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Descriptive Research Design | Definition, Methods & Examples

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

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

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

Table of contents

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

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

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

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

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

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

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

Observations

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

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

Case studies

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

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

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An Overview of Descriptive Studies in Relation to a General Design Research Methodology

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• L. T. M. Blessing ,
• A. Chakrabarti &
• K. M. Wallace  

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This paper describes a general design research methodology that aims at a more rigorous approach to design research by piecing together the various existing design research areas and by encouraging collaboration with other disciplines. It discusses the challenges involved in doing design research, such as the large number of factors that influence design, and highlights the importance of descriptive studies. The papers presented in this book are used throughout as examples, and set in the context of the proposed methodology in the Conclusion and Outlook at the end of this book. These papers and others revealed some of the key issues that need addressing: the formulation of criteria for success, the use of results from descriptive studies in the development of design methods and tools, and the validation of such methods and tools against these results.

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Blessing, L.T.M., Chakrabarti, A., Wallace, K.M. (1998). An Overview of Descriptive Studies in Relation to a General Design Research Methodology. In: Frankenberger, E., Birkhofer, H., Badke-Schaub, P. (eds) Designers. Springer, London. https://doi.org/10.1007/978-1-4471-1268-6_4

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Home » Descriptive Research Design – Types, Methods and Examples

Descriptive Research Design – Types, Methods and Examples

Table of Contents

Descriptive Research Design

Definition:

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

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

Types of Descriptive Research Design

Types of Descriptive Research Design are as follows:

Cross-sectional Study

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

Longitudinal Study

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

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

Survey Research

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

Observational Research

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

Correlational Research

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

Data Analysis Methods

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

Descriptive Statistics

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

Cross-tabulation

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

Content Analysis

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

Qualitative Coding

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

Visualization

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

Comparative Analysis

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

Applications of Descriptive Research Design

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

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

Descriptive Research Design Examples

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

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

How to Conduct Descriptive Research Design

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

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

When to Use Descriptive Research Design

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

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

Purpose of Descriptive Research Design

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

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

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

Characteristics of Descriptive Research Design

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

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

Advantages of Descriptive Research Design

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

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

Limitation of Descriptive Research Design

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

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

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An overview of the qualitative descriptive design within nursing research

Louise doyle.

Associate Professor in Mental Health Nursing, School of Nursing and Midwifery, Trinity College Dublin, Ireland

Catherine McCabe

Associate Professor in General Nursing, School of Nursing and Midwifery, Trinity College Dublin, Ireland

Brian Keogh

Assistant Professor in Mental Health Nursing, School of Nursing and Midwifery, Trinity College Dublin, Ireland

Annemarie Brady

Chair of Nursing and Chronic Illness, School of Nursing and Midwifery, Trinity College Dublin, Ireland

Qualitative descriptive designs are common in nursing and healthcare research due to their inherent simplicity, flexibility and utility in diverse healthcare contexts. However, the application of descriptive research is sometimes critiqued in terms of scientific rigor. Inconsistency in decision making within the research process coupled with a lack of transparency has created issues of credibility for this type of approach. It can be difficult to clearly differentiate what constitutes a descriptive research design from the range of other methodologies at the disposal of qualitative researchers.

This paper provides an overview of qualitative descriptive research, orientates to the underlying philosophical perspectives and key characteristics that define this approach and identifies the implications for healthcare practice and policy.

Methods and results

Using real-world examples from healthcare research, the paper provides insight to the practical application of descriptive research at all stages of the design process and identifies the critical elements that should be explicit when applying this approach.

Conclusions

By adding to the existing knowledge base, this paper enhances the information available to researchers who wish to use the qualitative descriptive approach, influencing the standard of how this approach is employed in healthcare research.

Introduction

Qualitative descriptive approaches to nursing and healthcare research provide a broad insight into particular phenomena and can be used in a variety of ways including as a standalone research design, as a precursor to larger qualitative studies and commonly as the qualitative component in mixed-methods studies. Despite the widespread use of descriptive approaches within nursing research, there is limited methodological guidance about this type of design in research texts or papers. The lack of adequate representation in research texts has at times resulted in novice researchers using other more complex qualitative designs including grounded theory or phenomenology without meeting the requirements of these approaches ( Lambert and Lambert, 2012 ), or having an appropriate rationale for use of these approaches. This suggests there is a need to have more discussion about how and why descriptive approaches to qualitative research are used. This serves to not only provide information and guidance for researchers, but to ensure acceptable standards in how this approach is applied in healthcare research.

