is a case study descriptive research

Case Study vs. Descriptive Approach to Research

What's the difference.

The case study approach and the descriptive approach are two different methods used in research. The case study approach involves in-depth analysis of a specific individual, group, or situation. It aims to provide a detailed understanding of the subject matter by examining various aspects and collecting qualitative data. On the other hand, the descriptive approach focuses on describing and summarizing a larger population or phenomenon. It involves collecting quantitative data through surveys, observations, or experiments to draw general conclusions. While the case study approach provides rich and detailed information, it is limited in terms of generalizability. In contrast, the descriptive approach allows for broader generalizations but may lack the depth and context provided by case studies. Ultimately, the choice between these approaches depends on the research objectives and the nature of the research question.

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Introduction.

Research is a fundamental aspect of any scientific inquiry, aiming to gather information and gain insights into various phenomena. When conducting research, researchers employ different approaches and methodologies to achieve their objectives. Two commonly used approaches are the case study and descriptive approach. While both approaches have their unique attributes, they differ in terms of their focus, data collection methods, and generalizability.

Case Study Approach

The case study approach is a qualitative research method that focuses on in-depth analysis of a specific individual, group, or event. It aims to provide a comprehensive understanding of the subject under investigation by examining its context, history, and unique characteristics. Case studies often involve multiple sources of data, such as interviews, observations, and document analysis, to gather rich and detailed information.

One of the key attributes of the case study approach is its ability to explore complex and unique phenomena that may not be easily captured by other research methods. By delving deep into a specific case, researchers can uncover intricate details and gain a holistic understanding of the subject. This approach is particularly useful when studying rare or exceptional cases, as it allows researchers to examine the intricacies and nuances that may not be apparent in larger-scale studies.

Furthermore, the case study approach enables researchers to generate new hypotheses and theories by closely examining the relationships and patterns within the case. It provides an opportunity for researchers to explore and develop new ideas, which can contribute to the advancement of knowledge in a particular field. Additionally, case studies often involve a longitudinal design, allowing researchers to track changes and developments over time.

However, it is important to note that the case study approach has limitations. Due to its focus on a specific case, the findings may not be easily generalizable to a larger population. The small sample size and unique characteristics of the case may limit the external validity of the findings. Therefore, caution should be exercised when applying the results of a case study to broader contexts.

Descriptive Approach

The descriptive approach, also known as the survey method, aims to describe and analyze the characteristics, behaviors, and opinions of a specific population or sample. It involves collecting data through questionnaires, interviews, or observations, and analyzing the responses to draw conclusions about the population under study. The descriptive approach provides a snapshot of the current state of affairs and allows researchers to identify patterns and trends.

One of the key attributes of the descriptive approach is its ability to provide a broad overview of a population or phenomenon. By collecting data from a large sample, researchers can make generalizations about the population and draw conclusions that are applicable to a wider context. This approach is particularly useful when studying large populations or when the research objective is to describe the prevalence of certain characteristics or behaviors.

Moreover, the descriptive approach allows researchers to quantify data and analyze it statistically. By using statistical techniques, researchers can identify relationships between variables, test hypotheses, and make predictions. This quantitative aspect of the descriptive approach provides a level of objectivity and allows for comparisons across different groups or populations.

However, the descriptive approach also has limitations. It may not capture the complexity and richness of individual cases or unique phenomena. The focus on generalizability may overlook important contextual factors that influence the research topic. Additionally, the reliance on self-report measures in surveys may introduce biases and inaccuracies in the data collected.

While the case study and descriptive approaches differ in their focus and data collection methods, they both contribute to the field of research in their own ways. The case study approach provides in-depth insights into specific cases, allowing researchers to explore complex phenomena and generate new hypotheses. On the other hand, the descriptive approach provides a broader overview of populations, enabling researchers to make generalizations and identify patterns.

Both approaches have their strengths and weaknesses, and the choice between them depends on the research objectives and the nature of the phenomenon under investigation. Researchers should carefully consider the specific research question, the available resources, and the desired level of generalizability when selecting the appropriate approach.

In conclusion, the case study and descriptive approaches are two distinct research methodologies that offer different perspectives and insights. The case study approach allows for in-depth analysis of specific cases, providing rich and detailed information. On the other hand, the descriptive approach provides a broader overview of populations, allowing for generalizations and statistical analysis. Both approaches have their merits and limitations, and researchers should choose the most appropriate approach based on their research objectives and the nature of the phenomenon under investigation.

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Methodology

• What Is a Case Study? | Definition, Examples & Methods

What Is a Case Study? | Definition, Examples & Methods

Published on May 8, 2019 by Shona McCombes . Revised on November 20, 2023.

A case study is a detailed study of a specific subject, such as a person, group, place, event, organization, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research.

A case study research design usually involves qualitative methods , but quantitative methods are sometimes also used. Case studies are good for describing , comparing, evaluating and understanding different aspects of a research problem .

Table of contents

When to do a case study, step 1: select a case, step 2: build a theoretical framework, step 3: collect your data, step 4: describe and analyze the case, other interesting articles.

A case study is an appropriate research design when you want to gain concrete, contextual, in-depth knowledge about a specific real-world subject. It allows you to explore the key characteristics, meanings, and implications of the case.

Case studies are often a good choice in a thesis or dissertation . They keep your project focused and manageable when you don’t have the time or resources to do large-scale research.

You might use just one complex case study where you explore a single subject in depth, or conduct multiple case studies to compare and illuminate different aspects of your research problem.

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Once you have developed your problem statement and research questions , you should be ready to choose the specific case that you want to focus on. A good case study should have the potential to:

• Provide new or unexpected insights into the subject
• Challenge or complicate existing assumptions and theories
• Propose practical courses of action to resolve a problem
• Open up new directions for future research

TipIf your research is more practical in nature and aims to simultaneously investigate an issue as you solve it, consider conducting action research instead.

Unlike quantitative or experimental research , a strong case study does not require a random or representative sample. In fact, case studies often deliberately focus on unusual, neglected, or outlying cases which may shed new light on the research problem.

Example of an outlying case studyIn the 1960s the town of Roseto, Pennsylvania was discovered to have extremely low rates of heart disease compared to the US average. It became an important case study for understanding previously neglected causes of heart disease.

However, you can also choose a more common or representative case to exemplify a particular category, experience or phenomenon.

Example of a representative case studyIn the 1920s, two sociologists used Muncie, Indiana as a case study of a typical American city that supposedly exemplified the changing culture of the US at the time.

While case studies focus more on concrete details than general theories, they should usually have some connection with theory in the field. This way the case study is not just an isolated description, but is integrated into existing knowledge about the topic. It might aim to:

• Exemplify a theory by showing how it explains the case under investigation
• Expand on a theory by uncovering new concepts and ideas that need to be incorporated
• Challenge a theory by exploring an outlier case that doesn’t fit with established assumptions

To ensure that your analysis of the case has a solid academic grounding, you should conduct a literature review of sources related to the topic and develop a theoretical framework . This means identifying key concepts and theories to guide your analysis and interpretation.

There are many different research methods you can use to collect data on your subject. Case studies tend to focus on qualitative data using methods such as interviews , observations , and analysis of primary and secondary sources (e.g., newspaper articles, photographs, official records). Sometimes a case study will also collect quantitative data.

Example of a mixed methods case studyFor a case study of a wind farm development in a rural area, you could collect quantitative data on employment rates and business revenue, collect qualitative data on local people’s perceptions and experiences, and analyze local and national media coverage of the development.

The aim is to gain as thorough an understanding as possible of the case and its context.

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In writing up the case study, you need to bring together all the relevant aspects to give as complete a picture as possible of the subject.

How you report your findings depends on the type of research you are doing. Some case studies are structured like a standard scientific paper or thesis , with separate sections or chapters for the methods , results and discussion .

Others are written in a more narrative style, aiming to explore the case from various angles and analyze its meanings and implications (for example, by using textual analysis or discourse analysis ).

In all cases, though, make sure to give contextual details about the case, connect it back to the literature and theory, and discuss how it fits into wider patterns or debates.

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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• 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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Descriptive Research in Psychology

Sometimes you need to dig deeper than the pure statistics

John Loeppky is a freelance journalist based in Regina, Saskatchewan, Canada, who has written about disability and health for outlets of all kinds.

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Types of Descriptive Research and the Methods Used

• Advantages & Limitations of Descriptive Research

Best Practices for Conducting Descriptive Research

Descriptive research is one of the key tools needed in any psychology researcher’s toolbox in order to create and lead a project that is both equitable and effective. Because psychology, as a field, loves definitions, let’s start with one. The University of Minnesota’s Introduction to Psychology defines this type of research as one that is “...designed to provide a snapshot of the current state of affairs.” That's pretty broad, so what does that mean in practice? Dr. Heather Derry-Vick (PhD) , an assistant professor in psychiatry at Hackensack Meridian School of Medicine, helps us put it into perspective. "Descriptive research really focuses on defining, understanding, and measuring a phenomenon or an experience," she says. "Not trying to change a person's experience or outcome, or even really looking at the mechanisms for why that might be happening, but more so describing an experience or a process as it unfolds naturally.”

Within the descriptive research methodology there are multiple types, including the following.

Descriptive Survey Research

This involves going beyond a typical tool like a LIkert Scale —where you typically place your response to a prompt on a one to five scale. We already know that scales like this can be ineffective, particularly when studying pain, for example.

When that's the case, using a descriptive methodology can help dig deeper into how a person is thinking, feeling, and acting rather than simply quantifying it in a way that might be unclear or confusing.

Descriptive Observational Research

Think of observational research like an ethically-focused version of people-watching. One example would be watching the patterns of children on a playground—perhaps when looking at a concept like risky play or seeking to observe social behaviors between children of different ages.

Descriptive Case Study Research

A descriptive approach to a case study is akin to a biography of a person, honing in on the experiences of a small group to extrapolate to larger themes. We most commonly see descriptive case studies when those in the psychology field are using past clients as an example to illustrate a point.

Correlational Descriptive Research

While descriptive research is often about the here and now, this form of the methodology allows researchers to make connections between groups of people. As an example from her research, Derry-Vick says she uses this method to identify how gender might play a role in cancer scan anxiety, aka scanxiety.

Dr. Derry-Vick's research uses surveys and interviews to get a sense of how cancer patients are feeling and what they are experiencing both in the course of their treatment and in the lead-up to their next scan, which can be a significant source of stress.

David Marlon, PsyD, MBA , who works as a clinician and as CEO at Vegas Stronger, and whose research focused on leadership styles at community-based clinics, says that using descriptive research allowed him to get beyond the numbers.

In his case, that includes data points like how many unhoused people found stable housing over a certain period or how many people became drug-free—and identify the reasons for those changes.

Those [data points] are some practical, quantitative tools that are helpful. But when I question them on how safe they feel, when I question them on the depth of the bond or the therapeutic alliance, when I talk to them about their processing of traumas,  wellbeing...these are things that don't really fall on to a yes, no, or even on a Likert scale.

For the portion of his thesis that was focused on descriptive research, Marlon used semi-structured interviews to look at the how and the why of transformational leadership and its impact on clinics’ clients and staff.

