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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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• 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

Dovetail streamlines analysis to help you uncover and share actionable insights

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!

extremely very educative

Indeed very educative and useful. Well explained. Thank you

Simple,easy to understand

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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.

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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.

Related resources

Market intelligence 10 min read, marketing insights 11 min read, ethnographic research 11 min read, qualitative vs quantitative research 13 min read, qualitative research questions 11 min read, qualitative research design 12 min read, primary vs secondary research 14 min read, request demo.

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• Knowledge Base
• Methodology
• 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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41.1 What Is Descriptive Research?

The type of question asked by the researcher will ultimately determine the type of approach necessary to complete an accurate assessment of the topic at hand. Descriptive studies, primarily concerned with finding out "what is," might be applied to investigate the following questions: Do teachers hold favorable attitudes toward using computers in schools? What kinds of activities that involve technology occur in sixth-grade classrooms and how frequently do they occur? What have been the reactions of school administrators to technological innovations in teaching the social sciences? How have high school computing courses changed over the last 10 years? How do the new multimediated textbooks compare to the print-based textbooks? How are decisions being made about using Channel One in schools, and for those schools that choose to use it, how is Channel One being implemented? What is the best way to provide access to computer equipment in schools? How should instructional designers improve software design to make the software more appealing to students? To what degree are special-education teachers well versed concerning assistive technology? Is there a relationship between experience with multimedia computers and problem-solving skills? How successful is a certain satellite-delivered Spanish course in terms of motivational value and academic achievement? Do teachers actually implement technology in the way they perceive? How many people use the AECT gopher server, and what do they use if for?

Descriptive research can be either quantitative or qualitative. It can involve collections of quantitative information that can be tabulated along a continuum in numerical form, such as scores on a test or the number of times a person chooses to use a-certain feature of a multimedia program, or it can describe categories of information such as gender or patterns of interaction when using technology in a group situation. Descriptive research involves gathering data that describe events and then organizes, tabulates, depicts, and describes the data collection (Glass & Hopkins, 1984). It often uses visual aids such as graphs and charts to aid the reader in understanding the data distribution. Because the human mind cannot extract the full import of a large mass of raw data, descriptive statistics are very important in reducing the data to manageable form. When in-depth, narrative descriptions of small numbers of cases are involved, the research uses description as a tool to organize data into patterns that emerge during analysis. Those patterns aid the mind in comprehending a qualitative study and its implications.

Most quantitative research falls into two areas: studies that describe events and studies aimed at discovering inferences or causal relationships. Descriptive studies are aimed at finding out "what is," so observational and survey methods are frequently used to collect descriptive data (Borg & Gall, 1989). Studies of this type might describe the current state of multimedia usage in schools or patterns of activity resulting from group work at the computer. An example of this is Cochenour, Hakes, and Neal's (1994) study of trends in compressed video applications with education and the private sector.

Descriptive studies report summary data such as measures of central tendency including the mean, median, mode, deviance from the mean, variation, percentage, and correlation between variables. Survey research commonly includes that type of measurement, but often goes beyond the descriptive statistics in order to draw inferences. See, for example, Signer's (1991) survey of computer-assisted instruction and at-risk students, or Nolan, McKinnon, and Soler's (1992) research on achieving equitable access to school computers. Thick, rich descriptions of phenomena can also emerge from qualitative studies, case studies, observational studies, interviews, and portfolio assessments. Robinson's (1994) case study of a televised news program in classrooms and Lee's (1994) case study about identifying values concerning school restructuring are excellent examples of case studies.

Descriptive research is unique in the number of variables employed. Like other types of research, descriptive research can include multiple variables for analysis, yet unlike other methods, it requires only one variable (Borg & Gall, 1989). For example, a descriptive study might employ methods of analyzing correlations between multiple variables by using tests such as Pearson's Product Moment correlation, regression, or multiple regression analysis. Good examples of this are the Knupfer and Hayes (1994) study about the effects of the Channel One broadcast on knowledge of current events, Manaev's (1991) study about mass media effectiveness, McKenna's (1993) study of the relationship between attributes of a radio program and it's appeal to listeners, Orey and Nelson's (1994) examination of learner interactions with hypermedia environments, and Shapiro's (1991) study of memory and decision processes.

On the other hand, descriptive research might simply report the percentage summary on a single variable. Examples of this are the tally of reference citations in selected instructional design and technology journals by Anglin and Towers (1992); Barry's (1994) investigation of the controversy surrounding advertising and Channel One; Lu, Morlan, Lerchlorlarn, Lee, and Dike's (1993) investigation of the international utilization of media in education (1993); and Pettersson, Metallinos, Muffoletto, Shaw, and Takakuwa's (1993) analysis of the use of verbo-visual information in teaching geography in various countries.

Descriptive statistics utilize data collection and analysis techniques that yield reports concerning the measures of central tendency, variation, and correlation. The combination of its characteristic summary and correlational statistics, along with its focus on specific types of research questions, methods, and outcomes is what distinguishes descriptive research from other research types.

Three main purposes of research are to describe, explain, and validate findings. Description emerges following creative exploration, and serves to organize the findings in order to fit them with explanations, and then test or validate those explanations (Krathwohl, 1993). Many research studies call for the description of natural or man-made phenomena such as their form, structure, activity, change over time, relation to other phenomena, and so on. The description often illuminates knowledge that we might not otherwise notice or even encounter. Several important scientific discoveries as well as anthropological information about events outside of our common experiences have resulted from making such descriptions. For example, astronomers use their telescopes to develop descriptions of different parts of the universe, anthropologists describe life events of socially atypical situations or cultures uniquely different from our own, and educational researchers describe activities within classrooms concerning the implementation of technology. This process sometimes results in the discovery of stars and stellar events, new knowledge about value systems or practices of other cultures, or even the reality of classroom life as new technologies are implemented within schools.

Educational researchers might use observational, survey, and interview techniques to collect data about group dynamics during computer-based activities. These data could then be used to recommend specific strategies for implementing computers or improving teaching strategies. Two excellent studies concerning the role of collaborative groups were conducted by Webb (1982), and Rysavy and Sales (1991). Noreen Webb's landmark study used descriptive research techniques to investigate collaborative groups as they worked within classrooms. Rysavy and Sales also apply a descriptive approach to study the role of group collaboration for working at computers. The Rysavy and Sales approach did not observe students in classrooms, but reported certain common findings that emerged through a literature search.

Descriptive studies have an important role in educational research. They have greatly increased our knowledge about what happens in schools. Some of the important books in education have reported studies of this type: Life in Classrooms, by Philip Jackson; The Good High School, by Sara Lawrence Lightfoot; Teachers and Machines: The Classroom Use of Technology Since 1920, by Larry Cuban; A Place Called School, by John Goodlad; Visual Literacy: A Spectrum of Learning, by D. M. Moore and Dwyer; Computers in Education: Social, Political, and Historical Perspectives, by Muffoletto and Knupfer; and Contemporary Issues in American Distance Education, by M. G. Moore.

Henry J. Becker's (1986) series of survey reports concerning the implementation of computers into schools across the United States as well as Nancy Nelson Knupfer's (1988) reports about teacher's opinions and patterns of computer usage also fit partially within the realm of descriptive research. Both studies describe categories of data and use statistical analysis to examine correlations between specific variables. Both also go beyond the bounds of descriptive research and conduct further statistical procedures appropriate to their research questions, thus enabling them to make further recommendations about implementing computing technology in ways to support grassroots change and equitable practices within the schools. Finally, Knupfer's study extended the analysis and conclusions in order to yield suggestions for instructional designers involved with educational computing.

41.1.1 The Nature of Descriptive Research

The descriptive function of research is heavily dependent on instrumentation for measurement and observation (Borg & Gall, 1989). Researchers may work for many years to perfect such instrumentation so that the resulting measurement will be accurate, reliable, and generalizable. Instruments such as the electron microscope, standardized tests for various purposes, the United States census, Michael Simonson's questionnaires about computer usage, and scores of thoroughly validated questionnaires are examples of some instruments that yield valuable descriptive data. Once the instruments are developed, they can be used to describe phenomena of interest to the researchers.

The intent of some descriptive research is to produce statistical information about aspects of education that interests policy makers and educators. The National Center for Education Statistics specializes in this kind of research. Many of its findings are published in an annual volume

called Digest of Educational Statistics. The center also administers the National Assessment of Educational Progress (NAEP), which collects descriptive information about how well the nation's youth are doing in various subject areas. A typical NAEP publication is The Reading Report Card, which provides descriptive information about the reading achievement of junior high and high school students during the past 2 decades.

On a larger scale, the International Association for the Evaluation of Education Achievement (IEA) has done major descriptive studies comparing the academic achievement levels of students in many different nations, including the United States (Borg & Gall, 1989). Within the United States, huge amounts of information are being gathered continuously by the Office of Technology Assessment, which influences policy concerning technology in education. As a way of offering guidance about the potential of technologies for distance education, that office has published a book called Linking for Learning: A New Course for Education, which offers descriptions of distance education and its potential.

There has been an ongoing debate among researchers about the value of quantitative (see 40.1.2) versus qualitative research, and certain remarks have targeted descriptive research as being less pure than traditional experimental, quantitative designs. Rumors abound that young researchers must conduct quantitative research in order to get published in Educational Technology Research and Development and other prestigious journals in the field. One camp argues the benefits of a scientific approach to educational research, thus preferring the experimental, quantitative approach, while the other camp posits the need to recognize the unique human side of educational research questions and thus prefers to use qualitative research methodology. Because descriptive research spans both quantitative and qualitative methodologies, it brings the ability to describe events in greater or less depth as needed, to focus on various elements of different research techniques, and to engage quantitative statistics to organize information in meaningful ways. The citations within this chapter provide ample evidence that descriptive research can indeed be published in prestigious journals.

Descriptive studies can yield rich data that lead to important recommendations. For example, Galloway (1992) bases recommendations for teaching with computer analogies on descriptive data, and Wehrs (1992) draws reasonable conclusions about using expert systems to support academic advising. On the other hand, descriptive research can be misused by those who do not understand its purpose and limitations. For example, one cannot try to draw conclusions that show cause and effect, because that is beyond the bounds of the statistics employed.

Borg and Gall (1989) classify the outcomes of educational research into the four categories of description, prediction, improvement, and explanation. They say that descriptive research describes natural or man-made educational phenomena that is of interest to policy makers and educators. Predictions of educational phenomenon seek to determine whether certain students are at risk and if teachers should use different techniques to instruct them. Research about improvement asks whether a certain technique does something to help students learn better and whether certain interventions can improve student learning by applying causal-comparative, correlational, and experimental methods. The final category of explanation posits that research is able to explain a set of phenomena that leads to our ability to describe, predict, and control the phenomena with a high level of certainty and accuracy. This usually takes the form of theories.

The methods of collecting data for descriptive research can be employed singly or in various combinations, depending on the research questions at hand. Descriptive research often calls upon quasi-experimental research design (Campbell & Stanley, 1963). Some of the common data collection methods applied to questions within the realm of descriptive research include surveys, interviews, observations, and portfolios.

Survey descriptive research: Method, design, and examples

• November 2, 2022

What is survey descriptive research?

The observational method: monitor people while they engage with a subject, the case study method: gain an in-depth understanding of a subject, survey descriptive research: easy and cost-effective, types of descriptive research design, what is the descriptive survey research design definition by authors, 1. quantitativeness and qualitatively, 2. uncontrolled variables, 3. natural environment, 4. provides a solid basis for further research, describe a group and define its characteristics, measure data trends by conducting descriptive marketing research, understand how customers perceive a brand, descriptive survey research design: how to make the best descriptive questionnaire, create descriptive surveys with surveyplanet.

Survey descriptive research is a quantitative method that focuses on describing the characteristics of a phenomenon rather than asking why it occurs. Doing this provides a better understanding of the nature of the subject at hand and creates a good foundation for further research.

Descriptive market research is one of the most commonly used ways of examining trends and changes in the market. It is easy, low-cost, and provides valuable in-depth information on a chosen subject.

This article will examine the basic principles of the descriptive survey study and show how to make the best descriptive survey questionnaire and how to conduct effective research.

It is often said to be quantitative research that focuses more on the what, how, when, and where instead of the why. But what does that actually mean?

The answer is simple. By conducting descriptive survey research, the nature of a phenomenon is focused upon without asking about what causes it.

The main goal of survey descriptive research is to shed light on the heart of the research problem and better understand it. The technique provides in-depth knowledge of what the research problem is before investigating why it exists.

Survey descriptive research and data collection methods

Descriptive research methods can differ based on data collection. We distinguish three main data collection methods: case study, observational method, and descriptive survey method.

