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  • What Is a Research Design | Types, Guide & Examples

What Is a Research Design | Types, Guide & Examples

Published on June 7, 2021 by Shona McCombes . Revised on November 20, 2023 by Pritha Bhandari.

A research design is a strategy for answering your   research question  using empirical data. Creating a research design means making decisions about:

  • Your overall research objectives and approach
  • Whether you’ll rely on primary research or secondary research
  • Your sampling methods or criteria for selecting subjects
  • Your data collection methods
  • The procedures you’ll follow to collect data
  • Your data analysis methods

A well-planned research design helps ensure that your methods match your research objectives and that you use the right kind of analysis for your data.

Table of contents

Step 1: consider your aims and approach, step 2: choose a type of research design, step 3: identify your population and sampling method, step 4: choose your data collection methods, step 5: plan your data collection procedures, step 6: decide on your data analysis strategies, other interesting articles, frequently asked questions about research design.

  • Introduction

Before you can start designing your research, you should already have a clear idea of the research question you want to investigate.

There are many different ways you could go about answering this question. Your research design choices should be driven by your aims and priorities—start by thinking carefully about what you want to achieve.

The first choice you need to make is whether you’ll take a qualitative or quantitative approach.

Qualitative research designs tend to be more flexible and inductive , allowing you to adjust your approach based on what you find throughout the research process.

Quantitative research designs tend to be more fixed and deductive , with variables and hypotheses clearly defined in advance of data collection.

It’s also possible to use a mixed-methods design that integrates aspects of both approaches. By combining qualitative and quantitative insights, you can gain a more complete picture of the problem you’re studying and strengthen the credibility of your conclusions.

Practical and ethical considerations when designing research

As well as scientific considerations, you need to think practically when designing your research. If your research involves people or animals, you also need to consider research ethics .

  • How much time do you have to collect data and write up the research?
  • Will you be able to gain access to the data you need (e.g., by travelling to a specific location or contacting specific people)?
  • Do you have the necessary research skills (e.g., statistical analysis or interview techniques)?
  • Will you need ethical approval ?

At each stage of the research design process, make sure that your choices are practically feasible.

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Within both qualitative and quantitative approaches, there are several types of research design to choose from. Each type provides a framework for the overall shape of your research.

Types of quantitative research designs

Quantitative designs can be split into four main types.

  • Experimental and   quasi-experimental designs allow you to test cause-and-effect relationships
  • Descriptive and correlational designs allow you to measure variables and describe relationships between them.

With descriptive and correlational designs, you can get a clear picture of characteristics, trends and relationships as they exist in the real world. However, you can’t draw conclusions about cause and effect (because correlation doesn’t imply causation ).

Experiments are the strongest way to test cause-and-effect relationships without the risk of other variables influencing the results. However, their controlled conditions may not always reflect how things work in the real world. They’re often also more difficult and expensive to implement.

Types of qualitative research designs

Qualitative designs are less strictly defined. This approach is about gaining a rich, detailed understanding of a specific context or phenomenon, and you can often be more creative and flexible in designing your research.

The table below shows some common types of qualitative design. They often have similar approaches in terms of data collection, but focus on different aspects when analyzing the data.

Your research design should clearly define who or what your research will focus on, and how you’ll go about choosing your participants or subjects.

In research, a population is the entire group that you want to draw conclusions about, while a sample is the smaller group of individuals you’ll actually collect data from.

Defining the population

A population can be made up of anything you want to study—plants, animals, organizations, texts, countries, etc. In the social sciences, it most often refers to a group of people.

For example, will you focus on people from a specific demographic, region or background? Are you interested in people with a certain job or medical condition, or users of a particular product?

The more precisely you define your population, the easier it will be to gather a representative sample.

  • Sampling methods

Even with a narrowly defined population, it’s rarely possible to collect data from every individual. Instead, you’ll collect data from a sample.

To select a sample, there are two main approaches: probability sampling and non-probability sampling . The sampling method you use affects how confidently you can generalize your results to the population as a whole.

Probability sampling is the most statistically valid option, but it’s often difficult to achieve unless you’re dealing with a very small and accessible population.

For practical reasons, many studies use non-probability sampling, but it’s important to be aware of the limitations and carefully consider potential biases. You should always make an effort to gather a sample that’s as representative as possible of the population.

Case selection in qualitative research

In some types of qualitative designs, sampling may not be relevant.

For example, in an ethnography or a case study , your aim is to deeply understand a specific context, not to generalize to a population. Instead of sampling, you may simply aim to collect as much data as possible about the context you are studying.

In these types of design, you still have to carefully consider your choice of case or community. You should have a clear rationale for why this particular case is suitable for answering your research question .

For example, you might choose a case study that reveals an unusual or neglected aspect of your research problem, or you might choose several very similar or very different cases in order to compare them.

Data collection methods are ways of directly measuring variables and gathering information. They allow you to gain first-hand knowledge and original insights into your research problem.

You can choose just one data collection method, or use several methods in the same study.

Survey methods

Surveys allow you to collect data about opinions, behaviors, experiences, and characteristics by asking people directly. There are two main survey methods to choose from: questionnaires and interviews .

Observation methods

Observational studies allow you to collect data unobtrusively, observing characteristics, behaviors or social interactions without relying on self-reporting.

Observations may be conducted in real time, taking notes as you observe, or you might make audiovisual recordings for later analysis. They can be qualitative or quantitative.

Other methods of data collection

There are many other ways you might collect data depending on your field and topic.

If you’re not sure which methods will work best for your research design, try reading some papers in your field to see what kinds of data collection methods they used.

Secondary data

If you don’t have the time or resources to collect data from the population you’re interested in, you can also choose to use secondary data that other researchers already collected—for example, datasets from government surveys or previous studies on your topic.

With this raw data, you can do your own analysis to answer new research questions that weren’t addressed by the original study.

Using secondary data can expand the scope of your research, as you may be able to access much larger and more varied samples than you could collect yourself.

However, it also means you don’t have any control over which variables to measure or how to measure them, so the conclusions you can draw may be limited.

As well as deciding on your methods, you need to plan exactly how you’ll use these methods to collect data that’s consistent, accurate, and unbiased.

Planning systematic procedures is especially important in quantitative research, where you need to precisely define your variables and ensure your measurements are high in reliability and validity.

Operationalization

Some variables, like height or age, are easily measured. But often you’ll be dealing with more abstract concepts, like satisfaction, anxiety, or competence. Operationalization means turning these fuzzy ideas into measurable indicators.

If you’re using observations , which events or actions will you count?

If you’re using surveys , which questions will you ask and what range of responses will be offered?

You may also choose to use or adapt existing materials designed to measure the concept you’re interested in—for example, questionnaires or inventories whose reliability and validity has already been established.

Reliability and validity

Reliability means your results can be consistently reproduced, while validity means that you’re actually measuring the concept you’re interested in.

For valid and reliable results, your measurement materials should be thoroughly researched and carefully designed. Plan your procedures to make sure you carry out the same steps in the same way for each participant.

If you’re developing a new questionnaire or other instrument to measure a specific concept, running a pilot study allows you to check its validity and reliability in advance.

Sampling procedures

As well as choosing an appropriate sampling method , you need a concrete plan for how you’ll actually contact and recruit your selected sample.

That means making decisions about things like:

  • How many participants do you need for an adequate sample size?
  • What inclusion and exclusion criteria will you use to identify eligible participants?
  • How will you contact your sample—by mail, online, by phone, or in person?

If you’re using a probability sampling method , it’s important that everyone who is randomly selected actually participates in the study. How will you ensure a high response rate?

If you’re using a non-probability method , how will you avoid research bias and ensure a representative sample?

Data management

It’s also important to create a data management plan for organizing and storing your data.

Will you need to transcribe interviews or perform data entry for observations? You should anonymize and safeguard any sensitive data, and make sure it’s backed up regularly.

Keeping your data well-organized will save time when it comes to analyzing it. It can also help other researchers validate and add to your findings (high replicability ).

On its own, raw data can’t answer your research question. The last step of designing your research is planning how you’ll analyze the data.

Quantitative data analysis

In quantitative research, you’ll most likely use some form of statistical analysis . With statistics, you can summarize your sample data, make estimates, and test hypotheses.

Using descriptive statistics , you can summarize your sample data in terms of:

  • The distribution of the data (e.g., the frequency of each score on a test)
  • The central tendency of the data (e.g., the mean to describe the average score)
  • The variability of the data (e.g., the standard deviation to describe how spread out the scores are)

The specific calculations you can do depend on the level of measurement of your variables.

Using inferential statistics , you can:

  • Make estimates about the population based on your sample data.
  • Test hypotheses about a relationship between variables.

Regression and correlation tests look for associations between two or more variables, while comparison tests (such as t tests and ANOVAs ) look for differences in the outcomes of different groups.

Your choice of statistical test depends on various aspects of your research design, including the types of variables you’re dealing with and the distribution of your data.

Qualitative data analysis

In qualitative research, your data will usually be very dense with information and ideas. Instead of summing it up in numbers, you’ll need to comb through the data in detail, interpret its meanings, identify patterns, and extract the parts that are most relevant to your research question.

Two of the most common approaches to doing this are thematic analysis and discourse analysis .

There are many other ways of analyzing qualitative data depending on the aims of your research. To get a sense of potential approaches, try reading some qualitative research papers in your field.

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

  • Simple random sampling
  • Stratified sampling
  • Cluster sampling
  • Likert scales
  • Reproducibility

 Statistics

  • Null hypothesis
  • Statistical power
  • Probability distribution
  • Effect size
  • Poisson distribution

Research bias

  • Optimism bias
  • Cognitive bias
  • Implicit bias
  • Hawthorne effect
  • Anchoring bias
  • Explicit bias

A research design is a strategy for answering your   research question . It defines your overall approach and determines how you will collect and analyze data.

A well-planned research design helps ensure that your methods match your research aims, that you collect high-quality data, and that you use the right kind of analysis to answer your questions, utilizing credible sources . This allows you to draw valid , trustworthy conclusions.

Quantitative research designs can be divided into two main categories:

  • Correlational and descriptive designs are used to investigate characteristics, averages, trends, and associations between variables.
  • Experimental and quasi-experimental designs are used to test causal relationships .

Qualitative research designs tend to be more flexible. Common types of qualitative design include case study , ethnography , and grounded theory designs.

The priorities of a research design can vary depending on the field, but you usually have to specify:

  • Your research questions and/or hypotheses
  • Your overall approach (e.g., qualitative or quantitative )
  • The type of design you’re using (e.g., a survey , experiment , or case study )
  • Your data collection methods (e.g., questionnaires , observations)
  • Your data collection procedures (e.g., operationalization , timing and data management)
  • Your data analysis methods (e.g., statistical tests  or thematic analysis )

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

Operationalization means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioral avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalize the variables that you want to measure.

A research project is an academic, scientific, or professional undertaking to answer a research question . Research projects can take many forms, such as qualitative or quantitative , descriptive , longitudinal , experimental , or correlational . What kind of research approach you choose will depend on your topic.

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5 Types of Qualitative Methods

5 qualitative research designs

But just as with quantitative methods, there are actually many varieties of qualitative methods.

Similar to the way you can group usability testing methods , there are also a number of ways to segment qualitative methods.

A popular and helpful categorization separate qualitative methods into five groups: ethnography, narrative, phenomenological, grounded theory, and case study. John Creswell outlines these five methods in Qualitative Inquiry and Research Design .

While the five methods generally use similar data collection techniques (observation, interviews, and reviewing text), the purpose of the study differentiates them—something similar with different types of usability tests . And like classifying different usability studies, the differences between the methods can be a bit blurry. Here are the five qualitative methods in more detail.

1. Ethnography

Ethnographic research is probably the most familiar and applicable type of qualitative method to UX professionals. In ethnography, you immerse yourself in the target participants’ environment to understand the goals, cultures, challenges, motivations, and themes that emerge. Ethnography has its roots in cultural anthropology where researchers immerse themselves within a culture, often for years! Rather than relying on interviews or surveys, you experience the environment first hand, and sometimes as a “participant observer.”

For example, one way of uncovering the unmet needs of customers is to “ follow them home ” and observe them as they interact with the product. You don’t come armed with any hypotheses to necessarily test; rather, you’re looking to find out how a product is used.

2. Narrative

The narrative approach weaves together a sequence of events, usually from just one or two individuals to form a cohesive story. You conduct in-depth interviews, read documents, and look for themes; in other words, how does an individual story illustrate the larger life influences that created it. Often interviews are conducted over weeks, months, or even years, but the final narrative doesn’t need to be in chronological order. Rather it can be presented as a story (or narrative) with themes, and can reconcile conflicting stories and highlight tensions and challenges which can be opportunities for innovation.

For example, a narrative approach can be an appropriate method for building a persona . While a persona should be built using a mix of methods—including segmentation analysis from surveys—in-depth interviews with individuals in an identified persona can provide the details that help describe the culture, whether it’s a person living with Multiple Sclerosis, a prospective student applying for college, or a working mom.

3. Phenomenological

When you want to describe an event, activity, or phenomenon, the aptly named phenomenological study is an appropriate qualitative method. In a phenomenological study, you use a combination of methods, such as conducting interviews, reading documents, watching videos, or visiting places and events, to understand the meaning participants place on whatever’s being examined. You rely on the participants’ own perspectives to provide insight into their motivations.

Like other qualitative methods, you don’t start with a well-formed hypothesis. In a phenomenological study, you often conduct a lot of interviews, usually between 5 and 25 for common themes , to build a sufficient dataset to look for emerging themes and to use other participants to validate your findings.

For example, there’s been an explosion in the last 5 years in online courses and training. But how do students engage with these courses? While you can examine time spent and content accessed using log data and even assess student achievement vis-a-vis in-person courses, a phenomenological study would aim to better understand the students experience and how that may impact comprehension of the material.

4. Grounded Theory

Whereas a phenomenological study looks to describe the essence of an activity or event, grounded theory looks to provide an explanation or theory behind the events. You use primarily interviews and existing documents to build a theory based on the data. You go through a series of open and axial coding techniques to identify themes and build the theory. Sample sizes are often also larger—between 20 to 60—with these studies to better establish a theory. Grounded theory can help inform design decisions by better understanding how a community of users currently use a product or perform tasks.

For example, a grounded theory study could involve understanding how software developers use portals to communicate and write code or how small retail merchants approve or decline customers for credit.

5. Case Study

Made famous by the Harvard Business School, even mainly quantitative researchers can relate to the value of the case study in explaining an organization, entity, company, or event. A case study involves a deep understanding through multiple types of data sources. Case studies can be explanatory, exploratory, or describing an event. The annual CHI conference has a peer-reviewed track dedicated to case studies.

For example, a case study of how a large multi-national company introduced UX methods into an agile development environment would be informative to many organizations.

The table below summarizes the differences between the five qualitative methods.

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What is Qualitative Research Design? Definition, Types, Methods and Best Practices

By Nick Jain

Published on: July 7, 2023

What is Qualitative Research Design

Table of Contents

What is Qualitative Research Design?

Types of qualitative research design, qualitative research design methods, qualitative research design process: 9 key steps, top 12 best practices for qualitative research design.

Qualitative research design is defined as a type of research methodology that focuses on exploring and understanding complex phenomena and the meanings attributed to them by individuals or groups. It is commonly used in social sciences, psychology, anthropology, and other fields where subjective experiences and interpretations are of interest.

Qualitative research is concerned with capturing the richness and depth of human experiences, beliefs, attitudes, and behaviors. It aims to go beyond simple statistical analysis and uncover insights that quantitative research may not be able to capture.

Qualitative research design typically involves gathering data through methods such as interviews, observations, focus groups , and analysis of documents or artifacts. These methods allow researchers to collect detailed, descriptive information about participants’ perspectives, experiences, and contexts.

Key characteristics of qualitative research design include:

  • Exploratory nature: Qualitative research often begins with an open-ended approach to allow for the discovery of new insights and patterns.
  • Contextual understanding: It emphasizes understanding phenomena within their social, cultural, and historical contexts, as these factors shape individuals’ experiences.
  • Subjectivity and reflexivity: Qualitative researchers acknowledge the influence of their own perspectives and biases and often engage in reflexivity to critically examine their role in shaping the research process and outcomes.
  • Small and purposive sampling: Rather than aiming for large representative samples, qualitative research often involves selecting participants who can provide rich and diverse information relevant to the research question.
  • In-depth data collection: Researchers spend considerable time with participants, collecting detailed and nuanced data, often through open-ended interviews, observations, or analysis of texts.
  • Iterative data analysis: Qualitative analysis involves coding, categorizing, and interpreting data to identify patterns, themes, and relationships. This process is often iterative, with researchers revisiting and refining their analysis as new insights emerge.

Types of Qualitative Research Design

There are several types of qualitative research designs, each with its own specific characteristics and purposes. Here are some common types:

  • Phenomenological Research

This design aims to understand the essence and meaning of human experiences related to a particular phenomenon. Researchers explore participants’ subjective experiences through in-depth interviews or observations to uncover the underlying structures and patterns of their lived experiences.

  • Ethnographic Research

Ethnography involves studying and understanding the culture, beliefs, practices, and social interactions of a specific group or community. Researchers immerse themselves in the participants’ natural environment for an extended period, often conducting participant observation, interviews, and document analysis to gain an in-depth understanding of the culture.

  • Grounded Theory

Grounded theory is an approach where researchers aim to develop theories or conceptual frameworks grounded in the data. Through constant comparison and analysis of collected data, researchers identify categories, concepts, and relationships to generate a theory that explains the phenomenon under investigation.

Case study research involves an in-depth examination of a single individual, group, organization, or specific context. Researchers collect multiple sources of data such as interviews, observations, and documents to provide a comprehensive understanding of the case and to draw insights that may have broader implications.

  • Narrative Research

Narrative research focuses on understanding and analyzing the stories and personal narratives shared by individuals. Researchers examine the structure, content, and context of these narratives to gain insights into how individuals construct meaning and make sense of their experiences.

  • Participatory Action Research (PAR)

PAR is a collaborative approach that involves researchers working closely with participants or communities to identify and address social issues or problems. The aim is to empower participants and generate actionable knowledge through a cyclical process of reflection, action, and change.

  • Constructivist/Interpretive Research

This design emphasizes the importance of understanding multiple subjective realities and interpretations of social phenomena. Researchers explore the different meanings and perspectives attributed to a phenomenon, often using interviews, focus groups , or textual analysis to uncover the complexities of individuals’ interpretations.

Learn more: What is Qualitative Market Research?

Qualitative research design employs various methods to gather data and generate insights. Here are some common methods used in qualitative research design:

  • Interviews: In-depth interviews are a primary method in qualitative research . Researchers conduct structured, semi-structured, or unstructured interviews to gather rich and detailed information from participants. Interviews can be one-on-one or conducted in a group setting (focus groups) to explore participants’ perspectives, experiences, beliefs, and attitudes.
  • Observations: Observational methods such as quantitative and qualitative observation , involve systematically watching and recording participants’ behavior in natural or controlled settings. Researchers may engage in participant observation, where they actively participate in the setting being studied, or non-participant observation, where they remain as an observer. Observations can provide insights into social interactions, behaviors, and contextual factors.
  • Document Analysis: Researchers analyze various documents, such as diaries, letters, official records, organizational documents, or online content, to gain insights into cultural practices, historical events, or social phenomena. Document analysis helps researchers understand the context, beliefs, and values of individuals or communities.
  • Focus Groups: Focus groups involve bringing together a small group of participants to discuss a specific topic or research question. A moderator guides the discussion, and participants can share their opinions, experiences, and perceptions in a group setting. Focus groups are useful for exploring group dynamics, and collective perspectives, and generating interactive discussions.
  • Case Studies: Case studies involve an in-depth investigation of a single case, such as an individual, group, organization, or community. Researchers gather multiple sources of data, including interviews, observations, and document analysis, to provide a comprehensive understanding of the case. Case studies are particularly useful for studying complex and unique phenomena within their real-world contexts.
  • Ethnography: Ethnographic methods involve immersing oneself in the natural setting of the participants to gain an in-depth understanding of their culture, practices, and social interactions. Researchers spend a significant amount of time conducting participant observation, interviews, and collecting field notes to capture the nuances of the participants’ experiences.
  • Visual Methods: Visual methods, such as photography, video recordings, or drawings, can be used to complement other qualitative research methods . Visual data can provide additional insights, perspectives, and documentation of participants’ experiences and environments.
  • Textual Analysis: Textual analysis involves analyzing written or verbal data, such as interviews, focus group transcripts, or written documents, to identify themes, patterns, and meanings. Researchers use coding techniques to categorize and interpret the data and derive insights from the text.

Qualitative Research Design Process: 9 Key Steps

The qualitative research design process typically involves several key steps. While the specific details may vary depending on the research context and methodology, here is a general overview of the steps involved:

1. Identify the Research Question

Start by providing a concise and unambiguous statement that outlines your research question or objective. What do you want to explore or understand through your qualitative research ? Ensure that the question is specific, focused, and relevant to your field of study.

2. Determine the Research Approach

Select the most appropriate qualitative research approach or design based on your research question and objectives. Consider the different types of qualitative research designs (such as phenomenology, ethnography, and grounded theory) and choose one that aligns with your research goals.

3. Develop a Research Plan

Create a research plan that outlines the steps, procedures, and timeline for your study. Identify the target population or participants, data collection methods, and data analysis techniques you intend to use.

4. Select Participants

Determine the criteria for selecting participants who can provide valuable insights related to your research question. Consider factors such as demographics, expertise, experiences, or specific characteristics relevant to your study. Choose a sampling method (e.g., purposive sampling, snowball sampling) to recruit participants.

5. Collect Data

Conduct data collection using the chosen qualitative methods . This may involve conducting interviews, observations, focus groups , or document analysis. To maintain ethical standards, it is crucial to adhere to ethical guidelines and ensure that participants provide informed consent. Consider audio or video recording to ensure accurate data capture.

6. Analyze Data

Engage in data analysis to identify patterns, themes, and insights from the collected data. This may involve coding, categorizing, and organizing the data using qualitative analysis software or manual techniques. Use iterative and reflexive processes to refine and deepen your analysis.

7. Interpret Findings

Interpret the findings based on the analysis of your data. Explore the emerging themes, relationships, and meanings that have emerged from the data. Consider how the findings relate to your research question and existing literature in your field.

8. Draw Conclusions and Generate Insights

Summarize the key findings of your study and draw conclusions based on your interpretation of the data. Reflect on the implications and significance of your findings for theory, practice, or future research. Identify any limitations or potential biases in your study.

9. Communicate Results

Prepare a report or manuscript to communicate your research findings. Present your qualitative data, analysis, interpretations, and conclusions in a clear and organized manner. Consider sharing your findings through presentations, publications, or other appropriate dissemination channels.

Learn more: What is Quantitative Market Research?

When conducting qualitative research , it is important to follow best practices to ensure the rigor, validity, and trustworthiness of your study. Here are some top best practices for qualitative research design:

1. Clearly Define Research Questions: Begin by clearly defining your research questions or objectives. Make sure they are specific, focused, and aligned with the purpose of your study. Clearly articulating your research questions will guide your entire research design.

2. Use a Theoretical Framework: Situate your research within a relevant theoretical framework or existing body of literature. This provides a foundation for understanding the context and helps you generate insights that contribute to theory development or refinement.

3. Select an Appropriate Research Design: Choose a qualitative research design that best suits your research questions and objectives. Consider the different approaches available, such as phenomenology, ethnography, or grounded theory, and select the one that aligns with your research goals.

4. Use Rigorous Sampling Techniques: Select participants or cases using rigorous sampling techniques. Consider purposeful sampling, where participants are chosen based on specific criteria relevant to your research question. Aim for diversity and seek saturation, where data collection reaches a point of redundancy and further data collection does not yield significant new insights.

5. Establish Trustworthiness and Credibility: Enhance the trustworthiness of your research findings by employing strategies such as member checking, where participants review and validate your interpretations, or peer debriefing, where colleagues provide feedback on your analysis and interpretations. Triangulation, or the use of multiple data sources or methods, can also strengthen the credibility of your findings.

6. Maintain Reflexivity: Be aware of your own biases, assumptions, and preconceptions throughout the research process. Engage in reflexivity by regularly reflecting on how your own perspectives may influence data collection, analysis, and interpretation. Documenting and acknowledging your own role and potential impact on the research process is essential.

7. Plan and Conduct Ethical Research: Adhere to ethical guidelines and obtain informed consent from participants. Ensure participant confidentiality, anonymity, and privacy. Seek ethics approval from relevant institutional review boards or ethics committees.

8. Use Clear and Consistent Data Collection Methods: Follow established protocols and guidelines for data collection methods such as interviews, observations, or document analysis. Develop interview guides or observation protocols to ensure consistency and standardization across participants or cases.

9. Maintain Detailed Documentation: Keep comprehensive records of your research process, including field notes, transcripts, or analysis memos. Thorough documentation allows for transparency, traceability, and the potential for independent audit or replication of your study.

10. Engage in Iterative Data Analysis: Conduct data analysis iteratively throughout the research process. Use coding techniques, thematic analysis, or other appropriate qualitative research methods to identify patterns, themes, and relationships in the data. Allow for revisions, refinements, and further exploration of emerging insights.

11. Ensure Researcher Independence and Objectivity: Be mindful of your own biases and maintain researcher independence throughout the research process. Strive for objectivity by critically examining your interpretations, seeking alternative explanations, and engaging in peer debriefing or external review.

12. Communicate Findings Effectively: Clearly communicate your research findings, including the methodology, data analysis, interpretations, and limitations. Provide rich and detailed descriptions to support your arguments and conclusions. Consider presenting findings in a way that resonates with your intended audience, whether it be academic researchers, practitioners, or policymakers.

Learn more: What is Qualitative Observation?

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9.4 Types of qualitative research designs

Learning objectives.

  • Define focus groups and outline how they differ from one-on-one interviews
  • Describe how to determine the best size for focus groups
  • Identify the important considerations in focus group composition
  • Discuss how to moderate focus groups
  • Identify the strengths and weaknesses of focus group methodology
  • Describe case study research, ethnography, and phenomenology.

There are various types of approaches to qualitative research.  This chapter presents information about focus groups, which are often used in social work research.  It also introduces case studies, ethnography, and phenomenology.

Focus Groups

Focus groups resemble qualitative interviews in that a researcher may prepare a guide in advance and interact with participants by asking them questions. But anyone who has conducted both one-on-one interviews and focus groups knows that each is unique. In an interview, usually one member (the research participant) is most active while the other (the researcher) plays the role of listener, conversation guider, and question-asker. Focus groups , on the other hand, are planned discussions designed to elicit group interaction and “obtain perceptions on a defined area of interest in a permissive, nonthreatening environment” (Krueger & Casey, 2000, p. 5).  In focus groups, the researcher play a different role than in a one-on-one interview. The researcher’s aim is to get participants talking to each other,  to observe interactions among participants, and moderate the discussion.

5 qualitative research designs

There are numerous examples of focus group research. In their 2008 study, for example, Amy Slater and Marika Tiggemann (2010) conducted six focus groups with 49 adolescent girls between the ages of 13 and 15 to learn more about girls’ attitudes towards’ participation in sports. In order to get focus group participants to speak with one another rather than with the group facilitator, the focus group interview guide contained just two questions: “Can you tell me some of the reasons that girls stop playing sports or other physical activities?” and “Why do you think girls don’t play as much sport/physical activity as boys?” In another focus group study, Virpi Ylanne and Angie Williams (2009) held nine focus group sessions with adults of different ages to gauge their perceptions of how older characters are represented in television commercials. Among other considerations, the researchers were interested in discovering how focus group participants position themselves and others in terms of age stereotypes and identities during the group discussion. In both examples, the researchers’ core interest in group interaction could not have been assessed had interviews been conducted on a one-on-one basis, making the focus group method an ideal choice.

Who should be in your focus group?

