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Descriptive Research Design – Types, Methods and Examples

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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.

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Muhammad Hassan

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• Descriptive Research Designs: Types, Examples & Methods

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

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

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

What is Descriptive Research?

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

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

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

What Are The Types of Descriptive Research?

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

• Descriptive-survey

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

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

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

• Descriptive-normative survey

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

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

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

• Descriptive-status

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

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

• Descriptive-analysis

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

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

• Descriptive classification

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

• Descriptive-comparative

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

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

• Correlative Survey

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

Examples of Descriptive Research

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

• Comparing Student Performance:

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

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

• Scientific Classification

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

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

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

• Human Behavior

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

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

What are the Characteristics of Descriptive Research?  

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

• Quantitativeness

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

• Qualitativeness

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

• Uncontrolled variables

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

• The basis for further research

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

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

Why Use Descriptive Research Design?  

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

• Define subject characteristics :

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

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

• Measure Data Trends

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

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

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

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

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

• Validate existing conditions

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

• Conducted Overtime

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

What are the Disadvantages of Descriptive Research?  

• Response and Non-response Bias

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

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

What are the Data Collection Methods in Descriptive Research?  

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

1. Observational Method

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

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

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

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

2. Case Study Method

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

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

3. Survey Research

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

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

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

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

What Are The Differences Between Descriptive and Correlational Research?  

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

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

Correlational research may be used in 2 situations;

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

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

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

• Definitions :

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

• Characteristics :

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

• Predictions :

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

Descriptive Research vs. Causal Research

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

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

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

Descriptive Research vs. Analytical Research

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

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

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

Descriptive Research vs. Exploratory Research

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

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

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

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

Descriptive Research vs. Experimental Research

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

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

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

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

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

Descriptive Research vs. Explanatory Research

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

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

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

Descriptive Research vs. Inferential Research

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

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

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

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

Related – Inferential Statistics: Definition, Types + Examples

Conclusion  

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

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

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

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• Descriptive Research | Definition, Types, Methods & Examples

Descriptive Research | Definition, Types, Methods & Examples

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

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

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

Table of contents

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

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

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

Descriptive research question examples

• How has the Amsterdam housing market changed over the past 20 years?
• Do customers of company X prefer product X or product Y?
• What are the main genetic, behavioural and morphological differences between European wildcats and domestic cats?
• What are the most popular online news sources among under-18s?
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Descriptive research is usually defined as a type of quantitative research , though qualitative research can also be used for descriptive purposes. The research design should be carefully developed to ensure that the results are valid and reliable .

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

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

Observations

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

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

Case studies

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

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

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

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

Research bias

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

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McCombes, S. (2023, June 22). Descriptive Research | Definition, Types, Methods & Examples. Scribbr. Retrieved April 6, 2024, from https://www.scribbr.com/methodology/descriptive-research/

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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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• 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?

Prevent plagiarism, run a free check.

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 .

Cite this Scribbr article

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McCombes, S. (2022, October 10). Descriptive Research Design | Definition, Methods & Examples. Scribbr. Retrieved 2 April 2024, from https://www.scribbr.co.uk/research-methods/descriptive-research-design/

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Descriptive Research 101: Definition, Methods and Examples

Parvathi vijayamohan.

18 October 2023

Table Of Contents

• Descriptive Research 101: The Definitive Guide

What is Descriptive Research?

Key characteristics of descriptive research.

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

Observation

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

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

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

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

Click to jump to the section that interests you.

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

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

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

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

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

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

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

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

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

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

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• Surveys can be hyper-local, regional, or global, depending on your objectives.
• Share surveys in-person, offline, via SMS, email, or QR codes – so many options !
• Easy to automate if you want to conduct many surveys over a period.

The observational method is a type of descriptive research in which you, the researcher, observe ongoing behavior.

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

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

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

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

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

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

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

1. Case Study: Airbnb’s Growth Strategy

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

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

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

2. Observation – Better Tech Experiences for the Elderly

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

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

3. Surveys – Decoding Sleep with SurveySparrow

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

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

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

1: Answer the six Ws –

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

#2: Introduce and explain your methodological approach

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

#4: Describe your methods of analysis.

#5: Explain the reasoning behind your choices.

#6: Collect data.

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

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

Wrapping Up

That’s all, folks!

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Comparative Studies

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• Mario Coccia 2 , 3 &
• Igor Benati 3  

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Benati I, Coccia M (2017) General trends and causes of high compensation of government managers in the OECD countries. Int J Public Adm. doi: https://doi.org/10.1080/01900692.2017.1318399

Benati I, Coccia M (2018) Rewards in Bureaucracy and Politics. In Global Encyclopedia of Public Administration, Public Policy, and Governance –section Bureaucracy (edited by Ali Farazmand) Chapter No: 3417-1, https://doi.org/10.1007/978-3-319-31816-5_3417-1 , Springer International Publishing AG

Coccia M, Rolfo S (2007) How research policy changes can affect the organization and productivity of public research institutes. Journal of Comparative Policy Analysis, Research and Practice, 9(3): 215–233. https://doi.org/10.1080/13876980701494624

Coccia M, Rolfo S (2013) Human Resource Management and Organizational Behavior of Public Research Institutions. International Journal of Public Administration, 36(4): 256–268, https://doi.org/10.1080/01900692.2012.756889

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Arizona State University, Tempe, AZ, USA

Mario Coccia

CNR – National Research Council of Italy, Torino, Italy

Mario Coccia & Igor Benati

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Coccia, M., Benati, I. (2018). Comparative Studies. In: Farazmand, A. (eds) Global Encyclopedia of Public Administration, Public Policy, and Governance. Springer, Cham. https://doi.org/10.1007/978-3-319-31816-5_1197-1

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The Qualitative Descriptive Approach in International Comparative Studies: Using Online Qualitative Surveys

Brayan v. seixas.

1 School of Population and Public Health, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada.

Neale Smith

2 Centre for Clinical Epidemiology & Evaluation, Vancouver Coastal Health Research Institute, University of British Columbia, Vancouver, BC, Canada.