Of these, the descriptive survey research method is most commonly used in fields such as market research, social research, psychology, politics, etc.

Sometimes also called the observational descriptive method, this is simply monitoring people while they engage with a particular subject. The aim is to examine people’s real-life behavior by maintaining a natural environment that does not change the respondents’ behavior—because they do not know they are being observed.

It is often used in fields such as market research, psychology, or social research. For example, customers can be monitored while dining at a restaurant or browsing through the products in a shop.

When doing case studies, researchers conduct thorough examinations of individuals or groups. The case study method is not used to collect general information on a particular subject. Instead, it provides an in-depth understanding of a particular subject and can give rise to interesting conclusions and new hypotheses.

The term case study can also refer to a sample group, which is a specific group of people that are examined and, afterward, findings are generalized to a larger group of people. However, this kind of generalization is rather risky because it is not always accurate.

Additionally, case studies cannot be used to determine cause and effect because of potential bias on the researcher’s part.

The survey descriptive research method consists of creating questionnaires or polls and distributing them to respondents, who then answer the questions (usually a mix of open-ended and closed-ended).

Surveys are the easiest and most cost-efficient way to gain feedback on a particular topic. They can be conducted online or offline, the size of the sample is highly flexible, and they can be distributed through many different channels.

When doing market research , use such surveys to understand the demographic of a certain market or population, better determine the target audience, keep track of the changes in the market, and learn about customer experience and satisfaction with products and services.

Several types of survey descriptive research are classified based on the approach used:

• Descriptive surveys gather information about a certain subject.
• Descriptive-normative surveys gather information just like a descriptive survey, after which results are compared with a norm.
• Correlative surveys explore the relationship between two variables and conclude if it is positive, neutral, or negative.

A descriptive survey research design is a methodology used in social science and other fields to gather information and describe the characteristics, behaviors, or attitudes of a particular population or group of interest. While there may not be a single definition provided by specific authors, the concept is widely understood and defined similarly across the literature.

Here’s a general definition that captures the essence of a descriptive survey research design definition by authors:

A descriptive survey research design is a systematic and structured approach to collecting data from a sample of individuals or entities within a larger population, with the primary aim of providing a detailed and accurate description of the characteristics, behaviors, opinions, or attitudes that exist within the target group. This method involves the use of surveys, questionnaires, interviews, or observations to collect data, which is then analyzed and summarized to draw conclusions about the population of interest.

It’s important to note that descriptive survey research is often used when researchers want to gain insights into a population or phenomenon, but without manipulating variables or testing hypotheses, as is common in experimental research. Instead, it focuses on providing a comprehensive overview of the subject under investigation. Researchers often use various statistical and analytical techniques to summarize and interpret the collected data in descriptive survey research.

The characteristics and advantages of a descriptive survey questionnaire

There are numerous advantages to using a descriptive survey design. First of all, it is cheap and easy to conduct. A large sample can be surveyed and extensive data gathered quickly and inexpensively.

The data collected provides both quantitative and qualitative information , which provides a holistic understanding of the topic. Moreover, it can be used in further research on this or related topics.

Here are some of the most important advantages of conducting a survey descriptive research:

The descriptive survey research design uses both quantitative and qualitative research methods. It is used primarily to conduct quantitative research and gather data that is statistically easy to analyze. However, it can also provide qualitative data that helps describe and understand the research subject.

Descriptive research explores more than one variable. However, unlike experimental research, descriptive survey research design doesn’t allow control of variables. Instead, observational methods are used during research. Even though these variables can change and have an unexpected impact on an inquiry, they will give access to honest responses.

The descriptive research is conducted in a natural environment. This way, answers gathered from responses are more honest because the nature of the research does not influence them.

The data collected through descriptive research can be used to further explore the same or related subjects. Additionally, it can help develop the next line of research and the best method to use moving forward.

Descriptive survey example: When to use a descriptive research questionnaire?

Descriptive research design can be used for many purposes. It is mainly utilized to test a hypothesis, define the characteristics of a certain phenomenon, and examine the correlations between them.

Market research is one of the main fields in which descriptive methods are used to conduct studies. Here’s what can be done using this method:

Understanding the needs of customers and their desires is the key to a business’s success. By truly understanding these, it will be possible to offer exactly what customers need and prevent them from turning to competitors.

By using a descriptive survey, different customer characteristics—such as traits, opinions, or behavior patterns—can be determined. With this data, different customer types can be defined and profiles developed that focus on their interests and the behavior they exhibit. This information can be used to develop new products and services that will be successful.

Measuring data trends is extremely important. Explore the market and get valuable insights into how consumers’ interests change over time—as well as how the competition is performing in the marketplace.

Over time, the data gathered from a descriptive questionnaire can be subjected to statistical analysis. This will deliver valuable insights.

Another important aspect to consider is brand awareness. People need to know about your brand, and they need to have a positive opinion of it. The best way to discover their perception is to conduct a brand survey , which gives deeper insight into brand awareness, perception, identity, and customer loyalty .

When conducting survey descriptive research, there are a few basic steps that are needed for a survey to be successful:

• Define the research goals.
• Decide on the research method.
• Define the sample population.
• Design the questionnaire.
• Write specific questions.
• Distribute the questionnaire.
• Analyze the data .
• Make a survey report.

First of all, define the research goals. By setting up clear objectives, every other step can be worked through. This will result in the perfect descriptive questionnaire example and collect only valuable data.

Next, decide on the research method to use—in this case, the descriptive survey method. Then, define the sample population for (that is, the target audience). After that, think about the design itself and the questions that will be asked in the survey .

If you’re not sure where to start, we’ve got you covered. As free survey software, SurveyPlanet offers pre-made themes that are clean and eye-catching, as well as pre-made questions that will save you the trouble of making new ones.

Simply scroll through our library and choose a descriptive survey questionnaire sample that best suits your needs, though our user-friendly interface can help you create bespoke questions in a process that is easy and efficient.

With a survey in hand, it will then need to be delivered to the target audience. This is easy with our survey embedding feature, which allows for the linking of surveys on a website, via emails, or by sharing on social media.

When all the responses are gathered, it’s time to analyze them. Use SurveyPlanet to easily filter data and do cross-sectional analysis. Finally, just export the results and make a survey report.

Conducting descriptive survey research is the best way to gain a deeper knowledge of a topic of interest and develop a sound basis for further research. Sign up for a free SurveyPlanet account to start improving your business today!

Photo by Scott Graham on Unsplash

Qualitative vs Quantitative Research Methods & Data Analysis

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

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Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

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What is the difference between quantitative and qualitative?

The main difference between quantitative and qualitative research is the type of data they collect and analyze.

Quantitative research collects numerical data and analyzes it using statistical methods. The aim is to produce objective, empirical data that can be measured and expressed in numerical terms. Quantitative research is often used to test hypotheses, identify patterns, and make predictions.

Qualitative research , on the other hand, collects non-numerical data such as words, images, and sounds. The focus is on exploring subjective experiences, opinions, and attitudes, often through observation and interviews.

Qualitative research aims to produce rich and detailed descriptions of the phenomenon being studied, and to uncover new insights and meanings.

Quantitative data is information about quantities, and therefore numbers, and qualitative data is descriptive, and regards phenomenon which can be observed but not measured, such as language.

What Is Qualitative Research?

Qualitative research is the process of collecting, analyzing, and interpreting non-numerical data, such as language. Qualitative research can be used to understand how an individual subjectively perceives and gives meaning to their social reality.

Qualitative data is non-numerical data, such as text, video, photographs, or audio recordings. This type of data can be collected using diary accounts or in-depth interviews and analyzed using grounded theory or thematic analysis.

Qualitative research is multimethod in focus, involving an interpretive, naturalistic approach to its subject matter. This means that qualitative researchers study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them. Denzin and Lincoln (1994, p. 2)

Interest in qualitative data came about as the result of the dissatisfaction of some psychologists (e.g., Carl Rogers) with the scientific study of psychologists such as behaviorists (e.g., Skinner ).

Since psychologists study people, the traditional approach to science is not seen as an appropriate way of carrying out research since it fails to capture the totality of human experience and the essence of being human.  Exploring participants’ experiences is known as a phenomenological approach (re: Humanism ).

Qualitative research is primarily concerned with meaning, subjectivity, and lived experience. The goal is to understand the quality and texture of people’s experiences, how they make sense of them, and the implications for their lives.

Qualitative research aims to understand the social reality of individuals, groups, and cultures as nearly as possible as participants feel or live it. Thus, people and groups are studied in their natural setting.

Some examples of qualitative research questions are provided, such as what an experience feels like, how people talk about something, how they make sense of an experience, and how events unfold for people.

Research following a qualitative approach is exploratory and seeks to explain ‘how’ and ‘why’ a particular phenomenon, or behavior, operates as it does in a particular context. It can be used to generate hypotheses and theories from the data.

Qualitative Methods

There are different types of qualitative research methods, including diary accounts, in-depth interviews , documents, focus groups , case study research , and ethnography.

The results of qualitative methods provide a deep understanding of how people perceive their social realities and in consequence, how they act within the social world.

The researcher has several methods for collecting empirical materials, ranging from the interview to direct observation, to the analysis of artifacts, documents, and cultural records, to the use of visual materials or personal experience. Denzin and Lincoln (1994, p. 14)

Here are some examples of qualitative data:

Interview transcripts : Verbatim records of what participants said during an interview or focus group. They allow researchers to identify common themes and patterns, and draw conclusions based on the data. Interview transcripts can also be useful in providing direct quotes and examples to support research findings.

Observations : The researcher typically takes detailed notes on what they observe, including any contextual information, nonverbal cues, or other relevant details. The resulting observational data can be analyzed to gain insights into social phenomena, such as human behavior, social interactions, and cultural practices.

Unstructured interviews : generate qualitative data through the use of open questions.  This allows the respondent to talk in some depth, choosing their own words.  This helps the researcher develop a real sense of a person’s understanding of a situation.

Diaries or journals : Written accounts of personal experiences or reflections.

Notice that qualitative data could be much more than just words or text. Photographs, videos, sound recordings, and so on, can be considered qualitative data. Visual data can be used to understand behaviors, environments, and social interactions.

Qualitative Data Analysis

Qualitative research is endlessly creative and interpretive. The researcher does not just leave the field with mountains of empirical data and then easily write up his or her findings.

Qualitative interpretations are constructed, and various techniques can be used to make sense of the data, such as content analysis, grounded theory (Glaser & Strauss, 1967), thematic analysis (Braun & Clarke, 2006), or discourse analysis.

For example, thematic analysis is a qualitative approach that involves identifying implicit or explicit ideas within the data. Themes will often emerge once the data has been coded .

Key Features

• Events can be understood adequately only if they are seen in context. Therefore, a qualitative researcher immerses her/himself in the field, in natural surroundings. The contexts of inquiry are not contrived; they are natural. Nothing is predefined or taken for granted.
• Qualitative researchers want those who are studied to speak for themselves, to provide their perspectives in words and other actions. Therefore, qualitative research is an interactive process in which the persons studied teach the researcher about their lives.
• The qualitative researcher is an integral part of the data; without the active participation of the researcher, no data exists.
• The study’s design evolves during the research and can be adjusted or changed as it progresses. For the qualitative researcher, there is no single reality. It is subjective and exists only in reference to the observer.
• The theory is data-driven and emerges as part of the research process, evolving from the data as they are collected.

Limitations of Qualitative Research

• Because of the time and costs involved, qualitative designs do not generally draw samples from large-scale data sets.
• The problem of adequate validity or reliability is a major criticism. Because of the subjective nature of qualitative data and its origin in single contexts, it is difficult to apply conventional standards of reliability and validity. For example, because of the central role played by the researcher in the generation of data, it is not possible to replicate qualitative studies.
• Also, contexts, situations, events, conditions, and interactions cannot be replicated to any extent, nor can generalizations be made to a wider context than the one studied with confidence.
• The time required for data collection, analysis, and interpretation is lengthy. Analysis of qualitative data is difficult, and expert knowledge of an area is necessary to interpret qualitative data. Great care must be taken when doing so, for example, looking for mental illness symptoms.

Advantages of Qualitative Research

• Because of close researcher involvement, the researcher gains an insider’s view of the field. This allows the researcher to find issues that are often missed (such as subtleties and complexities) by the scientific, more positivistic inquiries.
• Qualitative descriptions can be important in suggesting possible relationships, causes, effects, and dynamic processes.
• Qualitative analysis allows for ambiguities/contradictions in the data, which reflect social reality (Denscombe, 2010).
• Qualitative research uses a descriptive, narrative style; this research might be of particular benefit to the practitioner as she or he could turn to qualitative reports to examine forms of knowledge that might otherwise be unavailable, thereby gaining new insight.