In some ways, focus groups require more planning than other qualitative methods of data collection, such as one-on-one interviews in which a researcher may be better able to the dialogue. Researchers must take care to form focus groups with members who will want to interact with one another and to control the timing of the event so that participants are not asked nor expected to stay for a longer time than they’ve agreed to participate. The researcher should also be prepared to inform focus group participants of their responsibility to maintain the confidentiality of what is said in the group. But while the researcher can and should encourage all focus group members to maintain confidentiality, she should also clarify to participants that the unique nature of the group setting prevents her from being able to promise that confidentiality will be maintained by other participants. Once focus group members leave the research setting, researchers cannot control what they say to other people.

5 qualitative research designs

Group size should be determined in part by the topic of the interview and your sense of the likelihood that participants will have much to say without much prompting. If the topic is one about which you think participants feel passionately and will have much to say, a group of 3–5 could make sense. Groups larger than that, especially for heated topics, can easily become unmanageable. Some researchers say that a group of about 6–10 participants is the ideal size for focus group research (Morgan, 1997); others recommend that groups should include 3–12 participants (Adler & Clark, 2008).  The size of the focus group is ultimately the decision of the researcher. When forming groups and deciding how large or small to make them, take into consideration what you know about the topic and participants’ potential interest in, passion for, and feelings about the topic. Also consider your comfort level and experience in conducting focus groups. These factors will help you decide which size is right in your particular case.

It may seem counterintuitive, but in general, it is better to form focus groups consisting of participants who do not know one another than to create groups consisting of friends, relatives, or acquaintances (Agar & MacDonald, 1995).  The reason is that group members who know each other may not share some taken-for-granted knowledge or assumptions. In research, it is precisely the  taken-for-granted knowledge that is often of interest; thus, the focus group researcher should avoid setting up interactions where participants may be discouraged to question or raise issues that they take for granted. However, group members should not be so different from one another that participants will be unlikely to feel comfortable talking with one another.

Focus group researchers must carefully consider the composition of the groups they put together. In his text on conducting focus groups, Morgan (1997) suggests that “homogeneity in background and not homogeneity in attitudes” (p. 36) should be the goal, since participants must feel comfortable speaking up but must also have enough differences to facilitate a productive discussion.  Whatever composition a researcher designs for her focus groups, the important point to keep in mind is that focus group dynamics are shaped by multiple social contexts (Hollander, 2004). Participants’ silences as well as their speech may be shaped by gender, race, class, sexuality, age, or other background characteristics or social dynamics—all of which might be suppressed or exacerbated depending on the composition of the group. Hollander (2004) suggests that researchers must pay careful attention to group composition, must be attentive to group dynamics during the focus group discussion, and should use multiple methods of data collection in order to “untangle participants’ responses and their relationship to the social contexts of the focus group” (p. 632).

The role of the moderator

In addition to the importance of group composition, focus groups also require skillful moderation. A moderator is the researcher tasked with facilitating the conversation in the focus group. Participants may ask each other follow-up questions, agree or disagree with one another, display body language that tells us something about their feelings about the conversation, or even come up with questions not previously conceived of by the researcher. It is just these sorts of interactions and displays that are of interest to the researcher. A researcher conducting focus groups collects data on more than people’s direct responses to her question, as in interviews.

The moderator’s job is not to ask questions to each person individually, but to stimulate conversation between participants. It is important to set ground rules for focus groups at the outset of the discussion. Remind participants you’ve invited them to participate because you want to hear from all of them. Therefore, the group should aim to let just one person speak at a time and avoid letting just a couple of participants dominate the conversation. One way to do this is to begin the discussion by asking participants to briefly introduce themselves or to provide a brief response to an opening question. This will help set the tone of having all group members participate. Also, ask participants to avoid having side conversations; thoughts or reactions to what is said in the group are important and should be shared with everyone.

As the focus group gets rolling, the moderator will play a less active role as participants talk to one another. There may be times when the conversation stagnates or when you, as moderator, wish to guide the conversation in another direction. In these instances, it is important to demonstrate that you’ve been paying attention to what participants have said. Being prepared to interject statements or questions such as “I’d really like to hear more about what Sunil and Joe think about what Dominick and Jae have been saying” or “Several of you have mentioned X. What do others think about this?” will be important for keeping the conversation going. It can also help redirect the conversation, shift the focus to participants who have been less active in the group, and serve as a cue to those who may be dominating the conversation that it is time to allow others to speak. Researchers may choose to use multiple moderators to make managing these various tasks easier.

Moderators are often too busy working with participants to take diligent notes during a focus group. It is helpful to have a note-taker who can record participants’ responses (Liamputtong, 2011). The note-taker creates, in essence, the first draft of interpretation for the data in the study. They note themes in responses, nonverbal cues, and other information to be included in the analysis later on. Focus groups are analyzed in a similar way as interviews; however, the interactive dimension between participants adds another element to the analytical process. Researchers must attend to the group dynamics of each focus group, as “verbal and nonverbal expressions, the tactical use of humour, interruptions in interaction, and disagreement between participants” are all data that are vital to include in analysis (Liamputtong, 2011, p. 175). Note-takers record these elements in field notes, which allows moderators to focus on the conversation.

Strengths and weaknesses of focus groups

Focus groups share many of the strengths and weaknesses of one-on-one qualitative interviews. Both methods can yield very detailed, in-depth information; are excellent for studying social processes; and provide researchers with an opportunity not only to hear what participants say but also to observe what they do in terms of their body language. Focus groups offer the added benefit of giving researchers a chance to collect data on human interaction by observing how group participants respond and react to one another. Like one-on-one qualitative interviews, focus groups can also be quite expensive and time-consuming. However, there may be some savings with focus groups as it takes fewer group events than one-on-one interviews to gather data from the same number of people. Another potential drawback of focus groups, which is not a concern for one-on-one interviews, is that one or two participants might dominate the group, silencing other participants. Careful planning and skillful moderation on the part of the researcher are crucial for avoiding, or at least dealing with, such possibilities. The various strengths and weaknesses of focus group research are summarized in Table 91.

Grounded Theory

Grounded theory has been widely used since its development in the late 1960s (Glaser & Strauss, 1967). Largely derived from schools of sociology, grounded theory involves emersion of the researcher in the field and in the data. Researchers follow a systematic set of procedures and a simultaneous approach to data collection and analysis. Grounded theory is most often used to generate rich explanations of complex actions, processes, and transitions. The primary mode of data collection is one-on-one participant interviews. Sample sizes tend to range from 20 to 30 individuals, sampled purposively (Padgett, 2016). However, sample sizes can be larger or smaller, depending on data saturation. Data saturation is the point in the qualitative research data collection process when no new information is being discovered. Researchers use a constant comparative approach in which previously collected data are analyzed during the same time frame as new data are being collected.  This allows the researchers to determine when new information is no longer being gleaned from data collection and analysis — that data saturation has been reached — in order to conclude the data collection phase.

Rather than apply or test existing grand theories, or “Big T” theories, grounded theory focuses on “small t” theories (Padgett, 2016). Grand theories, or “Big T” theories, are systems of principles, ideas, and concepts used to predict phenomena. These theories are backed up by facts and tested hypotheses. “Small t” theories are speculative and contingent upon specific contexts. In grounded theory, these “small t” theories are grounded in events and experiences and emerge from the analysis of the data collected.

One notable application of grounded theory produced a “small t” theory of acceptance following cancer diagnoses (Jakobsson, Horvath, & Ahlberg, 2005). Using grounded theory, the researchers interviewed nine patients in western Sweden. Data collection and analysis stopped when saturation was reached. The researchers found that action and knowledge, given with respect and continuity led to confidence which led to acceptance. This “small t” theory continues to be applied and further explored in other contexts.

Case study research

Case study research is an intensive longitudinal study of a phenomenon at one or more research sites for the purpose of deriving detailed, contextualized inferences and understanding the dynamic process underlying a phenomenon of interest. Case research is a unique research design in that it can be used in an interpretive manner to build theories or in a positivist manner to test theories. The previous chapter on case research discusses both techniques in depth and provides illustrative exemplars. Furthermore, the case researcher is a neutral observer (direct observation) in the social setting rather than an active participant (participant observation). As with any other interpretive approach, drawing meaningful inferences from case research depends heavily on the observational skills and integrative abilities of the researcher.

Ethnography

The ethnographic research method, derived largely from the field of anthropology, emphasizes studying a phenomenon within the context of its culture. The researcher must be deeply immersed in the social culture over an extended period of time (usually 8 months to 2 years) and should engage, observe, and record the daily life of the studied culture and its social participants within their natural setting. The primary mode of data collection is participant observation, and data analysis involves a “sense-making” approach. In addition, the researcher must take extensive field notes, and narrate her experience in descriptive detail so that readers may experience the same culture as the researcher. In this method, the researcher has two roles: rely on her unique knowledge and engagement to generate insights (theory), and convince the scientific community of the trans-situational nature of the studied phenomenon.

The classic example of ethnographic research is Jane Goodall’s study of primate behaviors, where she lived with chimpanzees in their natural habitat at Gombe National Park in Tanzania, observed their behaviors, interacted with them, and shared their lives. During that process, she learnt and chronicled how chimpanzees seek food and shelter, how they socialize with each other, their communication patterns, their mating behaviors, and so forth. A more contemporary example of ethnographic research is Myra Bluebond-Langer’s (1996)14 study of decision making in families with children suffering from life-threatening illnesses, and the physical, psychological, environmental, ethical, legal, and cultural issues that influence such decision-making. The researcher followed the experiences of approximately 80 children with incurable illnesses and their families for a period of over two years. Data collection involved participant observation and formal/informal conversations with children, their parents and relatives, and health care providers to document their lived experience.

Phenomenology

Phenomenology is a research method that emphasizes the study of conscious experiences as a way of understanding the reality around us. Phenomenology is concerned with the systematic reflection and analysis of phenomena associated with conscious experiences, such as human judgment, perceptions, and actions, with the goal of (1) appreciating and describing social reality from the diverse subjective perspectives of the participants involved, and (2) understanding the symbolic meanings (“deep structure”) underlying these subjective experiences. Phenomenological inquiry requires that researchers eliminate any prior assumptions and personal biases, empathize with the participant’s situation, and tune into existential dimensions of that situation, so that they can fully understand the deep structures that drives the conscious thinking, feeling, and behavior of the studied participants.

Some researchers view phenomenology as a philosophy rather than as a research method. In response to this criticism, Giorgi and Giorgi (2003) developed an existential phenomenological research method to guide studies in this area. This method can be grouped into data collection and data analysis phases. In the data collection phase, participants embedded in a social phenomenon are interviewed to capture their subjective experiences and perspectives regarding the phenomenon under investigation. Examples of questions that may be asked include “can you describe a typical day” or “can you describe that particular incident in more detail?” These interviews are recorded and transcribed for further analysis. During data analysis, the researcher reads the transcripts to: (1) get a sense of the whole, and (2) establish “units of significance” that can faithfully represent participants’ subjective experiences. Examples of such units of significance are concepts such as “felt space” and “felt time,” which are then used to document participants’ psychological experiences. For instance, did participants feel safe, free, trapped, or joyous when experiencing a phenomenon (“felt-space”)? Did they feel that their experience was pressured, slow, or discontinuous (“felt-time”)? Phenomenological analysis should take into account the participants’ temporal landscape (i.e., their sense of past, present, and future), and the researcher must transpose herself in an imaginary sense in the participant’s situation (i.e., temporarily live the participant’s life). The participants’ lived experience is described in form of a narrative or using emergent themes. The analysis then delves into these themes to identify multiple layers of meaning while retaining the fragility and ambiguity of subjects’ lived experiences.

Key Takeaways

  • In terms of focus group composition, homogeneity of background among participants is recommended while diverse attitudes within the group are ideal.
  • The goal of a focus group is to get participants to talk with one another rather than the researcher.
  • Like one-on-one qualitative interviews, focus groups can yield very detailed information, are excellent for studying social processes, and provide researchers with an opportunity to observe participants’ body language; they also allow researchers to observe social interaction.
  • Focus groups can be expensive and time-consuming, as are one-on-one interviews; there is also the possibility that a few participants will dominate the group and silence others in the group.
  • Other types of qualitative research include case studies, ethnography, and phenomenology.
  • Data saturation – the point in the qualitative research data collection process when no new information is being discovered
  • Focus groups- planned discussions designed to elicit group interaction and “obtain perceptions on a defined area of interest in a permissive, nonthreatening environment” (Krueger & Casey, 2000, p. 5)
  • Moderator- the researcher tasked with facilitating the conversation in the focus group

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Foundations of Social Work Research Copyright © 2020 by Rebecca L. Mauldin is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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  • Types of qualitative research designs

Last updated

20 February 2023

Reviewed by

Jean Kaluza

Researchers often conduct these studies to gain a detailed understanding of a particular topic through a small, focused sample. Qualitative research methods delve into understanding why something is happening in a larger quantitative study. 

To determine whether qualitative research is the best choice for your study, let’s look at the different types of qualitative research design.

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  • What are qualitative research designs?

Qualitative research designs are research methods that collect and analyze non-numerical data. The research uncovers why or how a particular behavior or occurrence takes place. The information is usually subjective and in a written format instead of numerical.

Researchers may use interviews, focus groups , case studies , journaling, and open-ended questions to gather in-depth information. Qualitative research designs can determine users' concepts, develop a hypothesis , or add context to data from a quantitative study.

  • Characteristics of qualitative research design

Most often, qualitative data answers how or why something occurs. Certain characteristics are usually present in all qualitative research designs to ensure accurate data. 

The most common characteristics of qualitative research design include the following:

Natural environment

It’s best to collect qualitative research as close to the subject’s original environment as possible to encourage natural behavior and accurate insights.

Empathy is key

Qualitative researchers collect the best data when they’re in sync with their users’ concerns and motivations. They can play into natural human psychology by combining open-ended questioning and subtle cues.

They may mimic body language, adopt the users’ terminology, and use pauses or trailing sentences to encourage their participants to fill in the blanks. The more empathic the interviewer, the purer the data.

Participant selection

Qualitative research depends on the meaning obtained from participants instead of the meaning conveyed in similar research or studies. To increase research accuracy, you choose participants randomly from carefully chosen groups of potential participants.

Different research methods or multiple data sources

To gain in-depth knowledge, qualitative research designs often rely on multiple research methods within the same group. 

Emergent design

Qualitative research constantly evolves, meaning the initial study plan might change after you collect data. This evolution might result in changes in research methods or the introduction of a new research problem.

Inductive reasoning

Since qualitative research seeks in-depth meaning, you need complex reasoning to get the right results. Qualitative researchers build categories, patterns, and themes from separate data sets to form a complete conclusion.

Interpretive data

Once you collect the data, you need to read between the lines rather than just noting what your participant said. Qualitative research is unique as we can attach actions to feedback. 

If a user says they love the look of your design but haven’t completed any tasks, it’s up to you to interpret this as a failed test, even with their positive sentiments.  

Holistic account

To paint a large picture of an issue and potential solutions, a qualitative researcher works to develop a complex description of the research problem. You can avoid a narrow cause-and-effect perspective by describing the problem’s wider perspectives. 

  • When to use qualitative research design

Qualitative research aims to get a detailed understanding of a particular topic. To accomplish this, you’ll typically use small focus groups to gather in-depth data from varied perspectives. 

This approach is only effective for some types of study. For instance, a qualitative approach wouldn’t work for a study that seeks to understand a statistically relevant finding.

When determining if a qualitative research design is appropriate, remember the goal of qualitative research is understanding the “ why .” 

Qualitative research design gathers in-depth information that stands on its own. It can also answer the “why” of a quantitative study or be a precursor to forming a hypothesis. 

You can use qualitative research in these situations:

Developing a hypothesis for testing in a quantitative study

Identifying customer needs

Developing a new feature

Adding context to the results of a quantitative study

Understanding the motivations, values, and pain points that guide behavior

Difference between qualitative and quantitative research design

Qualitative and quantitative research designs gather data, but that's where the similarities end. Consider the difference between quality and quantity. Both are useful in different ways.

Qualitative research gathers in-depth information to answer how or why . It uses subjective data from detailed interviews, observations, and open-ended questions. Most often, qualitative data is thoughts, experiences, and concepts.

In contrast, quantitative research designs gather large amounts of objective data that you can quantify mathematically. You typically express quantitative data in numbers or graphs, and you use it to test or confirm hypotheses.

Qualitative research designs generally have the same goals. However, there are various ways to achieve these goals. Researchers may use one or more of these approaches in qualitative research.

Historical study

This is where you use extensive information about people and events in the past to draw conclusions about the present and future.

Phenomenology

Phenomenology investigates a phenomenon, activity, or event using data from participants' perspectives. Often, researchers use a combination of methods.

Grounded theory

Grounded theory uses interviews and existing data to build a theory inductively.

Ethnography

Researchers immerse themselves in the target participant's environments to understand goals, cultures, challenges, and themes with ethnography .

A case study is where you use multiple data sources to examine a person, group, community, or institution. Participants must share a connection to the research question you’re studying.

  • Advantages and disadvantages of qualitative research

All qualitative research design types share the common goal of obtaining in-depth information. Achieving this goal generally requires extensive data collection methods that can be time-consuming. As such, qualitative research has advantages and disadvantages. 

Natural settings

Since you can collect data closer to an authentic environment, it offers more accurate results.  

The ability to paint a picture with data

Quantitative studies don't always reveal the full picture. With multiple data collection methods, you can expose the motivations and reasons behind data.

Flexibility

Analysis processes aren't set in stone, so you can adapt the process as ideas or patterns emerge.

Generation of new ideas

Using open-ended responses can uncover new opportunities or solutions that weren't part of your original research plan.

Small sample sizes

You can generate meaningful results with small groups.

Disadvantages

Potentially unreliable.

A natural setting can be a double-edged sword. The inability to attach findings to anything statistically relevant can make data more difficult to quantify. 

Subjectivity

Since the researcher plays a vital role in collecting and interpreting data, qualitative research is subject to the researcher's skills. For example, they may miss a cue that changes some of the context of the quotes they collected.

Labor-intensive

You generally collect qualitative data through manual processes like extensive interviews, open-ended questions, and case studies.

Qualitative research designs allow researchers to provide an in-depth analysis of why specific behavior or events occur. It can offer fresh insights, generate new ideas, or add context to statistics from quantitative studies. Depending on your needs, qualitative data might be a great way to gain the information your organization needs to move forward.

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Qualitative Research Design

Qualitative Research Design An Interactive Approach

  • Joseph A. Maxwell - George Mason University, VA
  • Description

See what’s new to this edition by selecting the Features tab on this page. Should you need additional information or have questions regarding the HEOA information provided for this title, including what is new to this edition, please email [email protected] . Please include your name, contact information, and the name of the title for which you would like more information. For information on the HEOA, please go to http://ed.gov/policy/highered/leg/hea08/index.html .

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“This book uses everyday language that will captivate students’ attention and embed practical knowledge to supplement the technical.”

“The key strengths of the text are the passion and the enthusiasm that Dr. Maxwell has for qualitative research after all these years. I feel I can also utilize these concepts on my own research team and take them out of the classroom and into research team meetings with colleagues.”

“I really liked this book. I found myself taking notes and saying “yes” so many times because Maxwell captures the research process so well and provides many points worth quoting. As a faculty mentor, I particularly see the value of this book for my students who are conducting qualitative dissertations.”

"Maxwell provides a clear explanation regarding the nuances involved in the circular process of qualitative research design."

Useful book for students undertaking qualitative research

Good book for qualitative research design. Used as a secondary text.

comprehensive, well written

This really is an excellent text which covers a vast range of qualitative research approaches - and is very readable

Maxwell's book has been very helpful to my students to make a conceptual design for their research. They were asked to read the first 3 chapters carefully and make the Chapter 2 assignment. Some students had never thought about their qualitative research in this way. I adopted the book as reference, however I would have made it essential to the course if the price were more reasonable. I think 26 pounds would be acceptable. Maxwell's book gives a common-sense approach to designing social research. I used it to provide a framework for integrating discourse analysis in social research.

Although a very good book, we cover more material than the focus of this book and we would have to adopt too many texts for our students.

New to the Third Edition

  • Provides new and expanded coverage of key topics such as paradigms in qualitative research, conceptual frameworks and using theory, doing literature reviews, and writing research proposals

Key Features

  • Offers an original, innovative model of design based on a systemic rather than a linear or typological structure, well suited for designing studies and writing research proposals
  • Includes many exercises that help readers to design their study
  • Provides guidance in a clear, direct writing style , offering practical advice on research design

A major impetus for a new edition of this book was the opportunity to expand it somewhat beyond the page limits of the earlier series on Applied Social Research Methods, for which it was originally written. However, many readers of the previous editions have said that they appreciated the conciseness of the book, so I didn't want to lose this virtue. Consequently, much of the new material in this edition consists of additional examples of my students' work, including a second example of a dissertation proposal (Appendix B).

Another impetus has been the ongoing development of qualitative research 1 , with a flourishing of new approaches, including arts-based approaches, to how it is conducted and presented. I haven't attempted to deal comprehensively with these, which would have ballooned the book well past what I felt was an appropriate length, as well as taking it beyond an introductory level. If you want to investigate these developments, the SAGE Encyclopedia of Qualitative Research (Given, 2008), the SAGE Handbook of Qualitative Research , 4th edition (Denzin & Lincoln, 2011) and the journal Qualitative Inquiry are good places to start. I've tried to indicate, in Chapters 1 and 3, how I see my approach to design as compatible with some of these developments, in particular with aspects of postmodernism and with the approach known as bricolage, and I have substantially rewritten and expanded my discussion of research paradigms, in Chapter 2.

However, I am also sceptical of some of these developments, particularly those that adopt a radical constructivist and relativist stance that denies the existence of any "reality" that our research attempts to understand, and that rejects any conception of "validity" (or related terms) that addresses the relationship between our research conclusions and the phenomena that we study. While I am enough of a postmodernist to believe that every theory and conclusion is our own construction, with no claim to "objective" or absolute truth, and argue in Chapter 2 that no theory can capture the full complexity of the things we study, I refuse to abandon the goal of gaining a better understanding of the physical, social, and cultural world in which we live, or the possibility of developing credible explanations for these phenomena.

This position is grounded in my third impetus for revising this book: my increasing awareness of how my own perspective on qualitative research has been informed by a philosophical realism about the things we study. I have developed this perspective at length in my book A Realist Approach for Qualitative Research (2011), arguing that the "critical realist" position I have taken is not only compatible with most qualitative researchers' actual practices, but can be valuable in helping researchers with some difficult theoretical, methodological, and political issues that they face. However, I offer this as a useful perspective among other perspectives, not as the single correct paradigm for qualitative research. As the writing teacher Peter Elbow (1973, 2006) argued, it is important to play both the "believing game" and the "doubting game" with any theory or position you encounter, trying to see both its advantages and its distortions or blind spots. For this reason, I want the present book to be of practical value to students and researchers who hold a variety of positions on these issues. The model of qualitative research design that I develop here is compatible with a range of philosophical perspectives, and I believe it is broadly applicable to most qualitative research.

My greater awareness of the implications of a critical realist stance have led me to revise or expand other parts of the book—in particular, the discussion of theory in Chapter 3; developing (and revising) research questions in Chapter 4; research relationships and ethics, developing interview questions, and data analysis, in Chapter 5; the concept of validity in Chapter 6; and the appropriate functions and content of a literature review in a research proposal, in Chapter 7. I've also continued to compulsively tinker with the language of the book, striving to make what I say clearer. I would be grateful for any feedback you can give me on how the book could be made more useful to you.

Finally, I realized in revising this work that I had said almost nothing explicitly about how I define qualitative research—what I see as most essential about a qualitative approach. I say more about this in Chapter 2. However, a brief definition would be that qualitative research is research that is intended to help you better understand 1) the meanings and perspectives of the people you study—seeing the world from their point of view, rather than simply from your own; 2) how these perspectives are shaped by, and shape, their physical, social, and cultural contexts; and 3) the specific processes that are involved in maintaining or altering these phenomena and relationships. All three of these aspects of qualitative research, but particularly the last one, contrast with most quantitative approaches to research, which are based on seeing the phenomena studied in terms of variables —properties of things that can vary, and can thus be measured and compared across contexts. I see most of the more obvious aspects of qualitative research—its inductive, open-ended approach, its reliance on textual or visual rather than numerical data, its primary goal of particular understanding rather than generalization across persons and settings—as due to these three main features of qualitative inquiry. (For a more detailed discussion of these issues, see Maxwell, 2011b.)

1. Some qualitative practitioners prefer the term "inquiry" to "research," seeing the latter as too closely associated with a quantitative or positivist approach. I agree with their concerns (see Maxwell, 2004a, b), and I understand that some types of qualitative inquiry are more humanistic than scientific, but I prefer to argue for a broader definition of "research" that includes a range of qualitative approaches.

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Chapter 2. Research Design

Getting started.

When I teach undergraduates qualitative research methods, the final product of the course is a “research proposal” that incorporates all they have learned and enlists the knowledge they have learned about qualitative research methods in an original design that addresses a particular research question. I highly recommend you think about designing your own research study as you progress through this textbook. Even if you don’t have a study in mind yet, it can be a helpful exercise as you progress through the course. But how to start? How can one design a research study before they even know what research looks like? This chapter will serve as a brief overview of the research design process to orient you to what will be coming in later chapters. Think of it as a “skeleton” of what you will read in more detail in later chapters. Ideally, you will read this chapter both now (in sequence) and later during your reading of the remainder of the text. Do not worry if you have questions the first time you read this chapter. Many things will become clearer as the text advances and as you gain a deeper understanding of all the components of good qualitative research. This is just a preliminary map to get you on the right road.

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Research Design Steps

Before you even get started, you will need to have a broad topic of interest in mind. [1] . In my experience, students can confuse this broad topic with the actual research question, so it is important to clearly distinguish the two. And the place to start is the broad topic. It might be, as was the case with me, working-class college students. But what about working-class college students? What’s it like to be one? Why are there so few compared to others? How do colleges assist (or fail to assist) them? What interested me was something I could barely articulate at first and went something like this: “Why was it so difficult and lonely to be me?” And by extension, “Did others share this experience?”

Once you have a general topic, reflect on why this is important to you. Sometimes we connect with a topic and we don’t really know why. Even if you are not willing to share the real underlying reason you are interested in a topic, it is important that you know the deeper reasons that motivate you. Otherwise, it is quite possible that at some point during the research, you will find yourself turned around facing the wrong direction. I have seen it happen many times. The reason is that the research question is not the same thing as the general topic of interest, and if you don’t know the reasons for your interest, you are likely to design a study answering a research question that is beside the point—to you, at least. And this means you will be much less motivated to carry your research to completion.

Researcher Note

Why do you employ qualitative research methods in your area of study? What are the advantages of qualitative research methods for studying mentorship?

Qualitative research methods are a huge opportunity to increase access, equity, inclusion, and social justice. Qualitative research allows us to engage and examine the uniquenesses/nuances within minoritized and dominant identities and our experiences with these identities. Qualitative research allows us to explore a specific topic, and through that exploration, we can link history to experiences and look for patterns or offer up a unique phenomenon. There’s such beauty in being able to tell a particular story, and qualitative research is a great mode for that! For our work, we examined the relationships we typically use the term mentorship for but didn’t feel that was quite the right word. Qualitative research allowed us to pick apart what we did and how we engaged in our relationships, which then allowed us to more accurately describe what was unique about our mentorship relationships, which we ultimately named liberationships ( McAloney and Long 2021) . Qualitative research gave us the means to explore, process, and name our experiences; what a powerful tool!

How do you come up with ideas for what to study (and how to study it)? Where did you get the idea for studying mentorship?

Coming up with ideas for research, for me, is kind of like Googling a question I have, not finding enough information, and then deciding to dig a little deeper to get the answer. The idea to study mentorship actually came up in conversation with my mentorship triad. We were talking in one of our meetings about our relationship—kind of meta, huh? We discussed how we felt that mentorship was not quite the right term for the relationships we had built. One of us asked what was different about our relationships and mentorship. This all happened when I was taking an ethnography course. During the next session of class, we were discussing auto- and duoethnography, and it hit me—let’s explore our version of mentorship, which we later went on to name liberationships ( McAloney and Long 2021 ). The idea and questions came out of being curious and wanting to find an answer. As I continue to research, I see opportunities in questions I have about my work or during conversations that, in our search for answers, end up exposing gaps in the literature. If I can’t find the answer already out there, I can study it.