Rationale for qualitative descriptive research

The selection of an appropriate approach to answer research questions is one of the most important stages of the research process; consequently, there is a requirement that researchers can clearly articulate and defend their selection. Those who wish to undertake qualitative research have a range of approaches available to them including grounded theory, phenomenology and ethnography. However, these designs may not be the most suitable for studies that do not require a deeply theoretical context and aim to stay close to and describe participants’ experiences. The most frequently proposed rationale for the use of a descriptive approach to is to provide straightforward descriptions of experiences and perceptions ( Sandelowski, 2010 ), particularly in areas where little is known about the topic under investigation. A qualitative descriptive design may be deemed most appropriate as it recognises the subjective nature of the problem, the different experiences participants have and will present the findings in a way that directly reflects or closely resembles the terminology used in the initial research question ( Bradshaw et al., 2017 ). This is particularly relevant in nursing and healthcare research, which is commonly concerned with how patients experience illness and associated healthcare interventions. The utilisation of a qualitative descriptive approach is often encouraged in Master’s level nurse education programmes as it enables novice clinical nurse researchers explore important healthcare questions that have direct implications and impact for their specific healthcare setting (Colorafi and Evans, 2016). As a Master’s level project is often the first piece of primary research undertaken by nurses, the use of a qualitative descriptive design provides an excellent method to address important clinical issues where the focus is not on increasing theoretical or conceptual understanding, but rather contributing to change and quality improvement in the practice setting ( Chafe, 2017 ).

This design is also frequently used within mixed-methods studies where qualitative data can explain quantitative findings in explanatory studies, be used for questionnaire development in exploratory studies and validate and corroborate findings in convergent studies ( Doyle et al., 2016 ). There has also been an increase in the use of qualitative descriptive research embedded in large-scale healthcare intervention studies, which can serve a number of purposes including identifying participants’ perceptions of why an intervention worked or, just as importantly, did not work and how the intervention might be improved ( Doyle et al., 2016 ). Using qualitative descriptive research in this manner can help to make the findings of intervention studies more clinically meaningful.

Philosophical and theoretical influences

Qualitative descriptive research generates data that describe the ‘who, what, and where of events or experiences’ from a subjective perspective ( Kim et al., 2017 , p. 23). From a philosophical perspective, this approach to research is best aligned with constructionism and critical theories that use interpretative and naturalistic methods ( Lincoln et al., 2017 ). These philosophical perspectives represent the view that reality exists within various contexts that are dynamic and perceived differently depending on the subject, therefore, reality is multiple and subjective ( Lincoln et al., 2017 ). In qualitative descriptive research, this translates into researchers being concerned with understanding the individual human experience in its unique context. This type of inquiry requires flexible research processes that are inductive and dynamic but do not transform the data beyond recognition from the phenomenon being studied ( Ormston et al., 2014 ; Sandelwoski 2010). Descriptive qualitative research has also been aligned with pragmatism ( Neergaard et al., 2009 ) where decisions are made about how the research should be conducted based on the aims or objectives and context of the study ( Ormston et al., 2014 ). The pragmatist researcher is not aligned to one particular view of knowledge generation or one particular methodology. Instead they look to the concepts or phenomena being studied to guide decision making in the research process, facilitating the selection of the most appropriate methods to answer the research question ( Bishop, 2015 ).

Perhaps linked to the practical application of pragmatism to research, that is, applying the best methods to answer the research question, is the classification of qualitative descriptive research by Sandelowski ( 2010 , p. 82) into a ‘distributed residual category’. This recognises and incorporates uncertainty about the phenomena being studied and the research methods used to study them. For researchers, it permits the use of one or more different types of inquiry, which is essential when acknowledging and exploring different realities and subjective experiences in relation to phenomena ( Long et al., 2018 ). Clarity, in terms of the rationale for the phenomenon being studied and the methods used by the researcher, emerges from the qualitative descriptive approach because the data gathered continue to remain close to the phenomenon throughout the study ( Sandelowski, 2010 ). For this to happen a flexible approach is required and this is evident in the practice of ‘borrowing’ elements of other qualitative methodologies such as grounded theory, phenomenology and ethnography ( Vaismoradi et al., 2013 ).

