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• Descriptive Research Design | Definition, Methods & Examples

Descriptive Research Design | Definition, Methods & Examples

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

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

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

Table of contents

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

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

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

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

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

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

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

Observations

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

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

Case studies

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

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

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McCombes, S. (2022, October 10). Descriptive Research Design | Definition, Methods & Examples. Scribbr. Retrieved 25 March 2024, from https://www.scribbr.co.uk/research-methods/descriptive-research-design/

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Demystifying the research process: understanding a descriptive comparative research design

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• 1 College of Nursing, Villanova University, Villanova, PA, USA.
• PMID: 21916346

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• Pediatric Nursing
• Reproducibility of Results
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Methodology

• 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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McCombes, S. (2023, June 22). Descriptive Research | Definition, Types, Methods & Examples. Scribbr. Retrieved March 27, 2024, from https://www.scribbr.com/methodology/descriptive-research/

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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 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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• 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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Research Design in Business and Management pp 85–96 Cite as

Comparing Types of Research Designs

• Stefan Hunziker 3 &
• Michael Blankenagel 3  
• First Online: 10 November 2021

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Every researcher chooses the research design that is best suited to generate the envisioned conclusions they like to draw. There are several types of research designs. Each is especially well suited to generate a specific type of conclusion. Commonly used research designs in business and management are design science, action research, single case, multiple case, cross-sectional, longitudinal, experimental and literature review research. The specific characteristics depicting these research design’s idiosyncrasies, differences, and fields of application of these research designs are gathered in a synopsis. Also, we pose questions that guide researchers to the research design, matching their objectives and personal preferences. This chapter also addresses the popular terms “triangulation” and “mixed methods” and puts them into the context of research design.

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

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

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

Table of Contents

What Is Descriptive Research Design?

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

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

Importance of Descriptive Research in Scientific Studies

1. understanding of a population or phenomenon.

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

2. Baseline Information

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

3. Informative Data

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

4. Sampling Validation

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

5. Cost Effective

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

6. Easy to Replicate

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

Key Characteristics of Descriptive Research Design

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

2. Participants and Sampling

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

3. Data Collection Techniques

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

4. Data Analysis

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

5. Focus on Description

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

6. Non-Experimental

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

When Can a Researcher Conduct Descriptive Research?

A researcher can conduct descriptive research in the following situations:

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

Types of Descriptive Research Design

1. survey research.

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

2. Observational Research

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

3. Case Study Research

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

4. Focus Group Research

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

5. Ethnographic Research

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

Advantages of Descriptive Research Design

1. provides a comprehensive understanding.

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

2. Non-invasive

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

3. Flexibility

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

4. Cost-effective

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

5. Easy to Replicate

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

6. Informs Future Research

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

Disadvantages of Descriptive Research Design

1. limited scope.

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

2. Dependence on Existing Data

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

3. Lack of Control

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

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

5. Lack of Generalizability

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

6. Lack of Depth

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

7. Time-consuming

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

7 Ways to Avoid Common Flaws While Designing Descriptive Research

1. Clearly define the research question

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

2. Choose the appropriate research design

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

3. Select a representative sample

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

4. Use valid and reliable data collection methods

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

5. Minimize bias

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

6. Ensure adequate sample size

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

7. Use appropriate data analysis techniques

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

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

extremely very educative

Indeed very educative and useful. Well explained. Thank you

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Decision-making and autonomy among participants in early-phase cancer immunotherapy trials: a qualitative study

• Jonathan Avery   ORCID: orcid.org/0000-0002-7347-6224 1 , 2   na1 ,
• Jennifer A.H. Bell   ORCID: orcid.org/0000-0003-3617-6852 2 , 3 , 4 , 5 , 6   na1 ,
• Khotira Baryolay 2 ,
• Gary Rodin 2 , 7 , 8 , 9 , 10 ,
• Rinat Nissim 2 , 8 &
• Lynda G. Balneaves 11   na2  

BMC Cancer volume  24 , Article number:  373 ( 2024 ) Cite this article

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Participants considering early-phase cancer clinical trials (CTs) need to understand the unique risks and benefits prior to providing informed consent. This qualitative study explored the factors that influence patients’ decisions about participating in early-phase cancer immunotherapy CTs through the ethical lens of relational autonomy.

Using an interpretive descriptive design, interviews were conducted with 21 adult patients with advanced cancer who had enrolled in an early-phase CT. Data was analyzed using relational autonomy ethical theory and constant comparative analysis.

The extent to which participants perceived themselves as having a choice to participate in early-phase cancer immunotherapy CTs was a central construct. Perceptions of choice varied according to whether participants characterized their experience as an act of desperation or as an opportunity to receive a novel treatment. Intersecting psychosocial and structural factors influenced participants’ decision making about participating in early-phase cancer immunotherapy trials. These relational factors included: (1) being provided with hope; (2) having trust; (3) having the ability to withdraw; and (4) timing constraints.

Conclusions

Findings highlight the continuum of perceived choice that exists among patients with cancer when considering participation in early-phase cancer immunotherapy CTs. All participants were interpreted as exhibiting some degree of relational autonomy within the psychosocial and structural context of early-phase CT decision making. This study offers insights into the intersection of cancer care delivery, personal beliefs and values, and established CT processes and structures that can inform future practices and policies associated with early-phase cancer immunotherapy CTs to better support patients in making informed decisions.