What Is Quantitative Research?

Quantitative research involves the process of objectively collecting and analyzing numerical data to describe, predict, or control variables of interest.

The goals of quantitative research are to test causal relationships between variables , make predictions, and generalize results to wider populations.

Quantitative researchers aim to establish general laws of behavior and phenomenon across different settings/contexts. Research is used to test a theory and ultimately support or reject it.

Quantitative Methods

Experiments typically yield quantitative data, as they are concerned with measuring things.  However, other research methods, such as controlled observations and questionnaires , can produce both quantitative information.

For example, a rating scale or closed questions on a questionnaire would generate quantitative data as these produce either numerical data or data that can be put into categories (e.g., “yes,” “no” answers).

Experimental methods limit how research participants react to and express appropriate social behavior.

Findings are, therefore, likely to be context-bound and simply a reflection of the assumptions that the researcher brings to the investigation.

There are numerous examples of quantitative data in psychological research, including mental health. Here are a few examples:

Another example is the Experience in Close Relationships Scale (ECR), a self-report questionnaire widely used to assess adult attachment styles .

The ECR provides quantitative data that can be used to assess attachment styles and predict relationship outcomes.

Neuroimaging data : Neuroimaging techniques, such as MRI and fMRI, provide quantitative data on brain structure and function.

This data can be analyzed to identify brain regions involved in specific mental processes or disorders.

For example, the Beck Depression Inventory (BDI) is a clinician-administered questionnaire widely used to assess the severity of depressive symptoms in individuals.

The BDI consists of 21 questions, each scored on a scale of 0 to 3, with higher scores indicating more severe depressive symptoms. 

Quantitative Data Analysis

Statistics help us turn quantitative data into useful information to help with decision-making. We can use statistics to summarize our data, describing patterns, relationships, and connections. Statistics can be descriptive or inferential.

Descriptive statistics help us to summarize our data. In contrast, inferential statistics are used to identify statistically significant differences between groups of data (such as intervention and control groups in a randomized control study).

• Quantitative researchers try to control extraneous variables by conducting their studies in the lab.
• The research aims for objectivity (i.e., without bias) and is separated from the data.
• The design of the study is determined before it begins.
• For the quantitative researcher, the reality is objective, exists separately from the researcher, and can be seen by anyone.
• Research is used to test a theory and ultimately support or reject it.

Limitations of Quantitative Research

• Context: Quantitative experiments do not take place in natural settings. In addition, they do not allow participants to explain their choices or the meaning of the questions they may have for those participants (Carr, 1994).
• Researcher expertise: Poor knowledge of the application of statistical analysis may negatively affect analysis and subsequent interpretation (Black, 1999).
• Variability of data quantity: Large sample sizes are needed for more accurate analysis. Small-scale quantitative studies may be less reliable because of the low quantity of data (Denscombe, 2010). This also affects the ability to generalize study findings to wider populations.
• Confirmation bias: The researcher might miss observing phenomena because of focus on theory or hypothesis testing rather than on the theory of hypothesis generation.

Advantages of Quantitative Research

• Scientific objectivity: Quantitative data can be interpreted with statistical analysis, and since statistics are based on the principles of mathematics, the quantitative approach is viewed as scientifically objective and rational (Carr, 1994; Denscombe, 2010).
• Useful for testing and validating already constructed theories.
• Rapid analysis: Sophisticated software removes much of the need for prolonged data analysis, especially with large volumes of data involved (Antonius, 2003).
• Replication: Quantitative data is based on measured values and can be checked by others because numerical data is less open to ambiguities of interpretation.
• Hypotheses can also be tested because of statistical analysis (Antonius, 2003).

Antonius, R. (2003). Interpreting quantitative data with SPSS . Sage.

Black, T. R. (1999). Doing quantitative research in the social sciences: An integrated approach to research design, measurement and statistics . Sage.

Braun, V. & Clarke, V. (2006). Using thematic analysis in psychology . Qualitative Research in Psychology , 3, 77–101.

Carr, L. T. (1994). The strengths and weaknesses of quantitative and qualitative research : what method for nursing? Journal of advanced nursing, 20(4) , 716-721.

Denscombe, M. (2010). The Good Research Guide: for small-scale social research. McGraw Hill.

Denzin, N., & Lincoln. Y. (1994). Handbook of Qualitative Research. Thousand Oaks, CA, US: Sage Publications Inc.

Glaser, B. G., Strauss, A. L., & Strutzel, E. (1968). The discovery of grounded theory; strategies for qualitative research. Nursing research, 17(4) , 364.

Minichiello, V. (1990). In-Depth Interviewing: Researching People. Longman Cheshire.

Punch, K. (1998). Introduction to Social Research: Quantitative and Qualitative Approaches. London: Sage

Further Information

• Designing qualitative research
• Methods of data collection and analysis
• Introduction to quantitative and qualitative research
• Checklists for improving rigour in qualitative research: a case of the tail wagging the dog?
• Qualitative research in health care: Analysing qualitative data
• Qualitative data analysis: the framework approach
• Using the framework method for the analysis of
• Qualitative data in multi-disciplinary health research
• Content Analysis
• Grounded Theory
• Thematic Analysis

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Qualitative Research: Definition, Methodology, Limitation, Examples

Qualitative research is a method focused on understanding human behavior and experiences through non-numerical data. Examples of qualitative research include:

• One-on-one interviews,
• Focus groups, Ethnographic research,
• Case studies,
• Record keeping,
• Qualitative observations

In this article, we’ll provide tips and tricks on how to use qualitative research to better understand your audience through real world examples and improve your ROI. We’ll also learn the difference between qualitative and quantitative data.

Table of Contents

Marketers often seek to understand their customers deeply. Qualitative research methods such as face-to-face interviews, focus groups, and qualitative observations can provide valuable insights into your products, your market, and your customers’ opinions and motivations. Understanding these nuances can significantly enhance marketing strategies and overall customer satisfaction.

What is Qualitative Research

Qualitative research is a market research method that focuses on obtaining data through open-ended and conversational communication. This method focuses on the “why” rather than the “what” people think about you. Thus, qualitative research seeks to uncover the underlying motivations, attitudes, and beliefs that drive people’s actions. 

Let’s say you have an online shop catering to a general audience. You do a demographic analysis and you find out that most of your customers are male. Naturally, you will want to find out why women are not buying from you. And that’s what qualitative research will help you find out.

In the case of your online shop, qualitative research would involve reaching out to female non-customers through methods such as in-depth interviews or focus groups. These interactions provide a platform for women to express their thoughts, feelings, and concerns regarding your products or brand. Through qualitative analysis, you can uncover valuable insights into factors such as product preferences, user experience, brand perception, and barriers to purchase.

Types of Qualitative Research Methods

1. one-on-one interviews.

• A company might conduct interviews to understand why a product failed to meet sales expectations.
• A researcher might use interviews to gather personal stories about experiences with healthcare.

2. Focus groups

• A focus group could be used to test reactions to a new product concept.
• Marketers might use focus groups to see how different demographic groups react to an advertising campaign.

3. Ethnographic research

• A study of workplace culture within a tech startup.
• Observational research in a remote village to understand local traditions.

4. Case study research

• Analyzing a single school’s innovative teaching method.
• A detailed study of a patient’s medical treatment over several years.

H3: 5. Record keeping

• Historical research using old newspapers and letters.
• A study on policy changes over the years by examining government records.

6. Qualitative observation

• Sight : Observing the way customers visually interact with product displays in a store to understand their browsing behaviors and preferences.
• Smell : Noting reactions of consumers to different scents in a fragrance shop to study the impact of olfactory elements on product preference.
• Touch : Watching how individuals interact with different materials in a clothing store to assess the importance of texture in fabric selection.
• Taste : Evaluating reactions of participants in a taste test to identify flavor profiles that appeal to different demographic groups.
• Hearing : Documenting responses to changes in background music within a retail environment to determine its effect on shopping behavior and mood.

Qualitative Research Real World Examples

1. online grocery shop with a predominantly male audience, 2. software company launching a new product, 3. alan pushkin’s “god’s choice: the total world of a fundamentalist christian school”, 4. understanding buyers’ trends, 5. determining products/services missing from the market, real-time customer lifetime value (clv) benchmark report.

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Qualitative Research Approaches

• Narrative : This method focuses on individual life stories to understand personal experiences and journeys. It examines how people structure their stories and the themes within them to explore human existence. For example, a narrative study might look at cancer survivors to understand their resilience and coping strategies.
• Phenomenology : attempts to understand or explain life experiences or phenomena; It aims to reveal the depth of human consciousness and perception, such as by studying the daily lives of those with chronic illnesses.
• Grounded theory : investigates the process, action, or interaction with the goal of developing a theory “grounded” in observations and empirical data. 
• Ethnography : describes and interprets an ethnic, cultural, or social group;
• Case study : examines episodic events in a definable framework, develops in-depth analyses of single or multiple cases, and generally explains “how”. An example might be studying a community health program to evaluate its success and impact.

How to Analyze Qualitative Data

1. data collection, 2. data preparation, 3. familiarization.

• Descriptive Coding : Summarize the primary topic of the data.
• In Vivo Coding : Use language and terms used by the participants themselves.
• Process Coding : Use gerunds (“-ing” words) to label the processes at play.
• Emotion Coding : Identify and record the emotions conveyed or experienced.

5. Thematic Development

6. interpreting the data, 7. validation, 8. reporting, limitations of qualitative research, 1. it’s a time-consuming process, 2. you can’t verify the results of qualitative research, 3. it’s a labor-intensive approach, 4. it’s difficult to investigate causality, 5. qualitative research is not statistically representative, quantitative vs. qualitative research.

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Nature of Data:

• Quantitative research : Involves numerical data that can be measured and analyzed statistically.
• Qualitative research : Focuses on non-numerical data, such as words, images, and observations, to capture subjective experiences and meanings.

Research Questions:

• Quantitative research : Typically addresses questions related to “how many,” “how much,” or “to what extent,” aiming to quantify relationships and patterns.
• Qualitative research: Explores questions related to “why” and “how,” aiming to understand the underlying motivations, beliefs, and perceptions of individuals.

Data Collection Methods:

• Quantitative research : Relies on structured surveys, experiments, or observations with predefined variables and measures.
• Qualitative research : Utilizes open-ended interviews, focus groups, participant observations, and textual analysis to gather rich, contextually nuanced data.

Analysis Techniques:

• Quantitative research: Involves statistical analysis to identify correlations, associations, or differences between variables.
• Qualitative research: Employs thematic analysis, coding, and interpretation to uncover patterns, themes, and insights within qualitative data.

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14 Quantitative analysis: Descriptive statistics

Numeric data collected in a research project can be analysed quantitatively using statistical tools in two different ways. Descriptive analysis refers to statistically describing, aggregating, and presenting the constructs of interest or associations between these constructs. Inferential analysis refers to the statistical testing of hypotheses (theory testing). In this chapter, we will examine statistical techniques used for descriptive analysis, and the next chapter will examine statistical techniques for inferential analysis. Much of today’s quantitative data analysis is conducted using software programs such as SPSS or SAS. Readers are advised to familiarise themselves with one of these programs for understanding the concepts described in this chapter.

Data preparation

In research projects, data may be collected from a variety of sources: postal surveys, interviews, pretest or posttest experimental data, observational data, and so forth. This data must be converted into a machine-readable, numeric format, such as in a spreadsheet or a text file, so that they can be analysed by computer programs like SPSS or SAS. Data preparation usually follows the following steps:

Data coding. Coding is the process of converting data into numeric format. A codebook should be created to guide the coding process. A codebook is a comprehensive document containing a detailed description of each variable in a research study, items or measures for that variable, the format of each item (numeric, text, etc.), the response scale for each item (i.e., whether it is measured on a nominal, ordinal, interval, or ratio scale, and whether this scale is a five-point, seven-point scale, etc.), and how to code each value into a numeric format. For instance, if we have a measurement item on a seven-point Likert scale with anchors ranging from ‘strongly disagree’ to ‘strongly agree’, we may code that item as 1 for strongly disagree, 4 for neutral, and 7 for strongly agree, with the intermediate anchors in between. Nominal data such as industry type can be coded in numeric form using a coding scheme such as: 1 for manufacturing, 2 for retailing, 3 for financial, 4 for healthcare, and so forth (of course, nominal data cannot be analysed statistically). Ratio scale data such as age, income, or test scores can be coded as entered by the respondent. Sometimes, data may need to be aggregated into a different form than the format used for data collection. For instance, if a survey measuring a construct such as ‘benefits of computers’ provided respondents with a checklist of benefits that they could select from, and respondents were encouraged to choose as many of those benefits as they wanted, then the total number of checked items could be used as an aggregate measure of benefits. Note that many other forms of data—such as interview transcripts—cannot be converted into a numeric format for statistical analysis. Codebooks are especially important for large complex studies involving many variables and measurement items, where the coding process is conducted by different people, to help the coding team code data in a consistent manner, and also to help others understand and interpret the coded data.