Advantages & Limitations of Descriptive Research

So, if the advantages of using descriptive research include that it centers the research participants, gives us a clear picture of what is happening to a person in a particular moment,  and gives us very nuanced insights into how a particular situation is being perceived by the very person affected, are there drawbacks? Yes, there are. Dr. Derry-Vick says that it’s important to keep in mind that just because descriptive research tells us something is happening doesn’t mean it necessarily leads us to the resolution of a given problem.

I think that, by design, the descriptive research might not tell you why a phenomenon is happening. So it might tell you, very well, how often it's happening, or what the levels are, or help you understand it in depth. But that may or may not always tell you information about the causes or mechanisms for why something is happening.

Another limitation she identifies is that it also can’t tell you, on its own, whether a particular treatment pathway is having the desired effect.

“Descriptive research in and of itself can't really tell you whether a specific approach is going to be helpful until you take in a different approach to actually test it.”

Marlon, who believes in a multi-disciplinary approach, says that his subfield—addictions—is one where descriptive research had its limits, but helps readers go beyond preconceived notions of what addictions treatment looks and feels like when it is effective. “If we talked to and interviewed and got descriptive information from the clinicians and the clients, a much more precise picture would be painted, showing the need for a client's specific multidisciplinary approach augmented with a variety of modalities," he says. "If you tried to look at my discipline in a pure quantitative approach , it wouldn't begin to tell the real story.”

Because you’re controlling far fewer variables than other forms of research, it’s important to identify whether those you are describing, your study participants, should be informed that they are part of a study.

For example, if you’re observing and describing who is buying what in a grocery store to identify patterns, then you might not need to identify yourself.

However, if you’re asking people about their fear of certain treatment, or how their marginalized identities impact their mental health in a particular way, there is far more of a pressure to think deeply about how you, as the researcher, are connected to the people you are researching.

Many descriptive research projects use interviews as a form of research gathering and, as a result, descriptive research that is focused on this type of data gathering also has ethical and practical concerns attached. Thankfully, there are plenty of guides from established researchers about how to best conduct these interviews and/or formulate surveys .

While descriptive research has its limits, it is commonly used by researchers to get a clear vantage point on what is happening in a given situation.

Tools like surveys, interviews, and observation are often employed to dive deeper into a given issue and really highlight the human element in psychological research. At its core, descriptive research is rooted in a collaborative style that allows deeper insights when used effectively.

University of Minnesota. Introduction to Psychology .

By John Loeppky John Loeppky is a freelance journalist based in Regina, Saskatchewan, Canada, who has written about disability and health for outlets of all kinds.

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Distinguishing case study as a research method from case reports as a publication type

The purpose of this editorial is to distinguish between case reports and case studies. In health, case reports are familiar ways of sharing events or efforts of intervening with single patients with previously unreported features. As a qualitative methodology, case study research encompasses a great deal more complexity than a typical case report and often incorporates multiple streams of data combined in creative ways. The depth and richness of case study description helps readers understand the case and whether findings might be applicable beyond that setting.

Single-institution descriptive reports of library activities are often labeled by their authors as “case studies.” By contrast, in health care, single patient retrospective descriptions are published as “case reports.” Both case reports and case studies are valuable to readers and provide a publication opportunity for authors. A previous editorial by Akers and Amos about improving case studies addresses issues that are more common to case reports; for example, not having a review of the literature or being anecdotal, not generalizable, and prone to various types of bias such as positive outcome bias [ 1 ]. However, case study research as a qualitative methodology is pursued for different purposes than generalizability. The authors’ purpose in this editorial is to clearly distinguish between case reports and case studies. We believe that this will assist authors in describing and designating the methodological approach of their publications and help readers appreciate the rigor of well-executed case study research.

Case reports often provide a first exploration of a phenomenon or an opportunity for a first publication by a trainee in the health professions. In health care, case reports are familiar ways of sharing events or efforts of intervening with single patients with previously unreported features. Another type of study categorized as a case report is an “N of 1” study or single-subject clinical trial, which considers an individual patient as the sole unit of observation in a study investigating the efficacy or side effect profiles of different interventions. Entire journals have evolved to publish case reports, which often rely on template structures with limited contextualization or discussion of previous cases. Examples that are indexed in MEDLINE include the American Journal of Case Reports , BMJ Case Reports, Journal of Medical Case Reports, and Journal of Radiology Case Reports . Similar publications appear in veterinary medicine and are indexed in CAB Abstracts, such as Case Reports in Veterinary Medicine and Veterinary Record Case Reports .

As a qualitative methodology, however, case study research encompasses a great deal more complexity than a typical case report and often incorporates multiple streams of data combined in creative ways. Distinctions include the investigator’s definitions and delimitations of the case being studied, the clarity of the role of the investigator, the rigor of gathering and combining evidence about the case, and the contextualization of the findings. Delimitation is a term from qualitative research about setting boundaries to scope the research in a useful way rather than describing the narrow scope as a limitation, as often appears in a discussion section. The depth and richness of description helps readers understand the situation and whether findings from the case are applicable to their settings.

CASE STUDY AS A RESEARCH METHODOLOGY

Case study as a qualitative methodology is an exploration of a time- and space-bound phenomenon. As qualitative research, case studies require much more from their authors who are acting as instruments within the inquiry process. In the case study methodology, a variety of methodological approaches may be employed to explain the complexity of the problem being studied [ 2 , 3 ].

Leading authors diverge in their definitions of case study, but a qualitative research text introduces case study as follows:

Case study research is defined as a qualitative approach in which the investigator explores a real-life, contemporary bounded system (a case) or multiple bound systems (cases) over time, through detailed, in-depth data collection involving multiple sources of information, and reports a case description and case themes. The unit of analysis in the case study might be multiple cases (a multisite study) or a single case (a within-site case study). [ 4 ]

Methodologists writing core texts on case study research include Yin [ 5 ], Stake [ 6 ], and Merriam [ 7 ]. The approaches of these three methodologists have been compared by Yazan, who focused on six areas of methodology: epistemology (beliefs about ways of knowing), definition of cases, design of case studies, and gathering, analysis, and validation of data [ 8 ]. For Yin, case study is a method of empirical inquiry appropriate to determining the “how and why” of phenomena and contributes to understanding phenomena in a holistic and real-life context [ 5 ]. Stake defines a case study as a “well-bounded, specific, complex, and functioning thing” [ 6 ], while Merriam views “the case as a thing, a single entity, a unit around which there are boundaries” [ 7 ].

Case studies are ways to explain, describe, or explore phenomena. Comments from a quantitative perspective about case studies lacking rigor and generalizability fail to consider the purpose of the case study and how what is learned from a case study is put into practice. Rigor in case studies comes from the research design and its components, which Yin outlines as (a) the study’s questions, (b) the study’s propositions, (c) the unit of analysis, (d) the logic linking the data to propositions, and (e) the criteria for interpreting the findings [ 5 ]. Case studies should also provide multiple sources of data, a case study database, and a clear chain of evidence among the questions asked, the data collected, and the conclusions drawn [ 5 ].

Sources of evidence for case studies include interviews, documentation, archival records, direct observations, participant-observation, and physical artifacts. One of the most important sources for data in qualitative case study research is the interview [ 2 , 3 ]. In addition to interviews, documents and archival records can be gathered to corroborate and enhance the findings of the study. To understand the phenomenon or the conditions that created it, direct observations can serve as another source of evidence and can be conducted throughout the study. These can include the use of formal and informal protocols as a participant inside the case or an external or passive observer outside of the case [ 5 ]. Lastly, physical artifacts can be observed and collected as a form of evidence. With these multiple potential sources of evidence, the study methodology includes gathering data, sense-making, and triangulating multiple streams of data. Figure 1 shows an example in which data used for the case started with a pilot study to provide additional context to guide more in-depth data collection and analysis with participants.

Key sources of data for a sample case study

VARIATIONS ON CASE STUDY METHODOLOGY

Case study methodology is evolving and regularly reinterpreted. Comparative or multiple case studies are used as a tool for synthesizing information across time and space to research the impact of policy and practice in various fields of social research [ 9 ]. Because case study research is in-depth and intensive, there have been efforts to simplify the method or select useful components of cases for focused analysis. Micro-case study is a term that is occasionally used to describe research on micro-level cases [ 10 ]. These are cases that occur in a brief time frame, occur in a confined setting, and are simple and straightforward in nature. A micro-level case describes a clear problem of interest. Reporting is very brief and about specific points. The lack of complexity in the case description makes obvious the “lesson” that is inherent in the case; although no definitive “solution” is necessarily forthcoming, making the case useful for discussion. A micro-case write-up can be distinguished from a case report by its focus on briefly reporting specific features of a case or cases to analyze or learn from those features.

DATABASE INDEXING OF CASE REPORTS AND CASE STUDIES

Disciplines such as education, psychology, sociology, political science, and social work regularly publish rich case studies that are relevant to particular areas of health librarianship. Case reports and case studies have been defined as publication types or subject terms by several databases that are relevant to librarian authors: MEDLINE, PsycINFO, CINAHL, and ERIC. Library, Information Science & Technology Abstracts (LISTA) does not have a subject term or publication type related to cases, despite many being included in the database. Whereas “Case Reports” are the main term used by MEDLINE’s Medical Subject Headings (MeSH) and PsycINFO’s thesaurus, CINAHL and ERIC use “Case Studies.”

Case reports in MEDLINE and PsycINFO focus on clinical case documentation. In MeSH, “Case Reports” as a publication type is specific to “clinical presentations that may be followed by evaluative studies that eventually lead to a diagnosis” [ 11 ]. “Case Histories,” “Case Studies,” and “Case Study” are all entry terms mapping to “Case Reports”; however, guidance to indexers suggests that “Case Reports” should not be applied to institutional case reports and refers to the heading “Organizational Case Studies,” which is defined as “descriptions and evaluations of specific health care organizations” [ 12 ].

PsycINFO’s subject term “Case Report” is “used in records discussing issues involved in the process of conducting exploratory studies of single or multiple clinical cases.” The Methodology index offers clinical and non-clinical entries. “Clinical Case Study” is defined as “case reports that include disorder, diagnosis, and clinical treatment for individuals with mental or medical illnesses,” whereas “Non-clinical Case Study” is a “document consisting of non-clinical or organizational case examples of the concepts being researched or studied. The setting is always non-clinical and does not include treatment-related environments” [ 13 ].

Both CINAHL and ERIC acknowledge the depth of analysis in case study methodology. The CINAHL scope note for the thesaurus term “Case Studies” distinguishes between the document and the methodology, though both use the same term: “a review of a particular condition, disease, or administrative problem. Also, a research method that involves an in-depth analysis of an individual, group, institution, or other social unit. For material that contains a case study, search for document type: case study.” The ERIC scope note for the thesaurus term “Case Studies” is simple: “detailed analyses, usually focusing on a particular problem of an individual, group, or organization” [ 14 ].

PUBLICATION OF CASE STUDY RESEARCH IN LIBRARIANSHIP

We call your attention to a few examples published as case studies in health sciences librarianship to consider how their characteristics fit with the preceding definitions of case reports or case study research. All present some characteristics of case study research, but their treatment of the research questions, richness of description, and analytic strategies vary in depth and, therefore, diverge at some level from the qualitative case study research approach. This divergence, particularly in richness of description and analysis, may have been constrained by the publication requirements.