Peer Review reports

Advances in cancer care depend on evidence derived from clinical trials (CTs) to help practitioners and patients make informed treatment decisions. However, less than 5% of adult patients with cancer participate in CTs [ 1 ] and many trials suffer from insufficient accrual, with earlier phase trial being especially problematic [ 2 ]. Poor accrual and retention have been linked to complex and lengthy consent procedures, which may create difficulties for patients in providing informed consent [ 3 , 4 ]. A systematic review evaluating patient understanding of consent for participation in CTs concluded that patients often do not fully understand the potential health risks of novel experimental drugs and have unrealistic expectations of benefit [ 5 ].

Phase I trials, which test the toxicity and safety of a novel treatment in humans, have typically placed research subjects at greater risk of adverse effects with less likelihood of benefit compared to phase II and III trials [ 6 ]. Phase I cancer trials usually involve patients whose disease is advanced or refractory to standard treatment, and who may be more likely to view the CT as their last opportunity to receive treatment [ 7 ]. Such individuals may feel desperate about the severity and progression of their disease, which can undermine their capacity to provide meaningful informed consent [ 8 , 9 ].

Recent advances in our understanding of cancer biology and the emergence of precision medicine, with such transformative therapies as immune checkpoint inhibitors and molecularly targeted agents, have altered the cancer CT landscape [ 10 ]. Some phase I cancer trials have become highly targeted and are incorporating elements of later phase CTs. It is not uncommon now to have a combined phase I/II within a single study protocol. These early phase CTs include dose expansion, and allow modification of the trial design based on early evidence of a drug’s efficacy and acceptable toxicity [ 11 ]. These combined phase I/II trials [ 12 ] raise ethical concerns as the distinctions between trial phases becomes blurred, challenging previous understandings of the risks and benefits associated with phase I trials while at the same time offering participants a renewed sense of hope for a cure or delayed disease progression [ 13 ]. Early phase trials thus require special attention to informed consent procedures to ensure research subjects’ understanding of evolving safety and efficacy data, and realistic assessment of risks and benefits [ 11 ].

Given the ethical concerns associated with these modern early-phase CTs, the purpose of this qualitative study was to explore the decision-making process of patients living with cancer who have considered participating in early-phase cancer immunotherapy CTs, including the psychosocial (i.e. the interrelation of social factors, such as age and socio-economic status, with individual thought and behavior) and structural factors (i.e. inequities and unjust power differences in policies and practices) that intersect and influence perceptions of choice and ability to provide informed consent. Consideration of the dynamic influence of psychosocial and structural factors on individual-level decision making is essential to the development of a richer and more comprehensive understanding of CT decision-making processes. This knowledge can enhance ethical CT practices and the development of associated tools, resources, and policies to support patients in making informed decisions about early-phase cancer CTs in this rapidly advancing and complex trial landscape.

Research design and theoretical framework

A qualitative interpretive descriptive design [ 14 ], using semi-structured interviews and constant comparative analysis with a relational autonomy lens [ 15 ], was used to explore the intersection of the dynamic social and relational factors influencing patient decision making about early-phase cancer immunotherapy CTs. Relational autonomy was selected as a framework for this study because it is a theoretical approach that, in addition to psychosocial factors, considers the influence of structural factors on an individual’s beliefs and opportunities to develop autonomy, which is necessary for providing informed consent. By identifying the structural factors, such as gender or socioeconomic status, and addressing related inequities and unjust power differences in policies and practices, relational autonomy aims to empower those who may be oppressed [ 16 ]. According to relational autonomy theory, a person may be regarded as minimally, medially or fully relationally autonomous based on the degree to which their motivation arises from their own autonomous capacities (i.e., experience a desire as “one’s own”), within an overlapping network of social and structural contexts [ 17 ]. Although prior studies have identified psychosocial influences on trial decisions, less attention has been paid to identifying structural factors and the intersection between psychosocial and structural factors on cancer CT decision making [ 13 , 18 ]. Relational autonomy theory appreciates the intersectionality of these factors and is thus well-suited to guide an examination of the complex interplay of these factors in creating a holistic context in which persons make early-phase cancer CT decisions.

Bell’s method for applying relational autonomy to qualitative health research [ 15 ] guided all aspects of this study, including the development of the research question, study design, sampling, and interview guide. Relational autonomy was also used as an analytic lens to uncover and interpret the personal and structural factors that influence individuals’ autonomy and informed consent within the context of early-phase cancer immunotherapy CT decision-making.

Participants

Participants were recruited from lung, breast, gynecologic, gastrointestinal, brain and CT clinics at the Princess Margaret Cancer Centre in Toronto, Canada between September 2018 and June 2019. The hospital has a world-renowned early-phase CT program, conducting approximately over 400 phase I/phase I-II trials each year, predominantly testing novel anti-cancer agents such as immunotherapies. Convenience sampling was initially used to recruit participants followed by a purposeful sampling strategy to ensure that diverse gender perspectives were represented in the data, as well as individuals who had declined to participate in an early-phase CT. Patients were identified and informed about the study by CT nurses. Interested patients were then approached by a member of the research team to provide further information verbally and in written form about the study and to seek informed consent. The primary inclusion criteria for patients were English speaking individuals aged 18 years and older who had been approached to take part in an early-phase (I or I/II) CT. This study received research ethics approval from the University Health Network Research Ethics Board (#18-5408). All participants provided written informed consent to participate. A token of appreciation in the form of a $25.00 gift card was provided to those who participated.

