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Qualitative Research – Methods, Analysis Types and Guide

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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

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.

Also see Research Methods

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Qualitative Data Collection Methods: What it is + Process

If you want to go beyond numbers and really understand how people think and feel, qualitative data collection methods are the way to do it. These methods focus on gathering in-depth insights into the “why” and “how” behind people’s actions and experiences. Instead of just relying on statistics, you get detailed, personal feedback that helps you understand your audience on a deeper level.

Several methods are used to collect qualitative data, including interviews, surveys, focus groups, and observations. Understanding the various methods used for gathering qualitative data is essential for successful qualitative research.

In this blog, we will discuss qualitative data, its processes, and its collection methods.

What is Qualitative Data?

Qualitative data is information that describes and explains something. It can be seen, observed, and written down.

This data type is non-numerical in nature. This type of data is collected through methods of observations, one-to-one interviews, conducting focus groups, and similar methods.

Qualitative data in statistics is also known as categorical data – data that can be arranged categorically based on the attributes and properties of a thing or a phenomenon.

It’s pretty easy to understand the difference between qualitative and quantitative data. Qualitative data does not include numbers in its definition of traits, whereas quantitative research data is all about numbers.

• The cake is orange, blue, and black in color (qualitative).
• Females have brown, black, blonde, and red hair (qualitative).

What Are Qualitative Data Collection Methods?

Qualitative data collection methods are ways to gather information that helps you understand people’s thoughts, feelings, and experiences. Unlike numbers and statistics, this type of data is more about understanding the “why” and “how” behind something. It’s like having a conversation to get deeper insights into what people think or feel.

The data collected through qualitative methods are often subjective, open-ended, and unstructured and can provide a rich understanding of complex social phenomena.

In  statistical analysis , the diffe rence between categorical data and numerical data is essential, as categorical data involves distinct categories or labels, while numerical data consists of measurable quantities.

What is the Need For Qualitative Data Collection?

Qualitative research is a type of study carried out with a qualitative approach to understand the exploratory reasons and to assay how and why a specific program or phenomenon operates in the way it is working. A researcher can access numerous qualitative data collection methods that he/she feels are relevant.

Qualitative data collection methods serve the primary purpose of collecting textual data for research and analysis , like thematic analysis . The collected research data is used to examine:

• Knowledge around a specific issue or a program, experience of people.
• Meaning and relationships.
• Social norms and contextual or cultural practices demean people or impact a cause.

The qualitative data is textual or non-numerical. It covers mostly the images, videos, texts, and written or spoken words by the people. You can opt for any digital data collection methods , like structured or semi-structured surveys, or settle for the traditional approach comprising individual interviews, group discussions, etc.

Are you curious to know about Best Data Collection Tools? QuestionPro recently published a blog about it. Explore it to learn more.

Effective Qualitative Data Collection Methods

Data at hand leads to a smooth process ensuring all the decisions made are for the business’s betterment. You will be able to make informed decisions only if you have relevant data.

Well! With quality data, you will improve the quality of decision-making. You will also improve the quality of the results you expect from any effort.

Qualitative data collection methods are exploratory. Those are usually more focused on gaining insights and understanding the underlying reasons by digging deeper.

Although quantitative data cannot be quantified, measuring it or analyzing qualitative data might become an issue. Due to the lack of measurability, collection methods of qualitative data are primarily unstructured or structured in rare cases – that too to some extent.

Let’s explore the most common methods used for the collection of qualitative data:

Individual interview

It is one of the most trusted, widely used, and familiar qualitative data collection methods primarily because of its approach. An individual or face-to-face interview is a direct conversation between two people with a specific structure and purpose.

The interview questionnaire is designed to elicit the interviewee’s knowledge or perspective related to a topic, program, or issue.

At times, depending on the interviewer’s approach, the conversation can be unstructured or informal but focused on understanding the individual’s beliefs, values, understandings, feelings, experiences, and perspectives on an issue.

More often, the interviewer chooses to ask open-ended questions in individual interviews. If the interviewee selects answers from a set of given options, it becomes a structured, fixed response or a biased discussion.

The individual interview is an ideal qualitative data collection method. Particularly when the researchers want highly personalized information from the participants. The individual interview is a notable method if the interviewer decides to probe further and ask follow-up questions to gain more insights.

Qualitative surveys

To develop an informed hypothesis, many researchers use qualitative research surveys for data collection or to collect a piece of detailed information about a product or an issue. If you want to create questionnaires for collecting textual or qualitative data, then ask more open-ended questions .

To answer such qualitative research questions , the respondent has to write his/her opinion or perspective concerning a specific topic or issue. Unlike other collection methods, online surveys have a wider reach. People can provide you with quality data that is highly credible and valuable.

Paper surveys

Online surveys, focus group discussions.

Focus group discussions can also be considered a type of interview, but it is conducted in a group discussion setting. Usually, the focus group consists of 8 – 10 people (the size may vary depending on the researcher’s requirement). The researchers ensure appropriate space is given to the participants to discuss a topic or issue in a context. The participants are allowed to either agree or disagree with each other’s comments. 

With a focused group discussion, researchers know how a particular group of participants perceives the topic. Researchers analyze what participants think of an issue, the range of opinions expressed, and the ideas discussed. The data is collected by noting down the variations or inconsistencies (if any exist) in the participants, especially in terms of belief, experiences, and practice. 

The participants of focused group discussions are selected based on the topic or issues for which the researcher wants actionable insights. For example, if the research is about the recovery of college students from drug addiction. The participants have to be college students studying and recovering from drug addiction.

Other parameters such as age, qualification, financial background, social presence, and demographics are also considered, but not primarily, as the group needs diverse participants. Frequently, the qualitative data collected through focused group discussion is more descriptive and highly detailed.

Record keeping

This method uses reliable documents and other sources of information that already exist as the data source. This information can help with the new study. It’s a lot like going to the library. There, you can look through books and other sources to find information that can be used in your research.

Case studies

In this method, data is collected by looking at case studies in detail. This method’s flexibility is shown by the fact that it can be used to analyze both simple and complicated topics. This method’s strength is how well it draws conclusions from a mix of one or more qualitative data collection methods.

Observations

Observation is one of the traditional methods of qualitative data collection. It is used by researchers to gather descriptive analysis data by observing people and their behavior at events or in their natural settings. In this method, the researcher fully involves themselves in observing people and taking part in the activities while making notes.

There are two main types of observation:

• Covert: In this method, the observer is concealed without letting anyone know that they are being observed. For example, a researcher studying the rituals of a wedding in nomadic tribes must join them as a guest and quietly see everything. 
• Overt: In this method, everyone is aware that they are being watched. For example, A researcher or an observer wants to study the wedding rituals of a nomadic tribe. To proceed with the research, the observer or researcher can reveal why he is attending the marriage and even use a video camera to shoot everything around him. 

Observation is a useful method of qualitative data collection, especially when you want to study the ongoing process, situation, or reactions on a specific issue related to the people being observed.

When you want to understand people’s behavior or their way of interaction in a particular community or demographic, you can rely on the observation data. Remember, if you fail to get quality data through surveys, qualitative interviews , or group discussions, rely on observation.

It is the best and most trusted collection method of qualitative data to generate qualitative data as it requires equal to no effort from the participants.

Qualitative Data Analysis Process

You invested time and money acquiring your data, so analyze it. It’s necessary to avoid being in the dark after all your hard work. Qualitative data analysis starts with knowing its two basic techniques, but there are no rules.

• Deductive Approach: The deductive data analysis uses a researcher-defined structure to analyze qualitative data. This method is quick and easy when a researcher knows what the sample population will say.
• Inductive Approach: The inductive technique has no structure or framework. When a researcher knows little about the event, an inductive approach is applied.

Whether you want to analyze qualitative data from a one-on-one interview or a survey, these simple steps will ensure a smooth qualitative data analysis.

Step 1: Collect your Data

After collecting all the data, it is mostly unstructured and sometimes unclear. Arranging your data is the first stage in qualitative data analysis. So, researchers must transcribe data before analyzing it.

Step 2: Organize all your Data

After transforming and arranging your data, the next step is to organize it. One of the best ways to organize the data is to think back to your research goals and then organize the data based on the research questions you asked.

Step 3: Set a Code to the Data Collected

Setting up appropriate codes for the collected data gets you one step closer. Coding is one of the most effective methods for compressing a massive amount of data. It allows you to derive theories from relevant research findings.

Step 4: Validate your Data

Qualitative data analysis success requires data validation. Data validation should be done throughout the research process, not just once. There are two sides to validating data:

• The accuracy of your research design or methods.
• Reliability—how well the approaches deliver accurate data.

Step 5: Concluding the Analysis Process

Finally, conclude your data in a presentable report. The report should describe your research methods, their pros and cons, and research limitations. Your report should include findings, inferences, and future research.

QuestionPro is an excellent online survey software that offers a variety of qualitative data analysis tools to help businesses and researchers in making sense of their data. Users can use many different qualitative analysis methods to learn more about their data.

Users of QuestionPro can see their data in different charts and graphs, which makes it easier to spot patterns and trends. It can help researchers and businesses learn more about their target audience, which can lead to better decisions and better results.

Choosing the right software can be tough. Whether you’re a researcher, business leader, or marketer, check out the top 10  qualitative data analysis software  for analyzing qualitative data.

Advantages of Qualitative Data Collection

Qualitative data collection has several advantages, including:

• In-depth understanding: It provides in-depth information about attitudes and behaviors, leading to a deeper understanding of the research.
• Flexibility: The methods allow researchers to modify questions or change direction if new information emerges.
• Contextualization: Qualitative research data is in context, which helps to provide a deep understanding of the experiences and perspectives of individuals.
• Rich data: It often produces rich, detailed, and nuanced information that cannot be captured through numerical data.
• Engagement: The methods, such as interviews and focus groups, involve active meetings with participants, leading to a deeper understanding.
• Multiple perspectives: This can provide various views and a rich array of voices, adding depth and complexity.
• Realistic setting: It often occurs in realistic settings, providing more authentic experiences and behaviors.

Qualitative research methods are best for collecting qualitative data and identifying the behavior and patterns governing social conditions, issues, or topics. It spans a step ahead of quantitative data as it fails to explain the reasons and rationale behind a phenomenon, but qualitative data quickly does. 

Qualitative research is one of the best tools to identify behaviors and patterns governing social conditions. It goes a step beyond quantitative data by providing the reasons and rationale behind a phenomenon that cannot be explored quantitatively.

With QuestionPro, you can use it for qualitative data collection through various methods. Using Our robust suite correctly, you can enhance the quality and integrity of the collected data.

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Frequently Asked Questions (FAQs)

Qualitative methods provide deeper insights than numbers alone. They help you explore complex topics, understand motivations, and gather rich feedback. These methods are especially useful when you need to understand the underlying reasons for people’s actions or preferences.

Choosing the right method depends on your research goals. If you want detailed individual insights, interviews work well. For group dynamics, focus groups are better. If you want to observe natural behavior, observation is ideal. Consider what kind of data will give you the most valuable insights.

Some challenges include managing large amounts of data, ensuring participant honesty, and avoiding researcher bias during analysis. Qualitative research also requires more time and effort compared to quantitative methods, as it involves in-depth interviews and analysis.

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UpMetrics Blog

Expert insights, trends, and best practices around impact measurement and leveraging actionable data to drive meaningful change.

8 Essential Qualitative Data Collection Methods

Qualitative data methods allow you to dive deep into the mindset of your audience to discover areas for growth, development, and improvement. 

