The Ultimate Guide to Qualitative Research - Part 1: The Basics
- Introduction and overview
- What is qualitative research?
- What is qualitative data?
- Examples of qualitative data
- Qualitative vs. quantitative research
- Mixed methods
- Qualitative research preparation
- Theoretical perspective
- Theoretical framework
- Literature reviews
- Conceptual framework
- Conceptual vs. theoretical framework
- Qualitative research methods
- Focus groups
- Observational research
What is a case study?
Applications for case study research, what is a good case study, process of case study design, benefits and limitations of case studies.
- Ethnographical research
- Ethical considerations
- Confidentiality and privacy
- Power dynamics
Case studies are essential to qualitative research , offering a lens through which researchers can investigate complex phenomena within their real-life contexts. This chapter explores the concept, purpose, applications, examples, and types of case studies and provides guidance on how to conduct case study research effectively.
Whereas quantitative methods look at phenomena at scale, case study research looks at a concept or phenomenon in considerable detail. While analyzing a single case can help understand one perspective regarding the object of research inquiry, analyzing multiple cases can help obtain a more holistic sense of the topic or issue. Let's provide a basic definition of a case study, then explore its characteristics and role in the qualitative research process.
Definition of a case study
A case study in qualitative research is a strategy of inquiry that involves an in-depth investigation of a phenomenon within its real-world context. It provides researchers with the opportunity to acquire an in-depth understanding of intricate details that might not be as apparent or accessible through other methods of research. The specific case or cases being studied can be a single person, group, or organization – demarcating what constitutes a relevant case worth studying depends on the researcher and their research question .
Among qualitative research methods , a case study relies on multiple sources of evidence, such as documents, artifacts, interviews , or observations , to present a complete and nuanced understanding of the phenomenon under investigation. The objective is to illuminate the readers' understanding of the phenomenon beyond its abstract statistical or theoretical explanations.
Characteristics of case studies
Case studies typically possess a number of distinct characteristics that set them apart from other research methods. These characteristics include a focus on holistic description and explanation, flexibility in the design and data collection methods, reliance on multiple sources of evidence, and emphasis on the context in which the phenomenon occurs.
Furthermore, case studies can often involve a longitudinal examination of the case, meaning they study the case over a period of time. These characteristics allow case studies to yield comprehensive, in-depth, and richly contextualized insights about the phenomenon of interest.
The role of case studies in research
Case studies hold a unique position in the broader landscape of research methods aimed at theory development. They are instrumental when the primary research interest is to gain an intensive, detailed understanding of a phenomenon in its real-life context.
In addition, case studies can serve different purposes within research - they can be used for exploratory, descriptive, or explanatory purposes, depending on the research question and objectives. This flexibility and depth make case studies a valuable tool in the toolkit of qualitative researchers.
Remember, a well-conducted case study can offer a rich, insightful contribution to both academic and practical knowledge through theory development or theory verification, thus enhancing our understanding of complex phenomena in their real-world contexts.
What is the purpose of a case study?
Case study research aims for a more comprehensive understanding of phenomena, requiring various research methods to gather information for qualitative analysis . Ultimately, a case study can allow the researcher to gain insight into a particular object of inquiry and develop a theoretical framework relevant to the research inquiry.
Why use case studies in qualitative research?
Using case studies as a research strategy depends mainly on the nature of the research question and the researcher's access to the data.
Conducting case study research provides a level of detail and contextual richness that other research methods might not offer. They are beneficial when there's a need to understand complex social phenomena within their natural contexts.
The explanatory, exploratory, and descriptive roles of case studies
Case studies can take on various roles depending on the research objectives. They can be exploratory when the research aims to discover new phenomena or define new research questions; they are descriptive when the objective is to depict a phenomenon within its context in a detailed manner; and they can be explanatory if the goal is to understand specific relationships within the studied context. Thus, the versatility of case studies allows researchers to approach their topic from different angles, offering multiple ways to uncover and interpret the data .
The impact of case studies on knowledge development
Case studies play a significant role in knowledge development across various disciplines. Analysis of cases provides an avenue for researchers to explore phenomena within their context based on the collected data.
This can result in the production of rich, practical insights that can be instrumental in both theory-building and practice. Case studies allow researchers to delve into the intricacies and complexities of real-life situations, uncovering insights that might otherwise remain hidden.
Types of case studies
In qualitative research , a case study is not a one-size-fits-all approach. Depending on the nature of the research question and the specific objectives of the study, researchers might choose to use different types of case studies. These types differ in their focus, methodology, and the level of detail they provide about the phenomenon under investigation.
Understanding these types is crucial for selecting the most appropriate approach for your research project and effectively achieving your research goals. Let's briefly look at the main types of case studies.
Exploratory case studies
Exploratory case studies are typically conducted to develop a theory or framework around an understudied phenomenon. They can also serve as a precursor to a larger-scale research project. Exploratory case studies are useful when a researcher wants to identify the key issues or questions which can spur more extensive study or be used to develop propositions for further research. These case studies are characterized by flexibility, allowing researchers to explore various aspects of a phenomenon as they emerge, which can also form the foundation for subsequent studies.
Descriptive case studies
Descriptive case studies aim to provide a complete and accurate representation of a phenomenon or event within its context. These case studies are often based on an established theoretical framework, which guides how data is collected and analyzed. The researcher is concerned with describing the phenomenon in detail, as it occurs naturally, without trying to influence or manipulate it.
Explanatory case studies
Explanatory case studies are focused on explanation - they seek to clarify how or why certain phenomena occur. Often used in complex, real-life situations, they can be particularly valuable in clarifying causal relationships among concepts and understanding the interplay between different factors within a specific context.
Intrinsic, instrumental, and collective case studies
These three categories of case studies focus on the nature and purpose of the study. An intrinsic case study is conducted when a researcher has an inherent interest in the case itself. Instrumental case studies are employed when the case is used to provide insight into a particular issue or phenomenon. A collective case study, on the other hand, involves studying multiple cases simultaneously to investigate some general phenomena.
Each type of case study serves a different purpose and has its own strengths and challenges. The selection of the type should be guided by the research question and objectives, as well as the context and constraints of the research.
The flexibility, depth, and contextual richness offered by case studies make this approach an excellent research method for various fields of study. They enable researchers to investigate real-world phenomena within their specific contexts, capturing nuances that other research methods might miss. Across numerous fields, case studies provide valuable insights into complex issues.
Critical information systems research
Case studies provide a detailed understanding of the role and impact of information systems in different contexts. They offer a platform to explore how information systems are designed, implemented, and used and how they interact with various social, economic, and political factors. Case studies in this field often focus on examining the intricate relationship between technology, organizational processes, and user behavior, helping to uncover insights that can inform better system design and implementation.
Health research is another field where case studies are highly valuable. They offer a way to explore patient experiences, healthcare delivery processes, and the impact of various interventions in a real-world context.
Case studies can provide a deep understanding of a patient's journey, giving insights into the intricacies of disease progression, treatment effects, and the psychosocial aspects of health and illness.
Asthma research studies
Specifically within medical research, studies on asthma often employ case studies to explore the individual and environmental factors that influence asthma development, management, and outcomes. A case study can provide rich, detailed data about individual patients' experiences, from the triggers and symptoms they experience to the effectiveness of various management strategies. This can be crucial for developing patient-centered asthma care approaches.
Apart from the fields mentioned, case studies are also extensively used in business and management research, education research, and political sciences, among many others. They provide an opportunity to delve into the intricacies of real-world situations, allowing for a comprehensive understanding of various phenomena.
Case studies, with their depth and contextual focus, offer unique insights across these varied fields. They allow researchers to illuminate the complexities of real-life situations, contributing to both theory and practice.
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Understanding the key elements of case study design is crucial for conducting rigorous and impactful case study research. A well-structured design guides the researcher through the process, ensuring that the study is methodologically sound and its findings are reliable and valid. The main elements of case study design include the research question , propositions, units of analysis, and the logic linking the data to the propositions.
The research question is the foundation of any research study. A good research question guides the direction of the study and informs the selection of the case, the methods of collecting data, and the analysis techniques. A well-formulated research question in case study research is typically clear, focused, and complex enough to merit further detailed examination of the relevant case(s).
Propositions, though not necessary in every case study, provide a direction by stating what we might expect to find in the data collected. They guide how data is collected and analyzed by helping researchers focus on specific aspects of the case. They are particularly important in explanatory case studies, which seek to understand the relationships among concepts within the studied phenomenon.
Units of analysis
The unit of analysis refers to the case, or the main entity or entities that are being analyzed in the study. In case study research, the unit of analysis can be an individual, a group, an organization, a decision, an event, or even a time period. It's crucial to clearly define the unit of analysis, as it shapes the qualitative data analysis process by allowing the researcher to analyze a particular case and synthesize analysis across multiple case studies to draw conclusions.
This refers to the inferential model that allows researchers to draw conclusions from the data. The researcher needs to ensure that there is a clear link between the data, the propositions (if any), and the conclusions drawn. This argumentation is what enables the researcher to make valid and credible inferences about the phenomenon under study.
Understanding and carefully considering these elements in the design phase of a case study can significantly enhance the quality of the research. It can help ensure that the study is methodologically sound and its findings contribute meaningful insights about the case.
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Conducting a case study involves several steps, from defining the research question and selecting the case to collecting and analyzing data . This section outlines these key stages, providing a practical guide on how to conduct case study research.
Defining the research question
The first step in case study research is defining a clear, focused research question. This question should guide the entire research process, from case selection to analysis. It's crucial to ensure that the research question is suitable for a case study approach. Typically, such questions are exploratory or descriptive in nature and focus on understanding a phenomenon within its real-life context.
Selecting and defining the case
The selection of the case should be based on the research question and the objectives of the study. It involves choosing a unique example or a set of examples that provide rich, in-depth data about the phenomenon under investigation. After selecting the case, it's crucial to define it clearly, setting the boundaries of the case, including the time period and the specific context.
Previous research can help guide the case study design. When considering a case study, an example of a case could be taken from previous case study research and used to define cases in a new research inquiry. Considering recently published examples can help understand how to select and define cases effectively.
Developing a detailed case study protocol
A case study protocol outlines the procedures and general rules to be followed during the case study. This includes the data collection methods to be used, the sources of data, and the procedures for analysis. Having a detailed case study protocol ensures consistency and reliability in the study.
The protocol should also consider how to work with the people involved in the research context to grant the research team access to collecting data. As mentioned in previous sections of this guide, establishing rapport is an essential component of qualitative research as it shapes the overall potential for collecting and analyzing data.
Gathering data in case study research often involves multiple sources of evidence, including documents, archival records, interviews, observations, and physical artifacts. This allows for a comprehensive understanding of the case. The process for gathering data should be systematic and carefully documented to ensure the reliability and validity of the study.
Analyzing and interpreting data
The next step is analyzing the data. This involves organizing the data , categorizing it into themes or patterns , and interpreting these patterns to answer the research question. The analysis might also involve comparing the findings with prior research or theoretical propositions.
Writing the case study report
The final step is writing the case study report . This should provide a detailed description of the case, the data, the analysis process, and the findings. The report should be clear, organized, and carefully written to ensure that the reader can understand the case and the conclusions drawn from it.
Each of these steps is crucial in ensuring that the case study research is rigorous, reliable, and provides valuable insights about the case.
The type, depth, and quality of data in your study can significantly influence the validity and utility of the study. In case study research, data is usually collected from multiple sources to provide a comprehensive and nuanced understanding of the case. This section will outline the various methods of collecting data used in case study research and discuss considerations for ensuring the quality of the data.
Interviews are a common method of gathering data in case study research. They can provide rich, in-depth data about the perspectives, experiences, and interpretations of the individuals involved in the case. Interviews can be structured , semi-structured , or unstructured , depending on the research question and the degree of flexibility needed.
Observations involve the researcher observing the case in its natural setting, providing first-hand information about the case and its context. Observations can provide data that might not be revealed in interviews or documents, such as non-verbal cues or contextual information.
Documents and artifacts
Documents and archival records provide a valuable source of data in case study research. They can include reports, letters, memos, meeting minutes, email correspondence, and various public and private documents related to the case.
These records can provide historical context, corroborate evidence from other sources, and offer insights into the case that might not be apparent from interviews or observations.
Physical artifacts refer to any physical evidence related to the case, such as tools, products, or physical environments. These artifacts can provide tangible insights into the case, complementing the data gathered from other sources.
Ensuring the quality of data collection
Determining the quality of data in case study research requires careful planning and execution. It's crucial to ensure that the data is reliable, accurate, and relevant to the research question. This involves selecting appropriate methods of collecting data, properly training interviewers or observers, and systematically recording and storing the data. It also includes considering ethical issues related to collecting and handling data, such as obtaining informed consent and ensuring the privacy and confidentiality of the participants.
Analyzing case study research involves making sense of the rich, detailed data to answer the research question. This process can be challenging due to the volume and complexity of case study data. However, a systematic and rigorous approach to analysis can ensure that the findings are credible and meaningful. This section outlines the main steps and considerations in analyzing data in case study research.
Organizing the data
The first step in the analysis is organizing the data. This involves sorting the data into manageable sections, often according to the data source or the theme. This step can also involve transcribing interviews, digitizing physical artifacts, or organizing observational data.
Categorizing and coding the data
Once the data is organized, the next step is to categorize or code the data. This involves identifying common themes, patterns, or concepts in the data and assigning codes to relevant data segments. Coding can be done manually or with the help of software tools, and in either case, qualitative analysis software can greatly facilitate the entire coding process. Coding helps to reduce the data to a set of themes or categories that can be more easily analyzed.
Identifying patterns and themes
After coding the data, the researcher looks for patterns or themes in the coded data. This involves comparing and contrasting the codes and looking for relationships or patterns among them. The identified patterns and themes should help answer the research question.
Interpreting the data
Once patterns and themes have been identified, the next step is to interpret these findings. This involves explaining what the patterns or themes mean in the context of the research question and the case. This interpretation should be grounded in the data, but it can also involve drawing on theoretical concepts or prior research.
Verification of the data
The last step in the analysis is verification. This involves checking the accuracy and consistency of the analysis process and confirming that the findings are supported by the data. This can involve re-checking the original data, checking the consistency of codes, or seeking feedback from research participants or peers.
Like any research method , case study research has its strengths and limitations. Researchers must be aware of these, as they can influence the design, conduct, and interpretation of the study.
Understanding the strengths and limitations of case study research can also guide researchers in deciding whether this approach is suitable for their research question . This section outlines some of the key strengths and limitations of case study research.
Benefits include the following:
- Rich, detailed data: One of the main strengths of case study research is that it can generate rich, detailed data about the case. This can provide a deep understanding of the case and its context, which can be valuable in exploring complex phenomena.
- Flexibility: Case study research is flexible in terms of design , data collection , and analysis . A sufficient degree of flexibility allows the researcher to adapt the study according to the case and the emerging findings.
- Real-world context: Case study research involves studying the case in its real-world context, which can provide valuable insights into the interplay between the case and its context.
- Multiple sources of evidence: Case study research often involves collecting data from multiple sources , which can enhance the robustness and validity of the findings.
On the other hand, researchers should consider the following limitations:
- Generalizability: A common criticism of case study research is that its findings might not be generalizable to other cases due to the specificity and uniqueness of each case.
- Time and resource intensive: Case study research can be time and resource intensive due to the depth of the investigation and the amount of collected data.
- Complexity of analysis: The rich, detailed data generated in case study research can make analyzing the data challenging.
- Subjectivity: Given the nature of case study research, there may be a higher degree of subjectivity in interpreting the data , so researchers need to reflect on this and transparently convey to audiences how the research was conducted.
Being aware of these strengths and limitations can help researchers design and conduct case study research effectively and interpret and report the findings appropriately.
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Qualitative study design: Case Studies
- Qualitative study design
- Grounded theory
- Narrative inquiry
- Action research
- Field research
- Focus groups
- Surveys & questionnaires
- Study Designs Home
In depth description of the experience of a single person, a family, a group, a community or an organisation.
An example of a qualitative case study is a life history which is the story of one specific person. A case study may be done to highlight a specific issue by telling a story of one person or one group.
- Oral recording
Ability to explore and describe, in depth, an issue or event.
Develop an understanding of health, illness and health care in context.
Single case can be used to develop or disprove a theory.
Can be used as a model or prototype .
Labour intensive and generates large diverse data sets which can be hard to manage.
Case studies are seen by many as a weak methodology because they only look at one person or one specific group and aren’t as broad in their participant selection as other methodologies.
This methodology can be used to ask questions about a specific drug or treatment and its effects on an individual.
- Does thalidomide cause birth defects?
- Does exposure to a pesticide lead to cancer?
- Choi, T. S. T., Walker, K. Z., & Palermo, C. (2018). Diabetes management in a foreign land: A case study on Chinese Australians. Health & Social Care in the Community, 26(2), e225-e232.
- Reade, I., Rodgers, W., & Spriggs, K. (2008). New Ideas for High Performance Coaches: A Case Study of Knowledge Transfer in Sport Science. International Journal of Sports Science & Coaching , 3(3), 335-354.
- Wingrove, K., Barbour, L., & Palermo, C. (2017). Exploring nutrition capacity in Australia's charitable food sector. Nutrition & Dietetics , 74(5), 495-501.
- Green, J., & Thorogood, N. (2018). Qualitative methods for health research (4th ed.). London: SAGE.
- University of Missouri-St. Louis. Qualitative Research Designs. Retrieved from http://www.umsl.edu/~lindquists/qualdsgn.html
- << Previous: Action research
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- Last Updated: Oct 12, 2023 11:29 AM
- URL: https://deakin.libguides.com/qualitative-study-designs
- 1 University of Nebraska Medical Center
- 2 GDB Research and Statistical Consulting
- 3 GDB Research and Statistical Consulting/McLaren Macomb Hospital
- PMID: 29262162
- Bookshelf ID: NBK470395
Qualitative research is a type of research that explores and provides deeper insights into real-world problems. Instead of collecting numerical data points or intervene or introduce treatments just like in quantitative research, qualitative research helps generate hypotheses as well as further investigate and understand quantitative data. Qualitative research gathers participants' experiences, perceptions, and behavior. It answers the hows and whys instead of how many or how much. It could be structured as a stand-alone study, purely relying on qualitative data or it could be part of mixed-methods research that combines qualitative and quantitative data. This review introduces the readers to some basic concepts, definitions, terminology, and application of qualitative research.
Qualitative research at its core, ask open-ended questions whose answers are not easily put into numbers such as ‘how’ and ‘why’. Due to the open-ended nature of the research questions at hand, qualitative research design is often not linear in the same way quantitative design is. One of the strengths of qualitative research is its ability to explain processes and patterns of human behavior that can be difficult to quantify. Phenomena such as experiences, attitudes, and behaviors can be difficult to accurately capture quantitatively, whereas a qualitative approach allows participants themselves to explain how, why, or what they were thinking, feeling, and experiencing at a certain time or during an event of interest. Quantifying qualitative data certainly is possible, but at its core, qualitative data is looking for themes and patterns that can be difficult to quantify and it is important to ensure that the context and narrative of qualitative work are not lost by trying to quantify something that is not meant to be quantified.
However, while qualitative research is sometimes placed in opposition to quantitative research, where they are necessarily opposites and therefore ‘compete’ against each other and the philosophical paradigms associated with each, qualitative and quantitative work are not necessarily opposites nor are they incompatible. While qualitative and quantitative approaches are different, they are not necessarily opposites, and they are certainly not mutually exclusive. For instance, qualitative research can help expand and deepen understanding of data or results obtained from quantitative analysis. For example, say a quantitative analysis has determined that there is a correlation between length of stay and level of patient satisfaction, but why does this correlation exist? This dual-focus scenario shows one way in which qualitative and quantitative research could be integrated together.