Craig Mitton

International comparative studies constitute a highly valuable contribution to public policy research. Analysing different policy designs offers not only a mean of knowing the phenomenon itself but also gives us insightful clues on how to improve existing practices. Although much of the work carried out in this realm relies on quantitative appraisal of the data contained in international databases or collected from institutional websites, countless topics may simply not be studied using this type of methodological design due to, for instance, the lack of reliable databases, sparse or diffuse sources of information, etc. Here then we discuss the use of the qualitative descriptive approach as a methodological tool to obtain data on how policies are structured. We propose the use of online qualitative surveys with key stakeholders from each relevant national context in order to retrieve the fundamental pieces of information on how a certain public policy is addressed there. Starting from Sandelowski’s seminal paper on qualitative descriptive studies, we conduct a theoretical reflection on the current methodological proposition. We argue that a researcher engaged in this endeavour acts like a composite-sketch artist collecting pieces of information from witnesses in order to draw a valid depiction of reality. Furthermore, we discuss the most relevant aspects involving sampling, data collection and data analysis in this context. Overall, this methodological design has a great potential for allowing researchers to expand the international analysis of public policies to topics hitherto little appraised from this perspective.

Introduction

International comparative studies may contribute enormously to public policy research. Understanding the distinct manners in which a certain issue may be tackled provides better comprehension of the problem itself as well as useful insights on the design of institutional responses. For instance, the works of Hall and Lamont, 1 Stuckler and Basu, 2 and Schrecker and Bambra 3 consistently show through cross-national comparisons how certain economic policies have profoundly impacted on population health.

However international comparisons pose demanding data collection challenges. Much of the work performed in such studies relies on existing databases kept by international agencies, third sector organizations or research institutions (eg, World Bank, OECD, WHO, UN). For studies on some topics, however, there is no reliable database from which the necessary information might be retrieved. Thus, it is vital that alternative, methodologically rigorous approaches emerge.

Here we discuss the use of online qualitative surveys as a tool to overcome the difficulties of conducting comparative studies on public policies in different national jurisdictions. The basic idea is that instead of relying on institutional websites, publicly available policy documents or well-established databases to understand how certain policies have been addressed, we could question key stakeholders (such as policy-makers, public servants or researchers involved with the topic in question) from each relevant national context in order to retrieve essential information directly from them.

Given that the diversity of responses can be totally unanticipated by researchers, it is necessary to have a tool that is open enough to allow any type of information to be captured, for which purpose qualitative methodologies are highly appropriate. However, taking into account that the main objective of this type of research is to obtain comparable information from a potentially large number of different countries, the methodology needs also to pre-structure responses to a sufficient extent to allow for viable and efficient data reduction and analysis. And for this particularity, a qualitative description approach through the use of online qualitative surveys, ie, structured questionnaires with open-ended questions, seems to be an interesting solution.

Thus, this paper aims to provide a discussion of the theoretical reasoning underlying the qualitative description approach – presenting as an adequate solution to the tensions noted above – as well as practical insights on the development of such work within the realm of international comparative studies on public policies.

Theoretical Reasoning

According to Sandelowski, 4 basic or fundamental qualitative description differs from other types of qualitative research, such as grounded theory, ethnography, phenomenology or narrative analysis, in the sense that it is — as the label suggests — essentially descriptive rather than interpretive in focus. This does not mean that a qualitative descriptive approach lacks interpretive efforts or that it intends a supposedly neutral depiction of reality. Qualitative description represents the methodological category that has the least level of inference among the qualitative methods, one that allows “ the reading of lines, as opposed to reading into, between, over or beyond the lines. ” 5 However, it should not be understood as a low-quality approach or solely as an entry-point to really deep research. “ There is nothing trivial or easy about getting the facts, and the meanings participants give to those facts, right and then conveying them in a coherent and useful manner. ” 4 Such qualitative description must be viewed as a valuable end-product in itself, and not simply as an entry-point.

We propose the use of on-line surveys as a way of operationalizing qualitative description in international comparative studies, allowing the retrieval of information on governmental/institutional efforts to develop, implement and evaluate public policies based on the reports of involved stakeholders who draw upon their own situated experience and knowledge. Within this context, we offer a reflection emerging from Kvale’s metaphor 6 on the role of a researcher. Kvale presents two ideal types: the researcher as a miner and the researcher as a traveller. For the former, the reality is out there waiting to be discovered. The job of a miner is then to find the precious stones, the gems, ie, the pieces of reality that have value in a given social setting. Thus, the miner-researcher operates under a predominantly positivist framework. On the contrary, the traveller is experiencing the reality herself. There is no separation of what a traveller has to tell us about the reality from the actual reality. Therefore, the traveller-researcher is not a collector of pieces of information, but rather she/he is the proper constructor of the pieces. This type of researcher marches mainly under a socio-constructivist paradigm.

Kvale’s metaphor is indeed incredibly insightful to reflect on the role of the qualitative researcher in general, which should not be understood as either miner or traveller, but as an enterprise with a predominance of one or the other role. Yet for qualitative descriptive studies particularly, we suggest that another metaphorical representation can be even more powerful. Here we propose that the role of a researcher involved in qualitative descriptive efforts is that of a composite sketch artist . The underlying idea is that this artist has the role of depicting a ‘reality’ based on the reports of the witnesses. In other words, the artist has the duty of drawing a picture that is in accordance to the memories of the witnesses, rather than substituting his/her own speculation in its stead. The artist inevitably has her/his own images in mind, but the aim is to capture the understanding of the other—a picture that the witnesses would agree represents the reality they experienced. Contextualizing this for the field of policy research, the role of the researcher conducting qualitative descriptive study is to retrieve information from stakeholders about their own experiences with the institutions in order to reconstruct the actual governmental designs of public policies or organizational management systems. Thus, the method employed has to faithfully draw the picture upon which most of the interviewees from a given setting will agree.