British mathematician and marketing mastermind Clive Humby once famously stated that “Data is the new oil.”  He has a point. Without data, nonprofit organizations are left second-guessing what their clients and supporters think, how their brand compares to others in the market, whether their messaging is on-point, how their campaigns are performing, where improvements can be made, and how overall results can be optimized. 

There are two primary data collection methodologies: qualitative data collection and quantitative data collection. At UpMetrics, we believe that just relying on quantitative, static data is no longer an option to drive effective impact. In this guide, we’ll focus on qualitative data collection methods and how they can help you gather, analyze, and collate information that can help drive your organization forward. 

What is Qualitative Data? 

Data collection in qualitative research focuses on gathering contextual information. Unlike quantitative data, which focuses primarily on numbers to establish ‘how many’ or ‘how much,’ qualitative data collection tools allow you to assess the ‘why’s’ and ‘how’s’ behind those statistics. This is vital for nonprofits as it enables organizations to determine:

• Existing knowledge surrounding a particular issue.
• How social norms and cultural practices impact a cause.
• What kind of experiences and interactions people have with your brand.
• Trends in the way people change their opinions.
• Whether meaningful relationships are being established between all parties.

In short, qualitative data collection methods collect perceptual and descriptive information that helps you understand the reasoning and motivation behind particular reactions and behaviors. For that reason, qualitative data methods are usually non-numerical and center around spoken and written words rather than data extrapolated from a spreadsheet or report. 

Qualitative vs. Quantitative Data 

Quantitative and qualitative data represent both sides of the same coin. There will always be some degree of debate over the importance of quantitative vs. qualitative research, data, and collection. However, successful organizations should strive to achieve a balance between the two. 

Organizations can track their performance by collecting quantitative data based on metrics including dollars raised, membership growth, number of people served, overhead costs, etc. This is all essential information to have. However, the data lacks value without the additional details provided by qualitative research because it doesn’t tell you anything about how your target audience thinks, feels, and acts. 

Qualitative data collection is particularly relevant in the nonprofit sector as the relationships people have with the causes they support are fundamentally personal and cannot be expressed numerically. Qualitative data methods allow you to deep dive into the mindset of your audience to discover areas for growth, development, and improvement. 

8 Types of Qualitative Data Collection Methods  

As we have firmly established the need for qualitative data, it’s time to answer the next big question: how to collect qualitative data. 

Here is a list of the most common qualitative data collection methods. You don’t need to use them all in your quest for gathering information. However, a foundational understanding of each will help you refine your research strategy and select the methods that are likely to provide the highest quality business intelligence for your organization. 

1. Interviews

One-on-one interviews are one of the most commonly used data collection methods in qualitative research because they allow you to collect highly personalized information directly from the source. Interviews explore participants' opinions, motivations, beliefs, and experiences and are particularly beneficial in gathering data on sensitive topics because respondents are more likely to open up in a one-on-one setting than in a group environment. 

Interviews can be conducted in person or by online video call. Typically, they are separated into three main categories:

• Structured Interviews - Structured interviews consist of predetermined (and usually closed) questions with little or no variation between interviewees. There is generally no scope for elaboration or follow-up questions, making them better suited to researching specific topics. 
• Unstructured Interviews – Conversely, unstructured interviews have little to no organization or preconceived topics and include predominantly open questions. As a result, the discussion will flow in completely different directions for each participant and can be very time-consuming. For this reason, unstructured interviews are generally only used when little is known about the subject area or when in-depth responses are required on a particular subject.
• Semi-Structured Interviews – A combination of the two interviews mentioned above, semi-structured interviews comprise several scripted questions but allow both interviewers and interviewees the opportunity to diverge and elaborate so more in-depth reasoning can be explored. 

While each approach has its merits, semi-structured interviews are typically favored as a way to uncover detailed information in a timely manner while highlighting areas that may not have been considered relevant in previous research efforts. Whichever type of interview you utilize, participants must be fully briefed on the format, purpose, and what you hope to achieve. With that in mind, here are a few tips to follow: 

• Give them an idea of how long the interview will last
• If you plan to record the conversation, ask permission beforehand
• Provide the opportunity to ask questions before you begin and again at the end. 

2. Focus Groups

Focus groups share much in common with less structured interviews, the key difference being that the goal is to collect data from several participants simultaneously. Focus groups are effective in gathering information based on collective views and are one of the most popular data collection instruments in qualitative research when a series of one-on-one interviews proves too time-consuming or difficult to schedule. 

Focus groups are most helpful in gathering data from a specific group of people, such as donors or clients from a particular demographic. The discussion should be focused on a specific topic and carefully guided and moderated by the researcher to determine participant views and the reasoning behind them. 

Feedback in a group setting often provides richer data than one-on-one interviews, as participants are generally more open to sharing when others are sharing too. Plus, input from one participant may spark insight from another that would not have come to light otherwise. However, here are a couple of potential downsides:

• If participants are uneasy with each other, they may not be at ease openly discussing their feelings or opinions.
• If the topic is not of interest or does not focus on something participants are willing to discuss, data will lack value. 

The size of the group should be carefully considered. Research suggests over-recruiting to avoid risking cancellation, even if that means moderators have to manage more participants than anticipated. The optimum group size is generally between six and eight for all participants to be granted ample opportunity to speak. However, focus groups can still be successful with as few as three or as many as fourteen participants. 

3. Observation

Observation is one of the ultimate data collection tools in qualitative research for gathering information through subjective methods. A technique used frequently by modern-day marketers, qualitative observation is also favored by psychologists, sociologists, behavior specialists, and product developers. 

The primary purpose is to gather information that cannot be measured or easily quantified. It involves virtually no cognitive input from the participants themselves. Researchers simply observe subjects and their reactions during the course of their regular routines and take detailed field notes from which to draw information. 

Observational techniques vary in terms of contact with participants. Some qualitative observations involve the complete immersion of the researcher over a period of time. For example, attending the same church, clinic, society meetings, or volunteer organizations as the participants. Under these circumstances, researchers will likely witness the most natural responses rather than relying on behaviors elicited in a simulated environment. Depending on the study and intended purpose, they may or may not choose to identify themselves as a researcher during the process. 

Regardless of whether you take a covert or overt approach, remember that because each researcher is as unique as every participant, they will have their own inherent biases. Therefore, observational studies are prone to a high degree of subjectivity. For example, one researcher’s notes on the behavior of donors at a society event may vary wildly from the next. So, each qualitative observational study is unique in its own right. 

4. Open-Ended Surveys and Questionnaires

Open-ended surveys and questionnaires allow organizations to collect views and opinions from respondents without meeting in person. They can be sent electronically and are considered one of the most cost-effective qualitative data collection tools. Unlike closed question surveys and questionnaires that limit responses, open-ended questions allow participants to provide lengthy and in-depth answers from which you can extrapolate large amounts of data. 

The findings of open-ended surveys and questionnaires can be challenging to analyze because there are no uniform answers. A popular approach is to record sentiments as positive, negative, and neutral and further dissect the data from there. To gather the best business intelligence, carefully consider the presentation and length of your survey or questionnaire. Here is a list of essential considerations:

• Number of questions : Too many can feel intimidating, and you’ll experience low response rates. Too few can feel like it’s not worth the effort. Plus, the data you collect will have limited actionability. The consensus on how many questions to include varies depending on which sources you consult. However, 5-10 is a good benchmark for shorter surveys that take around 10 minutes and 15-20 for longer surveys that take approximately 20 minutes to complete. 
• Personalization: Your response rate will be higher if you greet patients by name and demonstrate a historical knowledge of their interactions with your brand. 
• Visual elements : Recipients can be easily turned off by poorly designed questionnaires. Besides, it’s a good idea to customize your survey template to include brand assets like colors, logos, and fonts to increase brand loyalty and recognition.
• Reminders : Sending survey reminders is the best way to improve your response rate. You don’t want to hassle respondents too soon, nor do you want to wait too long. Sending a follow-up at around the 3-7 mark is usually the most effective. 
• Building a feedback loop : Adding a tick-box requesting permission for further follow-ups is a proven way to elicit more in-depth feedback. Plus, it gives respondents a voice and makes their opinion feel valued.

5. Case Studies

Case studies are often a preferred method of qualitative research data collection for organizations looking to generate incredibly detailed and in-depth information on a specific topic. Case studies are usually a deep dive into one specific case or a small number of related cases. As a result, they work well for organizations that operate in niche markets.

Case studies typically involve several qualitative data collection methods, including interviews, focus groups, surveys, and observation. The idea is to cast a wide net to obtain a rich picture comprising multiple views and responses. When conducted correctly, case studies can generate vast bodies of data that can be used to improve processes at every client and donor touchpoint. 

The best way to demonstrate the purpose and value of a case study is with an example: A Longitudinal Qualitative Case Study of Change in Nonprofits – Suggesting A New Approach to the Management of Change . 

The researchers established that while change management had already been widely researched in commercial and for-profit settings, little reference had been made to the unique challenges in the nonprofit sector. The case study examined change and change management at a single nonprofit hospital from the viewpoint of all those who witnessed and experienced it. To gain a holistic view of the entire process, research included interviews with employees at every level, from nursing staff to CEOs, to identify the direct and indirect impacts of change. Results were collated based on detailed responses to questions about preparing for change, experiencing change, and reflecting on change.

6. Text Analysis

Text analysis has long been used in political and social science spheres to gain a deeper understanding of behaviors and motivations by gathering insights from human-written texts. By analyzing the flow of text and word choices, relationships between other texts written by the same participant can be identified so that researchers can draw conclusions about the mindset of their target audience. Though technically a qualitative data collection method, the process can involve some quantitative elements, as often, computer systems are used to scan, extract, and categorize information to identify patterns, sentiments, and other actionable information. 

You might be wondering how to collect written information from your research subjects. There are many different options, and approaches can be overt or covert. 

Examples include:

• Investigating how often certain cause-related words and phrases are used in client and donor social media posts.
• Asking participants to keep a journal or diary.
• Analyzing existing interview transcripts and survey responses.

By conducting a detailed analysis, you can connect elements of written text to specific issues, causes, and cultural perspectives, allowing you to draw empirical conclusions about personal views, behaviors, and social relations. With small studies focusing on participants' subjective experience on a specific theme or topic, diaries and journals can be particularly effective in building an understanding of underlying thought processes and beliefs. 

7. Audio and Video Recordings

Similarly to how data is collected from a person’s writing, you can draw valuable conclusions by observing someone’s speech patterns, intonation, and body language when you watch or listen to them interact in a particular environment or within specific surroundings. 

Video and audio recordings are helpful in circumstances where researchers predict better results by having participants be in the moment rather than having them think about what to write down or how to formulate an answer to an email survey. 

You can collect audio and video materials for analysis from multiple sources, including:

• Previously filmed records of events
• Interview recordings
• Video diaries

Utilizing audio and video footage allows researchers to revisit key themes, and it's possible to use the same analytical sources in multiple studies – providing that the scope of the original recording is comprehensive enough to cover the intended theme in adequate depth. 

It can be challenging to present the results of audio and video analysis in a quantifiable form that helps you gauge campaign and market performance. However, results can be used to effectively design concept maps that extrapolate central themes that arise consistently. Concept Mapping offers organizations a visual representation of thought patterns and how ideas link together between different demographics. This data can prove invaluable in identifying areas for improvement and change across entire projects and organizational processes. 

8. Hybrid Methodologies

It is often possible to utilize data collection methods in qualitative research that provide quantitative facts and figures. So if you’re struggling to settle on an approach, a hybrid methodology may be a good starting point. For instance, a survey format that asks closed and open questions can collect and collate quantitative and qualitative data. 