Examples of Qualitative Research Approaches
Ethnography as a research design has its origins in social and cultural anthropology, and involves the researcher being directly immersed in the participant’s environment. Through this immersion, the ethnographer can use a variety of data collection techniques with the aim of being able to produce a comprehensive account of the social phenomena that occurred during the research period. That is to say, the researcher’s aim with ethnography is to immerse themselves into the research population and come out of it with accounts of actions, behaviors, events, etc. through the eyes of someone involved in the population. Direct involvement of the researcher with the target population is one benefit of ethnographic research because it can then be possible to find data that is otherwise very difficult to extract and record.
Grounded Theory is the “generation of a theoretical model through the experience of observing a study population and developing a comparative analysis of their speech and behavior.” As opposed to quantitative research which is deductive and tests or verifies an existing theory, grounded theory research is inductive and therefore lends itself to research that is aiming to study social interactions or experiences. In essence, Grounded Theory’s goal is to explain for example how and why an event occurs or how and why people might behave a certain way. Through observing the population, a researcher using the Grounded Theory approach can then develop a theory to explain the phenomena of interest.
Phenomenology is defined as the “study of the meaning of phenomena or the study of the particular”. At first glance, it might seem that Grounded Theory and Phenomenology are quite similar, but upon careful examination, the differences can be seen. At its core, phenomenology looks to investigate experiences from the perspective of the individual. Phenomenology is essentially looking into the ‘lived experiences’ of the participants and aims to examine how and why participants behaved a certain way, from their perspective . Herein lies one of the main differences between Grounded Theory and Phenomenology. Grounded Theory aims to develop a theory for social phenomena through an examination of various data sources whereas Phenomenology focuses on describing and explaining an event or phenomena from the perspective of those who have experienced it.
One of qualitative research’s strengths lies in its ability to tell a story, often from the perspective of those directly involved in it. Reporting on qualitative research involves including details and descriptions of the setting involved and quotes from participants. This detail is called ‘thick’ or ‘rich’ description and is a strength of qualitative research. Narrative research is rife with the possibilities of ‘thick’ description as this approach weaves together a sequence of events, usually from just one or two individuals, in the hopes of creating a cohesive story, or narrative. While it might seem like a waste of time to focus on such a specific, individual level, understanding one or two people’s narratives for an event or phenomenon can help to inform researchers about the influences that helped shape that narrative. The tension or conflict of differing narratives can be “opportunities for innovation”.
Research paradigms are the assumptions, norms, and standards that underpin different approaches to research. Essentially, research paradigms are the ‘worldview’ that inform research. It is valuable for researchers, both qualitative and quantitative, to understand what paradigm they are working within because understanding the theoretical basis of research paradigms allows researchers to understand the strengths and weaknesses of the approach being used and adjust accordingly. Different paradigms have different ontology and epistemologies . Ontology is defined as the "assumptions about the nature of reality” whereas epistemology is defined as the “assumptions about the nature of knowledge” that inform the work researchers do. It is important to understand the ontological and epistemological foundations of the research paradigm researchers are working within to allow for a full understanding of the approach being used and the assumptions that underpin the approach as a whole. Further, it is crucial that researchers understand their own ontological and epistemological assumptions about the world in general because their assumptions about the world will necessarily impact how they interact with research. A discussion of the research paradigm is not complete without describing positivist, postpositivist, and constructivist philosophies.
Positivist vs Postpositivist
To further understand qualitative research, we need to discuss positivist and postpositivist frameworks. Positivism is a philosophy that the scientific method can and should be applied to social as well as natural sciences. Essentially, positivist thinking insists that the social sciences should use natural science methods in its research which stems from positivist ontology that there is an objective reality that exists that is fully independent of our perception of the world as individuals. Quantitative research is rooted in positivist philosophy, which can be seen in the value it places on concepts such as causality, generalizability, and replicability.
Conversely, postpositivists argue that social reality can never be one hundred percent explained but it could be approximated. Indeed, qualitative researchers have been insisting that there are “fundamental limits to the extent to which the methods and procedures of the natural sciences could be applied to the social world” and therefore postpositivist philosophy is often associated with qualitative research. An example of positivist versus postpositivist values in research might be that positivist philosophies value hypothesis-testing, whereas postpositivist philosophies value the ability to formulate a substantive theory.
Constructivism is a subcategory of postpositivism. Most researchers invested in postpositivist research are constructivist as well, meaning they think there is no objective external reality that exists but rather that reality is constructed. Constructivism is a theoretical lens that emphasizes the dynamic nature of our world. “Constructivism contends that individuals’ views are directly influenced by their experiences, and it is these individual experiences and views that shape their perspective of reality”. Essentially, Constructivist thought focuses on how ‘reality’ is not a fixed certainty and experiences, interactions, and backgrounds give people a unique view of the world. Constructivism contends, unlike in positivist views, that there is not necessarily an ‘objective’ reality we all experience. This is the ‘relativist’ ontological view that reality and the world we live in are dynamic and socially constructed. Therefore, qualitative scientific knowledge can be inductive as well as deductive.”
So why is it important to understand the differences in assumptions that different philosophies and approaches to research have? Fundamentally, the assumptions underpinning the research tools a researcher selects provide an overall base for the assumptions the rest of the research will have and can even change the role of the researcher themselves. For example, is the researcher an ‘objective’ observer such as in positivist quantitative work? Or is the researcher an active participant in the research itself, as in postpositivist qualitative work? Understanding the philosophical base of the research undertaken allows researchers to fully understand the implications of their work and their role within the research, as well as reflect on their own positionality and bias as it pertains to the research they are conducting.
The better the sample represents the intended study population, the more likely the researcher is to encompass the varying factors at play. The following are examples of participant sampling and selection:
Purposive sampling- selection based on the researcher’s rationale in terms of being the most informative.
Criterion sampling-selection based on pre-identified factors.
Convenience sampling- selection based on availability.
Snowball sampling- the selection is by referral from other participants or people who know potential participants.
Extreme case sampling- targeted selection of rare cases.
Typical case sampling-selection based on regular or average participants.
Data Collection and Analysis
Qualitative research uses several techniques including interviews, focus groups, and observation.    Interviews may be unstructured, with open-ended questions on a topic and the interviewer adapts to the responses. Structured interviews have a predetermined number of questions that every participant is asked. It is usually one on one and is appropriate for sensitive topics or topics needing an in-depth exploration. Focus groups are often held with 8-12 target participants and are used when group dynamics and collective views on a topic are desired. Researchers can be a participant-observer to share the experiences of the subject or a non-participant or detached observer.
While quantitative research design prescribes a controlled environment for data collection, qualitative data collection may be in a central location or in the environment of the participants, depending on the study goals and design. Qualitative research could amount to a large amount of data. Data is transcribed which may then be coded manually or with the use of Computer Assisted Qualitative Data Analysis Software or CAQDAS such as ATLAS.ti or NVivo.
After the coding process, qualitative research results could be in various formats. It could be a synthesis and interpretation presented with excerpts from the data. Results also could be in the form of themes and theory or model development.
To standardize and facilitate the dissemination of qualitative research outcomes, the healthcare team can use two reporting standards. The Consolidated Criteria for Reporting Qualitative Research or COREQ is a 32-item checklist for interviews and focus groups. The Standards for Reporting Qualitative Research (SRQR) is a checklist covering a wider range of qualitative research.
Examples of Application
Many times a research question will start with qualitative research. The qualitative research will help generate the research hypothesis which can be tested with quantitative methods. After the data is collected and analyzed with quantitative methods, a set of qualitative methods can be used to dive deeper into the data for a better understanding of what the numbers truly mean and their implications. The qualitative methods can then help clarify the quantitative data and also help refine the hypothesis for future research. Furthermore, with qualitative research researchers can explore subjects that are poorly studied with quantitative methods. These include opinions, individual's actions, and social science research.
A good qualitative study design starts with a goal or objective. This should be clearly defined or stated. The target population needs to be specified. A method for obtaining information from the study population must be carefully detailed to ensure there are no omissions of part of the target population. A proper collection method should be selected which will help obtain the desired information without overly limiting the collected data because many times, the information sought is not well compartmentalized or obtained. Finally, the design should ensure adequate methods for analyzing the data. An example may help better clarify some of the various aspects of qualitative research.
A researcher wants to decrease the number of teenagers who smoke in their community. The researcher could begin by asking current teen smokers why they started smoking through structured or unstructured interviews (qualitative research). The researcher can also get together a group of current teenage smokers and conduct a focus group to help brainstorm factors that may have prevented them from starting to smoke (qualitative research).
In this example, the researcher has used qualitative research methods (interviews and focus groups) to generate a list of ideas of both why teens start to smoke as well as factors that may have prevented them from starting to smoke. Next, the researcher compiles this data. The research found that, hypothetically, peer pressure, health issues, cost, being considered “cool,” and rebellious behavior all might increase or decrease the likelihood of teens starting to smoke.
The researcher creates a survey asking teen participants to rank how important each of the above factors is in either starting smoking (for current smokers) or not smoking (for current non-smokers). This survey provides specific numbers (ranked importance of each factor) and is thus a quantitative research tool.
The researcher can use the results of the survey to focus efforts on the one or two highest-ranked factors. Let us say the researcher found that health was the major factor that keeps teens from starting to smoke, and peer pressure was the major factor that contributed to teens to start smoking. The researcher can go back to qualitative research methods to dive deeper into each of these for more information. The researcher wants to focus on how to keep teens from starting to smoke, so they focus on the peer pressure aspect.
The researcher can conduct interviews and/or focus groups (qualitative research) about what types and forms of peer pressure are commonly encountered, where the peer pressure comes from, and where smoking first starts. The researcher hypothetically finds that peer pressure often occurs after school at the local teen hangouts, mostly the local park. The researcher also hypothetically finds that peer pressure comes from older, current smokers who provide the cigarettes.
The researcher could further explore this observation made at the local teen hangouts (qualitative research) and take notes regarding who is smoking, who is not, and what observable factors are at play for peer pressure of smoking. The researcher finds a local park where many local teenagers hang out and see that a shady, overgrown area of the park is where the smokers tend to hang out. The researcher notes the smoking teenagers buy their cigarettes from a local convenience store adjacent to the park where the clerk does not check identification before selling cigarettes. These observations fall under qualitative research.
If the researcher returns to the park and counts how many individuals smoke in each region of the park, this numerical data would be quantitative research. Based on the researcher's efforts thus far, they conclude that local teen smoking and teenagers who start to smoke may decrease if there are fewer overgrown areas of the park and the local convenience store does not sell cigarettes to underage individuals.
The researcher could try to have the parks department reassess the shady areas to make them less conducive to the smokers or identify how to limit the sales of cigarettes to underage individuals by the convenience store. The researcher would then cycle back to qualitative methods of asking at-risk population their perceptions of the changes, what factors are still at play, as well as quantitative research that includes teen smoking rates in the community, the incidence of new teen smokers, among others.
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- What Is Qualitative Research? | Methods & Examples
What Is Qualitative Research? | Methods & Examples
Published on June 19, 2020 by Pritha Bhandari . Revised on June 22, 2023.
Qualitative research involves collecting and analyzing non-numerical data (e.g., text, video, or audio) to understand concepts, opinions, or experiences. It can be used to gather in-depth insights into a problem or generate new ideas for research.
Qualitative research is the opposite of quantitative research , which involves collecting and analyzing numerical data for statistical analysis.
Qualitative research is commonly used in the humanities and social sciences, in subjects such as anthropology, sociology, education, health sciences, history, etc.
- How does social media shape body image in teenagers?
- How do children and adults interpret healthy eating in the UK?
- What factors influence employee retention in a large organization?
- How is anxiety experienced around the world?
- How can teachers integrate social issues into science curriculums?
Table of contents
Approaches to qualitative research, qualitative research methods, qualitative data analysis, advantages of qualitative research, disadvantages of qualitative research, other interesting articles, frequently asked questions about qualitative research.
Qualitative research is used to understand how people experience the world. While there are many approaches to qualitative research, they tend to be flexible and focus on retaining rich meaning when interpreting data.
Common approaches include grounded theory, ethnography , action research , phenomenological research, and narrative research. They share some similarities, but emphasize different aims and perspectives.
Note that qualitative research is at risk for certain research biases including the Hawthorne effect , observer bias , recall bias , and social desirability bias . While not always totally avoidable, awareness of potential biases as you collect and analyze your data can prevent them from impacting your work too much.
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Each of the research approaches involve using one or more data collection methods . These are some of the most common qualitative methods:
- Observations: recording what you have seen, heard, or encountered in detailed field notes.
- Interviews: personally asking people questions in one-on-one conversations.
- Focus groups: asking questions and generating discussion among a group of people.
- Surveys : distributing questionnaires with open-ended questions.
- Secondary research: collecting existing data in the form of texts, images, audio or video recordings, etc.
- You take field notes with observations and reflect on your own experiences of the company culture.
- You distribute open-ended surveys to employees across all the company’s offices by email to find out if the culture varies across locations.
- You conduct in-depth interviews with employees in your office to learn about their experiences and perspectives in greater detail.
Qualitative researchers often consider themselves “instruments” in research because all observations, interpretations and analyses are filtered through their own personal lens.
For this reason, when writing up your methodology for qualitative research, it’s important to reflect on your approach and to thoroughly explain the choices you made in collecting and analyzing the data.
Qualitative data can take the form of texts, photos, videos and audio. For example, you might be working with interview transcripts, survey responses, fieldnotes, or recordings from natural settings.
Most types of qualitative data analysis share the same five steps:
- Prepare and organize your data. This may mean transcribing interviews or typing up fieldnotes.
- Review and explore your data. Examine the data for patterns or repeated ideas that emerge.
- Develop a data coding system. Based on your initial ideas, establish a set of codes that you can apply to categorize your data.
- Assign codes to the data. For example, in qualitative survey analysis, this may mean going through each participant’s responses and tagging them with codes in a spreadsheet. As you go through your data, you can create new codes to add to your system if necessary.
- Identify recurring themes. Link codes together into cohesive, overarching themes.
There are several specific approaches to analyzing qualitative data. Although these methods share similar processes, they emphasize different concepts.
Qualitative research often tries to preserve the voice and perspective of participants and can be adjusted as new research questions arise. Qualitative research is good for:
The data collection and analysis process can be adapted as new ideas or patterns emerge. They are not rigidly decided beforehand.
- Natural settings
Data collection occurs in real-world contexts or in naturalistic ways.
- Meaningful insights
Detailed descriptions of people’s experiences, feelings and perceptions can be used in designing, testing or improving systems or products.
- Generation of new ideas
Open-ended responses mean that researchers can uncover novel problems or opportunities that they wouldn’t have thought of otherwise.
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Researchers must consider practical and theoretical limitations in analyzing and interpreting their data. Qualitative research suffers from:
The real-world setting often makes qualitative research unreliable because of uncontrolled factors that affect the data.
Due to the researcher’s primary role in analyzing and interpreting data, qualitative research cannot be replicated . The researcher decides what is important and what is irrelevant in data analysis, so interpretations of the same data can vary greatly.
- Limited generalizability
Small samples are often used to gather detailed data about specific contexts. Despite rigorous analysis procedures, it is difficult to draw generalizable conclusions because the data may be biased and unrepresentative of the wider population .
Although software can be used to manage and record large amounts of text, data analysis often has to be checked or performed manually.
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.
- Chi square goodness of fit test
- Degrees of freedom
- Null hypothesis
- Discourse analysis
- Control groups
- Mixed methods research
- Non-probability sampling
- Quantitative research
- Inclusion and exclusion criteria
- Rosenthal effect
- Implicit bias
- Cognitive bias
- Selection bias
- Negativity bias
- Status quo bias
Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.
Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.
There are five common approaches to qualitative research :
- Grounded theory involves collecting data in order to develop new theories.
- Ethnography involves immersing yourself in a group or organization to understand its culture.
- Narrative research involves interpreting stories to understand how people make sense of their experiences and perceptions.
- Phenomenological research involves investigating phenomena through people’s lived experiences.
- Action research links theory and practice in several cycles to drive innovative changes.
Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.
There are various approaches to qualitative data analysis , but they all share five steps in common:
- Prepare and organize your data.
- Review and explore your data.
- Develop a data coding system.
- Assign codes to the data.
- Identify recurring themes.
The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .
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Qualitative research method-interviewing and observation
Department of Pharmacy Practice, Kulliyyah of Pharmacy, International Islamic University Malaysia, Kuantan Campus, Pahang, Malaysia
Buckley and Chiang define research methodology as “a strategy or architectural design by which the researcher maps out an approach to problem-finding or problem-solving.”[ 1 ] According to Crotty, research methodology is a comprehensive strategy ‘that silhouettes our choice and use of specific methods relating them to the anticipated outcomes,[ 2 ] but the choice of research methodology is based upon the type and features of the research problem.[ 3 ] According to Johnson et al . mixed method research is “a class of research where the researcher mixes or combines quantitative and qualitative research techniques, methods, approaches, theories and or language into a single study.[ 4 ] In order to have diverse opinions and views, qualitative findings need to be supplemented with quantitative results.[ 5 ] Therefore, these research methodologies are considered to be complementary to each other rather than incompatible to each other.[ 6 ]
Qualitative research methodology is considered to be suitable when the researcher or the investigator either investigates new field of study or intends to ascertain and theorize prominent issues.[ 6 , 7 ] There are many qualitative methods which are developed to have an in depth and extensive understanding of the issues by means of their textual interpretation and the most common types are interviewing and observation.[ 7 ]
This is the most common format of data collection in qualitative research. According to Oakley, qualitative interview is a type of framework in which the practices and standards be not only recorded, but also achieved, challenged and as well as reinforced.[ 8 ] As no research interview lacks structure[ 9 ] most of the qualitative research interviews are either semi-structured, lightly structured or in-depth.[ 9 ] Unstructured interviews are generally suggested in conducting long-term field work and allow respondents to let them express in their own ways and pace, with minimal hold on respondents’ responses.[ 10 ]
Pioneers of ethnography developed the use of unstructured interviews with local key informants that is., by collecting the data through observation and record field notes as well as to involve themselves with study participants. To be precise, unstructured interview resembles a conversation more than an interview and is always thought to be a “controlled conversation,” which is skewed towards the interests of the interviewer.[ 11 ] Non-directive interviews, form of unstructured interviews are aimed to gather in-depth information and usually do not have pre-planned set of questions.[ 11 ] Another type of the unstructured interview is the focused interview in which the interviewer is well aware of the respondent and in times of deviating away from the main issue the interviewer generally refocuses the respondent towards key subject.[ 11 ] Another type of the unstructured interview is an informal, conversational interview, based on unplanned set of questions that are generated instantaneously during the interview.[ 11 ]
In contrast, semi-structured interviews are those in-depth interviews where the respondents have to answer preset open-ended questions and thus are widely employed by different healthcare professionals in their research. Semi-structured, in-depth interviews are utilized extensively as interviewing format possibly with an individual or sometimes even with a group.[ 6 ] These types of interviews are conducted once only, with an individual or with a group and generally cover the duration of 30 min to more than an hour.[ 12 ] Semi-structured interviews are based on semi-structured interview guide, which is a schematic presentation of questions or topics and need to be explored by the interviewer.[ 12 ] To achieve optimum use of interview time, interview guides serve the useful purpose of exploring many respondents more systematically and comprehensively as well as to keep the interview focused on the desired line of action.[ 12 ] The questions in the interview guide comprise of the core question and many associated questions related to the central question, which in turn, improve further through pilot testing of the interview guide.[ 7 ] In order to have the interview data captured more effectively, recording of the interviews is considered an appropriate choice but sometimes a matter of controversy among the researcher and the respondent. Hand written notes during the interview are relatively unreliable, and the researcher might miss some key points. The recording of the interview makes it easier for the researcher to focus on the interview content and the verbal prompts and thus enables the transcriptionist to generate “verbatim transcript” of the interview.
