and confirmability. For credibility, the researcher ensured prolonged engagement in the field [ 28 ], peer debriefing, [ 29 ] member checking, and an external auditor was used [ 25 ]. The study was also presented at a national conference. Transferability refers to the ability to extend the findings of one’s study to comparable environments or participants, as stated by Pitney et al. [ 30 ] The researcher ensured the study’s transferability by providing a richly documented account and in-depth description of all aspects and processes of the study protocol. Data saturation also confirmed transferability [ 23 ]. Dependability is evident in a study when other researchers are able to follow the researcher’s decision trail [ 31 ]. The researcher ensured dependability by densely describing the research process in congruence with Fouché et al.’s [ 25 ] guidelines, so that other researchers can follow similar steps of the same research methodology. Confirmability occurs when the research is judged by the way in which the findings and conclusions achieve their aim and are not the result of the researcher’s prior assumptions and preconceptions [ 32 ]. The researcher ensured this by remaining true to the research process through reflexivity and not compromising the research process in any way [ 28 ]. In addition, the researcher engaged an independent coder and provided a chain of evidence of the entire research process to enable an audit. Therefore, all forms of collected data, including raw data, reflexive journals, [ 29 ] notes and transcriptions, were recorded.

Ethical clearance to conduct this study was obtained from the University of Johannesburg Faculty of Health Sciences Higher Degrees Committee (ref. no. HDC-01-50-2018), University of Johannesburg Faculty of Health Research Ethics Committee (ref. no. REC-01-82-2018), and the Eswatini National Health Research Review Board (ref. no. NHRRB982/2018). The researcher applied and adhered to the four principles to be considered when conducting research: autonomy, beneficence, non-maleficence and justice [ 33 ]. Autonomy was adhered to by affording the participants the right to choose to participate in the study and by signing a written informed consent form a week after it was given to them before the interviews commenced. Beneficence was ensured through doing good and doing no harm to participants by prioritising the participants’ interests above those of the researcher, and did not engage in any practice that jeopardised their rights. Non-maleficence was observed by eradicating any possible harmful risks in the study; the researcher ensured the safety of the participants by conducting interviews in a familiar, private environment where they felt free and safe from harm. Furthermore, justice was observed by treating all participants equally regardless of their biographical, social and economic status.

Three themes and categories emerged from the data analysis. Table  2 summarises the themes and categories of midwives’ lived experiences caring for women with mobility disabilities during pregnancy, labour and puerperium in Eswatini.

Theme 1: physical and emotional efforts required from midwives to provide maternity care to women with mobility disabilities

Category 1.1: midwives experienced that woman with mobility disabilities needed assistance getting onto the bed during labour and delivery.

According to the participants, caring for women with mobility disabilities weighed heavily on them physically as they were required to assist the women onto delivery beds, which were too high for the women to climb up on their own:

“The beds are too high, they need to be adjustable…unless you change her to another room, we only have one in the other room…but to be honest she delivered on the same high bed with the help…It’s uncomfortable even with me who is normal, how about someone who has a disability? Getting the woman onto the bed is also uncomfortable for us we end up having pain on our backs.” (M3) . “The challenge is that I couldn’t help her to climb on to the bed, because I needed someone to assist when she came for postnatal care as she was even carrying 3 babies, I didn’t know what to do…I eventually went out and asked for assistance from my colleague…” (M10) . “I believe that the equipment should accommodate the women with disability, however, ours is not accommodative to the women…there are no special delivery beds, specifically designed for them because in my opinion the beds have to be shorter so they can be able to get on to them easily…yes so that they can be able to climb on the beds” (M1) .

Category 1.2: midwives experienced challenges in manoeuvring women with mobility disabilities during labour

Midwives reported it was difficult to perform some procedures while progressing these women during labour and delivery. This situation called for some adjustment and improvisation on their part, and they were unsure if it was the right thing to do.

“Even though she was a bit uncomfortable and anxious because the leg was just straight and could not bend, I reassured her…She had to remove the artificial leg and remain with the stump. I placed her on the lithotomy position. With the other hand she had to hold on to the ankle of the normal foot, even though it was awkward and difficult to manoeuvre, she managed to deliver the baby.” (M1) . “Luckily for us, she didn’t sustain a tear and we were saved from suturing her cause we foresaw difficulties as how we could have done it as she couldn’t open her thighs well due to the disability…yes I had to get a partner to assist, since she couldn’t even open her thighs. She also couldn’t cooperate possibly because of the pain that is also more reason I asked for my colleague to assist.” (M6) . “…yes…let me make an example, in my case she had a fracture, even if the pelvis was gynaecoid, there were problems of finding the right position for her during delivery, when she had to push the baby out…” (M8) . “The one that I saw did not have one leg. She had come for her postnatal care. We assisted and her on the couch, with my colleague. Since she couldn’t keep her legs open, I asked my colleague to keep one of her legs open whilst I examined her.” (M12) .