A Net Promoter Score (NPS) survey is a great example. The primary goal of an NPS survey is to collect quantitative ratings of various factors on a score of 1-10. However, they also utilize open-ended follow-up questions to collect qualitative data that helps identify insights into the trends, thought processes, reasoning, and behaviors behind the initial scoring. 

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Understanding the Meaning of Qualitative Research: Definition & Methods

Dive into the world of qualitative research with this insightful article that unpacks its definition, explores various methodologies, and highlights its significance in uncovering deep, nuanced insights beyond numbers..

Defining Qualitative Research

Qualitative research is a method of inquiry that focuses on understanding the meaning and experience behind various phenomena. It seeks to gain insights into specific behaviors, emotions, and thoughts by gathering non-numerical data. This approach often contrasts with quantitative research, which relies heavily on statistical analyses and numerical data to arrive at conclusions.

The essence of qualitative research lies in its depth and complexity. Researchers typically aim to comprehend not just “what” occurs, but also “how” and “why” certain phenomena manifest. By utilizing diverse methods such as interviews, observations, and textual analysis, qualitative research can reveal insights that statistical data might overlook. For instance, in studying consumer behavior, qualitative methods can uncover the motivations behind purchasing decisions, providing a richer context that numbers alone cannot convey. This nuanced understanding is invaluable for fields such as marketing, psychology, and sociology, where human behavior is central.

The Core Principles of Qualitative Research

One of the fundamental principles of qualitative research is that reality is subjective and constructed through social interactions. As such, qualitative researchers prioritize the perspectives and experiences of individuals within specific contexts. They recognize that an individual’s reality can vary based on cultural, social, and personal factors. This principle encourages researchers to adopt a reflexive approach, being aware of their biases and how these may influence the research process. By doing so, they can better appreciate the complexities of the human experience and ensure that their findings reflect the voices of the participants authentically.

Another principle is the commitment to a holistic understanding of the research subject. It focuses on the intricacies of human experiences, capturing the richness and variety of those experiences. This often means engaging with subjects in their natural environment, allowing for a more authentic view of their situations. For example, ethnographic studies may involve researchers immersing themselves in a community to observe and participate in daily life, thereby gaining insights that are often missed in more structured research settings. Such immersive techniques not only deepen the understanding of the subject matter but also foster a sense of trust and rapport between the researcher and participants, enhancing the quality of the data collected.

Key Terminology in Qualitative Research

Familiarity with key terms is crucial when navigating qualitative research. One of these terms is "data saturation," which refers to the point where additional data collection yields little to no new information. Reaching data saturation typically signifies that the researcher has comprehensively explored the research questions. It is a critical milestone that helps researchers determine the adequacy of their sample size and the richness of the data collected, ensuring that the findings are robust and well-supported.

Another key term is “phenomenology,” which studies individuals’ experiences, particularly concerning specific phenomena. This approach emphasizes the subjective nature of experience and seeks to understand how individuals make sense of their lived experiences. Understanding these terms and concepts helps researchers communicate their findings effectively, enhancing the overall rigor of qualitative research. Additionally, terms like "grounded theory" and "narrative analysis" further enrich the vocabulary of qualitative research, each representing unique methodologies that contribute to the diverse landscape of qualitative inquiry. By mastering this terminology, researchers can articulate their methodologies and findings with clarity, fostering a deeper engagement with their audience and the broader academic community.

The Importance of Qualitative Research

Qualitative research plays a significant role in several fields, including social sciences, healthcare, education, and market research. It is particularly valuable when exploring complex issues requiring in-depth understanding, such as cultural practices, social dynamics, or customer experiences.

The insights gleaned from qualitative research can inform policy-making, improve practice, and drive innovation. By providing a deeper understanding of the human experience, qualitative research can significantly influence how services are designed and delivered. Moreover, it fosters critical thinking and reflection among researchers and practitioners alike.

Benefits of Qualitative Research

One major benefit of qualitative research is its ability to uncover nuances that quantitative research may not reveal. It allows for exploration of attitudes, motivations, and feelings, leading to a richer understanding of the subject matter. This depth of insight can inform strategies that better align with individuals’ needs.

Furthermore, qualitative research is flexible, accommodating changes in direction as new insights emerge. This adaptability can lead to unexpected discoveries that enhance the research outcome significantly, making it a dynamic and engaging process.

Limitations of Qualitative Research

Despite its strengths, qualitative research does have limitations. One prominent challenge is subjectivity, as researchers’ biases may influence data collection and interpretation. Consequently, it is essential to maintain reflexivity throughout the research process to mitigate potential biases.

Moreover, generalizability can be an issue. Due to the typically smaller sample sizes and context-specific nature of qualitative studies, findings may not be easily extrapolated to broader populations. Recognizing these limitations is crucial for framing and contextualizing research outcomes effectively.

Different Methods in Qualitative Research

Qualitative research comprises various methodologies, each with unique strengths, characteristics, and applications. The choice of a method often depends on the research question, objectives, and the environment in which the study is conducted.

This section explores several prevalent methods that researchers may use to conduct qualitative investigations, illustrating the diversity and adaptability inherent in qualitative research.

Interviews and Focus Groups

Interviews are among the most popular qualitative research methods. They can be structured, semi-structured, or unstructured, allowing researchers to probe deeply into participants’ thoughts and experiences. The personal nature of interviews means they often yield rich, detailed data.

Focus groups also play a crucial role in qualitative research. In this method, a facilitated discussion among a group of participants provides insights into shared experiences and collective opinions. This interactive setting fosters dynamic discussions that can surface varying perspectives and spark new ideas.

Observations and Ethnography

Observation involves watching and recording behavior in natural settings, allowing researchers to gather contextual information that could be missed through verbal methods. Ethnography extends this approach, requiring extended immersion in the culture or environment being studied. This deep engagement yields rich data on social interactions, norms, and practices.

Both methods are incredibly effective for capturing real-world dynamics and complexities, helping researchers to understand phenomena in their natural context.

Textual and Content Analysis

Textual analysis focuses on examining written or spoken content to interpret meaning and context. Researchers analyze various texts—such as interviews, papers, and social media content—to uncover themes and patterns that provide insights into societal issues or behaviors.

Content analysis, while somewhat similar, quantitatively evaluates the presence of certain words, themes, or concepts within qualitative data. By combining qualitative and quantitative approaches, researchers can yield a more comprehensive understanding of the messages conveyed in the content being analyzed.

Choosing the Right Method for Your Research

Selecting the appropriate qualitative method is crucial for the success of a research project. Multiple factors come into play, including the research question, objectives, and available resources. Each method has its strengths and weaknesses, and understanding these helps in making an informed choice.

Factors to Consider When Selecting a Method

When choosing a method, consider the nature of your research question. If your focus is on individual experiences or personal narratives, semi-structured interviews or ethnography might be most suitable. Conversely, if you aim to explore group dynamics, focus groups may be more effective.

Additionally, the available resources, including time and expertise, should guide your selection. Some methods, like ethnography, require significant time and commitment, while others, like interviews, may be more manageable within tighter timelines.

Aligning Your Research Question with Your Method

It's essential that your chosen method aligns well with your research question. When this alignment is achieved, the collected data will be more relevant and meaningful. Engaging in preliminary reviews of literature can help clarify what methods have worked effectively in similar studies, guiding your decision-making process.

This careful alignment ensures that your qualitative research can effectively address the nuances of your questions, leading to more impactful conclusions and practical applications.

Analyzing Qualitative Data

After data collection, the analysis phase is where qualitative research truly transforms into knowledge. This is a critical stage where patterns are identified, themes are developed, and interpretations are constructed. Various strategies exist for analyzing qualitative data, each designed to illuminate specific aspects of the information gathered.

Thematic Analysis

Thematic analysis is one of the most commonly used methods in qualitative research. Researchers identify recurring themes across the dataset, allowing them to understand key insights relevant to the research question. This method provides flexibility and can be applied to a variety of qualitative data forms.

To conduct thematic analysis effectively, researchers must be systematic in their approach, allowing for detailed coding and categorization that ultimately reveals the nuances of the data.

Grounded Theory

Grounded theory is an approach particularly valuable in exploring new areas of inquiry. This analytic method involves developing theories based directly on the data collected, rather than starting with a pre-existing hypothesis. Researchers iteratively analyze data, often developing multiple rounds of coding to establish patterns and theoretical insights.

This approach is particularly effective in areas where existing theories may not adequately explain the phenomena under investigation, making it a powerful tool for discovering novel insights.

Narrative Analysis

Narrative analysis focuses on understanding the stories individuals tell about their experiences. By analyzing how narratives are constructed, researchers can gain insights into the meanings individuals ascribe to their lives and experiences. This method highlights the power of storytelling and the significance of context in shaping narratives.

By employing narrative analysis, researchers can uncover rich layers of meaning that deepen their understanding of human experiences, making it a compelling approach in qualitative research.

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• Introduction

Qualitative research is a type of research that explores and provides deeper insights into real-world problems. [1] Instead of collecting numerical data points or intervening or introducing treatments just like in quantitative research, qualitative research helps generate hypothenar to further investigate and understand quantitative data. Qualitative research gathers participants' experiences, perceptions, and behavior. It answers the hows and whys instead of how many or how much. It could be structured as a standalone study, purely relying on qualitative data, or part of mixed-methods research that combines qualitative and quantitative data. This review introduces the readers to some basic concepts, definitions, terminology, and applications of qualitative research.

Qualitative research, at its core, asks open-ended questions whose answers are not easily put into numbers, such as "how" and "why." [2] Due to the open-ended nature of the research questions, qualitative research design is often not linear like quantitative design. [2] One of the strengths of qualitative research is its ability to explain processes and patterns of human behavior that can be difficult to quantify. [3] Phenomena such as experiences, attitudes, and behaviors can be complex to capture accurately and quantitatively. In contrast, a qualitative approach allows participants themselves to explain how, why, or what they were thinking, feeling, and experiencing at a particular time or during an event of interest. Quantifying qualitative data certainly is possible, but at its core, qualitative data is looking for themes and patterns that can be difficult to quantify, and it is essential to ensure that the context and narrative of qualitative work are not lost by trying to quantify something that is not meant to be quantified.

However, while qualitative research is sometimes placed in opposition to quantitative research, where they are necessarily opposites and therefore "compete" against each other and the philosophical paradigms associated with each other, qualitative and quantitative work are neither necessarily opposites, nor are they incompatible. [4] While qualitative and quantitative approaches are different, they are not necessarily opposites and certainly not mutually exclusive. For instance, qualitative research can help expand and deepen understanding of data or results obtained from quantitative analysis. For example, say a quantitative analysis has determined a correlation between length of stay and level of patient satisfaction, but why does this correlation exist? This dual-focus scenario shows one way in which qualitative and quantitative research could be integrated.

Qualitative Research Approaches

Ethnography

Ethnography as a research design originates in social and cultural anthropology and involves the researcher being directly immersed in the participant’s environment. [2] Through this immersion, the ethnographer can use a variety of data collection techniques to produce a comprehensive account of the social phenomena that occurred during the research period. [2] That is to say, the researcher’s aim with ethnography is to immerse themselves into the research population and come out of it with accounts of actions, behaviors, events, etc, through the eyes of someone involved in the population. Direct involvement of the researcher with the target population is one benefit of ethnographic research because it can then be possible to find data that is otherwise very difficult to extract and record.

Grounded theory

Grounded Theory is the "generation of a theoretical model through the experience of observing a study population and developing a comparative analysis of their speech and behavior." [5] Unlike quantitative research, which is deductive and tests or verifies an existing theory, grounded theory research is inductive and, therefore, lends itself to research aimed at social interactions or experiences. [3] [2] In essence, Grounded Theory’s goal is to explain how and why an event occurs or how and why people might behave a certain way. Through observing the population, a researcher using the Grounded Theory approach can then develop a theory to explain the phenomena of interest.