Data entry. Coded data can be entered into a spreadsheet, database, text file, or directly into a statistical program like SPSS. Most statistical programs provide a data editor for entering data. However, these programs store data in their own native format—e.g., SPSS stores data as .sav files—which makes it difficult to share that data with other statistical programs. Hence, it is often better to enter data into a spreadsheet or database where it can be reorganised as needed, shared across programs, and subsets of data can be extracted for analysis. Smaller data sets with less than 65,000 observations and 256 items can be stored in a spreadsheet created using a program such as Microsoft Excel, while larger datasets with millions of observations will require a database. Each observation can be entered as one row in the spreadsheet, and each measurement item can be represented as one column. Data should be checked for accuracy during and after entry via occasional spot checks on a set of items or observations. Furthermore, while entering data, the coder should watch out for obvious evidence of bad data, such as the respondent selecting the ‘strongly agree’ response to all items irrespective of content, including reverse-coded items. If so, such data can be entered but should be excluded from subsequent analysis.

Data transformation. Sometimes, it is necessary to transform data values before they can be meaningfully interpreted. For instance, reverse coded items—where items convey the opposite meaning of that of their underlying construct—should be reversed (e.g., in a 1-7 interval scale, 8 minus the observed value will reverse the value) before they can be compared or combined with items that are not reverse coded. Other kinds of transformations may include creating scale measures by adding individual scale items, creating a weighted index from a set of observed measures, and collapsing multiple values into fewer categories (e.g., collapsing incomes into income ranges).

Univariate analysis

Univariate analysis—or analysis of a single variable—refers to a set of statistical techniques that can describe the general properties of one variable. Univariate statistics include: frequency distribution, central tendency, and dispersion. The frequency distribution of a variable is a summary of the frequency—or percentages—of individual values or ranges of values for that variable. For instance, we can measure how many times a sample of respondents attend religious services—as a gauge of their ‘religiosity’—using a categorical scale: never, once per year, several times per year, about once a month, several times per month, several times per week, and an optional category for ‘did not answer’. If we count the number or percentage of observations within each category—except ‘did not answer’ which is really a missing value rather than a category—and display it in the form of a table, as shown in Figure 14.1, what we have is a frequency distribution. This distribution can also be depicted in the form of a bar chart, as shown on the right panel of Figure 14.1, with the horizontal axis representing each category of that variable and the vertical axis representing the frequency or percentage of observations within each category.

With very large samples, where observations are independent and random, the frequency distribution tends to follow a plot that looks like a bell-shaped curve—a smoothed bar chart of the frequency distribution—similar to that shown in Figure 14.2. Here most observations are clustered toward the centre of the range of values, with fewer and fewer observations clustered toward the extreme ends of the range. Such a curve is called a normal distribution .

Lastly, the mode is the most frequently occurring value in a distribution of values. In the previous example, the most frequently occurring value is 15, which is the mode of the above set of test scores. Note that any value that is estimated from a sample, such as mean, median, mode, or any of the later estimates are called a statistic .

Bivariate analysis

Bivariate analysis examines how two variables are related to one another. The most common bivariate statistic is the bivariate correlation —often, simply called ‘correlation’—which is a number between -1 and +1 denoting the strength of the relationship between two variables. Say that we wish to study how age is related to self-esteem in a sample of 20 respondents—i.e., as age increases, does self-esteem increase, decrease, or remain unchanged?. If self-esteem increases, then we have a positive correlation between the two variables, if self-esteem decreases, then we have a negative correlation, and if it remains the same, we have a zero correlation. To calculate the value of this correlation, consider the hypothetical dataset shown in Table 14.1.

After computing bivariate correlation, researchers are often interested in knowing whether the correlation is significant (i.e., a real one) or caused by mere chance. Answering such a question would require testing the following hypothesis:

Social Science Research: Principles, Methods and Practices (Revised edition) Copyright © 2019 by Anol Bhattacherjee is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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• Published: 16 May 2024

Moving between positions: a qualitative study of mentoring relationships in chronic eating disorders

• Roni Elran-Barak 1 &
• Shiran Elmalah-Alon 1  

Journal of Eating Disorders volume  12 , Article number:  59 ( 2024 ) Cite this article

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Metrics details

Eating disorders (ED) are chronic and challenging-to-treat conditions, often persisting over extended periods. Some patients with EDs require prolonged intensive rehabilitation services, which may include weekly home visits by paraprofessional mentors serving as support persons, providing guidelines, emotional care, and assistance. This study aims to enhance our understanding of the nature of the relationship formed between mentors and patients with EDs.

Design & Methods

Fifteen in-depth qualitative interviews were conducted with patients and paraprofessional mentors. Interviews were analyzed using a descriptive phenomenological approach by two researchers to enhance reliability.

Qualitative analysis highlighted that mentors play a crucial role in patients’ rehabilitation. Mentors adapt two positions (investigative and embracing) to address the encountered difficulties, including conflicts, tension, and confusion associated with (in)equality and reciprocity in the mentoring relationship.

Practice Implications

Paraprofessional mentors can assist people with ED in their rehabilitation process. To support patients with EDs effectively, it is crucial to train and supervise the mentors in navigating between roles and dealing with boundaries, secrets, lies, and exposure to various aspects of the rehabilitation process. Additionally, we recommend further research using quantitative and empirical tools to complement the qualitative findings presented.

Impact and implications

Paraprofessional mentors can make a crucial contribution to the rehabilitation of patients with eating disorders.

Eating disorder mentors have a complex task in learning how to move between the embracing and the investigative position.

The mentor’s physical entry into the patient’s home is critically significant, as it enables an encounter typified by less concealment.

It is important to make such mentoring services available to more patients with eating disorders.

It is advised to develop a special training program for mentors, so that they can acquire knowledge and learn about the specific dynamics that are common among patients with eating disorders.

Plain English summary

Eating disorders (ED) can be challenging to treat, often requiring long-term intensive support. Paraprofessional mentors are support persons who make weekly home visits to help patients in the rehabilitation process.

The study aims to understand the relationship between mentors and patients with ED. Researchers interviewed 15 patients and mentors. They discovered that mentors play a key role in helping patients get better by taking on two important roles. First, mentors act like investigators, trying to understand the challenges and problems that patients face. Second, mentors act as supporters, offering comfort and assistance during difficult times.

The study emphasizes the importance of including mentorship in ED treatment and rehabilitation. It also suggests that training and supervision for paraprofessional mentors are crucial to help them handle their roles effectively, especially when dealing with boundaries and complex situations.

Introduction

Eating disorders (ED) are a group of complex and life-threatening psychiatric disorders manifested in disturbed body image and maladaptive eating patterns. They include, among other things, extreme diets, fasting, binge eating, the use of laxatives, and induced vomiting [ 10 , 25 ]. The most common EDs are anorexia nervosa, bulimia nervosa, and binge EDs, all of which can have a lengthy and chronic course that has a profound influence on patients’ health and well-being [ 15 , 21 ]. In the most severe EDs there is – in addition to pathological eating patterns and disturbed body image – reduced psychosocial functioning, which may include difficulties in obtaining an education, preserving employment, and maintaining a social life [ 28 ]. Multidisciplinary rehabilitation that includes medical, nutritional, emotional, and familial care is essential in order to address the various aspects of the EDs [ 4 , 19 ]. In-home paraprofessional mentoring care is provided to some patients with severe EDs, but studies focusing on this type of care are scarce.

In-home mentoring takes place in the natural environment of the patient and, as such, is characterized by direct non-hierarchal personal contact and collaborative work [ 3 , 8 , 13 , 22 , 23 , 24 ]. Originally designed for individuals with severe mental illness who struggle to navigate life independently within the community [ 9 ], home-based mentoring offers personal support and guidance across various aspects of life, such as employment, education and social interactions. In the context of EDs, mentors hold multifaceted responsibilities. Not only do they address and support patients in establishing healthy and regular eating habits, but they also extend their focus to other essential life domains. Many patients with EDs who participate in a mentoring program also participate in regular psychotherapy sessions, and some additionally consult with a dietician. The mentoring serves as an additional treatment modality, aiding patients in managing their day-to-day tasks, thereby enhancing the overall recovery and rehabilitation process.

There are very few studies whose focus is on mentoring in EDs [ 3 , 8 , 13 , 22 , 23 , 24 ]. In some, the focus has been on peer mentoring (i.e., by a peer with an ED), and in some, including the current study, the focus has been on mentoring by a non-professional (e.g., psychology students who are still not licensed to work as mental health providers). A systematic review [ 8 ] exploring the benefits, effects, and experiences of mentoring on those with EDs suggests that mentoring has great value for both mentors and mentees. The results of a qualitative study [ 13 ] focusing on mentoring among mentees undergoing intensive ED medical treatment, followed by participation in a mentoring program, revealed several benefits for mentees. These advantages included feelings of hope, reconnection with others, and increased engagement with the world. The majority of mentees emphasized the exceptional and irreplaceable support provided by their mentors. Ending the mentoring relationship at the conclusion of the program emerged as a significant challenge, with mentors citing boundary management as a primary obstacle.

Research on mentoring indicates that many fundamental challenges present in therapeutic relationships, such as building trust, fostering a sense of security, demonstrating non-judgmental attitudes, empathy, and understanding, are also relevant within mentoring relationships [ 3 , 13 ]. In the context of EDs, distinctive challenges emerge, notably when attempting to address ED behaviors such as increasing caloric intake, which patients often perceive as disrupting their perceived “perfect solution” [ 30 ]. In fact, any intervention challenging the patient’s eating habits can trigger opposition, refusal to cooperate, and even false reports of eating behaviors [ 31 ]. The aim of this study was therefore to expand the body of literature addressing the unique bond formed between mentors and patients with EDs by investigating both mentors’ and patients’ personal subjective experience within this mentoring relationship.

Sample and procedure

The sample included 15 Israeli women, comprising ten patients and five paraprofessional mentors (as described in Tables  1 and 2 ). Sampling was stopped when data reached saturation [ 14 ], that is when no new information or insights are obtained from the data collected. This occurs when the researcher repeatedly encounters the same themes, concepts, or patterns in the data, and further data collection is unlikely to provide additional understanding or perspectives. The mentoring program was structured as the second phase of a rehabilitation program tailored for individuals with EDs who have finished an intensive rehabilitation program [ 16 ] and transitioned to independent living. The mentees had weekly sessions with a psychotherapist and a dietician in addition to the mentoring sessions. The mentors were supervised by the psychotherapist and/or the dietician. The aims of the mentoring program were negotiated and agreed upon between the patient, the mentor, the psychotherapist, and the dietician. The paraprofessional mentors were mostly students (Table  2 ). They were recruited for the mentoring position through a job positing published by the rehabilitation organization. This organization was also responsible for mentor supervision. Mentors mostly viewed this position as a part-time job allowing them to gain therapeutic skills while completing their formal mental-health education.

The research was approved by the authors’ university ethics committee (#2066). Participants were recruited to the study through an organization that provides rehabilitation services. The second author reached out to the organization’s director to request the names of potential mentors and mentees. Subsequently, the author contacted these individuals to explain the study procedure. To ensure free and independent participation, the program director was not informed about the participants’ decisions to participate or decline involvement in the study. Participants were not compensated by the research team for the interview time. All participants signed an informed consent prior to the interviews.

The qualitative interview

The qualitative interviews were conducted in Hebrew, face-to-face (at patients’ homes or a coffee shop), in 2019 by the second author, and each lasted about 90 min. In accordance with the phenomenological method, a semi-structured interview was conducted, which focuses on questions that describe participants’ experience and their cognitive perceptions regarding the subject of the study [ 5 ]. The interview began with the following statement: “Please describe your experience in the mentoring relationship.” Next, participants were asked specific questions regarding different aspects, including the nature of the mentoring relationship and the role of the mentor in the rehabilitation process. The complete interview guidelines have been attached as a supplement, but the interviewer (second author) had the flexibility to navigate between questions to facilitate a natural flow in the conversation.