Category 1.3: midwives experienced anxiety and the need to exercise patience when caring for women with mobility disabilities

The participants experienced an emotional and psychological burden when caring for women with mobility disabilities. They felt unqualified and foresaw difficulties that triggered anxiety, which led to them not knowing what to do and how to handle these women.

“It was during labour…the woman was limping the woman she was on crutches. The moment she came into the ward I am a human being I just felt sorry for her kutsi (as to) how is she going to take care of the baby, and the hand was somehow deformed.” (M3) . “At first its emotionally draining as an individual you cause you start sympathising…(other midwife chips in)…yes you even find yourself saying things just because you pity her, and in the process they get hurt.” (M6) . “It came as a shock and it was my first experience, it came as a shock as to how I was going to help her as even my experience was limited in that area.” (M7) . “As I was taking care of her it became necessary for me to put myself into her shoes and to bear with her considering her situation….When you see her for the first time you would pity her yet she is now used to it.” (M1) .

Theme 2: lack of equipment to meet the needs of women with mobility disabilities

Category 2.1: midwives reported a lack of special beds and infrastructure to meet the needs of women with mobility disabilities.

Midwives reported their frustration at the lack of sufficient equipment like special beds and examination tables, tailored for women with mobility disabilities. It was a challenge to provide maternity care for women without this equipment.

“I believe that the infrastructure and equipment should accommodate the women with mobility disability, however, ours is not accommodative to the women…Usually we don’t have the prenatal ward in the maternity, most women who come in the latent phase have to ambulate, or go to the waiting huts and come back when the labour pains are stronger…There are no special delivery beds, specifically designed for them because in my opinion the beds have to be shorter so they can be able to get on to them easily. We do not even have toilets meant for them.” (M1) . “I was anxious as to how was she going to push how to push cause we do not have the right beds when it was time for pushing I asked for assistance…” (M2) . “The challenge is that I couldn’t help her to climb on to the bed, because I needed someone to assist when she came for postnatal care…the beds need to be adjustable so that they are able to be pushed lower for the mother to move from wheel chair to the bed and we pull the bed up again to examine her.” (M11) .

Theme 3: challenges in providing holistic care to women with mobility disabilities during pregnancy, labour, and puerperium

Category 3.1: midwives reported a lack of guidelines and protocols in caring holistically for women with mobility disabilities.

Midwives emphasised a lack of guidelines, protocols and knowledge about caring holistically for women with mobility disabilities. This resulted in everyone making their own decisions and doing as they saw fit in caring for these women:

“I think during antenatal care they (the women with mobility disabilities) need to be prepared for labour cause for others the pain is extraordinary, apart from the pain threshold, they also face self-esteem issues, they are looked down upon…I only saw that she was disabled during assessment cause nothing was recorded on the antenatal care card.” (M2) . “I was not aware of the disability at first, I only discovered when she was pushing…she was admitted and progressed by another midwife, I only attended to her when she was pushing… there was nothing written on the nurse’s notes/ handover notes about her disability.” (M5) . “There is no normal practice for a woman with mobility disability when they come and they are in labour, I usually admit regardless of the stage of labour or dilatation…It is not a protocol, it’s a midwife’s prerogative.” (M1) . “We assess and come up with our own discretion even in terms of admitting them (women with mobility disability). Some midwives will admit them regardless of the stage of labour and disregard the protocol that women who come into labour have to ambulate if they are in the latent phase.” (M8) . “There is one that came the past 3 days she has 3 children now and we just scheduled her for c/section because we know that she has been having c/section since she started. Just from looking at the way she walked, we could tell that she couldn’t deliver normally.” (M9) .

Category 3.2: midwives experienced challenges in allowing significant others to support women with mobility disabilities during labour and delivery

Consequent to the challenges in providing holistic care to women with mobility disabilities, midwives experienced challenges in allowing significant others to support these women during labour and delivery.

“It can depend on the patients themselves, they should decide and we need to be flexible for it to happen…as you can see our labour room also has the issue of privacy…we would need to restructure cause we have beds for 5 or more women in labour room…and then bringing someone from outside could be tricky” (M6) . “Maybe…not sure though, that they can bring their relatives, but maybe, considering staffing limitation…also the issue of discrimination and privacy, they (the women with disabilities) might feel we discriminate against them because they are disabled we now treat them differently.” (M7) . “Maybe if she can (bring her relative) but that’s not necessary, because I can always ask my colleague to assist, unless there is no one…” (M12) .

Childbirth is a special experience that requires a personal connection between the midwife and the woman giving birth, characterised by successful communication and respect [ 34 ]. However, the themes identified in the study indicated that midwives experienced challenges caring for women with mobility disabilities during pregnancy, labour and puerperium based on their limited capacity and preparedness, and lack of protocols to care for these women. They also reported a lack of supportive equipment for women with mobility disabilities. This posed a challenge for them in attending to these women’s specific needs, and they did not always know how to handle the situation appropriately.