Data collection

Semi-structured interviews were conducted with participants during September 2018-June 2019 either in person or over the phone by the first authors (JA, JAHB). We used the theory of relational autonomy to develop the interview guide. Questions were crafted that allowed us to probe the psychosocial (i.e. personal and relational) and larger structural (i.e. macro-level) context that may influence an individual’s autonomy and decision making in consenting to partake in an early-phase CT, and the potential influence of personal and relational factors (Table S1 ). Additional questions probed participants’ understanding of phase I trials and the purpose of the trial they were offered, reasons why the patient accepted a trial, who and what was influential in their decision-making process, and what information or other resources were important when making the decision. Applying the theory of relational autonomy to develop the interview guide allowed us to explore the context in which the trial was introduced and any perceived influences on making a decision about partaking in the trial (i.e. barriers and facilitators). All interviews were digitally recorded and transcribed verbatim. Before each interview, participants completed a self-reported sociodemographic questionnaire. This data was used to determine the heterogeneity of the sample across age and gender, which directed purposeful sampling strategies to ensure representation of our sample across these two criteria. This was facilitated by the research team asking our clinical partners if they had potential participants between certain ages or genders to fill the gaps in our sample.

Data analysis

All interviews were transcribed verbatim. Transcripts were analyzed using the constant comparative method to compare all “pieces” of data (codes, themes, and categories) within and across interviews until substantive patterns were developed [ 19 ]. In this approach, data collection and analysis are inextricably linked, with the interview data directing the coding and vice versa. A relational autonomy lens was applied to the analysis to examine the personal, social, and structural factors that influenced patients’ decisions about participating in early-phase CTs. The impact of family, the healthcare team, and the larger healthcare system was also explored, as well as how power manifested within these social dynamics. The use of a theoretical framework, such as a relational autonomy, in qualitative research is considered acceptable and does not undermine inductive analysis [ 20 ]. Each interview transcript was reviewed line-by-line, and/or in segments, to identify codes. Codes were grouped together into larger themes and corresponding categories. The first four interview transcripts were analyzed independently by three members of the research team (JA, JAHB, KB) and then discussed to create and agree upon a coding framework. Thereafter, the remaining interviews were analyzed by JA.

Consistent with interpretive description and reflexivity is acknowledgement that qualitative research is bound to historical context and the disciplinary perspectives of those involved in the study [ 19 ]. Reflexive journaling and memo writing was undertaken by JA to maintain rigour and transparency of the data analysis and emergent findings were discussed with the research team. Each member of the research team was instructed to discuss their thoughts and insights associated with the data analysis and emergent findings to illuminate potential beliefs and biases in the analysis. Any discrepancies between views were discussed and resolved through discussion. NVivo qualitative software program was used to facilitate coding and analysis. The use of rich, descriptive quotes and line-by-line coding further contributed to ensuring the representativeness and trustworthiness of the analysis and findings, as did engagement with the research team members who are active with cancer CTs in Canada and who believed the findings resonated with their experience.

Demographics

We approached 50 patients to participate in this study of which 23 consented to participate. Of those who did not participate, six patients did not meet eligibility requirements, eight patients declined the offer of study participation, and 13 did not respond to follow-up by the research team. Data was not collected on why participants declined to participate. Of the 23 who consented to participate, two individuals withdrew from the study leaving a final sample of 21 patients who were interviewed by telephone ( n  = 11) or in-person ( n  = 10) in a private space at the cancer centre. On average interviews were 50 min in duration (range: 22– 70 min). We did not note any differences in depth or length between interviews conducted in person versus those conducted by telephone. All the patients interviewed, except one, had accepted a phase I or phase I/II cancer CT of immunotherapy. One individual took part in a radiotherapy phase II trial. The predominance of immunotherapy trials reflects the current priorities of the CT program at the host institution. Despite repeated attempts, we were unable to recruit a larger number of participants who had declined an invitation to participate in an early-phase CT; however, some had previous experience withdrawing from a trial or declining a trial in the past. Just over half of the participants identified as male. Most participants identified as White and reported having at least a college/university education and a yearly income of $30–60,000 Canadian. The patient sample varied by cancer type (Table S2 ).

All participants considered participating in an early-phase CT. However, the extent to which they perceived themselves as having a choice to participate or not emerged as a central construct of their experience. Participants’ perceptions of choice varied according to whether they characterized their experience as either: (1) an act of desperation when standard care was seen as unsuccessful and/or no longer an option; or (2) an opportunity to receive a novel treatment to potentially improve their quality of life, increase their longevity, and/or be cured. These divergent perceptions exemplify opposite ends of a choice spectrum, where desperation coincided with the sense of having less choice, and opportunity afforded participants a sense of greater choice (see Table S3 ).