Similarly, in focus groups, invited groups of people are interviewed in a discussion setting in the presence of the session moderator and generally these discussions last for 90 min.[ 7 ] Like every research technique having its own merits and demerits, group discussions have some intrinsic worth of expressing the opinions openly by the participants. On the contrary in these types of discussion settings, limited issues can be focused, and this may lead to the generation of fewer initiatives and suggestions about research topic.
Observation is a type of qualitative research method which not only included participant's observation, but also covered ethnography and research work in the field. In the observational research design, multiple study sites are involved. Observational data can be integrated as auxiliary or confirmatory research.[ 11 ]
Research can be visualized and perceived as painstaking methodical efforts to examine, investigate as well as restructure the realities, theories and applications. Research methods reflect the approach to tackling the research problem. Depending upon the need, research method could be either an amalgam of both qualitative and quantitative or qualitative or quantitative independently. By adopting qualitative methodology, a prospective researcher is going to fine-tune the pre-conceived notions as well as extrapolate the thought process, analyzing and estimating the issues from an in-depth perspective. This could be carried out by one-to-one interviews or as issue-directed discussions. Observational methods are, sometimes, supplemental means for corroborating research findings.
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Qualitative Research: Case study evaluation
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- Justin Keen , research fellow, health economics research group a ,
- Tim Packwood a
- Brunel University, Uxbridge, Middlesex UB8 3PH
- a Correspondence to: Dr Keen.
Case study evaluations, using one or more qualitative methods, have been used to investigate important practical and policy questions in health care. This paper describes the features of a well designed case study and gives examples showing how qualitative methods are used in evaluations of health services and health policy.
This is the last in a series of seven articles describing non-quantitative techniques and showing their value in health research
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The medical approach to understanding disease has traditionally drawn heavily on qualitative data, and in particular on case studies to illustrate important or interesting phenomena. The tradition continues today, not least in regular case reports in this and other medical journals. Moreover, much of the everyday work of doctors and other health professionals still involves decisions that are qualitative rather than quantitative in nature.
This paper discusses the use of qualitative research methods, not in clinical care but in case study evaluations of health service interventions. It is useful for doctors to understand the principles guiding the design and conduct of these evaluations, because they are frequently used by both researchers and inspectorial agencies (such as the Audit Commission in the United Kingdom and the Office of Technology Assessment in the United States) to investigate the work of doctors and other health professionals.
We briefly discuss the circumstances in which case study research can usefully be undertaken in health service settings and the ways in which qualitative methods are used within case studies. Examples show how qualitative methods are applied, both in purely qualitative studies and alongside quantitative methods.
Case study evaluations
Doctors often find themselves asking important practical questions, such as should we be involved in the management of hospitals and, if so, how? how will new government policies affect the lives of our patients? and how can we cope with changes in practice in our local setting? There are, broadly, two ways in which such questions can usefully be addressed. One is to analyse the proposed policies themselves, by investigating whether they are internally consistent and by using theoretical frameworks to predict their effects on the ground. National policies, including the implementation of the NHS internal market 1 and the new community care arrangements 2 have been examined in this way by using economic theory to analyse their likely consequences.
The other approach, and the focus of this article, is to study implementation empirically. Empirical evaluative studies are concerned with placing a value on an intervention or policy change, and they typically involve forming judgments, firstly about the appropriateness of an intervention for those concerned (and often by implication also for the NHS as a whole) and, secondly about whether the outputs and outcomes of interventions are justified by their inputs and processes.
Case study evaluations are valuable where broad, complex questions have to be addressed in complex circumstances. No one method is sufficient to capture all salient aspects of an intervention, and case studies typically use multiple methods.
The methods used in case studies may be qualitative or quantitative, depending on the circumstances. Case studies using qualitative methods are most valuable when the question being posed requires an investigation of a real life intervention in detail, where the focus is on how and why the intervention succeeds or fails, where the general context will influence the outcome and where researchers asking the questions will have no control over events. As a result, the number of relevant variables will be far greater than can be controlled for, so that experimental approaches are simply not appropriate.
Other conditions that enhance the value of the case study approach concern the nature of the intervention being investigated. Often an intervention is ill defined, at least at the outset, and so cannot easily be distinguished from the general environment. Even where it is well defined, an intervention may not be discrete but consist of a complex mix of changes that occur over different timescales. This is a pervasive problem in health services in many countries, which are experiencing many parallel and interrelated changes. The doctor weighing up whether or how to become involved in hospital management would have to assess the various impacts on the managerial role of clinical audit, resource management, consultant job plans, and a raft of government legislation. Secondly, any intervention will typically depend for its success on the involvement of several different interested groups. Each group may have a legitimate, but different, interpretation of events; capturing these different views is often best achieved by using interviews or other qualitative methods within a case study design. Thirdly, it is not clear at the outset whether an intervention will be fully implemented by the end of a study period--accounts of major computer system failures show this. 3 Yet study of these failures may provide invaluable clues for future success.
Taken together, these conditions exclude experimental approaches to evaluation. The case study is an alternative approach--in effect, a different way of thinking about complex situations which takes the conditions into account, but is nevertheless rigorous and facilitates informed judgments about success or failure.
The design of case studies
As noted earlier, case studies using qualitative methods are used by bodies that inspect and regulate public services. Examples include the work of the National Audit Office and the Audit Commission 4 in the United Kingdom and the Office of Technology Assessment in the United States. 5 Sometimes these studies are retrospective, particularly in investigations of failed implementations of policies. Increasingly, though, these bodies use prospective studies designed to investigate the extent to which centrally determined standards or initiatives have been implemented. For example, the National Audit Office recently examined hospital catering in England, focusing on the existence of, and monitoring of, standards as required by the citizen's charter and on the application of central policy and guidance in the areas of nutritional standards and cost control. 6
Prospective studies have also been used by academic researchers, for example, to evaluate the introduction of general management 7 in Britain after the Griffiths report, 8 in the studies of specific changes following the 1989 NHS review 9 which were commissioned by the King's Fund, 10 and in the introduction of total quality management in hospitals in the United States. 11 In these cases the investigators were interested in understanding what happened in a complex environment where they had no control over events. Their research questions emerged from widespread concerns about the implications of new policies or management theories, and were investigated with the most appropriate methods at their disposal.
THE NATURE OF RESEARCH QUESTIONS
Once a broad research question has been identified, there are two approaches to the design of case study research, with appropriateness depending on the circumstances. In the first approach, precise questions are posed at the outset of the research and data collection and analysis are directed towards answering them. These studies are typically constructed to allow comparisons to be drawn. 12 The comparison may be between different approaches to implementation, or a comparison between sites where an intervention is taking place and ones where normal practice prevails.
An example is the recent study by Glennerster et al of the implementation of general practitioner fundholding. 13 Starting with a broad question about the value of general practitioner fundholding, the researchers narrowed down to precise questions about the extent to which the fundholding scheme promoted efficiency and preserved equity. They used one qualitative method, semistructured interviews, with the general practitioners and practice managers and also with people responsible for implementing the policy at national and regional level. The interviews were complemented by the collection of quantitative data such as financial information from the practices (box 1).
Box 1 Outline of case study of GPfundholding 13
Mix of qualitative and quantitative methods
Fundholding and non-fundholding practices
Programme of interviews with key staff at practices
Interviews with people responsible for imple-menting national policy
Study found that the general practitioner fund-holding scheme was achieving the aims set for it bygovernment and that adverse selection (“creamskimming”) of patients was less likely than some commentators had feared
The second approach is more open and in effect starts by asking broad questions such as what is happening here? and, what are the important features and relationships that explain the impact of this intervention? These questions are then refined and become more specific in the course of fieldwork and a parallel process of data analysis. This type of design, in which the eventual research questions emerge during the research, is termed ethnography and has been advocated for use in the study of the impact of government policies in the health system. 14 15 In some ways it is similar to the way in which consultations are conducted in that it involves initial exploration, progressing over time towards a diagnosis inferred from the available data.
The evaluation of resource management in the NHS, 16 which investigated the progress of six pilot hospitals in implementing new management arrangements, focused particularly on identifying ways in which doctors and general managers could jointly control the allocation and commitment of resources (box 2). At the outset the nature of resource management was unclear--sites were charged with finding ways of involving doctors in management, but how this would be achieved and, if achieved, how successful it would be in improving patient care were open questions. The researchers selected major specialties within each site and conducted interviews with relevant staff, observed meetings, and analysed documentation. Over time, the data were used to develop a framework which captured the essential features of resource management at the time and which was used to evaluate each site's progress in implementing it.
Box 2 Evaluation of resourcemanagement 16
Six hospitals, a mix of teaching and non-teaching
Focus on major specialties: general surgery and general medicine
Methods and data sources independent of each other
Qualitative methods included interviews, non-participant observation of meetings, analysis of documentation
Evaluation found that there were important changes in management processes, but little evidence of improvement in patient care
SELECTION OF SITES
The process of selecting sites for study is central to the case study approach. Researchers have developed a number of selection strategies, the objectives of which, as in any good research study, are to ensure that misinterpretation of results is as far as possible avoided. Criteria include the selection of cases that are typical of the phenomenon being investigated, those in which a specific theory can be tested, or those that will confirm or refute a hypothesis.
Researchers will benefit from expert advice from those with knowledge of the subject being investigated, and they can usefully build into the initial research design the possibility of testing findings at further sites. Replication of results across sites helps to ensure that findings are not due to characteristics of particular sites; hence it increases external validity. 17
SELECTION OF METHODS
The next step is to select research methods, the process being driven by criteria of validity and reliability. 18 A distinctive but not unique feature of case study research is the use of multiple methods and sources of evidence to establish construct validity. The use of particular methods is discussed in other papers in this series; the validity and reliability of individual methods is discussed in more detail by Mays and Pope. 19
Case studies often use triangulation 20 to ensure the validity of findings. In triangulation all data items are corroborated from at least one other source and normally by another method of data collection. The fundholding study referred to earlier 13 used interviews in combination with several different quantitative sources of data to establish an overall picture. The evaluation of resource management, in contrast, used a wider range of qualitative and quantitative methods. 16
Case studies are used by bodiesthat inspect public services--to monitor standards in hospital catering, for example
Any one of these methods by itself might have produced results of weak validity, but the different methods were used to obtain data from different sources. When they all suggested the emergence of an important development, therefore, they acted to strengthen the researchers' belief in the validity of their observations.
Another technique is to construct chains of evidence; these are conceptual arguments that link phenomena to one another in the following manner: “if this occurs then some other thing would be expected to occur; and if not, then it would not be expected.” For example, if quantitative evidence suggested that there had been an increase or decrease in admission rates in several specialties within a resource management site and if an interview programme revealed that the involvement of doctors in management (if developed as part of the resource management initiative) had led to a higher level of coordination of admissions policies, then this is evidence that resource management may facilitate the introduction of such policies. This type of argument is not always appropriate, but it can be valuable where it is important to investigate causation in complex environments.
The collection of data should be directed towards the development of an analytical framework that will facilitate interpretation of findings. Again, there are several ways in which this might be done. In the study of fundholding 13 the data were organised to “test” hypotheses which were derived from pre-existing economic theories. In the case of resource management there was no obvious pre-existing theory that could be used; the development of a framework during the study was crucial to help organise and evaluate the data collected. The framework was not imposed on the data but derived from it in an iterative process over the course of the evaluation; each was used to refine the other over time (box 3). 15
Framework: five interrelated elements of resource management 16
The target should be a reduction in the consumption itself
Commitment to resource management by the relevant personnel at each level in the organisation
Devolution of authority for the management ofresources
Collaboration within and between disciplines insecuring the objectives of resource management
Management infrastructure, particularly in termsof organisational structure and provision of information
A clear focus for the local resource management strategy
The investigator is finally left with the difficult task of making a judgment about the findings of a study. The purpose of the steps in designing and building the case study research is to maximise confidence in the findings, but interpretation inevitably involves value judgments. The findings may well include divergences of opinion among those involved about the value of the intervention, and the results will often point towards different conclusions.
The extent to which research findings can be assembled into a single coherent account of events varies widely. In some circumstances widely differing opinions are themselves very important and should be reflected in any report. Where an evaluation is designed to inform policy making, however, some attempt has to be made at an overall judgment of success or failure; this was the case in the evaluation of resource management, where it was important to indicate to policy makers and the NHS whether it was worth while.
The complexity of the issues that health professionals have to deal with and the increasing recognition by policy makers, academics, and practitioners of the value of case studies in evaluating health service interventions suggest that the use of such studies is likely to increase in the future. Qualitative methods can be used within case study designs to address many practical and policy questions that impinge on the lives of professionals, particularly where those questions are concerned with how or why events take a particular course.
- Committee of Public Accounts
- Audit Commission
- Office of Technology Assessment
- National Audit Office
- Pollitt C ,
- Harrison S ,
- Griffiths R
- Secretaries of State
- Robinson R ,
- Berwick D ,
- Godfrey AB ,
- St Leger A ,
- Schneider H ,
- Walsworth-Bell J
- Glennerster H ,
- Matsaganis M ,
- Packwood T ,
- Open access
- Published: 31 October 2023
“It was almost like it’s set up for people to fail” A qualitative analysis of experiences and unmet supportive needs of people with Long COVID
- Katherine C. McNabb 1 na1 ,
- Alanna J. Bergman 1 na1 ,
- Rhonda Smith-Wright 2 ,
- Jaime Seltzer 3 , 4 ,
- Sarah E. Slone 2 ,
- Tosin Tomiwa 5 ,
- Abeer Alharthi 2 ,
- Patricia M. Davidson 6 ,
- Yvonne Commodore-Mensah 2 , 7 &
- Oluwabunmi Ogungbe 2 , 8
BMC Public Health volume 23 , Article number: 2131 ( 2023 ) Cite this article
Almost twenty percent of adults with COVID-19 develop Long COVID, leading to prolonged symptoms and disability. Understanding the supportive needs of people with Long COVID is vital to enacting effective models of care and policies.
This qualitative sub-study explored the experiences of people with Long COVID and their unmet needs. Participants enrolled in a larger study to evaluate the post-acute cardiovascular impacts of COVID-19 were invited to participate in subsequent in-depth interviews. Participants were enrolled purposively until saturation at 24 participants. Data were analyzed using thematic content analysis.
Participants focused on adaptations to life with Long COVID and their unmet needs in different life spheres. Three domains, 1) occupational and financial; 2) healthcare-related; and 3) social and emotional support, emerged as areas affecting quality of life. Although participants were motivated to return to work for financial and personal reasons, Long COVID symptoms often resulted in the inability to perform tasks required by their existing jobs, and unemployment. Those who maintained employment through employer accommodations still needed additional support. Participants encountered diagnostic challenges, challenges in accessing specialty appointments, insurance loopholes, high healthcare costs, and medical skepticism. Existing social networks provided support for completing daily tasks; however, those with Long COVID typically turned to others with similar lived experiences for emotional support. Participants found government support programs inadequate and difficult to access in all three domains.
We propose a five-pronged policy approach to support persons with Long COVID. These overarching recommendations are (1) improve public awareness of Long COVID; (2) improve clinical care quality and access; (3) implement additional school and workplace accommodations; (4) strengthen socioeconomic benefits and social services; and (5) improve research on Long COVID.
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According to the World Health Organization (WHO), over 750 million SARS-CoV-2 infection (COVID-19) cases have been confirmed globally, leading to almost 7 million deaths [ 1 ] Over 1 million deaths have occurred in the U.S. alone [ 2 ]. Although the United States government and the WHO have recently declared the end of COVID-19 as a public health emergency [ 3 , 4 ], the ramifications on both the individual and societal levels continue to be significant. While the severity of acute impact of COVID-19 has waned due to vaccines [ 5 ], treatments [ 6 ], and new variants [ 7 ], COVID-19 has precipitated a range of ongoing physical, psychological, and social effects, many of which are not yet fully understood [ 8 , 9 ].
The median time between onset and resolution of symptoms related to COVID-19 is roughly two weeks [ 10 ]. Yet the burden of post-acute sequelae of COVID-19 infection (PASC) is substantial. Nearly one in five US adults previously infected with COVID-19 have developed PASC [ 11 ]. While PASC terminology and standardized case definition are still in evolution, the affected community has claimed the term “Long COVID” and the sequelae are generally defined as new, persistent, or recurrent symptoms four weeks post-acute COVID-19 infection [ 12 , 13 ]. Common symptoms of Long COVID include fatigue, post-exertional malaise (PEM), shortness of breath, cognitive dysfunction, and other symptoms that may be new-onset after acute COVID-19 or persist from the initial illness [ 14 ].
Early in the pandemic, many medical providers were unaware that patients might experience chronic symptoms after COVID-19 due to an unfamiliarity with infection-associated chronic illnesses. This knowledge deficit resulted in some medical providers dismissing Long COVID symptoms and delaying diagnosis. This is similar to stigma and dismissal associated with other post viral syndromes [ 15 ]. Some patients sought multiple medical consultations in search of diagnosis and treatment [ 16 ]. Diagnosis of Long COVID is challenging as it is not broadly clinically recognized, and there is no definitive diagnostic test. Diagnosis therefore requires systematic exclusion of differential diagnoses [ 17 , 18 , 19 ]. Ultimately, the initial diagnosis of Long COVID may be based on history and physical exam.
Little is known about the long-term impact of COVID-19 and the variety of PASC experiences, management, and recovery, including psychological and socioeconomic impact [ 19 , 20 ]. Of the existing studies, several have explored decreased quality of life and found negative impact on ability to maintain employment; however, research is limited [ 16 , 21 , 22 , 23 ]. People have conveyed a variety of experiences in regard to initial infection, isolation, protracted illness, and improvement of post-acute sequelae [ 24 ].
Although legislators, advocates, healthcare workers, and those with Long COVID within the United States recognize the need to adapt current public benefit programs and workplace accommodation policies to better support those with Long COVID, there is little existing research to inform new policy recommendations. This study aimed to explore existing and desired supports that facilitate improvement in Long COVID symptoms and, where possible, reintegration into social and professional spheres to inform practice and policy to better support people experiencing Long COVID.