Phenomenology

Phenomenology is the "study of the meaning of phenomena or the study of the particular.” [5] At first glance, it might seem that Grounded Theory and Phenomenology are pretty similar, but the differences can be seen upon careful examination. At its core, phenomenology looks to investigate experiences from the individual's perspective. [2] Phenomenology is essentially looking into the "lived experiences" of the participants and aims to examine how and why participants behaved a certain way from their perspective. Herein lies one of the main differences between Grounded Theory and Phenomenology. Grounded Theory aims to develop a theory for social phenomena through an examination of various data sources. In contrast, Phenomenology focuses on describing and explaining an event or phenomenon from the perspective of those who have experienced it.

Narrative research

One of qualitative research’s strengths lies in its ability to tell a story, often from the perspective of those directly involved in it. Reporting on qualitative research involves including details and descriptions of the setting involved and quotes from participants. This detail is called a "thick" or "rich" description and is a strength of qualitative research. Narrative research is rife with the possibilities of "thick" description as this approach weaves together a sequence of events, usually from just one or two individuals, hoping to create a cohesive story or narrative. [2] While it might seem like a waste of time to focus on such a specific, individual level, understanding one or two people’s narratives for an event or phenomenon can help to inform researchers about the influences that helped shape that narrative. The tension or conflict of differing narratives can be "opportunities for innovation." [2]

Research Paradigm

Research paradigms are the assumptions, norms, and standards underpinning different research approaches. Essentially, research paradigms are the "worldviews" that inform research. [4] It is valuable for qualitative and quantitative researchers to understand what paradigm they are working within because understanding the theoretical basis of research paradigms allows researchers to understand the strengths and weaknesses of the approach being used and adjust accordingly. Different paradigms have different ontologies and epistemologies. Ontology is defined as the "assumptions about the nature of reality,” whereas epistemology is defined as the "assumptions about the nature of knowledge" that inform researchers' work. [2] It is essential to understand the ontological and epistemological foundations of the research paradigm researchers are working within to allow for a complete understanding of the approach being used and the assumptions that underpin the approach as a whole. Further, researchers must understand their own ontological and epistemological assumptions about the world in general because their assumptions about the world will necessarily impact how they interact with research. A discussion of the research paradigm is not complete without describing positivist, postpositivist, and constructivist philosophies.

Positivist versus postpositivist

To further understand qualitative research, we must discuss positivist and postpositivist frameworks. Positivism is a philosophy that the scientific method can and should be applied to social and natural sciences. [4] Essentially, positivist thinking insists that the social sciences should use natural science methods in their research. It stems from positivist ontology, that there is an objective reality that exists that is wholly independent of our perception of the world as individuals. Quantitative research is rooted in positivist philosophy, which can be seen in the value it places on concepts such as causality, generalizability, and replicability.

Conversely, postpositivists argue that social reality can never be one hundred percent explained, but could be approximated. [4] Indeed, qualitative researchers have been insisting that there are “fundamental limits to the extent to which the methods and procedures of the natural sciences could be applied to the social world,” and therefore, postpositivist philosophy is often associated with qualitative research. [4] An example of positivist versus postpositivist values in research might be that positivist philosophies value hypothesis-testing, whereas postpositivist philosophies value the ability to formulate a substantive theory.

Constructivist

Constructivism is a subcategory of postpositivism. Most researchers invested in postpositivist research are also constructivist, meaning they think there is no objective external reality that exists but instead that reality is constructed. Constructivism is a theoretical lens that emphasizes the dynamic nature of our world. "Constructivism contends that individuals' views are directly influenced by their experiences, and it is these individual experiences and views that shape their perspective of reality.” [6]  constructivist thought focuses on how "reality" is not a fixed certainty and how experiences, interactions, and backgrounds give people a unique view of the world. Constructivism contends, unlike positivist views, that there is not necessarily an "objective"reality we all experience. This is the ‘relativist’ ontological view that reality and our world are dynamic and socially constructed. Therefore, qualitative scientific knowledge can be inductive as well as deductive.” [4]

So why is it important to understand the differences in assumptions that different philosophies and approaches to research have? Fundamentally, the assumptions underpinning the research tools a researcher selects provide an overall base for the assumptions the rest of the research will have. It can even change the role of the researchers. [2] For example, is the researcher an "objective" observer, such as in positivist quantitative work? Or is the researcher an active participant in the research, as in postpositivist qualitative work? Understanding the philosophical base of the study undertaken allows researchers to fully understand the implications of their work and their role within the research and reflect on their positionality and bias as it pertains to the research they are conducting.

Data Sampling 

The better the sample represents the intended study population, the more likely the researcher is to encompass the varying factors. The following are examples of participant sampling and selection: [7]

• Purposive sampling- selection based on the researcher’s rationale for being the most informative.
• Criterion sampling selection based on pre-identified factors.
• Convenience sampling- selection based on availability.
• Snowball sampling- the selection is by referral from other participants or people who know potential participants.
• Extreme case sampling- targeted selection of rare cases.
• Typical case sampling selection based on regular or average participants. 

Data Collection and Analysis

Qualitative research uses several techniques, including interviews, focus groups, and observation. [1] [2] [3] Interviews may be unstructured, with open-ended questions on a topic, and the interviewer adapts to the responses. Structured interviews have a predetermined number of questions that every participant is asked. It is usually one-on-one and appropriate for sensitive topics or topics needing an in-depth exploration. Focus groups are often held with 8-12 target participants and are used when group dynamics and collective views on a topic are desired. Researchers can be participant-observers to share the experiences of the subject or non-participants or detached observers.

While quantitative research design prescribes a controlled environment for data collection, qualitative data collection may be in a central location or the participants' environment, depending on the study goals and design. Qualitative research could amount to a large amount of data. Data is transcribed, which may then be coded manually or using computer-assisted qualitative data analysis software or CAQDAS such as ATLAS.ti or NVivo. [8] [9] [10]

After the coding process, qualitative research results could be in various formats. It could be a synthesis and interpretation presented with excerpts from the data. [11] Results could also be in the form of themes and theory or model development.

Dissemination

The healthcare team can use two reporting standards to standardize and facilitate the dissemination of qualitative research outcomes. The Consolidated Criteria for Reporting Qualitative Research or COREQ is a 32-item checklist for interviews and focus groups. [12] The Standards for Reporting Qualitative Research (SRQR) is a checklist covering a more comprehensive range of qualitative research. [13]

Applications

Many times, a research question will start with qualitative research. The qualitative research will help generate the research hypothesis, which can be tested with quantitative methods. After the data is collected and analyzed with quantitative methods, a set of qualitative methods can be used to dive deeper into the data to better understand what the numbers truly mean and their implications. The qualitative techniques can then help clarify the quantitative data and also help refine the hypothesis for future research. Furthermore, with qualitative research, researchers can explore poorly studied subjects with quantitative methods. These include opinions, individual actions, and social science research.

An excellent qualitative study design starts with a goal or objective. This should be clearly defined or stated. The target population needs to be specified. A method for obtaining information from the study population must be carefully detailed to ensure no omissions of part of the target population. A proper collection method should be selected that will help obtain the desired information without overly limiting the collected data because, often, the information sought is not well categorized or obtained. Finally, the design should ensure adequate methods for analyzing the data. An example may help better clarify some of the various aspects of qualitative research.

A researcher wants to decrease the number of teenagers who smoke in their community. The researcher could begin by asking current teen smokers why they started smoking through structured or unstructured interviews (qualitative research). The researcher can also get together a group of current teenage smokers and conduct a focus group to help brainstorm factors that may have prevented them from starting to smoke (qualitative research).

In this example, the researcher has used qualitative research methods (interviews and focus groups) to generate a list of ideas of why teens start to smoke and factors that may have prevented them from starting to smoke. Next, the researcher compiles this data. The research found that, hypothetically, peer pressure, health issues, cost, being considered "cool," and rebellious behavior all might increase or decrease the likelihood of teens starting to smoke.

The researcher creates a survey asking teen participants to rank how important each of the above factors is in either starting smoking (for current smokers) or not smoking (for current nonsmokers). This survey provides specific numbers (ranked importance of each factor) and is thus a quantitative research tool.

The researcher can use the survey results to focus efforts on the one or two highest-ranked factors. Let us say the researcher found that health was the primary factor that keeps teens from starting to smoke, and peer pressure was the primary factor that contributed to teens starting smoking. The researcher can go back to qualitative research methods to dive deeper into these for more information. The researcher wants to focus on keeping teens from starting to smoke, so they focus on the peer pressure aspect.

The researcher can conduct interviews and focus groups (qualitative research) about what types and forms of peer pressure are commonly encountered, where the peer pressure comes from, and where smoking starts. The researcher hypothetically finds that peer pressure often occurs after school at the local teen hangouts, mostly in the local park. The researcher also hypothetically finds that peer pressure comes from older, current smokers who provide the cigarettes.

The researcher could further explore this observation made at the local teen hangouts (qualitative research) and take notes regarding who is smoking, who is not, and what observable factors are at play for peer pressure to smoke. The researcher finds a local park where many local teenagers hang out and sees that the smokers tend to hang out in a shady, overgrown area of the park. The researcher notes that smoking teenagers buy their cigarettes from a local convenience store adjacent to the park, where the clerk does not check identification before selling cigarettes. These observations fall under qualitative research.

If the researcher returns to the park and counts how many individuals smoke in each region, this numerical data would be quantitative research. Based on the researcher's efforts thus far, they conclude that local teen smoking and teenagers who start to smoke may decrease if there are fewer overgrown areas of the park and the local convenience store does not sell cigarettes to underage individuals.

The researcher could try to have the parks department reassess the shady areas to make them less conducive to smokers or identify how to limit the sales of cigarettes to underage individuals by the convenience store. The researcher would then cycle back to qualitative methods of asking at-risk populations their perceptions of the changes and what factors are still at play, and quantitative research that includes teen smoking rates in the community and the incidence of new teen smokers, among others. [14] [15]

Qualitative research functions as a standalone research design or combined with quantitative research to enhance our understanding of the world. Qualitative research uses techniques including structured and unstructured interviews, focus groups, and participant observation not only to help generate hypotheses that can be more rigorously tested with quantitative research but also to help researchers delve deeper into the quantitative research numbers, understand what they mean, and understand what the implications are. Qualitative research allows researchers to understand what is going on, especially when things are not easily categorized. [16]

• Issues of Concern

As discussed in the sections above, quantitative and qualitative work differ in many ways, including the evaluation criteria. There are four well-established criteria for evaluating quantitative data: internal validity, external validity, reliability, and objectivity. Credibility, transferability, dependability, and confirmability are the correlating concepts in qualitative research. [4] [11] The corresponding quantitative and qualitative concepts can be seen below, with the quantitative concept on the left and the qualitative concept on the right:

• Internal validity: Credibility
• External validity: Transferability
• Reliability: Dependability
• Objectivity: Confirmability

In conducting qualitative research, ensuring these concepts are satisfied and well thought out can mitigate potential issues from arising. For example, just as a researcher will ensure that their quantitative study is internally valid, qualitative researchers should ensure that their work has credibility. 

Indicators such as triangulation and peer examination can help evaluate the credibility of qualitative work.