This metaphor leads us to reflect on the concepts of descriptive and interpretive validity, as elaborated by Maxwell. 7 For Maxwell, descriptive validity refers to the accurate, ‘correct’ or faithful use of the factual aspects of data. It is predominantly related to the elements “pertaining to physical and behavioral events that are, in principle, observable.” 7 For example, policy content and the means by which policy is enacted within given political jurisdictions. Thus, the large majority of the work conducted in qualitative descriptions are almost exclusively circumscribed to this level of interpretation and validity. In other words, descriptive validity deals with how the composite-sketch artist treats the information provided by the witness. It does not mean that the researcher would actually work as a copier or a mere reproducer – impossible as he/she is not within the head of the observer and does not share the experience in question. The important thing to note here is that qualitative description is not an inference-free approach, but rather the methodological work of least inference among categories of qualitative work. In the context of international comparative studies, the researcher has to ‘keep close to the surface’ of the information provided by the stakeholders in order to appropriately describe the local systems of management or public policies.

Albeit the fundamental concern of qualitative descriptive studies is to provide a sort of report of events, institutional structures, and commonly observable behaviors, it is also important that researchers account for the meaning of these things for the people studied. It does not signify that qualitative description will dive deeply into the web of meanings in which subjects are constantly moving, but there has to be at least a conscious movement of acknowledging this phenomenon in order to obtain a valid drawing of the reality. This is what Maxwell calls interpretive validity. 7 Thinking in terms of our proposed metaphor, the composite-sketch artist needs to take into consideration what pieces of information provided by witnesses actually can mean to them. So, the witness may say that the crime perpetrator has big green eyes, but although this constitutes factual information, this is not enough in order to draw the actual eyes that would be recognized by the witness. The understood meaning of ‘big’ emerges on paper through the efforts of the sketch artist. It is necessary to take account some level of interpretive data, though just as long as it indeed helps the ‘reconstruction of reality.’

The next section will focus on the more practical details of developing an online survey as a qualitative descriptive endeavour for international comparative studies.

Methodological Issues

As Sandelowski 5 points out, qualitative description is a distributed residual category and, as such, it makes visible the “ porous lines between qualitative and quantitative description (…) and between the erosion and re-invention of method ” (p. 82). In other words, this category of inquiry may incorporate elements from quantitative and qualitative methodologies and, thus, serve as an innovative research tool. In the particular case of obtaining information from different national contexts, a qualitative description approach allows collection of data that will be analysed not only from the perspective of traditionally qualitative methodologies, but also from a more quantitative lens, making possible a quasi-statistical analysis of content, providing an overall summary of the findings.

For this type of research, we propose a combination of purposeful sampling strategies – here we rely on the classification system developed by Patton. 8 At the initial level of sampling, ie, the country-level, it is important to ensure comparability among the selected nations. This is extremely important for the validity of the quantitizing stage of data analysis, which should report a numerical summary of the data and observed patterns. For this level of sampling, hence, it is important to combine two strategies: homogeneity sampling and criterion sampling. For instance, we could select countries by the number of inhabitants or we could decide to include countries only above or below a given value of gross domestic product (GDP) per capita.

Subsequently, sampling may focus on using strategies to guarantee that there is meaningful variation within the sample and that politically important cases are not missing. For example, it may be appropriate to include cases with distinct institutional models, such as countries with parliamentary and presidential systems, or countries with centralized and decentralized responsibilities for a given public service.

Once the countries to be included in an international comparative study are determined, researchers need to identify individual informants. While an explicit sampling frame (eg, a directory of government department heads) may sometimes be available, strategies such as snowball sampling and convenience sampling may be required in order to make the study viable. Figure depicts this whole process of sampling within the context of using a survey as a qualitative descriptive tool to study public policies across countries.

Purposeful Sampling Strategies for Qualitative Description in International Comparative Studies.

Data Collection

As aforementioned, the main objective of data collection within this context is to obtain information about the institutional design of public policies. For this, researchers will rely on the reports of participants to reconstruct the ‘reality’ of each national scenario.

It is precisely at this point that the survey is the basic tool for collecting data. Respondents located in each national context would be invited to participate in an online qualitative survey. Researchers will have to circulate a structured survey instrument that allows participants to express their ideas on their own terms, but, at the same time, within a format that facilitates or guides the process of data analysis. Considering that qualitative description aims to record the fact, or in other words, to describe the things upon which most people would readily agree, the research team needs to develop an effective survey to engage participants in the description of the essential policy elements, without narrowing their possibilities of responses.

Data Analysis

For Sandelowski, 4 the analytic strategy of choice in qualitative description is Qualitative Content Analysis . This is a dynamic analytical tool intended to depict the informational content of the data. 9 Although similar to quantitative content analysis, this is different because the codes are commonly generated from the data (ie, derived inductively) in the course of the study. In addition, in qualitative content analysis, the quantitizing phase (the stage when the coded data elements can be numerically organized) allows the researcher to go beyond the mere summarization of the manifest data (the information readily retrievable from the raw dataset). Inferring associations, depicting tendencies and making predictions provide insight into the latent content of data obtained (ie, the type of information that requires a deeper analytic effort to be revealed).

In the context of international comparative studies, other data analysis strategies may also prove fruitful. For instance, the gaps between qualitative and quantitative analyses can be bridged using Ragin’s Qualitative Comparative Analysis. 10 This may be a valuable tool to investigate the generalizability of findings as well as the causal complexity of the variables encountered in the coded data.

By conducting qualitative descriptive studies with decision-makers, public servants and/or the local research community, it is possible for international comparative studies to use participants’ contextually-situated knowledge to depict the realities of different public policy contexts. The metaphor of the composite sketch artist can be a powerful device to guide methodological reflections, such as the notions of descriptive validity (the depiction of events as perceived by observers in their apparent sequence) and interpretive validity (the appropriate elicitation of the meanings attributed by the agents to those events). It illuminates the researcher’s role in presenting a picture of the topic investigated that most observers would likely agree with.