—Kim McAloney, PhD, College Student Services Administration Ecampus coordinator and instructor

When you have a better idea of why you are interested in what it is that interests you, you may be surprised to learn that the obvious approaches to the topic are not the only ones. For example, let’s say you think you are interested in preserving coastal wildlife. And as a social scientist, you are interested in policies and practices that affect the long-term viability of coastal wildlife, especially around fishing communities. It would be natural then to consider designing a research study around fishing communities and how they manage their ecosystems. But when you really think about it, you realize that what interests you the most is how people whose livelihoods depend on a particular resource act in ways that deplete that resource. Or, even deeper, you contemplate the puzzle, “How do people justify actions that damage their surroundings?” Now, there are many ways to design a study that gets at that broader question, and not all of them are about fishing communities, although that is certainly one way to go. Maybe you could design an interview-based study that includes and compares loggers, fishers, and desert golfers (those who golf in arid lands that require a great deal of wasteful irrigation). Or design a case study around one particular example where resources were completely used up by a community. Without knowing what it is you are really interested in, what motivates your interest in a surface phenomenon, you are unlikely to come up with the appropriate research design.

These first stages of research design are often the most difficult, but have patience . Taking the time to consider why you are going to go through a lot of trouble to get answers will prevent a lot of wasted energy in the future.

There are distinct reasons for pursuing particular research questions, and it is helpful to distinguish between them.  First, you may be personally motivated.  This is probably the most important and the most often overlooked.   What is it about the social world that sparks your curiosity? What bothers you? What answers do you need in order to keep living? For me, I knew I needed to get a handle on what higher education was for before I kept going at it. I needed to understand why I felt so different from my peers and whether this whole “higher education” thing was “for the likes of me” before I could complete my degree. That is the personal motivation question. Your personal motivation might also be political in nature, in that you want to change the world in a particular way. It’s all right to acknowledge this. In fact, it is better to acknowledge it than to hide it.

There are also academic and professional motivations for a particular study.  If you are an absolute beginner, these may be difficult to find. We’ll talk more about this when we discuss reviewing the literature. Simply put, you are probably not the only person in the world to have thought about this question or issue and those related to it. So how does your interest area fit into what others have studied? Perhaps there is a good study out there of fishing communities, but no one has quite asked the “justification” question. You are motivated to address this to “fill the gap” in our collective knowledge. And maybe you are really not at all sure of what interests you, but you do know that [insert your topic] interests a lot of people, so you would like to work in this area too. You want to be involved in the academic conversation. That is a professional motivation and a very important one to articulate.

Practical and strategic motivations are a third kind. Perhaps you want to encourage people to take better care of the natural resources around them. If this is also part of your motivation, you will want to design your research project in a way that might have an impact on how people behave in the future. There are many ways to do this, one of which is using qualitative research methods rather than quantitative research methods, as the findings of qualitative research are often easier to communicate to a broader audience than the results of quantitative research. You might even be able to engage the community you are studying in the collecting and analyzing of data, something taboo in quantitative research but actively embraced and encouraged by qualitative researchers. But there are other practical reasons, such as getting “done” with your research in a certain amount of time or having access (or no access) to certain information. There is nothing wrong with considering constraints and opportunities when designing your study. Or maybe one of the practical or strategic goals is about learning competence in this area so that you can demonstrate the ability to conduct interviews and focus groups with future employers. Keeping that in mind will help shape your study and prevent you from getting sidetracked using a technique that you are less invested in learning about.

STOP HERE for a moment

I recommend you write a paragraph (at least) explaining your aims and goals. Include a sentence about each of the following: personal/political goals, practical or professional/academic goals, and practical/strategic goals. Think through how all of the goals are related and can be achieved by this particular research study . If they can’t, have a rethink. Perhaps this is not the best way to go about it.

You will also want to be clear about the purpose of your study. “Wait, didn’t we just do this?” you might ask. No! Your goals are not the same as the purpose of the study, although they are related. You can think about purpose lying on a continuum from “ theory ” to “action” (figure 2.1). Sometimes you are doing research to discover new knowledge about the world, while other times you are doing a study because you want to measure an impact or make a difference in the world.

Purpose types: Basic Research, Applied Research, Summative Evaluation, Formative Evaluation, Action Research

Basic research involves research that is done for the sake of “pure” knowledge—that is, knowledge that, at least at this moment in time, may not have any apparent use or application. Often, and this is very important, knowledge of this kind is later found to be extremely helpful in solving problems. So one way of thinking about basic research is that it is knowledge for which no use is yet known but will probably one day prove to be extremely useful. If you are doing basic research, you do not need to argue its usefulness, as the whole point is that we just don’t know yet what this might be.

Researchers engaged in basic research want to understand how the world operates. They are interested in investigating a phenomenon to get at the nature of reality with regard to that phenomenon. The basic researcher’s purpose is to understand and explain ( Patton 2002:215 ).

Basic research is interested in generating and testing hypotheses about how the world works. Grounded Theory is one approach to qualitative research methods that exemplifies basic research (see chapter 4). Most academic journal articles publish basic research findings. If you are working in academia (e.g., writing your dissertation), the default expectation is that you are conducting basic research.

Applied research in the social sciences is research that addresses human and social problems. Unlike basic research, the researcher has expectations that the research will help contribute to resolving a problem, if only by identifying its contours, history, or context. From my experience, most students have this as their baseline assumption about research. Why do a study if not to make things better? But this is a common mistake. Students and their committee members are often working with default assumptions here—the former thinking about applied research as their purpose, the latter thinking about basic research: “The purpose of applied research is to contribute knowledge that will help people to understand the nature of a problem in order to intervene, thereby allowing human beings to more effectively control their environment. While in basic research the source of questions is the tradition within a scholarly discipline, in applied research the source of questions is in the problems and concerns experienced by people and by policymakers” ( Patton 2002:217 ).

Applied research is less geared toward theory in two ways. First, its questions do not derive from previous literature. For this reason, applied research studies have much more limited literature reviews than those found in basic research (although they make up for this by having much more “background” about the problem). Second, it does not generate theory in the same way as basic research does. The findings of an applied research project may not be generalizable beyond the boundaries of this particular problem or context. The findings are more limited. They are useful now but may be less useful later. This is why basic research remains the default “gold standard” of academic research.

Evaluation research is research that is designed to evaluate or test the effectiveness of specific solutions and programs addressing specific social problems. We already know the problems, and someone has already come up with solutions. There might be a program, say, for first-generation college students on your campus. Does this program work? Are first-generation students who participate in the program more likely to graduate than those who do not? These are the types of questions addressed by evaluation research. There are two types of research within this broader frame; however, one more action-oriented than the next. In summative evaluation , an overall judgment about the effectiveness of a program or policy is made. Should we continue our first-gen program? Is it a good model for other campuses? Because the purpose of such summative evaluation is to measure success and to determine whether this success is scalable (capable of being generalized beyond the specific case), quantitative data is more often used than qualitative data. In our example, we might have “outcomes” data for thousands of students, and we might run various tests to determine if the better outcomes of those in the program are statistically significant so that we can generalize the findings and recommend similar programs elsewhere. Qualitative data in the form of focus groups or interviews can then be used for illustrative purposes, providing more depth to the quantitative analyses. In contrast, formative evaluation attempts to improve a program or policy (to help “form” or shape its effectiveness). Formative evaluations rely more heavily on qualitative data—case studies, interviews, focus groups. The findings are meant not to generalize beyond the particular but to improve this program. If you are a student seeking to improve your qualitative research skills and you do not care about generating basic research, formative evaluation studies might be an attractive option for you to pursue, as there are always local programs that need evaluation and suggestions for improvement. Again, be very clear about your purpose when talking through your research proposal with your committee.

Action research takes a further step beyond evaluation, even formative evaluation, to being part of the solution itself. This is about as far from basic research as one could get and definitely falls beyond the scope of “science,” as conventionally defined. The distinction between action and research is blurry, the research methods are often in constant flux, and the only “findings” are specific to the problem or case at hand and often are findings about the process of intervention itself. Rather than evaluate a program as a whole, action research often seeks to change and improve some particular aspect that may not be working—maybe there is not enough diversity in an organization or maybe women’s voices are muted during meetings and the organization wonders why and would like to change this. In a further step, participatory action research , those women would become part of the research team, attempting to amplify their voices in the organization through participation in the action research. As action research employs methods that involve people in the process, focus groups are quite common.

If you are working on a thesis or dissertation, chances are your committee will expect you to be contributing to fundamental knowledge and theory ( basic research ). If your interests lie more toward the action end of the continuum, however, it is helpful to talk to your committee about this before you get started. Knowing your purpose in advance will help avoid misunderstandings during the later stages of the research process!

The Research Question

Once you have written your paragraph and clarified your purpose and truly know that this study is the best study for you to be doing right now , you are ready to write and refine your actual research question. Know that research questions are often moving targets in qualitative research, that they can be refined up to the very end of data collection and analysis. But you do have to have a working research question at all stages. This is your “anchor” when you get lost in the data. What are you addressing? What are you looking at and why? Your research question guides you through the thicket. It is common to have a whole host of questions about a phenomenon or case, both at the outset and throughout the study, but you should be able to pare it down to no more than two or three sentences when asked. These sentences should both clarify the intent of the research and explain why this is an important question to answer. More on refining your research question can be found in chapter 4.

Chances are, you will have already done some prior reading before coming up with your interest and your questions, but you may not have conducted a systematic literature review. This is the next crucial stage to be completed before venturing further. You don’t want to start collecting data and then realize that someone has already beaten you to the punch. A review of the literature that is already out there will let you know (1) if others have already done the study you are envisioning; (2) if others have done similar studies, which can help you out; and (3) what ideas or concepts are out there that can help you frame your study and make sense of your findings. More on literature reviews can be found in chapter 9.

In addition to reviewing the literature for similar studies to what you are proposing, it can be extremely helpful to find a study that inspires you. This may have absolutely nothing to do with the topic you are interested in but is written so beautifully or organized so interestingly or otherwise speaks to you in such a way that you want to post it somewhere to remind you of what you want to be doing. You might not understand this in the early stages—why would you find a study that has nothing to do with the one you are doing helpful? But trust me, when you are deep into analysis and writing, having an inspirational model in view can help you push through. If you are motivated to do something that might change the world, you probably have read something somewhere that inspired you. Go back to that original inspiration and read it carefully and see how they managed to convey the passion that you so appreciate.

At this stage, you are still just getting started. There are a lot of things to do before setting forth to collect data! You’ll want to consider and choose a research tradition and a set of data-collection techniques that both help you answer your research question and match all your aims and goals. For example, if you really want to help migrant workers speak for themselves, you might draw on feminist theory and participatory action research models. Chapters 3 and 4 will provide you with more information on epistemologies and approaches.

Next, you have to clarify your “units of analysis.” What is the level at which you are focusing your study? Often, the unit in qualitative research methods is individual people, or “human subjects.” But your units of analysis could just as well be organizations (colleges, hospitals) or programs or even whole nations. Think about what it is you want to be saying at the end of your study—are the insights you are hoping to make about people or about organizations or about something else entirely? A unit of analysis can even be a historical period! Every unit of analysis will call for a different kind of data collection and analysis and will produce different kinds of “findings” at the conclusion of your study. [2]

Regardless of what unit of analysis you select, you will probably have to consider the “human subjects” involved in your research. [3] Who are they? What interactions will you have with them—that is, what kind of data will you be collecting? Before answering these questions, define your population of interest and your research setting. Use your research question to help guide you.

Let’s use an example from a real study. In Geographies of Campus Inequality , Benson and Lee ( 2020 ) list three related research questions: “(1) What are the different ways that first-generation students organize their social, extracurricular, and academic activities at selective and highly selective colleges? (2) how do first-generation students sort themselves and get sorted into these different types of campus lives; and (3) how do these different patterns of campus engagement prepare first-generation students for their post-college lives?” (3).

Note that we are jumping into this a bit late, after Benson and Lee have described previous studies (the literature review) and what is known about first-generation college students and what is not known. They want to know about differences within this group, and they are interested in ones attending certain kinds of colleges because those colleges will be sites where academic and extracurricular pressures compete. That is the context for their three related research questions. What is the population of interest here? First-generation college students . What is the research setting? Selective and highly selective colleges . But a host of questions remain. Which students in the real world, which colleges? What about gender, race, and other identity markers? Will the students be asked questions? Are the students still in college, or will they be asked about what college was like for them? Will they be observed? Will they be shadowed? Will they be surveyed? Will they be asked to keep diaries of their time in college? How many students? How many colleges? For how long will they be observed?

Recommendation

Take a moment and write down suggestions for Benson and Lee before continuing on to what they actually did.

Have you written down your own suggestions? Good. Now let’s compare those with what they actually did. Benson and Lee drew on two sources of data: in-depth interviews with sixty-four first-generation students and survey data from a preexisting national survey of students at twenty-eight selective colleges. Let’s ignore the survey for our purposes here and focus on those interviews. The interviews were conducted between 2014 and 2016 at a single selective college, “Hilltop” (a pseudonym ). They employed a “purposive” sampling strategy to ensure an equal number of male-identifying and female-identifying students as well as equal numbers of White, Black, and Latinx students. Each student was interviewed once. Hilltop is a selective liberal arts college in the northeast that enrolls about three thousand students.

How did your suggestions match up to those actually used by the researchers in this study? It is possible your suggestions were too ambitious? Beginning qualitative researchers can often make that mistake. You want a research design that is both effective (it matches your question and goals) and doable. You will never be able to collect data from your entire population of interest (unless your research question is really so narrow to be relevant to very few people!), so you will need to come up with a good sample. Define the criteria for this sample, as Benson and Lee did when deciding to interview an equal number of students by gender and race categories. Define the criteria for your sample setting too. Hilltop is typical for selective colleges. That was a research choice made by Benson and Lee. For more on sampling and sampling choices, see chapter 5.

Benson and Lee chose to employ interviews. If you also would like to include interviews, you have to think about what will be asked in them. Most interview-based research involves an interview guide, a set of questions or question areas that will be asked of each participant. The research question helps you create a relevant interview guide. You want to ask questions whose answers will provide insight into your research question. Again, your research question is the anchor you will continually come back to as you plan for and conduct your study. It may be that once you begin interviewing, you find that people are telling you something totally unexpected, and this makes you rethink your research question. That is fine. Then you have a new anchor. But you always have an anchor. More on interviewing can be found in chapter 11.

Let’s imagine Benson and Lee also observed college students as they went about doing the things college students do, both in the classroom and in the clubs and social activities in which they participate. They would have needed a plan for this. Would they sit in on classes? Which ones and how many? Would they attend club meetings and sports events? Which ones and how many? Would they participate themselves? How would they record their observations? More on observation techniques can be found in both chapters 13 and 14.

At this point, the design is almost complete. You know why you are doing this study, you have a clear research question to guide you, you have identified your population of interest and research setting, and you have a reasonable sample of each. You also have put together a plan for data collection, which might include drafting an interview guide or making plans for observations. And so you know exactly what you will be doing for the next several months (or years!). To put the project into action, there are a few more things necessary before actually going into the field.

First, you will need to make sure you have any necessary supplies, including recording technology. These days, many researchers use their phones to record interviews. Second, you will need to draft a few documents for your participants. These include informed consent forms and recruiting materials, such as posters or email texts, that explain what this study is in clear language. Third, you will draft a research protocol to submit to your institutional review board (IRB) ; this research protocol will include the interview guide (if you are using one), the consent form template, and all examples of recruiting material. Depending on your institution and the details of your study design, it may take weeks or even, in some unfortunate cases, months before you secure IRB approval. Make sure you plan on this time in your project timeline. While you wait, you can continue to review the literature and possibly begin drafting a section on the literature review for your eventual presentation/publication. More on IRB procedures can be found in chapter 8 and more general ethical considerations in chapter 7.

Once you have approval, you can begin!

Research Design Checklist

Before data collection begins, do the following:

  • Write a paragraph explaining your aims and goals (personal/political, practical/strategic, professional/academic).
  • Define your research question; write two to three sentences that clarify the intent of the research and why this is an important question to answer.
  • Review the literature for similar studies that address your research question or similar research questions; think laterally about some literature that might be helpful or illuminating but is not exactly about the same topic.
  • Find a written study that inspires you—it may or may not be on the research question you have chosen.
  • Consider and choose a research tradition and set of data-collection techniques that (1) help answer your research question and (2) match your aims and goals.
  • Define your population of interest and your research setting.
  • Define the criteria for your sample (How many? Why these? How will you find them, gain access, and acquire consent?).
  • If you are conducting interviews, draft an interview guide.
  •  If you are making observations, create a plan for observations (sites, times, recording, access).
  • Acquire any necessary technology (recording devices/software).
  • Draft consent forms that clearly identify the research focus and selection process.
  • Create recruiting materials (posters, email, texts).
  • Apply for IRB approval (proposal plus consent form plus recruiting materials).
  • Block out time for collecting data.
  • At the end of the chapter, you will find a " Research Design Checklist " that summarizes the main recommendations made here ↵
  • For example, if your focus is society and culture , you might collect data through observation or a case study. If your focus is individual lived experience , you are probably going to be interviewing some people. And if your focus is language and communication , you will probably be analyzing text (written or visual). ( Marshall and Rossman 2016:16 ). ↵
  • You may not have any "live" human subjects. There are qualitative research methods that do not require interactions with live human beings - see chapter 16 , "Archival and Historical Sources." But for the most part, you are probably reading this textbook because you are interested in doing research with people. The rest of the chapter will assume this is the case. ↵

One of the primary methodological traditions of inquiry in qualitative research, ethnography is the study of a group or group culture, largely through observational fieldwork supplemented by interviews. It is a form of fieldwork that may include participant-observation data collection. See chapter 14 for a discussion of deep ethnography. 

A methodological tradition of inquiry and research design that focuses on an individual case (e.g., setting, institution, or sometimes an individual) in order to explore its complexity, history, and interactive parts.  As an approach, it is particularly useful for obtaining a deep appreciation of an issue, event, or phenomenon of interest in its particular context.

The controlling force in research; can be understood as lying on a continuum from basic research (knowledge production) to action research (effecting change).

In its most basic sense, a theory is a story we tell about how the world works that can be tested with empirical evidence.  In qualitative research, we use the term in a variety of ways, many of which are different from how they are used by quantitative researchers.  Although some qualitative research can be described as “testing theory,” it is more common to “build theory” from the data using inductive reasoning , as done in Grounded Theory .  There are so-called “grand theories” that seek to integrate a whole series of findings and stories into an overarching paradigm about how the world works, and much smaller theories or concepts about particular processes and relationships.  Theory can even be used to explain particular methodological perspectives or approaches, as in Institutional Ethnography , which is both a way of doing research and a theory about how the world works.

Research that is interested in generating and testing hypotheses about how the world works.

A methodological tradition of inquiry and approach to analyzing qualitative data in which theories emerge from a rigorous and systematic process of induction.  This approach was pioneered by the sociologists Glaser and Strauss (1967).  The elements of theory generated from comparative analysis of data are, first, conceptual categories and their properties and, second, hypotheses or generalized relations among the categories and their properties – “The constant comparing of many groups draws the [researcher’s] attention to their many similarities and differences.  Considering these leads [the researcher] to generate abstract categories and their properties, which, since they emerge from the data, will clearly be important to a theory explaining the kind of behavior under observation.” (36).

An approach to research that is “multimethod in focus, involving an interpretative, naturalistic approach to its subject matter.  This means that qualitative researchers study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them.  Qualitative research involves the studied use and collection of a variety of empirical materials – case study, personal experience, introspective, life story, interview, observational, historical, interactional, and visual texts – that describe routine and problematic moments and meanings in individuals’ lives." ( Denzin and Lincoln 2005:2 ). Contrast with quantitative research .

Research that contributes knowledge that will help people to understand the nature of a problem in order to intervene, thereby allowing human beings to more effectively control their environment.

Research that is designed to evaluate or test the effectiveness of specific solutions and programs addressing specific social problems.  There are two kinds: summative and formative .

Research in which an overall judgment about the effectiveness of a program or policy is made, often for the purpose of generalizing to other cases or programs.  Generally uses qualitative research as a supplement to primary quantitative data analyses.  Contrast formative evaluation research .

Research designed to improve a program or policy (to help “form” or shape its effectiveness); relies heavily on qualitative research methods.  Contrast summative evaluation research

Research carried out at a particular organizational or community site with the intention of affecting change; often involves research subjects as participants of the study.  See also participatory action research .

Research in which both researchers and participants work together to understand a problematic situation and change it for the better.

The level of the focus of analysis (e.g., individual people, organizations, programs, neighborhoods).

The large group of interest to the researcher.  Although it will likely be impossible to design a study that incorporates or reaches all members of the population of interest, this should be clearly defined at the outset of a study so that a reasonable sample of the population can be taken.  For example, if one is studying working-class college students, the sample may include twenty such students attending a particular college, while the population is “working-class college students.”  In quantitative research, clearly defining the general population of interest is a necessary step in generalizing results from a sample.  In qualitative research, defining the population is conceptually important for clarity.

A fictional name assigned to give anonymity to a person, group, or place.  Pseudonyms are important ways of protecting the identity of research participants while still providing a “human element” in the presentation of qualitative data.  There are ethical considerations to be made in selecting pseudonyms; some researchers allow research participants to choose their own.

A requirement for research involving human participants; the documentation of informed consent.  In some cases, oral consent or assent may be sufficient, but the default standard is a single-page easy-to-understand form that both the researcher and the participant sign and date.   Under federal guidelines, all researchers "shall seek such consent only under circumstances that provide the prospective subject or the representative sufficient opportunity to consider whether or not to participate and that minimize the possibility of coercion or undue influence. The information that is given to the subject or the representative shall be in language understandable to the subject or the representative.  No informed consent, whether oral or written, may include any exculpatory language through which the subject or the representative is made to waive or appear to waive any of the subject's rights or releases or appears to release the investigator, the sponsor, the institution, or its agents from liability for negligence" (21 CFR 50.20).  Your IRB office will be able to provide a template for use in your study .

An administrative body established to protect the rights and welfare of human research subjects recruited to participate in research activities conducted under the auspices of the institution with which it is affiliated. The IRB is charged with the responsibility of reviewing all research involving human participants. The IRB is concerned with protecting the welfare, rights, and privacy of human subjects. The IRB has the authority to approve, disapprove, monitor, and require modifications in all research activities that fall within its jurisdiction as specified by both the federal regulations and institutional policy.

Introduction to Qualitative Research Methods Copyright © 2023 by Allison Hurst is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License , except where otherwise noted.

5 qualitative research designs

Types Of Qualitative Research Designs And Methods

Qualitative research design comes in many forms. Understanding what qualitative research is and the various methods that fall under its…

Types Of Qualitative Research Designs

Qualitative research design comes in many forms. Understanding what qualitative research is and the various methods that fall under its umbrella can help determine which method or design to use. Various techniques can achieve results, depending on the subject of study.

Types of qualitative research to explore social behavior or understand interactions within specific contexts include interviews, focus groups, observations and surveys. These identify concepts and relationships that aren’t easily observed through quantitative methods. Figuring out what to explore through qualitative research is the first step in picking the right study design.

Let’s look at the most common types of qualitative methods.

What Is Qualitative Research Design?

Types of qualitative research designs, how are qualitative answers analyzed, qualitative research design in business.

There are several types of qualitative research. The term refers to in-depth, exploratory studies that discover what people think, how they behave and the reasons behind their behavior. The qualitative researcher believes that to best understand human behavior, they need to know the context in which people are acting and making decisions.

Let’s define some basic terms.

Qualitative Method

A group of techniques that allow the researcher to gather information from participants to learn about their experiences, behaviors or beliefs. The types of qualitative research methods used in a specific study should be chosen as dictated by the data being gathered. For instance, to study how employers rate the skills of the engineering students they hired, qualitative research would be appropriate.

Quantitative Method

A group of techniques that allows the researcher to gather information from participants to measure variables. The data is numerical in nature. For instance, quantitative research can be used to study how many engineering students enroll in an MBA program.

Research Design

A plan or outline of how the researcher will proceed with the proposed research project. This defines the sample, the scope of work, the goals and objectives. It may also lay out a hypothesis to be tested. Research design could also combine qualitative and quantitative techniques.

Both qualitative and quantitative research are significant. Depending on the subject and the goals of the study, researchers choose one or the other or a combination of the two. This is all part of the qualitative research design process.

Before we look at some different types of qualitative research, it’s important to note that there’s no one correct approach to qualitative research design. No matter what the type of study, it’s important to carefully consider the design to ensure the method is suitable to the research question. Here are the types of qualitative research methods to choose from:

Cluster Sampling

This technique involves selecting participants from specific locations or teams (clusters). A researcher may set out to observe, interview, or create a focus group with participants linked by location, organization or some other commonality. For example, the researcher might select the top five teams that produce an organization’s finest work. The same can be done by looking at locations (stores in a geographic region). The benefit of this design is that it’s efficient in collecting opinions from specific working groups or areas. However, this limits the sample size to only those people who work within the cluster.

Random Sampling

This design involves randomly assigning participants into groups based on a set of variables (location, gender, race, occupation). In this design, each participant is assigned an equal chance of being selected into a particular group. For example, if the researcher wants to study how students from different colleges differ from one another in terms of workplace habits and friendships, a random sample could be chosen from the student population at these colleges. The purpose of this design is to create a more even distribution of participants across all groups. The researcher will need to choose which groups to include in the study.

Focus Groups

A focus group is a small group that meets to discuss specific issues. Participants are usually recruited randomly, although sometimes they might be recruited because of personal relationships with each other or because they represent part of a certain demographic (age, location). Focus groups are one of the most popular styles of qualitative research because they allow for individual views and opinions to be shared without introducing bias. Researchers gather data through face-to-face conversation or recorded observation.

Observation

This technique involves observing the interaction patterns in a particular situation. Researchers collect data by closely watching the behaviors of others. This method can only be used in certain settings, such as in the workplace or homes.

An interview is an open-ended conversation between a researcher and a participant in which the researcher asks predetermined questions. Successful interviews require careful preparation to ensure that participants are able to give accurate answers. This method allows researchers to collect specific information about their research topic, and participants are more likely to be honest when telling their stories. However, there’s no way to control the number of unique answers, and certain participants may feel uncomfortable sharing their personal details with a stranger.

A survey is a questionnaire used to gather information from a pool of people to get a large sample of responses. This study design allows researchers to collect more data than they would with individual interviews and observations. Depending on the nature of the survey, it may also not require participants to disclose sensitive information or details. On the flip side, it’s time-consuming and may not yield the answers researchers were looking for. It’s also difficult to collect and analyze answers from larger groups.

A large study can combine several of these methods. For instance, it can involve a survey to better understand which kind of organic produce consumers are looking for. It may also include questions on the frequency of such purchases—a numerical data point—alongside their views on the legitimacy of the organic tag, which is an open-ended qualitative question.

Knowledge of the types of qualitative research designs will help you achieve the results you desire.

With quantitative research, analysis of results is fairly straightforward. But, the nature of qualitative research design is such that turning the information collected into usable data can be a challenge. To do this, researchers have to code the non-numerical data for comparison and analysis.

The researcher goes through all their notes and recordings and codes them using a predetermined scheme. Codes are created by ‘stripping out’ words or phrases that seem to answer the questions posed. The researcher will need to decide which categories to code for. Sometimes this process can be time-consuming and difficult to do during the first few passes through the data. So, it’s a good idea to start off by coding a small amount of the data and conducting a thematic analysis to get a better understanding of how to proceed.

The data collected must be organized and analyzed to answer the research questions. There are three approaches to analyzing the data: exploratory, confirmatory and descriptive.

Explanatory Data Analysis

This approach involves looking for relationships within the data to make sense of it. This design can be useful if the research question is ambiguous or open-ended. Exploratory analysis is very flexible and can be used in a number of settings. But, it generally looks at the relationship between variables while the researcher is working with the data.

Confirmatory Data Analysis

This design is used when there’s a hypothesis or theory to be tested. Confirmatory research seeks to test how well past findings apply to new observations by comparing them to statistical tests that quantify relationships between variables. It can also use prior research findings to predict new results.