Trial participation as an act of desperation

Despite research consent forms that identify alternative options to trial participation, some participants believed they did not have a choice but to participate in an early-phase cancer CT. These participants reported that standard care (i.e., chemotherapy, radiation and/or surgery) was no longer effective in treating their cancer, or the side effects of these treatments were intolerable or too difficult to manage, thereby negatively impacting quality life. A minority reported never being presented with other treatment options by their oncology healthcare team because of the severity of their disease. When faced with a life-limiting diagnosis and no viable treatment, participants perceived they had no other option but to enroll in an early-phase trial. Such individuals did not believe that declining the trial was an acceptable option. As one woman with colon cancer said:

My understanding is they [CT staff] don’t really know if it’s going to help me. They definitely told me that it wasn’t a cure, but the chemo really wasn’t working… and when you’re told this is terminal, what are you going to do? There’s no other road as far as I myself am concerned. We’re out of options. (P007)

The belief that death was around the corner caused a great amount of anxiety in some participants, contributing to their sense of desperation for trial participation, even when faced with potential side effects from the drug being trialled. One woman with cervical cancer emphasized:

… it’s very scary. I was petrified of what the side effects could be [from the trial] but again you don’t have a choice. If you want to stay here [stay alive], you’re going to do it (P010).

Trial participation as an opportunity

In contrast to individuals who felt a sense of desperation about gaining access to a trial, there were those who perceived themselves as having a choice. While they held hope that an early-phase trial could help them, they expressed more equanimity about the outcome and felt able to critically evaluate their treatment options and the impact on their overall wellbeing. For many of these individuals, early-phase cancer immunotherapy CTs were understood as an opportunity to try a novel therapy that could provide a better quality of life when compared to standard forms of treatment. A woman with breast cancer said:

I mean chemo, when I looked at the chemo side effects and also the clinical trial side effects, they’re all so similar. I figured, you know what, why not just give it [the trial] a chance because we’ll never know until I give it a try… I just feel like this is something that could work (P005).

Other participants focused on the promise offered by an early-phase trial and contrasted it with the known risks, side effects, and limited success rate of standard treatment for their disease. For example, a woman with lung cancer shared:

You just hear horror stories about people on chemo. Do I want to put myself through hell… to be taken to the point of death for something that’s not a cure? (P013)

Logistics associated with participating in an early-phase CT, such as travelling to the cancer centre for treatments and follow-up care, were also considered by some when making a trial decision. Most participants who felt they had a choice appeared to weigh the pros and cons of participating in a trial regarding the impact on their daily routines, lifestyle, and on their desired quality of life. This type of decisional balancing is reflected in the following quotation from a man with lung cancer:

I felt I had a choice. I was offered the trial, but I didn’t accept right away. I was reluctant. There was a greater commitment [to participate] and perhaps a greater risk of side effects. My big concern was quality of life. As long as I can still think and write… I’m good… this seemed like an opportunity. (P016)

Applying a relational autonomy lens, this quote suggests that those who saw themselves as having a choice were better positioned to reflect and consider the impact of a trial on their lives and health. Those who perceived themselves as having less choice, may not have had the luxury to consider comprehensively the impact on themselves.

Relational influences on early-phase trial decision making

A myriad of psychosocial and structural factors, reflecting the relational nature of early-phase CT decision-making, influenced participants’ decisions about participating in early-phase cancer immunotherapy trials. These factors included: (1) being provided with some hope; (2) having trust; (3) having the ability to withdraw; and (4) timing constraints. In constructing these factors, it became apparent that all participants, even those who perceived a lack of choice, were able to exercise some degree of relational autonomy within the psychosocial and structural context of early-phase trial decision making.

Being provided with some hope

Foremost, participants’ decisions about participating in an early-phase cancer immunotherapy trial appeared to be influenced by their belief that the trial intervention would be effective in potentially extending their life and preserving their quality of life, which contributed to an overarching sense of hope. Important social relationships and structural influences, including the larger cancer care landscape, were influential in the maintenance of hope, which was an important relational factor that influenced participants throughout the choice continuum.

With regards to the impact of one’s social relationships, many patients experienced encouragement from their family and friends to persevere in the face of a dire prognosis– early-phase trial participation was seen as a logical next step in continuing “the fight” and maintaining hope. A woman with cervical cancer said:

You know what, my husband has been very, very strong and I know he’s…this is very, very hard for him because I try to put myself in his shoes to be the one that gets left behind. He’s been strong and I know it’s killing him inside. Now, my boys, they think mum’s strong, she’s coming out of this, like, they just…they won’t accept it either…they’re just of the belief that mum’s going to make it through this. I mean, decisions were made because of them, I can tell you that. (P010)

Considering this woman’s experience through a relational autonomy lens leads to further questions that could be explored related to how the social norms of gender identity influence CT decisions. Specifically, whether the woman was encouraged by her family to pursue the trial or whether her decision was circumscribed by a sense of responsibility to not leave her family members behind, stemming from social expectations regarding gender roles and motherhood.

In addition, although conversations between clinicians and patients were transparent about the experimental nature of early-phase cancer immunotherapy CTs, they often provided participants with hope that the trial would be beneficial. The body language, tone of voice, and choices of words when trials were introduced all influenced patients’ optimism about the outcomes of a trial. For example, some described receiving information about the uncertainty of personal benefit from the trial, yet remained hopeful that the trial could potentially extend their quality of life. As stated by a woman with colon cancer,

The doctors themselves, they don’t know if it’s going to help. They definitely told me it [the trial] wasn’t a cure, but it could give me more time. Hopefully. It was an alternative to chemo. It was kind of like, hey, I can handle that because I’m not feeling the nausea and I have the energy to actually live and go and do things. (P007)

The introduction or maintenance of hope through interpersonal relationships gained momentum from larger structural influences, such as the practice of introducing early-phase CTs to individuals shortly after receiving a dire prognosis. Given the devastating psychological impact for participants of being told they were out of options and could possibly die, the introduction of highly experimental treatments provided them with a renewed sense of hope that they still had a chance to live. A man with lung cancer said:

When you’re given a cancer diagnosis, I mean, I was told I had four months [left to live], that’s kind of a shock. And then you’re told that maybe you have a new lease on life by [Nurse X] about going on this trial! (P017)

Participants clung to this sense of hope in moments of despair and were highly influenced by it when considering participating in an early-phase CT.