One of the themes centred on midwives’ experiences of the physical and emotional efforts required of them to provide maternity care to women with mobility disabilities. They explained women with mobility disabilities required assistance getting onto the bed during labour and delivery, and more manoeuvring was expected of them (as midwives) as they had to adjust their performance and some procedures. The midwives also reported challenges in providing holistic care to women with mobility disabilities during pregnancy, labour and puerperium. Konig-Bachmann et al. [ 35 ] reiterate that caring for women with disabilities requires a level of flexibility, adaptation beyond routine procedures, and demands a high degree of improvisation from healthcare providers to ensure high-quality care. Morrison et al. [ 36 ] also found that healthcare providers reported difficulties with equipment when providing healthcare for women with physical disabilities; particularly the beds being too high for them to access. Smeltzer et al. [ 37 ] similarly allude to the importance of educating and training clinicians to equip them with knowledge and technical skills to provide more effective care to women with physical disabilities.

The midwives also shared that labour and deliveries were further complicated by some women with mobility disabilities not being able to cooperate due to the pain they experienced; others could not change position due to their disability. In a study by Sonalkar et al., [ 38 ] healthcare providers described the gynaecologic examination as challenging to complete as it required patience and the ability to be adaptable to different methods and positioning. Similarly, Konig-Bachmann et al. [ 35 ] indicate that in order to provide high-quality care for women with disabilities, healthcare providers need to exercise strong flexibility, adapt beyond routine procedures, and engage in a high degree of improvisation. Byrnes and Hickey [ 39 ] concur with this study’s findings and state that due to mobility restrictions, it may be difficult to assess the fundal height and foetal growth in women with physical disabilities.

Some midwives reported their caregiving role was emotionally draining as they felt sorry and pitied the women with mobility disabilities; thus, they needed to show compassion and reassure them. According to Mgwili et al., [ 40 ] psychoanalytic thinkers associate pity among staff members upon first contact with a physically disabled person as being instigated by personal feelings, stimulated by the disability. The midwives in this study stated they needed to be more patient and adjust their approach to caring for these women. Tarasoff [ 41 ] and Schildberger et al. [ 42 ] reiterated that healthcare providers seemed uncomfortable with women’s disability, consequently failing to offer needed support. According to Sonalkar et al., [ 38 ] healthcare providers reported there would be less fear and concern about hurting women with disabilities if midwives had increased training. Similarly, Mitra et al. [ 43 ] mentioned that healthcare providers had a general lack of confidence in their ability to provide adequate maternity care for women with physical disabilities.

Another theme was midwives’ challenges in providing competent and quality care for women with mobility disabilities due to a lack of equipment, including special beds and examination tables to meet these women’s needs. The examination, labour and delivery beds were too high and could not be adjusted for the women to get on by themselves, or even with the assistance of a midwife. In addition, the midwives reported there was no prenatal ward or waiting huts where they could place these women during the latent phase of labour. The midwives further emphasised there were no special toilets for women with mobility disabilities, which made it hazardous and difficult for them. Mitra et al. [ 43 ] concur on the barriers to providing maternity care to women with physical disabilities presented from health professionals’ perspectives. The authors indicated that participants from their study reported inaccessible equipment, including examination tables, as a barrier, making it more difficult and time-consuming to care for women with physical disabilities. In addition, Sonalkar et al. [ 38 ] said healthcare providers shared their concern about the lack of adjustable examination tables and transfer equipment, thus presenting a barrier to equitable care for women with disabilities.

Midwives further reported a lack of guidelines and protocols. This resulted in everyone making their own decisions and doing as they saw fit in caring for these women, and, in most instances, not recording the disability at all during antenatal care and admission into labour records. They often only discovered that the woman had a mobility disability at a later stage, when they were in labour. Sonalkar et al. [ 38 ] reported that healthcare providers felt frustrated and overwhelmed by the uncertainty of whether they made the correct decisions when caring for women with physical disabilities due to the lack of guidelines forcing them to use their own judgement. Mitra et al. [ 43 ] determined that most healthcare providers reported a lack of maternity practice guidelines for women with physical disabilities. Also, healthcare providers highlighted the importance of learning about disabilities and having a better understanding of a condition, particularly if it is likely to be exacerbated during pregnancy [ 44 ]. The need to make and read the notes on these women’s antenatal care cards or reports was emphasised.

Due to the lack of clear guidelines and protocols in caring for women with mobility disabilities, the midwives reported they sometimes admitted the woman into the labour ward regardless of the stage of labour, while other midwives did not and wanted them to walk around and come back for admission once they are in the active phase of labour. Furthermore, the midwives explained they often referred these women for caesarean sections right away, regardless of whether the woman could deliver normally due to mere panic from just seeing the disability or based on a previous record of surgery. Smeltzer et al. [ 45 ] researched obstetric clinicians’ experiences and educational preparation in caring for pregnant women with physical disabilities, and they agree on the lack of knowledge among health professionals caring for women with mobility disability.

Devkota et al. [ 46 ] also agree regarding midwives’ inefficiency in providing quality care for women with mobility disabilities. They claim healthcare providers often struggle to understand women with disabilities’ needs as they are not formally trained to provide services to this population. These healthcare providers were found to be undertrained in specific skills that would equip them to provide better and more targeted services for women with disabilities.