The qualitative analysis

We analyzed the interviews using a descriptive phenomenological approach [ 7 , 18 ]. Todres’ [ 26 ] concept of phenomenological qualitative analysis was used to reveal the essential general structure or structures of meaning within the shared experiences of the research participants. This process is conducted via bracketing: attempting to reduce the influence of researchers’ prior knowledge on the analysis [ 27 ]. To address biases, and to enhance reliability, the transcripts of the interviews were analyzed independently by the two coauthors [ 1 ]. Throughout the analysis, we systematically set aside our preconceived notions, beliefs, and presumptions regarding the subject matter. This process allowed us to engage with the data openly without imposing our prior knowledge. Following individual analyses, a collaborative discussion was conducted. We aimed to ensure that the outcomes truly reflected the shared experiences of all participants, thus enhancing the credibility and trustworthiness of our study. This joint discussion was held to integrate the results and to choose the quotations that best represented the shared experience of all participants. Another independent reader also read our analyses and approved them.

The four themes presented below describe how the mentor’s physical entry into the patient’s home is perceived as having critical significance in the rehabilitation and recovery process. We describe the mentoring relationship as a unique opportunity for advancing the rehabilitative process (first and second themes), while highlighting the challenges associated with the mentor’s presence in the patient’s home (third and fourth themes). All four themes demonstrate the two positions that the mentors adopt: The investigative and the embracing positions. These positions emerged as key findings, identified through our analysis of the interviews, and were labeled as a result of our thorough examination of the data.

1. First theme: home-based care as an opportunity for a dialogue about “what’s on the table”

Interviewees emphasized that the mentor’s presence in the patient’s home allowed the exposure of eating habits and symptoms they had been hiding for a long time (“what’s on the table”). Sometimes, the straightforward act in which the mentor opens the patient’s refrigerator can be perceived as a moment of intimacy and a breakthrough during which the mentor can gain information about the patient’s eating regimen.

Naomi (mentor)

We enter their home, in the full sense of the word, their life, their home. Unlike for example the dietitians, where it’s the patients who come to the dietitians and tell them at the clinic how it went this week […], you [the mentor] can open her [the patient’s] fridge to see if there are diet products inside.

In the following citation, the mentee and mentor cook together. The quate demonstrates how the mentor moves between the investigative and the embracing positions and suggests that this transition can be quick. The patient, in this case, devotes herself to the act of learning and she is willing to give up previous habits, even if doing so is difficult and threatening.

Shahar (patient)

I took the egg out of the fridge and when I had to put it in the mixing bowl, a little spilled out. She [the mentor] asked me if [spilling] was intentional or unintentional and to be honest I didn’t know the answer … So she told me to “pay attention” […] and then I came to get the oil and she told me I needed a tablespoon of it. For an omelet! That’s crazy… and I wouldn’t agree to it […] She really kind of taught me that the oil should cover the whole bottom of the pan … after that I wanted to pat the omelet with absorbent paper … because it was really shiny and greasy-looking. I asked her if I could, even though I knew she wouldn’t let me, but I tried my luck.

In the following description Maayan describes a joint cooking experience with her mentor. There is a feeling, in the quote, of a mother and daughter cooking together. Maayan appreciates the mentor’s knowledge but even more than that, she appreciates the specialness and uniqueness of this joint cooking experience.

Maayan (patient)

Practically, I actually also learned to cook with the help of the mentor. I still keep a recipe book I made with one of the mentors …. and it was really like the two of us were thinking together about what I felt like eating, finding a recipe and experimenting with it, so it was, like, a very meaningful experience for me.

The following quote demonstrates how the mentor’s containing and caring presence (embracing position) allows Liat to confront her “pasta issue.” With the mentor’s help, Liat can allow herself to experience the difficulty and loss of control, but can also collect herself and confront the anxiety that arises in her when she eats pasta.

Liat (patient)

I had anxiety about pasta for years. It’s something I would never eat… and every time we [the mentor and I] wanted to make pasta, it ended up being put off […] So we went out one evening to eat pasta … we planned it. And it was insanely hard, I had a panic attack. I said to her, “I’m getting on a bus, I’m going home…, this is all too much for me,” and she really managed to get my panic attack under control, but I couldn’t eat the pasta. Then, we realized we might have jumped the gun: going out to eat pasta in a restaurant. When we made the pasta at home, […] and I knew what was in it, and I made it, it was a little bit easier. A month later we finally did go out to eat, in a restaurant, and I was more able to deal with it ….

The following quote demonstrates how the investigative position can help identify problematic areas that need to be addressed.

Romi (mentor)

The mentor comes inside the girl’s house, assesses the situation, notices the little details. For example, I suddenly noticed with one of my patients that she had a beer mug on the counter. I asked her about it and she gave me some vague answer. After a while she told me about some beer she drank […] Because I went in, and because I know what’s going on with her, I was actually able to see and stop the drinking routine before it evolved into something bigger.

Maya, for her part, uses the term “spotlight” to describe the role of the mentor. That is, the mentor’s intervention is experienced as a kind of strong beam of light that shines in a certain direction: the direction of recovery. The mentor illuminates the path of recovery, mentions the challenges Maya needs to overcome, and presents matters in a healthy language, a language of recovery.

Maya (patient)

She [the mentor]is in my life to put a spotlight specifically on my ED. It’s very easy to forget this spotlight sometimes […] she [the mentor] is there to remind me that the thoughts that drive people [with an ED] are not the same thoughts that drive people without an ED.

In conclusion, this theme demonstrates how the mentor’s presence in the patient’s home enables the breaking of concealment habits and promotes rehabilitative work aimed to extinguish behaviors resulting directly from the ED. Rehabilitation is made possible through the mentor’s moving back and forth between an embracing position and an “investigative” position that heeds details, casts doubt, and asks difficult questions.

2. Second theme: home-based care as an opportunity to work on “beside the table” issues

In contrast to the first theme, which revolved around aspects related directly to eating (“on the table”), in the second theme we see how the mentor’s presence in the house allows the mentor to witness the ED’s effect on areas of life that are not directly related to food (“beside the table”). For instance, in the next quotation, the experience of shopping with the mentor is described as an example of intimacy.

Inbal (patient)

The mentor is in my life at the most personal level. She comes inside the house, she sees how I really live. Ummm, I know . I think she knows my life best. And she sees me in a variety of situations… situations in which others don’t see me. I can tell the dietitian certain things about myself, but she doesn’t experience what it’s like to actually go buy bras with me or go shopping with me and see what I have trouble with.

In addition to shopping, another “beside the table issue” is basic hygiene. In the next quote, the mentor’s flexibility, and the transition she makes between being an authority figure and being a partner, seem to create an opening for the formation of an intimate bond.

Agam (mentor)

Some houses were tough to enter, like one in which there were severe hygiene issues. It was challenging; I’d feel the need to clean up after our sessions, take a shower, and launder my clothes. There was garbage strewn around, which puzzled me. Our mentoring goals included establishing a hygiene routine; she struggled to shower regularly. We set rules, like ensuring that she showered before our meetings. We had intimate conversations; hygiene touches personal spaces deeply. We discussed menstruation and hygiene neglect. I guided her, even showing her how to wash her legs thoroughly. These were unique situations I’d never experienced.

In the following quote we can see the mentor’s position as an investigator who reveals hidden information that no one had previously been aware of: The mentor identifies suicidal actions that would not have been identified in any other therapeutic situation. The role of the patient is to plant clues, and the role of the mentor is to reveal that which is hidden by paying attention to details.

I once found a rope on her desk, and it turned out that she slept with it tied around her neck at night. This is something that would be missed in conversation with the dietitian if she [the patient] chose not to share it. And it’s not that she shared it with me. I just saw it because I was there.

Liat’s next quote expands on the mentor’s role as an investigator. The patient won’t reveal her secrets if no one asks questions; however, when the mentor asks the right questions, the patient will stop hiding. She’ll answer the mentor’s questions, even if they are difficult.

One time when she [the mentor] came to my house, she saw that I was taking a shower in the dark. […] she just happened to notice. No one else noticed. My roommate didn’t notice; in the rehabilitation house they didn’t notice. I had always showered in the dark; this was not something new… she [the mentor] had a conversation with me about it, [I was surprised that] it didn’t seem to be something strange or unheard of to her. And we started working on it […] I had to start showering with the light on, and she [the mentor] would sit outside […] I think that when she gave me [permission to be myself]… without judgment and without criticism, I allowed myself to reveal the darkest, strangest, most illogical things associated with my ED.

In the following two quotes, both the mentor and the patient agree that very little escapes the mentor’s eyes; she notices all sorts of behaviors. Liat uses the term “eyes in the back” to describe the situation in which the mentor is vigilant and observing all patients’ behaviors. Naomi provides a specific example - excessive shopping that the patient conceals from her psychotherapist but not from her mentor, as the mentor can see the new items when she visits the mentee.

You feel that you are seen; you feel that no matter what you do, the mentor will take notice […] There should be someone there who has eyes in the back of her head. Someone who knows how to read situations, who is very alert, who knows by the tone of your voice on the phone what is happening.

The mentor can show her [the patient] things she does not see herself […] For example, let’s say someone had a bad day and [to make herself feel better] she went shopping and spent a thousand shekels […] Now, the patient won’t bring this subject up in any conversation because it’s not related to food; it’s not something she’s going to report. And there’s no social worker looking at her expenses. So it’s the mentor who has to put it together and talk about it with the patient.

Nofar summarizes the mentoring experience and claims that without the mentor’s support, she could not have had a successful rehabilitation.

Nofar (patient)

There’s no chance I could have succeeded in the outside world without someone watching out for me, guarding me, setting boundaries for me. I really needed them to do these things for me […] There’s no chance I would have been able to do all these things alone. No chance.

In conclusion, the quotes illustrate the theme of “seeing,” according to which the mentor observes the patient closely, and the patient perceives the gaze as benevolent, one that helps promote recovery. In this sense it can be said that the mentor-patient relationship is a kind of dance between the two: the mentor can be both an investigator and a benevolent mother, and the patient allows the mentor to understand “what is happening.” Together they work toward rehabilitation in all life areas.

3. Third theme: confrontations, secrets, and lies

In the third theme, cases are depicted in which the patient feels anger toward the mentor. The mentor requires the patient to undergo a rehabilitative process and give up her ED behaviors, but the patient, in some cases, feels that she is not yet able to make these changes. In the following quote, the difficulty of bringing a mentor into the home, opening up, and devoting oneself to the rehabilitative process is described. This difficulty can later cause the patient to engage in secrets and lies.

Adi (patient)

At first, I thought I might not want the experience of having a mentor, and maybe I wouldn’t need one. Like, it’s a little hard to accept the idea that you’re going to have a mentor twice a week, and I thought that maybe I could manage on my own.

Unsurprisingly, patients often have ambivalent feelings toward the in-home mentor. Alongside moments when they want the mentor’s assistance, there are moments when they would prefer to be left alone. The mentor’s examining gaze can be perceived as threatening, and at times patients find it difficult to go along with the expectation of change and rehabilitation.

There are times when it’s difficult for them [the patients] – particularly at times when they don’t want me to see their symptoms, they don’t want my help, they prefer to be “inside” their ED, alone. There are times when they come to me and say, “I don’t have an ED, so why are you watching me?” On the other hand, there are the times they say, “Wait a minute, you’re here to help me and I need this help and I do want you to watch and eat with me and tell me if I’m eating poorly.”

The ED can be so ingrained, and so strong, that patients will try to preserve certain behaviors, even if doing so means lying, keeping secrets, and concealing things from the mentor.

A patient will end up lying about the amount she’s really supposed to eat. Or let’s say she’s supposed to have a chocolate drink or a cup of coffee in addition to a snack, and she’ll say, “No, it’s only in the morning” or “It’s only at ten” or “I’ve already drunk or already eaten,” and all sorts of such things. Or there are girls who will say, “I’ll do it later” or “I’ll do it tomorrow,” and you just know they won’t […] You’ll either close your eyes to it and [ignore it] and say, “Okay, I believe she’ll do it tomorrow” or you’ll [confront her] but say it in a tone of: “I want to help you, to be with you, let’s do it together, let’s make it easy on you.”

When the mentor enters the patient’s home, the patient’s ability to hide is at least partially taken away from her, making her feel she has no choice but to find other ways to hide the things she is afraid to reveal. The following quote shows the patient’s insight into her behaviors:

There are many things that are hidden from sight, that are very difficult to see if you do not bring them up … Let’s put it this way: I wouldn’t want to be a mentor to someone with an ED … it’s … it’s hard, it’s hard. You have to be very sharp to see that … not everything is fine […] I think you have to keep your eyes wide open because we are manipulative and liars… […] We know how to make people believe every word that comes out of our mouths and turn everything around in a way [.] that’s safe for us. But this is not necessarily good for us. I think you [the mentor] must absolutely be skeptical of everything we tell you.