We argue that qualitative descriptive efforts are neither thick nor thin descriptions, in the sense used by Clifford Geertz. 11 By his account, a thick description is an instrument that unveils the web of significance allowing the researcher to differentiate among ‘the conspiratorial winking,’ ‘the involuntary twitch,’ ‘the parodic-fake winking,’ and ‘the rehearsing winking,’ whereas the thin description is the mere report of people rapidly contracting the eyelids. A qualitative description is something else. A fundamental or basic qualitative descriptive endeavour would seek to describe, for instance, who are the ones supposedly winking, how many they are, how many times they wink, which other gestures are being done, where these people are situated, who else is present, etc. Basic or fundamental qualitative descriptive studies thus cannot be properly understood within this Geertzian dualistic epistemological framework. Its virtue as a qualitative category of inquiry that stand per se (despite its residual nature) is only acknowledged by inscribing it within other framings. A qualitative description could be understood as a comprehensive description, one that seeks to provide a detailed description of the findings more likely to generate consensus among observers.

In the voluminous literature on qualitative research methods, there is no comprehensive study with a systematic reflection about the use of online qualitative surveys in international comparative studies on public policies. Therefore, our current endeavour may provide a valuable contribution to the research community as a potential approach available to researchers for investigating comparative topics in a methodologically rigorous manner.

Ethical issues

Not applicable.

Competing interests

Authors declare that they have no competing interests.

Authors’ contributions

BVS developed the paper’s central reasoning and crafted the first draft; NS provided extensive support in reviewing the text and offering fundamental contributions; CM supervised the whole work and provided meaningful contributions up to its final version.

Authors’ affiliations

1 School of Population and Public Health, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada. 2 Centre for Clinical Epidemiology & Evaluation, Vancouver Coastal Health Research Institute, University of British Columbia, Vancouver, BC, Canada.

Citation: Seixas BV, Smith N, Mitton C. The qualitative descriptive approach in international comparative studies: using online qualitative surveys. Int J Health Policy Manag. 2018;7(9):778–781. doi:10.15171/ijhpm.2017.142

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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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Clarifying Quantitative Research Designs