Consequent to the challenges in providing holistic care to women with mobility disabilities during pregnancy, labour and puerperium, midwives experienced challenges in allowing significant others to support these women. They reported that as much as they needed assistance caring for these women, and as much as the women would prefer to have their family members or significant others assisting them, this is not possible due to the lack of privacy, especially in public health facilities. Walsh-Gallager et al.’s [ 13 ] study on the ambiguity of disabled women’s experiences of pregnancy, childbirth and motherhood resonate with this study’s findings. The authors reported that women with disabilities’ partners were denied access or had their visits curtailed on several occasions due to inflexible hospital visiting policies. Redshaw et al. [ 47 ] reiterated the same in their study; disabled women were less likely to say their companion or partner was welcome to visit, let alone provide any form of assistance. In addition, a study by Bassoumah and Mohammad [ 48 ] reported that women with disabilities were denied their spouses’ support while receiving maternity care. Byrnes and Hickey [ 39 ] also concur that every effort should be made to allow women with disabilities who are in labour to receive support from significant others, and they should be active partners in the labour process.

Limitations

The study was limited to two of the four regions of Eswatini, namely Hhohho and Manzini; hence, the results could not be generalised for the whole country. The study also only focused on mobility disabilities due to time constraints and limited funds. Future research could be conducted to cover all other forms of disabilities.

This study focused on midwives’ lived experiences caring for women with mobility disabilities during pregnancy, labour and puerperium in Eswatini. In-depth phenomenological interviews were conducted, the findings were analysed, and themes were established. The findings illustrate that midwives experienced challenges caring for women with mobility disabilities during pregnancy, labour and puerperium in Eswatini. There is a need to develop and implement guidelines to empower midwives with knowledge and skill to provide support and holistic maternity care, and enact protocols. They should also have access to appropriate equipment and infrastructure specifically tailored towards promoting optimal health for women with mobility disabilities.

Data availability

The data analysed is available from the corresponding author upon reasonable request.

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Acknowledgements

The authors would like to acknowledge the midwives in the Hhohho and Manzini regions of Eswatini who participated in the study and provided their own experiences of providing maternity care to women with mobility disabilities during pregnancy, labour and puerperium.

The research received funding from the University of Johannesburg Postgraduate Supervisor-linked Bursary.

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F.N.M conducted the research and wrote the manuscript. A.M.T supervised, reviewed, and finalised the manuscript. A.G.W.N co-supervised the study and edited the manuscript for final submission.

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Ethical clearance to conduct this study was obtained from the University of Johannesburg Faculty of Health Sciences Higher Degrees Committee (ref. no. HDC-01-50-2018), University of Johannesburg Faculty of Health Research Ethics Committee (ref. no. REC-01-82-2018) and the Eswatini National Health Research Review Board (ref. no. NHRRB982/2018). Participation in this study was voluntary, and informed consent was obtained from participants before the interviews commenced.

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Temane, A.M., Magagula, F.N. & Nolte, A.G.W. Midwives’ lived experiences of caring for women with mobility disabilities during pregnancy, labour and puerperium in Eswatini: a qualitative study. BMC Women's Health 24 , 207 (2024). https://doi.org/10.1186/s12905-024-03032-z

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Bioequivalence trials for the approval of generic drugs in Saudi Arabia: a descriptive analysis of design aspects

• Turki A. Althunian   ORCID: orcid.org/0000-0002-8030-7963 1 , 2 ,
• Bader R. Alzenaidy 3 ,
• Raseel A. Alroba 1 ,
• Ohoud A. Almadani 1 ,
• Fahad A. Alqahtani 3 ,
• Albatool A. Binajlan 3 ,
• Amal I. Almousa 3 ,
• Deema K. Alamr 3 ,
• Malak S. Al-Mofada 3 ,
• Nora Y. Alsaqer 3 ,
• Hessa A. Alarfaj 3 ,
• Abdulmohsen A. Bahlewa 3 ,
• Mohammed A. Alharbi 3 ,
• Ali M. Alhomaidan 4 ,
• Abdulaziz A. Alsuwyeh 3 &
• Abdulmohsen A. Alsaleh 3  

BMC Medical Research Methodology volume  24 , Article number:  82 ( 2024 ) Cite this article

Metrics details

This retrospective analysis aimed to comprehensively review the design and regulatory aspects of bioequivalence trials submitted to the Saudi Food and Drug Authority (SFDA) since 2017.

This was a retrospective, comprehensive analysis study. The Data extracted from the SFDA bioequivalence assessment reports were analyzed for reviewing the overall design and regulatory aspects of the successful bioequivalence trials, exploring the impact of the coefficient of variation of within-subject variability (CVw) on some design aspects, and providing an in-depth assessment of bioequivalence trial submissions that were deemed insufficient in demonstrating bioequivalence.