This paper represents a qualitative arm of a larger, multi-method research study underpinned by a pragmatic epistemology. The purpose of the larger study was to characterize the cardiovascular impact of Long COVID on people living with and without pre-existing cardiac disease [ 25 ]. Participants were recruited for the parent study via the Johns Hopkins University HOPE registry (Hopkins Opportunities for Patient Engagement registry) which solicits patient engagement through a variety of modalities including texts, social media, the electronic medical record, and MyChart. Individuals enrolled in the parent study were approached about their interest in participating in a qualitative sub-study. Participants were initially enrolled consecutively, and then later, researchers used purposive sampling to maximize variability in gender and COVID-19 related symptoms consistent with the parent study aims. At baseline, 63 individuals were interested in participating in the qualitative study. Recruitment was halted at 26 participants when redundant themes were identified indicating sufficient saturation as determined by the primary investigator who reviewed transcripts on an ongoing basis [ 26 ]. Participants in the qualitative study were contacted by a study team member to schedule an interview via Zoom at a mutually convenient time. Participants elected whether to appear on video based on their comfort, but Zoom video recording was disabled to increase confidentiality. All interviewers were PhD students formally trained in qualitative research and interview techniques. The semi-structured interview guides were designed to elicit information on participants’ past medical histories, baseline physical health and wellness routines, and the impact of Long COVID on work, finances, and relationships. Each interview was attended by the participant, an interviewer, and a note-taker – a study team member who collected information on non-verbal cues, emotional reactions, and feelings that are not captured in a written transcript. Interviews were audio recorded and professionally transcribed. Each participant received a $25 gift card to compensate for their time and effort. This study protocol was approved by an Institutional Review Board; written informed consent was obtained from all subjects involved in the study.
For this qualitative sub-study, we adopted a critical realist ontology to explain a reality that exists within a bias-laden cultural value system. A critical lens helped guide inquiry about institutional and structural barriers to health that are often beyond the control of individuals [ 27 , 28 ]. Three members of the qualitative research team divided the transcripts and read through them repeatedly to develop a deep familiarity with the data. After the initial review phase, the coding team developed an inductive codebook from the data and met weekly to discuss memos, reflections, and potential sources of bias. New codes were added to the codebook iteratively as new concepts and potential themes emerged. Every fifth interview was double coded for consistency and to evaluate coding agreement. We used thematic content analysis to group findings using constant comparison to triangulate the data and enhance confirmability [ 29 ].
Twenty-four participant interviews were included in the final analysis; we excluded two qualitative participants because those individuals did not report their lived experiences with Long COVID. Most (79%) were White adults, and 52% of participants were female. The median age of the interviewed participants was 46.5 years. Most participants reported their employment status as full-time, although this did not capture those who were on short-term disability, sick leave, or modified/hybrid schedules. The demographic makeup of the sample is presented in Table 1 .
Consistent with themes that emerged during data analysis, three domains of support were chosen for additional exploration and interpretation: (1) occupational and financial support; (2) social and emotional support; and (3) healthcare support are presented in Fig. 1 and discussed below.
Overlapping Dimensions of Support for People with Long COVID
Occupational and financial support
Participants expressed frustration in some circumstances and gratitude in others regarding their employers’ responses and accommodations to Long COVID symptoms. Some participants indicated that their employers were sympathetic and attempted to increase accessibility but did not understand their needs as chronically ill employees. Participants wanted to continue work that was fulfilling and that helped them feel productive.
I've never loved a job the way I loved my job. I worked with great people, but I love the patients, and the patients love me, and that was important to me... My identity is nebulous right now because I don't know if I'm ever going to be able to practice, in any way. (44-year-old female, Nurse)
However, participants who did maintain their prior positions often felt inadequately supported. People with Long COVID lacked the time and physical space to attend to their symptoms and health needs. Short breaks that did not allow for significant rest and recovery, few opportunities to sit at work, and a lack of privacy were some of the barriers to maintaining occupational roles post-COVID.
It’s a pretty physically demanding job, no matter what you do. It’s a lot of walking, and this Long COVID has basically made working there almost impossible because when I come home from work, forget it—I don’t even bother to eat. I’ve just got to lay down and go to sleep because I’m so tired, and we get breaks, but they aren’t what you would call normal people breaks. We get 15 minutes and 30 minutes here and there, and that’s like 15 seconds to me (63 year-old male, Warehouse Associate)
Across interviews, people with Long COVID had variable symptom severity, describing a constellation of symptoms that ebbed and flowed. Participants described having good days where they felt able to commute and work in person but also bad days where they needed time and space to rest for prolonged periods. As a result, individuals who were able to work from home acknowledged that remote work was key to maintaining their employment and financial stability. Similarly, people with Long COVID symptoms who were unable to work remotely described difficulty in maintaining employment due to unpredictable symptom presentation.
I have to do a lot of work in the field, the community, remember: [blinded for confidentiality] city. It was very hard for me just to come into the place... because you have to be there, there was not an option for virtual. It was [only] an option just to be there [in person]. That support I did not get, like saying, “Well today you can just go virtual and do whatever you can,” that kind of need. I need a mental health aid. I need to be flexible.( 42 year-old female, Nutritionist)
Some employers facilitated flexible work hours, including consultation work, to accommodate diverse schedule needs.
There are days I can’t do two hours a day. I’m down to an hour, or some days I can’t do anything. Luckily, I work for a justice organization, so they’ve been very supportive. They’re willing to take whatever I can give them at this point, and, as a consultant, that seems to have worked out. (53-year-old male , Nonprofit Director)
Difficulty navigating state and federal support systems was a common theme among participants. Many expressed dissatisfaction with the processes for enrolling in Medicare, Medicaid, and unemployment benefits due to burdensome enrollment systems and the complexity of service options. Some participants were able to access service navigators who supported them through enrollment, without whom government services fell out of reach. This contributed to a sense of fatalism for some workers experiencing Long COVID.
It was the worst. It was almost like it’s set up for people to fail at getting this help. … just [in] general, the government sites, like getting on unemployment. (40-year-old male, Actor/Singer)
Overall, participants voiced a desire to remain in the workforce both for financial reasons and for their sense of identity. Most of the participants in this study were still employed despite their chronic symptoms but felt the stress of not meeting their previous level of productivity. Participants stated that their financial stability was precarious due to a lack of formalized protection. They called for employers to make necessary changes to accommodate employees in their return to the workforce.
I have days where I could support from home. Heck, I might even be able to make it in once a week because I make it to doctor's appointments. I could come and check in. I really feel like my employers missed an opportunity to set an example… rather than behaving the way that they did in my condition... [They] had an opportunity to be the tip of the spear, I think, at reincorporating long haulers back into the workplace. It doesn't have to be an all-or-nothing thing…. A lot of what I did as a nurse in that office, I could do from home because it was a lot of talking to patients, explaining test results, helping triage their symptoms and things like that. (44-year-old female, Nurse)
In addition to occupational and financial support, participants detailed their experiences accessing a range of healthcare resources throughout the chronic phase of illness. Access to provider visits (both in-person and virtual), specialty care, and receipt of pharmacotherapeutic treatments for symptom management were impacted by a range of barriers and facilitators described by the participants.
Providers lacked knowledge about Long COVID incidence, symptoms, trajectory, and possible treatments. Limited provider knowledge also undermined confidence in the medical system and frustrated participants who felt their symptoms were ignored and glossed over. In some cases, healthcare providers denied the existence of Long COVID, attributing symptoms instead to inadequate sleep, depression, or other factors. One participant who experienced severe persistent shortness of breath and chest pain recounted:
The lung doctor they sent me to didn't think it was an issue. Just kinda said, "Ah, take some medicine for reflux," and that was it. I guess I felt like the way he acted that—almost kinda blew me off. He was very short. I don't know if he was stressed, or overstaffed, or whatever, but he was very short with me. Kind of dismissive of any concerns I might have that it was related to COVID. (50-year-old female, Profession Unknown)
Providers’ lack of familiarity with Long COVID led to delays in referral or treatment. Some providers were aware of Long COVID as a phenomenon but seemed unsure of how to appropriately treat, refer, and support people experiencing Long COVID. Recognizing the need for specialty care to treat Long COVID symptoms by itself was not sufficient in bridging the gap to receiving care. Participants reported difficulty in scheduling specialty appointments despite referrals from their primary care providers. One participant pointed out the access barrier created by surges in COVID-19.
My understanding is that the pulmonologists are just being swamped right now with people who have far worse symptoms than I do. I’m just like, yeah, how do I ever find out what the cause of this is? That’s just the frustration. I don’t know, maybe one day I can talk to my doctor. Maybe I can find a pulmonologist who has a free spot or something and talk to them . (61-year-old-female, Software Developer).
Among participants whose providers acknowledged Long COVID, a lack of follow-up often prevented them from receiving needed care. One participant remarked on receiving several referrals to specialty care but received no additional instructions about the next steps. Many participants felt trapped by their Long COVID symptoms and without treatment options.
“I told my primary doctor... ‘Hey, I noticed that COVID has bad brain fog,’ and they all say like, ‘We noticed that patients have that.’ I don't see any effort for referral or not even a medication needed to treat [it]. (42-year-old female, Nutritionist)”
The data suggests a level of self-advocacy and determination were required to overcome the lack of care continuity; however, this ongoing burden was stressful, exhausting, and incredibly challenging to maintain.
I have the feeling, given American healthcare, you have to be such a go-getter to figure this stuff out. If you just wait for your primary care doctor or even your pulmonologist, even these post-COVID clinics, you’d lose hope because you just don’t hear any—it’s crickets. It’s really crickets. To keep my own hope alive, I have to do this, or I’d be so down by now, I think. (53-year-old male , Nonprofit Director)
While provider knowledge and behavior impacted participants’ ability to receive healthcare support, more systemic barriers played a distinct role as well. Insurance coverage, workers’ compensation for employees infected on the job, and required documentation created significant frustration for many participants experiencing Long COVID symptoms.
Participants had mixed feelings about the role of telemedicine in expanding access during Long COVID. While some acknowledged a loss of connection during the provider visit when conducted remotely, many relished the convenience of conducting appointments virtually:
This is the best thing ever, because….I don't have to put on clothes. I don't have to get up off the couch. I can just lay here….That was really great. Then my next experience with telehealth was when I finally got an occupational health provider for my workers' comp claim. He started doing virtual visits with me probably about three, four months, probably four months into my illness. We've done virtual visits every two to four weeks for almost two years. (40-year-old female, Nurse)
Additionally, participants reported that prescription services by mail, drive-thru windows, and curbside pickups helped them stay safe during the pandemic by decreasing in-person contact. While participants reported some success navigating the effects of COVID-19 and Long COVID, overwhelmingly participants experienced frustrations regarding lack of acknowledgement and adequate assistance from medical providers, not receiving appropriate or timely treatment, and a lack of clinical follow-up.
Social and emotional support
Participants did not always differentiate between the social and emotional support that they needed and received in the acute phase of COVID versus the post-acute phase. In both phases, participants required support with physical tasks. During the acute phase, task-related supports such as meal and grocery drop-offs were essential due to the logistics of quarantine and were performed by friends, family, and co-workers. One participant discussed the support his family received in the first six weeks after he was diagnosed with COVID:
When I had COVID, a lot of our friends and a lot of her friends really chipped in and helped the family out through meal trains and people dropping off things for the girls. It really helped. It took the burden off the family of trying to figure out how do we go to the store. I'm in quarantine; my wife's supposed to be in quarantine; how do we go to the store? How do we provide for our family? For many weeks or a month and a half, it really helped as a family dynamic. (43-year-old-male, Profession Unknown)
The need for task-related support did not end with the acute phase of COVID. Delegation was necessary among the family, as family members experiencing Long COVID were unable to continue with the family-related tasks for which they had once been responsible.
We are a lot more reliant on the older kids to help out because I can't do very much. I have good days and bad days. There are some days that I might be able to cook dinner or something like that. Then there's bad days where I have to be served my dinner at the couch because I just don't even have the energy to eat at the table. I can't even sit up and sit at the table and eat with my family. We have had to put a lot more on the kids because there's so many of them [kids]. (44-year-old female, Nurse & Graduate Student)
Beyond this task-related support, family members and friends did not fully grasp the Long COVID experience. Participants often expressed a need for emotional support that was typically only found through others who shared the Long COVID experience, and they often connected through social media and support groups. Participants expressed a sense of comfort and hope in finding people who shared many of the same experiences, and Long COVID symptoms. Participants found online support groups especially helpful,
[…] I was so scared. I was like—just with all the body changes, and all this weird stuff happening to your body, and the feelings, and so I joined that Facebook Long COVID group. I’ve got to tell you that made me feel so good, because there are … thousands of people who have the same exact symptoms that I had, and that was the first time I was like, “Oh, my God. I’m normal.” It gave me hope. (42-year-old female, Police Officer)
Despite finding new social and emotional support for dealing with Long COVID, participants frequently discussed the barriers to engaging with their pre-pandemic social support structures. Participants often talked generally about social isolation that resulted from COVID protections during the pandemic, which were not unique to those experiencing Long COVID. However, people with Long COVID reported more complex barriers to social support related to their experience of the long-term consequences of COVID-19 and concerns around reinfection.
I did have some people say. ‘This is all in your head. Just get out of bed, and get up and go exercise. Go move around, and you’ll get to feeling better.’ They didn’t realize that it was making me feel worse....Initially, it was a few friends of mine. I have a family member that said, ‘Hey, you just need to get up and get going. You’ll feel better if you go outside’. (56-year-old male, Director of Software Support Staff)
The thematic domains of support included overlapping features (see Fig. 1 ). These multidimensional facilitators and barriers of support are presented as additional themes.
Leveraging social networks for medical information
The social networks built through Long COVID support groups allowed participants to leverage existing relationships to keep current on COVID research. Specifically, several participants relied on support group members and family members in the medical field to help them find and critique the current COVID literature. A nurse who participated in the study discussed how her COVID support group worked to fill the Long COVID knowledge gap:
We have a break off group, that's the data nerds working group where there's a lot of people that are either in the medical field or just plain out curious. Some of them are researchers, and a lot of people compile data there and so there's a lot of—we've done some of our own research. I think some of that's been published. Then also people will pull post articles and journals and things, and so it's just a one stop shop for you don't necessarily have to search it all out by yourself. I've read a ton of journals and articles there. (40-year-old female, Nurse)
Another participant discussed how he had connected with other patients that he met at his Long COVID clinic to share research on possible treatments , allowing treatment conversations to take place between affected people instead of being limited to the clinical environment. “I met some of his other patients, long-haulers, and we compared notes. We shared various case studies and reports that we were reading and seeing about long-haul treatment possibilities.” (53-year-old male , Nonprofit Director).
Participants also expressed a desire to contribute to the growing Long COVID knowledge base by participating in research studies and contributing back to the growing community of people living with Long COVID,
The other thing is, I think it’s important for those of us who have this to be able to reach out, or to search for research that they can be a part of […]. How are we going to figure all of this out, if people don’t volunteer to research? […] I think research is extremely important for long COVID. (55-year-old male, Director of Software Support Staff)
Health insurance and healthcare costs
Participants discussed the dual role that employment status played, contributing to personal finances and healthcare access via employer-sponsored insurance benefits. Their employment was tied to health insurance, which is a gateway to healthcare in a privatized model. Even though they had sufficient insurance coverage, certain participants faced a lack of support in their Long COVID care due to access barriers arising from loopholes that affected individuals receiving disability or workers' compensation benefits. One healthcare worker who became infected with COVID-19 at work clearly articulated these barriers.
I had to fight really hard to get in 'cause they are run ironically by the hospital that I'm affiliated with. At the time, they were only seeing patients that had their insurance, which of course I do but it was under my workers' comp claim, which is not the same insurance. I was like, "Okay, no, I'm gonna pitch a huge fit here. I got sick working for you guys so you are going to see me." They agreed to see me and said that they'll deal with the billing stuff later, which turned out to be a giant nightmare 'cause then of course, they turned around and billed me because workers' comp wouldn't pay for it, even though they had zero other options at the time. (41-year-old female, Nurse)
Some employers did not support employees infected with COVID-19 at work; moreover, employee benefits such as workers’ compensation failed to provide the intended safety net. In this case, the employee was burdened with billing disputes related to treatment costs. Even participants who had insurance incurred financial costs of care such as co-pays and lab fees.
I go to the doctor a lot, right? I have a lot of copays. I have a lot of tests that they run me through. I do have several thousand dollars of medical bills that I no longer had before. There is that side effect, or that burden. If that’s as bad as it gets economically, at least I still have a job. I still have insurance and stuff. (55-year-old male, Director of Software Support Staff)
Due to the emergent nature of COVID-19 and its sequelae, many participants engaged in alternative therapies that required financial resources to access. They were driven outside of the healthcare system, which had no answers or relief for their Long COVID symptoms. Despite employment and insurance access, participants still lacked financial support for the costs of these treatments.
I have to balance the amount of money I’m willing to pay ’cause a lotta this stuff is—you pay outta pocket. The supplements I’m on are expensive and maybe doing nothing –it's unclear. When you’re really sick, you’re willing to take risks that you wouldn’t normally take because your life already sucks, so maybe you’ll try something that normally you’d be like, “Well, am I gonna spend $200 bucks on that? No, I’m probably not,” and now, I might. (53-year-old male , Nonprofit Director)
Social networks as a driver of financial stability
Participants who were unable to work due to acute or chronic illness experienced stress and instability around their finances. Those who were unable to work or whose income was reduced due to their disability relied on financial support from spouses, partners, and other members of their social networks. Most often, participants framed this as an economic and social disruption created by loss of household income. This change in household income contributed to shifts in responsibility, and financial worry.
It did put more of a financial burden on myself, because at that point, I became the sole breadwinner, I guess. I don't know if that's the proper terminology, but the only income that was coming in was mine. That did add more stress, you know, because everything that we had done—the house that we were living in, our financial income—was based on a two-income household. Then all of a sudden, we went from a two-income household to a single-income household` (43-year-old male, Profession Unknown)
Individuals bore the physical strain of Long COVID alone, but their spouses, partners, and family shared the financial burden of their loved one’s disability. One participant describes his financial situation: “We can pay our rent, but we’re always a week late, so it’s like there’s an eviction notice on the door every time. It’s like we’re 12 h late, they definitely make it known.” He then goes on to describe the toll that it played on his relationship. “I had a lot of problems with my relationship with my fiancé… just feeling like we were both also so overwhelmed with things, because it’s like one thing after another.” (34-year-old male, Graduate Student).
This study aimed to deepen our understanding of the Long COVID experience, with a specific emphasis on supports that facilitate improvement in Long COVID and possible reintegration into social and professional spheres. We identified three domains that clarify the support needs of people with Long COVID: (1) occupational and financial support; (2) social and emotional support; and (3) healthcare support. These domains do not exist independently, they are overlapping and interrelated. To adequately address the needs of the individuals included in this study, an integrated, holistic approach is necessary.
People with Long COVID and their families experienced significant financial hardship due to employment barriers and healthcare costs. This is echoed in the existing qualitative research, which identifies financial challenges as a key issue facing those experiencing Long COVID and a contributor to psychological distress [ 30 ]. Although participants wanted to return to work, the persistent symptoms of Long COVID frequently led to job loss or impaired their ability to perform required tasks. Employer accommodations were inadequate even for those who were able to maintain employment. Beyond financial distress and high healthcare costs, participants encountered diagnostic challenges, scarce specialty appointments, insurance loopholes, and medical skepticism, which drove their healthcare support needs. Although qualitative research among people experiencing Long COVID is limited within the U.S. healthcare system, these findings are shared across the U.K [ 30 ]. and Spain [ 31 ], identifying healthcare-related discrimination and stigma in European healthcare systems. Patients leveraged social networks to deal with these deficiencies in the healthcare and social service systems. Ultimately, improvement in the occupational and healthcare domains may alleviate the strain that chronic disability places on family and friends in the social sphere.