• Triangulation: Triangulation involves using multiple data collection methods to increase the likelihood of getting a reliable and accurate result. In our above magic example, the result would be more reliable if we interviewed the magician, backstage hand, and the person who "vanished." In qualitative research, triangulation can include telephone surveys, in-person surveys, focus groups, and interviews and surveying an adequate cross-section of the target demographic.
• Peer examination: A peer can review results to ensure the data is consistent with the findings.

A "thick" or "rich" description can be used to evaluate the transferability of qualitative research, whereas an indicator such as an audit trail might help evaluate the dependability and confirmability.

• Thick or rich description:  This is a detailed and thorough description of details, the setting, and quotes from participants in the research. [5] Thick descriptions will include a detailed explanation of how the study was conducted. Thick descriptions are detailed enough to allow readers to draw conclusions and interpret the data, which can help with transferability and replicability.
• Audit trail: An audit trail provides a documented set of steps of how the participants were selected and the data was collected. The original information records should also be kept (eg, surveys, notes, recordings).

One issue of concern that qualitative researchers should consider is observation bias. Here are a few examples:

• Hawthorne effect: The effect is the change in participant behavior when they know they are being observed. Suppose a researcher wanted to identify factors that contribute to employee theft and tell the employees they will watch them to see what factors affect employee theft. In that case, one would suspect employee behavior would change when they know they are being protected.
• Observer-expectancy effect: Some participants change their behavior or responses to satisfy the researcher's desired effect. This happens unconsciously for the participant, so it is essential to eliminate or limit the transmission of the researcher's views.
• Artificial scenario effect: Some qualitative research occurs in contrived scenarios with preset goals. In such situations, the information may not be accurate because of the artificial nature of the scenario. The preset goals may limit the qualitative information obtained.
• Clinical Significance

Qualitative or quantitative research helps healthcare providers understand patients and the impact and challenges of the care they deliver. Qualitative research provides an opportunity to generate and refine hypotheses and delve deeper into the data generated by quantitative research. Qualitative research is not an island apart from quantitative research but an integral part of research methods to understand the world around us. [17]

• Enhancing Healthcare Team Outcomes

Qualitative research is essential for all healthcare team members as all are affected by qualitative research. Qualitative research may help develop a theory or a model for health research that can be further explored by quantitative research. Much of the qualitative research data acquisition is completed by numerous team members, including social workers, scientists, nurses, etc. Within each area of the medical field, there is copious ongoing qualitative research, including physician-patient interactions, nursing-patient interactions, patient-environment interactions, healthcare team function, patient information delivery, etc. 

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Disclosure: Steven Tenny declares no relevant financial relationships with ineligible companies.

Disclosure: Janelle Brannan declares no relevant financial relationships with ineligible companies.

Disclosure: Grace Brannan declares no relevant financial relationships with ineligible companies.

This book is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ), which permits others to distribute the work, provided that the article is not altered or used commercially. You are not required to obtain permission to distribute this article, provided that you credit the author and journal.

• Cite this Page Tenny S, Brannan JM, Brannan GD. Qualitative Study. [Updated 2022 Sep 18]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.

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The Ultimate Guide to Qualitative Research - Part 1: The Basics

• Introduction and overview

Basics of qualitative research

Types, aspects, examples, benefits and challenges, how qualitative research complements quantitative research, how is qualitative research reported.

• What is qualitative data?
• Examples of qualitative data
• Qualitative vs. quantitative research
• Mixed methods
• Qualitative research preparation
• Theoretical perspective
• Theoretical framework
• Literature reviews
• Research question
• Conceptual framework
• Conceptual vs. theoretical framework
• Data collection
• Qualitative research methods
• Focus groups
• Observational research
• Case studies
• Ethnographical research

Ethical considerations

• Confidentiality and privacy
• Power dynamics
• Reflexivity

What is qualitative research?

Qualitative research is an essential approach in various academic disciplines and professional fields, as it seeks to understand and interpret the meanings, experiences, and social realities of people in their natural settings. This type of research employs an array of qualitative methods to gather and analyze non-numerical data, such as words, images, and behaviors, and aims to generate in-depth and contextualized insights into the phenomena under study.

Qualitative research is designed to address research questions that focus on understanding the "why" and "how" of human behavior, experiences, and interactions, rather than just the "what" or "how many" that quantitative methods typically seek to answer. The main purpose of qualitative research is to gain a rich and nuanced understanding of people's perspectives, emotions, beliefs, and motivations in relation to specific issues, situations, or phenomena.

Characteristics of qualitative research

Several key characteristics distinguish qualitative research from other types of research, such as quantitative research:

Naturalistic settings : Qualitative researchers collect data in the real-world settings where the phenomena of interest occur, rather than in controlled laboratory environments. This allows researchers to observe and understand the participants' behavior, experiences, and social interactions in their natural context.

Inductive approach : Unlike quantitative research, which often follows a deductive approach , qualitative research begins with the collection of data and then seeks to develop theories, concepts, or themes that emerge from the data. This inductive approach enables researchers to stay open to new insights and unexpected findings.

Holistic perspective : Qualitative research aims to provide a comprehensive understanding of the phenomena under study by considering multiple dimensions, such as the social, cultural, historical, and psychological aspects that shape people's experiences and behavior.

Subjectivity and interpretation : Epistemology plays a crucial role in qualitative research. Researchers are encouraged to reflect on their biases, assumptions, and values , and to consider how these may influence their data collection, analysis, and interpretation.

Flexibility : Qualitative research methods are often flexible and adaptable, allowing researchers to refine their research questions , sampling strategies, or data collection techniques as new insights and perspectives emerge during the research process.

Key principles of qualitative research

Qualitative research is guided by several fundamental principles that shape its approach, methods, and analysis:

Empathy and reflexivity : Qualitative researchers strive to empathize with the participants and to understand their perspectives, experiences, and emotions from their viewpoint. This requires researchers to be attentive, open-minded, and sensitive to the participants' verbal and non-verbal cues. At the same, qualitative researchers critically reflect on their participants’ perspectives, experiences, and emotions to develop their findings and conclusions, instead of taking these at face value. In addition, it is important for the researcher to reflect on how their own role and viewpoint may be shaping the research.

Trustworthiness : Establishing trustworthiness in qualitative research involves demonstrating credibility, transferability, dependability, and confirmability. Researchers can enhance trustworthiness by using various strategies, such as triangulation, member checking , peer debriefing , and reflexivity .

Iterative analysis : Qualitative data analysis is an ongoing and iterative process, in which researchers continually review, compare, and revise their interpretations as they collect and analyze more data. This iterative process allows researchers to refine their understanding of the phenomena and to develop more robust and nuanced theories, concepts, or themes.

Rich description : Providing detailed, vivid, and context-sensitive descriptions of the data is essential in qualitative research. Rich descriptions help convey the complexity and nuances of the phenomena under study, and enable readers to assess the relevance and transferability of the findings to other settings or populations.

What are the common types of qualitative research?

Qualitative research is an umbrella term for various methodologies that focus on understanding and interpreting human experiences, behaviors, and social phenomena within their context. These approaches seek to gather in-depth, rich data through the analysis of language, actions, and expressions. Five common types of qualitative research are narrative research , phenomenology , grounded theory , ethnography , and case study .

Narrative research : This approach focuses on the stories and experiences of individuals, aiming to understand their lives and personal perspectives. Researchers can collect data through interviews, letters, diaries, or autobiographies, and analyze these narratives to identify recurring themes, patterns, and meanings . Narrative research can be valuable for exploring individual identities, cultural beliefs, and historical events.

Phenomenology : Phenomenology seeks to understand the essence of a particular phenomenon by analyzing the experiences and perceptions of individuals who have gone through that phenomenon . Researchers can explore participants' thoughts, feelings, and experiences through in-depth interviews, observations, or written materials. The goal is to describe the commonalities and variations in these experiences, ultimately revealing the underlying structures and meaning of the phenomenon under study.

Grounded theory : This inductive research method aims to generate new theories by systematically collecting and analyzing data. Researchers begin with an open-ended research question and gather data through observations, interviews, and document analysis . They then use a process of coding and constant comparison to identify patterns, categories, and relationships in the data. This iterative process continues until a comprehensive, grounded theory emerges that is based in the recollected data and explains the topic of interest.

Ethnography : Ethnographic research involves the in-depth study of a specific cultural or social group, focusing on understanding its members' behaviors, beliefs, and interactions. Researchers immerse themselves in the group's environment, often for extended periods, to observe and participate in daily activities. They can collect data through field notes, interviews, and document analysis, aiming to provide a holistic and nuanced understanding of the group's cultural practices and social dynamics.

Case study : A case study is an in-depth examination of a specific instance, event, organization, or individual within its real-life context. Researchers use multiple sources of data, such as interviews, observations, documents, and artifacts to build a rich, detailed understanding of the case. Case study research can be used to explore complex phenomena, generate new hypotheses , or evaluate the effectiveness of interventions or policies.

What are the purposes of qualitative research?

Qualitative research presents outcomes that emerge from the process of collecting and analyzing qualitative data. These outcomes often involve generating new theories, developing or challenging existing theories, and proposing practical implications based on actionable insights. The products of qualitative research contribute to a deeper understanding of human experiences, social phenomena, and cultural contexts. Qualitative research can also be a powerful complement to quantitative research.

Generating new theory : One of the primary goals of qualitative research is to develop new theories or conceptual frameworks that help explain previously unexplored or poorly understood phenomena. By conducting in-depth investigations and analyzing rich data, researchers can identify patterns, relationships, and underlying structures that form the basis of novel theoretical insights.

Developing or challenging existing theory : Qualitative research can also contribute to the refinement or expansion of existing theories by providing new perspectives, revealing previously unnoticed complexities, or highlighting areas where current theories may be insufficient or inaccurate. By examining the nuances and context-specific details of a phenomenon, researchers can generate evidence that supports, contradicts, or modifies existing theoretical frameworks .

Proposing practical implications : Qualitative research often yields actionable insights that can inform policy, practice, and intervention strategies. By delving into the lived experiences of individuals and communities, researchers can identify factors that contribute to or hinder the effectiveness of certain approaches, uncovering opportunities for improvement or innovation. The insights gained from qualitative research can be used to design targeted interventions, develop context-sensitive policies, or inform the professional practices of practitioners in various fields.

Enhancing understanding and empathy : Qualitative research promotes a deeper understanding of human experiences, emotions, and perspectives, fostering empathy and cultural sensitivity. By engaging with diverse voices and experiences, researchers can develop a more nuanced appreciation of the complexities of human behavior and social dynamics, ultimately contributing to more compassionate and inclusive societies.

Informing mixed-methods research : The products of qualitative research can also be used in conjunction with quantitative research, as part of a mixed-methods approach . Qualitative findings can help generate hypotheses for further testing, inform the development of survey instruments , or provide context and explanation for quantitative results. Combining the strengths of both approaches can lead to more robust and comprehensive understanding of complex research questions .

What are some examples of qualitative research?

Qualitative research can be conducted across various scientific fields, exploring diverse topics and phenomena. Here are six brief descriptions of qualitative studies that can provide researchers with ideas for their own projects:

Exploring the lived experiences of refugees : A phenomenological study could be conducted to investigate the lived experiences and coping strategies of refugees in a specific host country. By conducting in-depth interviews with refugees and analyzing their narratives , researchers can gain insights into the challenges they face, their resilience, and the factors that contribute to successful integration into their new communities.

Understanding the dynamics of online communities : An ethnographic study could be designed to explore the culture and social dynamics of a particular online community or social media platform. By immersing themselves in the virtual environment, researchers can observe patterns of interaction, communication styles, and shared values among community members, providing a nuanced understanding of the factors that influence online behavior and group dynamics.