The next quote describes how despite the confrontations, anger, and lies, the mentoring relationship can eventually be used to promote rehabilitation.

There’s no way even to cheat a little bit, or to fool the mentor. Yesterday at dinner I made myself a toasted cheese sandwich and she [the mentor] said, before I had even put the sandwich in the sandwich maker, “Remember, do not squash it down too much. Just put the top down and close it; so the cheese doesn’t come out of the toast” [.] So when she said to me, “Remember not to do it,” I immediately said, “I didn’t even want to do that! Why are you putting ideas in my head??” Like I got mad at her… but that wasn’t right of me to get mad at her, because actually I probably did plan to do what she said, and that’s why I got annoyed that she said it […] mentoring is intense, and it’s just the two of you and the mentor gets to know your “tricks” very quickly.

In conclusion, the above quotes highlight the inevitable conflicts that arise in the mentoring relationship. It seems clear that this relationship has to withstand complex challenges of lies and concealment, and that the ability of the mentor and mentee to overcome these challenges is critical in the recovery process.

4. Fourth theme: home-based care as an acknowledgment of inequality - similar but different

Sometimes patients try to see the mentor as a friend or older sister, thus blurring the hierarchy that exists between them. In the following quote we can see Jasmine’s difficulty in accepting the built-in inequality of the mentor-patient relationship.

Jasmine (patient)

A lot of my difficulties with Shirley [the mentor] stemmed from the fact that it was an unequal relationship. I wanted to know more about her ]…[ It was hard for me because I felt like, because of the situation we were in, she couldn’t see that I too had abilities. And also there were moments when I didn’t want to express any particular weaknesses because I wanted to be with her in some equal place. Because there’s something really weird about it. It’s true that she’s not my age, she’s older than me by a few years, but it doesn’t matter, I have girlfriends who are her age, I have older girlfriends. We often had a lot of laughs, and it was funny and fun for us, like on a human level, we already knew each other so well that it was like … She knew about my difficulties, she knew about my weaknesses, about my strengths. I kept telling her about me, but I seemed to know nothing about her… .

In contrast to Jasmine who experienced difficulties with the inequality, Reut described the advantage of the mentor’s “in-between” position.

Reut (patient)

I think it’s good to have someone who’s somewhere between being a professional and being a …. I don’t know how to define it… a more mature person who can accompany you during the process […] a friend who was older than me and in a different place in life. Um … there is something about this in-between situation […] the lack of formal professional training allows for something a little more fluid and natural. It feels like the help [from the mentor] is also more at the everyday level […] things are more practical .

The tension around the unequal mentor-patient status can also put the mentor in uncomfortable and challenging situations. Linoy ranged from wanting to set a personal example for the patients to wanting to be authentic (e.g., eating the amount of food that actually suited her). Linoy made sacrifices in order to create in the patient a feeling (even a deceptive one) of equality in the relationship.

Linoy (mentor)

I don’t really have the option of coming and telling the patients I’m not hungry. [When we sit down for meals] I should be able to eat the same amounts they’re supposed to eat; I can’t eat less than what they’re supposed to eat. There is some minimum I need to eat, so I eat it, there’s nothing to be done about it. I try to plan my day accordingly and not show any difficulty [when I’m with them]. If I have a hard time eating, they’ll definitely notice; girls with EDs are very sensitive to these little nuances. So, of course, they watch me too. It bothers me. First of all it bothers me because I’m eating alongside them and it feels a bit intrusive sometimes: They look at what I eat, and whether I eat properly, and whether I’m different [from the patient]; it is a bit intrusive. On the other hand, it’s also my job. I’m supposed to come and set an example for them and if I don’t set an example for them, it’s a bit problematic in my opinion.

In many cases, patients try to overstep boundaries and invade the mentor’s privacy; they also test the relationship in ways that could threaten it. As can be seen below, this issue intensifies when Agam wonders whether, in different circumstances, she and the patient could have been friends.

The girls I worked with were around my age, studying social work or education. We frequented similar places, had mutual acquaintances, and even worked in similar settings. One of the girls started asking me personal questions from the very first session—not extremely personal, but enough for me to set clear boundaries. She’d comment on my Facebook photos, discussing whether they were flattering or not, asking about my weight, my past, and my diet. It wasn’t easy. I had to firmly tell her not to ask such questions, to clarify that we weren’t going to discuss my weight, that I wasn’t her girlfriend. It took time for us to adjust to each other. Eventually, with most of the girls, I felt it was successful. However, some of them felt like they could have been my little sister in another universe. There were moments when I could have had fun with them, but it was challenging initially. I had to understand what triggered me in their presence and quickly discern what was my own and what was theirs.

Along these same lines, sometimes there was tension between mentor and patient regarding perceptions of the relationship’s boundaries. Merav’s below quote highlights the confusion that was created when the mentor angrily dismissed Merav’s interest in her personal life.

Merav (patient)

My mentor had moved apartments and she talked about her move. [After a few days] I asked her how the move went because I care about her and I was interested, because I really love her. […] But she was very angry with me. She said she didn’t want to talk about it, and that she was the one who would decide whether to talk about it […]and it wasn’t pleasant for her … and I told her that it felt like she had something against me, that she had a hard time with me. So if she was having a hard time with me, then let’s talk about it.

Iris, a mentor, talked about how carefully the boundaries between mentor and patient must be negotiated.

Iris (mentor)

But I realized over the years that in order to make contact, in order to get them to trust me, I would need to bend the boundaries a bit at first. Like, I would need to be a bit warm with them or speak to them from a place of equal standing, so that later they would listen to me and give me respect.

In conclusion, this theme demonstrates how the closeness between mentor and patient can create tension and sometimes even role confusion: There must be an acknowledgement of the similarities between them but also of the essential difference. Many mentors aim to meet this challenge by setting clear boundaries while also allowing, at times, moments of flexibility and boundary crossing (e.g., when the mentor shares something personal about her life with the mentee) in order to maintain a sense of partnership and intimacy.

This qualitative study was designed to examine the unique experience of in-home mentoring relationships in the context of EDs, as perceived by both mentors and patients. Four themes emerged, all of which describe the unique bonding experience between the two, and its contribution to the rehabilitation process. Mentors and patients alike emphasized that the mentor’s physical entry into the patient’s home is critically significant, as it enables an encounter typified by less concealment, during which the mentor can gain access to the patient’s hidden and intimate world. Figure  1 demonstrates the complex task of the ED mentor who enters the patient’s home and must learn to move between the embracing and investigative position while dealing with boundaries, secrets and lies, and exposure to what’s both “on” and “beside” the table.

Home-based care for eating disorders - When the mentor enters the patient’s home

Patients with EDs tend to be secretive about their symptoms [ 2 , 12 ]. They tend to avoid sharing the difficulties they face while at the same time feeling they are “alone in the world” and cannot trust other people, including therapists, especially due to the fear and shame of being exposed to judgment. In addition, as some of the ED symptoms (e.g., fasting, vomiting, over-exercising) serve the patients’ goal (i.e., losing weight), they would rather conceal these symptoms than have the therapist try to eradicate them [ 2 , 20 ]. Therefore, secrecy and lack of self-disclosure are perceived in the literature as one of the major challenges faced by ED therapists [ 2 , 12 ]. In this context, the mentoring relationship, which allows the mentor to come inside the house and see what’s “on the table” can be helpful in overcoming concealment issues that oftentimes prevent ED treatments from succeeding.

Prior findings from qualitative interviews about mentoring relationships in the context of EDs have highlighted the concealment barrier [ 17 ] – that is, when patients avoid revealing information about themselves to their mentors. It is possible that patients fear that mentors will criticize and even reject them [ 20 ] and may worry that once mentors know what is really happening, they will put pressure on patients to change their eating habits (e.g., add more food to their meals) [ 11 ]. In a retrospective study [ 29 ], it was suggested that secretive behaviors were planned and conscious strategies among most (57-73%) patients with EDs. These secretive behaviors include attempts to conceal the truth, such as providing incorrect information about what has been consumed, or refusing to get on the scale during therapeutic sessions. It has also been suggested that therapists’ attempts to discover these secretive behaviors are followed by patients’ negative reactions [ 29 ]. Our findings suggest that the mentor’s entrance into the patient’s home can on the one hand be experienced as intrusive and threatening (as explained in the third theme), but at the same time can break the vicious cycle of secrecy (as explained in the first and second themes) and promote recovery. The mentoring relationship takes place in the midst of a conflict in which patients both wish to receive help but also fear the consequences of their exposure. If mentors are able to behave in a consistent and empathic way, while being sensitive to patients’ internal conflict (i.e., moving between the embracing and the investigative position, according to the patient’s needs) both parties will presumably be able to overcome this barrier and help patients reveal what they are going through.

Another major challenge in the mentoring relationship is the issue of boundaries. Clear boundaries, for instance regarding the role of each member, are crucial in helping mental health professionals define, determine, and maintain the therapeutic relationship [ 6 ]. The mentor-patient relationship in this context suffers from an inherent lack of clarity about the nature of the distance between the parties – for example, when patients invade mentors’ privacy by looking at the mentors as friends and expecting them to reveal details about their personal lives (as explained in the fourth theme). Our findings suggest that each mentor must find her own individual way of defining boundaries in this context, and therefore mentors would benefit from close supervision to help them tailor and establish boundaries for the benefit of their patients.

Overall, the study findings highlight important aspects of mentors´ tasks and roles in the context of severe and enduring EDs. Some of these tasks and roles overlap with those of other mental health providers (e.g., dieticians, psychotherapists), while others are specific to the mentors. Both mentors and other ED professionals must learn how to move between the “embracing” position, in which they hold a containing and caring presence, and the “investigative” position, in which they identify problematic areas that need to be addressed. However, the mentoring relationship is unique because certain boundaries may easily dissolve, requiring mentors to put extra effort into their establishment. The mentoring relationship takes place in the mentee’s home, and the mentor can therefore be perceived as a visiting friend, in contrast to the experience that takes place in a formal therapeutic setting typically found in a clinic. This “informal” setting demands that mentors navigate the delicate balance between intimacy and professionalism and work diligently to establish clear boundaries that might otherwise easily dissolve. It is also possible that the mentor and mentee will be of similar ages or backgrounds, adding depth to the mentoring bond but also creating a challenge to the professional relationship. Given that mentors work in a team, and often receive supervision from the psychotherapist or the dietician who regularly sees the patient, it is vital for all team members to align on treatment goals and collaborate effectively toward achieving them.

Despite the contribution of this qualitative study to the field, several limitations should be noted. Although saturation was achieved, it is possible that participants who were not included in this study (e.g., patients who refuse receiving assistance from mentors) would have shed light on factors other than the ones presented. We would recommend that researchers, in further studies, examine the mentoring relationship via the use of quantitative and empirical tools to supplement the findings presented. Such studies could include standardized surveys assessing mentor-mentee dynamics, structured observation protocols during mentoring sessions, and outcome measures quantifying specific aspects of recovery or progress.

The findings of this study have important implications for practice. First, it is critical to draw attention to the significant contribution that mentoring relationships can make to patients with EDs, and it is important to make this service available to more patients. That said, mentors are not licensed mental health professionals; they therefore need to have a great deal of knowledge about mental health rehabilitation in general and EDs in particular. They must also have several personal strengths including sensitivity, empathy, persistence, and assertiveness. These personal strengths will help them overcome the main challenges that are experienced, according to our findings (Fig.  1 ), in home-based mentoring relationships. It is important to develop a special training program for mentors, so that they can acquire knowledge and learn about the specific dynamics that are common among patients with EDs. In addition, clinical supervision is required so that mentors can bring up their mentor-patient dilemmas with mental health professionals (e.g., clinical social workers) along the way. Due to the nature of EDs, mentors’ dilemmas (e.g., boundaries, secrecy) can be complex, and mentoring work in this context can put a great deal of pressure on mentors that can be both stressful and cumulative. Mentors need to be able to reflect on their dilemmas in the presence of a clinical supervisor, as it may be almost impossible for mentors to find solutions on their own, and without continuous clinical supervision.