Chapter 8 Clarifying Quantitative Research Designs Chapter Overview Identifying Designs Used in Nursing Studies Descriptive Designs Typical Descriptive Design Comparative Descriptive Design Correlational Designs Descriptive Correlational Design Predictive Correlational Design Model Testing Design Understanding Concepts Important to Causality in Designs Multicausality Probability Bias Control Manipulation Examining the Validity of Studies Statistical Conclusion Validity Internal Validity Construct Validity External Validity Elements of Designs Examining Causality Examining Interventions in Nursing Studies Experimental and Control or Comparison Groups Quasi-Experimental Designs Pretest and Post-test Designs with Comparison Group Experimental Designs Classic Experimental Pretest and Post-test Designs with Experimental and Control Groups Post-test–Only with Control Group Design Randomized Controlled Trials Introduction to Mixed-Methods Approaches Key Concepts References Learning Outcomes After completing this chapter, you should be able to: 1.  Identify the nonexperimental designs (descriptive and correlational) and experimental designs (quasi-experimental and experimental) commonly used in nursing studies. 2.  Critically appraise descriptive and correlational designs in published studies. 3.  Describe the concepts important to examining causality—multicausality, probability, bias, control, and manipulation. 4.  Examine study designs for strengths and threats to statistical conclusion, and to internal, construct, and external validity. 5.  Describe the elements of designs that examine causality. 6.  Critically appraise the interventions implemented in studies. 7.  Critically appraise the quasi-experimental and experimental designs in published studies. 8.  Examine the quality of randomized controlled trials (RCTs) conducted in nursing. 9.  Discuss the implementation of mixed-methods approaches in nursing studies. Key Terms Bias, p. 223 Blinding, p. 241 Causality, p. 222 Comparative descriptive design, p. 216 Construct validity, p. 227 Control, p. 224 Control or comparison group, p. 230 Correlational design, p. 217 Cross-sectional design, p. 212 Descriptive correlational design, p. 218 Descriptive design, p. 212 Design validity, p. 211 Experimental designs, p. 237 Experimental or treatment group, p. 230 Experimenter expectancy, p. 228 External validity, p. 228 Internal validity, p. 226 Intervention, p. 230 Intervention fidelity, p. 230 Longitudinal design, p. 212 Low statistical power, p. 226 Manipulation, p. 224 Mixed-methods approaches, p. 243 Model testing design, p. 221 Multicausality, p. 223 Nonexperimental designs, p. 212 Predictive correlational design, p. 220 Probability, p. 223 Quasi-experimental design, p. 232 Randomized controlled trial (RCT), p. 241 Research design, p. 211 Statistical conclusion validity, p. 224 Study validity, p. 224 Threats to validity, p. 224 Triangulation, p. 244 Typical descriptive design, p. 214 A research design is a blueprint for conducting a study. Over the years, several quantitative designs have been developed for conducting descriptive, correlational, quasi-experimental, and experimental studies. Descriptive and correlational designs are focused on describing and examining relationships of variables in natural settings. Quasi-experimental and experimental designs were developed to examine causality, or the cause and effect relationships between interventions and outcomes. The designs focused on causality were developed to maximize control over factors that could interfere with or threaten the validity of the study design. The strengths of the design validity increase the probability that the study findings are an accurate reflection of reality. Well-designed studies, especially those focused on testing the effects of nursing interventions, are essential for generating sound research evidence for practice ( Brown, 2014 ; Craig & Smyth, 2012 ). Being able to identify the study design and evaluate design flaws that might threaten the validity of the findings is an important part of critically appraising studies. Therefore this chapter introduces you to the different types of quantitative study designs and provides an algorithm for determining whether a study design is descriptive, correlational, quasi-experimental, or experimental. Algorithms are also provided so that you can identify specific types of designs in published studies. A background is provided for understanding causality in research by defining the concepts of multicausality, probability, bias, control, and manipulation. The different types of validity—statistical conclusion validity, internal validity, construct validity, and external validity—are described. Guidelines are provided for critically appraising descriptive, correlational, quasi-experimental, and experimental designs in published studies. In addition, a flow diagram is provided to examine the quality of randomized controlled trials conducted in nursing. The chapter concludes with an introduction to mixed-method approaches, which include elements of quantitative designs and qualitative procedures in a study. Identifying Designs Used in Nursing Studies A variety of study designs are used in nursing research; the four most commonly used types are descriptive, correlational, quasi-experimental, and experimental. These designs are categorized in different ways in textbooks ( Fawcett & Garity, 2009 ; Hoe & Hoare, 2012 ; Kerlinger & Lee, 2000 ). Sometimes, descriptive and correlational designs are referred to as nonexperimental designs because the focus is on examining variables as they naturally occur in environments and not on the implementation of a treatment by the researcher. Some of these nonexperimental designs include a time element. Designs with a cross-sectional element involve data collection at one point in time. Cross-sectional design involves examining a group of subjects simultaneously in various stages of development, levels of education, severity of illness, or stages of recovery to describe changes in a phenomenon across stages. The assumption is that the stages are part of a process that will progress over time. Selecting subjects at various points in the process provides important information about the totality of the process, even though the same subjects are not monitored throughout the entire process ( Grove, Burns, & Gray, 2013 ). Longitudinal design involves collecting data from the same subjects at different points in time and might also be referred to as repeated measures. Repeated measures might be included in descriptive, correlational, quasi-experimental, or experimental study designs. Quasi-experimental and experimental studies are designed to examine causality or the cause and effect relationship between a researcher-implemented treatment and selected study outcome. The designs for these studies are sometime referred to as experimental because the focus is on examining the differences in dependent variables thought to be caused by independent variables or treatments. For example, the researcher-implemented treatment might be a home monitoring program for patients initially diagnosed with hypertension, and the dependent or outcome variable could be blood pressure measured at 1 week, 1 month, and 6 months. This chapter introduces you to selected experimental designs and provides examples of these designs from published nursing studies. Details on other study designs can be found in a variety of methodology sources ( Campbell & Stanley, 1963 ; Creswell, 2014 ; Grove et al., 2013 ; Kerlinger & Lee, 2000 ; Shadish, Cook, & Campbell, 2002 ). The algorithm shown in Figure 8-1 may be used to determine the type of design (descriptive, correlational, quasi-experimental, and experimental) used in a published study. This algorithm includes a series of yes or no responses to specific questions about the design. The algorithm starts with the question, “Is there a treatment?” The answer leads to the next question, with the four types of designs being identified in the algorithm. Sometimes, researchers combine elements of different designs to accomplish their study purpose. For example, researchers might conduct a cross-sectional, descriptive, correlational study to examine the relationship of body mass index (BMI) to blood lipid levels in early adolescence (ages 13 to 16 years) and late adolescence (ages 17 to 19 years). It is important that researchers clearly identify the specific design they are using in their research report. Fig 8-1 Algorithm for determining the type of study design. Descriptive Designs Descriptive studies are designed to gain more information about characteristics in a particular field of study. The purpose of these studies is to provide a picture of a situation as it naturally happens. A descriptive design may be used to develop theories, identify problems with current practice, make judgments about practice, or identify trends of illnesses, illness prevention, and health promotion in selected groups. No manipulation of variables is involved in a descriptive design. Protection against bias in a descriptive design is achieved through (1) conceptual and operational definitions of variables, (2) sample selection and size, (3) valid and reliable instruments, and (4) data collection procedures that might partially control the environment. Descriptive studies differ in level of complexity. Some contain only two variables; others may include multiple variables that are studied over time. You can use the algorithm shown in Figure 8-2 to determine the type of descriptive design used in a published study. Typical descriptive and comparative descriptive designs are discussed in this chapter. Grove and colleagues (2013) have provided details about additional descriptive designs. Fig 8-2 Algorithm for determining the type of descriptive design. Typical Descriptive Design A typical descriptive design is used to examine variables in a single sample ( Figure 8-3 ). This descriptive design includes identifying the variables within a phenomenon of interest, measuring these variables, and describing them. The description of the variables leads to an interpretation of the theoretical meaning of the findings and the development of possible relationships or hypotheses that might guide future correlational or quasi-experimental studies. Fig 8-3 Typical descriptive design. Critical Appraisal Guidelines Descriptive and Correlational Designs When critically appraising the designs of descriptive and correlational studies, you need to address the following questions: 1.  Is the study design descriptive or correlational? Review the algorithm in Figure 8-1 to determine the type of study design. 2.  If the study design is descriptive, use the algorithm in Figure 8-2 to identify the specific type of descriptive design implemented in the study. 3.  If the study design is correlational, use the algorithm in Figure 8-5 to identify the specific type of correlational design implemented in the study. 4.  Does the study design address the study purpose and/or objectives or questions? 5.  Was the sample appropriate for the study? 6.  