Participants also appeared to derive a sense of hope from the numerous medical tests that were required to determine if they were a candidate for a trial. These tests made the trial appear highly personalized and, depending on the results, eliminated any hesitancy about taking part. A man with leukemia said:

I did a bunch of tests, so they knew how good or bad of a candidate I was and they said, ‘you’re like, a perfect candidate’. So, it was a no brainer [to participate] (P015).

This example illustrates how the structural context of trial work-up, reinforced by the positive framing of test results by CT personnel, contributed to patients’ trial decisions.

The experience of hope also appeared to be heightened by social expectations regarding the new trial landscape of breakthrough therapies, including immunotherapy agents. A man with sarcoma discussed how these therapies were less toxic than other cancer treatments and leveraged the body’s natural immune system:

It’s using your own immune system so it’s more of a natural approach than chemo. Chemo is a chemical, it’s poison […] and the idea is that they give you the chemical and it kills all the cells including the good ones and the idea is the hope that you bounce back. (P002)

Having trust

Trust played an important role in encouraging participants to consent to an early-phase CT. Foremost, the faith and trust patients had for the clinical institution in which the trial was being offered was an influential factor in the decision to take part and increased their confidence in the safety of the trial. A woman with ovarian cancer said:

Initially, I was very hesitant to participate but I have great faith in [Hospital X]… they’re not going to introduce a phase I [trial] if there’s going to be a high degree of danger. (P020)

Participants also felt assured that the institution would look out for their best interests. As a man with colon cancer noted:

I’m not a 100% sure about them [early-phase clinical trials]. But I know that [Hospital X] is highly reputable… they’re going to take care of me. They are going to keep a close eye on how things are going and if things go bad, they will stop the treatment. I was just very excited that I was able to get to [Hospital X]. (P003)

In addition to trusting the institution, participants were also influenced by the opinions of trusted CT staff and other members of their healthcare team. A man with leukemia said:

[Doctor X] offered me [the trial] and when I think about it, I trust [Doctor X] and his integrity and I trust his beliefs that this [the trial] is the best choice for me… I followed. (P009)

Another man with pancreatic cancer reflected on how the history of successful treatment recommendations provided by his oncologist influenced his trial decision:

I wanted to talk to him so I could get his input because he’s important and he’s kept me going this long. He said, ‘Go ahead with it, you’re foolish not to take it’. (P011)

The use of the word “foolish”, while potentially reflecting the established and comfortable rapport between the patient and the clinician, could have also made it challenging for the patient to do anything but accept their physician’s recommendation to participate in the trial.

Having the ability to withdraw

The regulatory and ethical requirement that allows patients to voluntarily withdraw from a CT at any time was a structural factor that appeared to facilitate participants’ decisions related to early-phase trials. Both participants who felt desperate and those who perceived participating as an opportunity described the ability to withdraw as a ‘failsafe’, making it easier for them to ‘take the risk’ of participating in an early-phase trial where there is more uncertainty about safety and efficacy. A man with leukemia elaborated:

I wanted to know whether I could quit at any time. I didn’t want to just be a guinea pig unless I had a chance of survival and some kind of potential improvement. (P014)

Similarly, a man with lung cancer who felt he had no choice but to participate, appeared comfortable with his decision because he had the option of withdrawing from the trial, saying:

The bottom line is I didn’t think I had any choice… but it’s nice to know that I could have walked away at any time. (P018)

Timing constraints

There were both real and perceived timing constraints expressed by participants in relation to decisions about taking part in early-phase cancer immunotherapy trials. Structurally, CTs can have a limited time frame to recruit subjects and eligibility criteria can restrict access to individuals within a narrow window of time in the cancer continuum and with regards to pre-screening. As such, some participants internalized a sense of pressure to make a quick decision, lest their spot in the trial would be filled by someone else. This contributed to their feelings of desperation and perceived lack of time to make a considered choice. A man with pancreatic cancer said:

There was pressure to make the decision in a hurry… they [CT staff] have to fill these spots… they only have a certain amount of time for you to make the decision. Eventually, you’re going to get to the point where we have no choice. You have to go for a clinical trial. (P011)

Some participants also perceived themselves to personally be under a time constraint to participate in an early-phase cancer immunotherapy trial with regards to gaining access to a novel treatment while they believed benefit was still possible. However, the nature of early-phase CTs, which are typically reserved for individuals with refractory disease who have been provided all treatment options, creates a structural barrier to those seeking early access. For example, a man with sarcoma was informed by their treatment team that early-phase CTs were not yet an option because the patient had not exhausted more proven lines of cancer therapy. Waiting for a trial to become available became a point of contention and distress for this participant, who was desperate to receive the immunotherapy trial drug as soon as possible because they perceived it as the better treatment option that they would benefit from, especially if received earlier in their disease trajectory:

After it [immunotherapy clinical trials] was mentioned, I kept pushing for it. I wanted to try it out. I was willing but the doctors kept saying ‘that’s something to keep your back pocket. That’s for later’. I’m going, ‘well, later on may be too late’. (P002)