Addressing these systemic issues requires major shifts in the way medicine is practiced and social services are regulated [ 32 ]. Fortunately, numerous policy recommendations already exist aimed at addressing the support needs identified in this analysis. In April 2022, President Biden signed a presidential memorandum to create and strengthen support services for Long COVID treatment and for workers with Long COVID [ 33 ]. As part of the federal government’s acknowledgement of Long COVID as a disability under the Americans with Disabilities Act (ADA), the Department of Labor has issued guidance on supporting employees with Long COVID. The operationalization of this memo continues to develop along with our understanding of Long COVID. Advocacy groups have proposed policy recommendations and have advanced the TREAT Long COVID Act [ 34 ], CARE for Long COVID Act [ 35 , 36 ], and the Long COVID Recovery Now Act [ 37 ] to secure funding and enact policy changes for Long COVID research and social support systems. The Department of Health and Human Services produced the Health + Long COVID Human Centered Design Report [ 38 ], which had multiple suggestions that require policy support, as did a report from the Wellesley Institute [ 32 ]. Advocacy groups also advanced suggestions for research priorities [ 39 ], calls for Long COVID Centers of Excellence [ 40 ], and integration of research and advocacy in the infection-associated chronic illness space, including ME/CFS and dysautonomia [ 39 ]. Based on this study’s findings and review of relevant policy documents, we suggest a 5-pronged approach for future policy development.
Improve public awareness
Long COVID information must be presented as an inherent, vital part of COVID-19 messaging. Many participants in this study were frustrated by time-limited empathy from friends and colleagues who did not understand the chronic and ongoing nature of Long COVID. Participants experienced pressure from acquaintances and loved ones to “push through” their symptoms to their detriment. A recent analysis shows that there is a growing public interest in Long COVID information [ 41 ]. Advocates suggest declaring a Long COVID public health emergency with regular public information updates from the White House that would help to increase the public’s awareness of the prevalence, characteristics, and impact of Long COVID [ 34 , 35 , 36 , 42 ]. Long COVID messaging should be targeted toward marginalized groups who may have less access to health information [ 32 , 39 ]. Messaging should be culturally and linguistically appropriate for diverse groups to ensure the uptake of public health campaigns. Public information updates would also provide easy access to reliable, scientifically-sound information. Awareness campaigns should include symptom management and make recommendations based on available resources [ 35 , 36 , 38 ].
Improve clinical care quality and access
A recent study found that of people accessing Long COVID clinics, 40% traveled over one hour to access care, and more than 50% waited between one and three months for an appointment [ 43 ]. Our participants affirm the lived experience of these findings, expressing frustration about a lack of available, quality services. People with Long COVID need expanded access to virtual or geographically convenient locations, rapid appointments, and knowledgeable providers. The President’s emergency plan for AIDS relief or PEPFAR could be a model for a permanent Long COVID response that includes agency-based guidelines for clinicians, ongoing clinical education, healthcare facility training to increase access, and increased Long COVID education in medical and nursing schools [ 44 ]. A similar model would also help to streamline the clinical definition of Long COVID and mandate reimbursement for care standards [ 45 ]. More nuanced ICD-10 codes related to PEM or post-exertional symptom exacerbation (PESE), the pathognomonic symptom of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and common in people with Long COVID have been proposed to track treatment and improve service quality within marginalized communities and assure access to quality treatment [ 46 ].
School and workplace accommodations
Loss of employment among study participants and the need for additional workplace accommodations are demonstrated in the existing quantitative literature. Davis et al. (2021) showed that 22% of people experiencing Long COVID were not able to work, and another 45% needed reduced work schedules. [ 16 ] Because Long COVID appears to be more prevalent in people of working age compared to older adults, this impact on productivity has the potential for significant economic loss [ 47 ].
Our participants expressed specific needs for flexible work hours and options for remote work; difficulty accessing unemployment benefits and other social support services; and a desire for physical support to help with fatigue management. These needs are consistent with the “opportunities” identified in the Department of Health and Human Services Health + Long COVID report. Broader policy suggestions for addressing needs include creating government guidance regarding appropriate accommodations at school and at work [ 34 , 35 , 36 , 38 ], and involving occupational therapists and vocational rehabilitation specialists in determinations around reasonable accommodations [ 38 ]. Suggestions specific to individual workplaces include a change of role, reduced work hours, and the opportunity for remote work [ 32 , 38 , 48 ]. Additionally, workplaces can shift their focus to meeting goals or targets rather than hours spent in the office or online. This can help workplaces accommodate individuals’ needs for activity management strategies like symptom-contingent pacing.
Strengthen economic benefits and social services
Our study participants were older and more financially stable than the average American, and they may not fully represent minoritized or marginalized populations. Given the documented racial, ethnic, and income disparities in COVID-19 [ 49 ], it is important to consider the needs of these underrepresented populations during Long COVID policy creation and implementation. We anticipate that many people with Long COVID may benefit from expanded access to public benefit programs, such as the Supplemental Nutrition Assistance Program (SNAP), Temporary Assistance for Needy Families (TANF), Medicaid, Supplemental Security Income (SSI), and Social Security Disability Insurance (SSDI), especially if they continue to be unable to work. This is consistent with needs identified and policies suggested by multiple advocacy organizations [ 48 ]. Our participants discussed a need for assistance navigating existing programs suggesting a need for funding for Long COVID-literate, trauma-informed caseworkers to guide applicants through these programs [ 48 ].
Policy recommendations also included government organizations ensuring people with Long COVID had the ability to go on and off disability without reapplication [ 38 ]. Further, government programs could shoulder some of the economic burden of long-term disability on employers through programs like tax credits or loan forgiveness [ 38 ].
Improve research and data collection on Long COVID
Currently, there are many publications describing the epidemiology and symptomology of Long COVID, but there is a dearth of published research on Long COVID diagnostics and treatment. Participants in our study looked to alternative and unstudied treatments for Long COVID in their need for symptom relief. Increased federal funding for Long COVID research will help facilitate interventional research; and fast-tracking research for pharmaceutical interventions that have shown promise in infection-associated chronic illnesses, such as ME/CFS, postural orthostatic tachycardia syndrome (POTS), or mast cell activation syndrome (MCAS), will bring the possibility of relief to millions living with Long COVID [ 39 ]. Additionally, long-term, methodologically-sound Long COVID cohort studies are needed to better understand Long COVID onset after initial infection, reinfection, infection based on variant, and vaccination, as well as the course, symptomology, and effective management of Long COVID [ 46 ].
Although we discussed recommendations in several disparate policy areas, an integrated approach is necessary for effective and efficient COVID-19 policy implementation. This integration is not limited to policy professionals and public officials, but must also include employers, healthcare providers, as well as those living with and impacted by Long COVID.
There was a lack of racial/ethnic and socioeconomic diversity in this study. We are cautious in our interpretation of these findings because of the history of erasure of people marginalized by race, ethnicity, and economics in research and medicine. Further studies that focus on and center the experiences of people of color are warranted, as are studies that feature participants with different socioeconomic backgrounds. Additionally, the focus on cardiovascular symptoms during recruitment for the parent study may have led to a sample that skewed older, with more male participants, than the current Long COVID demographics suggest [ 16 ].
Additionally, because this was a qualitative sub-analysis nested within a parent study with separate aims and scientific underpinnings, the interview guide was not structured specifically to understand experiences of support. This analysis was inductive and exploratory. Thus, the results may not include the full breadth of perspectives on this topic. Future research should seek to comprehensively explore the support and access needs of people with Long COVID.
Availability of data and materials
Data cannot be shared publicly because it contains protected health information, and due to IRB confidentiality and data sharing restrictions. Data are available from the Johns Hopkins Medicine Institutional Data Access / Ethics Committee (contact via Phone: 410–502-2092 or E-Mail: [email protected]) for researchers who meet the criteria for access to confidential data.
The Americans with Disabilities Act
Severe Acute Respiratory Syndrome Coronavirus 2, or SARS-CoV-2
General Education Development
Post-Acute Sequelae of COVID-19 Infection
Mast Cell Activation Syndrome
Myalgic Encephalomyelitis/Chronic Fatigue Syndrome
Post-exertional symptom exacerbation
Postural Orthostatic Tachycardia Syndrome
Supplemental Nutrition Assistance Program
Supplemental Security Income
Social Security Disability Insurance
Temporary Assistance for Needy Families
United States Dollar ($)
World Health Organiaztion. WHO Coronavirus (COVID-19) Dashboard. Available from: https://covid19.who.int/ . Cited 2023 May 24.
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The authors acknowledge and thank the study participants for their contributions and openness throughout the interview process.
Alanna Bergman’s research and training is funded by the National Institute of Nursing Research (1F31NR020588), as well as the Johns Hopkins University School of Nursing Discovery and Innovation Award. Katherine McNabb’s training and research is supported by the National Institute of Allergy and Infectious Disease (F30AI165167).
Katherine C. McNabb and Alanna J. Bergman are co-first authors.
Authors and Affiliations
Center for Infectious Disease and Nursing Innovation, Johns Hopkins University School of Nursing, 525 N. Wolfe St., Baltimore, MD, 21205, USA
Katherine C. McNabb & Alanna J. Bergman
Johns Hopkins University, Johns Hopkins School of Nursing, Baltimore, USA
Rhonda Smith-Wright, Sarah E. Slone, Abeer Alharthi, Yvonne Commodore-Mensah & Oluwabunmi Ogungbe
Stanford University, Stanford School of Medicine, Palo Alto, USA
The Myalgic Encephalomyelitis Action Network, Santa Monica, USA
Johns Hopkins University, Johns Hopkins Institute for Clinical and Translational Research, Baltimore, USA
University of Wollongong, Wollongong, Australia
Patricia M. Davidson
Johns Hopkins University, Bloomberg School of Public Health, Baltimore, USA
Johns Hopkins University, Johns Hopkins School of Medicine, Baltimore, USA
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KM and AB contributed equally to this manuscript and consider themselves co-first authors. The contribution of the remaining authors is as follows: Conceptualization: OO, AB, KM, RW, YCM, and PD; Methodology: OO, AB, and KM; Formal Analysis: AB, KM, and RW; Writing – Original Draft Preparation: AB, KM, RW, JS, SS and OO; Writing – Review & Editing: AB, KM, RW, JS, SS, TT, AA, PD, YCM, and OO; Visualization: AB and KM; Policy Supplement: JS and KM; Supervision: OO, YCM, and PD; Funding Acquisition: OO.
The subjective position of the research team should be noted. Interviews were conducted by a team of all-female PhD students trained in qualitative methods, and masters students who served as note-takers and observers. Interviews were conducted on Zoom, thus, participants had varying levels of information about interviewers depending on whether cameras were enabled and what information interviewers chose to disclose. All interviewers introduced themselves by name to each participant. The analysis team consisted of three female PhD students who also acted as interviewers. Two of these were Black women and one White, all of whom identify as able-bodied, and one who lives with a chronic illness. We reflexively considered the power dynamics of the analysis and how that may have influenced decisions in coding, how we constructed themes and selected particular quotes. Throughout the history of academic publishing, researchers and scientists outside of the experiential group often speak for people with lived experience. In this case, the three PhD students were speaking for people with Long COVID. In an effort to include alternative perspectives and to respectfully represent those voices, we approached a scientific member of the Long COVID/ME/CFS advocacy community. She encouraged us to consider alternative framings that more authentically reflected experience, challenged sick/well narratives, and advocated for policy change.
Correspondence to Katherine C. McNabb .
Ethics approval and consent to participate.
The study received approval from Johns Hopkins Medicine Institutional Review Board (IRB00299548). All interview participants gave both oral and written consent and an electronic signature was obtained.
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The authors declare no competing interests.
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Additional file 1..
Synthesis of Long Covid Policy Recommendations.
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McNabb, K.C., Bergman, A.J., Smith-Wright, R. et al. “It was almost like it’s set up for people to fail” A qualitative analysis of experiences and unmet supportive needs of people with Long COVID. BMC Public Health 23 , 2131 (2023). https://doi.org/10.1186/s12889-023-17033-4
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Accepted : 20 October 2023
Published : 31 October 2023
DOI : https://doi.org/10.1186/s12889-023-17033-4
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Social media usage and students’ social anxiety, loneliness and well-being: does digital mindfulness-based intervention effectively work?
BMC Psychology volume 11 , Article number: 362 ( 2023 ) Cite this article
The increasing integration of digital technologies into daily life has spurred a growing body of research in the field of digital psychology. This research has shed light on the potential benefits and drawbacks of digital technologies for mental health and well-being. However, the intricate relationship between technology and psychology remains largely unexplored.
This study aimed to investigate the impact of mindfulness-based mobile apps on university students' anxiety, loneliness, and well-being. Additionally, it sought to explore participants' perceptions of the addictiveness of these apps.
The research utilized a multi-phase approach, encompassing a correlational research method, a pretest–posttest randomized controlled trial, and a qualitative case study. Participants were segmented into three subsets: correlations ( n = 300), treatment ( n = 60), and qualitative ( n = 20). Data were gathered from various sources, including the social anxiety scale, well-being scale, social media use integration scale, and an interview checklist. Quantitative data was analyzed using Pearson correlation, multiple regression, and t-tests, while qualitative data underwent thematic analysis.
The study uncovered a significant correlation between social media use and the variables under investigation. Moreover, the treatment involving mindfulness-based mobile apps led to a reduction in students' anxiety and an enhancement of their well-being. Notably, participants held various positive perceptions regarding the use of these apps.
The findings of this research hold both theoretical and practical significance for the field of digital psychology. They provide insight into the potential of mindfulness-based mobile apps to positively impact university students' mental health and well-being. Additionally, the study underscores the need for further exploration of the intricate dynamics between technology and psychology in an increasingly digital world.
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The field of digital psychology is undergoing rapid evolution, navigating the intricate intersection of psychology and technology to elucidate the profound impact of digital technologies on human behavior, cognition, and emotions [ 1 , 2 ]. With digital technologies becoming increasingly ingrained in our daily lives, researchers are embarking on a journey to explore the multifaceted implications they bear for mental health and overall well-being. Within the realm of digital psychology, a diverse array of topics has captured the attention of investigators, encompassing the innovative use of technology for psychological interventions like cognitive-behavioral therapy (CBT) and mindfulness-based stress reduction (MBSR) [ 1 , 2 ]. Furthermore, scrutiny has extended to the influence of social media on mental health, unveiling the potential for excessive social media use to contribute to feelings of anxiety and loneliness [ 3 , 4 ].
The exploration of digital psychology has also delved into the impact of video games on cognitive and emotional faculties, with some studies suggesting that specific genres of video games have the potential to enhance attention and problem-solving skills [ 5 , 6 ]. However, concerns surrounding video game addiction and the potential influence of violent video games on aggressive behavior have been the subject of extensive investigation [ 7 , 8 , 9 , 10 ]. The ubiquity of digital technologies in our daily existence has ignited a burgeoning interest in the domain of digital psychology. While research in this domain has yielded valuable insights into the prospective benefits and hazards of digital technologies for mental health and well-being, there remains a vast expanse of knowledge yet to be uncovered regarding the intricate interplay between technology and psychology. Specifically, there is a compelling need for an extensive body of research aimed at comprehending the enduring impacts of digital technologies on cognitive, emotional, and social functionality. Furthermore, it is crucial to decipher how these effects may vary among diverse demographic groups.
One particularly promising avenue of research within digital psychology is the integration of mindfulness-based mobile applications, which has shown considerable potential in alleviating symptoms of anxiety and loneliness. These applications typically offer guided meditation, breathing exercises, and various mindfulness practices that are readily accessible via mobile devices [ 2 ]. Their accessibility and user-friendly nature render them an appealing resource for individuals seeking to enhance their mental well-being without the need for traditional face-to-face therapy [ 3 , 6 ].
In the contemporary landscape of higher education, university students are exposed to the pervasive influence of social media, which has the potential to induce negative psychological consequences such as heightened social anxiety and increased feelings of loneliness. The omnipresence of social media platforms can foster a sense of comparison, social pressure, and disconnection among undergraduate students, amplifying the challenges they already face. Given these circumstances, there is a compelling need to explore interventions that can counteract these adverse impacts, and mindfulness-based interventions emerge as a promising avenue for consideration.
By examining the intersection of these interventions with the digital sphere, this study seeks to illuminate how Digital Mindfulness-based treatments might serve as a potent tool to mitigate the detrimental effects of social media exposure, thereby fostering a healthier psychological landscape among university students [ 11 , 12 , 13 , 14 , 15 ].
Furthermore, many of these applications provide personalized features such as progress tracking and goal setting, which enhance user engagement and motivation [ 9 ]. As the popularity of these applications continues to soar, it becomes imperative to further investigate their effectiveness across various demographic cohorts and contextual settings, as well as to identify the most potent features and interventions for fostering improvements in mental health [ 10 ].
The rationale for this study is firmly grounded in the contemporary higher education landscape, where undergraduate students navigate a myriad of challenges that may impact their mental well-being. With the pervasive integration of digital technologies into students' lives, the investigation of Digital Mindfulness-based interventions becomes not only relevant but crucial. The novelty of this study lies in its exploration of the intricate relationship between social media usage and the well-being of university students, specifically targeting social anxiety and loneliness. Moreover, it introduces an innovative approach by examining the effectiveness of digital mindfulness-based interventions in ameliorating these psychological challenges. By addressing this uncharted territory, the study not only contributes to the growing field of digital psychology but also offers valuable insights into the potential of technology-driven mindfulness interventions as a means to enhance the mental well-being of the digital-native student population. This unique blend of investigating the impact of technology on psychological well-being while simultaneously assessing the effectiveness of digital interventions positions the study at the forefront of contemporary research in the field. Given the potential benefits of digital mindfulness apps in reducing anxiety and loneliness, coupled with the distinct challenges that emerge during the undergraduate phase, this research seeks to provide invaluable insights into the perceptions and experiences of students. By delving into the perceptions of adults regarding these treatments, this study aspires to shed light on the feasibility, effectiveness, and potential limitations of digital mindfulness-based interventions for enhancing the mental health of undergraduate students in the modern digital age. Therefore, this study endeavors to address the following critical questions:
What is the relationship between social media use and symptoms of social anxiety, loneliness, and well-being among university students?
Does the use of a mindfulness-based mobile app intervention result in significant improvements in social anxiety, loneliness, and well-being in college students?
What are university students’ perspectives on the use of technology for mental health support, including the benefits and challenges of using technology for this purpose?
Review of literature
The study investigating the effects of mindfulness-based mobile apps on university students' anxiety, loneliness, and well-being in the context of social media usage draws upon a multifaceted theoretical framework. At its core, it is rooted in mindfulness theory, which emphasizes present-moment awareness and non-judgmental acceptance to alleviate stress and anxiety [ 5 , 6 , 7 , 8 ]. To understand the influence of social media on students, social cognitive theory is relevant, as it explores how individuals learn from observing others in their social networks. Additionally, social comparison theory informs the study by shedding light on how students may constantly compare themselves to others on social media, potentially leading to feelings of loneliness and social anxiety [ 11 , 12 , 13 , 14 , 15 ]. The study also taps into addiction and compulsive behavior theories to comprehend the perceived addictiveness of mindfulness-based mobile apps. Technology acceptance models (TAM) help in understanding user acceptance and perceptions of these apps. Moreover, the study aligns with principles of positive psychology by aiming to enhance well-being and reduce anxiety and loneliness, which are central concerns in this field. Finally, media effects theories, like cultivation theory and uses and gratifications theory, inform the exploration of how social media use affects students' mental health and well-being [ 13 ]. This multifaceted theoretical approach provides a comprehensive foundation for unraveling the intricate relationship between technology, psychology, and well-being in the digital age, offering a well-rounded perspective on the research questions at hand [ 12 , 13 ].