Examining the impact of gentrification on local communities : A case study could be conducted to explore the impact of gentrification on a specific neighborhood or community. Researchers can collect data through interviews with residents, local business owners, and policymakers, as well as analyzing relevant documents and media coverage. The study can shed light on the effects of gentrification on housing affordability, social cohesion, and cultural identity, informing policy and urban planning decisions.

Studying the career trajectories of women in STEM fields : A narrative research project can be designed to investigate the career experiences and pathways of women in science, technology, engineering, and mathematics (STEM) fields. By collecting and analyzing the stories of women at various career stages, researchers can identify factors that contribute to their success, as well as barriers and challenges they face in male-dominated fields.

Evaluating the effectiveness of a mental health intervention : A qualitative study can be conducted to evaluate the effectiveness of a specific mental health intervention, such as a mindfulness-based program for reducing stress and anxiety. Researchers can gather data through interviews and focus groups with program participants, exploring their experiences, perceived benefits, and suggestions for improvement. The findings can provide valuable insights for refining the intervention and informing future mental health initiatives.

Investigating the role of social media in political activism : A qualitative study using document analysis and visual methods could explore the role of social media in shaping political activism and public opinion during a specific social movement or election campaign. By analyzing user-generated content, such as tweets, posts, images, and videos, researchers can examine patterns of communication, mobilization, and discourse, shedding light on the ways in which social media influences political engagement and democratic processes.

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What are common qualitative research methods?

Qualitative research methods are techniques used to collect, analyze, and interpret data in qualitative studies. These methods prioritize the exploration of meaning, context, and individual experiences. Common qualitative research methods include interviews, focus groups, observations, document analysis, and visual methods.

Interviews : Interviews involve one-on-one conversations between the researcher and the participant. They can be structured, semi-structured, or unstructured, depending on the level of guidance provided by the researcher. Interviews allow for in-depth exploration of participants' experiences, thoughts, and feelings, providing rich and detailed data for analysis.

Focus groups : Focus groups are group discussions facilitated by a researcher, usually consisting of 6-12 participants. They enable researchers to explore participants' collective perspectives, opinions, and experiences in a social setting. Focus groups can generate insights into group dynamics, cultural norms, and shared understandings, as participants interact and respond to each other's viewpoints.

Observations : Observational research involves the systematic collection of data through watching and recording people, events, or behaviors in their natural settings. Researchers can take on different roles, such as participant-observer or non-participant observer, depending on their level of involvement. Observations provide valuable information about context, social interactions, and non-verbal communication, which can help researchers understand the nuances of a particular phenomenon.

Document analysis : Document analysis is the examination of written or visual materials, such as letters, diaries, reports, newspaper articles, photographs, or videos. This method can provide insights into historical or cultural contexts, individual perspectives, and organizational processes. Researchers may use content analysis, discourse analysis, or other analytic techniques to interpret the meaning and significance of these documents.

Visual methods : Visual methods involve the use of visual materials, such as photographs, drawings, or videos, to explore and represent participants' experiences and perspectives. Techniques like photo elicitation, where participants are asked to take or select photographs related to the research topic and discuss their meaning, can encourage reflection and stimulate discussion. Visual methods can be particularly useful in capturing non-verbal information, promoting cross-cultural understanding, and engaging with hard-to-reach populations.

Importance of qualitative research and qualitative data analysis

Qualitative research and qualitative data analysis play a vital role in advancing knowledge, informing policies, and improving practices in various fields, such as education, healthcare, business, and social work. The unique insights and in-depth understanding generated through qualitative research can accomplish a number of goals.

Inform decision-making

Qualitative research helps decision-makers better understand the needs, preferences, and concerns of different stakeholders, such as customers, employees, or community members. This can lead to more effective and tailored policies, programs, or interventions that address real-world challenges.

Enhance innovation

By exploring people's experiences, motivations, and aspirations, qualitative research can uncover new ideas, opportunities, and trends that can drive innovation in products, services, or processes.

Foster empathy and cultural competence

Qualitative research can increase our empathy and understanding of diverse populations, cultures, and contexts. This can enhance our ability to communicate, collaborate, and work effectively with people from different backgrounds.

Complement quantitative research

Qualitative research can complement quantitative research by providing rich contextual information and in-depth insights into the underlying mechanisms, processes, or factors that may explain the patterns or relationships observed in quantitative data.

Facilitate social change

Qualitative research can give voice to marginalized or underrepresented groups, highlight social injustices or inequalities, and inspire actions and reforms that promote social change and well-being.

Challenges of conducting qualitative research

While qualitative research offers valuable insights and understanding of human experiences, it also presents some challenges that researchers must navigate. Acknowledging and addressing these challenges can help ensure the rigor, credibility, and relevance of qualitative research. In this section, we will discuss some common challenges that researchers may encounter when conducting qualitative research and offer suggestions on how to overcome them.

Subjectivity and bias

One of the primary challenges in qualitative research is managing subjectivity and potential biases that may arise from the researcher's personal beliefs, values, and experiences. Since qualitative research relies on the researcher's interpretation of the data , there is a risk that the researcher's subjectivity may influence the findings.

Researchers can minimize the impact of subjectivity and bias by maintaining reflexivity , or ongoing self-awareness and critical reflection on their role, assumptions, and influences in the research process. This may involve keeping a reflexive journal, engaging in peer debriefing , and discussing potential biases with research participants during member checking .

Data collection and quality

Collecting high-quality data in qualitative research can be challenging, particularly when dealing with sensitive topics , hard-to-reach populations, or complex social phenomena. Ensuring the trustworthiness of qualitative data collection is essential to producing credible and meaningful findings.

Researchers can enhance data quality by employing various strategies, such as purposive or theoretical sampling, triangulation of data sources, methods or researchers, and establishing rapport and trust with research participants.

Data analysis and interpretation

The analysis and interpretation of qualitative data can be a complex, time-consuming, and sometimes overwhelming process. Researchers must make sense of large amounts of diverse and unstructured data, while also ensuring the rigor, transparency, and consistency of their analysis.

Researchers can facilitate data analysis and interpretation by adopting systematic and well-established approaches, such as thematic analysis , grounded theory , or content analysis . Utilizing qualitative data analysis software , like ATLAS.ti, can also help manage and analyze data more efficiently and rigorously.

Qualitative research often involves exploring sensitive issues or working with vulnerable populations, which raises various ethical considerations , such as privacy, confidentiality , informed consent , and potential harm to participants.

Researchers should be familiar with the ethical guidelines and requirements of their discipline, institution, or funding agency, and should obtain ethical approval from relevant review boards or committees before conducting the research. Researchers should also maintain open communication with participants, respect their autonomy and dignity, and protect their well-being throughout the research process.

Generalizability and transferability

Qualitative research typically focuses on in-depth exploration of specific cases or contexts, which may limit the generalizability or transferability of the findings to other settings or populations. However, the goal of qualitative research is not to produce statistically generalizable results but rather to provide a rich, contextualized, and nuanced understanding of the phenomena under study.

Researchers can enhance the transferability of their findings by providing rich descriptions of the research context, participants, and methods, and by discussing the potential applicability or relevance of the findings to other settings or populations. Readers can then assess the transferability of the findings based on the similarity of their own context to the one described in the research.

By addressing these challenges and adopting rigorous and transparent research practices, qualitative researchers can contribute valuable and meaningful insights that advance knowledge, inform policies, and improve practices in various fields and contexts.

Qualitative and quantitative research approaches are often seen as distinct and even opposing paradigms. However, these two approaches can be complementary, providing a more comprehensive understanding of complex social phenomena when combined. In this section, we will discuss how qualitative research can complement quantitative research and enhance the overall depth, breadth, and rigor of research findings.

Exploring and understanding context

Quantitative research excels at identifying patterns, trends, and relationships among variables using numerical data, while qualitative research provides rich and nuanced insights into the context, meaning, and underlying processes that shape these patterns or relationships. By integrating qualitative research with quantitative research, researchers can explore not only the "what" or "how many" but also the "why" and "how" of the phenomena under study.

For example, a quantitative study in health services research might reveal a correlation between social media usage and mental health outcomes, while a qualitative study could help explain the reasons behind this correlation by exploring users' experiences, motivations, and perceptions of social media. Qualitative and quantitative data in this case complement each other to contribute to a more robust theory and more informed policy implications.

Generating and refining hypotheses

Qualitative research can inform the development and refinement of hypotheses for quantitative research by identifying new concepts, variables, or relationships that emerge from the data. This can lead to more focused, relevant, and innovative quantitative research questions and hypotheses. For instance, a qualitative study on employee motivation might uncover the importance of meaningful work and supportive relationships with supervisors as key factors influencing motivation. These findings could then be incorporated into a quantitative study to test the relationships between these factors and employee motivation.

Validating and triangulating findings

Combining qualitative and quantitative research methods can enhance the credibility and trustworthiness of research findings through validation and triangulation. Validation involves comparing the findings from different methods to assess their consistency and convergence, while triangulation involves using multiple methods, data sources, or researchers to gain a more comprehensive understanding of the phenomena under study.

For example, a researcher might use both quantitative surveys and qualitative interviews in a mixed methods research design to assess the effectiveness of a health intervention. If both methods yield similar findings, this can increase confidence in the results. If the findings differ, the researcher can further investigate the reasons for these discrepancies and refine their understanding of the intervention's effectiveness.

Enhancing communication and dissemination

Qualitative research can enhance the communication and dissemination of quantitative research findings by providing vivid narratives, case studies, or examples that bring the data to life and make it more accessible and engaging for diverse audiences, such as policymakers, practitioners, or the public.

For example, a quantitative study on the impact of a community-based program might report the percentage of participants who experienced improvements in various outcomes. By adding qualitative data, such as quotes or stories from participants, the researcher can illustrate the human impact of the program and make the findings more compelling and relatable.

In conclusion, qualitative research can complement and enrich quantitative research in various ways, leading to a more comprehensive, contextualized, and rigorous understanding of complex social phenomena. By integrating qualitative and quantitative research methods, researchers can harness the strengths of both approaches to produce more robust, relevant, and impactful findings that inform theory, policy, and practice.

Qualitative research findings are typically reported in various formats, depending on the audience, purpose, and context of the research. Common ways to report qualitative research include dissertations, journal articles, market research reports, and needs assessment reports. Each format has its own structure and emphasis, tailored to meet the expectations and requirements of its target audience.

Dissertations and theses : Doctoral,master's, or bachelor students often conduct qualitative research as part of their dissertation or thesis projects. In this format, researchers provide a comprehensive account of their research questions , methodology, data collection , data analysis , and findings. Dissertations are expected to make a significant contribution to the existing body of knowledge and demonstrate the researcher's mastery of the subject matter.

Journal articles : Researchers frequently disseminate their qualitative research findings through articles published in academic journals . These articles are typically structured in a way that includes an introduction, literature review, methodology, results, and discussion sections. In addition, articles often undergo a peer-review process before being published in the academic journal. Journal articles focus on communicating the study's purpose, methods, and findings in a concise and coherent manner, providing enough detail for other researchers to evaluate the rigor and validity of the research so that they can cite the article and build on it in their own studies.

Market research reports : Market research often employs qualitative methods to gather insights into consumer behavior, preferences, and attitudes. Market research reports present the findings of these studies to clients, typically businesses or organizations interested in understanding their target audience or market trends. These reports focus on providing actionable insights and recommendations based on the qualitative data, helping clients make informed decisions and develop effective marketing strategies.

Needs assessment reports : Needs assessment is a process used to identify gaps or areas of improvement in a specific context, such as healthcare, education, or social services. Qualitative research methods can be used to collect data on the needs, challenges, and experiences of the target population. Needs assessment reports present the findings of this research, highlighting the identified needs and providing recommendations for addressing them. These reports are used by organizations and policymakers to inform the development and implementation of targeted interventions and policies.