As one example, a case study by Janke and Rush documented a time- and context-bound collaboration involving a librarian and a nursing faculty member [ 15 ]. Three objectives were stated: (1) describing their experience of working together on an interprofessional research team, (2) evaluating the value of the librarian role from librarian and faculty member perspectives, and (3) relating findings to existing literature. Elements that signal the qualitative nature of this case study are that the authors were the research participants and their use of the term “evaluation” is reflection on their experience. This reads like a case study that could have been enriched by including other types of data gathered from others engaging with this team to broaden the understanding of the collaboration.

As another example, the description of the academic context is one of the most salient components of the case study written by Clairoux et al., which had the objectives of (1) describing the library instruction offered and learning assessments used at a single health sciences library and (2) discussing the positive outcomes of instruction in that setting [ 16 ]. The authors focus on sharing what the institution has done more than explaining why this institution is an exemplar to explore a focused question or understand the phenomenon of library instruction. However, like a case study, the analysis brings together several streams of data including course attendance, online material page views, and some discussion of results from surveys. This paper reads somewhat in between an institutional case report and a case study.

The final example is a single author reporting on a personal experience of creating and executing the role of research informationist for a National Institutes of Health (NIH)–funded research team [ 17 ]. There is a thoughtful review of the informationist literature and detailed descriptions of the institutional context and the process of gaining access to and participating in the new role. However, the motivating question in the abstract does not seem to be fully addressed through analysis from either the reflective perspective of the author as the research participant or consideration of other streams of data from those involved in the informationist experience. The publication reads more like a case report about this informationist’s experience than a case study that explores the research informationist experience through the selection of this case.

All of these publications are well written and useful for their intended audiences, but in general, they are much shorter and much less rich in depth than case studies published in social sciences research. It may be that the authors have been constrained by word counts or page limits. For example, the submission category for Case Studies in the Journal of the Medical Library Association (JMLA) limited them to 3,000 words and defined them as “articles describing the process of developing, implementing, and evaluating a new service, program, or initiative, typically in a single institution or through a single collaborative effort” [ 18 ]. This definition’s focus on novelty and description sounds much more like the definition of case report than the in-depth, detailed investigation of a time- and space-bound problem that is often examined through case study research.

Problem-focused or question-driven case study research would benefit from the space provided for Original Investigations that employ any type of quantitative or qualitative method of analysis. One of the best examples in the JMLA of an in-depth multiple case study that was authored by a librarian who published the findings from her doctoral dissertation represented all the elements of a case study. In eight pages, she provided a theoretical basis for the research question, a pilot study, and a multiple case design, including integrated data from interviews and focus groups [ 19 ].

We have distinguished between case reports and case studies primarily to assist librarians who are new to research and critical appraisal of case study methodology to recognize the features that authors use to describe and designate the methodological approaches of their publications. For researchers who are new to case research methodology and are interested in learning more, Hancock and Algozzine provide a guide [ 20 ].

We hope that JMLA readers appreciate the rigor of well-executed case study research. We believe that distinguishing between descriptive case reports and analytic case studies in the journal’s submission categories will allow the depth of case study methodology to increase. We also hope that authors feel encouraged to pursue submitting relevant case studies or case reports for future publication.

Editor’s note: In response to this invited editorial, the Journal of the Medical Library Association will consider manuscripts employing rigorous qualitative case study methodology to be Original Investigations (fewer than 5,000 words), whereas manuscripts describing the process of developing, implementing, and assessing a new service, program, or initiative—typically in a single institution or through a single collaborative effort—will be considered to be Case Reports (formerly known as Case Studies; fewer than 3,000 words).

Research Writing and Analysis

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Writing a Case Study

What is a case study?

A Case study is: 

• An in-depth research design that primarily uses a qualitative methodology but sometimes​​ includes quantitative methodology.
• Used to examine an identifiable problem confirmed through research.
• Used to investigate an individual, group of people, organization, or event.
• Used to mostly answer "how" and "why" questions.

What are the different types of case studies?

Note: These are the primary case studies. As you continue to research and learn

about case studies you will begin to find a robust list of different types. 

Who are your case study participants?

What is triangulation ? 

Validity and credibility are an essential part of the case study. Therefore, the researcher should include triangulation to ensure trustworthiness while accurately reflecting what the researcher seeks to investigate.

How to write a Case Study?

When developing a case study, there are different ways you could present the information, but remember to include the five parts for your case study.

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• Descriptive Research Designs: Types, Examples & Methods

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

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

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

What is Descriptive Research?

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

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

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

What Are The Types of Descriptive Research?

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

• Descriptive-survey

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

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

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

• Descriptive-normative survey

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

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

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

• Descriptive-status

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

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

• Descriptive-analysis

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

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

• Descriptive classification

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

• Descriptive-comparative

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

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

• Correlative Survey

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

Examples of Descriptive Research

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

• Comparing Student Performance:

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

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

• Scientific Classification

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

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

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

• Human Behavior

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

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

What are the Characteristics of Descriptive Research?  

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

• Quantitativeness

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

• Qualitativeness

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

• Uncontrolled variables

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

• The basis for further research

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

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

Why Use Descriptive Research Design?  

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

• Define subject characteristics :

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

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

• Measure Data Trends

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

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

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

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

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

• Validate existing conditions

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

• Conducted Overtime

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

What are the Disadvantages of Descriptive Research?  

• Response and Non-response Bias

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

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

What are the Data Collection Methods in Descriptive Research?  

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

1. Observational Method

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

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

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

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

2. Case Study Method

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

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

3. Survey Research

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

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

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

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

What Are The Differences Between Descriptive and Correlational Research?  

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

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

Correlational research may be used in 2 situations;

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

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

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

• Definitions :

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

• Characteristics :

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

• Predictions :

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

Descriptive Research vs. Causal Research

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

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

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

Descriptive Research vs. Analytical Research

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

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

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

Descriptive Research vs. Exploratory Research

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

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

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

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

Descriptive Research vs. Experimental Research

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

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

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

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

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

Descriptive Research vs. Explanatory Research

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

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

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

Descriptive Research vs. Inferential Research

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

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

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

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

Related – Inferential Statistics: Definition, Types + Examples

Conclusion  

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

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

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

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

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

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

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

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

Free eBook: 2024 global market research trends report

What is descriptive research?

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

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

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

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

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

Descriptive research design

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

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

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

Descriptive research characteristics

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

Here are a few of the things to consider:

Measure data trends with statistical outcomes

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

Descriptive research design is ideal for further research

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

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

Uncontrolled variables

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

It’s carried out in a natural environment

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

Data can be gathered using survey questions or online surveys.

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

Descriptive research allows for cross sectional study

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

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

Descriptive research advantages

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

Cost effectiveness

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

Multiple types of data can be collected

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

Descriptive research disadvantages

Potential reliability issues.

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

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

Potential limitations

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

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

Descriptive research methods

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

Use case studies

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

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

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

Use observational methods

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

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

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

Use survey research

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

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

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

Descriptive research examples

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

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

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

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

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

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

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

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

Where Qualtrics helps with descriptive research

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

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

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

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Module 2: Research and Ethics in Abnormal Psychology

Descriptive research and case studies, learning objectives.

• Explain the importance and uses of descriptive research, especially case studies, in studying abnormal behavior

Types of Research Methods

There are many research methods available to psychologists in their efforts to understand, describe, and explain behavior and the cognitive and biological processes that underlie it. Some methods rely on observational techniques. Other approaches involve interactions between the researcher and the individuals who are being studied—ranging from a series of simple questions; to extensive, in-depth interviews; to well-controlled experiments.

The three main categories of psychological research are descriptive, correlational, and experimental research. Research studies that do not test specific relationships between variables are called descriptive, or qualitative, studies . These studies are used to describe general or specific behaviors and attributes that are observed and measured. In the early stages of research, it might be difficult to form a hypothesis, especially when there is not any existing literature in the area. In these situations designing an experiment would be premature, as the question of interest is not yet clearly defined as a hypothesis. Often a researcher will begin with a non-experimental approach, such as a descriptive study, to gather more information about the topic before designing an experiment or correlational study to address a specific hypothesis. Descriptive research is distinct from correlational research , in which psychologists formally test whether a relationship exists between two or more variables. Experimental research goes a step further beyond descriptive and correlational research and randomly assigns people to different conditions, using hypothesis testing to make inferences about how these conditions affect behavior. It aims to determine if one variable directly impacts and causes another. Correlational and experimental research both typically use hypothesis testing, whereas descriptive research does not.

Each of these research methods has unique strengths and weaknesses, and each method may only be appropriate for certain types of research questions. For example, studies that rely primarily on observation produce incredible amounts of information, but the ability to apply this information to the larger population is somewhat limited because of small sample sizes. Survey research, on the other hand, allows researchers to easily collect data from relatively large samples. While surveys allow results to be generalized to the larger population more easily, the information that can be collected on any given survey is somewhat limited and subject to problems associated with any type of self-reported data. Some researchers conduct archival research by using existing records. While existing records can be a fairly inexpensive way to collect data that can provide insight into a number of research questions, researchers using this approach have no control on how or what kind of data was collected.

Correlational research can find a relationship between two variables, but the only way a researcher can claim that the relationship between the variables is cause and effect is to perform an experiment. In experimental research, which will be discussed later, there is a tremendous amount of control over variables of interest. While performing an experiment is a powerful approach, experiments are often conducted in very artificial settings, which calls into question the validity of experimental findings with regard to how they would apply in real-world settings. In addition, many of the questions that psychologists would like to answer cannot be pursued through experimental research because of ethical concerns.

The three main types of descriptive studies are case studies, naturalistic observation, and surveys.

Clinical or Case Studies

Psychologists can use a detailed description of one person or a small group based on careful observation.  Case studies  are intensive studies of individuals and have commonly been seen as a fruitful way to come up with hypotheses and generate theories. Case studies add descriptive richness. Case studies are also useful for formulating concepts, which are an important aspect of theory construction. Through fine-grained knowledge and description, case studies can fully specify the causal mechanisms in a way that may be harder in a large study.

Sigmund Freud   developed  many theories from case studies (Anna O., Little Hans, Wolf Man, Dora, etc.). F or example, he conducted a case study of a man, nicknamed “Rat Man,”  in which he claimed that this patient had been cured by psychoanalysis.  T he nickname derives from the fact that among the patient’s many compulsions, he had an obsession with nightmarish fantasies about rats. 

Today, more commonly, case studies reflect an up-close, in-depth, and detailed examination of an individual’s course of treatment. Case studies typically include a complete history of the subject’s background and response to treatment. From the particular client’s experience in therapy, the therapist’s goal is to provide information that may help other therapists who treat similar clients.

Case studies are generally a single-case design, but can also be a multiple-case design, where replication instead of sampling is the criterion for inclusion. Like other research methodologies within psychology, the case study must produce valid and reliable results in order to be useful for the development of future research. Distinct advantages and disadvantages are associated with the case study in psychology.

A commonly described limit of case studies is that they do not lend themselves to generalizability . The other issue is that the case study is subject to the bias of the researcher in terms of how the case is written, and that cases are chosen because they are consistent with the researcher’s preconceived notions, resulting in biased research. Another common problem in case study research is that of reconciling conflicting interpretations of the same case history.