Descriptive Data Analysis

In this design, the researcher will describe patterns that can be observed from the data. The researcher will take raw data and interpret it with an eye for patterns to formulate a theory that can eventually be tested with quantitative data. The qualitative design is ideal for exploring events that can’t be observed (such as people’s thoughts) or when a process is being evaluated.

With careful planning and insightful analysis, qualitative research is a versatile and useful tool in business, public policy and social studies. In the workplace, managers can use it to understand markets and consumers better or to study the health of an organization.

Businesses conduct qualitative research for many reasons. Harappa’s Thinking Critically course prepares professionals to use such data to understand their work better. Driven by experienced faculty with real-world experience, the course equips employees on a growth trajectory with frameworks and skills to use their reasoning abilities to build better arguments. It’s possible to build more effective teams. Find out how with Harappa.

Explore Harappa Diaries to learn more about topics such as What is Qualitative Research , Quantitative Vs Qualitative Research , Examples of Phenomenological Research and Tips For Studying Online to upgrade your knowledge and skills.

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Qualitative Research: Characteristics, Design, Methods & Examples

Lauren McCall

MSc Health Psychology Graduate

MSc, Health Psychology, University of Nottingham

Lauren obtained an MSc in Health Psychology from The University of Nottingham with a distinction classification.

Learn about our Editorial Process

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, Ph.D., is a qualified psychology teacher with over 18 years experience of working in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

On This Page:

“Not everything that can be counted counts, and not everything that counts can be counted“ (Albert Einstein)

Qualitative research is a process used for the systematic collection, analysis, and interpretation of non-numerical data (Punch, 2013). 

Qualitative research can be used to: (i) gain deep contextual understandings of the subjective social reality of individuals and (ii) to answer questions about experience and meaning from the participant’s perspective (Hammarberg et al., 2016).

Unlike quantitative research, which focuses on gathering and analyzing numerical data for statistical analysis, qualitative research focuses on thematic and contextual information.

Characteristics of Qualitative Research 

Reality is socially constructed.

Qualitative research aims to understand how participants make meaning of their experiences – individually or in social contexts. It assumes there is no objective reality and that the social world is interpreted (Yilmaz, 2013). 

The primacy of subject matter 

The primary aim of qualitative research is to understand the perspectives, experiences, and beliefs of individuals who have experienced the phenomenon selected for research rather than the average experiences of groups of people (Minichiello, 1990).

Variables are complex, interwoven, and difficult to measure

Factors such as experiences, behaviors, and attitudes are complex and interwoven, so they cannot be reduced to isolated variables , making them difficult to measure quantitatively.

However, a qualitative approach enables participants to describe what, why, or how they were thinking/ feeling during a phenomenon being studied (Yilmaz, 2013). 

Emic (insider’s point of view)

The phenomenon being studied is centered on the participants’ point of view (Minichiello, 1990).

Emic is used to describe how participants interact, communicate, and behave in the context of the research setting (Scarduzio, 2017).

Why Conduct Qualitative Research? 

In order to gain a deeper understanding of how people experience the world, individuals are studied in their natural setting. This enables the researcher to understand a phenomenon close to how participants experience it. 

Qualitative research allows researchers to gain an in-depth understanding, which is difficult to attain using quantitative methods. 

An in-depth understanding is attained since qualitative techniques allow participants to freely disclose their experiences, thoughts, and feelings without constraint (Tenny et al., 2022). 

This helps to further investigate and understand quantitative data by discovering reasons for the outcome of a study – answering the why question behind statistics. 

The exploratory nature of qualitative research helps to generate hypotheses that can then be tested quantitatively (Busetto et al., 2020).

To design hypotheses, theory must be researched using qualitative methods to find out what is important in order to begin research. 

For example, by conducting interviews or focus groups with key stakeholders to discover what is important to them. 

Examples of qualitative research questions include: 

  • How does stress influence young adults’ behavior?
  • What factors influence students’ school attendance rates in developed countries?
  • How do adults interpret binge drinking in the UK?
  • What are the psychological impacts of cervical cancer screening in women?
  • How can mental health lessons be integrated into the school curriculum? 

Collecting Qualitative Data

There are four main research design methods used to collect qualitative data: observations, interviews,  focus groups, and ethnography.

Observations

This method involves watching and recording phenomena as they occur in nature. Observation can be divided into two types: participant and non-participant observation.

In participant observation, the researcher actively participates in the situation/events being observed.

In non-participant observation, the researcher is not an active part of the observation and tries not to influence the behaviors they are observing (Busetto et al., 2020). 

Observations can be covert (participants are unaware that a researcher is observing them) or overt (participants are aware of the researcher’s presence and know they are being observed).

However, awareness of an observer’s presence may influence participants’ behavior. 

Interviews give researchers a window into the world of a participant by seeking their account of an event, situation, or phenomenon. They are usually conducted on a one-to-one basis and can be distinguished according to the level at which they are structured (Punch, 2013). 

Structured interviews involve predetermined questions and sequences to ensure replicability and comparability. However, they are unable to explore emerging issues.

Informal interviews consist of spontaneous, casual conversations which are closer to the truth of a phenomenon. However, information is gathered using quick notes made by the researcher and is therefore subject to recall bias. 

Semi-structured interviews have a flexible structure, phrasing, and placement so emerging issues can be explored (Denny & Weckesser, 2022).

The use of probing questions and clarification can lead to a detailed understanding, but semi-structured interviews can be time-consuming and subject to interviewer bias. 

Focus groups 

Similar to interviews, focus groups elicit a rich and detailed account of an experience. However, focus groups are more dynamic since participants with shared characteristics construct this account together (Denny & Weckesser, 2022).

A shared narrative is built between participants to capture a group experience shaped by a shared context. 

The researcher takes on the role of a moderator, who will establish ground rules and guide the discussion by following a topic guide to focus the group discussions.

Typically, focus groups have 4-10 participants as a discussion can be difficult to facilitate with more than this, and this number allows everyone the time to speak.

Ethnography

Ethnography is a methodology used to study a group of people’s behaviors and social interactions in their environment (Reeves et al., 2008).

Data are collected using methods such as observations, field notes, or structured/ unstructured interviews.

The aim of ethnography is to provide detailed, holistic insights into people’s behavior and perspectives within their natural setting. In order to achieve this, researchers immerse themselves in a community or organization. 

Due to the flexibility and real-world focus of ethnography, researchers are able to gather an in-depth, nuanced understanding of people’s experiences, knowledge and perspectives that are influenced by culture and society.

In order to develop a representative picture of a particular culture/ context, researchers must conduct extensive field work. 

This can be time-consuming as researchers may need to immerse themselves into a community/ culture for a few days, or possibly a few years.

Qualitative Data Analysis Methods

Different methods can be used for analyzing qualitative data. The researcher chooses based on the objectives of their study. 

The researcher plays a key role in the interpretation of data, making decisions about the coding, theming, decontextualizing, and recontextualizing of data (Starks & Trinidad, 2007). 

Grounded theory

Grounded theory is a qualitative method specifically designed to inductively generate theory from data. It was developed by Glaser and Strauss in 1967 (Glaser & Strauss, 2017).

 This methodology aims to develop theories (rather than test hypotheses) that explain a social process, action, or interaction (Petty et al., 2012). To inform the developing theory, data collection and analysis run simultaneously. 

There are three key types of coding used in grounded theory: initial (open), intermediate (axial), and advanced (selective) coding. 

Throughout the analysis, memos should be created to document methodological and theoretical ideas about the data. Data should be collected and analyzed until data saturation is reached and a theory is developed. 

Content analysis

Content analysis was first used in the early twentieth century to analyze textual materials such as newspapers and political speeches.

Content analysis is a research method used to identify and analyze the presence and patterns of themes, concepts, or words in data (Vaismoradi et al., 2013). 

This research method can be used to analyze data in different formats, which can be written, oral, or visual. 

The goal of content analysis is to develop themes that capture the underlying meanings of data (Schreier, 2012). 

Qualitative content analysis can be used to validate existing theories, support the development of new models and theories, and provide in-depth descriptions of particular settings or experiences.

The following six steps provide a guideline for how to conduct qualitative content analysis.
  • Define a Research Question : To start content analysis, a clear research question should be developed.
  • Identify and Collect Data : Establish the inclusion criteria for your data. Find the relevant sources to analyze.
  • Define the Unit or Theme of Analysis : Categorize the content into themes. Themes can be a word, phrase, or sentence.
  • Develop Rules for Coding your Data : Define a set of coding rules to ensure that all data are coded consistently.
  • Code the Data : Follow the coding rules to categorize data into themes.
  • Analyze the Results and Draw Conclusions : Examine the data to identify patterns and draw conclusions in relation to your research question.

Discourse analysis

Discourse analysis is a research method used to study written/ spoken language in relation to its social context (Wood & Kroger, 2000).

In discourse analysis, the researcher interprets details of language materials and the context in which it is situated.

Discourse analysis aims to understand the functions of language (how language is used in real life) and how meaning is conveyed by language in different contexts. Researchers use discourse analysis to investigate social groups and how language is used to achieve specific communication goals.

Different methods of discourse analysis can be used depending on the aims and objectives of a study. However, the following steps provide a guideline on how to conduct discourse analysis.
  • Define the Research Question : Develop a relevant research question to frame the analysis.
  • Gather Data and Establish the Context : Collect research materials (e.g., interview transcripts, documents). Gather factual details and review the literature to construct a theory about the social and historical context of your study.
  • Analyze the Content : Closely examine various components of the text, such as the vocabulary, sentences, paragraphs, and structure of the text. Identify patterns relevant to the research question to create codes, then group these into themes.
  • Review the Results : Reflect on the findings to examine the function of the language, and the meaning and context of the discourse. 

Thematic analysis

Thematic analysis is a method used to identify, interpret, and report patterns in data, such as commonalities or contrasts. 

Although the origin of thematic analysis can be traced back to the early twentieth century, understanding and clarity of thematic analysis is attributed to Braun and Clarke (2006).

Thematic analysis aims to develop themes (patterns of meaning) across a dataset to address a research question. 

In thematic analysis, qualitative data is gathered using techniques such as interviews, focus groups, and questionnaires. Audio recordings are transcribed. The dataset is then explored and interpreted by a researcher to identify patterns. 

This occurs through the rigorous process of data familiarisation, coding, theme development, and revision. These identified patterns provide a summary of the dataset and can be used to address a research question.

Themes are developed by exploring the implicit and explicit meanings within the data. Two different approaches are used to generate themes: inductive and deductive. 

An inductive approach allows themes to emerge from the data. In contrast, a deductive approach uses existing theories or knowledge to apply preconceived ideas to the data.

Phases of Thematic Analysis

Braun and Clarke (2006) provide a guide of the six phases of thematic analysis. These phases can be applied flexibly to fit research questions and data. 

Template analysis

Template analysis refers to a specific method of thematic analysis which uses hierarchical coding (Brooks et al., 2014).

Template analysis is used to analyze textual data, for example, interview transcripts or open-ended responses on a written questionnaire.

To conduct template analysis, a coding template must be developed (usually from a subset of the data) and subsequently revised and refined. This template represents the themes identified by researchers as important in the dataset. 

Codes are ordered hierarchically within the template, with the highest-level codes demonstrating overarching themes in the data and lower-level codes representing constituent themes with a narrower focus.

A guideline for the main procedural steps for conducting template analysis is outlined below.
  • Familiarization with the Data : Read (and reread) the dataset in full. Engage, reflect, and take notes on data that may be relevant to the research question.
  • Preliminary Coding : Identify initial codes using guidance from the a priori codes, identified before the analysis as likely to be beneficial and relevant to the analysis.
  • Organize Themes : Organize themes into meaningful clusters. Consider the relationships between the themes both within and between clusters.
  • Produce an Initial Template : Develop an initial template. This may be based on a subset of the data.
  • Apply and Develop the Template : Apply the initial template to further data and make any necessary modifications. Refinements of the template may include adding themes, removing themes, or changing the scope/title of themes. 
  • Finalize Template : Finalize the template, then apply it to the entire dataset. 

Frame analysis

Frame analysis is a comparative form of thematic analysis which systematically analyzes data using a matrix output.

Ritchie and Spencer (1994) developed this set of techniques to analyze qualitative data in applied policy research. Frame analysis aims to generate theory from data.

Frame analysis encourages researchers to organize and manage their data using summarization.

This results in a flexible and unique matrix output, in which individual participants (or cases) are represented by rows and themes are represented by columns. 

Each intersecting cell is used to summarize findings relating to the corresponding participant and theme.

Frame analysis has five distinct phases which are interrelated, forming a methodical and rigorous framework.
  • Familiarization with the Data : Familiarize yourself with all the transcripts. Immerse yourself in the details of each transcript and start to note recurring themes.
  • Develop a Theoretical Framework : Identify recurrent/ important themes and add them to a chart. Provide a framework/ structure for the analysis.
  • Indexing : Apply the framework systematically to the entire study data.
  • Summarize Data in Analytical Framework : Reduce the data into brief summaries of participants’ accounts.
  • Mapping and Interpretation : Compare themes and subthemes and check against the original transcripts. Group the data into categories and provide an explanation for them.

Preventing Bias in Qualitative Research

To evaluate qualitative studies, the CASP (Critical Appraisal Skills Programme) checklist for qualitative studies can be used to ensure all aspects of a study have been considered (CASP, 2018).

The quality of research can be enhanced and assessed using criteria such as checklists, reflexivity, co-coding, and member-checking. 

Co-coding 

Relying on only one researcher to interpret rich and complex data may risk key insights and alternative viewpoints being missed. Therefore, coding is often performed by multiple researchers.

A common strategy must be defined at the beginning of the coding process  (Busetto et al., 2020). This includes establishing a useful coding list and finding a common definition of individual codes.

Transcripts are initially coded independently by researchers and then compared and consolidated to minimize error or bias and to bring confirmation of findings. 

Member checking

Member checking (or respondent validation) involves checking back with participants to see if the research resonates with their experiences (Russell & Gregory, 2003).

Data can be returned to participants after data collection or when results are first available. For example, participants may be provided with their interview transcript and asked to verify whether this is a complete and accurate representation of their views.

Participants may then clarify or elaborate on their responses to ensure they align with their views (Shenton, 2004).

This feedback becomes part of data collection and ensures accurate descriptions/ interpretations of phenomena (Mays & Pope, 2000). 

Reflexivity in qualitative research

Reflexivity typically involves examining your own judgments, practices, and belief systems during data collection and analysis. It aims to identify any personal beliefs which may affect the research. 

Reflexivity is essential in qualitative research to ensure methodological transparency and complete reporting. This enables readers to understand how the interaction between the researcher and participant shapes the data.

Depending on the research question and population being researched, factors that need to be considered include the experience of the researcher, how the contact was established and maintained, age, gender, and ethnicity.

These details are important because, in qualitative research, the researcher is a dynamic part of the research process and actively influences the outcome of the research (Boeije, 2014). 

Reflexivity Example

Who you are and your characteristics influence how you collect and analyze data. Here is an example of a reflexivity statement for research on smoking. I am a 30-year-old white female from a middle-class background. I live in the southwest of England and have been educated to master’s level. I have been involved in two research projects on oral health. I have never smoked, but I have witnessed how smoking can cause ill health from my volunteering in a smoking cessation clinic. My research aspirations are to help to develop interventions to help smokers quit.

Establishing Trustworthiness in Qualitative Research

Trustworthiness is a concept used to assess the quality and rigor of qualitative research. Four criteria are used to assess a study’s trustworthiness: credibility, transferability, dependability, and confirmability.

Credibility in Qualitative Research

Credibility refers to how accurately the results represent the reality and viewpoints of the participants.

To establish credibility in research, participants’ views and the researcher’s representation of their views need to align (Tobin & Begley, 2004).

To increase the credibility of findings, researchers may use data source triangulation, investigator triangulation, peer debriefing, or member checking (Lincoln & Guba, 1985). 

Transferability in Qualitative Research

Transferability refers to how generalizable the findings are: whether the findings may be applied to another context, setting, or group (Tobin & Begley, 2004).

Transferability can be enhanced by giving thorough and in-depth descriptions of the research setting, sample, and methods (Nowell et al., 2017). 

Dependability in Qualitative Research

Dependability is the extent to which the study could be replicated under similar conditions and the findings would be consistent.

Researchers can establish dependability using methods such as audit trails so readers can see the research process is logical and traceable (Koch, 1994).

Confirmability in Qualitative Research

Confirmability is concerned with establishing that there is a clear link between the researcher’s interpretations/ findings and the data.

Researchers can achieve confirmability by demonstrating how conclusions and interpretations were arrived at (Nowell et al., 2017).

This enables readers to understand the reasoning behind the decisions made. 

Audit Trails in Qualitative Research

An audit trail provides evidence of the decisions made by the researcher regarding theory, research design, and data collection, as well as the steps they have chosen to manage, analyze, and report data. 

The researcher must provide a clear rationale to demonstrate how conclusions were reached in their study.

A clear description of the research path must be provided to enable readers to trace through the researcher’s logic (Halpren, 1983).

Researchers should maintain records of the raw data, field notes, transcripts, and a reflective journal in order to provide a clear audit trail. 

Discovery of unexpected data

Open-ended questions in qualitative research mean the researcher can probe an interview topic and enable the participant to elaborate on responses in an unrestricted manner.

This allows unexpected data to emerge, which can lead to further research into that topic. 

Flexibility

Data collection and analysis can be modified and adapted to take the research in a different direction if new ideas or patterns emerge in the data.

This enables researchers to investigate new opportunities while firmly maintaining their research goals. 

Naturalistic settings

The behaviors of participants are recorded in real-world settings. Studies that use real-world settings have high ecological validity since participants behave more authentically. 

Limitations

Time-consuming .

Qualitative research results in large amounts of data which often need to be transcribed and analyzed manually.

Even when software is used, transcription can be inaccurate, and using software for analysis can result in many codes which need to be condensed into themes. 

Subjectivity 

The researcher has an integral role in collecting and interpreting qualitative data. Therefore, the conclusions reached are from their perspective and experience.

Consequently, interpretations of data from another researcher may vary greatly. 

Limited generalizability

The aim of qualitative research is to provide a detailed, contextualized understanding of an aspect of the human experience from a relatively small sample size.

Despite rigorous analysis procedures, conclusions drawn cannot be generalized to the wider population since data may be biased or unrepresentative.

Therefore, results are only applicable to a small group of the population. 

Extraneous variables

Qualitative research is often conducted in real-world settings. This may cause results to be unreliable since extraneous variables may affect the data, for example:

  • Situational variables : different environmental conditions may influence participants’ behavior in a study. The random variation in factors (such as noise or lighting) may be difficult to control in real-world settings.
  • Participant characteristics : this includes any characteristics that may influence how a participant answers/ behaves in a study. This may include a participant’s mood, gender, age, ethnicity, sexual identity, IQ, etc.
  • Experimenter effect : experimenter effect refers to how a researcher’s unintentional influence can change the outcome of a study. This occurs when (i) their interactions with participants unintentionally change participants’ behaviors or (ii) due to errors in observation, interpretation, or analysis. 

What sample size should qualitative research be?

The sample size for qualitative studies has been recommended to include a minimum of 12 participants to reach data saturation (Braun, 2013).

Are surveys qualitative or quantitative?

Surveys can be used to gather information from a sample qualitatively or quantitatively. Qualitative surveys use open-ended questions to gather detailed information from a large sample using free text responses.

The use of open-ended questions allows for unrestricted responses where participants use their own words, enabling the collection of more in-depth information than closed-ended questions.

In contrast, quantitative surveys consist of closed-ended questions with multiple-choice answer options. Quantitative surveys are ideal to gather a statistical representation of a population.

What are the ethical considerations of qualitative research?

Before conducting a study, you must think about any risks that could occur and take steps to prevent them. Participant Protection : Researchers must protect participants from physical and mental harm. This means you must not embarrass, frighten, offend, or harm participants. Transparency : Researchers are obligated to clearly communicate how they will collect, store, analyze, use, and share the data. Confidentiality : You need to consider how to maintain the confidentiality and anonymity of participants’ data.

What is triangulation in qualitative research?

Triangulation refers to the use of several approaches in a study to comprehensively understand phenomena. This method helps to increase the validity and credibility of research findings. 

Types of triangulation include method triangulation (using multiple methods to gather data); investigator triangulation (multiple researchers for collecting/ analyzing data), theory triangulation (comparing several theoretical perspectives to explain a phenomenon), and data source triangulation (using data from various times, locations, and people; Carter et al., 2014).

Why is qualitative research important?

Qualitative research allows researchers to describe and explain the social world. The exploratory nature of qualitative research helps to generate hypotheses that can then be tested quantitatively.

In qualitative research, participants are able to express their thoughts, experiences, and feelings without constraint.

Additionally, researchers are able to follow up on participants’ answers in real-time, generating valuable discussion around a topic. This enables researchers to gain a nuanced understanding of phenomena which is difficult to attain using quantitative methods.

What is coding data in qualitative research?

Coding data is a qualitative data analysis strategy in which a section of text is assigned with a label that describes its content.

These labels may be words or phrases which represent important (and recurring) patterns in the data.

This process enables researchers to identify related content across the dataset. Codes can then be used to group similar types of data to generate themes.

What is the difference between qualitative and quantitative research?

Qualitative research involves the collection and analysis of non-numerical data in order to understand experiences and meanings from the participant’s perspective.

This can provide rich, in-depth insights on complicated phenomena. Qualitative data may be collected using interviews, focus groups, or observations.

In contrast, quantitative research involves the collection and analysis of numerical data to measure the frequency, magnitude, or relationships of variables. This can provide objective and reliable evidence that can be generalized to the wider population.

Quantitative data may be collected using closed-ended questionnaires or experiments.

What is trustworthiness in qualitative research?

Trustworthiness is a concept used to assess the quality and rigor of qualitative research. Four criteria are used to assess a study’s trustworthiness: credibility, transferability, dependability, and confirmability. 

Credibility refers to how accurately the results represent the reality and viewpoints of the participants. Transferability refers to whether the findings may be applied to another context, setting, or group.

Dependability is the extent to which the findings are consistent and reliable. Confirmability refers to the objectivity of findings (not influenced by the bias or assumptions of researchers).

What is data saturation in qualitative research?

Data saturation is a methodological principle used to guide the sample size of a qualitative research study.

Data saturation is proposed as a necessary methodological component in qualitative research (Saunders et al., 2018) as it is a vital criterion for discontinuing data collection and/or analysis. 

The intention of data saturation is to find “no new data, no new themes, no new coding, and ability to replicate the study” (Guest et al., 2006). Therefore, enough data has been gathered to make conclusions.

Why is sampling in qualitative research important?

In quantitative research, large sample sizes are used to provide statistically significant quantitative estimates.

This is because quantitative research aims to provide generalizable conclusions that represent populations.

However, the aim of sampling in qualitative research is to gather data that will help the researcher understand the depth, complexity, variation, or context of a phenomenon. The small sample sizes in qualitative studies support the depth of case-oriented analysis.

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Research Method

Home » Qualitative Research – Methods, Analysis Types and Guide

Qualitative Research – Methods, Analysis Types and Guide

Table of Contents

Qualitative Research

Qualitative Research

Qualitative research is a type of research methodology that focuses on exploring and understanding people’s beliefs, attitudes, behaviors, and experiences through the collection and analysis of non-numerical data. It seeks to answer research questions through the examination of subjective data, such as interviews, focus groups, observations, and textual analysis.

Qualitative research aims to uncover the meaning and significance of social phenomena, and it typically involves a more flexible and iterative approach to data collection and analysis compared to quantitative research. Qualitative research is often used in fields such as sociology, anthropology, psychology, and education.

Qualitative Research Methods

Types of Qualitative Research

Qualitative Research Methods are as follows:

One-to-One Interview

This method involves conducting an interview with a single participant to gain a detailed understanding of their experiences, attitudes, and beliefs. One-to-one interviews can be conducted in-person, over the phone, or through video conferencing. The interviewer typically uses open-ended questions to encourage the participant to share their thoughts and feelings. One-to-one interviews are useful for gaining detailed insights into individual experiences.

Focus Groups

This method involves bringing together a group of people to discuss a specific topic in a structured setting. The focus group is led by a moderator who guides the discussion and encourages participants to share their thoughts and opinions. Focus groups are useful for generating ideas and insights, exploring social norms and attitudes, and understanding group dynamics.

Ethnographic Studies

This method involves immersing oneself in a culture or community to gain a deep understanding of its norms, beliefs, and practices. Ethnographic studies typically involve long-term fieldwork and observation, as well as interviews and document analysis. Ethnographic studies are useful for understanding the cultural context of social phenomena and for gaining a holistic understanding of complex social processes.

Text Analysis

This method involves analyzing written or spoken language to identify patterns and themes. Text analysis can be quantitative or qualitative. Qualitative text analysis involves close reading and interpretation of texts to identify recurring themes, concepts, and patterns. Text analysis is useful for understanding media messages, public discourse, and cultural trends.

This method involves an in-depth examination of a single person, group, or event to gain an understanding of complex phenomena. Case studies typically involve a combination of data collection methods, such as interviews, observations, and document analysis, to provide a comprehensive understanding of the case. Case studies are useful for exploring unique or rare cases, and for generating hypotheses for further research.

Process of Observation

This method involves systematically observing and recording behaviors and interactions in natural settings. The observer may take notes, use audio or video recordings, or use other methods to document what they see. Process of observation is useful for understanding social interactions, cultural practices, and the context in which behaviors occur.

Record Keeping

This method involves keeping detailed records of observations, interviews, and other data collected during the research process. Record keeping is essential for ensuring the accuracy and reliability of the data, and for providing a basis for analysis and interpretation.

This method involves collecting data from a large sample of participants through a structured questionnaire. Surveys can be conducted in person, over the phone, through mail, or online. Surveys are useful for collecting data on attitudes, beliefs, and behaviors, and for identifying patterns and trends in a population.

Qualitative data analysis is a process of turning unstructured data into meaningful insights. It involves extracting and organizing information from sources like interviews, focus groups, and surveys. The goal is to understand people’s attitudes, behaviors, and motivations

Qualitative Research Analysis Methods

Qualitative Research analysis methods involve a systematic approach to interpreting and making sense of the data collected in qualitative research. Here are some common qualitative data analysis methods:

Thematic Analysis

This method involves identifying patterns or themes in the data that are relevant to the research question. The researcher reviews the data, identifies keywords or phrases, and groups them into categories or themes. Thematic analysis is useful for identifying patterns across multiple data sources and for generating new insights into the research topic.

Content Analysis

This method involves analyzing the content of written or spoken language to identify key themes or concepts. Content analysis can be quantitative or qualitative. Qualitative content analysis involves close reading and interpretation of texts to identify recurring themes, concepts, and patterns. Content analysis is useful for identifying patterns in media messages, public discourse, and cultural trends.

Discourse Analysis

This method involves analyzing language to understand how it constructs meaning and shapes social interactions. Discourse analysis can involve a variety of methods, such as conversation analysis, critical discourse analysis, and narrative analysis. Discourse analysis is useful for understanding how language shapes social interactions, cultural norms, and power relationships.

Grounded Theory Analysis

This method involves developing a theory or explanation based on the data collected. Grounded theory analysis starts with the data and uses an iterative process of coding and analysis to identify patterns and themes in the data. The theory or explanation that emerges is grounded in the data, rather than preconceived hypotheses. Grounded theory analysis is useful for understanding complex social phenomena and for generating new theoretical insights.

Narrative Analysis

This method involves analyzing the stories or narratives that participants share to gain insights into their experiences, attitudes, and beliefs. Narrative analysis can involve a variety of methods, such as structural analysis, thematic analysis, and discourse analysis. Narrative analysis is useful for understanding how individuals construct their identities, make sense of their experiences, and communicate their values and beliefs.

Phenomenological Analysis

This method involves analyzing how individuals make sense of their experiences and the meanings they attach to them. Phenomenological analysis typically involves in-depth interviews with participants to explore their experiences in detail. Phenomenological analysis is useful for understanding subjective experiences and for developing a rich understanding of human consciousness.