A total of 590 bioequivalence trials were included of which 521 demonstrated bioequivalence (440 single active pharmaceutical ingredients [APIs] and 81 fixed combinations). Most of the successful trials were for cardiovascular drugs (84 out of 521 [16.1%]), and the 2 × 2 crossover design was used in 455 (87.3%) trials. The sample size tended to increase with the increase in the CVw in trials of single APIs. Biopharmaceutics Classification System Class II and IV drugs accounted for the majority of highly variable drugs (58 out of 82 [70.7%]) in the study. Most of the 51 rejected trials were rejected due to concerns related to the study center ( n  = 21 [41.2%]).

This comprehensive analysis provides valuable insights into the regulatory and design aspects of bioequivalence trials and can inform future research and assist in identifying opportunities for improvement in conducting bioequivalence trials in Saudi Arabia.

Peer Review reports

The development of generic drugs has played a pivotal role in increasing patient access to affordable medications (90% of the prescribed drugs in the United States [U.S.] are dispensed as generics with $2.4 trillion dollars cost savings in the past decade), and has been associated with improved patient adherence and clinical outcomes [ 1 , 2 , 3 , 4 , 5 , 6 ]. These impacts were anticipated given the abbreviated nature of developing and approving generic drugs (i.e. generic drug manufacturers are precluded from replicating pre-clinical and clinical development programs of the corresponding brand-name drugs) [ 7 , 8 , 9 , 10 ]. From a clinical perspective, generic drugs are only anticipated to achieve equivalence to their corresponding brand-name drugs in terms of the rate and extent of absorption (i.e. bioequivalence) [ 7 , 8 , 9 , 10 ]. The in vivo assessment of bioequivalence is performed in the context of bioequivalence trials that are conducted mostly in a small sample of at least 24 healthy volunteers ( n  = 12 per group), and designed in a crossover fashion to demonstrate equivalence in several pharmacokinetic parameters using pre-defined bioequivalence margins [ 7 , 8 , 9 , 10 ]. However, alternative design aspects/settings might be acceptable by regulators in certain conditions (e.g. drugs with a long plasma elimination half-life, drugs with highly variable pharmacokinetic parameters, or when recruiting healthy volunteers is considered unethical for safety reasons) [ 7 , 8 , 9 , 10 ]. Notwithstanding the submission of thousands of bioequivalence trials to regulatory agencies, little is known about their designs, the extent of alternative design choices were used, and to what extent bioequivalence was demonstrated as judged by regulators both internationally and in Saudi Arabia.

Most reviews on published bioequivalence trials (or those assessed by regulators) were directed towards re-analyzing their original findings (e.g. pharmacokinetic parameter estimation, bioequivalence testing) [ 11 , 12 , 13 ]. A comprehensive design characterization was only provided by one study which covered bioequivalence trials that were assessed by the Ministry of Food and Drug Safety in South Korea [ 14 ]. However, the latter study excluded trials that did not demonstrate bioequivalence and those conducted for fixed-combination products. Additionally, the study did not provide data on some important bioequivalence design aspects (e.g. country of the trial center, patient ages, body measurements, number of patients who completed the study, details about the nature of replicated trials). None of the published reviews was conducted using data on bioequivalence trials from the Middle East in general and in Saudi Arabia in particular. In Saudi Arabia, there is a lack of knowledge about bioequivalence data of the approved generic drugs in the Saudi health market [ 15 , 16 ]. Studies have shown that medical representatives have been the major source of clinical information about generic drugs for physicians, and only small proportion relies on published bioequivalence trials [ 17 , 18 ]. A panel of Saudi experts also recommended providing more data about bioequivalence trials for the approved generic drugs in the Saudi Arabia [ 15 , 18 ].

Since the establishment of the new electronic recording system of bioequivalence trials at the Saudi Food and Drug Authority (SFDA) in 2017, hundreds of bioequivalence trials have been reviewed by the SFDA’s evaluators for the approval of generic drugs in Saudi Arabia. The review process has been based on the SFDA Guidelines for Bioequivalence and on the SFDA’s Product Specific Bioequivalence Guidance [ 7 , 8 ]. This study was aimed to provide comprehensive review of all bioequivalence trials that were assessed by the SFDA since 2017 from a design and regulatory perspective.

Study design and data source

This was a retrospective, comprehensive analysis study. The SFDA generates assessment reports for bioequivalence trials if they were included in generic drug registration applications (one report for all bioequivalence trials per drug application). In each assessment report, all details per trial about the design, technical, and logistic aspects are added, with feedback on each aspect from the SFDA’s scientific evaluators. Each report ends with a decision on whether bioequivalence was demonstrated, was not demonstrated, or whether a decision could not be reached due to concerns related to the design or conduct of the trial. Data for trials since 2017 were extracted by the study team members using several data collection sheets. Approval from the SFDA Institutional Review Board was granted (the data are confidential and not available in the public domain of the SFDA).