Other formats : In addition to the aforementioned formats, qualitative research findings can also be reported in conference presentations, white papers, policy briefs, blog posts, or multimedia presentations. The choice of format depends on the target audience and the intended purpose of the research, as well as the researcher's preferences and resources. Regardless of the format, it is important for researchers to present their findings in a clear, accurate, and engaging manner, ensuring that their work is accessible and relevant to their audience.

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The SAGE Handbook of Qualitative Data Collection

• Edited by: Uwe Flick
• Publisher: SAGE Publications Ltd
• Publication year: 2018
• Online pub date: December 13, 2018
• Discipline: Anthropology
• Methods: Qualitative data collection , Mixed methods
• DOI: https:// doi. org/10.4135/9781526416070
• Keywords: data collection , interviews , mixed methods , qualitative data collection , qualitative research , social research , triangulation Show all Show less
• Print ISBN: 9781473952133
• Online ISBN: 9781526416070
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Subject index

How we understand and define qualitative data is changing, with implications not only for the techniques of data analysis, but also how data are collected. New devices, technologies and online spaces open up new ways for researchers to approach and collect images, moving images, text and talk. The SAGE Handbook of Qualitative Data Collection systematically explores the approaches, techniques, debates and new frontiers for creating, collecting and producing qualitative data. Bringing together contributions from internationally leading scholars in the field, the handbook offers a state-of-the-art look at key themes across six thematic parts: Part I Charting the Routes Part II Concepts, Contexts, Basics Part III Types of Data and How to Collect Them Part IV Digital and Internet Data Part V Triangulation and Mixed Methods Part VI Collecting Data in Specific Populations

Front Matter

• International Advisory Editorial Board
• List of Figures
• List of Tables
• Notes on the Editor and Contributors
• Acknowledgements
• Chapter 1 | Doing Qualitative Data Collection – Charting the Routes
• Chapter 2 | Collecting Qualitative Data: A Realist Approach
• Chapter 3 | Ethics of Qualitative Data Collection
• Chapter 4 | Deduction, Induction, and Abduction
• Chapter 5 | Upside Down – Reinventing Research Design
• Chapter 6 | Sampling and Generalization
• Chapter 7 | Accessing the Research Field
• Chapter 8 | Recording and Transcribing Social Interaction
• Chapter 9 | Collecting Data in Other Languages – Strategies for Cross-Language Research in Multilingual Societies
• Chapter 10 | From Scholastic to Emic Comparison: Generating Comparability and Handling Difference in Ethnographic Research
• Chapter 11 | Data Collection in Secondary Analysis
• Chapter 12 | The Virtues of Naturalistic Data
• Chapter 13 | Performance, Hermeneutics, Interpretation
• Chapter 14 | Quality of Data Collection
• Chapter 15 | Qualitative Interviews
• Chapter 16 | Focus Groups
• Chapter 17 | Narrative Data
• Chapter 18 | Data Collection in Conversation Analysis
• Chapter 19 | Collecting Data for Analyzing Discourses
• Chapter 20 | Observations
• Chapter 21 | Doing Ethnography: Ways and Reasons
• Chapter 22 | Go-Alongs
• Chapter 23 | Videography
• Chapter 24 | Collecting Documents as Data
• Chapter 25 | Collecting Images as Data
• Chapter 26 | Collecting Media Data: TV and Film Studies
• Chapter 27 | Sounds as Data
• Chapter 28 | The Concept of ‘Data’ in Digital Research
• Chapter 29 | Moving Through Digital Flows: An Epistemological and Practical Approach
• Chapter 30 | Ethics in Digital Research
• Chapter 31 | Collecting Data for Analyzing Blogs
• Chapter 32 | Collecting Qualitative Data from Facebook: Approaches and Methods
• Chapter 33 | Troubling the Concept of Data in Qualitative Digital Research
• Chapter 34 | Triangulation in Data Collection
• Chapter 35 | Toward an Understanding of a Qualitatively Driven Mixed Methods Data Collection and Analysis: Moving Toward a Theoretically Centered Mixed Methods Praxis
• Chapter 36 | Data-Related Issues in Qualitatively Driven Mixed-Method Designs: Sampling, Pacing, and Reflexivity
• Chapter 37 | Combining Digital and Physical Data
• Chapter 38 | Using Photographs in Interviews: When We Lack the Words to Say What Practice Means
• Chapter 39 | Collecting Qualitative Data with Children
• Chapter 40 | Collecting Qualitative Data with Older People
• Chapter 41 | Generating Qualitative Data with Experts and Elites
• Chapter 42 | Collecting Qualitative Data with Hard-to-Reach Groups

Back Matter

• Author Index

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• Published: 22 March 2008

Methods of data collection in qualitative research: interviews and focus groups

• P. Gill 1 ,
• K. Stewart 2 ,
• E. Treasure 3 &
• B. Chadwick 4  

British Dental Journal volume  204 ,  pages 291–295 ( 2008 ) Cite this article

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Interviews and focus groups are the most common methods of data collection used in qualitative healthcare research

Interviews can be used to explore the views, experiences, beliefs and motivations of individual participants

Focus group use group dynamics to generate qualitative data

Qualitative research in dentistry

Conducting qualitative interviews with school children in dental research

Analysing and presenting qualitative data

This paper explores the most common methods of data collection used in qualitative research: interviews and focus groups. The paper examines each method in detail, focusing on how they work in practice, when their use is appropriate and what they can offer dentistry. Examples of empirical studies that have used interviews or focus groups are also provided.

You have full access to this article via your institution.

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Interviews in the social sciences

A review of technical and quality assessment considerations of audio-visual and web-conferencing focus groups in qualitative health research

Professionalism in dentistry: deconstructing common terminology, introduction.

Having explored the nature and purpose of qualitative research in the previous paper, this paper explores methods of data collection used in qualitative research. There are a variety of methods of data collection in qualitative research, including observations, textual or visual analysis (eg from books or videos) and interviews (individual or group). 1 However, the most common methods used, particularly in healthcare research, are interviews and focus groups. 2 , 3

The purpose of this paper is to explore these two methods in more detail, in particular how they work in practice, the purpose of each, when their use is appropriate and what they can offer dental research.

Qualitative research interviews

There are three fundamental types of research interviews: structured, semi-structured and unstructured. Structured interviews are, essentially, verbally administered questionnaires, in which a list of predetermined questions are asked, with little or no variation and with no scope for follow-up questions to responses that warrant further elaboration. Consequently, they are relatively quick and easy to administer and may be of particular use if clarification of certain questions are required or if there are likely to be literacy or numeracy problems with the respondents. However, by their very nature, they only allow for limited participant responses and are, therefore, of little use if 'depth' is required.

Conversely, unstructured interviews do not reflect any preconceived theories or ideas and are performed with little or no organisation. 4 Such an interview may simply start with an opening question such as 'Can you tell me about your experience of visiting the dentist?' and will then progress based, primarily, upon the initial response. Unstructured interviews are usually very time-consuming (often lasting several hours) and can be difficult to manage, and to participate in, as the lack of predetermined interview questions provides little guidance on what to talk about (which many participants find confusing and unhelpful). Their use is, therefore, generally only considered where significant 'depth' is required, or where virtually nothing is known about the subject area (or a different perspective of a known subject area is required).

Semi-structured interviews consist of several key questions that help to define the areas to be explored, but also allows the interviewer or interviewee to diverge in order to pursue an idea or response in more detail. 2 This interview format is used most frequently in healthcare, as it provides participants with some guidance on what to talk about, which many find helpful. The flexibility of this approach, particularly compared to structured interviews, also allows for the discovery or elaboration of information that is important to participants but may not have previously been thought of as pertinent by the research team.

For example, in a recent dental public heath study, 5 school children in Cardiff, UK were interviewed about their food choices and preferences. A key finding that emerged from semi-structured interviews, which was not previously thought to be as highly influential as the data subsequently confirmed, was the significance of peer-pressure in influencing children's food choices and preferences. This finding was also established primarily through follow-up questioning (eg probing interesting responses with follow-up questions, such as 'Can you tell me a bit more about that?') and, therefore, may not have emerged in the same way, if at all, if asked as a predetermined question.

The purpose of research interviews

The purpose of the research interview is to explore the views, experiences, beliefs and/or motivations of individuals on specific matters (eg factors that influence their attendance at the dentist). Qualitative methods, such as interviews, are believed to provide a 'deeper' understanding of social phenomena than would be obtained from purely quantitative methods, such as questionnaires. 1 Interviews are, therefore, most appropriate where little is already known about the study phenomenon or where detailed insights are required from individual participants. They are also particularly appropriate for exploring sensitive topics, where participants may not want to talk about such issues in a group environment.

Examples of dental studies that have collected data using interviews are 'Examining the psychosocial process involved in regular dental attendance' 6 and 'Exploring factors governing dentists' treatment philosophies'. 7 Gibson et al . 6 provided an improved understanding of factors that influenced people's regular attendance with their dentist. The study by Kay and Blinkhorn 7 provided a detailed insight into factors that influenced GDPs' decision making in relation to treatment choices. The study found that dentists' clinical decisions about treatments were not necessarily related to pathology or treatment options, as was perhaps initially thought, but also involved discussions with patients, patients' values and dentists' feelings of self esteem and conscience.

There are many similarities between clinical encounters and research interviews, in that both employ similar interpersonal skills, such as questioning, conversing and listening. However, there are also some fundamental differences between the two, such as the purpose of the encounter, reasons for participating, roles of the people involved and how the interview is conducted and recorded. 8

The primary purpose of clinical encounters is for the dentist to ask the patient questions in order to acquire sufficient information to inform decision making and treatment options. However, the constraints of most consultations are such that any open-ended questioning needs to be brought to a conclusion within a fairly short time. 2 In contrast, the fundamental purpose of the research interview is to listen attentively to what respondents have to say, in order to acquire more knowledge about the study topic. 9 Unlike the clinical encounter, it is not to intentionally offer any form of help or advice, which many researchers have neither the training nor the time for. Research interviewing therefore requires a different approach and a different range of skills.

The interview

When designing an interview schedule it is imperative to ask questions that are likely to yield as much information about the study phenomenon as possible and also be able to address the aims and objectives of the research. In a qualitative interview, good questions should be open-ended (ie, require more than a yes/no answer), neutral, sensitive and understandable. 2 It is usually best to start with questions that participants can answer easily and then proceed to more difficult or sensitive topics. 2 This can help put respondents at ease, build up confidence and rapport and often generates rich data that subsequently develops the interview further.

As in any research, it is often wise to first pilot the interview schedule on several respondents prior to data collection proper. 8 This allows the research team to establish if the schedule is clear, understandable and capable of answering the research questions, and if, therefore, any changes to the interview schedule are required.

The length of interviews varies depending on the topic, researcher and participant. However, on average, healthcare interviews last 20-60 minutes. Interviews can be performed on a one-off or, if change over time is of interest, repeated basis, 4 for example exploring the psychosocial impact of oral trauma on participants and their subsequent experiences of cosmetic dental surgery.

Developing the interview

Before an interview takes place, respondents should be informed about the study details and given assurance about ethical principles, such as anonymity and confidentiality. 2 This gives respondents some idea of what to expect from the interview, increases the likelihood of honesty and is also a fundamental aspect of the informed consent process.