Regarded as a positive aspect by many researchers who are interested in studying human nature and phenomenon, others believe this flexibility leads to inconsistency across studies and in some cases complacency by researchers. This can result in vague or unexplained decision making around the research process and subsequent lack of credibility. Accordingly, nurse researchers need to be reflexive, that is, clear about their role and position in terms of the phenomena being studied, the context, the theoretical framework and all decision-making processes used in a qualitative descriptive study. This adds credibility to both the study and qualitative descriptive research.

Methods in qualitative descriptive research

As with any research study, the application of descriptive methods will emerge in response to the aims and objectives, which will influence the sampling, data collection and analysis phases of the study.

Most qualitative research aligns itself with non-probability sampling and descriptive research is no different. Descriptive research generally uses purposive sampling and a range of purposive sampling techniques have been described ( Palinkas et al., 2015 ). Many researchers use a combination of approaches such as convenience, opportunistic or snowball sampling as part of the sampling framework, which is determined by the desired sample and the phenomena being studied.

Purposive sampling refers to selecting research participants that can speak to the research aims and who have knowledge and experience of the phenomenon under scrutiny ( Ritchie et al., 2014 ). When purposive sampling is used in a study it delimits and narrows the study population; however, researchers need to remember that other characteristics of the sample will also affect the population, such as the location of the researcher and their flexibility to recruit participants from beyond their base. In addition, the heterogeneity of the population will need to be considered and how this might influence sampling and subsequent data collection and analysis ( Palinkas et al ., 2015 ). Take, for example, conducting research on the experience of caring for people with Alzheimer’s disease (AD). For the most part AD is a condition that affects older people and experiences of participants caring for older people will ultimately dominate the sample. However, AD also affects younger people and how this will impact on sampling needs to be considered before recruitment as both groups will have very different experiences, although there will be overlap. Teddlie and Fu (2007) suggest that although some purposive sampling techniques generate representative cases, most result in describing contrasting cases, which they argue are at the heart of qualitative analysis. To achieve this, Sandelowski (2010) suggests that maximum variation sampling is particularly useful in qualitative descriptive research, which may acknowledge the range of experiences that exist especially in healthcare research. Palinkas et al . (2015) describe maximum variation sampling as identifying shared patterns that emerge from heterogeneity. In other words, researchers attempt to include a wide range of participants and experiences when collecting data. This may be more difficult to achieve in areas where little is known about the substantive area and may depend on the researcher’s knowledge and immersion within the subject area.

Sample size will also need to be considered and although small sample sizes are common in qualitative descriptive research, researchers need to be careful they have enough data collected to meet the study aims ( Ritchie et al., 2014 ). Pre-determining the sample size prior to data collection may stifle the analytic process, resulting in too much or too little data. Traditionally, the gold standard for sample size in qualitative research is data saturation, which differs depending on the research design and the size of the population ( Fusch and Ness, 2015 ). Data saturation is reached ‘when there is enough information to replicate the study, when the ability to obtain additional new information has been attained, and when further coding is no longer feasible’ ( Fusch and Ness, 2015 , p. 1408). However, some argue that although saturation is often reported, it is rarely demonstrated in qualitative descriptive research reports ( Caelli et al., 2003 ; Malterud et al., 2016 ). If data saturation is used to determine sample size, it is suggested that greater emphasis be placed on demonstrating how saturation was reached and at what level to provide more credibility to sample sizes ( Caelli et al., 2003 ). Sample size calculation should be an estimate until saturation has been achieved through the concurrent processes of data collection and analysis. Where saturation has not been achieved, or where sample size has been predetermined for resource reasons, this should be clearly acknowledged. However, there is also a movement away from the reliance on data saturation as a measure of sample size in qualitative research ( Malterud et al., 2016 ). O’Reilly and Parker (2012) question the appropriateness of the rigid application of saturation as a sample size measure arguing that outside of Grounded Theory, its use is inconsistent and at times questionable. Malterud et al. (2016) focus instead on the concept of ‘information power’ to determine sample size. Here, they suggest sample size is determined by the amount of information the sample holds relevant to the actual study rather than the number of participants ( Malterud et al., 2016 ). Some guidance on specific sample size depending on research design has been provided in the literature; however, these are sometimes conflicting and in some cases lack evidence to support their claims ( Guest et al., 2006 ). This is further complicated by the range of qualitative designs and data collection approaches available.