Despite these limitations, there are advantages to using case studies. One major advantage of the case study in psychology is the potential for the development of novel hypotheses of the  cause of abnormal behavior   for later testing. Second, the case study can provide detailed descriptions of specific and rare cases and help us study unusual conditions that occur too infrequently to study with large sample sizes. The major disadvantage is that case studies cannot be used to determine causation, as is the case in experimental research, where the factors or variables hypothesized to play a causal role are manipulated or controlled by the researcher. 

Single-Case Experimental Designs

The lack of control available in the traditional case study research strategy led researchers to develop more sophisticated methods, such as single-subject research, which provides the statistical framework for making inferences from quantitative case-study data.

Figure 1 . Antipsychotics are the treatment of choice in managing schizophrenia and other psychotic disorders. Several major trials have been conducted examining the clinical difference between typical antipsychotics and atypical antipsychotics and how the selection may affect the quality of life.

The single-case experimental design  (sometimes called  single-participant research designs ), is particularly useful for studies of treatment effectiveness.  In  single-case experimental designs ,  the same  research participant  serves as the subject in both the experimental and control conditions.  One of the most common forms of the single-case experimental design is the A-B-A-B design, or  reversal design ,  reflecting the alternation between conditions, or phases A and B. The  AB design is a two-part or phase design composed of a baseline (“A” phase) with no changes, and a treatment or intervention (“B”) phase.  If there is a change, then the treatment may be said to have had an effect. However, it is subject to many possible competing hypotheses, making strong conclusions difficult. The A-B-A-B design, or reversal design, is a variant on the AB design. It introduces ways to control for the competing hypotheses and allows for stronger conclusions. T he reversal design (ABAB) is the most powerful of the single-subject research designs because it shows a strong reversal from baseline (“A”) to treatment (“B”) and back again. In an ABAB design, researchers observe behaviors in the “A” phase, institute treatment in the “B” phase, and then repeat the process. If the variable returns to baseline measure without treatment and then resumes its effects when reapplied, the researcher can have greater confidence in the efficacy of that treatment. However, many interventions cannot be reversed for ethical reasons (e.g., involving self-injurious behavior like smoking).  It may be unethical to end an experiment on a baseline measure if the treatment is self-sustaining and highly beneficial and/or related to health. Control condition participants may also deserve the benefits of research once all data has been collected. It is a researcher’s ethical duty to maximize benefits and to ensure that all participants have access to those benefits when possible.

Figure 2. The investigator looks for evidence that the change in the observed behavior occurred coincident with treatment. If the problem behavior declines whenever treatment is introduced (during the first and second treatment phases) but returns (is “reversed”) to baseline levels during the reversal phase, the experimenter can be reasonably confident the treatment had the intended effect.

Link to Learning: Famous Case Studies

Some well-known case studies that related to abnormal psychology include the following:

• Harlow— Phineas Gage
• Breuer & Freud (1895)— Anna O.
• Cleckley’s case studies: on psychopathy ( The Mask of Sanity ) (1941) and multiple personality disorder ( The Three Faces of Eve ) (1957)
• Freud and  Little Hans
• Freud and the  Rat Man
• John Money and the  John/Joan case
• Genie (feral child)
• Piaget’s studies
• Rosenthal’s book on the  murder of Kitty Genovese
• Washoe (sign language)
• Patient H.M.

Naturalistic Observation

If you want to understand how behavior occurs, one of the best ways to gain information is to simply observe the behavior in its natural context. However, people might change their behavior in unexpected ways if they know they are being observed. How do researchers obtain accurate information when people tend to hide their natural behavior? As an example, imagine that your professor asks everyone in your class to raise their hand if they always wash their hands after using the restroom. Chances are that almost everyone in the classroom will raise their hand, but do you think hand washing after every trip to the restroom is really that universal?

This is very similar to the phenomenon mentioned earlier in this module: many individuals do not feel comfortable answering a question honestly. But if we are committed to finding out the facts about handwashing, we have other options available to us.

Suppose we send a researcher to a school playground to observe how aggressive or socially anxious children interact with peers. Will our observer blend into the playground environment by wearing a white lab coat, sitting with a clipboard, and staring at the swings? We want our researcher to be inconspicuous and unobtrusively positioned—perhaps pretending to be a school monitor while secretly recording the relevant information. This type of observational study is called naturalistic observation : observing behavior in its natural setting. To better understand peer exclusion, Suzanne Fanger collaborated with colleagues at the University of Texas to observe the behavior of preschool children on a playground. How did the observers remain inconspicuous over the duration of the study? They equipped a few of the children with wireless microphones (which the children quickly forgot about) and observed while taking notes from a distance. Also, the children in that particular preschool (a “laboratory preschool”) were accustomed to having observers on the playground (Fanger, Frankel, & Hazen, 2012).

Figure 3 . In naturalistic observation, psychologists take their research into the streets, homes, restaurants, schools, and other settings where behavior can be directly observed.

It is critical that the observer be as unobtrusive and as inconspicuous as possible: when people know they are being watched, they are less likely to behave naturally. For example, psychologists have spent weeks observing the behavior of homeless people on the streets, in train stations, and bus terminals. They try to ensure that their naturalistic observations are unobtrusive, so as to minimize interference with the behavior they observe. Nevertheless, the presence of the observer may distort the behavior that is observed, and this must be taken into consideration (Figure 1).

The greatest benefit of naturalistic observation is the validity, or accuracy, of information collected unobtrusively in a natural setting. Having individuals behave as they normally would in a given situation means that we have a higher degree of ecological validity, or realism, than we might achieve with other research approaches. Therefore, our ability to generalize the findings of the research to real-world situations is enhanced. If done correctly, we need not worry about people modifying their behavior simply because they are being observed. Sometimes, people may assume that reality programs give us a glimpse into authentic human behavior. However, the principle of inconspicuous observation is violated as reality stars are followed by camera crews and are interviewed on camera for personal confessionals. Given that environment, we must doubt how natural and realistic their behaviors are.

The major downside of naturalistic observation is that they are often difficult to set up and control. Although something as simple as observation may seem like it would be a part of all research methods, participant observation is a distinct methodology that involves the researcher embedding themselves into a group in order to study its dynamics. For example, Festinger, Riecken, and Shacter (1956) were very interested in the psychology of a particular cult. However, this cult was very secretive and wouldn’t grant interviews to outside members. So, in order to study these people, Festinger and his colleagues pretended to be cult members, allowing them access to the behavior and psychology of the cult. Despite this example, it should be noted that the people being observed in a participant observation study usually know that the researcher is there to study them. [1]

Another potential problem in observational research is observer bias . Generally, people who act as observers are closely involved in the research project and may unconsciously skew their observations to fit their research goals or expectations. To protect against this type of bias, researchers should have clear criteria established for the types of behaviors recorded and how those behaviors should be classified. In addition, researchers often compare observations of the same event by multiple observers, in order to test inter-rater reliability : a measure of reliability that assesses the consistency of observations by different observers.

Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally (Figure 3). Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.

Surveys allow researchers to gather data from larger samples than may be afforded by other research methods . A sample is a subset of individuals selected from a population , which is the overall group of individuals that the researchers are interested in. Researchers study the sample and seek to generalize their findings to the population.

Figure 4 . Surveys can be administered in a number of ways, including electronically administered research, like the survey shown here. (credit: Robert Nyman)

There is both strength and weakness in surveys when compared to case studies. By using surveys, we can collect information from a larger sample of people. A larger sample is better able to reflect the actual diversity of the population, thus allowing better generalizability. Therefore, if our sample is sufficiently large and diverse, we can assume that the data we collect from the survey can be generalized to the larger population with more certainty than the information collected through a case study. However, given the greater number of people involved, we are not able to collect the same depth of information on each person that would be collected in a case study.

Another potential weakness of surveys is something we touched on earlier in this module: people do not always give accurate responses. They may lie, misremember, or answer questions in a way that they think makes them look good. For example, people may report drinking less alcohol than is actually the case.

Any number of research questions can be answered through the use of surveys. One real-world example is the research conducted by Jenkins, Ruppel, Kizer, Yehl, and Griffin (2012) about the backlash against the U.S. Arab-American community following the terrorist attacks of September 11, 2001. Jenkins and colleagues wanted to determine to what extent these negative attitudes toward Arab-Americans still existed nearly a decade after the attacks occurred. In one study, 140 research participants filled out a survey with 10 questions, including questions asking directly about the participant’s overt prejudicial attitudes toward people of various ethnicities. The survey also asked indirect questions about how likely the participant would be to interact with a person of a given ethnicity in a variety of settings (such as, “How likely do you think it is that you would introduce yourself to a person of Arab-American descent?”). The results of the research suggested that participants were unwilling to report prejudicial attitudes toward any ethnic group. However, there were significant differences between their pattern of responses to questions about social interaction with Arab-Americans compared to other ethnic groups: they indicated less willingness for social interaction with Arab-Americans compared to the other ethnic groups. This suggested that the participants harbored subtle forms of prejudice against Arab-Americans, despite their assertions that this was not the case (Jenkins et al., 2012).

Think iT Over

Research has shown that parental depressive symptoms are linked to a number of negative child outcomes. A classmate of yours is interested in  the associations between parental depressive symptoms and actual child behaviors in everyday life [2] because this associations remains largely unknown. After reading this section, what do you think is the best way to better understand such associations? Which method might result in the most valid data?

A-B-A-B design:  an experimental design in which the a person is given treatment, or experimental condition (B), to compare against the baseline (A), and this repeats in order to determine effectiveness

clinical or case study:  observational research study focusing on one or a few people

correlational research:  tests whether a relationship exists between two or more variables

descriptive research:  research studies that do not test specific relationships between variables; they are used to describe general or specific behaviors and attributes that are observed and measured

experimental research:  tests a hypothesis to determine cause-and-effect relationships

generalizability:  inferring that the results for a sample apply to the larger population

inter-rater reliability:  measure of agreement among observers on how they record and classify a particular event

naturalistic observation:  observation of behavior in its natural setting

observer bias:  when observations may be skewed to align with observer expectations

population:  overall group of individuals that the researchers are interested in

sample:  subset of individuals selected from the larger population

single-case experimental design:   when the same  research participant  serves as the subject in both the experimental and control conditions

survey:  list of questions to be answered by research participants—given as paper-and-pencil questionnaires, administered electronically, or conducted verbally—allowing researchers to collect data from a large number of people