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Elran-Barak, R., Elmalah-Alon, S. Moving between positions: a qualitative study of mentoring relationships in chronic eating disorders. J Eat Disord 12 , 59 (2024). https://doi.org/10.1186/s40337-024-01007-x

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Biodiesel supply chain network design: a comprehensive review with qualitative and quantitative insights

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The global community is actively pursuing alternative energy sources to mitigate environmental concerns and decrease dependence on fossil fuels. Biodiesel, recognized as a clean and eco-friendly fuel with advantages over petroleum-based alternatives, has been identified as a viable substitute. However, its commercialization encounters challenges due to costly production processes. Establishing a more efficient supply chain for mass production and distribution could surmount these obstacles, rendering biodiesel a cost-effective solution. Despite numerous review articles across various renewable energy supply chain domains, there remains a gap in the literature specifically addressing the biodiesel supply chain network design. This research entails a comprehensive systematic literature review (SLR) focusing on the design of biodiesel supply chain networks. The primary objective is to formulate an economically, environmentally, and socially optimized supply chain framework. The review also seeks to offer a holistic overview of pertinent technical terms and key activities involved in these supply chains. Through this SLR, a thorough examination and synthesis of existing literature will yield valuable insights into the design and optimization of biodiesel supply chains. Additionally, it will identify critical research gaps in the field, proposing the exploration of fourth-generation feedstocks, integration of multi-channel chains, and the incorporation of sustainability and resilience aspects into the supply chain network design. These proposed areas aim to address existing knowledge gaps and enhance the overall effectiveness of biodiesel supply chain networks.

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Rahmani, S., Goli, A. & Zackery, A. Biodiesel supply chain network design: a comprehensive review with qualitative and quantitative insights. Environ Sci Pollut Res (2024). https://doi.org/10.1007/s11356-024-33392-w

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Conducting and Writing Quantitative and Qualitative Research

Edward barroga.

1 Department of Medical Education, Showa University School of Medicine, Tokyo, Japan.

Glafera Janet Matanguihan

2 Department of Biological Sciences, Messiah University, Mechanicsburg, PA, USA.

Atsuko Furuta

Makiko arima, shizuma tsuchiya, chikako kawahara, yusuke takamiya.

Comprehensive knowledge of quantitative and qualitative research systematizes scholarly research and enhances the quality of research output. Scientific researchers must be familiar with them and skilled to conduct their investigation within the frames of their chosen research type. When conducting quantitative research, scientific researchers should describe an existing theory, generate a hypothesis from the theory, test their hypothesis in novel research, and re-evaluate the theory. Thereafter, they should take a deductive approach in writing the testing of the established theory based on experiments. When conducting qualitative research, scientific researchers raise a question, answer the question by performing a novel study, and propose a new theory to clarify and interpret the obtained results. After which, they should take an inductive approach to writing the formulation of concepts based on collected data. When scientific researchers combine the whole spectrum of inductive and deductive research approaches using both quantitative and qualitative research methodologies, they apply mixed-method research. Familiarity and proficiency with these research aspects facilitate the construction of novel hypotheses, development of theories, or refinement of concepts.

Graphical Abstract

INTRODUCTION

Novel research studies are conceptualized by scientific researchers first by asking excellent research questions and developing hypotheses, then answering these questions by testing their hypotheses in ethical research. 1 , 2 , 3 Before they conduct novel research studies, scientific researchers must possess considerable knowledge of both quantitative and qualitative research. 2

In quantitative research, researchers describe existing theories, generate and test a hypothesis in novel research, and re-evaluate existing theories deductively based on their experimental results. 1 , 4 , 5 In qualitative research, scientific researchers raise and answer research questions by performing a novel study, then propose new theories by clarifying their results inductively. 1 , 6

RATIONALE OF THIS ARTICLE

When researchers have a limited knowledge of both research types and how to conduct them, this can result in substandard investigation. Researchers must be familiar with both types of research and skilled to conduct their investigations within the frames of their chosen type of research. Thus, meticulous care is needed when planning quantitative and qualitative research studies to avoid unethical research and poor outcomes.

Understanding the methodological and writing assumptions 7 , 8 underpinning quantitative and qualitative research, especially by non-Anglophone researchers, is essential for their successful conduct. Scientific researchers, especially in the academe, face pressure to publish in international journals 9 where English is the language of scientific communication. 10 , 11 In particular, non-Anglophone researchers face challenges related to linguistic, stylistic, and discourse differences. 11 , 12 Knowing the assumptions of the different types of research will help clarify research questions and methodologies, easing the challenge and help.

SEARCH FOR RELEVANT ARTICLES

To identify articles relevant to this topic, we adhered to the search strategy recommended by Gasparyan et al. 7 We searched through PubMed, Scopus, Directory of Open Access Journals, and Google Scholar databases using the following keywords: quantitative research, qualitative research, mixed-method research, deductive reasoning, inductive reasoning, study design, descriptive research, correlational research, experimental research, causal-comparative research, quasi-experimental research, historical research, ethnographic research, meta-analysis, narrative research, grounded theory, phenomenology, case study, and field research.

AIMS OF THIS ARTICLE

This article aims to provide a comparative appraisal of qualitative and quantitative research for scientific researchers. At present, there is still a need to define the scope of qualitative research, especially its essential elements. 13 Consensus on the critical appraisal tools to assess the methodological quality of qualitative research remains lacking. 14 Framing and testing research questions can be challenging in qualitative research. 2 In the healthcare system, it is essential that research questions address increasingly complex situations. Therefore, research has to be driven by the kinds of questions asked and the corresponding methodologies to answer these questions. 15 The mixed-method approach also needs to be clarified as this would appear to arise from different philosophical underpinnings. 16

This article also aims to discuss how particular types of research should be conducted and how they should be written in adherence to international standards. In the US, Europe, and other countries, responsible research and innovation was conceptualized and promoted with six key action points: engagement, gender equality, science education, open access, ethics and governance. 17 , 18 International ethics standards in research 19 as well as academic integrity during doctoral trainings are now integral to the research process. 20

POTENTIAL BENEFITS FROM THIS ARTICLE

This article would be beneficial for researchers in further enhancing their understanding of the theoretical, methodological, and writing aspects of qualitative and quantitative research, and their combination.

Moreover, this article reviews the basic features of both research types and overviews the rationale for their conduct. It imparts information on the most common forms of quantitative and qualitative research, and how they are carried out. These aspects would be helpful for selecting the optimal methodology to use for research based on the researcher’s objectives and topic.

This article also provides information on the strengths and weaknesses of quantitative and qualitative research. Such information would help researchers appreciate the roles and applications of both research types and how to gain from each or their combination. As different research questions require different types of research and analyses, this article is anticipated to assist researchers better recognize the questions answered by quantitative and qualitative research.

Finally, this article would help researchers to have a balanced perspective of qualitative and quantitative research without considering one as superior to the other.

TYPES OF RESEARCH

Research can be classified into two general types, quantitative and qualitative. 21 Both types of research entail writing a research question and developing a hypothesis. 22 Quantitative research involves a deductive approach to prove or disprove the hypothesis that was developed, whereas qualitative research involves an inductive approach to create a hypothesis. 23 , 24 , 25 , 26

In quantitative research, the hypothesis is stated before testing. In qualitative research, the hypothesis is developed through inductive reasoning based on the data collected. 27 , 28 For types of data and their analysis, qualitative research usually includes data in the form of words instead of numbers more commonly used in quantitative research. 29

Quantitative research usually includes descriptive, correlational, causal-comparative / quasi-experimental, and experimental research. 21 On the other hand, qualitative research usually encompasses historical, ethnographic, meta-analysis, narrative, grounded theory, phenomenology, case study, and field research. 23 , 25 , 28 , 30 A summary of the features, writing approach, and examples of published articles for each type of qualitative and quantitative research is shown in Table 1 . 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43

QUANTITATIVE RESEARCH

Deductive approach.

The deductive approach is used to prove or disprove the hypothesis in quantitative research. 21 , 25 Using this approach, researchers 1) make observations about an unclear or new phenomenon, 2) investigate the current theory surrounding the phenomenon, and 3) hypothesize an explanation for the observations. Afterwards, researchers will 4) predict outcomes based on the hypotheses, 5) formulate a plan to test the prediction, and 6) collect and process the data (or revise the hypothesis if the original hypothesis was false). Finally, researchers will then 7) verify the results, 8) make the final conclusions, and 9) present and disseminate their findings ( Fig. 1A ).

Types of quantitative research

The common types of quantitative research include (a) descriptive, (b) correlational, c) experimental research, and (d) causal-comparative/quasi-experimental. 21

Descriptive research is conducted and written by describing the status of an identified variable to provide systematic information about a phenomenon. A hypothesis is developed and tested after data collection, analysis, and synthesis. This type of research attempts to factually present comparisons and interpretations of findings based on analyses of the characteristics, progression, or relationships of a certain phenomenon by manipulating the employed variables or controlling the involved conditions. 44 Here, the researcher examines, observes, and describes a situation, sample, or variable as it occurs without investigator interference. 31 , 45 To be meaningful, the systematic collection of information requires careful selection of study units by precise measurement of individual variables 21 often expressed as ranges, means, frequencies, and/or percentages. 31 , 45 Descriptive statistical analysis using ANOVA, Student’s t -test, or the Pearson coefficient method has been used to analyze descriptive research data. 46

Correlational research is performed by determining and interpreting the extent of a relationship between two or more variables using statistical data. This involves recognizing data trends and patterns without necessarily proving their causes. The researcher studies only the data, relationships, and distributions of variables in a natural setting, but does not manipulate them. 21 , 45 Afterwards, the researcher establishes reliability and validity, provides converging evidence, describes relationship, and makes predictions. 47

Experimental research is usually referred to as true experimentation. The researcher establishes the cause-effect relationship among a group of variables making up a study using the scientific method or process. This type of research attempts to identify the causal relationships between variables through experiments by arbitrarily controlling the conditions or manipulating the variables used. 44 The scientific manuscript would include an explanation of how the independent variable was manipulated to determine its effects on the dependent variables. The write-up would also describe the random assignments of subjects to experimental treatments. 21

Causal-comparative/quasi-experimental research closely resembles true experimentation but is conducted by establishing the cause-effect relationships among variables. It may also be conducted to establish the cause or consequences of differences that already exist between, or among groups of individuals. 48 This type of research compares outcomes between the intervention groups in which participants are not randomized to their respective interventions because of ethics- or feasibility-related reasons. 49 As in true experiments, the researcher identifies and measures the effects of the independent variable on the dependent variable. However, unlike true experiments, the researchers do not manipulate the independent variable.

In quasi-experimental research, naturally formed or pre-existing groups that are not randomly assigned are used, particularly when an ethical, randomized controlled trial is not feasible or logical. 50 The researcher identifies control groups as those which have been exposed to the treatment variable, and then compares these with the unexposed groups. The causes are determined and described after data analysis, after which conclusions are made. The known and unknown variables that could still affect the outcome are also included. 7

QUALITATIVE RESEARCH

Inductive approach.

Qualitative research involves an inductive approach to develop a hypothesis. 21 , 25 Using this approach, researchers answer research questions and develop new theories, but they do not test hypotheses or previous theories. The researcher seldom examines the effectiveness of an intervention, but rather explores the perceptions, actions, and feelings of participants using interviews, content analysis, observations, or focus groups. 25 , 45 , 51

Distinctive features of qualitative research

Qualitative research seeks to elucidate about the lives of people, including their lived experiences, behaviors, attitudes, beliefs, personality characteristics, emotions, and feelings. 27 , 30 It also explores societal, organizational, and cultural issues. 30 This type of research provides a good story mimicking an adventure which results in a “thick” description that puts readers in the research setting. 52

The qualitative research questions are open-ended, evolving, and non-directional. 26 The research design is usually flexible and iterative, commonly employing purposive sampling. The sample size depends on theoretical saturation, and data is collected using in-depth interviews, focus groups, and observations. 27

In various instances, excellent qualitative research may offer insights that quantitative research cannot. Moreover, qualitative research approaches can describe the ‘lived experience’ perspectives of patients, practitioners, and the public. 53 Interestingly, recent developments have looked into the use of technology in shaping qualitative research protocol development, data collection, and analysis phases. 54

Qualitative research employs various techniques, including conversational and discourse analysis, biographies, interviews, case-studies, oral history, surveys, documentary and archival research, audiovisual analysis, and participant observations. 26

Conducting qualitative research

To conduct qualitative research, investigators 1) identify a general research question, 2) choose the main methods, sites, and subjects, and 3) determine methods of data documentation access to subjects. Researchers also 4) decide on the various aspects for collecting data (e.g., questions, behaviors to observe, issues to look for in documents, how much (number of questions, interviews, or observations), 5) clarify researchers’ roles, and 6) evaluate the study’s ethical implications in terms of confidentiality and sensitivity. Afterwards, researchers 7) collect data until saturation, 8) interpret data by identifying concepts and theories, and 9) revise the research question if necessary and form hypotheses. In the final stages of the research, investigators 10) collect and verify data to address revisions, 11) complete the conceptual and theoretical framework to finalize their findings, and 12) present and disseminate findings ( Fig. 1B ).