Comparative Analysis

This method involves comparing and contrasting data across different cases or groups to identify similarities and differences. Comparative analysis can be used to identify patterns or themes that are common across multiple cases, as well as to identify unique or distinctive features of individual cases. Comparative analysis is useful for understanding how social phenomena vary across different contexts and groups.

Applications of Qualitative Research

Qualitative research has many applications across different fields and industries. Here are some examples of how qualitative research is used:

  • Market Research: Qualitative research is often used in market research to understand consumer attitudes, behaviors, and preferences. Researchers conduct focus groups and one-on-one interviews with consumers to gather insights into their experiences and perceptions of products and services.
  • Health Care: Qualitative research is used in health care to explore patient experiences and perspectives on health and illness. Researchers conduct in-depth interviews with patients and their families to gather information on their experiences with different health care providers and treatments.
  • Education: Qualitative research is used in education to understand student experiences and to develop effective teaching strategies. Researchers conduct classroom observations and interviews with students and teachers to gather insights into classroom dynamics and instructional practices.
  • Social Work : Qualitative research is used in social work to explore social problems and to develop interventions to address them. Researchers conduct in-depth interviews with individuals and families to understand their experiences with poverty, discrimination, and other social problems.
  • Anthropology : Qualitative research is used in anthropology to understand different cultures and societies. Researchers conduct ethnographic studies and observe and interview members of different cultural groups to gain insights into their beliefs, practices, and social structures.
  • Psychology : Qualitative research is used in psychology to understand human behavior and mental processes. Researchers conduct in-depth interviews with individuals to explore their thoughts, feelings, and experiences.
  • Public Policy : Qualitative research is used in public policy to explore public attitudes and to inform policy decisions. Researchers conduct focus groups and one-on-one interviews with members of the public to gather insights into their perspectives on different policy issues.

How to Conduct Qualitative Research

Here are some general steps for conducting qualitative research:

  • Identify your research question: Qualitative research starts with a research question or set of questions that you want to explore. This question should be focused and specific, but also broad enough to allow for exploration and discovery.
  • Select your research design: There are different types of qualitative research designs, including ethnography, case study, grounded theory, and phenomenology. You should select a design that aligns with your research question and that will allow you to gather the data you need to answer your research question.
  • Recruit participants: Once you have your research question and design, you need to recruit participants. The number of participants you need will depend on your research design and the scope of your research. You can recruit participants through advertisements, social media, or through personal networks.
  • Collect data: There are different methods for collecting qualitative data, including interviews, focus groups, observation, and document analysis. You should select the method or methods that align with your research design and that will allow you to gather the data you need to answer your research question.
  • Analyze data: Once you have collected your data, you need to analyze it. This involves reviewing your data, identifying patterns and themes, and developing codes to organize your data. You can use different software programs to help you analyze your data, or you can do it manually.
  • Interpret data: Once you have analyzed your data, you need to interpret it. This involves making sense of the patterns and themes you have identified, and developing insights and conclusions that answer your research question. You should be guided by your research question and use your data to support your conclusions.
  • Communicate results: Once you have interpreted your data, you need to communicate your results. This can be done through academic papers, presentations, or reports. You should be clear and concise in your communication, and use examples and quotes from your data to support your findings.

Examples of Qualitative Research

Here are some real-time examples of qualitative research:

  • Customer Feedback: A company may conduct qualitative research to understand the feedback and experiences of its customers. This may involve conducting focus groups or one-on-one interviews with customers to gather insights into their attitudes, behaviors, and preferences.
  • Healthcare : A healthcare provider may conduct qualitative research to explore patient experiences and perspectives on health and illness. This may involve conducting in-depth interviews with patients and their families to gather information on their experiences with different health care providers and treatments.
  • Education : An educational institution may conduct qualitative research to understand student experiences and to develop effective teaching strategies. This may involve conducting classroom observations and interviews with students and teachers to gather insights into classroom dynamics and instructional practices.
  • Social Work: A social worker may conduct qualitative research to explore social problems and to develop interventions to address them. This may involve conducting in-depth interviews with individuals and families to understand their experiences with poverty, discrimination, and other social problems.
  • Anthropology : An anthropologist may conduct qualitative research to understand different cultures and societies. This may involve conducting ethnographic studies and observing and interviewing members of different cultural groups to gain insights into their beliefs, practices, and social structures.
  • Psychology : A psychologist may conduct qualitative research to understand human behavior and mental processes. This may involve conducting in-depth interviews with individuals to explore their thoughts, feelings, and experiences.
  • Public Policy: A government agency or non-profit organization may conduct qualitative research to explore public attitudes and to inform policy decisions. This may involve conducting focus groups and one-on-one interviews with members of the public to gather insights into their perspectives on different policy issues.

Purpose of Qualitative Research

The purpose of qualitative research is to explore and understand the subjective experiences, behaviors, and perspectives of individuals or groups in a particular context. Unlike quantitative research, which focuses on numerical data and statistical analysis, qualitative research aims to provide in-depth, descriptive information that can help researchers develop insights and theories about complex social phenomena.

Qualitative research can serve multiple purposes, including:

  • Exploring new or emerging phenomena : Qualitative research can be useful for exploring new or emerging phenomena, such as new technologies or social trends. This type of research can help researchers develop a deeper understanding of these phenomena and identify potential areas for further study.
  • Understanding complex social phenomena : Qualitative research can be useful for exploring complex social phenomena, such as cultural beliefs, social norms, or political processes. This type of research can help researchers develop a more nuanced understanding of these phenomena and identify factors that may influence them.
  • Generating new theories or hypotheses: Qualitative research can be useful for generating new theories or hypotheses about social phenomena. By gathering rich, detailed data about individuals’ experiences and perspectives, researchers can develop insights that may challenge existing theories or lead to new lines of inquiry.
  • Providing context for quantitative data: Qualitative research can be useful for providing context for quantitative data. By gathering qualitative data alongside quantitative data, researchers can develop a more complete understanding of complex social phenomena and identify potential explanations for quantitative findings.

When to use Qualitative Research

Here are some situations where qualitative research may be appropriate:

  • Exploring a new area: If little is known about a particular topic, qualitative research can help to identify key issues, generate hypotheses, and develop new theories.
  • Understanding complex phenomena: Qualitative research can be used to investigate complex social, cultural, or organizational phenomena that are difficult to measure quantitatively.
  • Investigating subjective experiences: Qualitative research is particularly useful for investigating the subjective experiences of individuals or groups, such as their attitudes, beliefs, values, or emotions.
  • Conducting formative research: Qualitative research can be used in the early stages of a research project to develop research questions, identify potential research participants, and refine research methods.
  • Evaluating interventions or programs: Qualitative research can be used to evaluate the effectiveness of interventions or programs by collecting data on participants’ experiences, attitudes, and behaviors.

Characteristics of Qualitative Research

Qualitative research is characterized by several key features, including:

  • Focus on subjective experience: Qualitative research is concerned with understanding the subjective experiences, beliefs, and perspectives of individuals or groups in a particular context. Researchers aim to explore the meanings that people attach to their experiences and to understand the social and cultural factors that shape these meanings.
  • Use of open-ended questions: Qualitative research relies on open-ended questions that allow participants to provide detailed, in-depth responses. Researchers seek to elicit rich, descriptive data that can provide insights into participants’ experiences and perspectives.
  • Sampling-based on purpose and diversity: Qualitative research often involves purposive sampling, in which participants are selected based on specific criteria related to the research question. Researchers may also seek to include participants with diverse experiences and perspectives to capture a range of viewpoints.
  • Data collection through multiple methods: Qualitative research typically involves the use of multiple data collection methods, such as in-depth interviews, focus groups, and observation. This allows researchers to gather rich, detailed data from multiple sources, which can provide a more complete picture of participants’ experiences and perspectives.
  • Inductive data analysis: Qualitative research relies on inductive data analysis, in which researchers develop theories and insights based on the data rather than testing pre-existing hypotheses. Researchers use coding and thematic analysis to identify patterns and themes in the data and to develop theories and explanations based on these patterns.
  • Emphasis on researcher reflexivity: Qualitative research recognizes the importance of the researcher’s role in shaping the research process and outcomes. Researchers are encouraged to reflect on their own biases and assumptions and to be transparent about their role in the research process.

Advantages of Qualitative Research

Qualitative research offers several advantages over other research methods, including:

  • Depth and detail: Qualitative research allows researchers to gather rich, detailed data that provides a deeper understanding of complex social phenomena. Through in-depth interviews, focus groups, and observation, researchers can gather detailed information about participants’ experiences and perspectives that may be missed by other research methods.
  • Flexibility : Qualitative research is a flexible approach that allows researchers to adapt their methods to the research question and context. Researchers can adjust their research methods in real-time to gather more information or explore unexpected findings.
  • Contextual understanding: Qualitative research is well-suited to exploring the social and cultural context in which individuals or groups are situated. Researchers can gather information about cultural norms, social structures, and historical events that may influence participants’ experiences and perspectives.
  • Participant perspective : Qualitative research prioritizes the perspective of participants, allowing researchers to explore subjective experiences and understand the meanings that participants attach to their experiences.
  • Theory development: Qualitative research can contribute to the development of new theories and insights about complex social phenomena. By gathering rich, detailed data and using inductive data analysis, researchers can develop new theories and explanations that may challenge existing understandings.
  • Validity : Qualitative research can offer high validity by using multiple data collection methods, purposive and diverse sampling, and researcher reflexivity. This can help ensure that findings are credible and trustworthy.

Limitations of Qualitative Research

Qualitative research also has some limitations, including:

  • Subjectivity : Qualitative research relies on the subjective interpretation of researchers, which can introduce bias into the research process. The researcher’s perspective, beliefs, and experiences can influence the way data is collected, analyzed, and interpreted.
  • Limited generalizability: Qualitative research typically involves small, purposive samples that may not be representative of larger populations. This limits the generalizability of findings to other contexts or populations.
  • Time-consuming: Qualitative research can be a time-consuming process, requiring significant resources for data collection, analysis, and interpretation.
  • Resource-intensive: Qualitative research may require more resources than other research methods, including specialized training for researchers, specialized software for data analysis, and transcription services.
  • Limited reliability: Qualitative research may be less reliable than quantitative research, as it relies on the subjective interpretation of researchers. This can make it difficult to replicate findings or compare results across different studies.
  • Ethics and confidentiality: Qualitative research involves collecting sensitive information from participants, which raises ethical concerns about confidentiality and informed consent. Researchers must take care to protect the privacy and confidentiality of participants and obtain informed consent.

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What is Qualitative in Qualitative Research

Patrik aspers.

1 Department of Sociology, Uppsala University, Uppsala, Sweden

2 Seminar for Sociology, Universität St. Gallen, St. Gallen, Switzerland

3 Department of Media and Social Sciences, University of Stavanger, Stavanger, Norway

What is qualitative research? If we look for a precise definition of qualitative research, and specifically for one that addresses its distinctive feature of being “qualitative,” the literature is meager. In this article we systematically search, identify and analyze a sample of 89 sources using or attempting to define the term “qualitative.” Then, drawing on ideas we find scattered across existing work, and based on Becker’s classic study of marijuana consumption, we formulate and illustrate a definition that tries to capture its core elements. We define qualitative research as an iterative process in which improved understanding to the scientific community is achieved by making new significant distinctions resulting from getting closer to the phenomenon studied. This formulation is developed as a tool to help improve research designs while stressing that a qualitative dimension is present in quantitative work as well. Additionally, it can facilitate teaching, communication between researchers, diminish the gap between qualitative and quantitative researchers, help to address critiques of qualitative methods, and be used as a standard of evaluation of qualitative research.

If we assume that there is something called qualitative research, what exactly is this qualitative feature? And how could we evaluate qualitative research as good or not? Is it fundamentally different from quantitative research? In practice, most active qualitative researchers working with empirical material intuitively know what is involved in doing qualitative research, yet perhaps surprisingly, a clear definition addressing its key feature is still missing.

To address the question of what is qualitative we turn to the accounts of “qualitative research” in textbooks and also in empirical work. In his classic, explorative, interview study of deviance Howard Becker ( 1963 ) asks ‘How does one become a marijuana user?’ In contrast to pre-dispositional and psychological-individualistic theories of deviant behavior, Becker’s inherently social explanation contends that becoming a user of this substance is the result of a three-phase sequential learning process. First, potential users need to learn how to smoke it properly to produce the “correct” effects. If not, they are likely to stop experimenting with it. Second, they need to discover the effects associated with it; in other words, to get “high,” individuals not only have to experience what the drug does, but also to become aware that those sensations are related to using it. Third, they require learning to savor the feelings related to its consumption – to develop an acquired taste. Becker, who played music himself, gets close to the phenomenon by observing, taking part, and by talking to people consuming the drug: “half of the fifty interviews were conducted with musicians, the other half covered a wide range of people, including laborers, machinists, and people in the professions” (Becker 1963 :56).

Another central aspect derived through the common-to-all-research interplay between induction and deduction (Becker 2017 ), is that during the course of his research Becker adds scientifically meaningful new distinctions in the form of three phases—distinctions, or findings if you will, that strongly affect the course of his research: its focus, the material that he collects, and which eventually impact his findings. Each phase typically unfolds through social interaction, and often with input from experienced users in “a sequence of social experiences during which the person acquires a conception of the meaning of the behavior, and perceptions and judgments of objects and situations, all of which make the activity possible and desirable” (Becker 1963 :235). In this study the increased understanding of smoking dope is a result of a combination of the meaning of the actors, and the conceptual distinctions that Becker introduces based on the views expressed by his respondents. Understanding is the result of research and is due to an iterative process in which data, concepts and evidence are connected with one another (Becker 2017 ).

Indeed, there are many definitions of qualitative research, but if we look for a definition that addresses its distinctive feature of being “qualitative,” the literature across the broad field of social science is meager. The main reason behind this article lies in the paradox, which, to put it bluntly, is that researchers act as if they know what it is, but they cannot formulate a coherent definition. Sociologists and others will of course continue to conduct good studies that show the relevance and value of qualitative research addressing scientific and practical problems in society. However, our paper is grounded in the idea that providing a clear definition will help us improve the work that we do. Among researchers who practice qualitative research there is clearly much knowledge. We suggest that a definition makes this knowledge more explicit. If the first rationale for writing this paper refers to the “internal” aim of improving qualitative research, the second refers to the increased “external” pressure that especially many qualitative researchers feel; pressure that comes both from society as well as from other scientific approaches. There is a strong core in qualitative research, and leading researchers tend to agree on what it is and how it is done. Our critique is not directed at the practice of qualitative research, but we do claim that the type of systematic work we do has not yet been done, and that it is useful to improve the field and its status in relation to quantitative research.

The literature on the “internal” aim of improving, or at least clarifying qualitative research is large, and we do not claim to be the first to notice the vagueness of the term “qualitative” (Strauss and Corbin 1998 ). Also, others have noted that there is no single definition of it (Long and Godfrey 2004 :182), that there are many different views on qualitative research (Denzin and Lincoln 2003 :11; Jovanović 2011 :3), and that more generally, we need to define its meaning (Best 2004 :54). Strauss and Corbin ( 1998 ), for example, as well as Nelson et al. (1992:2 cited in Denzin and Lincoln 2003 :11), and Flick ( 2007 :ix–x), have recognized that the term is problematic: “Actually, the term ‘qualitative research’ is confusing because it can mean different things to different people” (Strauss and Corbin 1998 :10–11). Hammersley has discussed the possibility of addressing the problem, but states that “the task of providing an account of the distinctive features of qualitative research is far from straightforward” ( 2013 :2). This confusion, as he has recently further argued (Hammersley 2018 ), is also salient in relation to ethnography where different philosophical and methodological approaches lead to a lack of agreement about what it means.

Others (e.g. Hammersley 2018 ; Fine and Hancock 2017 ) have also identified the treat to qualitative research that comes from external forces, seen from the point of view of “qualitative research.” This threat can be further divided into that which comes from inside academia, such as the critique voiced by “quantitative research” and outside of academia, including, for example, New Public Management. Hammersley ( 2018 ), zooming in on one type of qualitative research, ethnography, has argued that it is under treat. Similarly to Fine ( 2003 ), and before him Gans ( 1999 ), he writes that ethnography’ has acquired a range of meanings, and comes in many different versions, these often reflecting sharply divergent epistemological orientations. And already more than twenty years ago while reviewing Denzin and Lincoln’ s Handbook of Qualitative Methods Fine argued:

While this increasing centrality [of qualitative research] might lead one to believe that consensual standards have developed, this belief would be misleading. As the methodology becomes more widely accepted, querulous challengers have raised fundamental questions that collectively have undercut the traditional models of how qualitative research is to be fashioned and presented (1995:417).

According to Hammersley, there are today “serious treats to the practice of ethnographic work, on almost any definition” ( 2018 :1). He lists five external treats: (1) that social research must be accountable and able to show its impact on society; (2) the current emphasis on “big data” and the emphasis on quantitative data and evidence; (3) the labor market pressure in academia that leaves less time for fieldwork (see also Fine and Hancock 2017 ); (4) problems of access to fields; and (5) the increased ethical scrutiny of projects, to which ethnography is particularly exposed. Hammersley discusses some more or less insufficient existing definitions of ethnography.

The current situation, as Hammersley and others note—and in relation not only to ethnography but also qualitative research in general, and as our empirical study shows—is not just unsatisfactory, it may even be harmful for the entire field of qualitative research, and does not help social science at large. We suggest that the lack of clarity of qualitative research is a real problem that must be addressed.

Towards a Definition of Qualitative Research

Seen in an historical light, what is today called qualitative, or sometimes ethnographic, interpretative research – or a number of other terms – has more or less always existed. At the time the founders of sociology – Simmel, Weber, Durkheim and, before them, Marx – were writing, and during the era of the Methodenstreit (“dispute about methods”) in which the German historical school emphasized scientific methods (cf. Swedberg 1990 ), we can at least speak of qualitative forerunners.

Perhaps the most extended discussion of what later became known as qualitative methods in a classic work is Bronisław Malinowski’s ( 1922 ) Argonauts in the Western Pacific , although even this study does not explicitly address the meaning of “qualitative.” In Weber’s ([1921–-22] 1978) work we find a tension between scientific explanations that are based on observation and quantification and interpretative research (see also Lazarsfeld and Barton 1982 ).

If we look through major sociology journals like the American Sociological Review , American Journal of Sociology , or Social Forces we will not find the term qualitative sociology before the 1970s. And certainly before then much of what we consider qualitative classics in sociology, like Becker’ study ( 1963 ), had already been produced. Indeed, the Chicago School often combined qualitative and quantitative data within the same study (Fine 1995 ). Our point being that before a disciplinary self-awareness the term quantitative preceded qualitative, and the articulation of the former was a political move to claim scientific status (Denzin and Lincoln 2005 ). In the US the World War II seem to have sparked a critique of sociological work, including “qualitative work,” that did not follow the scientific canon (Rawls 2018 ), which was underpinned by a scientifically oriented and value free philosophy of science. As a result the attempts and practice of integrating qualitative and quantitative sociology at Chicago lost ground to sociology that was more oriented to surveys and quantitative work at Columbia under Merton-Lazarsfeld. The quantitative tradition was also able to present textbooks (Lundberg 1951 ) that facilitated the use this approach and its “methods.” The practices of the qualitative tradition, by and large, remained tacit or was part of the mentoring transferred from the renowned masters to their students.

This glimpse into history leads us back to the lack of a coherent account condensed in a definition of qualitative research. Many of the attempts to define the term do not meet the requirements of a proper definition: A definition should be clear, avoid tautology, demarcate its domain in relation to the environment, and ideally only use words in its definiens that themselves are not in need of definition (Hempel 1966 ). A definition can enhance precision and thus clarity by identifying the core of the phenomenon. Preferably, a definition should be short. The typical definition we have found, however, is an ostensive definition, which indicates what qualitative research is about without informing us about what it actually is :

Qualitative research is multimethod in focus, involving an interpretative, naturalistic approach to its subject matter. This means that qualitative researchers study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them. Qualitative research involves the studied use and collection of a variety of empirical materials – case study, personal experience, introspective, life story, interview, observational, historical, interactional, and visual texts – that describe routine and problematic moments and meanings in individuals’ lives. (Denzin and Lincoln 2005 :2)

Flick claims that the label “qualitative research” is indeed used as an umbrella for a number of approaches ( 2007 :2–4; 2002 :6), and it is not difficult to identify research fitting this designation. Moreover, whatever it is, it has grown dramatically over the past five decades. In addition, courses have been developed, methods have flourished, arguments about its future have been advanced (for example, Denzin and Lincoln 1994) and criticized (for example, Snow and Morrill 1995 ), and dedicated journals and books have mushroomed. Most social scientists have a clear idea of research and how it differs from journalism, politics and other activities. But the question of what is qualitative in qualitative research is either eluded or eschewed.

We maintain that this lacuna hinders systematic knowledge production based on qualitative research. Paul Lazarsfeld noted the lack of “codification” as early as 1955 when he reviewed 100 qualitative studies in order to offer a codification of the practices (Lazarsfeld and Barton 1982 :239). Since then many texts on “qualitative research” and its methods have been published, including recent attempts (Goertz and Mahoney 2012 ) similar to Lazarsfeld’s. These studies have tried to extract what is qualitative by looking at the large number of empirical “qualitative” studies. Our novel strategy complements these endeavors by taking another approach and looking at the attempts to codify these practices in the form of a definition, as well as to a minor extent take Becker’s study as an exemplar of what qualitative researchers actually do, and what the characteristic of being ‘qualitative’ denotes and implies. We claim that qualitative researchers, if there is such a thing as “qualitative research,” should be able to codify their practices in a condensed, yet general way expressed in language.

Lingering problems of “generalizability” and “how many cases do I need” (Small 2009 ) are blocking advancement – in this line of work qualitative approaches are said to differ considerably from quantitative ones, while some of the former unsuccessfully mimic principles related to the latter (Small 2009 ). Additionally, quantitative researchers sometimes unfairly criticize the first based on their own quality criteria. Scholars like Goertz and Mahoney ( 2012 ) have successfully focused on the different norms and practices beyond what they argue are essentially two different cultures: those working with either qualitative or quantitative methods. Instead, similarly to Becker ( 2017 ) who has recently questioned the usefulness of the distinction between qualitative and quantitative research, we focus on similarities.

The current situation also impedes both students and researchers in focusing their studies and understanding each other’s work (Lazarsfeld and Barton 1982 :239). A third consequence is providing an opening for critiques by scholars operating within different traditions (Valsiner 2000 :101). A fourth issue is that the “implicit use of methods in qualitative research makes the field far less standardized than the quantitative paradigm” (Goertz and Mahoney 2012 :9). Relatedly, the National Science Foundation in the US organized two workshops in 2004 and 2005 to address the scientific foundations of qualitative research involving strategies to improve it and to develop standards of evaluation in qualitative research. However, a specific focus on its distinguishing feature of being “qualitative” while being implicitly acknowledged, was discussed only briefly (for example, Best 2004 ).

In 2014 a theme issue was published in this journal on “Methods, Materials, and Meanings: Designing Cultural Analysis,” discussing central issues in (cultural) qualitative research (Berezin 2014 ; Biernacki 2014 ; Glaeser 2014 ; Lamont and Swidler 2014 ; Spillman 2014). We agree with many of the arguments put forward, such as the risk of methodological tribalism, and that we should not waste energy on debating methods separated from research questions. Nonetheless, a clarification of the relation to what is called “quantitative research” is of outmost importance to avoid misunderstandings and misguided debates between “qualitative” and “quantitative” researchers. Our strategy means that researchers, “qualitative” or “quantitative” they may be, in their actual practice may combine qualitative work and quantitative work.

In this article we accomplish three tasks. First, we systematically survey the literature for meanings of qualitative research by looking at how researchers have defined it. Drawing upon existing knowledge we find that the different meanings and ideas of qualitative research are not yet coherently integrated into one satisfactory definition. Next, we advance our contribution by offering a definition of qualitative research and illustrate its meaning and use partially by expanding on the brief example introduced earlier related to Becker’s work ( 1963 ). We offer a systematic analysis of central themes of what researchers consider to be the core of “qualitative,” regardless of style of work. These themes – which we summarize in terms of four keywords: distinction, process, closeness, improved understanding – constitute part of our literature review, in which each one appears, sometimes with others, but never all in the same definition. They serve as the foundation of our contribution. Our categories are overlapping. Their use is primarily to organize the large amount of definitions we have identified and analyzed, and not necessarily to draw a clear distinction between them. Finally, we continue the elaboration discussed above on the advantages of a clear definition of qualitative research.

In a hermeneutic fashion we propose that there is something meaningful that deserves to be labelled “qualitative research” (Gadamer 1990 ). To approach the question “What is qualitative in qualitative research?” we have surveyed the literature. In conducting our survey we first traced the word’s etymology in dictionaries, encyclopedias, handbooks of the social sciences and of methods and textbooks, mainly in English, which is common to methodology courses. It should be noted that we have zoomed in on sociology and its literature. This discipline has been the site of the largest debate and development of methods that can be called “qualitative,” which suggests that this field should be examined in great detail.

In an ideal situation we should expect that one good definition, or at least some common ideas, would have emerged over the years. This common core of qualitative research should be so accepted that it would appear in at least some textbooks. Since this is not what we found, we decided to pursue an inductive approach to capture maximal variation in the field of qualitative research; we searched in a selection of handbooks, textbooks, book chapters, and books, to which we added the analysis of journal articles. Our sample comprises a total of 89 references.

In practice we focused on the discipline that has had a clear discussion of methods, namely sociology. We also conducted a broad search in the JSTOR database to identify scholarly sociology articles published between 1998 and 2017 in English with a focus on defining or explaining qualitative research. We specifically zoom in on this time frame because we would have expect that this more mature period would have produced clear discussions on the meaning of qualitative research. To find these articles we combined a number of keywords to search the content and/or the title: qualitative (which was always included), definition, empirical, research, methodology, studies, fieldwork, interview and observation .

As a second phase of our research we searched within nine major sociological journals ( American Journal of Sociology , Sociological Theory , American Sociological Review , Contemporary Sociology , Sociological Forum , Sociological Theory , Qualitative Research , Qualitative Sociology and Qualitative Sociology Review ) for articles also published during the past 19 years (1998–2017) that had the term “qualitative” in the title and attempted to define qualitative research.

Lastly we picked two additional journals, Qualitative Research and Qualitative Sociology , in which we could expect to find texts addressing the notion of “qualitative.” From Qualitative Research we chose Volume 14, Issue 6, December 2014, and from Qualitative Sociology we chose Volume 36, Issue 2, June 2017. Within each of these we selected the first article; then we picked the second article of three prior issues. Again we went back another three issues and investigated article number three. Finally we went back another three issues and perused article number four. This selection criteria was used to get a manageable sample for the analysis.

The coding process of the 89 references we gathered in our selected review began soon after the first round of material was gathered, and we reduced the complexity created by our maximum variation sampling (Snow and Anderson 1993 :22) to four different categories within which questions on the nature and properties of qualitative research were discussed. We call them: Qualitative and Quantitative Research, Qualitative Research, Fieldwork, and Grounded Theory. This – which may appear as an illogical grouping – merely reflects the “context” in which the matter of “qualitative” is discussed. If the selection process of the material – books and articles – was informed by pre-knowledge, we used an inductive strategy to code the material. When studying our material, we identified four central notions related to “qualitative” that appear in various combinations in the literature which indicate what is the core of qualitative research. We have labeled them: “distinctions”, “process,” “closeness,” and “improved understanding.” During the research process the categories and notions were improved, refined, changed, and reordered. The coding ended when a sense of saturation in the material arose. In the presentation below all quotations and references come from our empirical material of texts on qualitative research.

Analysis – What is Qualitative Research?

In this section we describe the four categories we identified in the coding, how they differently discuss qualitative research, as well as their overall content. Some salient quotations are selected to represent the type of text sorted under each of the four categories. What we present are examples from the literature.