This study explored patients’ decision making related to early-phase cancer CTs using the lens of relational autonomy. A choice spectrum was uncovered that captures patients’ decision-making experiences, ranging from trial participation being framed as an opportunity to it being perceived as an act of desperation. Our use of the theory of relational autonomy in the construction of our interview guide allowed us to explore and uncover the personal, relational, and larger structural factors that framed this experience. For example, asking questions pertaining the participants motivations and reasons for accepting/declining/withdrawing their participation illustrated how their clinical team influenced participants’ perceived hope and trust that the trial would extend their quality of life and even provide a potential cure, while structural factors, such as trial design and ethical requirements that ensured voluntariness of decisions, enabled the ability of patient participants the option of withdrawing from a trial should they change their mind. A perceived sense of hope and trust that the trial would succeed, and the ability to withdrawal were fundamental attributes that influenced the decision to partake.

Our study findings align with and expand upon previous research. For example, Halpern et al. [ 21 ] illustrate that upwards of 94% of patient-subjects enroll in early-phase CTs with unrealistic therapeutic benefits formed when facing a life-limiting illness that is very difficult to treat. Cox et al. [ 22 ] note that beliefs about therapeutic benefit may be influenced by a myriad of factors including how healthcare professionals working in early-phase CT recruitment communicate with potential participants and the discourse used that could impact patients’ perceptions of choice. For example, the use of the term ‘foolish’ to describe a decision not to enter a CT has significant implications for patients’ decision making, as other studies have also found patients are highly influenced by their physician’s communication [ 23 ]. Additionally, recent studies have also uncovered that some patients perceived they have no other choice but to participate in the trial, perceiving ‘no treatment’ as an untenable option as it means giving up on life [ 23 , 24 ]. For those who were ineligible for trials, this led to feelings of despair and uncertainty about their options [ 23 ]. More research is needed that explores patients who are ineligible or who choose not to enroll in clinical trials to offer tailored psychosocial support, especially since one study has found a correlation between moderate to high levels of clinical depression and the decision to decline CT participation [ 25 ].

Applying a relational autonomy lens allowed us to explore potentially influencing factors in more detail by highlighting the overlapping social and structural factors that affected patients’ ability to enact preferred choices and how they were supported in their preference-formation and decision-making process. Many participants shared that they were approached by their physician about taking part in an early-phase trial immediately following the devastating news of a cancer recurrence, progression of disease, or lack of response to standard treatment. This timing and the framing of early-phase cancer immunotherapy trials as the next logical step in treatment may have limited participants’ ability to make a considered decision about trial participation. Patients’ desperation related to the severity of their disease has been identified in previous literature as autonomy-undermining by interfering with persons’ abilities to clearly consider and reflect upon one’s values, interests, and options [ 26 ]. The paradox of obtaining informed consent for early-phase trials in circumstances described by many patients as life versus death, in which they perceive no other options but to choose the trial, has been previously discussed [ 27 , 28 ]. While the vulnerability of patients must be acknowledged and addressed in this scenario, the nuanced lens of relational autonomy recognizes that individuals may still have capacity for autonomy, although grounded in important social relationships and influenced by structural factors. Therefore, instead of questioning whether patients have the ability to make their own decisions, a relational autonomy lens encourages the healthcare team and CT personnel to consider ways to support patients so that they are more fully relationally autonomous in the early-phase CT decision making-process. For example, patients’ capacity for autonomy within a relational context would be enhanced by CT personnel taking the time to ensure an individual’s emotional and psychosocial needs are met, that their personal values and beliefs are reflected upon during the decision-making process, and that their understanding and expectations regarding trial outcomes are realistic [ 27 , 28 ].

The larger social discourse surrounding cancer and emerging cancer treatments also had an influence on participants and their decision making related to early-phase cancer immunotherapy trials. When faced with a poor prognosis or limited treatment options and the associated fear and desperation, some patients and family members leveraged bellicose metaphors, such as continuing “the fight” against cancer, to provide hope and to support their decision to enter an early-phase trial [ 29 ]. Further, the recent emergence of cancer immunotherapy and precision medicine, and the accompanying discourse regarding the personalized and “natural” immune boosting nature of treatment, has further contributed to patients’ and clinicians’ sense of optimism towards early-phase trials focused on these types of therapies. Acknowledging the powerful influence of these discourses on patients’ decision making and their ability to reflect on their personal values as well as the potential benefits and risks of trial participation may be an important consideration to enhance patients’ relational autonomy in the context of early-phase cancer immunotherapy CTs. There is considerable debate in the scientific and ethics literature about whether phase I trials are likely to provide direct therapeutic benefit in some instances [ 6 , 30 , 31 ]. We do not weigh in on this debate. Instead, we underscore the need for patients to understand the potential benefits and risks of a particular early-phase trial without hyperbole or unreasonable optimism [ 32 ]. Specifically, immunotherapy is not without potentially life-threatening risk of adverse events, such as neurotoxicities and uncertainty exists regarding the long-term benefits and remission status of patients receiving these therapies [ 33 ]. It behooves physicians when discussing immunotherapy or other targeted cancer CTs to remain committed to providing balanced communication with patients about the purpose of a trial and to clearly explain the associated risks / benefits so as not to engender unrealistic expectation and provide false hope [ 23 ]. Additionally, those who contribute social commentary and public-facing information about novel cancer drugs and CTs such as the media, industry, and trusted cancer centres and organizations, need to be held accountable (perhaps by regulation if not by ethical standards) to present information about modern day CTs fairly, without the use of unjustified superlatives or emotional advertising that obscures a more full appreciation of the risks, benefits, and direct participant costs/resources [ 34 , 35 ].