SFDA requirements for bioequivalence testing

Based on the SFDA guidelines [ 7 ], the successful demonstration of bioequivalence is conditional mainly on the following:

Achieving statistical equivalence in the targeted pharmacokinetic parameters : The 90% confidence interval (CI) for the ratio of the test generic drug vs. reference brand-name drug must be contained within 80.0 to 125.0% equivalence margins in the targeted pharmacokinetic parameters, mainly the area under the plasma concentration curve from administration to last observed concentration at time t (AUC 0-t ) and the maximum plasma concentration (C max ). Stricter equivalence margins are required for drugs with a narrow therapeutic index. However, more lenient margins (up to a maximum of 69.84 to 143.19 in C max ) might be acceptable with highly variable drugs, i.e., CVw > 30%.

Choosing the right design aspects : The typical 2-sequence, 2-period, crossover design (i.e., 2 × 2) under fasting conditions is generally requested for immediate-release oral formulations, unless the brand-name drug is administered under fed conditions. Two 2 × 2 bioequivalence trials (one under fasting and one under fed conditions) are required for specific dosage forms (e.g., modified-release dosage forms, microemulsions, and solid dispersions). Alternative designs (e.g., replicate and parallel trial designs) could be considered in highly variable drugs or in drugs with a long elimination half-life (t 1/2 ). Other considerations about alternative design aspects are provided in the SFDA Guidelines for Bioequivalence and by the SFDA Product Specific Guidelines.

Compliance with quality and other regulatory standards : Assessing bioequivalence findings cannot be completed without meeting certain quality and regulatory standards. Examples of these standards are the selection of the production batch, specifications of critical quality attributes, whether the trial was conducted in a center accredited by the SFDA, and the choice of bioanalytical methodology.

Study outcomes and statistical analysis

Our review of bioequivalence trials that were assessed by the SFDA was conducted for three outcomes: reviewing the overall design and regulatory aspects of bioequivalence trials that were deemed successful by the SFDA in demonstrating bioequivalence, exploring the nature of within-subject variability in these trials and its relevance to other design aspects (e.g. the trial sample size), and providing an in-depth assessment of bioequivalence trial submissions that were deemed insufficient in demonstrating bioequivalence.

The overall review of the successful bioequivalence trials covered the following: the biopharmaceutics classification system (BCS), the therapeutic class of the active pharmaceutical ingredient (API) which was determined according to the World Health Organization Anatomical Therapeutic Chemical codes (ATC), the dosage form, the safety index (wide vs. narrow therapeutic index), the trial center, the trial design (2 × 2 crossover, replicate or parallel designs), the study condition (fasting vs. fed), masking study participants (blinding vs. open-label designs), the washout period, the sample size, the choice of equivalence margins, the coefficient of variation of within-subject variability (CVw), age, sex, and body mass index. The review was conducted at the single-API and fixed-combination levels.

The extracted CVws from the accepted trials (for both single APIs and fixed combinations) were assessed in relation to the trial sample size , trial design, and the different BCS classes (the recent Korean review found that highly variable drugs are mostly BCS Class II or IV [i.e. drugs with poor solubility]) [ 14 ]. Reasons for rejecting the submission of bioequivalence trials or for rejecting their results were explored in addition to the success rate of study centers per country. All study outcomes were analyzed descriptively using RStudio Version 2022.12.0.

A total of 590 bioequivalence trials were included in the study (Fig. 1 ). Bioequivalence was demonstrated in 521 trials (440 and 81 trials for single-API and fixed combination drugs; respectively), which were used to evaluate bioequivalence for 184 unique APIs and 36 unique fixed combinations. The remaining 69 of 590 were rejected either due to failed submissions of marketing authorization applications or due to the failure of a trial to demonstrate bioequivalence. Of the included trials, 240 (40.7%) were conducted ≥ 2017 (the trial date was not available for one trial). Almost two-third of 590 trial were conducted using Jordanian and Indian populations (237 and 203 trial centers; respectively), and 98 trials (16.6%) were conducted in European centers (only one study was conducted in Saudi Arabia).

The process of selecting the included bioequivalence trials

The design of the successful bioequivalence trials

Most of the 521 successful trials were conducted for single APIs/fixed-combinations of the cardiovascular system (84 of 521 [16.1%]), antineoplastic and immunomodulating drugs (75 [14.4%]), drugs for alimentary tract and metabolism (73 [14.0%]), and drugs for the nervous system (65 [12.5%]), Fig. 2 . More than half of single-API trials were BCS Class I drugs, and most BCS combinations in the fixed-combinations were BCS Class I and II combination and Class I and III combination (15 combinations each). Almost two-third and all of single-API and fixed-combination trials were conducted for tablet and capsule dosage forms; respectively (Table 1 ). A large proportion (79.0%) was conducted under fasting conditions (85.5% of these trials were conducted for immediate-release dosage oral dosage forms), and all trials. except for six, were conducted for drugs with a wide therapeutic index.