Were the study variables measured with quality measurement methods? Research Example Typical Descriptive Design Research Study Excerpt Maloni, Przeworski, and Damato (2013) studied women with postpartum depression (PPD) after pregnancy complications for the purpose of describing their barriers to treatment for PPD, use of online resources for assistance with PPD, and preference for Internet treatment for PPD. This study included a typical descriptive design; key aspects of this study’s design are presented in the following excerpt. “Methods An exploratory descriptive survey design was used to obtain a convenience sample of women who self-report feelings of PPD across the past week [sample size n  = 53]. Inclusion criteria were women between 2 weeks and 6 months postpartum who had been hospitalized for pregnancy complications. Women were excluded if they had a score of < 6 on the Edinburgh Postnatal Depression Scale (EPDS)…. EPDS is a widely used screening instrument to detect postpartum depression…. In addition, a series of 26 descriptive questions assessed women’s barriers to PPD treatment, whether they sought information about depression after birth from any sources and their information seeking about PPD from the Internet, how often they sought the information, and whether the information was helpful. Questions were developed from review of the literature.… Content validity was established by a panel of four experts.… The survey was posted using a university-protected website using standardized software for surveys.” ( Maloni et al., 2013, pp. 91-92 ) Critical Appraisal Maloni and associates (2013) clearly identified their study design as descriptive and indicated that the data were collected using an online survey. This type of design was appropriate to address the study purpose. The sample section was strengthened by using the EPDS to identify women with PPD and using the sample criteria to ensure that the women had been hospitalized for pregnancy complications. However, the sample size of 53 was small for a descriptive study. The 26-item questionnaire had content validity and was consistently implemented online using standard survey software. This typical descriptive design was implemented in a way to provide quality study findings. Implications for Practice Maloni and co-workers (2013) noted that of the 53 women who were surveyed because they reported PPD, 70% had major depression. The common barriers that prevented them from getting treatment included time and the stigma of PPD diagnosis. Over 90% of the women did use the Internet as a resource to learn about coping with PPD and expressed an interest in a web-based PPD treatment. Comparative Descriptive Design A comparative descriptive design is used to describe variables and examine differences in variables in two or more groups that occur naturally in a setting. A comparative descriptive design compares descriptive data obtained from different groups, which might have been formed using gender, age, educational level, medical diagnosis, or severity of illness. Figure 8-4 provides a diagram of this design’s structure. Fig 8-4 Comparative descriptive design. Research Example Comparative Descriptive Design Research Study Excerpt Buet and colleagues (2013) conducted a comparative descriptive study to describe and determine differences in the hand hygiene (HH) opportunities and adherence of clinical (e.g., nurses and physicians) and nonclinical (e.g., teachers and parents) caregivers for patients in pediatric extended-care facilities (ECFs). The following study excerpt includes key elements of this comparative descriptive design: “Eight children across four pediatric ECFs were observed for a cumulative 128 hours, and all caregiver HH opportunities were characterized by the World Health Organization [WHO] ‘5 Moments for HH.’… A convenience sample of two children from each site ( n  = 8) was observed.… Four observers participated in two hours of didactic training and two hours of monitored practice observations at one of the four study sites to ensure consistent documentation and interpretation of observations. Observers learned how to accurately record HH opportunities and HH adherence using the WHO ‘5 Moments of HH’ data acquisition tool, discussed below. Throughout the study, regular debriefings were also held to review and discuss data recording.…The World Health Organization ( WHO, 2009 ) ‘5 Moments for HH’ define points of contact when healthcare workers should perform HH: ‘before touching a patient, before clean/aseptic procedures, after body fluid exposure/risk, after touching a patient, and after touching patient surroundings…. During approximately 128 hours of observation, 865 HH opportunities were observed.” ( Buet et al., 2013, pp. 72-73 ) Critical Appraisal Buet and associates (2013) clearly described the aspects of their study design but did not identify the specific type of design used in their study. The design was comparative descriptive because the HH opportunities and adherence for clinical and nonclinical caregivers were described and compared. The study included 128 hours of observation (16 hours per child) of 865 HH opportunities in four different ECF settings. Thus the sampling process was strong and seemed focused on accomplishing the study purpose. The data collectors were well trained and monitored to ensure consistent observation and recording of data. HH was measured using an observational tool based on international standards ( WHO, 2009 ) for HH. Implications for Practice Buet and co-workers (2013) found that the HH of the clinical caregivers was significantly higher than the nonclinical caregivers. However, the overall HH adherence for the clinical caregivers was only 43%. The low HH adherence suggested increased potential for transmission of infections among children in ECFs. Additional HH education is needed for clinical and nonclinical caregivers of these children to prevent future adverse events. Quality and Safety Education for Nurses ( QSEN, 2013 ) implications from this study encourage nurses to follow evidence-based practice (EBP) guidelines in adhering to HH measures to ensure safe care of their patients and reduce their risk of potentially life-threatening infections ( Sherwood & Barnsteiner, 2012 ). Correlational Designs The purpose of a correlational design is to examine relationships between or among two or more variables in a single group in a study. This examination can occur at any of several levels— descriptive correlational, in which the researcher can seek to describe a relationship, predictive correlational, in which the researcher can predict relationships among variables, or the model testing design, in which all the relationships proposed by a theory are tested simultaneously. In correlational designs, a large range in the variable scores is necessary to determine the existence of a relationship. Therefore the sample should reflect the full range of scores possible on the variables being measured. Some subjects should have very high scores and others very low scores, and the scores of the rest should be distributed throughout the possible range. Because of the need for a wide variation on scores, correlational studies generally require large sample sizes. Subjects are not divided into groups, because group differences are not examined. To determine the type of correlational design used in a published study, use the algorithm shown in Figure 8-5 . More details on correlational designs referred to in this algorithm are available from other sources ( Grove et al., 2013 ; Kerlinger & Lee, 2000 ). Fig 8-5 Algorithm for determining the type of correlational design. Descriptive Correlational Design The purpose of a descriptive correlational design is to describe variables and examine relationships among these variables. Using this design facilitates the identification of many interrelationships in a situation ( Figure 8-6 ). The study may examine variables in a situation that has already occurred or is currently occurring. Researchers make no attempt to control or manipulate the situation. As with descriptive studies, variables must be clearly identified and defined conceptually and operationally (see Chapter 5 ). Fig 8-6 Descriptive correlational design. Research Example Descriptive Correlational Design Research Study Excerpt Burns, Murrock, and Graor (2012) conducted a correlational study to examine the relationship between BMI and injury severity in adolescent males attending a National Boy Scout Jamboree. The key elements of this descriptive correlational design are presented in the following study excerpt. “Design This study used a descriptive, correlational design to examine the relationship between obesity and injury severity.… The convenience sample consisted of the 611 adolescent males, aged 11-17 years, who received medical attention for an injury at one of eight participating medical facilities. Exclusion criteria were adolescent males presenting with medical complaints unrelated to an injury (e.g., sore throat, dehydration, insect bite) and those who were classified as ‘special needs’ participants because of the disability affecting their mobility or requiring the use of an assistive device.… There were 20 medical facilities located throughout the 2010 National Boy Scout Jamboree. Each facility was equipped to manage both medical complaints and injuries.…” ( Burns et al., 2012, pp. 509–510 ) “Measures Past medical history, weight (in pounds) and height (in inches) were obtained from the HMR [health and medical record]. BMI [body mass index] and gender-specific BMI percentage were calculated electronically using online calculators from the Centers for Disease Control and Prevention and height and weight data. The BMI value was plotted on the CDC’s gender-specific BMI-for-age growth chart to obtain a percentile ranking (BMI-P)…. BMI-P defines four weight status categories: less than 5% is considered underweight, 5% to less than 85% is categorized healthy weight, 85% to less than 95% is the overweight category, and 95% or greater is categorized as obese. Age was measured in years and was self-reported. Severity of injury was measured using the ESI [Emergency Severity Index] Version 4. This five-level triage rating scale was developed by the Agency for Healthcare Research and Quality and provides rapid, reproducible, clinically relevant stratification of patients into levels based on acuity and resource needs.… Training sessions were held for each medical facility to educate staff on the project, process, data collection techniques, and injury severity scoring methods.