• Scollon, C. N. (2020). Research designs. In R. Biswas-Diener & E. Diener (Eds), Noba textbook series: Psychology. Champaign, IL: DEF publishers. Retrieved from http://noba.to/acxb2thy ↵
• Slatcher, R. B., & Trentacosta, C. J. (2011). A naturalistic observation study of the links between parental depressive symptoms and preschoolers' behaviors in everyday life. Journal of family psychology : JFP : journal of the Division of Family Psychology of the American Psychological Association (Division 43), 25(3), 444–448. https://doi.org/10.1037/a0023728 ↵
• Modification and adaptation. Authored by : Sonja Ann Miller for Lumen Learning. Provided by : Lumen Learning. License : CC BY-SA: Attribution-ShareAlike
• Approaches to Research. Authored by : OpenStax College. Located at : http://cnx.org/contents/[email protected]:iMyFZJzg@5/Approaches-to-Research . License : CC BY: Attribution . License Terms : Download for free at http://cnx.org/contents/[email protected]
• Descriptive Research. Provided by : Boundless. Located at : https://www.boundless.com/psychology/textbooks/boundless-psychology-textbook/researching-psychology-2/types-of-research-studies-27/descriptive-research-124-12659/ . License : CC BY-SA: Attribution-ShareAlike
• Case Study. Provided by : Wikipedia. Located at : https://en.wikipedia.org/wiki/Case_study . License : CC BY-SA: Attribution-ShareAlike
• Rat man. Provided by : Wikipedia. Located at : https://en.wikipedia.org/wiki/Rat_Man#Legacy . License : CC BY-SA: Attribution-ShareAlike
• Case study in psychology. Provided by : Wikipedia. Located at : https://en.wikipedia.org/wiki/Case_study_in_psychology . License : CC BY-SA: Attribution-ShareAlike
• Research Designs. Authored by : Christie Napa Scollon. Provided by : Singapore Management University. Located at : https://nobaproject.com/modules/research-designs#reference-6 . Project : The Noba Project. License : CC BY-NC-SA: Attribution-NonCommercial-ShareAlike
• Single subject design. Provided by : Wikipedia. Located at : https://en.wikipedia.org/wiki/Single-subject_design . License : CC BY-SA: Attribution-ShareAlike
• Single subject research. Provided by : Wikipedia. Located at : https://en.wikipedia.org/wiki/Single-subject_research#A-B-A-B . License : Public Domain: No Known Copyright
• Pills. Authored by : qimono. Provided by : Pixabay. Located at : https://pixabay.com/illustrations/pill-capsule-medicine-medical-1884775/ . License : CC0: No Rights Reserved
• ABAB Design. Authored by : Doc. Yu. Provided by : Wikimedia. Located at : https://commons.wikimedia.org/wiki/File:A-B-A-B_Design.png . License : CC BY-SA: Attribution-ShareAlike

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Home Market Research

Descriptive Research: Definition, Characteristics, Methods + Examples

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

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

What is descriptive research?

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

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

Characteristics of descriptive research

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

Some distinctive characteristics of descriptive research are:

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

Applications of descriptive research with examples

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

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

Advantages of descriptive research

Some of the significant advantages of descriptive research are:

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

Descriptive research methods

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

Observational method

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

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

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

Case study method

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

Survey research

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

Examples of descriptive research

Some examples of descriptive research are:

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

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

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

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Descriptive Research 101: Definition, Methods and Examples

Parvathi vijayamohan.

Last Updated:  

5 June 2024

Table Of Contents

• Descriptive Research 101: The Definitive Guide

What is Descriptive Research?

Key characteristics of descriptive research.

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

Observation

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

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

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

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

Click to jump to the section that interests you.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

1. Case Study: Airbnb’s Growth Strategy

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

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

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

2. Observation – Better Tech Experiences for the Elderly

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

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

3. Surveys – Decoding Sleep with SurveySparrow

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

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

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

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• When should we collect the information?
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• Why are we obtaining the information?
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#2: Introduce and explain your methodological approach

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

#4: Describe your methods of analysis.

#5: Explain the reasoning behind your choices.

#6: Collect data.

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

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

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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

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What is case study research?

Last updated

8 February 2023

Reviewed by

Cathy Heath

Short on time? Get an AI generated summary of this article instead

Suppose a company receives a spike in the number of customer complaints, or medical experts discover an outbreak of illness affecting children but are not quite sure of the reason. In both cases, carrying out a case study could be the best way to get answers.

Organization

Case studies can be carried out across different disciplines, including education, medicine, sociology, and business.

Most case studies employ qualitative methods, but quantitative methods can also be used. Researchers can then describe, compare, evaluate, and identify patterns or cause-and-effect relationships between the various variables under study. They can then use this knowledge to decide what action to take. 

Another thing to note is that case studies are generally singular in their focus. This means they narrow focus to a particular area, making them highly subjective. You cannot always generalize the results of a case study and apply them to a larger population. However, they are valuable tools to illustrate a principle or develop a thesis.

Analyze case study research

Dovetail streamlines case study research to help you uncover and share actionable insights

• What are the different types of case study designs?

Researchers can choose from a variety of case study designs. The design they choose is dependent on what questions they need to answer, the context of the research environment, how much data they already have, and what resources are available.

Here are the common types of case study design:

Explanatory

An explanatory case study is an initial explanation of the how or why that is behind something. This design is commonly used when studying a real-life phenomenon or event. Once the organization understands the reasons behind a phenomenon, it can then make changes to enhance or eliminate the variables causing it. 

Here is an example: How is co-teaching implemented in elementary schools? The title for a case study of this subject could be “Case Study of the Implementation of Co-Teaching in Elementary Schools.”

Descriptive

An illustrative or descriptive case study helps researchers shed light on an unfamiliar object or subject after a period of time. The case study provides an in-depth review of the issue at hand and adds real-world examples in the area the researcher wants the audience to understand. 

The researcher makes no inferences or causal statements about the object or subject under review. This type of design is often used to understand cultural shifts.

Here is an example: How did people cope with the 2004 Indian Ocean Tsunami? This case study could be titled "A Case Study of the 2004 Indian Ocean Tsunami and its Effect on the Indonesian Population."

Exploratory

Exploratory research is also called a pilot case study. It is usually the first step within a larger research project, often relying on questionnaires and surveys . Researchers use exploratory research to help narrow down their focus, define parameters, draft a specific research question , and/or identify variables in a larger study. This research design usually covers a wider area than others, and focuses on the ‘what’ and ‘who’ of a topic.

Here is an example: How do nutrition and socialization in early childhood affect learning in children? The title of the exploratory study may be “Case Study of the Effects of Nutrition and Socialization on Learning in Early Childhood.”

An intrinsic case study is specifically designed to look at a unique and special phenomenon. At the start of the study, the researcher defines the phenomenon and the uniqueness that differentiates it from others. 

In this case, researchers do not attempt to generalize, compare, or challenge the existing assumptions. Instead, they explore the unique variables to enhance understanding. Here is an example: “Case Study of Volcanic Lightning.”

This design can also be identified as a cumulative case study. It uses information from past studies or observations of groups of people in certain settings as the foundation of the new study. Given that it takes multiple areas into account, it allows for greater generalization than a single case study. 

The researchers also get an in-depth look at a particular subject from different viewpoints.  Here is an example: “Case Study of how PTSD affected Vietnam and Gulf War Veterans Differently Due to Advances in Military Technology.”

Critical instance

A critical case study incorporates both explanatory and intrinsic study designs. It does not have predetermined purposes beyond an investigation of the said subject. It can be used for a deeper explanation of the cause-and-effect relationship. It can also be used to question a common assumption or myth. 

The findings can then be used further to generalize whether they would also apply in a different environment.  Here is an example: “What Effect Does Prolonged Use of Social Media Have on the Mind of American Youth?”

Instrumental

Instrumental research attempts to achieve goals beyond understanding the object at hand. Researchers explore a larger subject through different, separate studies and use the findings to understand its relationship to another subject. This type of design also provides insight into an issue or helps refine a theory. 

For example, you may want to determine if violent behavior in children predisposes them to crime later in life. The focus is on the relationship between children and violent behavior, and why certain children do become violent. Here is an example: “Violence Breeds Violence: Childhood Exposure and Participation in Adult Crime.”

Evaluation case study design is employed to research the effects of a program, policy, or intervention, and assess its effectiveness and impact on future decision-making. 

For example, you might want to see whether children learn times tables quicker through an educational game on their iPad versus a more teacher-led intervention. Here is an example: “An Investigation of the Impact of an iPad Multiplication Game for Primary School Children.” 

• When do you use case studies?

Case studies are ideal when you want to gain a contextual, concrete, or in-depth understanding of a particular subject. It helps you understand the characteristics, implications, and meanings of the subject.

They are also an excellent choice for those writing a thesis or dissertation, as they help keep the project focused on a particular area when resources or time may be too limited to cover a wider one. You may have to conduct several case studies to explore different aspects of the subject in question and understand the problem.

• What are the steps to follow when conducting a case study?

1. Select a case

Once you identify the problem at hand and come up with questions, identify the case you will focus on. The study can provide insights into the subject at hand, challenge existing assumptions, propose a course of action, and/or open up new areas for further research.

2. Create a theoretical framework

While you will be focusing on a specific detail, the case study design you choose should be linked to existing knowledge on the topic. This prevents it from becoming an isolated description and allows for enhancing the existing information. 

It may expand the current theory by bringing up new ideas or concepts, challenge established assumptions, or exemplify a theory by exploring how it answers the problem at hand. A theoretical framework starts with a literature review of the sources relevant to the topic in focus. This helps in identifying key concepts to guide analysis and interpretation.

3. Collect the data

Case studies are frequently supplemented with qualitative data such as observations, interviews, and a review of both primary and secondary sources such as official records, news articles, and photographs. There may also be quantitative data —this data assists in understanding the case thoroughly.

4. Analyze your case

The results of the research depend on the research design. Most case studies are structured with chapters or topic headings for easy explanation and presentation. Others may be written as narratives to allow researchers to explore various angles of the topic and analyze its meanings and implications.

In all areas, always give a detailed contextual understanding of the case and connect it to the existing theory and literature before discussing how it fits into your problem area.

• What are some case study examples?

What are the best approaches for introducing our product into the Kenyan market?

How does the change in marketing strategy aid in increasing the sales volumes of product Y?

How can teachers enhance student participation in classrooms?

How does poverty affect literacy levels in children?

Case study topics

Case study of product marketing strategies in the Kenyan market

Case study of the effects of a marketing strategy change on product Y sales volumes

Case study of X school teachers that encourage active student participation in the classroom

Case study of the effects of poverty on literacy levels in children

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Child Care and Early Education Research Connections

Descriptive research studies.

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

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

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

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

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

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

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

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

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

Limitations:

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

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

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

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

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Examining the response to covid-19 in logistics and supply chain processes: insights from a state-of-the-art literature review and case study analysis.

1. Introduction

• RQ1 (scientific): How have researchers studied the impact of COVID-19 on logistics and supply chain processes? Which industrial sectors were mostly studied and why? Which additional topics can be related to COVID-19 and logistics/supply chain?
• RQ2 (practical): What effects of COVID-19 on logistics and supply chain processes were experienced by companies?

2. Materials and Methods

2.1. systematic literature review, 2.1.1. sample creation, 2.1.2. descriptive analyses, 2.1.3. paper classification.

• Macro theme: sustainability, resilience, risk, information technology, economics, performance, planning and food security. This classification represents paper’s core topic.
• Industrial sector: aerospace, agri-food, apparel, automotive, construction, e-commerce, electronic, energy, fast-moving consumer goods, food, healthcare, logistics, manufacturing and service.
• Data collection method: questionnaire/interview, third-party sources or case study. This classification represents the method used by the authors to collect the data useful to their study.
• Research method: statistical, decision-making, simulation, empirical, literature review or economic. This category describes the tool used by the authors to conduct the study and reach the related goals.
• Specific method, e.g., descriptive statistics, structural equation modeling (SEM), multi-criteria decision making (MCDM), etc.; this feature describes more accurately the type of work carried out by the authors and the tools used.
• Country: it reflects the geographical area in which the study was carried out, in terms, for instance, of the country in which a sample of people has been interviewed or where empirical data were collected, or where the simulation was set. This method of classification, although more elaborated, was preferred over traditional approaches, in which the country of the study is defined based merely on the affiliation of the first author of the paper, because the exact knowledge of the country in which the study was carried out is, for sure, a more representative source of information about the research. This is true in general, but it is even more important for this subject matter, as the management of the COVID-19 pandemic was made on a country or regional basis, with significant differences from country to country; knowing the exact location of the study helps in better interpreting the research outcomes. Possible entries in this field also include “multiple countries” and “not specified”, with the obvious meanings of the terms.