Data collection

Data collection methods in qualitative descriptive research are diverse and aim to discover the who, what and where of phenomena ( Sandelowski, 2000 ). Although semi-structured individual face-to-face interviews are the most commonly used data collection approaches ( Kim et al ., 2017 ), focus groups, telephone interviews and online approaches are also used.

Focus groups involve people with similar characteristics coming together in a relaxed and permissive environment to share their thoughts, experiences and insights ( Krueger and Casey, 2009 ). Participants share their own views and experiences, but also listen to and reflect on the experiences of other group members. It is this synergistic process of interacting with other group members that refines individuals’ viewpoints to a deeper and more considered level and produces data and insights that would not be accessible without the interaction found in a group (Finch et al., 2014). Telephone interviews and online approaches are gaining more traction as they offer greater flexibility and reduced costs for researchers and ease of access for participants. In addition, they may help to achieve maximum variation sampling or examine experiences from a national or international perspective. Face-to-face interviews are often perceived as more appropriate than telephone interviews; however, this assumption has been challenged as evidence to support the use of telephone interviews emerges ( Ward et al., 2015 ). Online data collection also offers the opportunity to collect synchronous and asynchronous data using instant messaging and other online media ( Hooley et al., 2011 ). Online interviews or focus groups conducted via Skype or other media may overcome some of the limitations of telephone interviews, although observation of non-verbal communication may be more difficult to achieve ( Janghorban et al., 2014 ). Open-ended free-text responses in surveys have also been identified as useful data sources in qualitative descriptive studies ( Kim et al . , 2017 ) and in particular the use of online open-ended questions, which can have a large geographical reach ( Seixas et al., 2018 ). Observation is also cited as an approach to data collection in qualitative descriptive research ( Sandelowski, 2000 ; Lambert and Lambert, 2012 ); however, in a systematic review examining the characteristics of qualitative research studies, observation was cited as an additional source of data and was not used as a primary source of data collection ( Kim et al. , 2017 ).

Data analysis and interpretation

According to Lambert and Lambert (2012) , data analysis in qualitative descriptive research is data driven and does not use an approach that has emerged from a pre-existing philosophical or epistemological perspective. Within qualitative descriptive research, it is important analysis is kept at a level at which those to whom the research pertains are easily able to understand and so can use the findings in healthcare practice ( Chafe, 2017 ). The approach to analysis is dictated by the aims of the research and as qualitative descriptive research is generally explorative, inductive approaches will commonly need to be applied although deductive approaches can also be used ( Kim et al . , 2017 ).

Content and thematic analyses are the most commonly used data analysis techniques in qualitative descriptive research. Vaismoradi et al . (2013) argue that content and thematic analysis, although poorly understood and unevenly applied, offer legitimate ways of a lower level of interpretation that is often required in qualitative descriptive research. Sandelowski (2000) indicated that qualitative content analysis is the approach of choice in descriptive research; however, confusion exists between content and thematic analysis, which sometimes means researchers use a combination of the two. Vaismoradi et al. (2013) argue there are differences between the two and that content analysis allows the researchers to analyse the data qualitatively as well as being able to quantify the data whereas thematic analysis provides a purely qualitative account of the data that is richer and more detailed. Decisions to use one over the other will depend on the aims of the study, which will dictate the depth of analysis required. Although there is a range of analysis guidelines available, they share some characteristics and an overview of these, derived from some key texts ( Sandleowski, 2010 ; Braun and Clark, 2006 ; Newell and Burnard, 2006), is presented in Table 1 . Central to these guidelines is an attempt by the researcher to immerse themselves in the data and the ability to demonstrate a consistent and systematic approach to the analysis.

Common characteristics of descriptive qualitative analysis.

Coding in qualitative descriptive research can be inductive and emerge from the data, or a priori where they are based on a pre-determined template as in template analysis. Inductive codes can be ‘in vivo’ where the researcher uses the words or concepts as stated by the participants ( Howitt, 2019 ), or can be named by the researcher and grouped together to form emerging themes or categories through an iterative systematic process until the final themes emerge. Template analysis involves designing a coding template, which is designed inductively from a subset of the data and then applied to all the data and refined as appropriate ( King, 2012 ). It offers a standardised approach that may be useful when several researchers are involved in the analysis process.