The most common therapeutic classes of successful trials

The typical 2 × 2 crossover design was used in 455 (87.3%) trials. The replicate design was used in 58 trials (wider C max equivalence margins were used in 25 of 58 replicate trials). Nine trials were designed as randomized, parallel design trials (four trials for generic forms of fingolimod hydrochloride, and five for enzalutamide, toremifene, entecavir, and terifunormide). The range of t 1/2 for drugs in these nine parallel trials was 4 to 20 days. The range of the sample size was 12 to 216. The median sample size for the single APIs was 36, and per trial design, the parallel-design trials had the highest median number of study participants ( n  = 71), followed by the replicate and 2 × 2 crossover trials (40 and 35; respectively). Similarly, the fixed-combination trials had a median of the sample size ( n  = 36), and almost comparable medians per trial design ( n  = 39 and 36 for the replicate and 2 × 2 crossover trials).

CVw, sample size, trial design and BCS classification

Figure 3 shows that the sample size tended to increase with the increase in CVw in bioequivalence trials of single APIs. The median sample size in trials of highly variable, single APIs was higher vs. the median in trials of drugs with CVw of ≤30%. This trend was not observed in trials of the fixed-combinations (Fig. 3 ); however, the median sample size in trials of fixed-combinations with a highly variable API was slightly higher vs. those low-CVw APIs (40 vs. 36; respectively).

Trials with replicate design had the highest median CVw for both the single APIs (33.5% vs. 18.9% vs. 16.3% compared with the 2 × 2 crossover and parallel trials; respectively) and the fixed combinations (31.1% vs. 19.8% compared with the 2 × 2 crossover trials). BCS Class II and IV drugs accounted for most of the highly variable drugs (58 of 82 [70.7%] of the highly variable drugs in the successful trials were BCS Class II and IV drugs). Figure 4 shows the distribution of CVw at the BCS class level in the single-API trials.

The distribution of CVws per BCS class. Class I: Trials with BCS Class I active pharmaceutical ingredients. Class II: Trials with BCS Class II active pharmaceutical ingredients. Class III: Trials with BCS Class III active pharmaceutical ingredients. Class IV: Trials with Class IV active pharmaceutical ingredients

The rejected bioequivalence trials

Justifications for the SFDA rejection was available for 51 of 69 (73.9%) rejected trials (Table 2 ). Most of these 51 trials ( n  = 21 [41.2%]) were rejected due to concerns related to the study centers (e.g. the center was not accredited by the SFDA; the center was suspended by the SFDA or a reference regulatory authority [e.g. US FDA or EMA]). Ten trials (19.6%) failed do demonstrate bioequivalence, and 17 had major regulatory or design concerns or concerns related to the quality of the APIs (Table 2 ).

There were four unsuccessful attempts to obtain waivers for demonstrating bioequivalence through in-vivo testing, commonly known as biowaivers. The first was denied because the request to register a 20 mg generic form of rosuvastatin relied on previous in-vivo bioequivalence data from the unregistered higher strength of 40 mg (i.e., additional strength waiver requests for generic drugs might be acceptable if the maximum strength is approved by the SFDA). Additionally, two other requests for biowaivers were made for generic forms of two drugs, ibuprofen and mirtazapine, which are not classified as BCS Class I (the SFDA only accepts biowaiver requests for BCS Class I drugs). The fourth and final rejected request was for a generic form of dabigatran etexilate mesylate, which failed in the in-vitro comparative dissolution testing—a requirement by the SFDA for biowaiver applications.

Figure 5 illustrates the risk of rejecting a bioequivalence trial per country. There were five countries with a number of conducted bioequivalence trials of higher than 10: Jordan ( n  = 237), India (203), Canada ( n  = 47), Egypt ( n  = 41), and Romania ( n  = 15). The highest risk of rejection among these five countries was in Egypt (48.8%), followed by Canada (12.8%), and Jordan (8.4%). The SFDA rejection decision in the Egyptian trials was driven by one of the three trial centers, which led to its suspension by the SFDA.

The risk of rejecting bioequivalence trials per country

For the support of the marketing authorization of generic drugs in Saudi Arabia, we found that the majority of submitted bioequivalence trials were accepted by the SFDA. Most were designed in the conventional 2 × 2 crossover format, with a focus on immediate-release dosage forms. These trials were primarily conducted in Jordan and India, with most drugs exhibiting low CVw. Additionally, a significant proportion of the trials involved BCS Class II drugs, and the therapeutic categories most frequently tested were drugs for the cardiovascular system, and antineoplastic agents and immunomodulatory drugs. Studies involving single APIs with high CVw tended to require larger sample sizes, with BCS Class II and IV drugs accounting for the majority of high CVw drugs. Finally, our findings indicate that conducting trials at centers not accredited by the SFDA or suspended by other stringent authorities is likely to result in trial rejection.

Several design aspects of the accepted bioequivalence trials in our study share similarities with those submitted to other regulators [ 13 , 14 , 19 ]. This similarity can be attributed to the common adoption of a 2 × 2 crossover design, immediate-release oral dosage forms, and drugs for the cardiovascular system as the most commonly targeted therapeutic class. Our study identified six parallel trials, which typically had a larger sample size than other designs (median sample sizes were 70, 40, and 35 for parallel, replicate, and crossover trials; respectively). The range of sample sizes in our study was wider compared to those reported in published reviews (12 to 216 versus 12 to 170) [ 13 , 14 ]. Our study also revealed that an increase in sample size was necessary to accommodate an increase in CVw for trials with single APIs. Notably, we observed that the replicate design had the highest median CVw, as expected. Consistent with previous research, which found that CVw was influenced by solubility-limited absorption and/or low permeability, our results indicated that BCS Class II and IV drugs accounted for the highest variability [ 14 , 20 ].