2.1.4. Cross-Analyses

2.1.5. interrelated aspects, 2.2. case study, 2.2.1. data collection.

• Economic data: some key economic data were retrieved from the company’s balance sheet, from 2019 up to the latest available document, which refers to 2022.
• Organizational data: these data describe changes in the operational, decision-making and business structure of the company in terms, e.g., of number of employees hired, number of drivers, etc.
• The related data were collected and elaborated between July and September 2023.

2.2.2. Survey Phase

2.2.3. analysis and summary, 3. results—systematic literature review, 3.1. descriptive statistics, 3.2. common classification fields, 3.2.1. macro theme, 3.2.2. industrial sector, 3.2.3. data collection method, 3.2.4. research method, 3.2.5. country, 3.3. cross-analyses, 3.3.1. macro theme vs. industrial sector, 3.3.2. research method vs. macro theme, 3.4. interrelated aspects, 4. results—case study, 4.1. company overview, 4.2. pre-covid-19 period, 4.3. covid-19 period, 4.4. post-covid-19 period, 4.5. analysis and summary.

• Strengths : at present, Company A benefits from a robust network of relationships with customers and suppliers (e.g., drivers), which was leveraged during the pandemic period to provide a rapid response to the increased request by the consumers. The company has also leveraged the usage of digital technologies, which made logistics activities more efficient and, again, allowed the company to respond to consumer demand in the pandemic period.
• Weaknesses : Company A has suffered from low economic results, in particular in the post-COVID-19 period, mainly due to the high production costs. Efforts must be made by the company to reduce expenses. At the same time, however, the service level, in terms of delivery lead time or on-time delivery, should be safeguarded.
• Opportunities : the growth of e-commerce, experienced in the COVID-19 period but expected to last over time, creates opportunities for increasing the volume of items handled by Company A. Indeed, the survey phase demonstrated that the company’s consumers have shifted towards the usage of online sales; hence, the company could consider investing in this area to increase its market share. By leveraging the e-commerce logistics and diversifying service, expansions could also be possible at an international level. Even if the company has already embraced the implementation of digital technologies, some emerging technologies (e.g., drones or advanced traceability systems) could also be introduced for further improving the logistics efficiency. Finally, sustainability is another opportunity to be leveraged, because of the current push towards the adoption of environmental-friendly logistics solutions. Examples of those solutions include a reduction in CO 2 emissions, and the usage of electric vehicles or zero-impact materials.
• Threats : the growth of e-commerce can be seen as an opportunity, but because many logistics companies have already entered this field, the sector is characterized by very high competition, which could limit the market share of Company A; this could instead be seen as a threat needing to be properly managed. Another threat comes from the increased cost of fuel, which, for sure, for a logistics company plays an important role in determining the cost of the transport activities (also, having previously observed that the company suffered from a limited revenue in recent years). This factor could further push towards the adoption of environmentally friendly transport modes (e.g., electric vehicles), which have been previously mentioned as an opportunity for leveraging in the logistics sector.

5. Conclusions

5.1. answer to the research questions, 5.2. scientific and practical implications, 5.3. suggestions for future research directions, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

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Monferdini, L.; Bottani, E. Examining the Response to COVID-19 in Logistics and Supply Chain Processes: Insights from a State-of-the-Art Literature Review and Case Study Analysis. Appl. Sci. 2024 , 14 , 5317. https://doi.org/10.3390/app14125317

Monferdini L, Bottani E. Examining the Response to COVID-19 in Logistics and Supply Chain Processes: Insights from a State-of-the-Art Literature Review and Case Study Analysis. Applied Sciences . 2024; 14(12):5317. https://doi.org/10.3390/app14125317

Monferdini, Laura, and Eleonora Bottani. 2024. "Examining the Response to COVID-19 in Logistics and Supply Chain Processes: Insights from a State-of-the-Art Literature Review and Case Study Analysis" Applied Sciences 14, no. 12: 5317. https://doi.org/10.3390/app14125317

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• Open access
• Published: 11 June 2024

Perception of enhanced learning in medicine through integrating of virtual patients: an exploratory study on knowledge acquisition and transfer

• Zhien Li 1 ,
• Maryam Asoodar 1 ,
• Nynke de Jong 2 ,
• Tom Keulers 3 ,
• Xian Liu 1 &
• Diana Dolmans 1  

BMC Medical Education volume  24 , Article number:  647 ( 2024 ) Cite this article

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Introduction

Virtual Patients (VPs) have been shown to improve various aspects of medical learning, however, research has scarcely delved into the specific factors that facilitate the knowledge gain and transfer of knowledge from the classroom to real-world applications. This exploratory study aims to understand the impact of integrating VPs into classroom learning on students’ perceptions of knowledge acquisition and transfer.

The study was integrated into an elective course on “Personalized Medicine in Cancer Treatment and Care,” employing a qualitative and quantitative approach. Twenty-two second-year medical undergraduates engaged in a VP session, which included role modeling, practice with various authentic cases, group discussion on feedback, and a plenary session. Student perceptions of their learning were measured through surveys and focus group interviews and analyzed using descriptive statistics and thematic analysis.

Quantitative data shows that students highly valued the role modeling introduction, scoring it 4.42 out of 5, and acknowledged the practice with VPs in enhancing their subject matter understanding, with an average score of 4.0 out of 5. However, students’ reflections on peer dialogue on feedback received mixed reviews, averaging a score of 3.24 out of 5. Qualitative analysis (of focus-group interviews) unearthed the following four themes: ‘Which steps to take in clinical reasoning’, ‘Challenging their reasoning to enhance deeper understanding’, ‘Transfer of knowledge ‘, and ' Enhance Reasoning through Reflections’. Quantitative and qualitative data are cohered.

The study demonstrates evidence for the improvement of learning by incorporating VPs with learning activities. This integration enhances students’ perceptions of knowledge acquisition and transfer, thereby potentially elevating students’ preparedness for real-world clinical settings. Key facets like expert role modeling and various authentic case exposures were valued for fostering a deeper understanding and active engagement, though with some mixed responses towards peer feedback discussions. While the preliminary findings are encouraging, the necessity for further research to refine feedback mechanisms and explore a broader spectrum of medical disciplines with larger sample sizes is underscored. This exploration lays a groundwork for future endeavors aimed at optimizing VP-based learning experiences in medical education.

Peer Review reports

In Medical Education, a persistent challenge lies in the bridge between acquiring theoretical knowledge and applying it in real-world clinical scenarios. Many medical students struggle with translating their classroom learning into practical settings. The primary challenge lies in effectively translating the concepts students have learned into authentic patient interactions. This gap is particularly concerning because it affects the quality of patient care, as medical students are not just learning to acquire knowledge but must be able to apply this knowledge in complex healthcare settings.

One approach to address this challenge is the use of Virtual Patients (VPs), a computer-based simulation of real-life clinical scenarios for students to train clinical skills [ 1 ]. Research has shown that using VPs in the classroom can effectively improve various aspects of learning, from core knowledge and clinical reasoning to decision-making skills and knowledge transfer [ 2 , 3 , 4 , 5 ]. The VPs provide students with the opportunity to practice skills in a safe and controlled simulation environment.

Recent studies have focused on optimizing the design and arrangement of VPs as part of learning activities to facilitate both knowledge acquisition and retention [ 6 , 7 , 8 ]. For instance, Verkuyl, Hughes [ 8 ] demonstrated that using VPs as gamification tools can improve students’ confidence, engagement, and satisfaction.

However, studies focusing on the specific factors that contribute to these improvements when integrating VPs into the classroom are limited, particularly in understanding how to use VPs in the classroom to facilitate the transfer of knowledge students’ gain from the class to the subsequent studying stage of their education and eventual practice.

Acquisition and transfer of knowledge are critical factors in medical education, as medical students must be able to apply their knowledge and skills to real-world clinical scenarios [ 9 ]. Research suggests that for the effective transfer of knowledge, students should be immersed in authentic environments, enabling the transition of learned competencies to advanced stages [ 10 , 11 , 12 , 13 ].

Despite the consensus on the efficacy of VPs as a tool, there is a gap in understanding how to integrate VPs in the classroom to optimize students’ learning, especially in facilitating learning transfer. The effectiveness of VPs is not just in their use but also in how they are used by students to enhance their understanding on how to reason and make decisions about medical treatments when dealing with clinical cases. Without a clear and deep understanding, we risk underutilizing their potential and losing opportunities for medical students to become well prepared for real-world clinical scenarios.

Certain elements, such as role modeling instruction [ 14 , 15 , 16 ], using various authentic cases [ 17 , 18 , 19 ], and engaging in peer discussions on feedback [ 20 , 21 , 22 ], emerge as potential key components that could be integrated to maximize the knowledge acquisition via VPs. For instance, Stalmeijer, Dolmans [ 23 ] show how an expert, serving as a role model, provides guidance that facilitates student learning by demonstrating clinical skills and reasoning out loud. While there is ample evidence supporting the advantages of inclusion of VPs in education, there is not enough research focusing on the detailed aspects of effective instructional design techniques. This paper delves into these components, seeking to understand how the VP integration influences students’ learning and knowledge transfer. Figure  1 shows the theoretical framework of how integrating VPs in class affects students’ learning and might impact the transfer of learning in a simulated VP environment to practice.

Relationship of implementing, impact factor, and transfer of training

This exploratory study aims to investigate how instructional design elements such as role modeling, various authentic cases, and peer dialogues on feedback within VP sessions affect students’ learning from the learner’s perceptions. The core research question in this study focuses on how the implementation of role modeling, various authentic cases, and peer dialogue on feedback in VPs, influences learners’ perception of knowledge gain and transfer in personalized medicine.

The study was conducted at Maastricht University in the elective course, “Personalized Medicine in Cancer Treatment and Care”. This course is open to second-year undergraduate medical students of Maastricht University.

Participants

Initially, 24 students enrolled in this course for the academic year of 2022–2023, and 22 students participated in the Virtual Patient session. In total, 19 students voluntarily completed the survey designed to evaluate their experiences and perceptions of the Virtual Patients session. Thereafter, 9 of the 19 survey respondents voluntarily agreed to participate in three focus group interviews, with 2–4 students in each focus group. Students were informed that participation in this research study had no impact on student’s academic performance or their continuation in their studies.

Intervention

The instructional approach for the VP cases was structured in a specific format for the students. Figure  2 shows the instructional design for VP integration. The first stage was a role-modeling phase, where an expert demonstrated the clinical reasoning process using VP Case A. This was followed by a practice session where students worked in pairs on two different VP cases (Case B and C). After that, students formed two larger groups each including 5 or 6 students, and discussed the system feedback that was provided by VP platform. Finally, the expert summarized the session and addressed students’ questions. The whole intervention lasted 120 min. Figure  1 gives an overview of the intervention steps.