Within qualitative research studies generally, the analysis of data and subsequent presentation of research findings can range from studies with a relatively minimal amount of interpretation to those with high levels of interpretation ( Sandelowski and Barroso, 2003 ). The degree of interpretation required in qualitative descriptive research is contentious. Sandelowski (2010) argues that although descriptive research produces findings that are ‘data-near’, they are nevertheless interpretative. Sandelowski (2010) reports that a common misconception in qualitative descriptive designs is that researchers do not need to include any level of analysis and interpretation and can rely solely on indiscriminately selecting direct quotations from participants to answer the research question(s). Although it is important to ensure those familiar with the topic under investigation can recognise their experiences in the description of it ( Kim et al . , 2017 ), this is not to say that there should be no transformation of data. Researchers using a qualitative descriptive design need to, through data analysis, move from un-interpreted participant quotations to interpreted research findings, which can still remain ‘data-near’ ( Sandeklwoski, 2010 ). Willis et al. (2016) suggest that researchers using the qualitative descriptive method might report a comprehensive thematic summary as findings, which moves beyond individual participant reports by developing an interpretation of a common theme. The extent of description and/or interpretation in a qualitative descriptive study is ultimately determined by the focus of the study (Neergard et al ., 2009).

As with any research design, ensuring the rigor or trustworthiness of findings from a qualitative descriptive study is crucial. For a more detailed consideration of the quality criteria in qualitative studies, readers are referred to the seminal work of Lincoln and Guba (1985) in which the four key criteria of credibility, dependability, confirmability and transferability are discussed. At the very least, researchers need to be clear about the methodological decisions taken during the study so readers can judge the trustworthiness of the study and ultimately the findings ( Hallberg, 2013 ). Being aware of personal assumptions and the role they play in the research process is also an important quality criterion (Colorafi and Evans, 2016) and these assumptions can be made explicit through the use of researcher reflexivity in the study ( Bradshaw et al., 2017 ).

Challenges in using a qualitative descriptive design

One of the challenges of utilising a qualitative descriptive design is responding to the charge that many qualitative designs have historically encountered, which is that qualitative designs lack the scientific rigor associated with quantitative approaches ( Vaismoradi et al . , 2013 ). The descriptive design faces further critique in this regard as, unlike other qualitative approaches such as phenomenology or grounded theory, it is not theory driven or oriented ( Neergaard et al ., 2009 ). However, it is suggested that this perceived limitation of qualitative descriptive research only holds true if it is used for the wrong purposes and not primarily for describing the phenomenon ( Neergaard et al ., 2009 ). Kahlke (2014) argues that rather than being atheoretical, qualitative descriptive approaches require researchers to consider to what extent theory will inform the study and are sufficiently flexible to leave space for researchers to utilise theoretical frameworks that are relevant and inform individual research studies. Kim et al. (2017) reported that most descriptive studies reviewed did not identify a theoretical or philosophical framework, but those that did used it to inform the development of either the interview guide or the data analysis framework, thereby identifying the potential use of theory in descriptive designs.

Another challenge around the use of qualitative descriptive research is that it can erroneously be seen as a ‘quick fix’ for researchers who want to employ qualitative methods, but perhaps lack the expertise or familiarity with qualitative research ( Sandelowski, 2010 ). Kim et al. (2017) report how in their review fewer than half of qualitative descriptive papers explicitly identified a rationale for choosing this design, suggesting that in some cases the rationale behind its use was ill considered. Providing a justification for choosing a particular research design is an important part of the research process and, in the case of qualitative descriptive research, a clear justification can offset concerns that a descriptive design was an expedient rather than a measured choice. For studies exploring participants’ experiences, which could be addressed using other qualitative designs, it also helps to clearly make a distinction as to why a descriptive design was the best choice for the research study ( Kim et al ., 2017 ). Similarly, there is a perception that the data analysis techniques most commonly associated with descriptive research – thematic and content analysis are the ‘easiest’ approaches to qualitative analysis; however, as Vaismoradi et al . (2013) suggest, this does not mean they produce low-quality research findings.