Qualitative and Quantitative

This analytic category comprises quotations comparing qualitative and quantitative research, a distinction that is frequently used (Brown 2010 :231); in effect this is a conceptual pair that structures the discussion and that may be associated with opposing interests. While the general goal of quantitative and qualitative research is the same – to understand the world better – their methodologies and focus in certain respects differ substantially (Becker 1966 :55). Quantity refers to that property of something that can be determined by measurement. In a dictionary of Statistics and Methodology we find that “(a) When referring to *variables, ‘qualitative’ is another term for *categorical or *nominal. (b) When speaking of kinds of research, ‘qualitative’ refers to studies of subjects that are hard to quantify, such as art history. Qualitative research tends to be a residual category for almost any kind of non-quantitative research” (Stiles 1998:183). But it should be obvious that one could employ a quantitative approach when studying, for example, art history.

The same dictionary states that quantitative is “said of variables or research that can be handled numerically, usually (too sharply) contrasted with *qualitative variables and research” (Stiles 1998:184). From a qualitative perspective “quantitative research” is about numbers and counting, and from a quantitative perspective qualitative research is everything that is not about numbers. But this does not say much about what is “qualitative.” If we turn to encyclopedias we find that in the 1932 edition of the Encyclopedia of the Social Sciences there is no mention of “qualitative.” In the Encyclopedia from 1968 we can read:

Qualitative Analysis. For methods of obtaining, analyzing, and describing data, see [the various entries:] CONTENT ANALYSIS; COUNTED DATA; EVALUATION RESEARCH, FIELD WORK; GRAPHIC PRESENTATION; HISTORIOGRAPHY, especially the article on THE RHETORIC OF HISTORY; INTERVIEWING; OBSERVATION; PERSONALITY MEASUREMENT; PROJECTIVE METHODS; PSYCHOANALYSIS, article on EXPERIMENTAL METHODS; SURVEY ANALYSIS, TABULAR PRESENTATION; TYPOLOGIES. (Vol. 13:225)

Some, like Alford, divide researchers into methodologists or, in his words, “quantitative and qualitative specialists” (Alford 1998 :12). Qualitative research uses a variety of methods, such as intensive interviews or in-depth analysis of historical materials, and it is concerned with a comprehensive account of some event or unit (King et al. 1994 :4). Like quantitative research it can be utilized to study a variety of issues, but it tends to focus on meanings and motivations that underlie cultural symbols, personal experiences, phenomena and detailed understanding of processes in the social world. In short, qualitative research centers on understanding processes, experiences, and the meanings people assign to things (Kalof et al. 2008 :79).

Others simply say that qualitative methods are inherently unscientific (Jovanović 2011 :19). Hood, for instance, argues that words are intrinsically less precise than numbers, and that they are therefore more prone to subjective analysis, leading to biased results (Hood 2006 :219). Qualitative methodologies have raised concerns over the limitations of quantitative templates (Brady et al. 2004 :4). Scholars such as King et al. ( 1994 ), for instance, argue that non-statistical research can produce more reliable results if researchers pay attention to the rules of scientific inference commonly stated in quantitative research. Also, researchers such as Becker ( 1966 :59; 1970 :42–43) have asserted that, if conducted properly, qualitative research and in particular ethnographic field methods, can lead to more accurate results than quantitative studies, in particular, survey research and laboratory experiments.

Some researchers, such as Kalof, Dan, and Dietz ( 2008 :79) claim that the boundaries between the two approaches are becoming blurred, and Small ( 2009 ) argues that currently much qualitative research (especially in North America) tries unsuccessfully and unnecessarily to emulate quantitative standards. For others, qualitative research tends to be more humanistic and discursive (King et al. 1994 :4). Ragin ( 1994 ), and similarly also Becker, ( 1996 :53), Marchel and Owens ( 2007 :303) think that the main distinction between the two styles is overstated and does not rest on the simple dichotomy of “numbers versus words” (Ragin 1994 :xii). Some claim that quantitative data can be utilized to discover associations, but in order to unveil cause and effect a complex research design involving the use of qualitative approaches needs to be devised (Gilbert 2009 :35). Consequently, qualitative data are useful for understanding the nuances lying beyond those processes as they unfold (Gilbert 2009 :35). Others contend that qualitative research is particularly well suited both to identify causality and to uncover fine descriptive distinctions (Fine and Hallett 2014 ; Lichterman and Isaac Reed 2014 ; Katz 2015 ).

There are other ways to separate these two traditions, including normative statements about what qualitative research should be (that is, better or worse than quantitative approaches, concerned with scientific approaches to societal change or vice versa; Snow and Morrill 1995 ; Denzin and Lincoln 2005 ), or whether it should develop falsifiable statements; Best 2004 ).

We propose that quantitative research is largely concerned with pre-determined variables (Small 2008 ); the analysis concerns the relations between variables. These categories are primarily not questioned in the study, only their frequency or degree, or the correlations between them (cf. Franzosi 2016 ). If a researcher studies wage differences between women and men, he or she works with given categories: x number of men are compared with y number of women, with a certain wage attributed to each person. The idea is not to move beyond the given categories of wage, men and women; they are the starting point as well as the end point, and undergo no “qualitative change.” Qualitative research, in contrast, investigates relations between categories that are themselves subject to change in the research process. Returning to Becker’s study ( 1963 ), we see that he questioned pre-dispositional theories of deviant behavior working with pre-determined variables such as an individual’s combination of personal qualities or emotional problems. His take, in contrast, was to understand marijuana consumption by developing “variables” as part of the investigation. Thereby he presented new variables, or as we would say today, theoretical concepts, but which are grounded in the empirical material.

Qualitative Research

This category contains quotations that refer to descriptions of qualitative research without making comparisons with quantitative research. Researchers such as Denzin and Lincoln, who have written a series of influential handbooks on qualitative methods (1994; Denzin and Lincoln 2003 ; 2005 ), citing Nelson et al. (1992:4), argue that because qualitative research is “interdisciplinary, transdisciplinary, and sometimes counterdisciplinary” it is difficult to derive one single definition of it (Jovanović 2011 :3). According to them, in fact, “the field” is “many things at the same time,” involving contradictions, tensions over its focus, methods, and how to derive interpretations and findings ( 2003 : 11). Similarly, others, such as Flick ( 2007 :ix–x) contend that agreeing on an accepted definition has increasingly become problematic, and that qualitative research has possibly matured different identities. However, Best holds that “the proliferation of many sorts of activities under the label of qualitative sociology threatens to confuse our discussions” ( 2004 :54). Atkinson’s position is more definite: “the current state of qualitative research and research methods is confused” ( 2005 :3–4).

Qualitative research is about interpretation (Blumer 1969 ; Strauss and Corbin 1998 ; Denzin and Lincoln 2003 ), or Verstehen [understanding] (Frankfort-Nachmias and Nachmias 1996 ). It is “multi-method,” involving the collection and use of a variety of empirical materials (Denzin and Lincoln 1998; Silverman 2013 ) and approaches (Silverman 2005 ; Flick 2007 ). It focuses not only on the objective nature of behavior but also on its subjective meanings: individuals’ own accounts of their attitudes, motivations, behavior (McIntyre 2005 :127; Creswell 2009 ), events and situations (Bryman 1989) – what people say and do in specific places and institutions (Goodwin and Horowitz 2002 :35–36) in social and temporal contexts (Morrill and Fine 1997). For this reason, following Weber ([1921-22] 1978), it can be described as an interpretative science (McIntyre 2005 :127). But could quantitative research also be concerned with these questions? Also, as pointed out below, does all qualitative research focus on subjective meaning, as some scholars suggest?

Others also distinguish qualitative research by claiming that it collects data using a naturalistic approach (Denzin and Lincoln 2005 :2; Creswell 2009 ), focusing on the meaning actors ascribe to their actions. But again, does all qualitative research need to be collected in situ? And does qualitative research have to be inherently concerned with meaning? Flick ( 2007 ), referring to Denzin and Lincoln ( 2005 ), mentions conversation analysis as an example of qualitative research that is not concerned with the meanings people bring to a situation, but rather with the formal organization of talk. Still others, such as Ragin ( 1994 :85), note that qualitative research is often (especially early on in the project, we would add) less structured than other kinds of social research – a characteristic connected to its flexibility and that can lead both to potentially better, but also worse results. But is this not a feature of this type of research, rather than a defining description of its essence? Wouldn’t this comment also apply, albeit to varying degrees, to quantitative research?

In addition, Strauss ( 2003 ), along with others, such as Alvesson and Kärreman ( 2011 :10–76), argue that qualitative researchers struggle to capture and represent complex phenomena partially because they tend to collect a large amount of data. While his analysis is correct at some points – “It is necessary to do detailed, intensive, microscopic examination of the data in order to bring out the amazing complexity of what lies in, behind, and beyond those data” (Strauss 2003 :10) – much of his analysis concerns the supposed focus of qualitative research and its challenges, rather than exactly what it is about. But even in this instance we would make a weak case arguing that these are strictly the defining features of qualitative research. Some researchers seem to focus on the approach or the methods used, or even on the way material is analyzed. Several researchers stress the naturalistic assumption of investigating the world, suggesting that meaning and interpretation appear to be a core matter of qualitative research.

We can also see that in this category there is no consensus about specific qualitative methods nor about qualitative data. Many emphasize interpretation, but quantitative research, too, involves interpretation; the results of a regression analysis, for example, certainly have to be interpreted, and the form of meta-analysis that factor analysis provides indeed requires interpretation However, there is no interpretation of quantitative raw data, i.e., numbers in tables. One common thread is that qualitative researchers have to get to grips with their data in order to understand what is being studied in great detail, irrespective of the type of empirical material that is being analyzed. This observation is connected to the fact that qualitative researchers routinely make several adjustments of focus and research design as their studies progress, in many cases until the very end of the project (Kalof et al. 2008 ). If you, like Becker, do not start out with a detailed theory, adjustments such as the emergence and refinement of research questions will occur during the research process. We have thus found a number of useful reflections about qualitative research scattered across different sources, but none of them effectively describe the defining characteristics of this approach.

Although qualitative research does not appear to be defined in terms of a specific method, it is certainly common that fieldwork, i.e., research that entails that the researcher spends considerable time in the field that is studied and use the knowledge gained as data, is seen as emblematic of or even identical to qualitative research. But because we understand that fieldwork tends to focus primarily on the collection and analysis of qualitative data, we expected to find within it discussions on the meaning of “qualitative.” But, again, this was not the case.

Instead, we found material on the history of this approach (for example, Frankfort-Nachmias and Nachmias 1996 ; Atkinson et al. 2001), including how it has changed; for example, by adopting a more self-reflexive practice (Heyl 2001), as well as the different nomenclature that has been adopted, such as fieldwork, ethnography, qualitative research, naturalistic research, participant observation and so on (for example, Lofland et al. 2006 ; Gans 1999 ).

We retrieved definitions of ethnography, such as “the study of people acting in the natural courses of their daily lives,” involving a “resocialization of the researcher” (Emerson 1988 :1) through intense immersion in others’ social worlds (see also examples in Hammersley 2018 ). This may be accomplished by direct observation and also participation (Neuman 2007 :276), although others, such as Denzin ( 1970 :185), have long recognized other types of observation, including non-participant (“fly on the wall”). In this category we have also isolated claims and opposing views, arguing that this type of research is distinguished primarily by where it is conducted (natural settings) (Hughes 1971:496), and how it is carried out (a variety of methods are applied) or, for some most importantly, by involving an active, empathetic immersion in those being studied (Emerson 1988 :2). We also retrieved descriptions of the goals it attends in relation to how it is taught (understanding subjective meanings of the people studied, primarily develop theory, or contribute to social change) (see for example, Corte and Irwin 2017 ; Frankfort-Nachmias and Nachmias 1996 :281; Trier-Bieniek 2012 :639) by collecting the richest possible data (Lofland et al. 2006 ) to derive “thick descriptions” (Geertz 1973 ), and/or to aim at theoretical statements of general scope and applicability (for example, Emerson 1988 ; Fine 2003 ). We have identified guidelines on how to evaluate it (for example Becker 1996 ; Lamont 2004 ) and have retrieved instructions on how it should be conducted (for example, Lofland et al. 2006 ). For instance, analysis should take place while the data gathering unfolds (Emerson 1988 ; Hammersley and Atkinson 2007 ; Lofland et al. 2006 ), observations should be of long duration (Becker 1970 :54; Goffman 1989 ), and data should be of high quantity (Becker 1970 :52–53), as well as other questionable distinctions between fieldwork and other methods:

Field studies differ from other methods of research in that the researcher performs the task of selecting topics, decides what questions to ask, and forges interest in the course of the research itself . This is in sharp contrast to many ‘theory-driven’ and ‘hypothesis-testing’ methods. (Lofland and Lofland 1995 :5)

But could not, for example, a strictly interview-based study be carried out with the same amount of flexibility, such as sequential interviewing (for example, Small 2009 )? Once again, are quantitative approaches really as inflexible as some qualitative researchers think? Moreover, this category stresses the role of the actors’ meaning, which requires knowledge and close interaction with people, their practices and their lifeworld.

It is clear that field studies – which are seen by some as the “gold standard” of qualitative research – are nonetheless only one way of doing qualitative research. There are other methods, but it is not clear why some are more qualitative than others, or why they are better or worse. Fieldwork is characterized by interaction with the field (the material) and understanding of the phenomenon that is being studied. In Becker’s case, he had general experience from fields in which marihuana was used, based on which he did interviews with actual users in several fields.

Grounded Theory

Another major category we identified in our sample is Grounded Theory. We found descriptions of it most clearly in Glaser and Strauss’ ([1967] 2010 ) original articulation, Strauss and Corbin ( 1998 ) and Charmaz ( 2006 ), as well as many other accounts of what it is for: generating and testing theory (Strauss 2003 :xi). We identified explanations of how this task can be accomplished – such as through two main procedures: constant comparison and theoretical sampling (Emerson 1998:96), and how using it has helped researchers to “think differently” (for example, Strauss and Corbin 1998 :1). We also read descriptions of its main traits, what it entails and fosters – for instance, an exceptional flexibility, an inductive approach (Strauss and Corbin 1998 :31–33; 1990; Esterberg 2002 :7), an ability to step back and critically analyze situations, recognize tendencies towards bias, think abstractly and be open to criticism, enhance sensitivity towards the words and actions of respondents, and develop a sense of absorption and devotion to the research process (Strauss and Corbin 1998 :5–6). Accordingly, we identified discussions of the value of triangulating different methods (both using and not using grounded theory), including quantitative ones, and theories to achieve theoretical development (most comprehensively in Denzin 1970 ; Strauss and Corbin 1998 ; Timmermans and Tavory 2012 ). We have also located arguments about how its practice helps to systematize data collection, analysis and presentation of results (Glaser and Strauss [1967] 2010 :16).

Grounded theory offers a systematic approach which requires researchers to get close to the field; closeness is a requirement of identifying questions and developing new concepts or making further distinctions with regard to old concepts. In contrast to other qualitative approaches, grounded theory emphasizes the detailed coding process, and the numerous fine-tuned distinctions that the researcher makes during the process. Within this category, too, we could not find a satisfying discussion of the meaning of qualitative research.

Defining Qualitative Research

In sum, our analysis shows that some notions reappear in the discussion of qualitative research, such as understanding, interpretation, “getting close” and making distinctions. These notions capture aspects of what we think is “qualitative.” However, a comprehensive definition that is useful and that can further develop the field is lacking, and not even a clear picture of its essential elements appears. In other words no definition emerges from our data, and in our research process we have moved back and forth between our empirical data and the attempt to present a definition. Our concrete strategy, as stated above, is to relate qualitative and quantitative research, or more specifically, qualitative and quantitative work. We use an ideal-typical notion of quantitative research which relies on taken for granted and numbered variables. This means that the data consists of variables on different scales, such as ordinal, but frequently ratio and absolute scales, and the representation of the numbers to the variables, i.e. the justification of the assignment of numbers to object or phenomenon, are not questioned, though the validity may be questioned. In this section we return to the notion of quality and try to clarify it while presenting our contribution.

Broadly, research refers to the activity performed by people trained to obtain knowledge through systematic procedures. Notions such as “objectivity” and “reflexivity,” “systematic,” “theory,” “evidence” and “openness” are here taken for granted in any type of research. Next, building on our empirical analysis we explain the four notions that we have identified as central to qualitative work: distinctions, process, closeness, and improved understanding. In discussing them, ultimately in relation to one another, we make their meaning even more precise. Our idea, in short, is that only when these ideas that we present separately for analytic purposes are brought together can we speak of qualitative research.

Distinctions

We believe that the possibility of making new distinctions is one the defining characteristics of qualitative research. It clearly sets it apart from quantitative analysis which works with taken-for-granted variables, albeit as mentioned, meta-analyses, for example, factor analysis may result in new variables. “Quality” refers essentially to distinctions, as already pointed out by Aristotle. He discusses the term “qualitative” commenting: “By a quality I mean that in virtue of which things are said to be qualified somehow” (Aristotle 1984:14). Quality is about what something is or has, which means that the distinction from its environment is crucial. We see qualitative research as a process in which significant new distinctions are made to the scholarly community; to make distinctions is a key aspect of obtaining new knowledge; a point, as we will see, that also has implications for “quantitative research.” The notion of being “significant” is paramount. New distinctions by themselves are not enough; just adding concepts only increases complexity without furthering our knowledge. The significance of new distinctions is judged against the communal knowledge of the research community. To enable this discussion and judgements central elements of rational discussion are required (cf. Habermas [1981] 1987 ; Davidsson [ 1988 ] 2001) to identify what is new and relevant scientific knowledge. Relatedly, Ragin alludes to the idea of new and useful knowledge at a more concrete level: “Qualitative methods are appropriate for in-depth examination of cases because they aid the identification of key features of cases. Most qualitative methods enhance data” (1994:79). When Becker ( 1963 ) studied deviant behavior and investigated how people became marihuana smokers, he made distinctions between the ways in which people learned how to smoke. This is a classic example of how the strategy of “getting close” to the material, for example the text, people or pictures that are subject to analysis, may enable researchers to obtain deeper insight and new knowledge by making distinctions – in this instance on the initial notion of learning how to smoke. Others have stressed the making of distinctions in relation to coding or theorizing. Emerson et al. ( 1995 ), for example, hold that “qualitative coding is a way of opening up avenues of inquiry,” meaning that the researcher identifies and develops concepts and analytic insights through close examination of and reflection on data (Emerson et al. 1995 :151). Goodwin and Horowitz highlight making distinctions in relation to theory-building writing: “Close engagement with their cases typically requires qualitative researchers to adapt existing theories or to make new conceptual distinctions or theoretical arguments to accommodate new data” ( 2002 : 37). In the ideal-typical quantitative research only existing and so to speak, given, variables would be used. If this is the case no new distinction are made. But, would not also many “quantitative” researchers make new distinctions?

Process does not merely suggest that research takes time. It mainly implies that qualitative new knowledge results from a process that involves several phases, and above all iteration. Qualitative research is about oscillation between theory and evidence, analysis and generating material, between first- and second -order constructs (Schütz 1962 :59), between getting in contact with something, finding sources, becoming deeply familiar with a topic, and then distilling and communicating some of its essential features. The main point is that the categories that the researcher uses, and perhaps takes for granted at the beginning of the research process, usually undergo qualitative changes resulting from what is found. Becker describes how he tested hypotheses and let the jargon of the users develop into theoretical concepts. This happens over time while the study is being conducted, exemplifying what we mean by process.

In the research process, a pilot-study may be used to get a first glance of, for example, the field, how to approach it, and what methods can be used, after which the method and theory are chosen or refined before the main study begins. Thus, the empirical material is often central from the start of the project and frequently leads to adjustments by the researcher. Likewise, during the main study categories are not fixed; the empirical material is seen in light of the theory used, but it is also given the opportunity to kick back, thereby resisting attempts to apply theoretical straightjackets (Becker 1970 :43). In this process, coding and analysis are interwoven, and thus are often important steps for getting closer to the phenomenon and deciding what to focus on next. Becker began his research by interviewing musicians close to him, then asking them to refer him to other musicians, and later on doubling his original sample of about 25 to include individuals in other professions (Becker 1973:46). Additionally, he made use of some participant observation, documents, and interviews with opiate users made available to him by colleagues. As his inductive theory of deviance evolved, Becker expanded his sample in order to fine tune it, and test the accuracy and generality of his hypotheses. In addition, he introduced a negative case and discussed the null hypothesis ( 1963 :44). His phasic career model is thus based on a research design that embraces processual work. Typically, process means to move between “theory” and “material” but also to deal with negative cases, and Becker ( 1998 ) describes how discovering these negative cases impacted his research design and ultimately its findings.

Obviously, all research is process-oriented to some degree. The point is that the ideal-typical quantitative process does not imply change of the data, and iteration between data, evidence, hypotheses, empirical work, and theory. The data, quantified variables, are, in most cases fixed. Merging of data, which of course can be done in a quantitative research process, does not mean new data. New hypotheses are frequently tested, but the “raw data is often the “the same.” Obviously, over time new datasets are made available and put into use.

Another characteristic that is emphasized in our sample is that qualitative researchers – and in particular ethnographers – can, or as Goffman put it, ought to ( 1989 ), get closer to the phenomenon being studied and their data than quantitative researchers (for example, Silverman 2009 :85). Put differently, essentially because of their methods qualitative researchers get into direct close contact with those being investigated and/or the material, such as texts, being analyzed. Becker started out his interview study, as we noted, by talking to those he knew in the field of music to get closer to the phenomenon he was studying. By conducting interviews he got even closer. Had he done more observations, he would undoubtedly have got even closer to the field.

Additionally, ethnographers’ design enables researchers to follow the field over time, and the research they do is almost by definition longitudinal, though the time in the field is studied obviously differs between studies. The general characteristic of closeness over time maximizes the chances of unexpected events, new data (related, for example, to archival research as additional sources, and for ethnography for situations not necessarily previously thought of as instrumental – what Mannay and Morgan ( 2015 ) term the “waiting field”), serendipity (Merton and Barber 2004 ; Åkerström 2013 ), and possibly reactivity, as well as the opportunity to observe disrupted patterns that translate into exemplars of negative cases. Two classic examples of this are Becker’s finding of what medical students call “crocks” (Becker et al. 1961 :317), and Geertz’s ( 1973 ) study of “deep play” in Balinese society.

By getting and staying so close to their data – be it pictures, text or humans interacting (Becker was himself a musician) – for a long time, as the research progressively focuses, qualitative researchers are prompted to continually test their hunches, presuppositions and hypotheses. They test them against a reality that often (but certainly not always), and practically, as well as metaphorically, talks back, whether by validating them, or disqualifying their premises – correctly, as well as incorrectly (Fine 2003 ; Becker 1970 ). This testing nonetheless often leads to new directions for the research. Becker, for example, says that he was initially reading psychological theories, but when facing the data he develops a theory that looks at, you may say, everything but psychological dispositions to explain the use of marihuana. Especially researchers involved with ethnographic methods have a fairly unique opportunity to dig up and then test (in a circular, continuous and temporal way) new research questions and findings as the research progresses, and thereby to derive previously unimagined and uncharted distinctions by getting closer to the phenomenon under study.

Let us stress that getting close is by no means restricted to ethnography. The notion of hermeneutic circle and hermeneutics as a general way of understanding implies that we must get close to the details in order to get the big picture. This also means that qualitative researchers can literally also make use of details of pictures as evidence (cf. Harper 2002). Thus, researchers may get closer both when generating the material or when analyzing it.

Quantitative research, we maintain, in the ideal-typical representation cannot get closer to the data. The data is essentially numbers in tables making up the variables (Franzosi 2016 :138). The data may originally have been “qualitative,” but once reduced to numbers there can only be a type of “hermeneutics” about what the number may stand for. The numbers themselves, however, are non-ambiguous. Thus, in quantitative research, interpretation, if done, is not about the data itself—the numbers—but what the numbers stand for. It follows that the interpretation is essentially done in a more “speculative” mode without direct empirical evidence (cf. Becker 2017 ).

Improved Understanding

While distinction, process and getting closer refer to the qualitative work of the researcher, improved understanding refers to its conditions and outcome of this work. Understanding cuts deeper than explanation, which to some may mean a causally verified correlation between variables. The notion of explanation presupposes the notion of understanding since explanation does not include an idea of how knowledge is gained (Manicas 2006 : 15). Understanding, we argue, is the core concept of what we call the outcome of the process when research has made use of all the other elements that were integrated in the research. Understanding, then, has a special status in qualitative research since it refers both to the conditions of knowledge and the outcome of the process. Understanding can to some extent be seen as the condition of explanation and occurs in a process of interpretation, which naturally refers to meaning (Gadamer 1990 ). It is fundamentally connected to knowing, and to the knowing of how to do things (Heidegger [1927] 2001 ). Conceptually the term hermeneutics is used to account for this process. Heidegger ties hermeneutics to human being and not possible to separate from the understanding of being ( 1988 ). Here we use it in a broader sense, and more connected to method in general (cf. Seiffert 1992 ). The abovementioned aspects – for example, “objectivity” and “reflexivity” – of the approach are conditions of scientific understanding. Understanding is the result of a circular process and means that the parts are understood in light of the whole, and vice versa. Understanding presupposes pre-understanding, or in other words, some knowledge of the phenomenon studied. The pre-understanding, even in the form of prejudices, are in qualitative research process, which we see as iterative, questioned, which gradually or suddenly change due to the iteration of data, evidence and concepts. However, qualitative research generates understanding in the iterative process when the researcher gets closer to the data, e.g., by going back and forth between field and analysis in a process that generates new data that changes the evidence, and, ultimately, the findings. Questioning, to ask questions, and put what one assumes—prejudices and presumption—in question, is central to understand something (Heidegger [1927] 2001 ; Gadamer 1990 :368–384). We propose that this iterative process in which the process of understanding occurs is characteristic of qualitative research.

Improved understanding means that we obtain scientific knowledge of something that we as a scholarly community did not know before, or that we get to know something better. It means that we understand more about how parts are related to one another, and to other things we already understand (see also Fine and Hallett 2014 ). Understanding is an important condition for qualitative research. It is not enough to identify correlations, make distinctions, and work in a process in which one gets close to the field or phenomena. Understanding is accomplished when the elements are integrated in an iterative process.

It is, moreover, possible to understand many things, and researchers, just like children, may come to understand new things every day as they engage with the world. This subjective condition of understanding – namely, that a person gains a better understanding of something –is easily met. To be qualified as “scientific,” the understanding must be general and useful to many; it must be public. But even this generally accessible understanding is not enough in order to speak of “scientific understanding.” Though we as a collective can increase understanding of everything in virtually all potential directions as a result also of qualitative work, we refrain from this “objective” way of understanding, which has no means of discriminating between what we gain in understanding. Scientific understanding means that it is deemed relevant from the scientific horizon (compare Schütz 1962 : 35–38, 46, 63), and that it rests on the pre-understanding that the scientists have and must have in order to understand. In other words, the understanding gained must be deemed useful by other researchers, so that they can build on it. We thus see understanding from a pragmatic, rather than a subjective or objective perspective. Improved understanding is related to the question(s) at hand. Understanding, in order to represent an improvement, must be an improvement in relation to the existing body of knowledge of the scientific community (James [ 1907 ] 1955). Scientific understanding is, by definition, collective, as expressed in Weber’s famous note on objectivity, namely that scientific work aims at truths “which … can claim, even for a Chinese, the validity appropriate to an empirical analysis” ([1904] 1949 :59). By qualifying “improved understanding” we argue that it is a general defining characteristic of qualitative research. Becker‘s ( 1966 ) study and other research of deviant behavior increased our understanding of the social learning processes of how individuals start a behavior. And it also added new knowledge about the labeling of deviant behavior as a social process. Few studies, of course, make the same large contribution as Becker’s, but are nonetheless qualitative research.

Understanding in the phenomenological sense, which is a hallmark of qualitative research, we argue, requires meaning and this meaning is derived from the context, and above all the data being analyzed. The ideal-typical quantitative research operates with given variables with different numbers. This type of material is not enough to establish meaning at the level that truly justifies understanding. In other words, many social science explanations offer ideas about correlations or even causal relations, but this does not mean that the meaning at the level of the data analyzed, is understood. This leads us to say that there are indeed many explanations that meet the criteria of understanding, for example the explanation of how one becomes a marihuana smoker presented by Becker. However, we may also understand a phenomenon without explaining it, and we may have potential explanations, or better correlations, that are not really understood.