Social media and symptoms of mental health
The use of social media has become increasingly prevalent among university students, and with it comes growing concern about its potential impact on mental health and well-being. Specifically, research has focused on the relationship between social media use and symptoms of social anxiety, loneliness, and well-being among university students. The majority of studies focused on the relationship between social media use and symptoms of social anxiety and/or loneliness. These studies generally found that higher levels of social media use were associated with greater symptoms of social anxiety and loneliness among university students [ 11 , 12 , 13 , 14 , 15 , 16 ]. For example, Schønning et al. [ 16 ] found that social media use was positively associated with symptoms of social anxiety among Chinese university students. Similarly, a study by Wang et al. [ 13 ] found that social media use was positively associated with symptoms of loneliness among Chinese university students.
Two studies focused on the relationship between social media use and well-being. One study found that higher levels of social media use were associated with lower levels of well-being among university students [ 17 ] Another study found that social media use had a curvilinear relationship with well-being, such that moderate levels of social media use were associated with higher levels of well-being, while both low and high levels of social media use were associated with lower levels of well-being [ 13 ].
The findings of this literature review suggest that social media use may be associated with greater symptoms of social anxiety and loneliness among university students. However, the relationship between social media use and well-being is less clear, with some studies suggesting a negative relationship and others suggesting a curvilinear relationship. Several additional studies have also examined this relationship. For example, a study by Kose and Dogan [ 18 ] found that social media use was negatively associated with psychological well-being among Turkish university students. Another study by Błachnio, et al., [ 19 ] found that Facebook addiction was negatively associated with self-esteem and life satisfaction among Polish university students. Similarly, Chen et al. [ 20 ] conducted a systematic review of 23 studies examining the relationship between social media use and mental health outcomes among college students. The authors concluded that social media use was generally associated with negative mental health outcomes, including loneliness, anxiety, and stress. However, they noted that the strength of this relationship varied across studies and suggested that more research was needed to better understand the mechanisms underlying this relationship. In another study, Seabrook et al. [ 21 ] conducted a systematic review of 20 studies examining the relationship between social networking sites and loneliness and anxiety. They found that social networking sites were associated with both loneliness and anxiety, but that the strength of this relationship varied across studies and depended on factors such as frequency and intensity of social networking site use and individual differences in vulnerability to mental health problems. Similarly, Tandoc Jr. et al. [ 14 ] conducted a study examining the relationship between Facebook use, envy, and depression among college students in the United States. They found that Facebook use was positively associated with envy, which in turn was positively associated with depression. They suggested that envy may be a mechanism underlying the relationship between social media use and negative mental health outcomes.
Mindfulness-based apps effect mental health
Mindfulness-based mobile apps are becoming increasingly popular as a tool for promoting mental health and wellbeing. These apps include a variety of different mindfulness-based practices, such as guided meditations, breathing exercises, and other techniques aimed at reducing stress and anxiety. While there is growing evidence that mindfulness-based interventions can be effective in promoting mental health, less is known about the effectiveness of these interventions when delivered via mobile apps. This literature review aims to synthesize the existing research on mindfulness-based mobile apps and mental health outcomes.
The majority of studies focused on the effectiveness of mindfulness-based mobile apps in reducing symptoms of anxiety and depression. These studies generally found that mindfulness-based mobile apps were effective in reducing symptoms of anxiety and depression in a variety of populations, including college students, adults, and individuals with chronic medical conditions [ 2 , 10 , 22 , 23 , 24 ]. For example, a study by Strauss et al. [ 23 ] found that a mindfulness-based mobile app was effective in reducing stress and improving coping skills in a sample of healthcare workers. Similarly, a study by Lomas et al. [ 24 ] found that a mindfulness-based mobile app was effective in reducing stress and improving resilience in a sample of university students. In addition to examining the effectiveness of mindfulness-based mobile apps, several studies explored the factors that influence user engagement and adherence to these interventions. For example, a study by Valinskas et al. [ 25 ] that users who were using the app for more than 24 days and had at least 12 active days during that time had 3.463 (95% CI 1.142–11.93) and 2.644 (95% CI 1.024–7.127) times higher chances to reduce their DASS-21 subdomain scores of depression and anxiety, respectively. Another study by Linardon, et al. [ 22 ] found that interventions that were more interactive and personalized were more effective in promoting user engagement and adherence.
Some studies also explored the effectiveness of mindfulness-based mobile apps in addressing other mental health conditions beyond anxiety and depression. For example, a study by Wahbeh et al. [ 10 ] found that a mindfulness-based mobile app intervention was effective in reducing symptoms of posttraumatic stress disorder (PTSD) in a sample of veterans. Similarly, a study by Biegel et al. [ 26 ] found that a mindfulness-based mobile app intervention was effective in reducing symptoms of ADHD in a sample of adolescents.
The use of technology for mental health support
The utilization of technology for the provision of mental health support has gained increasing prominence within the context of university students, prompting a burgeoning interest in comprehending their encounters and viewpoints. Related inquiries have been undertaken in diverse geographical regions, including the United States, Canada, Australia, and the United Kingdom. Predominantly, these investigations have centered on the advantages and obstacles inherent in employing technology for mental health support. Generally, these inquiries have ascertained that technology is perceived as a convenient and readily accessible modality for accessing mental health support services among university students [ 27 , 28 , 29 , 30 ]. For instance, Birnbaum et al. [ 27 ] conducted a study revealing that college students in the United States exhibited a willingness to engage with mental health applications to manage their stress and anxiety. Nevertheless, certain studies have also discerned impediments associated with the adoption of technology for mental health support, encompassing apprehensions regarding privacy and confidentiality [ 27 , 28 , 29 , 30 ], concerns about the quality and dependability of information [ 29 ], and challenges related to navigating and effectively utilizing mental health applications [ 30 ].
Additionally, two investigations have focused their attention on delineating the determinants influencing the utilization of technology for mental health support among university students. These studies have identified an array of factors exerting an influence over students' engagement with technology for mental health support, encompassing individual attributes (e.g., mental health literacy, technological attitudes) [ 31 ], societal influences (e.g., stigma, peer support) [ 31 ], and environmental considerations (e.g., technology availability, access to mental health services). The cumulative insights garnered from this comprehensive literature review underscore the potential of technology as a convenient and accessible avenue for accessing mental health support among university students. However, it is essential to acknowledge that complexities and multifaceted dynamics underlie the factors influencing its utilization, and an array of challenges remain associated with its application in this context.
Likewise, a study conducted by Kern et al. [ 32 ] documented that 23.8% of users reported experiencing a positive impact on their mental health through the use of mental health applications. Notably, individuals who had received mental health services within the past 12 months exhibited a significantly higher propensity to embrace mental health apps in comparison to those who had not accessed such services. The allure of convenience, immediate availability, and confidentiality emerged as prevalent factors driving interest in Mental Health Apps (MHAs).
Furthermore, a study conducted by Free et al. [ 33 ] unveiled the unsurprising proliferation of numerous mobile applications designed to aid in the diagnosis, monitoring, and management of health conditions, albeit with varying levels of efficacy. Similarly, research by Brindal et al. [ 34 ] found that participants who had intermittent access to a smartphone app over a 4-week trial period demonstrated notable enhancements in indicators of emotional well-being. This broader observation suggests that uncomplicated and easily accessible solutions can yield substantial improvements in overall well-being. In addition, a study by Karyotaki et al. [ 35 ] reported the effectiveness of web-based interventions in mitigating the symptoms of depression and anxiety among college students.
This was a multi-phase research design. In the first phase, a correlational research method was used for exploring the correlation among the research variables. In the second phase, we used a pretest–posttest randomized controlled trial to assess the effectiveness of a mindfulness-based mobile app intervention on symptoms of anxiety, loneliness, and well-being. Moreover, in the third phase, a qualitative research method was used for exploring the participants’ perceptions of mindfulness-based intervention.
Participants for this study were selected from graduate students at Zhoukou Vocational and Technical College in China. Three separate groups were recruited for the study. The first group consisted of 300 participants who were recruited for a correlational study related to question 1. The eligibility criteria for this group were as follows: participants must be graduate students at Fudan University and willing to participate in the study. The sample size was determined based on power analysis and the expected effect size. The second group consisted of 100 participants who were recruited for question 2. The eligibility criteria for this group were the same as for the first group. Participants were randomly assigned to either an intervention group or a control group. The third group consisted of 20 participants who were recruited for question 3. The eligibility criteria for this group were the same as for the first two groups. Participants were selected using purposive sampling based on their responses to the questionnaire in question 2. All participants provided informed consent prior to participating in the study. The study was approved by the Institutional Review Board at Zhoukou Vocational and Technical College. Participants were assured of confidentiality and the right to withdraw from the study at any time without penalty.
The following instruments were used to collect data for this study:
Social Anxiety Scale for Adolescents (SAS-A)
It is a 22-item self-report questionnaire that measures social anxiety in adolescents [ 36 ]. SAS-A assesses various aspects of social anxiety, including fear of negative evaluation, social avoidance and distress, and physiological symptoms such as sweating and blushing. Each item is measured on a 5-point Likert scale, ranging from 1 (not at all) to 5 (extremely). The total score on the SAS-A ranges from 22 to 110, with higher scores indicating higher levels of social anxiety.
Warwick-Edinburgh Mental Well-being Scale (WEMWBS)
It is a 14-item self-report questionnaire that measures mental well-being in adults and adolescents [ 37 ]. The items on the WEMWBS assess various aspects of mental well-being, including optimism, positive relationships, and a sense of purpose. Participants rate each item on a 5-point Likert scale, ranging from 1 (none of the time) to 5 (all of the time). The total score on the WEMWBS ranges from 14 to 70, with higher scores indicating higher levels of mental well-being. The fourth instrument was social.
Social Media Use Integration Scale (SMUIS)
The SMUIS is a 10-item self-report questionnaire that assesses the frequency, duration and emotional connection to social media use [ 38 ]. The SMUIS includes questions related to the frequency and duration of social media use, as well as questions related to the emotional connection to social media use, such as "How often do you feel happy when using social media?" and "How often do you feel anxious when you are not able to use social media?" Participants are asked to rate each item on a 5-point Likert scale, ranging from 1 (never) to 5 (always). The reliability of the instruments was estimated using Cronbach’s alpha. Results revealed that the obtained Cronbach’s alpha for the instrument was above, 0.78 indicating that all used instruments enjoyed an acceptable level of reliability.
The interview checklist consisted of 8 open-ended questions followed by the interviewer’s prompts. The questions elicited the interviewees’ perceptions of the benefits and challenges of using mobile apps for improving mental health and well-being and reducing social anxiety symptoms and loneliness (See Additional file 1 ). The interview checklist was approved by 4 colleagues and there was a high agreement among the panel of experts regarding the relevance of the interview questions.
Mindfulness-based mobile apps
Mindfulness-based mobile apps are mobile applications designed to help individuals develop mindfulness skills and reduce symptoms of stress, anxiety, and depression. These apps typically include guided mindfulness exercises, educational resources, and other features to help individuals practice mindfulness on a regular basis. The specific features of mindfulness-based mobile apps may vary but typically include guided meditations, breathing exercises, and other mindfulness practices. Some apps may also include educational resources, such as articles or videos that provide information about mindfulness and its benefits. Many apps also include features for tracking progress, setting goals, and sharing progress with others. In this study, the participants who participated in the treatment phase were asked to download popular mindfulness-based mobile apps including Headspace, Calm, and Insight Timer. These apps are available for download on mobile devices and offer a range of mindfulness exercises and resources for users to explore.
The study was conducted in multiple steps. Initially, a sample of 300 graduate students from Fudan University was selected to participate in the research. These participants were asked to complete the Social Media Use Integration Scale (SMUIS) and the Depression Anxiety Stress Scales (DASS-21) to evaluate their social media use and mental health status. Next, a sample of 60 students from the same university was selected for the intervention study. These participants were randomly assigned to either an intervention group or a control group. The intervention group was given access to a mindfulness-based mobile app for eight weeks, while the control group received no intervention. Both groups completed the SMUIS and the DASS-21 at baseline, post-intervention, and three-month follow-up to evaluate the effectiveness of the intervention. Lastly, a qualitative study was conducted to gather in-depth information about the participants' experience with the mindfulness-based mobile app intervention. A purposive sample of 20 participants from the intervention group was selected for this study. They underwent semi-structured interviews to provide qualitative data about their perceptions and opinions regarding the intervention.
For the quantitative data, the statistical software was employed. Firstly, descriptive statistics were calculated to determine the mean, and standard deviation of the Social Media Use Integration Scale (SMUIS) and Depression Anxiety Stress Scales (DASS-21) scores, as well as the mean, and standard deviation of the SMUIS and DASS-21 scores at baseline, post-intervention, and three-month follow-up for both the intervention and control groups. Secondly, bivariate correlations were conducted to examine the relationship between social media use and symptoms of anxiety and depression. Thirdly, multiple regression analysis was performed to determine the unique contribution of social media use to symptoms of anxiety and depression while controlling for other relevant variables. Fourthly, repeated measures ANOVA was conducted to examine changes in SMUIS and DASS-21 scores over time and to determine if there were differences between the intervention and control groups. Finally, post hoc tests were conducted to examine differences between groups at each time point. Effect sizes were calculated to determine the magnitude of the intervention's effects. However, for the qualitative data, the qualitative analysis software was employed. Firstly, the transcripts of the semi-structured interviews were analyzed using thematic analysis to identify themes and subthemes related to participants' experiences with the mindfulness-based mobile app intervention. Secondly, quotes were selected to support and illustrate the identified themes and subthemes. Lastly, the themes and subthemes were interpreted and discussed to provide insight into participants' perceptions and opinions regarding the intervention.
Pearson correlations between the variables were estimated and results are presented in Table 1 .
This table shows that social media use is negatively correlated with well-being ( r = -0.21, p < 0.01) and positively correlated with symptoms of social anxiety ( r = -0.35, p < 0.01) and loneliness ( r = 0.24, p < 0.01). Additionally, symptoms of social anxiety are positively correlated with loneliness ( r = 0.47, p < 0.01) and negatively correlated with well-being ( r = -0.61, p < 0.01), while loneliness is negatively correlated with well-being ( r = -0.50, p < 0.01). These results suggest that social media use is associated with poorer mental health outcomes, including higher levels of social anxiety and loneliness and lower levels of well-being, among university students.
Table 2 shows the results of a multiple regression analysis that examined the relationship between social media use, social anxiety, and loneliness as predictor variables and well-being as the outcome variable. The regression equation is:
The results indicate that all three predictor variables significantly contributed to the prediction of well-being, with social media use (β = -0.29, p = 0.001), social anxiety (β = 0.31, p = 0.001), and loneliness (β = 0.28, p = 0.001) each having a significant unique effect on well-being, after controlling for the other variables. The constant term (B = 3.10, p = 0.001) represents the predicted well-being score when all predictor variables are held at zero.
Research question 2
The second research aimed at investigating the effects of the intervention on the students’ social anxiety, loneliness, and well-being. Results are presented in Table 3 .
This table presents the results of a pretest–posttest randomized control-experimental research design investigating the effects of a mindfulness-based mobile app intervention on social anxiety, loneliness, and well-being in college students. The results indicate that the intervention group showed a significant improvement in social anxiety (F (1, 98) = 17.23, p < 0.001, partial eta squared = 0.15), loneliness (F (1, 98) = 13.70, p < 0.001, partial eta squared = 0.12), and well-being (F(1, 98) = 21.41, p < 0.001, partial eta squared = 0.18) from pretest to posttest. The control group did not show significant changes in any of the measures. The effect sizes (partial eta squared) ranged from moderate to large, indicating that the intervention had a meaningful impact. These findings suggest that the use of a mindfulness-based mobile app intervention can be an effective approach for improving mental health outcomes in college students.
Research question 3
The third research question explored the students’ perceptions of the effects of mindfulness-based mobile apps on the students’ social anxiety, loneliness, and well-being. The detailed analysis of the interviews revealed 6 benefits and 4 challenges of using technology for mental health support. The first extracted benefit as mentioned by 10 students was thematically coded "Convenience and Accessibility". Participants reported that technology-based mental health support services are convenient and accessible, allowing them to access support anytime and anywhere. The following quotations exemplify the theme:
"I like using mental health apps because I can access them whenever I need to. I don't have to wait for an appointment or anything like that." (Student 3). Another student stated, "Online support groups are great because I can connect with people who have similar experiences no matter where I am."(student 11).
The second extracted benefit was thematically coded "Anonymity and Privacy". Participants appreciated the ability to access mental health support services online while maintaining anonymity and privacy. For instance, student 5 stated, "I like that I can access support without having to go to an office or talk to someone face-to-face. It feels less intimidating." This finding was also confirmed by student 6, who stated, "I feel more comfortable talking about my mental health online because I know that no one else needs to know about it."
The third extracted benefit was thematically coded "Customizable and Tailored Support". Participants appreciated the range of options available for mental health support online, including customizable and tailored support that they could access at their own pace. For instance, student 11 stated, "I like that I can choose the type of support that works for me. Some days I just need to read something and other days I need to talk to someone”. Similarly, student 6 stated, "The mental health app I use sends me reminders to check in with myself and practice self-care. It's nice to have that kind of tailored support."
The fourth extracted benefit was thematically coded as "Cost-effective". Participants reported that technology-based mental health support services are often more affordable than traditional face-to-face therapy, making them a more accessible option for those with limited financial resources. This finding was supported by student 17 who stated, "I can't afford traditional therapy, so using mental health apps is a great option for me since it's usually free or very affordable." Similarly, one of the students stated, “Online therapy is much cheaper than traditional therapy, so it's more accessible for people who can't afford to pay a lot."
The fifth extracted benefit was thematically coded as "Increased Awareness and Education". Participants reported that technology-based mental health support services helped them to become more aware of their mental health and provided education about mental health issues and coping strategies. For example, student 12 stated, "The mental health app I use has taught me a lot about mindfulness and how to manage my anxiety." Student 14 also stated, "I learned a lot about depression and how to cope with it from an online support group I joined."
The sixth extracted benefit was thematically coded as "Reduced Stigma". Participants reported that accessing mental health support services online helped to reduce the stigma associated with seeking mental health The following quotations exemplify the theme of support. For instance, one of the students stated, “I used to feel ashamed about seeking mental health support, but using mental health apps has helped me realize that it's okay to take care of my mental health." (Student 9). Similarly, another student argued, “Online support groups have helped me realize that I'm not alone in my struggles with mental health. It's nice to know there are others out there who understand."
Despite the above-mentioned benefits, the participants mentioned some challenges. The first extracted challenge was thematically coded "Quality and Accuracy of Information". Participants expressed concerns about the quality and accuracy of mental health information available online, and the potential for misinformation to be spread. For instance, student 11 stated, "There's so much information online, it's hard to know what's trustworthy and what's not." Another student stated, "I worry that some of the mental health information I see online is not based on evidence and could actually be harmful."(student 6).
The second extracted challenge was thematically coded as "Lack of Human Connection". Participants reported missing the human connection they would get from traditional face-to-face therapy and felt that technology-based mental health support services lacked the same level of personal connection. The following quotations from student 12 exemplify the theme:
"Sometimes I just need someone to talk to face-to-face. It's not the same as talking to a computer screen…. I miss the empathetic listening I would get from a therapist in person. It's hard to replicate that online."