The flow of integrated virtual patient session

1. Role modeling (30 min): The intervention started with an expert, a clinician with teaching experience, demonstrating a clinical case (Case A) and showing the clinical reasoning process by thinking aloud. The expert served as a role model in showcasing the approach toward clinical problem-solving, provided supportive information, and demonstrated how to proceed through the case. The aim of the role modeling session was to empower students to apply the insights and methodology gained from experts in case A to solve subsequent cases (case B and case C), Although these cases shared similarities in underlying principles, they diverged on patient characteristics such as age, complications, and smoking history that can influence patient treatment outcomes.

2 and 3. Two VP pair tasks (20 min each): In this segment, the 22 participating students were paired, resulting in 11 pairs. These pairs were then divided into two groups. Group 1 (6 pairs) and group 2 (5 pairs) alternated in going through Case B and Case C to account for the practice effect. These cases were variations of the clinical cases introduced during the role-modeling demonstration, differing in patient characteristics such as age, complications, and smoking history to challenge the students’ reasoning. Students were encouraged to work collaboratively.

4. Feedback discussion (30 min): Upon completion of the VP cases, an automated feedback is immediately provided about the reasoning analysis. Participants were instructed to save this feedback for later discussion. After that, Students were organized into groups of six, based on the sequence in which they engaged with the cases. For instance, those who first practiced with Case B and then proceeded to Case C formed Group (1) Conversely, students who started with case C and then moved on to case B were assembled into Group (2) To foster meaningful dialogue, students engaged in discussions focused on the feedback generated by the Virtual Patient system, guided by a printed discussion guide distributed to each group (see Appendix 2 ). The discussion aimed to deepen students’ understanding and enrich their conversations about the cases they had just completed.

5. Plenary (15 min): This part lasted 15 min. Hosted by the expert to summarize the session and address questions or doubts raised by students.

During the practice and discussion sessions, the expert circulated among the groups to offer additional guidance and support.

The virtual patient cases

Three Virtual Patient (VP) cases (Case A, B, and C) were created to enhance students’ comprehension of specific concepts, knowledge, and skills in clinical reasoning. The VP practice was developed on the P-Scribe ( www.pscribe.nl ) learning platform, a web-based e-learning system based in the Netherlands. The platform facilitates the design and implementation of text-based VP sessions (Appendix 4 ).

While these cases shared a foundation on authentic head and neck cancer treatment, they were characterized by varying patient characteristics in terms of age, gender, and medical history (anamnesis).

VP case flow chart

Within each VP case, students were presented with a scenario related to neck cancer. Figure  3 shows the chart of a VP case. Each case starts with an overview of the patient and their medical history which students had to use to make an initial assessment. After this, students encountered a mix of multiple-choice and open-ended practice questions. These questions guided students in planning diagnostics, formulating a diagnosis, and devising a treatment plan tailored to the patient’s specific needs. Immediate feedback was provided after students submitted each response, and comprehensive summative feedback was given at the conclusion of each case to foster understanding and learning from any potential misjudgments or oversights (See Appendix 4 ).

Measurement instruments

Learning-perception survey : The survey (Appendix 1 ) consisted of 20 items, structured into five primary sections: general experience, intended learning outcome, role modeling, practicing with various authentic cases, and reflection on peer dialogue around feedback. The first item asked about students’ general experience through the whole session. The second item focused on their perception of intended learning outcomes. Six items then focused on the students’ perceptions of learning through role modeling followed by 5 items addressing perceptions related to their learning on practicing with authentic cases. The final seven items explored students’ perception of learning from dialogue around feedback. Participants indicated their level of agreement for each statement using a 5-point Likert scale: 1 denoting “Strongly Disagree”, 2 for “Disagree”, 3 for “Neutral”, 4 for “Agree”, and 5 for “Strongly Agree”. For interpretation, average scores below 3 were considered as “in need for improvement”, those of 4 or higher as ‘good’, and those between 3 and 4 as ‘neutral’.

Focus group interviews : Three focus group interviews (Appendix 3 ) were conducted to dive deeper into students’ perceptions of their learning experience, knowledge gain, and knowledge transfer in real-world settings. The focus group took place after the survey and the survey data did not affect the development of the focus group questions. In focus group 1, two students, in focus group 2, two students and in focus group 3, five students participated. The interviews were structured around a series of questions that explored students’ perceptions of their learning across specifically designed sections. These sections included Role Modeling, Practice with Various Authentic Cases, and Dialogue around Feedback. The structure aimed to understand students’ perspectives on each key component of the learning sections.

The analysis of the survey data was conducted by calculating the mean, standard deviation, and the Alpha Coefficient for the responses pertaining to each of the five key dimensions of the survey. The mean score provided an indicator of the average student perception, while the standard deviation offered insights into the variability of the responses. The Alpha Coefficient, a measure of internal consistency, was computed to assess the reliability of the survey dimensions. Through these statistical measures, an overall understanding of the students’ perceptions regarding the various aspects of the Virtual Patients was attained, facilitating a robust analysis aligned with the research objectives.

The focus-group interview data were analyzed following the thematic analysis procedure set out by Braun and Clarke [ 24 ]: (1) familiarize yourself with your data, (2) generate initial codes, (3) search for themes, (4) review themes, (5) define and name themes, and (6) produce the report. The interview was guided by pre-existing frameworks or theories in medical education. This ensured the capture of major aspects of the VP learning experience as underscored in the existing literature: role modeling, using various authentic cases, and peer dialogue around feedback [ 16 , 17 , 18 , 20 , 21 ]. The focus group interview was recorded, transcribed, and coded by three team members and ordered in initial themes (Z.L, M.A, and X.L). These themes were discussed with the larger team. We used a process of inductive and deductive analysis and used the three design principles of role modeling, practice with various authentic cases, and group discussion on feedback as sensitizing concepts to study the data [ 24 ]. Thereafter, quantitative and qualitative analyses were collectively appraised, compared, and checked for inconsistencies. In this triangulation, the themes identified in focus-group interviews were explanatory to the descriptive statistics of the survey.

Trustworthiness

Several measures were taken to enhance the study’s trustworthiness. First, triangulation was achieved by employing multiple data collection methods, including surveys and focus group interviews. The interview data collection continued until saturation was reached, ensuring a comprehensive understanding of the student’s experiences and perceptions. Secondly, the coding process followed an iterative approach. Team members initially coded transcripts independently, and then met to reach a consensus before moving on to code subsequent transcripts. Three researchers conducted the coding independently to minimize bias and enhance the validity of the findings. Finally, a member check among a sample of the focus group interviewees was conducted. In response to the question asking whether they agreed with summaries of preliminary results and would provide comments, confirmatory responses were received as well as some minor additional comments and clarifications. The latter were taken into account in the analysis and interpretation of the data.

Ethical approval

The Maastricht University Ethical Committee reviewed and approved this study. The approval number is FHML-REC/2023/021.

The findings from both the survey data and focus group interviews were presented to explore students’ perceptions of the effectiveness of the Virtual Patient (VP) Session in enhancing their clinical reasoning skills.

Survey data

The survey explored students’ perceptions across five key dimensions: General Experience, Intended Learning Outcome, Role Modeling, Practicing with Various Authentic Cases, and students’ reflection on Peer Dialogue around Feedback. The students scored the VP sessions on 20 items (Table  1 ). The scores varied between M = 2.95 to M = 4.58, on a scale of 1–5.

For the General Experience of Virtual Patient Session (Items Q1-Q2) the average score was M = 4.13 (SD = 0.70). Specifically, the overall experience was positively rated at M = 4.11. The component that assessed the improvement of clinical reasoning skills received an average score of M = 4.16.

Regarding the Students’ Perception of Learning from Role Modeling (Items Q3-Q8), the average score was M = 4.38 (SD = 0.61). Students agreed that the expert demonstration at the start of the session helped them understand the intended learning outcomes and was useful in guiding them through the Virtual Patient cases, with scores ranging from M = 4.26 to M = 4.58.

Students’ perception of learning from practicing with various authentic cases (Items Q9-Q13), received an average score of M = 4.00 (SD = 0.86). The scores measured the students’ perception of how well the provided Virtual Patient cases matched their current level of understanding, enhanced their comprehension of the subject matter, and helped them grasp the complexities inherent in real-world clinical scenarios.

For their perception of learning from Peer Dialogue around Feedback (Questions 14–20), the average score was M = 3.24 (SD = 1.05). These scores measure the students’ perception of the effectiveness of peer dialogue in enhancing understanding, generating strategies to address feedback, and prioritizing areas of improvement.

Focus group interview data

The interviews revealed five themes: ' Which steps to take in clinical reasoning’, ' Asking challenging questions to enhance deeper understanding of knowledge’, ‘The variety in cases helps to enhance transfer to the real world’, and ‘Deeper understanding of reasoning through reflections’.

Which steps to take in clinical reasoning

Students acknowledged the expert’s initial demonstration helped them to develop structured knowledge and gain understanding of the clinical reasoning process.

I think it (Role modeling) helps to find a pattern in clinical reasoning as well. At first, it (the expert) explained to us. For example, are there possible lymph nodes? Yes or no. Then you need to do this and this…Then you can make kind of…pattern that differs for the diagnosis and the prognosis. So you can make kind of a diagram in your head. Which you can use later on. And your knowledge becomes more structured. (Focus Group 2, Student B)

Students also perceived that the integrated practice with Virtual Patients helped them to anticipate the subsequent steps in clinical reasoning. They indicated the patterns learned through practicing with virtual Patients helped them understand the procedures they needed to follow to evaluate the patient.

I think now I know the steps which they (the procedural) followed to evaluate the patient, so first we can do this and then that. First, you determine the TNM (Tumour, Node, Metastasis) staging and do the endoscopy, then the TNM staging, and then you make the treatment plan. Now it’s more clear how they do those steps. (Focus Group 1, Student A)

Moreover, students thought the pair work and dialogue helped them think and clarify with each other what steps they needed to do in clinical reasoning when they had different opinions.

Yeah, that (pair working) was really nice because you can discuss, like I think do this and the other one says, you know, I think do that step, and then you’re already discussing the answers which is really nice to have. (The discussion) really make you think about the steps. (Focus Group 1, Student b)

Challenging their reasoning to enhance deeper understanding

Students reported how the course design differed from other blocks. According to the students, the VP practice was particularly beneficial in helping them integrate knowledge, and make the knowledge their own.

It (the VP practice) helps you to integrate knowledge because other blocks are really only lectures, they are all listening and listening. So the virtual patient was really nice to make this stuff our own. (Focus Group 2, Student A)

Students indicated the examples given by the expert helped them get a better understanding of the more detailed TNM (Tumor, Node, Metastasis) table, that are used in clinical reasoning.

Yeah, she (the expert) gave examples and guided the reading of the tables for TNM (Tumor, Node, Metastasis) staging, and those were also in the Virtual Patient cases, but because she already used them once and explained how we have to use them, it became more clear to us, what these tables are for and how they are used (Focus Group 1, Student B) .

The students noted that in VP practice sessions, compared with passive learning in traditional lectures, they were challenged to engage directly with the material by making clinical decisions, such as selecting appropriate tests to reach a diagnosis.

In lectures, we passively learn the trajectory from symptoms to diagnosis. During Virtual Patient practice, we actively process it. So you have to make decisions and select the test etc. (Focus Group 2, Student B)

Students indicated that practicing with the VP cases challenged them to look up information and reasoned by themselves. They gave an example of the imaging practice in which they were tasked with examining specific body parts in medical images on their own, they thought they were challenged to reason about what they saw instead of getting the information directly.