We may speak more generally of quantitative research and its data to clarify what we see as an important distinction. The “raw data” that quantitative research—as an idealtypical activity, refers to is not available for further analysis; the numbers, once created, are not to be questioned (Franzosi 2016 : 138). If the researcher is to do “more” or “change” something, this will be done by conjectures based on theoretical knowledge or based on the researcher’s lifeworld. Both qualitative and quantitative research is based on the lifeworld, and all researchers use prejudices and pre-understanding in the research process. This idea is present in the works of Heidegger ( 2001 ) and Heisenberg (cited in Franzosi 2010 :619). Qualitative research, as we argued, involves the interaction and questioning of concepts (theory), data, and evidence.

Ragin ( 2004 :22) points out that “a good definition of qualitative research should be inclusive and should emphasize its key strengths and features, not what it lacks (for example, the use of sophisticated quantitative techniques).” We define qualitative research as an iterative process in which improved understanding to the scientific community is achieved by making new significant distinctions resulting from getting closer to the phenomenon studied. Qualitative research, as defined here, is consequently a combination of two criteria: (i) how to do things –namely, generating and analyzing empirical material, in an iterative process in which one gets closer by making distinctions, and (ii) the outcome –improved understanding novel to the scholarly community. Is our definition applicable to our own study? In this study we have closely read the empirical material that we generated, and the novel distinction of the notion “qualitative research” is the outcome of an iterative process in which both deduction and induction were involved, in which we identified the categories that we analyzed. We thus claim to meet the first criteria, “how to do things.” The second criteria cannot be judged but in a partial way by us, namely that the “outcome” —in concrete form the definition-improves our understanding to others in the scientific community.

We have defined qualitative research, or qualitative scientific work, in relation to quantitative scientific work. Given this definition, qualitative research is about questioning the pre-given (taken for granted) variables, but it is thus also about making new distinctions of any type of phenomenon, for example, by coining new concepts, including the identification of new variables. This process, as we have discussed, is carried out in relation to empirical material, previous research, and thus in relation to theory. Theory and previous research cannot be escaped or bracketed. According to hermeneutic principles all scientific work is grounded in the lifeworld, and as social scientists we can thus never fully bracket our pre-understanding.

We have proposed that quantitative research, as an idealtype, is concerned with pre-determined variables (Small 2008 ). Variables are epistemically fixed, but can vary in terms of dimensions, such as frequency or number. Age is an example; as a variable it can take on different numbers. In relation to quantitative research, qualitative research does not reduce its material to number and variables. If this is done the process of comes to a halt, the researcher gets more distanced from her data, and it makes it no longer possible to make new distinctions that increase our understanding. We have above discussed the components of our definition in relation to quantitative research. Our conclusion is that in the research that is called quantitative there are frequent and necessary qualitative elements.

Further, comparative empirical research on researchers primarily working with ”quantitative” approaches and those working with ”qualitative” approaches, we propose, would perhaps show that there are many similarities in practices of these two approaches. This is not to deny dissimilarities, or the different epistemic and ontic presuppositions that may be more or less strongly associated with the two different strands (see Goertz and Mahoney 2012 ). Our point is nonetheless that prejudices and preconceptions about researchers are unproductive, and that as other researchers have argued, differences may be exaggerated (e.g., Becker 1996 : 53, 2017 ; Marchel and Owens 2007 :303; Ragin 1994 ), and that a qualitative dimension is present in both kinds of work.

Several things follow from our findings. The most important result is the relation to quantitative research. In our analysis we have separated qualitative research from quantitative research. The point is not to label individual researchers, methods, projects, or works as either “quantitative” or “qualitative.” By analyzing, i.e., taking apart, the notions of quantitative and qualitative, we hope to have shown the elements of qualitative research. Our definition captures the elements, and how they, when combined in practice, generate understanding. As many of the quotations we have used suggest, one conclusion of our study holds that qualitative approaches are not inherently connected with a specific method. Put differently, none of the methods that are frequently labelled “qualitative,” such as interviews or participant observation, are inherently “qualitative.” What matters, given our definition, is whether one works qualitatively or quantitatively in the research process, until the results are produced. Consequently, our analysis also suggests that those researchers working with what in the literature and in jargon is often called “quantitative research” are almost bound to make use of what we have identified as qualitative elements in any research project. Our findings also suggest that many” quantitative” researchers, at least to some extent, are engaged with qualitative work, such as when research questions are developed, variables are constructed and combined, and hypotheses are formulated. Furthermore, a research project may hover between “qualitative” and “quantitative” or start out as “qualitative” and later move into a “quantitative” (a distinct strategy that is not similar to “mixed methods” or just simply combining induction and deduction). More generally speaking, the categories of “qualitative” and “quantitative,” unfortunately, often cover up practices, and it may lead to “camps” of researchers opposing one another. For example, regardless of the researcher is primarily oriented to “quantitative” or “qualitative” research, the role of theory is neglected (cf. Swedberg 2017 ). Our results open up for an interaction not characterized by differences, but by different emphasis, and similarities.

Let us take two examples to briefly indicate how qualitative elements can fruitfully be combined with quantitative. Franzosi ( 2010 ) has discussed the relations between quantitative and qualitative approaches, and more specifically the relation between words and numbers. He analyzes texts and argues that scientific meaning cannot be reduced to numbers. Put differently, the meaning of the numbers is to be understood by what is taken for granted, and what is part of the lifeworld (Schütz 1962 ). Franzosi shows how one can go about using qualitative and quantitative methods and data to address scientific questions analyzing violence in Italy at the time when fascism was rising (1919–1922). Aspers ( 2006 ) studied the meaning of fashion photographers. He uses an empirical phenomenological approach, and establishes meaning at the level of actors. In a second step this meaning, and the different ideal-typical photographers constructed as a result of participant observation and interviews, are tested using quantitative data from a database; in the first phase to verify the different ideal-types, in the second phase to use these types to establish new knowledge about the types. In both of these cases—and more examples can be found—authors move from qualitative data and try to keep the meaning established when using the quantitative data.

A second main result of our study is that a definition, and we provided one, offers a way for research to clarify, and even evaluate, what is done. Hence, our definition can guide researchers and students, informing them on how to think about concrete research problems they face, and to show what it means to get closer in a process in which new distinctions are made. The definition can also be used to evaluate the results, given that it is a standard of evaluation (cf. Hammersley 2007 ), to see whether new distinctions are made and whether this improves our understanding of what is researched, in addition to the evaluation of how the research was conducted. By making what is qualitative research explicit it becomes easier to communicate findings, and it is thereby much harder to fly under the radar with substandard research since there are standards of evaluation which make it easier to separate “good” from “not so good” qualitative research.

To conclude, our analysis, which ends with a definition of qualitative research can thus both address the “internal” issues of what is qualitative research, and the “external” critiques that make it harder to do qualitative research, to which both pressure from quantitative methods and general changes in society contribute.

Acknowledgements

Financial Support for this research is given by the European Research Council, CEV (263699). The authors are grateful to Susann Krieglsteiner for assistance in collecting the data. The paper has benefitted from the many useful comments by the three reviewers and the editor, comments by members of the Uppsala Laboratory of Economic Sociology, as well as Jukka Gronow, Sebastian Kohl, Marcin Serafin, Richard Swedberg, Anders Vassenden and Turid Rødne.

Biographies

is professor of sociology at the Department of Sociology, Uppsala University and Universität St. Gallen. His main focus is economic sociology, and in particular, markets. He has published numerous articles and books, including Orderly Fashion (Princeton University Press 2010), Markets (Polity Press 2011) and Re-Imagining Economic Sociology (edited with N. Dodd, Oxford University Press 2015). His book Ethnographic Methods (in Swedish) has already gone through several editions.

is associate professor of sociology at the Department of Media and Social Sciences, University of Stavanger. His research has been published in journals such as Social Psychology Quarterly, Sociological Theory, Teaching Sociology, and Music and Arts in Action. As an ethnographer he is working on a book on he social world of big-wave surfing.

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Contributor Information

Patrik Aspers, Email: [email protected] .

Ugo Corte, Email: [email protected] .

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Qualitative Research Design

This course is part of Qualitative Research Design and Methods for Public Health Specialization

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Design a qualitative research project to respond to specific public health problems/questions.

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There are 6 modules in this course

This course introduces qualitative research, compares and contrasts qualitative and quantitative research approaches, and provides an overview of qualitative methods for data collection. It outlines a step-by-step approach to qualitative research design that begins by identifying a public health topic of interest, works to hone in on a specific research problem, and then specifies research questions, objectives, and specific aims. The course emphasizes the iterative nature of research design in qualitative inquiry and highlights the importance of specifying a population of interest, an appropriate sampling strategy, and potential approaches to recruitment. It introduces the relationship between these considerations and key concepts such as saturation and transferability in qualitative research. Finally, the course considers ethical concerns specific to qualitative research and potential solutions. Learners of this course will not only be able to put what they learn into practice, but they'll also develop a portfolio of qualitative research materials for career advancement.

Introduction to Qualitative Research

In this first week, you'll get the chance to explore characteristics and approaches of both qualitative and quantitative research, understand their differences, and acknowledge how both are complementary.

What's included

6 videos 4 readings 1 quiz 1 peer review

6 videos • Total 20 minutes

  • Welcome to the Course! • 2 minutes • Preview module
  • What Is Research? • 2 minutes
  • What Is Qualitative Research? • 3 minutes
  • How Is Qualitative Different From Quantitative? • 4 minutes
  • Five Basic Approaches to Qualitative Research • 4 minutes
  • Qualitative and Quantitative As Complementary Methods • 3 minutes

4 readings • Total 145 minutes

  • Course Outline and Grading Information • 5 minutes
  • Introduction to Qualitative Research • 20 minutes
  • Qualitative Inquiry • 90 minutes
  • Mixed Methods Design • 30 minutes

1 quiz • Total 20 minutes

  • Practice • 20 minutes

1 peer review • Total 60 minutes

  • Week 1: Comparing Quantitative and Qualitative Studies • 60 minutes

Qualitative Methods

This week, we'll look at two types of data that can be collected and dive into the three main data collection methods used in qualitative studies. Finally, we'll wrap up by discussing the concept of saturation and consider the lingering question, "how much data is enough?"

6 videos 2 readings 1 quiz 1 peer review

6 videos • Total 15 minutes

  • A Look at This Week • 2 minutes • Preview module
  • Types of Data • 1 minute
  • Observation • 4 minutes
  • Interviews • 3 minutes
  • Focus Group Discussions • 2 minutes
  • Saturation: How Much Data to Collect? • 2 minutes

2 readings • Total 135 minutes

  • Data Collection • 90 minutes
  • Saturation Point • 45 minutes
  • Week 2: Exploring Qualitative Methods • 60 minutes

Objective-Driven Design

In our third week, we'll discuss how to develop a problem statement from a topic of interest, craft research questions and aims, and discuss how this process all relates to objective-driven design.

5 videos 2 readings 1 quiz 1 peer review

5 videos • Total 21 minutes

  • A Look at This Week • 3 minutes • Preview module
  • What Is Objective-Driven Design? • 1 minute
  • Uncovering a Problem • 6 minutes
  • Developing & Refining a Problem Statement • 3 minutes
  • Developing Research Questions & Specific Aims • 6 minutes

2 readings • Total 75 minutes

  • Setting Up a Qualitative Project • 30 minutes
  • Resources for Developing Your Research Problem & Question • 45 minutes
  • Week 3: Identifying Your Research Problem • 60 minutes

Methods, Population, Sampling, & Recruitment

For our fourth week, we'll take a look at how to choose data collection methods that are best suited for your aims, explore the various sampling and recruitment strategies to select participants, and finally consider how research design is an iterative process.

  • A Look at This Week • 1 minute • Preview module
  • Aligning Methods with Aims • 2 minutes
  • Identifying a Setting and Honing in on a Population • 2 minutes
  • Sampling Strategies • 6 minutes
  • Recruitment Strategies • 2 minutes
  • Iterative Design • 0 minutes

2 readings • Total 95 minutes

  • Resources for Selecting Appropriate Methods • 35 minutes
  • Resources for Identifying Your Strategies • 60 minutes

1 quiz • Total 30 minutes

  • Practice • 30 minutes
  • Week 4: Identifying Your Methods, Population, Sampling, & Recruitment Strategies • 60 minutes

Research Ethics

Our fifth week is all about ethical considerations in qualitative research. As researchers, we need to be aware and take precautions to ensure our work with human subjects is never exploitative, deceitful, or harmful. We'll go over the key ethical principles to keep in mind when beginning a qualitative study.

4 videos 3 readings 1 quiz 1 peer review 1 discussion prompt

4 videos • Total 12 minutes

  • Overview of Research Ethics • 4 minutes
  • Key Issues and Benefits of Qualitative Research • 5 minutes
  • Strategies for IRBs and Ethics Committees • 1 minute

3 readings • Total 130 minutes

  • CITI Certification for Human Subjects Research • 10 minutes
  • Studies with Questionable Ethics • 30 minutes
  • Resources for Ethics in Qualitative Research • 90 minutes
  • Week 5: Considering Ethics in Research • 60 minutes

1 discussion prompt • Total 10 minutes

  • Ethics Around the World • 10 minutes

Course Project and Design Examples

In this final week, you'll combine all items of your research design for a final submission. We'll also review real cases of graduates in the MPH program to see the different approaches that can be taken.

5 videos 2 readings 1 peer review

5 videos • Total 47 minutes

  • Elements of Research Design: An Example (from Tamar Goldenberg's MPH Thesis Research) • 5 minutes
  • Candace Girod: Menstrual Hygiene Management at Schools in Nairobi, Kenya • 13 minutes
  • Wendy Avila: Exclusive Breast-Feeding among Women in Managua, Nicaragua • 15 minutes
  • Jasmine Kelly: Maternal & Child Nutrition in Rural Tanzania • 11 minutes

2 readings • Total 60 minutes

  • Interview Series • 30 minutes
  • Preparing Your Research Design • 30 minutes
  • Week 6: Your Qualitative Research Design • 60 minutes

Instructor ratings

We asked all learners to give feedback on our instructors based on the quality of their teaching style.

5 qualitative research designs

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Reviewed on Oct 2, 2023

It was really a difficult nut to crack but a very useful and descriptive course for those people who wants to do research

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Excellent Course. Improved my understanding of Qualitative Research Design through actually doing it for my research.

Reviewed on Jun 18, 2022

I could acquire all the skills necessary for writing a qualitative research proposal including ethical concerns

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  • Open access
  • Published: 21 February 2024

Usefulness of pedagogical design features of a digital educational resource into nursing home placement: a qualitative study of nurse educators’ experiences

  • Monika Ravik   ORCID: orcid.org/0000-0002-1490-9341 1 ,
  • Kristin Laugaland   ORCID: orcid.org/0000-0003-3451-2584 2 ,
  • Kristin Akerjordet   ORCID: orcid.org/0000-0002-4300-4496 2 , 3 ,
  • Ingunn Aase   ORCID: orcid.org/0000-0002-0243-6436 2 &
  • Marianne Thorsen Gonzalez   ORCID: orcid.org/0000-0003-1208-5470 1  

BMC Nursing volume  23 , Article number:  135 ( 2024 ) Cite this article

Metrics details

The rapid advancement of technology-enhanced learning opportunities has resulted in requests of applying improved pedagogical design features of digital educational resources into nursing education. Digital educational resources refers to technology-mediated learning approaches. Efficient integration of digital educational resources into nursing education, and particularly into clinical placement, creates considerable challenges. The successful use of digital educational resources requires thoughtful integration of technological and pedagogical design features. Thus, we have designed and developed a digital educational resource, digiQUALinPRAX, by emphasizing pedagogical design features. The nurse educators’ experiences of the usefulness of this digital educational resource is vital for securing improved quality in placement studies.

To obtain an in-depth understanding of the usefulness of the pedagogical design features of a digital educational resource, digiQUALinPRAX, in supporting nurse educators’ educational role in nursing home placements in the first year of nursing education.

An explorative and descriptive qualitative research design was used. Individual semi-structured interviews were conducted with six nurse educators working in first year of a Bachelor’s of Nursing programme after using the digital educational resource, digiQUALinPRAX, during an eight-week clinical placement period in nursing homes in April 2022.

Two main categories were identified: (1) supporting supervision and assessment of student nurses and (2) supporting interactions and partnerships between stakeholders.

The pedagogical design features of the digiQUALinPRAX resource provided nurse educators with valuable pedagogical knowledge in terms of supervision and assessment of student nurses, as well as simplified and supported interaction and partnership between stakeholders.

Peer Review reports

Contributions of the paper

What is already known.

The educational role in clinical placement education poses substantial challenges for nurse educators, such as tailoring pedagogical approaches to the learning needs and abilities of individual students.

Digital educational resources are increasingly used in clinical placement education in nursing to enhance student learning.

To improve the quality of clinical placement learning for student nurses, attention should be paid to the design, development, and use of digital educational resources.

What this paper adds

This paper adds that nurse educators experienced that pedagogical design features of a digital educational resource, digiQUALinPRAX, provided them with valuable knowledge in supervising and assessing student nurses in clinical placement education in nursing homes.

This paper further adds that nurse educators experienced that the pedagogical design features of the digital educational resource, digiQUALinPRAX, were supportive and enhanced their role by providing possibilities for interaction and partnership between stakeholders in nursing home placement.

Nursing homes hold great potential as clinical learning arenas for first year student nurses; thus, improved quality in these clinical placement studies is crucial [ 1 ]. To provide optimal and high-quality clinical placement education and benefit from the nursing home learning potential, nurse educators play a key role in their supervision and assessment approaches [ 2 ]. Thus, nurse educators’ pedagogical approaches during clinical placement education entails meeting different levels of students’ individual learning needs and preparedness for learning [ 3 ]. From this perspective, nurse educators’ competence, engagement, pedagogical practice and experience might motivate or demotivate student nurses early on in their education, both directly and indirectly, for their future careers working with elderly in the nursing home context [ 4 ]. However, in nursing homes as an important learning context, recruiting registered nurses filling roles as students’ clinical supervisors is often a challenge [ 5 , 6 ].

Nonetheless, supervising student nurses during placement education in nursing homes is reported to be a low priority among nurse educators [ 5 ]. Additionally, nurse educators in nursing homes frequently lack the formal preparation to fulfil their educational role at the expected educational level [ 5 , 7 ], and are often hired to act as nurse educators for a short time during placement education [ 5 ]. Consequently, part-time nurse-educators will lead to a lack of continuity in student follow-ups [ 5 ]. Thus, addressing improved quality in clinical supervision and assessment in the Bachelor’s of Nursing Education Programs is vital [ 8 , 9 ].

Tailoring pedagogical approaches to students’ individual learning needs pose substantial challenges for nurse educators [ 10 ]. Thus, supporting and enhancing nurse educators’ proficiency in supervising student nurses during placement education in nursing homes for pedagogical purposes has been suggested; this should be done using digital educational resources [ 8 ]. The present study responds to this request.

The use of digital educational resources has been increasingly developed owing to the extensively available and easily accessible internet connection [ 11 ]. These resources could be electronic (e-learning), mobile (m-learning), and online and game-based learning [ 12 , 13 , 14 , 15 ]. Digital educational resources are innovative educational approaches to provide knowledge in an interactive and flexible environment, thus facilitating personalised learning and improved understanding [ 16 , 17 ]. Digital educational resources aimed at ensuring that student nurses have appropriate learning opportunities and that experiences are increasingly being used [ 18 , 19 , 20 , 21 , 22 ].

However, integrating digital educational resources in various educational institutions goes beyond easy and flexible access to these learning resources. Koehler and Mishra [ 23 ] underline the need to effectively utilise these resources for educational purposes. Thus, there is a need for educators to improve their understanding of using digital educational resources when teaching, supervising, and assessing to optimally enhance students’ learning experiences [ 23 , 24 ]. Nurse educators are often underconfident and unable to optimally use digital resources, and thus are unable to understand how to modify their pedagogical approaches digitally [ 10 , 16 , 17 , 25 ]. A recent review has reported that digital educational resources in nursing education often lacks anchoring in pedagogical theories [ 26 ]. Consequently, this will directly affect the quality of education provided to student nurses [ 16 ]. To compensate for the above mentioned shortcomings, we designed and developed a digital educational resource, digiQUALinPRAX. This resource aims to support nurse educators in developing suitable and theoretically anchored pedagogical knowledge that is adapted to student nurses during nursing home placement [ 8 ]. The co-creative process informed the educational content, design, and functionality of the digiQUALinPRAX resource, which were informed by and grounded in learning theory and principles, in line with Koehler and Mishra’s [ 23 ] ‘Technological pedagogical and content knowledge’ framework. Technological knowledge refers to knowledge of the technological characteristics, whereas pedagogical knowledge refers to how students learn best, and content knowledge refers to the domain-specific subject matter that is being taught and learned [ 23 ]. Koehler and Mishra [ 23 ] emphasise the necessity of interrelatedness and dynamic interplay between content and pedagogical and technological knowledge to effectively cater to students’ learning needs. Here, technological pedagogical knowledge refers to knowledge about the use of technology to optimally implement pedagogical approaches (i.e. the use of digital educational resources as a vehicle for the learning outcomes and experiences desired by an educator) [ 23 ].

This study aimed to obtain an in-depth understanding of how nurse educators experienced the usefulness of the pedagogical design features of the digiQUALinPRAX resource to support their role in nursing home placements. Experiences enables the identification and addressing of any issues that require improvement before the final version of a digital educational resource is released, resulting in a better pedagogical experience for nurse educators [ 27 ]. When exploring experiences about digital educational resources, experiencing educators’ feedback is crucial. This is because they have the pedagogical competence and experience necessary to create resources that align with curriculum goals [ 28 ].

The current study applied an explorative and descriptive qualitative research design. This is appropriate for investigating an unexplored subject descriptively, along with its characteristics [ 29 ]. The study is part of a larger research project [ 8 ] that developed the digiQUALinPRAX resource. The digiQUALinPRAX resource was co-created with key stakeholders (i.e. student nurses, nurse educators, registered nurse mentors, e-learning designers and researchers) to enhance quality in nursing home placements, including the support and enhancement of the nurse educators’ role. For a detailed description of the overall co-creative development process, see Laugaland et al. [ 30 ].

Educational placement context

In Norway, becoming a registered nurse requires the successful completion of a 3-year Bachelor’s curriculum programme (180 credits), developed in accordance with the European Directive [ 31 ] and national regulations [ 32 ]. Half of this nursing education programme in Norway and elsewhere in Europe comprises of the clinical placement component [ 31 , 32 ]. As part of their professional responsibilities, the qualified and experienced registered nurses fulfilled the role of registered nurse mentors for students during their clinical placements. They focused on mentorship rather than actively teaching and developing the students’ competencies, indicating that mentoring by registered nurses was service-led rather than educationally driven. Although these registered nurse mentors possessed appropriate qualifications, they lacked formal academic educator competencies. Meanwhile, nurse educators bridged the gap between academic and placement knowledge. They possessed pedagogical knowledge and played a vital role in supporting, supervising and assessing student nurses. Nurse educators, who hail from the academic setting, bear the pivotal responsibility for the final decision of whether students pass or fail. They support, supervise and assist students and their registered nurse mentors during clinical placement and take care of the collaboration between these two stakeholders. The clinical experience for student nurses was set up through a collaborative effort between nurse educators from the university setting and registered nurse mentors in the clinical setting. In this collaboration, nurse educators were crucial to facilitating clinical learning experiences by securing optimal learning situations in the nursing homes in line with the educational learning outcomes. In these learning situations, the registered nurse mentors served as facilitators, mentors and role models. They also consistently provided valuable insight from their professional experiences, offered daily mentoring, and delivered feedback. This collaboration between the stakeholders aimed to help students in bridging the gap between the knowledge gained in the university setting and their clinical experiences in the nursing homes.

The digiQUALinPRAX resource being experienced in the study

The digiQUALinPRAX resource (Fig.  1 ) is a password-protected learning management system named Canvas (website), a technology that is used to plan, implement, and assess learning processes [ 33 ]. The overall educational aim of the digiQUALinPRAX resource was to enhance quality in nursing home placements by addressing students’ learning and the mentorship practices of educators and registered nurses (i.e. supervision and assessment). Nurse educators and registered nurse mentors, in turn, utilised this resource to enhance their teaching strategies, coordinate clinical placement activities, and ensure meaningful and enriching learning experiences for their students. The digiQUALinPRAX resource was designed to support the collaborative efforts of the stakeholders, fostering a dynamic and effective learning environment within the entire context of clinical placement education in nursing homes.

The digiQUALinPRAX resource consists of several core components as design features (i.e. interactive components, content components , and resource components ). The interactive components entailed features such as file sharing and messaging (through a dialogue forum), enabling stakeholders to interact with each other during the placement period. The dialogue forum provided a digital room where nurse educators and registered nurse mentors could provide written feedback on students’ assignments submitted through the digital educational resource.

Furthermore, the content components of the digiQUALinPRAX resource consisted of three content modules, including practical, educational, and contextual knowledge relevant for clinical placement in nursing homes. The three content modules were organized with different topics by the following titles: (1) Preparation to the clinical placement; (2) To study and supervise in clinical placementt; and (3) assessment of professional nursing competence. The first content module contained literature on pre-placement information, addressing the nursing home as a learning arena, role expectations, and schedule of the placement period. This content module further included a fixed time structure with predefined meetings. Additionally, an overview of the students’ theoretical educational content before placement and thus, their expected level of professional competence, was provided. The second content module contained literature on how to study, learn, and provide appropriate mentoring. This module provided examples of learning situations, as well as a description of students’ competence domains. These were tailored to accommodate the students’ learning objectives and mentoring activities. The use of reflection as a learning strategy was emphasized in this module. During the eight-week placement period, students had to write several reflection papers about various topics. The module further facilitated possibilities for nurse educators to provide written feedback on the reflection papers to stimulate and enhance students’ reflection skills. The third content module focused on assessment practices and provided information about formal and formative assessments. This was done by thoroughly describing the assessment forms through exemplifying how they could be used based on one specific patient situation. The formal assessment documents were all available directly in the digiQUALinPRAX resource.

The resource components of the digiQUALinPRAX resource consisted of practical, educational, and context-specific resources. These resources were illustrations, podcasts, video lectures, reflective activities, case-related activities, and resources to support nurse educators’ educational roles. Additional resources were study requirements, advice, and summaries of the core components.

figure 1

Core components of the digiQUALinPRAX resource

Study sample and recruitment

The target group for this study was nurse educators who were employees at one university in Norway, at which the digiQUALinPRAX was explored. The inclusion criterion was nurse educators having used the digiQUALinPRAX resource during an eight-week clinical placement period in nursing homes.

A purposive sampling strategy [ 34 ] was applied to recruit participants. After obtaining approval from the Vice-Dean of the Faculty of Health Sciences, potential nurse educators were sent recruitment e-mails. The e-mails contained general study information and a waiver of consent. Invitations were sent openly to nurse educators who had a supervisory responsibility to student nurses in nursing home placement. Six nurse educators consented to participate and received complete verbal information about the study. We considered these six nurse educators to be a representative sample [ 35 ] because they had used the digiQUALinPRAX resource during an eight-week placement period.

Research context

One week before the clinical placement period, the digiQUALinPRAX resource was precented and made accessible to the stakeholders (i.e. nurse educators, student nurses and registered nurse mentors) involved in the overall study. All stakeholders had access to the digiQUALinPRAX resource throughout the eight-week clinical placement period. As the target group in this study, the nurse educators were the only stakeholders possessing pedagogical knowledge and thus played a vital role in supporting, supervising, and assessing student nurses during their placements using the digiQUALinPRAX resource. Furthermore, they were responsible for collaborating with registered nurse mentors in their supervision of student nurses and in the use of the digiQUALinPRAX resource.