… All BMI and BMI-P values were recalculated to verify accuracy. To assess interrater reliability for injury severity scoring, ESI scores reported were compared with the primary researcher’s scores. When discrepancies were found, the primary researcher reviewed the treatment record to determine the most accurate score.” ( Burns et al., 2012, p. 510 ) Critical Appraisal Descriptive Correlational Design Burns and colleagues (2012) clearly identified their study design in their research report. The sampling method was a nonrandom sample of convenience that is commonly used in descriptive and correlational studies. Nonrandom sampling methods decrease the sample’s representativeness of the population; however, the sample size was large and included 20 medical facilities at a national event. The exclusion sampling criteria ensured that the subjects selected were most appropriate to address the study purpose. The adolescents’ height and weight were obtained from their medical records but the researchers did not indicate if these were reported or measured by the healthcare professionals. Self-reported height and weight for subjects could decrease the accuracy of the BMI and BMI-P calculated in a study. The BMI-P and severity injury scores were obtained using reliable and valid measurement methods, and the data from the medical facilities were checked for accuracy. The design of this study seemed strong and the knowledge generated provides a basis for future research. Implications for Practice Burns and associates (2012) found a significant relationship between BMI-P and injury severity. They noted that overweight/obese adolescents may have increased risks of serious injuries. Additional research is needed to examine the relationship of BMI to injury risk and to identify ways to prevent injuries in these adolescents. The findings from this study also emphasize the importance of healthy weight in adolescents to prevent health problems. QSEN (2013) implications are that evidence-based knowledge about the relationship between obesity and severity of injury provides nurses and students with information for educating adolescents to promote their health. Predictive Correlational Design The purpose of a predictive correlational design is to predict the value of one variable based on the values obtained for another variable or variables. Prediction is one approach to examining causal relationships between variables. Because causal phenomena are being examined, the terms dependent and independent are used to describe the variables. The variable to be predicted is classified as the dependent variable, and all other variables are independent or predictor variables. A predictive correlational design study attempts to predict the level of a dependent variable from the measured values of the independent variables. For example, the dependent variable of medication adherence could be predicted using the independent variables of age, number of medications, and medication knowledge of patients with congestive heart failure. The independent variables that are most effective in prediction are highly correlated with the dependent variable but are not highly correlated with other independent variables used in the study. The predictive correlational design structure is presented in Figure 8-7 . Predictive correlational designs require the development of a theory-based mathematical hypothesis proposing variables expected to predict the dependent variable effectively. Researchers then use regression analysis to test the hypothesis (see Chapter 11 ). Fig 8-7 Predictive correlational design. Research Example Predictive Correlational Design Research Study Excerpt Coyle (2012) used a predictive correlational design to determine if depressive symptoms were predictive of self-care behaviors in adults who had suffered a myocardial infarction (MI). The following study excerpt presents key elements of this design. “Design, Setting, and Sample A descriptive correlational design examined the relationship between the independent variable of depressive symptoms [agitation and loss of energy] and the dependent variable of self-care. Data were collected from 62 patients in one hospital, who were recovering from an MI in the metropolitan Washington, areaA….” ( Coyle, 2012, p. 128 ) Measures “Beck Depression Inventory II Depressive symptoms were measured using the BDI-II [Beck Depression Inventory II], a well-validated, 21-item scale designed to measure self-reported depressive symptomatology.… Internal-consistency estimates coefficient alpha of the total scores were .92 for psychiatric outpatients and .93 for college students. Construct validity was .93 (p < .001) when correlated with the BDI-I. In this study, the BDI-II Cronbach’s alpha was .68 at baseline.” ( Coyle, 2012, p. 128 ) “Health Behavior Scale Self-care behaviors after an MI were measured by the Health Behavior Scale (HBS), developed specifically for measuring the extent to which persons with cardiac disease perform prescribed self-care behaviors.… This self-report, a 20-item instrument, assesses the degree to which patients perform five types of prescribed self-care (following diet, limiting smoking, performing activities, taking medications, and changing responses to stressful situations).… Cronbach’s alphas for different self-care behaviors ranged from .82 to .95. In this study, reliability was measured by Cronbach’s alpha and was .62 at 2 weeks and .71 at 30 days….Prior to hospital discharge, the Medical and Demographic Characteristics Questionnaire and BDI-II were administered by the researcher.… At 2 weeks and at 30 days after hospital discharge, participants were contacted by telephone to determine responses to the HBS.” ( Coyle, 2012, pp. 128-129 ) Critical Appraisal Coyle (2012) might have identified her study design more clearly as predictive correlational but did clearly identify the dependent variable as self-care and the independent variables as depressive symptoms. The design also included the longitudinal measurement of self-care with the HBS at 2 weeks and 30 days. The design was appropriate to accomplish the study purpose. The sample of 62 subjects was adequate because the study findings indicated significant results. The BDI-II has documented reliability (Cronbach’s alphas > 0.7) and validity from previous studies, but the reliability of .68 was low in this study. Reliability indicates how consistently the scale measured depression and, in this study, it had 68% consistency and 32% error (1.00 − .68 = .32 × 100% = 32%; see Chapter 10 ). HBS had strong reliability in previous studies but the validity of the scale was not addressed. The reliability of HBS was limited at 2 weeks (62% reliable and 38% error) but acceptable at 30 days (71% reliable and 29% error). This study has a strong design with more strengths than weaknesses, and the findings are probably an accurate reflection of reality. The study needs to be replicated with stronger measurement methods and a larger sample. Implications for Practice Coyle (2012) found that depressive symptoms of agitation and loss of energy were significantly predictive of self-care performance in patients with an MI at 30 days post–hospital discharge. Coyle recommended screening post-MI patients for depressive symptoms so that their symptoms might be managed before they were discharged. Further research is recommended to examine depression and self-care behaviors after hospital discharge to identify and treat potential problems. Model Testing Design Some studies are designed specifically to test the accuracy of a hypothesized causal model (see Chapter 7 for content on middle range theory). The model testing design requires that all concepts relevant to the model be measured and the relationships among these concepts examined. A large heterogeneous sample is required. Correlational analyses are conducted to determine the relationships among the model concepts, and the results are presented in the framework model for the study. This type of design is very complex; this text provides only an introduction to a model testing design implemented by Battistelli, Portoghese, Galletta, and Pohl (2013) . Research Example Model Testing Design Research Study Battistelli and co-workers (2013) developed and tested a theoretical model to examine turnover intentions of nurses working in hospitals. The concepts of work-family conflict, job satisfaction, community embeddedness, and organizational affective commitment were identified as predictive of nurse turnover intention. The researchers collected data on these concepts using a sample of 440 nurses from a public hospital. The analysis of study data identified significant relationships ( p  < 0.05) among all concepts in the model. The results of this study are presented in Figure 8-8 and indicate the importance of these concepts in predicting nurse turnover intention. Fig 8-8 Results of the structural equation modeling analysis of the hypothesized model of turnover intention on the cross-validation sample ( n  = 440, standardized path loadings, p  < 0.05, two-tailed). (From Battistelli, A., Portoghese, I., Galletta, M., & Pohl, S. [2012]. Beyond the tradition: Test of an integrative conceptual model on nurse turnover. International Nursing Review, 60 (1), p. 109.) Understanding Concepts Important to Causality in Designs Quasi-experimental and experimental designs were developed to examine causality or the effect of an intervention on selected outcomes. Causality basically says that things have causes, and causes lead to effects. In a critical appraisal, you need to determine whether the purpose of the study is to examine causality, examine relationships among variables (correlational designs), or describe variables (descriptive designs). You may be able to determine whether the purpose of a study is to examine causality by reading the purpose statement and propositions within the framework (see Chapter 7 ). For example, the purpose of a causal study may be to examine the effect of a specific, preoperative, early ambulation educational program on length of hospital stay. The proposition may state that preoperative teaching results in shorter hospitalizations. However, the preoperative early ambulation educational program is not the only factor affecting length of hospital stay. Other important factors include the diagnosis, type of surgery, patient’s age, physical condition of the patient prior to surgery, and complications that occurred after surgery. Researchers usually design quasi-experimental and experimental studies to examine causality or the effect of an intervention (independent variable) on a selected outcome (dependent variable), using a design that controls extraneous variables. Critically appraising studies designed to examine causality requires an understanding of such concepts as multicausality, probability, bias, control, and manipulation. Multicausality Very few phenomena in nursing can be clearly linked to a single cause and a single effect. A number of interrelating variables can be involved in producing a particular effect. Therefore studies developed from a multicausal perspective will include more variables than those using a strict causal orientation. The presence of multiple causes for an effect is referred to as multicausality . For example, patient diagnosis, age, presurgical condition, and complications after surgery will be involved in causing the length of hospital stay. Because of the complexity of causal relationships, a theory is unlikely to identify every element involved in causing a particular outcome. However, the greater the proportion of causal factors that can be identified and examined or controlled in a single study, the clearer the understanding will be of the overall phenomenon. This greater understanding is expected to increase the ability to predict and control the effects of study interventions.