As previously identified, a further challenge with the use of qualitative descriptive methods is that as a research design it has limited visibility in research texts and methodological papers ( Kim et al ., 2017 ). This means that novice qualitative researchers have little guidance on how to design and implement a descriptive study as there is a lack of a ‘methodological rulebook’ to guide researchers ( Kahlke, 2014 ). It is also suggested that this lack of strict boundaries and rules around qualitative descriptive research also offers researchers flexibility to design a study using a variety of data collection and analysis approaches that best answer the research question ( Kahlke, 2014 ; Kim et al . , 2017 ). However, should researchers choose to integrate methods ‘borrowed’ from other qualitative designs such as phenomenology or grounded theory, they should do so with the caveat that they do not claim they are using designs they are not actually using ( Neergaard et al . , 2009 ).

Examples of the use of qualitative descriptive research in healthcare

Findings from qualitative descriptive studies within healthcare have the potential to describe the experiences of patients, families and health providers, inform the development of health interventions and policy and promote health and quality of life ( Neergaard et al ., 2009 ; Willis et al ., 2016 ). The examples provided here demonstrate different ways qualitative descriptive methods can be used in a range of healthcare settings.

Simon et al. (2015) used a qualitative descriptive design to identify the perspectives of seriously ill, older patients and their families on the barriers and facilitators to advance care planning. The authors provided a rationale for using a descriptive design, which was to gain a deeper understanding of the phenomenon under investigation. Data were gathered through nine open-ended questions on a researcher-administered questionnaire. Responses to all questions were recorded verbatim and transcribed. Using descriptive, interpretative and explanatory coding that transformed raw data recorded from 278 patients and 225 family members to more abstract ideas and concepts ( Simon et al. , 2015 ), a deeper understanding of the barriers and facilitators to advance care planning was developed. Three categories were developed that identified personal beliefs, access to doctors and interaction with doctors as the central barriers and facilitators to advance care planning. The use of a qualitative descriptive design facilitated the development of a schematic based on these three themes, which provides a framework for use by clinicians to guide improvement in advance care planning.

Focus group interviews are a common data collection method in qualitative descriptive studies and were the method of choice in a study by Pelentsov et al. (2015), which sought to identify the supportive care needs of parents whose child has a rare disease. The rationale provided for using a qualitative descriptive design was to obtain a ‘straight description of the phenomena’ and to provide analysis and interpretation of the findings that remained data-near and representative of the responses of participants. In this study, four semi-structured focus group interviews were conducted with 23 parents. The data from these focus groups were then subjected to a form of thematic analysis during which emerging theories and inferences were identified and organised into a series of thematic networks and ultimately into three global themes. These themes identified that a number of factors including social isolation and lack of knowledge on behalf of healthcare professionals significantly affected how supported parents felt. Identifying key areas of the supportive needs of parents using qualitative description provides direction to health professionals on how best to respond to and support parents of children with a rare disease.

The potential for findings from a qualitative descriptive study to impact on policy was identified in a study by Syme et al. (2016) , who noted a lack of guidance and policies around sexual expression management of residents in long-term care settings. In this study, 20 directors of nursing from long-term care settings were interviewed with a view to identifying challenges in addressing sexual expression in these settings and elicit their recommendations for addressing these challenges in practice and policy. Following thematic analysis, findings relating to what directors of nursing believed to be important components of policy to address sexual expression were identified. These included providing educational resources, having a person-centred care delivery model when responding to sexual expression and providing guidance when working with families. Findings from this qualitative descriptive study provide recommendations that can then feed in to a broader policy on sexual expression in long-term care settings.

The final example of the use of a qualitative descriptive study comes from a mixed-methods study comprising a randomised control trial and a qualitative process evaluation. He et al. (2015) sought to determine the effects of a play intervention for children on parental perioperative anxiety and to explore parents’ perceptions of the intervention. Parents who had children going for surgery were assigned to a control group or an intervention group. The intervention group took part in a 1-hour play therapy session with their child whereas the control group received usual care. Quantitative findings identified there was no difference in parents’ anxiety levels between the intervention and control group. However, qualitative findings identified that parents found the intervention helpful in preparing both themselves and their child for surgery and perceived a reduction in their anxiety about the procedure thereby capturing findings that were not captured by the quantitative measures. In addition, in the qualitative interviews, parents made suggestions about how the play group could be improved, which provides important data for the further development of the intervention.

These examples across a range of healthcare settings provide evidence of the way findings from qualitative descriptive research can be directly used to more fully understand the experiences and perspectives of patients, their families and healthcare providers in addition to guiding future healthcare practice and informing further research.