Data collection

Individual qualitative interviews with the six nurse educators were conducted for data collection. Data from individual interviews are valuable when the insight and understanding of participants’ perceptions, experiences, thoughts, and suggestions with respect to a given subject are of interest [ 29 ]. The qualitative nature of our research design, employing an in-depth exploration of the experiences of nurse educators, warranted a focus on detailed and context-specific insight rather than a large sample size [ 35 ]. The selected sample size was determined through a careful balance between power of information and the specific group of nurse educators with unique experience characteristics, which contribute to the depth of the analysis and results [ 35 ]. The nurse educators’ interviews were arranged in an academic nursing setting immediately after the eight-week clinical placement period in nursing homes for first year student nurses. Data were collected by the first author in April 2022.

A semi-structured interview guide was employed, addressing themes such as supervision and assessment possibilities, partnership, interaction and communication opportunities, and knowledge provided by the digital educational resource (see Supplementary File 1 ). Participants were offered opportunities to speak freely about their experiences, with follow-up questions where appropriate. Owing to COVID-19 restrictions, all interviews were conducted through a virtual platform via ZOOM using video and sound. This interview format encouraged two-way communication, allowing for conversations on relevant themes [ 29 ]. The interviews were audio recorded and lasted between 56 and 99 min. The six nurse educators provided rich information on their experienced usefulness of the pedagogical design features of the digiQUALinPRAX resource. The more information the participants held relevant to the actual study, the lower the number of participants needed [ 35 ].

Data analysis

All audio files were transcribed verbatim, resulting in text describing spoken words from the audio files underpinning the analysis, as recommended by Halcomb and Davidson [ 36 ]. After transcription of the audio files, text data were analysed using systematic text condensation in line with Malterud [ 37 ] (e.g. an explorative and descriptive method for thematic analysis that addresses the characteristics and essence of the subject being studied). NVivo software [ 38 ] version 12 was used for data analysis.

Data analysis was inductive; the text was re-read for a general overview and to familiarise the researchers with the content. Preliminary themes were captured in the first phase of the analysis. In the second phase, meaning units were identified and organised in relation to each of the themes captured in phase one. This data extraction approach entailed the decontextualization of the text: to be separated into parts or segments and removed from the belonging context [ 37 ]. Each meaning unit was coded and sorted into code groups. These were created in relation to each theme and provided a platform for the next phase of the analysis, in which a deeper meaning of experience was sought. In the third phase, the code groups were divided into sub-groups; the meaning units in the sub-groups were rewritten into condensates [ 37 ]. I–form was chosen to optimally represent the participants’ views, and their own words were used to maintain the original terminology. After completing the condensates, illustrative quotations (translated into English) were selected. Adjustments were made to provide a clearer understanding of the statements. In the fourth phase, the decontextualised text was recontextualised and synthesised; that is, parts were put into a new context while being true to the text from which the data were extracted. The condensed text from each sub-group within the code groups ‘went beyond’ the condensates, and new interpretive descriptions about the subject being studied were generated, to be presented in a third-person format [ 37 ]. Throughout the analysis, the first and last authors discussed the codes, sub-categories, and categories until reaching consensus. The recontextualisation resulted in two categories and five sub-categories.

To ensure the trustworthiness of this qualitative study, credibility, dependability, transferability, and confirmability were considered

[ 39 ]. Credibility was ensured in this study using an interview guide to establish consistency in the data collection process. Furthermore, video recordings (ZOOM) and transcription of the interviews verbatim helped ensure an accurate and complete representation of the nurse educators’ responses. Dependability was ensured by describing data collection and analysis in detail. NVivo was used to organise and visualise the data. Moreover, nurse educators’ arguments were quoted to show the links between the findings and data. To enhance the transferability, detailed descriptions of the research process were provided. Investigator triangulation was applied, where the first and last authors engaged in discussions and revisited the transcripts to ensure that the interpretations were supported by the data transcripts. The first and last authors held regular meetings to discuss the data analysis and ensure confirmability. Nurse educators were selected to provide in-depth data. Few participants were needed; information power was attained owing to the sample specificity and quality of dialogue [ 35 ].

Ethical considerations

This study was approved by the Norwegian Centre for Research Data (2018/61,309 and 489,776) and the university included prior to data collection. According to national regulations, approval from a medical ethical committee (Regional Committees for Medical and Health Research Ethics) to collect this type of data was not necessary. The study was conducted in accordance with the ethical principles of the Declaration of Helsinki [ 40 ]. The consolidated criteria for reporting qualitative research (COREQ) guideline was used to report the study. All participants received written and verbal information about the study, including the voluntary nature of participation and the right to withdraw from the study. All participants provided written informed consent, while non-participants refused to take part in the study. To ensure confidentiality, participants’ characteristics such as age, sex, educational background, and years of experience in placement education supervision were not provided. All data were anonymised and securely stored to ensure confidentiality and protect private information.

The qualitative analysis of nurse educators’ experiences in relation to the pedagogical design features of the developed digiQUALinPRAX resource resulted in perceptions and reflections of the following key categories: (1) supporting supervision and assessment of student nurses and (2) supporting interaction and partnership between stakeholders (Table  1 ).

Supporting supervision and assessment of student nurses

Nurse educators experienced that the pedagogical design features of the digiQUALinPRAX resource allowed for supporting supervision and assessment in terms of giving students feedback on their written assignments, encouraging their reflections and facilitating summative assessments of their study progression.

Offering possibilities to provide students feedback on their written assignments (directly in the dialogue forum)

Nurse educators positively experienced the interactive component of the digiQUALinPRAX resource as providing possibilities for giving written feedback on students’ written submissions in the dialogue forum, both from nurse educators and registered nurse mentors. Moreover, nurse educators experienced the digiQUALinPRAX resource to be useful as it forced them to provide feedback on all the students’ written assignments. However, they found it challenging to provide written feedback via the dialogue forum because it was not possible to simultaneously review students’ submissions while providing written feedback through the digiQUALinPRAX resource.

I had to go in and out of the dialogue forum when written feedback was provided on students’ submissions to read the text of the submissions. (Informant 4)

Offering possibilities to encourage students’ reflections

Nurse educators experienced the digiQUALinPRAX resource to be useful in terms of guiding specific topics for the reflection papers that were written and submitted by student nurses during placement, stating that it contributed to a more common focus on student learning during placement. They also positively experienced that the digiQUALinPRAX resource ensured that the topics of the reflection papers were not arbitrary and dependent on the individual nurse educators’ personal recommendations and preferences, which helped them provide more consistent supervision with a focus on student learning.

Learning focus became more common for student nurses because the digital educational resource guided them in terms of the topics that they should write about. (Informant 5)

Furthermore, nurse educators experienced the digiQUALinPRAX resource-led reflection papers written by students as a useful source of information. Specifically, these papers allowed nurse educators to gain valuable insights into each student’s learning and knowledge levels, enabling them to identify areas requiring further attention for learning and development. They experienced such papers as providing them with a clear understanding of the aspects that they should focus on and providing feedback to students. This approach enabled them to help correct misunderstandings and fill gaps in students’ academic and professional knowledge.

The use of the digiQUALinPRAX resource was experienced by nurse educators to help both inexperienced and experienced nurse educators when supervising students in nursing home placements and guiding reflection group meetings. Inexperienced nurse educators were helped to understand the concept and purpose of reflection and how to encourage students to engage in reflective processes. They further faced experienced educators as helping them obtain a better structure for the reflection group meeting, focusing on the reflection group towards the real education levels and learning outcomes. Nurse educators experienced that the use of the digiQUALinPRAX resource in reflection group meetings resulted in a superior focus on students’ learning processes. Moreover, supervision became more student- rather than teacher-centred.

I became more like a facilitator than a nurse educator in the reflection group meetings because the digital educational resource-led questions helped me encourage the students to reflect amongst themselves and with me as an educator. (Informant 1)

Nurse educators experienced the digiQUALinPRAX resource-led pedagogical materials as useful in influencing students’ engagement and verbal activity during reflection group meetings.

The case is great to work on together with the students. Additionally, the students enjoyed working on the case, they became actively engaged. (Informant 4)

Nurse educators experienced that digiQUALinPRAX resource-led pedagogical materials, such as cases, care plans, and reflection questions, served as a foundation for the reflection group meetings and consequently, facilitated students’ development of professional understanding and competence about the nursing profession.

Facilitating provision of summative assessments of students’ study progression

Several nurse educators experienced that using digiQUALinPRAX resource-led single patient situations as the basis for providing summative student assessments restricted the ability to comprehensively assess student progression on all items of the assessment form.

Sufficient data were unavailable to provide summative assessments of student progression using only one patient situation. (Informant 2)

Some nurse educators included multiple patient situations as the basis for providing summative student assessments, even though this was not guided by the digiQUALinPRAX resource; they experienced this to be beneficial for ensuring comprehensive coverage of all items on the assessment form. The nurse educators felt that this allowed students to demonstrate their study progress and identify areas of improvement.

It was unproblematic that the varied assessment items were written based on different patient situations because they provided more information about the student’s progression. (Informant 1)
Students completed the assessment based on several patient situations to show their knowledge well enough. (Informant 6)

Nurse educators experienced their role in summative assessment meetings as more constructive when registered nurse mentors completed the digiQUALinPRAX resource-led assessment form prior to the summative assessment meetings. This was because they adopted a cautious approach during assessment meetings as the registered nurse mentors’ verbal participation increased when they filled in their digiQUALinPRAX resource-led student evaluation form prior to the assessment. Specifically, nurse educators regarded it as a positive experience when registered nurse mentors provided clear verbal feedback on areas where students required further progress during the placement study.

Registered nurse mentors’ threshold for being verbally engaged during summative assessment situations was lowered because they had completed the digital-educational resource-led assessment form prior to the assessment meetings (Informant 1) .
Registered nurse mentors who had prepared themselves by writing in the digital educational resource-led assessment form were more verbally engaged during the summative assessment meetings. (Informant 6)

The registered nurse mentors’ clear and precise communication of students’ areas that required improvement during the placement was experienced positively by the nurse educators, as it provided them with a clear focus on what to prioritise when further supervising the students’ progress.

When the registered nurse mentor completed the digital-educational resource-led assessment form and was verbally engaged during the summative assessment meeting, the student’s next steps became clear. (Informant 2)

Supporting interaction and partnership between stakeholders

Nurse educators experienced that the interactive digiQUALinPRAX resource design contributed to increased support for interactions and establishing partnerships between stakeholders through stimulating communication and cooperation between stakeholders.

Simplifying and supporting interactions and cooperation between the stakeholders

Nurse educators experienced that the digiQUALinPRAX resource-led timeline enabled them to schedule equal in-person supervision group meetings with students during their clinical placement. Further, they experienced interactions and cooperation with students as important for encouraging students to engage in appropriate and meaningful learning processes and as a feature of conducting accurate student assessments during placements.

I established closer contact with the students because I used the digital education resource. (Informant 6)

Additionally, nurse educators experienced their cooperation with registered nurse mentors to have improved because of the use of the digiQUALinPRAX resource; that is, the registered nurse mentors contacted nurse educators more during clinical placement compared with before. As part of the appropriate student supervision, nurse educators emphasised the importance of a proper relationship between the clinical placement setting and various registered nurse mentors.

The threshold for the registered nurse mentors to contact me as an educator was lowered owing to the use of the digital educational resource. (Informant 1)

Simplifying and stimulating communication using the dialogue forum

Nurse educators experienced the dialogue forum usage to be unclear, and gave feedback on how they could appropriately use the dialogue forum (i.e. the digiQUALinPRAX resource-led interactive component that facilitates communication between the stakeholders during the placement).

Clarifications about the use of the dialogue forum should have been made because we were not used to making discussions in this forum. (Informant 1)

However, the nurse educators considered that the dialogue forum should only provide possibilities for communication between the varied stakeholders included in the supervision collaboration: the students, registered nurse mentors, and nurse educators. Nurse educators experienced this as a necessity for a dialogue forum that also fosters transparency and open communication between the nurse educator and their student group, such as an information channel providing possibilities for a nurse educator to disseminate the same information to all students in the student group simultaneously.

It is out of question sending information to students individually that can be disseminated to all students. (Informant 5)

Nurse educators experienced it that it was necessary for a dialogue forum to provide possibilities for confidentiality (e.g. as an alternative to emails for stakeholder communication). Moreover, confidentiality was not ensured in cases where students might not pass their placement. Students’ exclusion from the forum was requested when discussions solely between the educator and registered nurse mentor might be necessary.

I cannot raise challenging student situations in a dialogue forum if the student has access to the digital room. (Informant 3)

The current study aimed to explore and describe how nurse educators experienced the usefulness of the pedagogical design features of the digiQUALinPRAX resource from their perspective. Nurse educators’ positive experiences regarding the digital educational resource highlighted the pedagogical design features as unique features, improving their supervision and assessment of student nurses during clinical placement education in nursing homes. These findings align with those of previous studies suggesting that pedagogical design is essential for creating digital educational resources [ 26 ]. This is an important finding, as pedagogical design features are often overlooked in the technologies designed to enhance and support clinical placement education in Bachelor’s nursing programmes [ 26 , 41 ].

Nurse educators experienced the interactive communication features of the digiQUALinPRAX resource as a valued component, as it enhanced their ability to provide written feedback on students’ submissions for their learning processes. This finding is also important, as earlier research [ 42 , 43 ] has revealed that many students received insufficient written feedback on their submissions from nurse educators during clinical placement education. This inappropriate feedback may have a negative influence on students’ learning experiences, whereas it might hinder them in their ability to identify areas in which they need to improve and further study to close their gap in knowledge [ 43 ]. Hence, feedback plays a crucial role in supporting students in understanding their strengths and weaknesses, thereby helping them achieve their learning outcomes [ 44 , 45 , 46 ].

Providing written feedback on student submissions was also important for nurse educators in our study. File sharing, as an interactive part of the digiQUALinPRAX resource, enabled the nurse educators to gain insights into the students’ knowledge levels and provide feedback based on their individual learning needs. This aligns with the sociocultural learning perspective, which underscores Vygotsky’s [ 46 ] theory of learning and development. According to this theory, interactions with more proficient persons can help the learner advance to the next level of knowledge and understanding within their zone of proximal development.

Our findings also revealed that nurse educators experienced that scheduled digiQUALinPRAX resource-led submissions contributed to students receiving frequent feedback. This finding is in line with the results of Bosse et al. [ 47 ], who emphasised the benefits of receiving frequent feedback, as it led to better learning outcomes. Moreover, this illustrates that considering integrating pedagogical design features when developing digital educational resources is valuable in stimulating nurse educators to facilitate students’ learning processes.

Nurse educators noted that pedagogical design features of the digiQUALinPRAX resource helped them encourage students to actively engage in reflective thinking, both verbally and in writing. Reflective thinking involves critically analysing experiences, considering one’s thoughts and emotions and examining the broader context [ 48 ]. Improved learning through reflective-thinking processes among students has also been considered in prior research, showing that it can deepen the comprehension of learning objectives and increase the awareness of decision-making in clinical reasoning [ 49 , 50 ]. This indicates the importance of possessing reflective thinking skills, not only in improving self-directed learning but also in delivering high-quality patient care [ 48 , 51 ].

The study findings indicated that pedagogical design features of the digiQUALinPRAX resource facilitated a shift in the nurse educators’ role in reflection group meetings. The shift entailed moving from being nurse educators who often communicated their knowledge to assuming the role of facilitators who guided discussions and encouraged students’ reflections and critical thinking. This pedagogical approach prioritises a student-centred learning model, enabling student nurses to construct their understanding actively rather than passively receiving the presented information [ 49 , 50 ]. This finding is important because nurse educators often fail to involve students in reflective-thinking activities during their educational process, resulting in a lack of student participation and difficulties in comprehending learning objectives [ 6 , 48 , 52 , 53 , 54 , 55 ]. Regarding this issue, Dalsmo et al. [ 52 ] revealed that nurse educators were often ‘invisible’ in students’ learning processes during nursing home placement, hindering students’ ability to participate fully and comprehend the learning objectives.

Nurse educators positively experienced that pedagogical design features of the digiQUALinPRAX resource encouraged registered nurse mentors to provide a written assessment concerning both the strengths and weaknesses of student progression prior to summative assessment meetings, resulting in registered nurse mentors becoming more verbal during the meetings. Several studies have reported that nurse educators experience challenges in assessment meetings because of registered nurse mentors’ silence [ 42 , 52 , 56 ]. When nurse educators in our study experienced that registered nurse mentors wrote and verbalised what was expected from the students to work on during the remaining placement study, they were given opportunities to gear their student supervision towards the learning needs to focus on. From this perspective, nurse educators experienced that pedagogical design features of the digiQUALinPRAX resource facilitated both themselves and the registered nurse mentor to develop a common understanding regarding students’ learning needs. Previous research has revealed that educators and registered nurse mentors often have different expectations regarding students’ learning needs during placement studies [ 56 , 57 ]; thus, creating a common understanding among the stakeholders is crucial for effective student supervision.

Having a clear structure in the form of a timeline was a distinct pedagogical design feature of the digiQUALinPRAXresource that enhanced nurse educators’ student supervision abilities. They reported that the timeline specifying the number of physical meetings to be held during the placement period (and when they occurred) contributed to nurse educators being able to organise physical meeting frequency more equally. This is a valuable pedagogical design feature of the digiQUALinPRAX resource because dissatisfaction among students with their nurse educators’ physical presence in follow-ups during placement studies has been reported [ 3 , 6 ]. Further, the nurse educators experienced the timeline-defined specific topics for the reflection papers positively, ensuring that the topics did not become dependent on individual nurse educators’ preferences. In Ravik et al. [ 42 ], nurse educators requested greater consensus among themselves to enhance student supervision. Differences among nurse educators might be perceived as unjust by students and could account for some students learning more than others during placement studies because they receive more personalised attention from their nurse educators [ 58 ]. Therefore, including timeline-defined physical meetings for nurse educators and defined topics of the reflection papers might help address this issue. Both Cant et al. [ 3 ] and Laugaland et al. [ 8 ] reported that inconsistency between educators hinders improvements in students’ learning. Moreover, it was deemed essential for nurse educators to be physically present during clinical placement to ensure that they maintained suitable communication with registered nurse mentors. These findings are consistent with those of previous studies, suggesting that appropriate relationships and communication between stakeholders are critical for creating a supportive and collaborative learning environment for students [ 3 ].

Nurse educators positively experienced the inclusion of interactive design features in the form of a dialogue forum. This forum played a vital role in facilitating interactions between students and the stakeholders involved in overseeing and supervising students during their nursing home placement. Previous research supports the notion that this interactive design feature, integrated into digital educational resources, is essential for effectively implementing and utilising technology to enhance student supervision [ 20 , 42 , 59 ]. Notably, the presence of such dialogue forums, which enables interaction among stakeholders, has been reported as an indicator of satisfaction with digital educational resources [ 20 ]. This underscores the importance of fostering a sense of belonging within a learning community, which has been recognised as vital to student nurses’ placement learning experiences [ 60 ]. Even though the nurse educators highlighted the importance of a dialogue forum contributing to openness between all stakeholders during student supervision, they pointed out that the dialogue forum should be available for the nurse educator and registered nurse mentor only, allowing for confidential dialogues in challenging situations. Therefore, the interactive dialogue forum can create an atmosphere where nurse educators and registered nurse mentors can share concerns, exchange perspectives, and collaboratively develop strategies to address the challenges faced by students [ 42 ]. This is in line with previous research suggesting that open and confidential communication among stakeholders contributes to finding common ground and fostering productive resolutions [ 57 ].

Limitations and future research directions

Some limitations should be considered when interpreting the results of this study. Individual interviews were conducted by the first author, who was also involved in the design and development of the digital educational resource, digiQUALinPRAX. However, the first author was unknown to the participants, and lived and worked in another part of the country. Additionally, the participants were encouraged to frankly share their experiences and opinions regarding the use of digital educational resources. Despite the small sample size, the rich information that they provided allowed for the in-depth feedback and experiences we had aimed for in this study. It is, however, important to acknowledge that while the results may provide valuable insight into the experiences of the nurse educators, transferability to broader populations may be limited. Qualitative research is needed to explore and deepen these findings from the perspectives of student nurses and registered nurse mentors for the improvement of digiQUALinPRAX. Moreover, quantitative research is essential to providing knowledge about the effectiveness of digiQUALinPRAX in measuring and assessing student learning. Additionally, to broaden the applicability of the current study, it is recommended to explore the results across diverse healthcare educational settings, such as hospital settings for second- or third-year students. It is also suggested to explore revisions to the digital educational resource that would enable its adaptation to other internships within nursing education. This expanded exploration may contribute to the transferability of the results and enhance the broader relevance of the study’s implications.

Conclusions

The nurse educators gave in-depth information on how they experienced the usefulness of the pedagogical design features of the digiQUALinPRAX resource, developed to support their role in nursing home placements. The digiQUALinPRAX resource was experienced to display several positive pedagogical design features for enhancing the supervision and assessment of student nurses, while also promoting possibilities for interactions and partnerships among stakeholders. Notably, its inclusion of a timeframe was experienced as beneficial for ensuring greater consistency among nurse educators in student supervision. Additionally, its resource design facilitated student feedback, enabled nurse educators to better understand students’ current knowledge levels as well as their need for further supervision and learning. Furthermore, it was experienced as positive that pedagogical design features of the digiQUALinPRAX encouraged nurse educators to engage students in the reflective-thinking processes. Moreover, it was positively experienced that pedagogical design features of the digiQUALinPRAX contributed to registered nurse mentors becoming more verbal in assessment meetings, which also positively contributed to nurse educators’ further supervision of students during nursing home placement.

Data availability

To access the data in this study, please contact the corresponding author.

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Acknowledgements

We would like to thank all the participants who made the study possible. Thanks to Ingrid Espegren Dalsmo, UiA and NETTOPP-UIS, Department for Development of Digital Learning Tools, for their valuable participation and contribution in design and development of Fig.  1 .

This study was supported by the Research Council of Norway (RCN) (Grant number 273558). The funder had no role in the design of the project, data collection, analysis, interpretation of data or writing and publication of the manuscript.

Open access funding provided by University Of South-Eastern Norway

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Contributions

All authors conceptualised the study and developed the interview guides. MR conducted the data collection and designed and developed Fig.  1 . MR and MTG conducted the data analysis and interpretation, as well as drafted and revised the manuscript. KL, KA, and IA provided critical revisions for important intellectual content. All authors reviewed and approved the manuscript.

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Correspondence to Monika Ravik .

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This study was approved by the Norwegian Centre for Research Data (2018/61309 and 489776) and the university included prior to data collection. According to national regulations, approval from a medical ethical committee (Regional Committees for Medical and Health Research Ethics) to collect this type of data was not necessary. The study was conducted in accordance with the ethical principles of the Declaration of Helsinki [ 40 ]. The consolidated criteria for reporting qualitative research (COREQ) guideline was used to report the study. All participants received written and oral information about the study, including voluntary nature of participation, and the right to reject or withdraw from the study. All participants provided written informed consent. To ensure confidentiality, participants’ characteristics such as age, sex, educational background, and years of experience in placement education supervision were not provided. All data were anonymised and securely stored to ensure confidentiality and protect private information.

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Ravik, M., Laugaland, K., Akerjordet, K. et al. Usefulness of pedagogical design features of a digital educational resource into nursing home placement: a qualitative study of nurse educators’ experiences. BMC Nurs 23 , 135 (2024). https://doi.org/10.1186/s12912-024-01776-5

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Received : 22 October 2023

Accepted : 29 January 2024

Published : 21 February 2024

DOI : https://doi.org/10.1186/s12912-024-01776-5

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  • Digital educational resource
  • Nurse educator
  • Nursing education
  • Nursing home placement
  • Pedagogical design features
  • Placement learning

BMC Nursing

ISSN: 1472-6955

5 qualitative research designs

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  1. Qualitative Research Designs and Methods

    5 Qualitative Research Designs and Research Methods Lissie Hoover November 03, 2021 in [ Doctoral Journey ] Before constructing a qualitative study, you must first know your approach. Second, you must know how you intend to gather the research. These are called research methods.

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    We will discuss the process of selecting, contrasting, and implementing five qualitative designs: narrative research, case studies, grounded theory, phenom- enology, and participatory action research (PAR). In counseling, the two most widely used qualitative designs appear to be case study and grounded theory, followed distantly by phenomenology.

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    A popular and helpful categorization separate qualitative methods into five groups: ethnography, narrative, phenomenological, grounded theory, and case study. John Creswell outlines these five methods in Qualitative Inquiry and Research Design.

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    Author Information and Affiliations Last Update: September 18, 2022. Go to: Introduction Qualitative research is a type of research that explores and provides deeper insights into real-world problems. [1]

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    Qualitative Research Design: The Five Essential Components1 1. Goals. Why is your study worth doing? Why do you want to conduct this study, and why should we care about the results? 2. Conceptual Framework. What do you think is going on with the issues, settings, or people you plan to study?

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    In this chapter, we will discuss how to design a qualitative research project using two of the most common qualitative research methods: in-depth interviewing and ethnographic observations (also known as ethnography or participant observation). We will begin the chapter by discussing the what, how, and why of interviewing and ethnography.

  11. What is Qualitative Research Design? Definition, Types, Methods and

    Here are some common types: Phenomenological Research This design aims to understand the essence and meaning of human experiences related to a particular phenomenon. Researchers explore participants' subjective experiences through in-depth interviews or observations to uncover the underlying structures and patterns of their lived experiences.

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    The outcomes of qualitative research designs are situated narratives of peoples' activities in real settings, reasoned explanations of behavior, discoveries of new phenomena, and creating and testing of theories.A three-level framework can be used to describe the layers of qualitative research design and conceptualize its multifaceted nature ...

  13. PDF Comparing the Five Approaches

    All five approaches have in common the general process of research that begins with a research problem and proceeds to the questions, the data, the data analysis and interpretations, and the research report. Qualitative researchers have found it helpful to see at this point an overall sketch for each of the five approaches.

  14. 9.4 Types of qualitative research designs

    Describe case study research, ethnography, and phenomenology. There are various types of approaches to qualitative research. This chapter presents information about focus groups, which are often used in social work research. It also introduces case studies, ethnography, and phenomenology.

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    Qualitative research designs are research methods that collect and analyze non-numerical data. The research uncovers why or how a particular behavior or occurrence takes place. The information is usually subjective and in a written format instead of numerical. Researchers may use interviews, focus groups, case studies, journaling, and open ...

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    Qualitative Research Design: An Interactive Approach provides researchers and students with a user-friendly, step-by-step guide to planning qualitative research. It shows how the components of design interact with each other, and provides a strategy for creating coherent and workable relationships among these design components, highlighting key design issues.

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    Chapter 2. Research Design Getting Started When I teach undergraduates qualitative research methods, the final product of the course is a "research proposal" that incorporates all they have learned and enlists the knowledge they have learned about qualitative research methods in an original design that addresses a particular research question.

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    Types of qualitative research to explore social behavior or understand interactions within specific contexts include interviews, focus groups, observations and surveys. These identify concepts and relationships that aren't easily observed through quantitative methods.

  19. Qualitative Methods in Health Care Research

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    January 8, 2024 Reviewed by Saul Mcleod, PhD On This Page: Characteristics of Qualitative Research Why Conduct Qualitative Research? Data Collection Data Analysis Preventing Bias Establishing Trustworthiness Advantages Limitations "Not everything that can be counted counts, and not everything that counts can be counted" (Albert Einstein)

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    Text Analysis This method involves analyzing written or spoken language to identify patterns and themes. Text analysis can be quantitative or qualitative. Qualitative text analysis involves close reading and interpretation of texts to identify recurring themes, concepts, and patterns.

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    Qualitative research involves the studied use and collection of a variety of empirical materials - case study, personal experience, introspective, life story, interview, observational, historical, interactional, and visual texts - that describe routine and problematic moments and meanings in individuals' lives.

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    Design. The current study applied an explorative and descriptive qualitative research design. This is appropriate for investigating an unexplored subject descriptively, along with its characteristics [].The study is part of a larger research project [] that developed the digiQUALinPRAX resource.The digiQUALinPRAX resource was co-created with key stakeholders (i.e. student nurses, nurse ...