The third extracted challenge was thematically coded as "Technical Difficulties". Participants reported experiencing technical difficulties with technology-based mental health support services, which could be frustrating and hinder their ability to access support. For instance, student 8 stated, “Sometimes the mental health app I use glitches or crashes, which can be really frustrating when I'm trying to use it for support…. I don't have the best internet connection, so sometimes it's hard to access online support groups."
The fourth extracted challenge was thematically coded "Privacy and Security Concerns". Participants expressed concerns about the privacy and security of their personal information when using technology-based mental health support services, and whether their information was being shared without their consent. As an example, student 13 stated, "I worry that my personal information could be shared without my consent, which would be a huge breach of trust." Student 9 also stated, “It's hard to know if my information is really secure when I'm using online mental health support services."
The study investigating the effects of mindfulness-based mobile apps on university students' anxiety, loneliness, and well-being in the context of social media usage is anchored in a multifaceted theoretical framework. At its core, the research draws upon mindfulness theory, a foundational framework emphasizing present-moment awareness and non-judgmental acceptance to alleviate stress and anxiety [ 5 , 6 , 7 , 8 ]. This theory forms the bedrock of the study's understanding, as mindfulness-based mobile apps are designed to foster these very principles, encouraging users to engage with the present, accept their experiences without judgment, and, in doing so, mitigate stress and anxiety.
In parallel, to fathom the intricate influence of social media on university students, the study leverages social cognitive theory, a framework highly pertinent for analyzing how individuals acquire and adapt behaviors, attitudes, and emotional responses through observation and modeling within their social networks [ 11 , 12 , 13 , 14 , 15 ]. Given the pervasive role of social media, this theory is essential for comprehending how the behaviors, emotions, and attitudes of students may be shaped by the content and interactions they encounter in the digital realm.
Moreover, the research takes into consideration social comparison theory, which underscores how social media users frequently engage in relentless self-comparisons with others, potentially fostering feelings of loneliness and social anxiety [ 11 , 12 , 13 , 14 , 15 ]. This theory is critical for acknowledging the "highlight reel" effect, wherein users predominantly share their positive experiences and achievements, inadvertently prompting social comparison and potentially engendering negative emotional responses.
In the exploration of the perceived addictiveness of mindfulness-based mobile apps, the study employs addiction and compulsive behavior theories. These theories unearth the underlying factors contributing to the allure and habit-forming nature of certain digital interventions, thereby offering valuable insights into the psychology of user engagement and potential addiction [ 12 , 13 ]. When assessing user acceptance and perceptions of mindfulness-based mobile apps, the study draws from technology acceptance models (TAM). TAM provides a valuable framework for unraveling the intricacies of user adoption and attitudes toward technology-based interventions, elucidating critical factors like perceived usefulness and ease of use, which shed light on participants' acceptance of these apps [ 12 , 13 ].
Furthermore, the research aligns with the principles of positive psychology, a framework that centers on the enhancement of human well-being and strengths. The study's focus on bolstering well-being and mitigating anxiety and loneliness aligns closely with the core tenets of positive psychology, making it a pertinent theoretical perspective [ 12 , 13 ].
Lastly, media effects theories, such as cultivation theory and uses and gratifications theory, play a pivotal role in offering insights into how social media usage affects students' mental health and well-being [ 13 ]. Cultivation theory underscores the potential long-term impact of repeated exposure to media content, while uses and gratifications theory delves into how individuals actively use and engage with media to fulfill specific needs and gratifications.
By encompassing this multifaceted theoretical approach, the study constructs a comprehensive foundation for unraveling the intricate relationship between technology, psychology, and well-being in the digital age. This holistic perspective serves as a valuable compass in navigating the complexities of the research questions at hand, offering a deeper understanding of how these factors interconnect and influence one another [ 12 , 13 ]. Additionally, the study incorporates media effects theories to further enrich its theoretical foundation. Cultivation theory, as one of the key media effects theories, underlines the potential long-term consequences of repeated exposure to media content. Given the omnipresence of social media in the lives of university students, understanding how continuous media exposure might shape their perceptions and attitudes is crucial [ 39 , 40 , 41 , 42 , 43 , 44 , 45 ]. Moreover, uses and gratifications theory plays a pivotal role by exploring how individuals actively engage with media to fulfill specific needs and gratifications. In the context of the study, this theory sheds light on why students turn to social media, whether it's for social interaction, information seeking, or entertainment, and how these purposes might be linked to their mental well-being [ 13 ].
To round out the comprehensive theoretical framework, the study interweaves elements of positive psychology. This perspective emphasizes the enhancement of human well-being, positive emotions, and strengths. By striving to boost well-being and alleviate symptoms of anxiety and loneliness, the study directly aligns with the core principles of positive psychology. Positive psychology focuses on fostering qualities like resilience, optimism, and emotional intelligence, which are highly relevant to the study's objectives [ 46 , 47 , 48 , 49 , 50 ]. Thus, this framework adds a positive, growth-oriented dimension to the study's theoretical foundation, underscoring the importance of not only addressing negative mental health outcomes but also promoting positive psychological well-being [ 12 , 13 ].
In summary, the multifaceted theoretical framework encompassing mindfulness theory, social cognitive theory, social comparison theory, addiction and compulsive behavior theories, technology acceptance models (TAM), positive psychology, and media effects theories creates a robust and comprehensive foundation for unraveling the intricate relationship between technology, psychology, and well-being in the digital age. This holistic perspective enables the study to navigate the complexities of its research questions, offering a deeper understanding of how these factors interconnect and influence one another, and providing valuable insights into the impact of technology-driven interventions on the mental well-being of university students.
It can be concluded that the current findings add to the growing body of literature suggesting that social media use is linked to negative mental health outcomes. However, it is important to note that the causal direction of these relationships remains unclear. Although social media use may contribute to negative mental health outcomes, it is also possible that individuals who are already experiencing symptoms of anxiety and loneliness may use social media as a coping mechanism or to seek social support. Therefore, more research is needed to understand the complex relationship between social media use and mental health outcomes. It can also be concluded that the use of technology-based interventions can provide increased accessibility and convenience, anonymity and privacy, customizable and tailored support, cost-effectiveness, increased awareness and education, and reduced stigma. These findings demonstrate the potential of technology to offer effective and accessible mental health support for individuals in need.
The implications of investigating the relationship between social media usage and students' social anxiety, loneliness, and well-being within the context of digital mindfulness-based intervention are multifaceted. Firstly, as social media becomes increasingly integrated into students' lives, the study underscores the significance of understanding its potential repercussions on mental health. The findings can offer valuable insights to educational institutions, mental health professionals, and policymakers, prompting them to recognize the importance of promoting responsible social media usage among students. Secondly, the study's exploration of the effectiveness of digital mindfulness-based interventions in alleviating social anxiety, loneliness, and enhancing well-being holds significant implications for mental health intervention strategies. If proven efficacious, these interventions could serve as a practical and accessible means of addressing the psychological challenges posed by social media usage. This could potentially guide the development of tailored programs aimed at improving students' mental health and emotional resilience in the digital age. Furthermore, the study's focus on digital mindfulness-based interventions acknowledges the evolving nature of psychological interventions in the digital era. The implications of successful intervention highlight the potential of technology-assisted approaches to bridge the gap between traditional therapeutic methods and the modern digital landscape. This insight could inspire further innovation in mental health care, encouraging the integration of technology to reach wider audiences and promote positive mental well-being [ 51 ].
The current study also provides evidence that the intervention was effective in improving mental health outcomes over time. However, the study design does not allow us to determine the specific mechanisms by which the intervention was effective. Therefore, more research is needed to better understand how interventions can be optimized to improve mental health outcomes. Finally, while technology-based interventions can provide benefits such as convenience and accessibility, concerns about the quality and accuracy of mental health information available online, the lack of personal connection compared to traditional face-to-face therapy, and technical difficulties with accessing support have been reported by participants in this study.
Availability of data and materials
The data will be made available upon request from the author ( email: [email protected]).
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Phased Results of Key Projects of Vocational Education and Teaching Reform in Henan Province in 2021 (Project No.: Yujiao  57946).
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Sun, L. Social media usage and students’ social anxiety, loneliness and well-being: does digital mindfulness-based intervention effectively work?. BMC Psychol 11 , 362 (2023). https://doi.org/10.1186/s40359-023-01398-7
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DOI : https://doi.org/10.1186/s40359-023-01398-7
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The influence of Gamification on medical students’ diagnostic decision making and awareness of medical cost: a mixed-method study
- Kosuke Ishizuka 1 , 2 ,
- Kiyoshi Shikino 1 , 3 , 4 ,
- Hajme Kasai 4 , 5 , 6 ,
- Yoji Hoshina 1 ,
- Saito Miura 7 ,
- Tomoko Tsukamoto 1 , 6 ,
- Kazuyo Yamauchi 3 , 4 ,
- Shoichi Ito 4 , 6 &
- Masatomi Ikusaka 1
BMC Medical Education volume 23 , Article number: 813 ( 2023 ) Cite this article
The gamification of learning increases student enjoyment, and motivation and engagement in learning tasks. This study investigated the effects of gamification using decision-making cards (DMCs) on diagnostic decision-making and cost using case scenarios.
Thirty medical students in clinical clerkship participated and were randomly assigned to 14 small groups of 2–3 medical students each. Decision-making was gamified using DMCs with a clinical information heading and medical cost on the front, and clinical information details on the back. First, each team was provided with brief clinical information on case scenarios. Subsequently, DMCs depending on the case were distributed to each team, and team members chose cards one at a time until they reached a diagnosis of the case. The total medical cost was then scored based on the number and contents of cards drawn. Four case scenarios were conducted. The quantitative outcomes including confidence in effective clinical decision-making, motivation to learn diagnostic decision-making, and awareness of medical costs were measured before and after our gamification by self-evaluation using a 7-point Likert scale. The qualitative component consisted of a content analysis on the benefits of learning clinical reasoning using DMCs.
Confidence in effective clinical decision-making, motivation to learn diagnostic decision-making, and awareness of medical cost were significantly higher after the gamification. Furthermore, comparing the clinical case scenario tackled last with the one tackled first, the average medical cost of all cards drawn by students decreased significantly from 11,921 to 8,895 Japanese yen. In the content analysis, seven advantage categories of DMCs corresponding to clinical reasoning components were extracted (information gathering, hypothesis generation, problem representation, differential diagnosis, leading or working diagnosis, diagnostic justification, and management and treatment).
Teaching medical students clinical reasoning using DMCs can improve clinical decision-making confidence and learning motivation, and reduces medical cost in clinical case scenarios. In addition, it can help students to acquire practical knowledge, deepens their understanding of clinical reasoning, and identifies several important clinical reasoning skills including diagnostic decision-making and awareness of medical costs. Gamification using DMCs can be an effective teaching method for improving medical students’ diagnostic decision-making and reducing costs.
Peer Review reports
Clinical reasoning is a core competency for all health-care professionals; therefore, it is critical for medical students to develop clinical reasoning skills [ 1 , 2 ]. The process of clinical reasoning is a series of steps that include selecting and visiting a medical institution when a patient has a health problem, gathering information when the patient consults a medical professional, and making a tentative diagnosis [ 3 ]. In this process, history-taking, physical examination, clinical tests, referrals, and consultations are conducted, and a clinical decision/diagnosis is made. In addition, clinical reasoning has a context-specific nature [ 4 ]. For example, a physician can make two different diagnostic decisions despite examining two patients with the same chief complaint and similar history and physical examination findings [ 4 ].
Competencies that are important for teaching clinical reasoning can be categorized into five domains, each of which requires specific knowledge, skills, and behaviors [ 5 ]. These domains are: (1) clinical reasoning concepts, (2) history and physical examination, (3) choosing and interpreting diagnostic tests, (4) problem identification and management, and (5) shared decision-making. It is important to promote the acquisition of effective clinical reasoning skills for each of these processes by designing a curriculum with a specific purpose in terms of what, how, and when they are taught [ 3 , 5 ]. However, clinical reasoning is challenging for many novice students owing to inadequate knowledge, poor data collection skills, and inappropriate approaches to information processing [ 1 ].
Although it is important for medical students to learn the process of clinical reasoning, it is also important for them to learn the components such as communication skills, relationship of mutual trust among health-care professionals, evidence-based practice, reasoning outside of the medical context, patient-physician relationship and rapport with the patient, clinical skills of data collection (history-taking, physical examination, specific procedural skills), critical thinking, consideration of medical costs, explicit reliance on baseline probabilities, appropriate use of algorithms, visual-based diagnosis, and cognitive styles [ 6 ]. Furthermore, although diagnosis is a major component of the clinical reasoning process, it is important for students to develop management and decision-making skills that take into account various additional factors such as resources and cost-effectiveness [ 5 , 6 , 7 ]. Curbing medical expenses is a pressing issue in any country, but it is especially important to raise awareness in Japan, where the universal health insurance system and universal access provide patients with easy access to medical care, which has led to a high frequency of medical consultations [ 8 , 9 ]. In addition, in order to shorten the time required for a single consultation, diagnosis by laboratory or radiological examination, rather than using time-consuming medical interviews and physical examination, has become the norm [ 9 , 10 , 11 ]. This is a major reason for the increase in medical costs, and research has shown that both patients and doctors in Japan have a low level of awareness of medical costs [ 9 , 10 , 11 ]. A previous study of residents and clinical fellows in Japan reported that displaying fees at the time of ordering clinical tests in paper-based simulated cases resulted in cost reduction [ 9 ]. Intervention studies and education, audit and feedback, system-, incentive- or penalty-based interventions have been shown to be effective in increasing awareness of medical costs in several countries [ 12 , 13 , 14 , 15 , 16 ].
Although it is significant to acquire clinical reasoning skills through self-study, emphasis should also be placed on developing these skills using in-depth case studies [ 17 ]. The increasing use of technology to supplement learning resources for students in problem-based learning has recently attracted much attention in many areas of gamification [ 18 ]. Gamification is defined as “the use of game design elements in non-game contexts.” [ 19 ]. The gamification of learning increases student enjoyment, and motivation and engagement in learning tasks [ 18 , 20 , 21 ]. In addition, the usefulness of gamification in clinical reasoning education for health care professional education has been reported to date [ 22 , 23 ].
The purpose of this study is to investigate the effect of gamification using decision-making cards (DMCs) on diagnostic decision-making and awareness of medical costs in the clinical reasoning education of medical students.
To integrate quantitative and qualitative evaluation, a mixed-methods study was conducted using an exploratory sequential design [ 24 , 25 , 26 ]. This type of research study design takes advantage of the strengths of each type of study design and minimizes their shortcomings. Furthermore, it allows the researchers to understand the experimental results better by incorporating medical students’ perspectives. This is based on the US National Institutes of Health guidelines, which advocate a mixed-methods approach to research “to improve the quality and scientific power of data” and better address the complexity of issues in health science education [ 27 , 28 ].
A cross-sectional study was conducted using case scenarios to investigate the effects of gamification using DMCs on diagnostic decision-making and awareness of medical costs among medical students as a component of their clinical reasoning education. The quantitative outcomes included students’ confidence in effective clinical decision-making, motivation to learn diagnostic decision-making, and awareness of medical costs. In addition, the correctness of the final diagnosis was scored, and the total number of cards drawn, and the total medical cost were recorded.
A qualitative evaluation was conducted to examine the cognitive aspects of the medical students, which is thought to influence the learning effectiveness of clinical reasoning by gamification using DMCs.
The results of the quantitative and qualitative components were integrated as a mixed-methods, sequential explanatory study [ 24 , 25 , 26 ]. The qualitative data were collected using an open-ended questionnaire, and content analysis was used to investigate the advantages of clinical reasoning education for medical students through gamification using DMCs.
This study was conducted at a single facility in the Department of General Medicine of Chiba University Hospital in Japan. The study included all 30 medical students (two fourth-year medical students, 26 fifth-year medical students, and two sixth-year medical students) at the Chiba University School of Medicine who participated in a clinical clerkship (CC) in our department in November and December 2019. This study was embedded in their CC rotation in the department; thus, the participants were not sampled randomly. Additionally, it was conducted with medical students in the year of study in which they participated in CC. Therefore, we included students from different study years. Ahmad et al. reported that individual and small-group settings are ideal for gamification because they enhance students’ interest, effort, and motivation [ 29 ]. In addition, peer-assisted learning, which is defined as learning through matched-status individuals from “similar social groupings who are not professional teachers,” has been shown to improve medical students’ learning of clinical information and skills [ 30 ]. Therefore, in this study, considering these backgrounds and the number of participants, they were randomly assigned to 14 small-group teams, with each team consisting of 2–3 medical students. The gamification using DMCs for four case scenarios was implemented and the order in which the case scenarios were assigned to each team was randomized. All participants had already received lectures and simulation training in basic and clinical medicine by the fourth year and a pre-CC objective structured clinical examination as one of examinations for promotion to CC together with the Computer-Based Test, which is another assessment of medical knowledge applied before CC. Students who were unable to participate in one of the case scenarios for any reason were excluded from the study. We had to suspend this study because of the interruption in CCs by the COVID-19 pandemic. Therefore, we only analyzed the gathered data up till then.
The use of the DMCs was gamified. The DMCs had a clinical information heading and medical cost on the front of the card, and clinical information details on the back of the card (Figs. 1 and 2 ). First, each team was provided with brief clinical information on each case scenario (Supplement 1). DMCs were then distributed to each team according to the case scenario, and team members chose cards one at a time until they reached a diagnosis (Supplement 2). There was no limit to the number of times that a card could be drawn. The medical costs were calculated in Japanese yen [JPY]. (According to the foreign exchange rates on January 27, 2023, 1 JPY = 0.0062 Great Britain pound [GBP], 0.0077 US dollars [USD], or 0.0071 euro [EUR].) The four case scenarios were chest pain (herpes zoster), dyspnea (panic disorder), back pain (ureteral calculus), and abdominal pain (diverticulitis). The total number of cards and total medical costs for each case scenario are shown in Table 1 .
Type of cards on DMC
The front and back of DMC cards
The DMCs had a clinical information heading and medical cost on the front. In addition, these cards had the details of clinical information on the back. A letter of the alphabet on the DMC card was used as the card identifier.
Five faculty members (KI, KS, HK, YH, and SM) were randomly assigned to supervise the four case scenarios, with at least one faculty member assigned to each case scenario. Before conducting the gamification, each faculty member was given instruction on the case scenarios and the contents of the gamification. All instructions were standardized and were given immediately before the gamification (Supplement 3). Gamification using DMCs followed the simulation education methods with the steps of briefing, simulation, and debriefing. The faculty members briefed the students in advance to clarify the purpose of gamification using DMCs. The faculty members provided the following briefing (explanation of the rules before the start). “Teams of two or three students will be challenged with the problem.” “You will have 10 minutes to respond. When the time is up, the timekeeper will give you instructions.” “Question and answer sheets will be distributed. Answer sheets will be collected after the completion of the session. You may write notes on the answer sheet. Do not write on the question paper, as it will be used by other groups.” “Points are awarded for each correct diagnosis, and points are deducted for each additional card drawn.” “Please fill in the name of your group on the answer sheet and wait until the signal to begin.” During the gamification, which lasted approximately 10 min. students learned by using the DMCs independently under the supervision of the faculty members, without any intervention or lecture by the faculty members. Immediately after the gamification, the faculty members debriefed the students on the process of selecting the cards for approximately 10 min. The correct answers were given during the debriefing, and the students and the instructor reflected on the reasoning process. In addition, the diagnosis, number of cards drawn, the order in which the cards were drawn, and the appropriateness of the total medical cost were reviewed. Furthermore, the faculty members were able to give an example of the process model. Each faculty member was adequately skilled to explain the process of clinical reasoning to the participating students.