Examining the study findings through a relational autonomy lens highlights the power differential between patients and clinicians, and its potential impact on patients’ perceptions of choice. The trust and sense of indebtedness that many patients feel towards their oncologists, as well as the institution in which they are receiving care, may restrict patients from fully considering their own personal values and preferences when making an early-phase trial decision. In addition, the immutable expertise and scientific knowledge held by oncologists may be prioritized by some patients and motivate them to accept a clinical recommendation to participate in an early-phase trial. The structural location of oncologists as the “gatekeeper” to early-phase CTs may also contribute to a power imbalance that restricts the choices available to patients and families [ 36 ]. In addition, it is important to acknowledge that clinicians and institutions are under pressure and may feel a sense of responsibility to successfully accrue to early-phase trials, not only to contribute to the scientific evidence but to provide patients with the latest advances in cancer treatment [ 36 ].

Applying a relational autonomy lens in this study also uncovered how structural factors, including the design and pre-screening processes associated with an early-phase trial, impacted patients’ decisions and their perceptions of choice. It is important that CT personnel and healthcare professionals recognize how the restrictive eligibility criteria, extensive screening procedures, and conversations about trial participation unintentionally characterize early-phase cancer immunotherapy trials as exclusive and time-limited, which may lead some patients to feel pressure to accept the trial as well as form unrealistic expectations and hope for personal benefit. Successfully making it through the comprehensive early-phase trial screening may also create a situation in which patients feel the trial is tailored to them and that refusing to take part would be nonsensical. Healthcare professionals and CT personnel, thus, need to be aware of how the very structure of immunotherapy or targeted early-phase trials may inadvertently influence patients’ decisions related to trial participation. Being clear in conversations with patients that being an eligible candidate for an early-phase trial does not necessarily equate with receiving direct benefit, including an extension of life, may be an important addition to discussions about trial participation.

In accordance with interpretive description study methodology, we sought to not only interpret what was stated by our study participants, but also to recognize the silences in the data, or what was not alluded to and constituted a marked absence from what may have been expected in the data. Notably, when participants were asked about what was discussed when considering early-phase immunotherapy CT participation, as well as what type of information was important to them, the topic of advance care planning did not emerge at all. Further exploration of how advance care planning and goals of care conversations are managed in this context, and how patients can be supported in considering and evaluating all possible treatment and care options, including palliative care, may be a valuable line of future inquiry. This finding aligns with research that has identified a divergence between patients receiving specialist palliative care and those considering an early-phase trial that is based in misconceptions about palliative care as only applicable near the end of life [ 37 ]. The heavy physical symptoms and psychological burdens that many patients face is highly relevant to the services of specialist palliative care, and it has been argued that earlier education be provided to patients and caregivers to explain the role and opportunity for palliative care throughout the cancer trajectory [ 38 ]. However, when prognosis changes and end of life is near, the social and structural context of cancer care needs to more fully embrace end-of-life care as an acceptable and appropriate option for some individuals, countering the perception of palliative care at this stage of disease as a clinical “failure” [ 39 ]. CT personnel thus need to work closely with a patient’s healthcare team to ensure meaningful discussion about palliative care occur alongside or prior to early-phase trial recruitment procedures. Such discussions will support patients’ re-evaluation of their priorities related to quantity of life versus quality of life, create space for patients and their family members to consider the full spectrum of healthcare alternatives, and enable patients to make a more fully informed and relationally autonomous decision.

Limitations

This was an interpretive descriptive qualitative study undertaken with a cross-sectional design. It is important to acknowledge that the study design restricts our ability to make inferences regarding how the personal, social, and structural factors influence where a participant was located on the choice spectrum with regards to perceiving their decision to participate in an early-phase trial as being an act of desperation or one of opportunity. Future research utilizing other methodologies, such as grounded theory or survey research, may provide further insight into the relationships between these factors and choice perceptions.

In addition, despite our best efforts, we were not able to recruit participants who had withdrawn from, or declined the offer to join, an early-phase CT. Several participants, however, did have experience in declining a CT offer in the past. As such, the study findings must be cautiously applied to all individuals engaging in decisions about early-phase trial participation as the study sample may have captured a select population with regards to attitudes and beliefs towards clinical research and end-of-life care, as well as their overall decision-making experience. Further, the study was conducted at an urban, academic cancer centre with a highly resourced and active early-phase CT program - the experience of individuals living in rural or remote regions and receiving care from community-based oncology programs may be quite different. The study sample, however, was diverse with regards to gender identity, type of cancer, and yearly income.

Lastly, Canada’s commitment to universal health care and the associated stewardship constraints with regards to approving and funding new cancer therapies creates a unique context regarding the role of early-phase CTs in providing individuals access to novel and expensive treatments. Replicating this study in a non-single payer healthcare system, such as the United States, may offer additional insights.

Practice and policy implications

In the context of presenting an early-phase trial to patients, all clinicians and CT personnel need to be meticulous in their language and how they frame and present such trials, including how they discuss screening procedures and the suitability of a person given the trial’s eligibility criteria. Specifically, there must be an explicit description that the trial is research, not treatment, that the benefits are unknown, and the risks are still being understood. In addition, care is needed so that the often-extensive screening procedures associated with early-phase trials (i.e., blood work, biomarker testing, MRI/CT scans) do not create what has been called “hype and hope” [ 40 ], in which patients do not fully appreciate the potential for harm, including having their quality of life suffer for unknown benefit.