Yeah, also the (medical) imaging in the assignments where you need to look at a specific part of the body, normally you just see a picture and someone says, yeah, this is the stomach or this is the heart, whatever, and now you need to look it up yourself and think about it yourself, what you see, so that really helps. (Focus Group 1, Student B)

Furthermore, they emphasized the questions asked by experts challenged them to think, put the knowledge in their own words and apply the knowledge with their own reasoning.

The questions she (the expert) asked really make you think about the things she’s learning(teaching). So if she asks questions, you’re really thinking, and yeah, you’re challenged to put it in your own words. (Focus Group 1, Student B) For instance, she (the expert) asked questions that not from official guidelines, instead, it came from where widely doctor worked and her personal experiences. I applied what she said with my own reasoning behind it. (Focus Group 2, Student B)

Transfer of knowledge

Students perceived that practicing with VP cases in different situations offered them hands-on experience, where they actively engaged with various situations, which prepared them for future patient interactions.

Having cases that are closer to the real world, like the comorbidity we discussed, would make it more realistic. (For instance, ) What if he also has obesity or diabetes? Those are the patients that we are going to see in the future. So it helps out a lot to have those different conditions as well. (Focus Group 2, Student B)

Students also indicated their preference for the structured approach of the VP session, where an initial demonstration by an expert, sharing their clinical experience, followed by hands-on practice with VP cases was perceived to enhance transfer to practice. This method, as described by the student, bridged the gap between theoretical knowledge and practical application. They think this structure made the knowledge clear and further helped them to transfer their knowledge from theory to practice.

You (the Virtual Patient session that integrated with role modeling, authentic VP practice, and peer discussion around feedback) made it (the clinical reasoning) clear for me because of the first case we discussed with the teacher. Well, he discussed it and showed us how to think, and how to get things from certain perspectives with risk factors, age, et cetera. And then we do it ourselves. We had to find out what was wrong and go on. So I quite liked it. It gave me a deeper understanding. (Focus Group 3, Student A)

Students indicated the sense of practical immersion is amplified by the “side information that you don’t really need” (Focus Group 3, Student E) from the cases. They highlighted the side information represented the interaction with real patients and made them think of clinical situations in real-world settings.

(Side) information would be more realistic, also side information that you don’t really need because a patient also tells you a lot of things, and some of those things aren’t as important, but you still need to decide if they are important or not. What do you see, why do you see it, what’s different than normal. (Focus Group 3, Student E)

Moreover, several students indicated that the hypothetical “what-if” discussions during the role modeling session helped them with reasoning, prompting them to consider complications that might arise in real-life medical situations.

So for example, about age, it’s more difficult to do a treatment above 70. (What if that patient) has things like smoking history and that kind of stuff. I think it’s really valuable because you have already had an example about it (Demonstrating Case A). (Focus Group 1, Student A)

Students indicated that the diagnosis practice in VP led them to realize the difference in real-world scenarios. They said while in the simulated environment might seem easy to choose multiple diagnostic options, in the real world, medical professionals must make more selective decisions due to limitations. They think this experience taught them to think of prioritizing and decision-making in a realistic medical setting.

Yeah, maybe also there (in VP cases) were also a question about which imaging techniques you would use and then it was Echo or CT, MRI, there was also an option where you could listen to the lungs and some of the people also checked that one, but it isn’t really necessary, so you think it only takes one minute, so why not, but in the real world there isn’t always time to do everything, so it’s also good to think what is really necessary and what’s not. (Focus Group 1, Student A)

Enhance reasoning through reflections

During the VP session, students received feedback and conducted conversations around the feedback provided by the Virtual Patient system. Students thought the peer dialogues around feedback provided opportunities for collective reflection and insights, allowing them to pinpoint areas of improvement.

I thought that (the peer dialogue) was really useful, because sometimes one person, for example, when the teacher explains everything, you don’t pick up everything he says. She (your peer) might pick up a different thing, and I pick up a different thing, and we can ask each other, do you know how this works? So I thought that was really useful. (Focus Group 3, Student B)

The students emphasized the importance of expressing and discussing different opinions. They noted that such interactions could provide new insights and perspectives that they would not have considered independently, thereby enriching their understanding.

When you do have different opinions, I think they (your peers) can give you insight that you maybe didn’t have for yourself. So you can add to each other’s knowledge. If somebody has another view, then we can discuss it. It (the discussion) brightens my tunnel view. Also having to say it (the knowledge) out loud and explaining your thoughts to someone else can also help, I think. (Focus Group 2, Student A)

When talking about the peer dialogues around feedback during the VP session, Some students highlighted the benefits of immediate feedback, which provided them with clarity and instant validation. However, others saw value in delayed feedback, as it fostered discussion and multiple interpretations.

I liked that the Virtual Patient program, that it gave you immediate feedback. That was really handy. And I also liked the discussion afterward so we could speak about it a bit more (Focus Group 3, Student B) . There was immediate feedback on most questions, so you knew if you had been correct or wrong. But for the learning process it might be handy to have that after the group discussion, because now we all have the same answer. (Focus Group 2, Student B)

The study demonstrated the perception of students’ learning and knowledge transfer by integrating VP cases with role modeling introductions, and peer dialogue around feedback, specifically in the context of personalized medicine in cancer treatment and care. The survey reflected a positive learning experience and students reported they gained a better understanding of the clinical reasoning process as well as which steps to take when dealing with a clinical case through this specific course design with integration of VP cases. Qualitative data showed that the integration of VPs into the educational setting clearly shifted the students from being passive observers in a traditional lecture-based format to active participants in a simulated clinical environment. This shift is in line with previous research findings, which suggest that the use of VPs in clinical training actively engages learners and encourages the application of their knowledge [ 4 ].

The quantitative data revealed that students highly valued the role modeling session, as indicated by the high average scores. Qualitative data explained that the role modeling session enabled students to not only observe the clinical process being demonstrated but also to engage in active thinking by interacting with the expert. As discussed by Cruess, Cruess [ 15 ], role modeling not only consciously imparts knowledge but also unconsciously influences students’ attitudes and behaviors, making the learning experience more relatable to the clinical environment. In this study, by sharing clinical reasoning and personal anecdotes during the class, experts made the learning experience more relatable to the clinical environment that students would face in the future. This mirrored the role modeling research by Morgenroth, Ryan [ 25 ] which emphasizes the importance of role models in shaping the self-concept and motivation of individuals. Moreover, the qualitative data showed that the demonstration by the expert serves as a fundamental pre-knowledge for students to cover the knowledge gap and prepare them with the following practice. This finding aligns with van Merrienboer’s scaffolding concept emphasizing the importance of initial expert guidance in learning processes [ 16 ].

Followed by the role modeling demonstration, students practiced on two VP cases in pairs and perceived that the VP practice enhanced their clinical reasoning skills, and also helped them understand the real-world clinical setting. The result showed that the variety and real-life complexity of cases in the VP sessions were perceived to be essential for students’ knowledge gain and transfer. The positive perception of various authentic cases aligns with previous research highlighting the importance of exposure to diverse and authentic scenarios in medical training [ 17 , 18 ]. Moreover, the hypothetical “what-if” scenarios further enhanced students’ analytical abilities, preparing them for the multifaceted challenges they would encounter in real-world medical situations. Survey responses (Q10, mean = 4.37; Q13, mean = 4.05 in Table  1 ) indicated a consensus among students on the improvement with this practice in understanding and applying knowledge. Our findings corroborate with Jonassen and Hernandez-Serrano [ 26 ]’s study emphasis on the importance of authentic learning environments for effective knowledge transfer.

After the practice, students discussed the feedback provided by the VP system. Despite its mixed quantitative reception, the peer dialogue on feedback was qualitatively found to be a vital component for promoting critical thinking, discussion, and reflection. The Feedback from the VPs, both immediate and delayed, along with peer dialogue, emerged as crucial elements in students’ learning process. In this study, students showed different preferences for receiving feedback. Some students preferred immediate feedback, however, others preferred delayed feedback. How feedback was provided notably influenced peer interactions. Given that immediate feedback was dispensed upon submission of answers, the peer dialogues automatically started when students noticed disparities or encountered obstacles. Such dialogues not only served to resolve ambiguities but also fostered collective reflection, enhancing comprehension of the subject. By vocalizing their thoughts and engaging in active discussions, students were able to solidify their understanding and uncover nuances they might have missed otherwise. This aligns with the importance of engaging in peer discussions on feedback as outlined in the theoretical background [ 20 , 21 , 22 ].

When looking at the integration of VP cases with the particular course design, students perceived that the expert demonstration, followed by VP practice, and peer dialogue around feedback fostered a comprehensive understanding, allowing them to integrate diverse clinical knowledge, which in turn promoted understanding. The “Watch-think-do-reflect” structure not only ensured better knowledge retention but also enhanced students’ enthusiasm towards the subject. Observing model demonstrations enabled students to assimilate clinical nuances and contemplate real-world applications. Subsequent hands-on practice with VP cases fortified their cognitive structures, honing their clinical reasoning. Ultimately, students perceived that reflective peer discussions on feedback solidified their learnings, enhancing knowledge retention.

Limitations

This study employed a survey and focus group interviews that provided a comprehensive understanding of students’ perceptions of learning. However, there are several limitations. The study had a small sample size and was conducted in the context of an elective course, which may limit the generalizability of the findings. Furthermore, the study was exploratory in nature and did not measure actual learning outcomes or long-term retention, which are critical aspects of educational impact.

Implications for future research

Future research should investigate whether integrating Virtual Patients (VPs) into classroom activities enhance student learning outcomes by incorporating learning assessments and involving larger and more diverse participant groups to validate our findings. Additionally, a deeper analysis of students’ reasoning processes and interactions could provide insights into how and why knowledge gain and transfer are fostered or hindered. Furthermore, it is also important to understand the most beneficial moment for integrating VPs into educational settings to enhance transfer from a simulated to a real practice setting. This understanding could inform the development of more effective educational strategies and interventions.

The integration of Virtual Patients into classroom learning appears to offer a promising approach to enrich medical education. Key elements such as role modeling and various authentic cases contribute positively to students’ perception of learning, as well as peer dialogue on feedback. However, the approach to peer dialogue on feedback may need to be refined for more consistent benefits. Furthermore, studies with larger sample sizes and broader participant groups are essential to provide robust support for the efficacy of this educational approach and its components.

Data availability

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

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Acknowledgements

Thanks to all the participants and education workers who contributed to the study. ZL was supported by a scholarship granted by the China Scholarship Council. Thanks for the support of my family, and thanks Ang Li for joining our family.

ZL was supported by a scholarship granted by the China Scholarship Council (CSC, 202208440100).

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ZL, MA, DD, and NJ conceived of the presented idea. MA and DD verified the analytical methods. TK and ZL contribute to the creation of learning materials. ZL analyzed the data and drafted the manuscript under the supervision of MA and DD. All authors contributed to the article and approved the submitted version.

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Li, Z., Asoodar, M., de Jong, N. et al. Perception of enhanced learning in medicine through integrating of virtual patients: an exploratory study on knowledge acquisition and transfer. BMC Med Educ 24 , 647 (2024). https://doi.org/10.1186/s12909-024-05624-7

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