For each group, the gamification using DMCs was implemented using the four case scenarios. The order in which the case scenarios were assigned to each group was randomly assigned equally (Fig. 3 ). The case scenarios were selected through focus group discussion by two supervisors of the Department of General Medicine and one supervisor of Respiratory Medicine at the University (KI, KS, and HK). The four case scenarios of chest pain (herpes zoster), dyspnea (panic disorder), back pain (ureteral calculus), and abdominal pain (diverticulitis) were conducted (Table 1 ). The four case scenarios were selected because they present challenges in pattern recognition and can be used to assess analytical and diagnostic-reasoning skills. In Japan, the fourth version of the national core curriculum for undergraduate medical education, released in 2016, introduced a new list of possible diagnoses for 37 common signs, symptoms, and pathophysiological findings that ought to be learned as part of the six-year undergraduate curriculum [ 31 ]. Regarding these common signs, students must acquire the competence to anticipate a set of differential diagnoses from the earliest phase of the diagnostic process, and should gather information to confirm or refute an initial hypothesis, select and perform the relevant history-taking and physical examination, and interpret the findings to confirm or refute the initial hypothesis [ 31 , 32 ]. The four case scenarios were selected to include any one of the 37 common signs in the Japanese National Medical Examination questions.
Flow diagram of the design
Making the correct final diagnosis, number of cards drawn, and medical cost.
Each group calculated the total medical cost for each case scenario, and we compared the percentage making the correct final diagnosis, the total number of cards drawn, and the total medical costs for the first and last clinical case scenario exercises.
Confidence in effective clinical decision-making, motivation to learn diagnostic decision-making, and awareness of medical cost
The confidence in effective clinical decision-making, motivation to learn diagnostic decision-making, and awareness of medical cost were evaluated before and after the gamification using a 7-point Likert scale ranging from 1 (“strongly disagree”) to 7 (“strongly agree”). The content of the questionnaire survey was decided through focus group discussion by two supervisors of the Department of General Medicine and one supervisor of Respiratory Medicine at the University (KI, KS, and HK).
As this study also served as an educational program for a CC in our department, medical students who were assigned to the rotation at the beginning of the study period were included in the study. For the quantitative data, the sample size required for the Wilcoxon signed-rank test of the difference between the means of the two groups was calculated to be 28 students in total, assuming a significance level of 0.05, a power of 0.8, and an effect size of 0.5. However, we had to suspend this study because of the COVID-19 pandemic and only analyzed the data collected prior to the study suspension. Therefore, a total of 30 students distributed across 14 groups were included in the analysis.
All statistical analyses were performed using SPSS Statistics for Windows 26.0 (IBM Co., Armonk, NY, USA) with a significance level of less than 5%. The quantitative data are expressed as mean ± standard deviation (SD) unless otherwise indicated. The correct final diagnosis, the total number of cards drawn, and the total medical cost were compared using the Wilcoxon signed-rank test. We also compared confidence in effective clinical decision-making, motivation to learn diagnostic decision-making, and awareness of medical cost before and after the gamification using the Wilcoxon signed-rank test.
Following the quantitative evaluation, the qualitative evaluation was conducted to evaluate the cognitive aspects of the intervention on medical students. Gamification using DMCs is thought to enhance the learning effectiveness of clinical reasoning [ 24 , 25 , 26 , 33 ]. The results of the quantitative and qualitative evaluations were integrated as a mixed-methods sequential explanatory study [ 24 , 25 , 26 , 33 ]. An open-ended questionnaire, designed according to the study objectives, was used to investigate the advantages of clinical reasoning education through gamification using DMCs [ 28 , 33 ]. The content of the questionnaire survey was decided through discussions among the faculty members (KI and KS) [ 28 ]. Medical students were asked the following open-ended questions: “What are the advantages of gamification using DMCs? Why do you think so?” [ 28 , 33 ]. All 30 medical students who participated in the gamification using DMCs answered the questionnaire [ 28 ]. Names and other identifiers were removed from the questionnaire and the statements were tabulated [ 28 ]. The faculty members did not reveal their personal attitudes and behaviors to the students [ 28 , 33 ]. A team debrief was held after the questionnaire survey [ 28 , 33 ]. There were no repeat questionnaire surveys, and participants were not asked to review the transcripts or to provide feedback [ 28 , 33 ].
Content analysis was used to analyze the response categories in the qualitative research (Table 2 ) [ 28 , 33 , 34 , 35 ]. A preliminary analytic template was developed as a starting point for analysis [ 28 , 33 , 34 , 35 ] Two researchers (KI, KS) independently read all open-ended questionnaire transcripts and performed the initial coding [ 28 , 33 , 34 , 35 ]. To ensure the quality of the research, researcher triangulation was conducted by two researchers (KI and KS), who discussed, identified, and agreed on the coding of the descriptors [ 28 , 33 , 34 , 35 ]. Following the coding, similar codes were grouped into categories and subcategories, which were regularly discussed and reviewed by a third researcher, HK (who had experience in qualitative research), to ensure the credibility of the findings [ 28 , 33 , 34 , 35 ]. The findings were reported using the consolidated criteria for reporting qualitative research (COREQ) checklist [ 35 ].
The analytic categories were set according to the seven working definitions for the different components of clinical reasoning (information gathering, hypothesis generation, problem representation, differential diagnosis, leading or working diagnosis, diagnostic justification, and management and treatment) (Supplement 4) [ 36 ]. After open coding, similar codes were classified into subcategories and categories. We analyzed the concepts in each of the seven clinical reasoning components and calculated the number of analysis units for each concept [ 36 ]. We also grouped similar codes as categories and checked the clinical reasoning components to which they corresponded.
This research was performed in accordance with the Declaration of Helsinki and approved by the Ethics Review Committee of the Chiba University Graduate School of Medicine (Chiba, Japan) on May 7, 2019 (approval number: 3425). The study procedures were explained to the medical students, and informed consent for participation was obtained. Although the researcher who administered the consent was also a class teacher, it was made clear to the medical students that participation in this study would not affect their grade evaluations. This study was registered in the University Hospital Medical Information Network Clinical Trials Registry (UMIN-CRT) (UMIN000049765).
All 30 eligible students (2 fourth year medical students (6.7%), 26 fifth year medical students (86.7%), and 2 sixth year medical students (6.7%)) provided informed consent and were included in both the quantitative and qualitative components of the evaluation. The mean age of the students was 23.9 years (standard deviation: 2.3 years) and 19 of the 30 students (63.3%) were male. There were no missing data.
The percentage of students making the correct final diagnosis, total number of cards drawn, total medical cost of the case scenarios did not differ significantly between the first and last clinical case scenario exercises (71% and 43%, p = 0.157, r = 0.378; 5.6 ± 2.1 and 6.2 ± 4.7, p = 0.825, r = 0.059; and 30,351 ± 8,710 JPY and 29,569 ± 7,774 JPY, p = 0.825, r = 0.059, respectively). However, the average medical cost of all cards drawn by students decreased significantly between the first and last clinical case scenario exercises (from 11,921 ± 8,895 JPY to 8,699 ± 13,167 JPY, p = 0.046, r = 0.411).
Confidence in effective clinical decision-making, motivation to learn diagnostic decision-making, and awareness of medical cost were significantly increased after participating in the gamification than before (2.9 ± 0.2 to 3.6 ± 0.2, p < 0.001, r = 0.697 5.8 ± 0.1 to 6.2 ± 0.2, p = 0.014, r = 0.448, 3.3 ± 0.2 to 4.8 ± 0.2, p < 0.001, r = 0.685, respectively) (Fig. 4 ).
The scale of 7-point Likert scale was 1: strongly disagree, 7: strongly agree. SD: standard deviation.
Informed consent was obtained from all 30 medical students who were subjected to the quantitative evaluation. All 30 participants were included in the qualitative analysis. The categories of analysis were set according to the seven working definitions for the different components of clinical reasoning (Supplemental 4) [ 36 ]. After analyzing the records of all 30 medical students, we confirmed that we had reached thematic saturation.
Table 3 shows the categories, subcategories, number of codes, and representative quotations. A total of 92 codes were generated from the open-ended questionnaire. We identified seven categories and 24 subcategories of advantages of clinical reasoning education by gamification using DMCs, covering all seven clinical reasoning components [ 36 ]. Furthermore, in the subcategories of content analysis, “listing differential diagnosis” was the most frequent subcategory, followed by “awareness of medical costs,” “clinical features of diseases,” “narrowing down the differential diagnosis,” and “generating differential diagnoses.”
The subcategories “clinical features of diseases” (9 codes), “methods of clinical information gathering” (2 codes), “physical examination” (2 codes), “appropriate medical history-taking to gather information” (1 code), and “case specificity in clinical reasoning” (1 code) were grouped in the category “information gathering” (Total 15 codes).
‘ Gamification allows medical students to learn clinical features of common diseases .’ (ID = 11).
The subcategories “generating differential diagnoses” (6 codes), and “hypothesis-driven information gathering” (5 codes) were grouped in the category “hypothesis generation” (Total 11 codes).
‘ I am confident that I can generate clinical hypotheses from the patient’s chief complaint, thanks to the gamification .’ (ID = 2).
The subcategories “cognitive bias” (5 codes), “priority of clinical information” (2 codes), and “priority of physical examination” (1 code) were grouped in the category “problem representation” (Total 8 codes).
‘ I was able to learn actively. Thanks to gamification, I think that we can realize the terror of falling into cognitive bias .’ (ID = 22).
The subcategory “listing the differential diagnosis” (16 codes), was assigned to the category “differential diagnosis” (Total 16 codes).
‘ Gamification was a lot of fun. The advantage of gamification is that it increases students’ ability to list differential diagnoses from symptoms .’ (ID = 9).
The subcategories “awareness of medical costs” (11 codes), “priority of diagnostic testing” (3 codes), “cost-effectiveness of diagnostic testing” (1 code), “under-adaptation to clinical examination” (1 code) and “examination procedures” (1 code) were grouped into the category “leading or working diagnosis” (Total 17 codes).
‘ It was fun, like a game. I think that the gamification helps medical students realize the importance of being aware of the medical costs .’ (ID = 8). The subcategories “narrowing down the differential diagnosis” (8.codes), “diagnostic error” (5 codes), “definitive diagnosis process” (3 codes), “sensitivity and specificity of clinical examinations” (3 codes), and “false-positive test results” (2 codes) were grouped into the category “diagnostic justification” (Total 21 codes). ‘ It was fun to learn with a game-like atmosphere. I think that gamification helps medical students learn how to narrow down the differential diagnosis .’ (ID = 21).
The subcategories “appropriate management and treatment” (2 codes), “exclusion of critical disease” (1 code), and “decision-making in real time” (1 code) were classified into the category “management and treatment” (Total 4 codes).
‘ Gamification motivates medical students to learn more about treatment and management according to the differential diagnosis .’ (ID = 13).
This study suggests that gamification using DMC may be considered an effective educational method for improving medical students’ diagnostic decision-making ability and their awareness of medical costs in the clinical reasoning process. Comparing the first and last clinical case scenario exercises, the average medical cost of all cards drawn by students decreased significantly. In addition, confidence in effective clinical decision-making, motivation to learn diagnostic decision-making, and awareness of medical cost were significantly higher after than before the gamification.
Gamification has been reported to improve motivation and engagement with learning tasks, produce positive learning outcomes through increased enjoyment, and improve clinical care [ 18 , 20 , 21 ]. The quotes from the qualitative survey in this study also showed that the medical students perceived factors such as “enjoy learning,” “sense of fun and games,” “active learning,” and “serious learning” as advantages of gamification using DMCs in addition to the seven clinical reasoning components. Another advantage of gamification may be that students can simulate the decision-making process by imagining real patients and real situations in clinical settings, although the common benefit of using a case-based approach is considered [ 37 ]. There are various subtypes of gamification, which are based on a combination of attributes such as skill, strategy, and chance [ 37 ]. Learning with card and board games, defined by the layout of the game, improves medical students’ communication skills and promotes active interaction learning with other players [ 38 , 39 ]. Therefore, gamification using DMCs is likely to stimulate the decision-making process, which is one of the most important processes of clinical reasoning, and bring positive learning effects to medical students. In line with self-determination theory, game design elements can be used to enhance learners’ feelings of relatedness, autonomy, and competence to foster their intrinsic motivation [ 40 ]. However, these basic psychological needs may be undermined by the over-justification effect and the negative effects of competition if they are not consistent with the objectives of gamification [ 40 ]. Adding game design elements to increase extrinsic motivation can adversely impact learners who already have a strong intrinsic motivation because of over-justification owing to overreliance on external motivating factors can result in a net negative effect on engagement and motivation [ 40 , 41 ]. Consideration of the potential for either negative or positive effects on motivation is key in choosing which systems to gamify, which game design elements to use, and which students are most likely to benefit [ 40 ]. In addition, the negative effects of competition may result in a deficit of trust among fellow learners, and a loss of motivation to learn among low-ranking learners, and when there is no change in ranking [ 40 , 42 ]. Steps to minimize the negative effects of competition include maximizing collaborative opportunities (e.g., team-based competition) [ 40 ]. Also, the percentage of students making the correct final diagnosis did not differ significantly between the first and last clinical case scenario exercises. The possible reason was considered that the evaluation of clinical reasoning has highly case-specificity elements [ 43 ].
It is important to clearly understand the advantages and disadvantages of gamification, to take a cautious approach when integrating gamification, to discuss comprehensive learning objectives between teachers and students, and for the teacher to provide feedback to the students [ 40 ]. In this study, the briefing and debriefing by the faculty members were used to clarify the significance and learning objectives of gamification using DMCs [ 40 ]. In addition, gamification using DMCs is an easy-to-implement educational method because it can be easily created from existing cases and the cards can be printed on both sides. Therefore, gamification using DMCs may provide an educational opportunity to teach medical students clinical reasoning skills.
The quantitative and qualitative data of this study showed that teaching medical students clinical reasoning using DMCs as a gamification method, led to improved clinical decision-making confidence and learning motivation in clinical case scenarios. In addition, it helped students to acquire practical knowledge, deepened their understanding of clinical reasoning, and identified several important clinical reasoning skills, including diagnostic decision-making.
Conversely, although diagnosis is an important part of the clinical reasoning process, it is also important for students to develop management and decision-making skills in this process, taking into account various factors such as resources and cost-effectiveness [ 5 , 7 ]. In Japan, clinical reasoning education with an awareness of medical costs is important because of increasing medical costs and a low level of awareness of medical costs among physicians and patients [ 9 ]. In this study, awareness of medical costs increased significantly after the gamification, and the average medical cost of all cards drawn by the students decreased significantly from the first to the last clinical case scenario exercise. Furthermore, among the subcategories of the content analysis, “listing differential diagnoses” and “awareness of medical costs” were the first and second more frequently mentioned, suggesting that the intervention was effective at teaching clinical reasoning with an awareness of medical costs. Therefore, gamification using DMCs of case scenarios appears to be an effective educational method for reducing medical costs and teaching clinical reasoning with awareness of medical costs.
This study has several limitations. First, it was conducted using scenario tasks with paper-based materials, not actual patients. Although this study revealed the usefulness of gamification using DMCs for teaching clinical reasoning to medical students, it is necessary to verify whether the advantages of gamification using DMCs for teaching clinical reasoning are similar for real patients. Second, the qualitative study of the present study revealed that teaching clinical reasoning to medical students through gamification using DMCs is effective in identifying some important skills related to clinical reasoning. However, it could not separate the effect of gamification using DMCs from the effect of using a case-based approach and increased interaction with faculty members on improving students’ competence in clinical reasoning such as reflection. Third, the lack of a control group is a limitation. Cook and Beckman reported that showing a significant difference of an educational intervention without a control group only demonstrates that learning can occur [ 44 ]. Furthermore, this study revealed that the average total cost was significantly reduced in the last case scenario exercise compared to the first, but further comparative verification of the average cost using a control group that is not shown the cost is needed. Fourth, in this study, the clinical tests were limited to those related to the diagnosis determined in the focus group discussion, and not necessarily those obtained by broader consensus. The required clinical tests may differ depending on whether the evaluation includes treatment, and on the practices in each country. In actual clinical practice, it is necessary to consider the characteristics and evidence of each clinical test, treatment guidelines, and discussions among medical professionals including specialists in charge of diagnosis and treatment to decide which tests are necessary. Fifth, this study was conducted on medical students at a single institution and department in Japan. Therefore, the results of this study may not be generalizable beyond the specific population from which the sample was drawn. Further validation is needed to determine whether the results can be applied to residents and general physicians. Sixth, in this study, participants were randomly assigned to 14 small-group teams, with each team consisting of 2–3 medical students. However, the learning effects of gamification may vary according to differences in group size. Seventh, quantitative outcomes gauged before and after educational intervention were anchored in self-assessment. Eighth, the questionnaire’s content was formulated through focus group discussions involving two supervisors from the Department of General Medicine and one from Respiratory Medicine at the university (KI, KS, and HK). Ninth, the reliability and validity of the survey haven’t been ascertained.
Teaching medical students clinical reasoning using DMCs can improve clinical decision-making confidence and learning motivation and reduces medical cost in clinical case scenarios. In addition, it can help students acquire practical knowledge, deepens their understanding of clinical reasoning, and be trained in several important clinical reasoning skills, including diagnostic decision-making and awareness of medical costs. Gamification using DMCs can be effective at reducing medical costs in clinical case scenarios and educating medical students in clinical reasoning with awareness of medical costs.
The raw dataset supporting the conclusions of this article is available from the corresponding author upon request.
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Department of General Medicine, Chiba University Hospital, 1-8-1, Inohana, Chuo-ku, Chiba-city, Chiba pref, Japan
Kosuke Ishizuka, Kiyoshi Shikino, Yoji Hoshina, Tomoko Tsukamoto & Masatomi Ikusaka
Department of General Medicine, Yokohama City University School of Medicine, Yokohama, Kanagawa, Japan
Department of Community-oriented Medical Education, Graduate School of Medicine, Chiba University, Chiba, Japan
Kiyoshi Shikino & Kazuyo Yamauchi
Health Professional Development Center, Chiba University Hospital, Chiba, Japan
Kiyoshi Shikino, Hajme Kasai, Kazuyo Yamauchi & Shoichi Ito
Department of Respirology, Graduate School of Medicine, Chiba University, Chiba, Japan
Department of Medical Education, Graduate School of Medicine, Chiba University, Chiba, Japan
Hajme Kasai, Tomoko Tsukamoto & Shoichi Ito
Department of Psychiatry, Chiba University Hospital, Chiba, Japan
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KI, KS, HK, YH, and SM contributed to the study conceptualization, design, and data collection. KI and KS contributed to analysis and interpretation of the data. KI wrote the manuscript and prepared all figures and Tables. KS revised and edited the manuscript. HK, YH, SM, TT, KY, SI and MI reviewed the final manuscript. The authors read and approved the final manuscript.
Correspondence to Kosuke Ishizuka .
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Ishizuka, K., Shikino, K., Kasai, H. et al. The influence of Gamification on medical students’ diagnostic decision making and awareness of medical cost: a mixed-method study. BMC Med Educ 23 , 813 (2023). https://doi.org/10.1186/s12909-023-04808-x
Received : 10 April 2023
Accepted : 25 October 2023
Published : 28 October 2023
DOI : https://doi.org/10.1186/s12909-023-04808-x
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- Clinical reasoning
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