Qualitative research designs have made significant contributions to the development of nursing and healthcare practices and policy. The utilisation of qualitative descriptive research is common within nursing research and is gaining popularity with other healthcare professions. This paper has identified that the utilisation of this design can be particularly relevant to nursing and healthcare professionals undertaking a primary piece of research and provides an excellent method to address issues that are of real clinical significance to them and their practice setting. However, the conundrum facing researchers who wish to use this approach is its lack of visibility and transparency within methodological papers and texts, resulting in a deficit of available information to researchers when designing such studies. By adding to the existing knowledge base, this paper enhances the information available to researchers who wish to use the qualitative descriptive approach, thus influencing the standard in how this approach is employed in healthcare research. We highlight the need for researchers using this research approach to clearly outline the context, theoretical framework and concepts underpinning it and the decision-making process that informed the design of their qualitative descriptive study including chosen research methods, and how these contribute to the achievement of the study’s aims and objectives. Failure to describe these issues may have a negative impact on study credibility. As seen in our paper, qualitative descriptive studies have a role in healthcare research providing insight into service users and providers’ perceptions and experiences of a particular phenomenon, which can inform healthcare service provision.

Key points for policy, practice and/or research

• Despite its widespread use, there is little methodological guidance to orientate novice nurse researchers when using the qualitative descriptive design. This paper provides this guidance and champions the qualitative descriptive design as appropriate to explore research questions that require accessible and understandable findings directly relevant to healthcare practice and policy.
• This paper identifies how the use of a qualitative descriptive design gives direct voice to participants including patients and healthcare staff, allowing exploration of issues of real and immediate importance in the practice area.
• This paper reports how within qualitative descriptive research, the analysis of data and presentation of findings in a way that is easily understood and recognised is important to contribute to the utilisation of research findings in nursing practice.
• As this design is often overlooked in research texts despite its suitability to exploring many healthcare questions, this paper adds to the limited methodological guidance and has utility for researchers who wish to defend their rationale for the use of the qualitative descriptive design in nursing and healthcare research.

Louise Doyle (PhD, MSc, BNS, RNT, RPN) is an Associate Professor in Mental Health Nursing at the School of Nursing and Midwifery, Trinity College Dublin. Her research interests are in the area of self-harm and suicide and she has a particular interest and expertise in mixed-methods and qualitative research designs.

Catherine McCabe (PhD, MSc, BNS, RNT, RGN) is an Associate Professor in General Nursing at the School of Nursing and Midwifery, Trinity College Dublin. Her research interests and expertise are in the areas of digital health (chronic disease self-management and social/cultural wellbeing), cancer, dementia, arts and health and systematic reviews.

Brian Keogh (PhD, MSc, BNS, RNT, RPN) is an Assistant Professor in Mental Health Nursing at the School of Nursing and Midwifery, Trinity College Dublin. His main area of research interest is mental health recovery and he specialises in qualitative research approaches with a particular emphasis on grounded theory.

Annemarie Brady (PhD, MSc, BNS, RNT, RPN) is Chair of Nursing and Chronic Illness and Head of School of Nursing and Midwifery at Trinity College Dublin. Her research work has focused on the development of healthcare systems and workforce solutions to respond to increased chronic illness demands within healthcare. She has conducted a range of mixed-method research studies in collaboration with health service providers to examine issues around patient-related outcomes measures, workload measurement, work conditions, practice development, patient safety and competency among healthcare workers.

Margaret McCann (PhD, MSc, BNS, RNT, RGN) is an Assistant Professor in General Nursing at the School of Nursing and Midwifery, Trinity College Dublin. Research interests are focused on chronic illness management, the use of digital health and smart technology in supporting patient/client education, self-management and independence. Other research interests include conducting systematic reviews, infection prevention and control and exploring patient outcomes linked to chronic kidney disease.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Ethical approval was not required for this paper as it is a methodological paper and does not report on participant data.

The author(s) received no financial support for the research, authorship and/or publication of this article.

Louise Doyle https://orcid.org/0000-0002-0153-8326

Margaret McCann https://orcid.org/0000-0002-7925-6396

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• Descriptive Research | Definition, Types, Methods & Examples

Descriptive Research | Definition, Types, Methods & Examples

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

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

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

Table of contents

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

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

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

Descriptive research question examples

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

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

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

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

Observations

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

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

Case studies

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

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

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

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

Research bias

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

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