From both a practice and policy perspective, it is imperative that the power imbalances that exist between patients and physicians be acknowledged in early-phase CT accrual. There is enormous trust and confidence placed on physicians and their advice; the perception that one’s physician is enthusiastic about a trial and supportive of participation may unintentionally influence patients’ decisions. As such, it is not enough to simply remind patients that their participation in an early-phase trial is voluntary and they can withdraw at any time; instead, a more in-depth conversation needs to occur about their goals of care, where they are in the cancer trajectory, and the social and structural influences that may impact patients’ decisions. For example, unpacking the complex relationship between clinical care and research and how members of the healthcare team may have dual roles as clinicians and researchers may be important to clarify with patients to support them in making a fully informed decision. Guidelines and training for physicians and CT personnel are also required to promote reflection of how power and influence is manifested in early-phase trial discussions and provide them with the skills and insight to have nuanced conversations that support patients’ relational autonomy in the decision-making process.

One way that the power imbalance between patients, physicians, and CT personnel could be addressed is by co-creating opportunities with patients and patient advocacy groups for greater engagement in the planning and design of early-phase CTs. By including patients as equal partners throughout the trial continuum, from conception to translation, not only will power be better distributed, but problematic issues related to patients’ relational autonomy can be identified and addressed. Such an approach has been put forth by both patient advocacy groups (e.g., Colorectal Cancer Canada) as well as national (e.g., Canadian Cancer Trials Group, N2 Canada) and international research alliances (Network Institute of Health and Care in the United Kingdom). These initiatives promote transparency and education regarding the intent, nature, and potential benefits and risks of CTs among patient communities, as well as increase awareness of on-going trials. Such engagement may also lead to more patient-oriented and pragmatic trial designs that allow a more diverse population of individuals to be recruited and retained in trials, and the inclusion of person-centred outcomes that may reflect the needs and values of patients. A national summit to discuss the ethical challenges posed by modern day early-phase trials is urgently needed, especially for trials of breakthrough therapies (i.e., immunotherapy), whose early promising results can create pressure to rapidly implement costly therapies with limited long-term efficacy and safety data into clinical practice.

Early-phase CTs are an essential step in the development and implementation of new cancer therapies that provide hope to patients and their families who have reached an impasse in their curative treatment journey. In this challenging time, coupled with the potential “renaissance” of new and emerging targeted experimental therapies [ 41 ], it is imperative that patients are supported in their ability to make a fully informed decision about trial participation, without undue influence from social and structural factors. A relational autonomy lens encourages us to recognize the complexity of the early-phase trial decision-making process and view the patient not as a vulnerable individual incapacitated by despair and grasping for straws, but as someone who is to be supported and empowered by their healthcare team and CT personnel.

Data availability

The datasets analysed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

Lillian Siu, Steven Joffe, Amit Oza, Pamela Degendorfer.

This study was funded by The Canadian Institutes of Health Research Catalyst Grant: Ethics (#154143).

Author information

Jonathan Avery and Jennifer A.H. Bell are co-lead authors.

Lynda G. Balneaves is a senior author.

Authors and Affiliations

School of Nursing, University of British Columbia, Vancouver, BC, Canada

Jonathan Avery

Department of Supportive Care Research, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada

Jonathan Avery, Jennifer A.H. Bell, Khotira Baryolay, Gary Rodin & Rinat Nissim

Department of Clinical and Organizational Ethics, University Health Network, Toronto, ON, Canada

Jennifer A.H. Bell

The Institute for Education Research, University Health Network, Toronto, ON, Canada

Department of Psychiatry and Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada

Princess Margaret Cancer Centre, Department of Supportive Care, Research Division, 700 Bay St., 23rd Floor, Toronto, ON, M5G 1Z6, Canada

Global Institute of Psychosocial, Palliative and End-of-Life Care (GIPPEC), Faculty of Medicine, University of Toronto, Toronto, ON, Canada

Department of Psychiatry, Faculty of Medicine, University of Toronto, Toronto, ON, Canada

Gary Rodin & Rinat Nissim

Cancer Experience, University Health Network Cancer Program, University Health Network, Toronto, ON, Canada

Princess Margaret Research Institute, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada

Rady Faculty of Health Sciences, College of Nursing, University of Manitoba, Winnipeg, MB, Canada

Lynda G. Balneaves

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All authors (J.A.H.B., J.A., K.B., G.R., R.N., L.G.B.) were involved in the conceptualization of the research and reviewed, edited, and approved the final manuscript. J.A.H.B. was the principal investigator and oversaw all research activities. J.A. acted as a post-doctoral fellow on the study and led data collection and analysis activities, as well as constructed an initial draft of the manuscript. K.B. was the research analyst and responsible for overall study management.

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Correspondence to Jennifer A.H. Bell .

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Avery, J., Bell, J.A., Baryolay, K. et al. Decision-making and autonomy among participants in early-phase cancer immunotherapy trials: a qualitative study. BMC Cancer 24 , 373 (2024). https://doi.org/10.1186/s12885-024-12119-7

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DOI : https://doi.org/10.1186/s12885-024-12119-7

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