Types of qualitative research

The different types of qualitative research include (a) historical research, (b) ethnographic research, (c) meta-analysis, (d) narrative research, (e) grounded theory, (f) phenomenology, (g) case study, and (h) field research. 23 , 25 , 28 , 30

Historical research is conducted by describing past events, problems, issues, and facts. The researcher gathers data from written or oral descriptions of past events and attempts to recreate the past without interpreting the events and their influence on the present. 6 Data is collected using documents, interviews, and surveys. 55 The researcher analyzes these data by describing the development of events and writes the research based on historical reports. 2

Ethnographic research is performed by observing everyday life details as they naturally unfold. 2 It can also be conducted by developing in-depth analytical descriptions of current systems, processes, and phenomena or by understanding the shared beliefs and practices of a particular group or culture. 21 The researcher collects extensive narrative non-numerical data based on many variables over an extended period, in a natural setting within a specific context. To do this, the researcher uses interviews, observations, and active participation. These data are analyzed by describing and interpreting them and developing themes. A detailed report of the interpreted data is then provided. 2 The researcher immerses himself/herself into the study population and describes the actions, behaviors, and events from the perspective of someone involved in the population. 23 As examples of its application, ethnographic research has helped to understand a cultural model of family and community nursing during the coronavirus disease 2019 outbreak. 56 It has also been used to observe the organization of people’s environment in relation to cardiovascular disease management in order to clarify people’s real expectations during follow-up consultations, possibly contributing to the development of innovative solutions in care practices. 57

Meta-analysis is carried out by accumulating experimental and correlational results across independent studies using a statistical method. 21 The report is written by specifying the topic and meta-analysis type. In the write-up, reporting guidelines are followed, which include description of inclusion criteria and key variables, explanation of the systematic search of databases, and details of data extraction. Meta-analysis offers in-depth data gathering and analysis to achieve deeper inner reflection and phenomenon examination. 58

Narrative research is performed by collecting stories for constructing a narrative about an individual’s experiences and the meanings attributed to them by the individual. 9 It aims to hear the voice of individuals through their account or experiences. 17 The researcher usually conducts interviews and analyzes data by storytelling, content review, and theme development. The report is written as an in-depth narration of events or situations focused on the participants. 2 , 59 Narrative research weaves together sequential events from one or two individuals to create a “thick” description of a cohesive story or narrative. 23 It facilitates understanding of individuals’ lives based on their own actions and interpretations. 60

Grounded theory is conducted by engaging in an inductive ground-up or bottom-up strategy of generating a theory from data. 24 The researcher incorporates deductive reasoning when using constant comparisons. Patterns are detected in observations and then a working hypothesis is created which directs the progression of inquiry. The researcher collects data using interviews and questionnaires. These data are analyzed by coding the data, categorizing themes, and describing implications. The research is written as a theory and theoretical models. 2 In the write-up, the researcher describes the data analysis procedure (i.e., theoretical coding used) for developing hypotheses based on what the participants say. 61 As an example, a qualitative approach has been used to understand the process of skill development of a nurse preceptor in clinical teaching. 62 A researcher can also develop a theory using the grounded theory approach to explain the phenomena of interest by observing a population. 23

Phenomenology is carried out by attempting to understand the subjects’ perspectives. This approach is pertinent in social work research where empathy and perspective are keys to success. 21 Phenomenology studies an individual’s lived experience in the world. 63 The researcher collects data by interviews, observations, and surveys. 16 These data are analyzed by describing experiences, examining meanings, and developing themes. The researcher writes the report by contextualizing and reporting the subjects’ experience. This research approach describes and explains an event or phenomenon from the perspective of those who have experienced it. 23 Phenomenology understands the participants’ experiences as conditioned by their worldviews. 52 It is suitable for a deeper understanding of non-measurable aspects related to the meanings and senses attributed by individuals’ lived experiences. 60

Case study is conducted by collecting data through interviews, observations, document content examination, and physical inspections. The researcher analyzes the data through a detailed identification of themes and the development of narratives. The report is written as an in-depth study of possible lessons learned from the case. 2

Field research is performed using a group of methodologies for undertaking qualitative inquiries. The researcher goes directly to the social phenomenon being studied and observes it extensively. In the write-up, the researcher describes the phenomenon under the natural environment over time with no implantation of controls or experimental conditions. 45

DIFFERENCES BETWEEN QUANTITATIVE AND QUALITATIVE RESEARCH

Scientific researchers must be aware of the differences between quantitative and qualitative research in terms of their working mechanisms to better understand their specific applications. This knowledge will be of significant benefit to researchers, especially during the planning process, to ensure that the appropriate type of research is undertaken to fulfill the research aims.

In terms of quantitative research data evaluation, four well-established criteria are used: internal validity, external validity, reliability, and objectivity. 23 The respective correlating concepts in qualitative research data evaluation are credibility, transferability, dependability, and confirmability. 30 Regarding write-up, quantitative research papers are usually shorter than their qualitative counterparts, which allows the latter to pursue a deeper understanding and thus producing the so-called “thick” description. 29

Interestingly, a major characteristic of qualitative research is that the research process is reversible and the research methods can be modified. This is in contrast to quantitative research in which hypothesis setting and testing take place unidirectionally. This means that in qualitative research, the research topic and question may change during literature analysis, and that the theoretical and analytical methods could be altered during data collection. 44

Quantitative research focuses on natural, quantitative, and objective phenomena, whereas qualitative research focuses on social, qualitative, and subjective phenomena. 26 Quantitative research answers the questions “what?” and “when?,” whereas qualitative research answers the questions “why?,” “how?,” and “how come?.” 64

Perhaps the most important distinction between quantitative and qualitative research lies in the nature of the data being investigated and analyzed. Quantitative research focuses on statistical, numerical, and quantitative aspects of phenomena, and employ the same data collection and analysis, whereas qualitative research focuses on the humanistic, descriptive, and qualitative aspects of phenomena. 26 , 28

Structured versus unstructured processes

The aims and types of inquiries determine the difference between quantitative and qualitative research. In quantitative research, statistical data and a structured process are usually employed by the researcher. Quantitative research usually suggests quantities (i.e., numbers). 65 On the other hand, researchers typically use opinions, reasons, verbal statements, and an unstructured process in qualitative research. 63 Qualitative research is more related to quality or kind. 65

In quantitative research, the researcher employs a structured process for collecting quantifiable data. Often, a close-ended questionnaire is used wherein the response categories for each question are designed in which values can be assigned and analyzed quantitatively using a common scale. 66 Quantitative research data is processed consecutively from data management, then data analysis, and finally to data interpretation. Data should be free from errors and missing values. In data management, variables are defined and coded. In data analysis, statistics (e.g., descriptive, inferential) as well as central tendency (i.e., mean, median, mode), spread (standard deviation), and parameter estimation (confidence intervals) measures are used. 67

In qualitative research, the researcher uses an unstructured process for collecting data. These non-statistical data may be in the form of statements, stories, or long explanations. Various responses according to respondents may not be easily quantified using a common scale. 66

Composing a qualitative research paper resembles writing a quantitative research paper. Both papers consist of a title, an abstract, an introduction, objectives, methods, findings, and discussion. However, a qualitative research paper is less regimented than a quantitative research paper. 27

Quantitative research as a deductive hypothesis-testing design

Quantitative research can be considered as a hypothesis-testing design as it involves quantification, statistics, and explanations. It flows from theory to data (i.e., deductive), focuses on objective data, and applies theories to address problems. 45 , 68 It collects numerical or statistical data; answers questions such as how many, how often, how much; uses questionnaires, structured interview schedules, or surveys 55 as data collection tools; analyzes quantitative data in terms of percentages, frequencies, statistical comparisons, graphs, and tables showing statistical values; and reports the final findings in the form of statistical information. 66 It uses variable-based models from individual cases and findings are stated in quantified sentences derived by deductive reasoning. 24

In quantitative research, a phenomenon is investigated in terms of the relationship between an independent variable and a dependent variable which are numerically measurable. The research objective is to statistically test whether the hypothesized relationship is true. 68 Here, the researcher studies what others have performed, examines current theories of the phenomenon being investigated, and then tests hypotheses that emerge from those theories. 4

Quantitative hypothesis-testing research has certain limitations. These limitations include (a) problems with selection of meaningful independent and dependent variables, (b) the inability to reflect subjective experiences as variables since variables are usually defined numerically, and (c) the need to state a hypothesis before the investigation starts. 61

Qualitative research as an inductive hypothesis-generating design

Qualitative research can be considered as a hypothesis-generating design since it involves understanding and descriptions in terms of context. It flows from data to theory (i.e., inductive), focuses on observation, and examines what happens in specific situations with the aim of developing new theories based on the situation. 45 , 68 This type of research (a) collects qualitative data (e.g., ideas, statements, reasons, characteristics, qualities), (b) answers questions such as what, why, and how, (c) uses interviews, observations, or focused-group discussions as data collection tools, (d) analyzes data by discovering patterns of changes, causal relationships, or themes in the data; and (e) reports the final findings as descriptive information. 61 Qualitative research favors case-based models from individual characteristics, and findings are stated using context-dependent existential sentences that are justifiable by inductive reasoning. 24

In qualitative research, texts and interviews are analyzed and interpreted to discover meaningful patterns characteristic of a particular phenomenon. 61 Here, the researcher starts with a set of observations and then moves from particular experiences to a more general set of propositions about those experiences. 4

Qualitative hypothesis-generating research involves collecting interview data from study participants regarding a phenomenon of interest, and then using what they say to develop hypotheses. It involves the process of questioning more than obtaining measurements; it generates hypotheses using theoretical coding. 61 When using large interview teams, the key to promoting high-level qualitative research and cohesion in large team methods and successful research outcomes is the balance between autonomy and collaboration. 69

Qualitative data may also include observed behavior, participant observation, media accounts, and cultural artifacts. 61 Focus group interviews are usually conducted, audiotaped or videotaped, and transcribed. Afterwards, the transcript is analyzed by several researchers.

Qualitative research also involves scientific narratives and the analysis and interpretation of textual or numerical data (or both), mostly from conversations and discussions. Such approach uncovers meaningful patterns that describe a particular phenomenon. 2 Thus, qualitative research requires skills in grasping and contextualizing data, as well as communicating data analysis and results in a scientific manner. The reflective process of the inquiry underscores the strengths of a qualitative research approach. 2

Combination of quantitative and qualitative research

When both quantitative and qualitative research methods are used in the same research, mixed-method research is applied. 25 This combination provides a complete view of the research problem and achieves triangulation to corroborate findings, complementarity to clarify results, expansion to extend the study’s breadth, and explanation to elucidate unexpected results. 29

Moreover, quantitative and qualitative findings are integrated to address the weakness of both research methods 29 , 66 and to have a more comprehensive understanding of the phenomenon spectrum. 66

For data analysis in mixed-method research, real non-quantitized qualitative data and quantitative data must both be analyzed. 70 The data obtained from quantitative analysis can be further expanded and deepened by qualitative analysis. 23

In terms of assessment criteria, Hammersley 71 opined that qualitative and quantitative findings should be judged using the same standards of validity and value-relevance. Both approaches can be mutually supportive. 52

Quantitative and qualitative research must be carefully studied and conducted by scientific researchers to avoid unethical research and inadequate outcomes. Quantitative research involves a deductive process wherein a research question is answered with a hypothesis that describes the relationship between independent and dependent variables, and the testing of the hypothesis. This investigation can be aptly termed as hypothesis-testing research involving the analysis of hypothesis-driven experimental studies resulting in a test of significance. Qualitative research involves an inductive process wherein a research question is explored to generate a hypothesis, which then leads to the development of a theory. This investigation can be aptly termed as hypothesis-generating research. When the whole spectrum of inductive and deductive research approaches is combined using both quantitative and qualitative research methodologies, mixed-method research is applied, and this can facilitate the construction of novel hypotheses, development of theories, or refinement of concepts.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

• Conceptualization: Barroga E, Matanguihan GJ.
• Data curation: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C, Takamiya Y, Izumi M.
• Formal analysis: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C.
• Investigation: Barroga E, Matanguihan GJ, Takamiya Y, Izumi M.
• Methodology: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C, Takamiya Y, Izumi M.
• Project administration: Barroga E, Matanguihan GJ.
• Resources: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C, Takamiya Y, Izumi M.
• Supervision: Barroga E.
• Validation: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C, Takamiya Y, Izumi M.
• Visualization: Barroga E, Matanguihan GJ.
• Writing - original draft: Barroga E, Matanguihan GJ.
• Writing - review & editing: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C, Takamiya Y, Izumi M.