The age range of trial participants in our study was wider (18 to 87 years) than those reported in previous reviews (18 to 60 years) [ 13 , 19 ]. The SFDA might accept an age limit higher than 60 years if adequately justified by the marketing authorization holder. Almost two-third of the trials in our study were conducted under fasting conditions, similar to trials conducted in South Korea [ 19 ]. Only six trials were conducted for narrow-therapeutic index drugs, and no data from published reviews were available for these drugs. Only one study was conducted in Saudi Arabia, with the majority of trials conducted in Jordanian and Indian populations. Further studies are needed to explore opportunities and to identify gaps in conducting bioequivalence in Saudi Arabia, and to determine the extent to which bioequivalence results can be extrapolated directly to the Saudi population as a previous study found differences in fed-between-population pharmacokinetic parameters [ 21 ].

The study findings indicated a potential lack of understanding or insufficient knowledge regarding SFDA requirements and guidelines for the design and conduct of bioequivalence trials. For instance, conducting trials at centers not accredited by the SFDA resulted in a rejection of 23 bioequivalence trials, and two trials were rejected because the approved brand-name drug was not chosen as the reference drug. There might also be insufficient awareness for the conditions of accepting applications for biowaivers. The SFDA published a comprehensive product-specific bioequivalence guideline in 2022 and they have advised marketing authorization holders to seek for an SFDA scientific advice during the design, conduct or submission stages if further clarification is needed [ 8 ]. The number of SFDA bioequivalence scientific advice letters/meetings increased in the first two months of 2024 in comparison with those of 2023 (43 vs. 15; respectively). The SFDA is in the process of updating its guideline for biowaivers to include more details with illustrative examples. These initiatives are expected to facilitate the development of generic drugs and reduce the number of failed or suboptimal applications for demonstrating or waiving bioequivalence [ 22 ].

Our study provides a comprehensive assessment of bioequivalence trials submitted to a regulator for marketing authorizations of generic drugs, making it among the few studies of its kind and the first in the Middle East. We presented a summary of the design, conduct, and regulatory aspects of these trials, investigated the association of CVw with certain design factors, and analyzed trials rejected by the SFDA in an effort to support the implementation of these trials in the region. However, our study had several limitations. Trials submitted for marketing authorization prior to the introduction of the new electronic recording system for bioequivalence trials in 2017 were not included in our analysis. Additionally, we did not evaluate the selection of reference drugs in these trials or explore the submission of marketing authorization applications for biowaivers. Future studies that address these aspects would complement the findings of our study.

Conclusions

In conclusion, this study provides valuable insights into the design, conduct, and regulatory aspects of bioequivalence trials submitted to the SFDA for marketing authorization of generic drugs in Saudi Arabia. The findings of this study highlight the need for further research to explore opportunities and identify gaps in conducting bioequivalence trials in Saudi Arabia.

Availability of data and materials

The datasets generated during and/or analysed during the current study are not publicly available due to confidentiality but are available from the corresponding author on reasonable request.

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Contributions

Turki A. Althunian, Bader R. Alzenaidy, Abdulaziz A. Alsuwyeh, and Abdulmohsen A. Alsaleh designed the study. Turki A. Althunian, Bader R. Alzenaidy, Raseel A. Alroba, Ohoud  A. Almadani, Fahad A. Alqahtani,  Albatool A. Binajlan,  Amal I. Almousa, Deema K. Alamr, Malak S. Al-Mofada, Nora Y. Alsaqer , Hessa A. Alarfaj, Abdulmohsen A. Bahlewa, Mohammed A. Alharbi, Ali M. Alhomaidan, Abdulaziz A. Alsuwyeh, and Abdulmohsen A. Alsaleh involved in the study conduct, data collection and analysis. Turki A. Althunian wrote the manuscript, and the final version of the manuscript was reviewed by all authors and approved by the study supervisors (Turki A. Althunian and Abdulmohsen A. Alsaleh).

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Correspondence to Turki A. Althunian .

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Our study did not involve human participants and consent forms were not required. The study included anonymized human data from anonymized bioequivalence trials. As a result, an assessment by the SFDA’s institutional review board was deemed unnecessary by the board. However, the final draft of the manuscript was approved by the SFDA’s Research Committee for the publication. (approval number: RL-2022-016).

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Althunian, T.A., Alzenaidy, B.R., Alroba, R.A. et al. Bioequivalence trials for the approval of generic drugs in Saudi Arabia: a descriptive analysis of design aspects. BMC Med Res Methodol 24 , 82 (2024). https://doi.org/10.1186/s12874-024-02207-4

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Received : 29 November 2023

Accepted : 22 March 2024

Published : 05 April 2024

DOI : https://doi.org/10.1186/s12874-024-02207-4

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