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Characteristics of a Comparative Research Design

Hannah richardson, 28 jun 2018.

Comparative research essentially compares two groups in an attempt to draw a conclusion about them. Researchers attempt to identify and analyze similarities and differences between groups, and these studies are most often cross-national, comparing two separate people groups. Comparative studies can be used to increase understanding between cultures and societies and create a foundation for compromise and collaboration. These studies contain both quantitative and qualitative research methods.

Explore this article

• Comparative Quantitative
• Comparative Qualitative
• When to Use It
• When Not to Use It

1 Comparative Quantitative

Quantitative, or experimental, research is characterized by the manipulation of an independent variable to measure and explain its influence on a dependent variable. Because comparative research studies analyze two different groups -- which may have very different social contexts -- it is difficult to establish the parameters of research. Such studies might seek to compare, for example, large amounts of demographic or employment data from different nations that define or measure relevant research elements differently.

However, the methods for statistical analysis of data inherent in quantitative research are still helpful in establishing correlations in comparative studies. Also, the need for a specific research question in quantitative research helps comparative researchers narrow down and establish a more specific comparative research question.

2 Comparative Qualitative

Qualitative, or nonexperimental, is characterized by observation and recording outcomes without manipulation. In comparative research, data are collected primarily by observation, and the goal is to determine similarities and differences that are related to the particular situation or environment of the two groups. These similarities and differences are identified through qualitative observation methods. Additionally, some researchers have favored designing comparative studies around a variety of case studies in which individuals are observed and behaviors are recorded. The results of each case are then compared across people groups.

3 When to Use It

Comparative research studies should be used when comparing two people groups, often cross-nationally. These studies analyze the similarities and differences between these two groups in an attempt to better understand both groups. Comparisons lead to new insights and better understanding of all participants involved. These studies also require collaboration, strong teams, advanced technologies and access to international databases, making them more expensive. Use comparative research design when the necessary funding and resources are available.

4 When Not to Use It

Do not use comparative research design with little funding, limited access to necessary technology and few team members. Because of the larger scale of these studies, they should be conducted only if adequate population samples are available. Additionally, data within these studies require extensive measurement analysis; if the necessary organizational and technological resources are not available, a comparative study should not be used. Do not use a comparative design if data are not able to be measured accurately and analyzed with fidelity and validity.

• 1 San Jose State University: Selected Issues in Study Design
• 2 University of Surrey: Social Research Update 13: Comparative Research Methods

About the Author

Hannah Richardson has a Master's degree in Special Education from Vanderbilt University and a Bacheor of Arts in English. She has been a writer since 2004 and wrote regularly for the sports and features sections of "The Technician" newspaper, as well as "Coastwach" magazine. Richardson also served as the co-editor-in-chief of "Windhover," an award-winning literary and arts magazine. She is currently teaching at a middle school.

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