Wherever possible, interviews should be conducted in areas free from distractions and at times and locations that are most suitable for participants. For many this may be at their own home in the evenings. Whilst researchers may have less control over the home environment, familiarity may help the respondent to relax and result in a more productive interview. 9 Establishing rapport with participants prior to the interview is also important as this can also have a positive effect on the subsequent development of the interview.

When conducting the actual interview it is prudent for the interviewer to familiarise themselves with the interview schedule, so that the process appears more natural and less rehearsed. However, to ensure that the interview is as productive as possible, researchers must possess a repertoire of skills and techniques to ensure that comprehensive and representative data are collected during the interview. 10 One of the most important skills is the ability to listen attentively to what is being said, so that participants are able to recount their experiences as fully as possible, without unnecessary interruptions.

Other important skills include adopting open and emotionally neutral body language, nodding, smiling, looking interested and making encouraging noises (eg, 'Mmmm') during the interview. 2 The strategic use of silence, if used appropriately, can also be highly effective at getting respondents to contemplate their responses, talk more, elaborate or clarify particular issues. Other techniques that can be used to develop the interview further include reflecting on remarks made by participants (eg, 'Pain?') and probing remarks ('When you said you were afraid of going to the dentist what did you mean?'). 9 Where appropriate, it is also wise to seek clarification from respondents if it is unclear what they mean. The use of 'leading' or 'loaded' questions that may unduly influence responses should always be avoided (eg, 'So you think dental surgery waiting rooms are frightening?' rather than 'How do you find the waiting room at the dentists?').

At the end of the interview it is important to thank participants for their time and ask them if there is anything they would like to add. This gives respondents an opportunity to deal with issues that they have thought about, or think are important but have not been dealt with by the interviewer. 9 This can often lead to the discovery of new, unanticipated information. Respondents should also be debriefed about the study after the interview has finished.

All interviews should be tape recorded and transcribed verbatim afterwards, as this protects against bias and provides a permanent record of what was and was not said. 8 It is often also helpful to make 'field notes' during and immediately after each interview about observations, thoughts and ideas about the interview, as this can help in data analysis process. 4 , 8

Focus groups

Focus groups share many common features with less structured interviews, but there is more to them than merely collecting similar data from many participants at once. A focus group is a group discussion on a particular topic organised for research purposes. This discussion is guided, monitored and recorded by a researcher (sometimes called a moderator or facilitator). 11 , 12

Focus groups were first used as a research method in market research, originating in the 1940s in the work of the Bureau of Applied Social Research at Columbia University. Eventually the success of focus groups as a marketing tool in the private sector resulted in its use in public sector marketing, such as the assessment of the impact of health education campaigns. 13 However, focus group techniques, as used in public and private sectors, have diverged over time. Therefore, in this paper, we seek to describe focus groups as they are used in academic research.

When focus groups are used

Focus groups are used for generating information on collective views, and the meanings that lie behind those views. They are also useful in generating a rich understanding of participants' experiences and beliefs. 12 Suggested criteria for using focus groups include: 13

As a standalone method, for research relating to group norms, meanings and processes

In a multi-method design, to explore a topic or collect group language or narratives to be used in later stages

To clarify, extend, qualify or challenge data collected through other methods

To feedback results to research participants.

Morgan 12 suggests that focus groups should be avoided according to the following criteria:

If listening to participants' views generates expectations for the outcome of the research that can not be fulfilled

If participants are uneasy with each other, and will therefore not discuss their feelings and opinions openly

If the topic of interest to the researcher is not a topic the participants can or wish to discuss

If statistical data is required. Focus groups give depth and insight, but cannot produce useful numerical results.

Conducting focus groups: group composition and size

The composition of a focus group needs great care to get the best quality of discussion. There is no 'best' solution to group composition, and group mix will always impact on the data, according to things such as the mix of ages, sexes and social professional statuses of the participants. What is important is that the researcher gives due consideration to the impact of group mix (eg, how the group may interact with each other) before the focus group proceeds. 14

Interaction is key to a successful focus group. Sometimes this means a pre-existing group interacts best for research purposes, and sometimes stranger groups. Pre-existing groups may be easier to recruit, have shared experiences and enjoy a comfort and familiarity which facilitates discussion or the ability to challenge each other comfortably. In health settings, pre-existing groups can overcome issues relating to disclosure of potentially stigmatising status which people may find uncomfortable in stranger groups (conversely there may be situations where disclosure is more comfortable in stranger groups). In other research projects it may be decided that stranger groups will be able to speak more freely without fear of repercussion, and challenges to other participants may be more challenging and probing, leading to richer data. 13

Group size is an important consideration in focus group research. Stewart and Shamdasani 14 suggest that it is better to slightly over-recruit for a focus group and potentially manage a slightly larger group, than under-recruit and risk having to cancel the session or having an unsatisfactory discussion. They advise that each group will probably have two non-attenders. The optimum size for a focus group is six to eight participants (excluding researchers), but focus groups can work successfully with as few as three and as many as 14 participants. Small groups risk limited discussion occurring, while large groups can be chaotic, hard to manage for the moderator and frustrating for participants who feel they get insufficient opportunities to speak. 13

Preparing an interview schedule

Like research interviews, the interview schedule for focus groups is often no more structured than a loose schedule of topics to be discussed. However, in preparing an interview schedule for focus groups, Stewart and Shamdasani 14 suggest two general principles:

Questions should move from general to more specific questions

Question order should be relative to importance of issues in the research agenda.

There can, however, be some conflict between these two principles, and trade offs are often needed, although often discussions will take on a life of their own, which will influence or determine the order in which issues are covered. Usually, less than a dozen predetermined questions are needed and, as with research interviews, the researcher will also probe and expand on issues according to the discussion.

Moderating a focus group looks easy when done well, but requires a complex set of skills, which are related to the following principles: 15

Participants have valuable views and the ability to respond actively, positively and respectfully. Such an approach is not simply a courtesy, but will encourage fruitful discussions

Moderating without participating: a moderator must guide a discussion rather than join in with it. Expressing one's own views tends to give participants cues as to what to say (introducing bias), rather than the confidence to be open and honest about their own views

Be prepared for views that may be unpalatably critical of a topic which may be important to you

It is important to recognise that researchers' individual characteristics mean that no one person will always be suitable to moderate any kind of group. Sometimes the characteristics that suit a moderator for one group will inhibit discussion in another

Be yourself. If the moderator is comfortable and natural, participants will feel relaxed.

The moderator should facilitate group discussion, keeping it focussed without leading it. They should also be able to prevent the discussion being dominated by one member (for example, by emphasising at the outset the importance of hearing a range of views), ensure that all participants have ample opportunity to contribute, allow differences of opinions to be discussed fairly and, if required, encourage reticent participants. 13

Other relevant factors

The venue for a focus group is important and should, ideally, be accessible, comfortable, private, quiet and free from distractions. 13 However, while a central location, such as the participants' workplace or school, may encourage attendance, the venue may affect participants' behaviour. For example, in a school setting, pupils may behave like pupils, and in clinical settings, participants may be affected by any anxieties that affect them when they attend in a patient role.

Focus groups are usually recorded, often observed (by a researcher other than the moderator, whose role is to observe the interaction of the group to enhance analysis) and sometimes videotaped. At the start of a focus group, a moderator should acknowledge the presence of the audio recording equipment, assure participants of confidentiality and give people the opportunity to withdraw if they are uncomfortable with being taped. 14

A good quality multi-directional external microphone is recommended for the recording of focus groups, as internal microphones are rarely good enough to cope with the variation in volume of different speakers. 13 If observers are present, they should be introduced to participants as someone who is just there to observe, and sit away from the discussion. 14 Videotaping will require more than one camera to capture the whole group, as well as additional operational personnel in the room. This is, therefore, very obtrusive, which can affect the spontaneity of the group and in a focus group does not usually yield enough additional information that could not be captured by an observer to make videotaping worthwhile. 15

The systematic analysis of focus group transcripts is crucial. However, the transcription of focus groups is more complex and time consuming than in one-to-one interviews, and each hour of audio can take up to eight hours to transcribe and generate approximately 100 pages of text. Recordings should be transcribed verbatim and also speakers should be identified in a way that makes it possible to follow the contributions of each individual. Sometimes observational notes also need to be described in the transcripts in order for them to make sense.

The analysis of qualitative data is explored in the final paper of this series. However, it is important to note that the analysis of focus group data is different from other qualitative data because of their interactive nature, and this needs to be taken into consideration during analysis. The importance of the context of other speakers is essential to the understanding of individual contributions. 13 For example, in a group situation, participants will often challenge each other and justify their remarks because of the group setting, in a way that perhaps they would not in a one-to-one interview. The analysis of focus group data must therefore take account of the group dynamics that have generated remarks.

Focus groups in dental research

Focus groups are used increasingly in dental research, on a diverse range of topics, 16 illuminating a number of areas relating to patients, dental services and the dental profession. Addressing a special needs population difficult to access and sample through quantitative measures, Robinson et al . 17 used focus groups to investigate the oral health-related attitudes of drug users, exploring the priorities, understandings and barriers to care they encounter. Newton et al . 18 used focus groups to explore barriers to services among minority ethnic groups, highlighting for the first time differences between minority ethnic groups. Demonstrating the use of the method with professional groups as subjects in dental research, Gussy et al . 19 explored the barriers to and possible strategies for developing a shared approach in prevention of caries among pre-schoolers. This mixed method study was very important as the qualitative element was able to explain why the clinical trial failed, and this understanding may help researchers improve on the quantitative aspect of future studies, as well as making a valuable academic contribution in its own right.

Interviews and focus groups remain the most common methods of data collection in qualitative research, and are now being used with increasing frequency in dental research, particularly to access areas not amendable to quantitative methods and/or where depth, insight and understanding of particular phenomena are required. The examples of dental studies that have employed these methods also help to demonstrate the range of research contexts to which interview and focus group research can make a useful contribution. The continued employment of these methods can further strengthen many areas of dentally related work.

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Gill, P., Stewart, K., Treasure, E. et al. Methods of data collection in qualitative research: interviews and focus groups. Br Dent J 204 , 291–295 (2008). https://doi.org/10.1038/bdj.2008.192

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Part 4: Using qualitative methods

18. Qualitative data collection

Chapter outline.

• Ethical responsibility and cultural respect (5 minute read)
• Critical considerations (3 minute read)
• Preparations for the data gathering process (6 minute read)
• Interviews (20 minute read)
• Focus groups (15 minute read)
• Observations (6 minute read)
• Documents and other artifacts (13 minute read)

Content warning: examples in this chapter contain references to multiple demands on students’ time, loss of employment, sexual assault, trauma-informed care, inpatient psychiatric services, immigration, and the Holocaust.

In this chapter we will explore information to help you plan for and organize your strategy to gather your qualitative data. You will face a number of decisions as you plan this section of your proposal. Gathering qualitative data comes with important ethical and cultural responsibilities. Furthermore, qualitative research can be a powerful tool, but we need to be thoughtful as to how it will be used, as it can as easily become a tool of oppression as one of empowerment. Below are some considerations to help you reflect on some of these dynamics as you plan your study. The first sections apply to every type of qualitative research. Then, we discuss specific strategies to choose from as you plan your qualitative study.

18.1 Ethical responsibility and cultural respect

Learning objectives.

Learners will be able to…

• Explain the special considerations researchers should keep in mind as they design qualitative studies and collect qualitative data
• Determine steps that can be taken to protect participants and exhibit cultural respect during qualitative data collection

Because qualitative data collection so often involves direct contact with human participants and requesting them to share detailed and potentially personally sensitive information with us as researchers, we need to be especially sensitive to ethical considerations. It is a process that requires forethought, planning, and mindful attention throughout. Below are some ethical considerations to help guide you in this activity.

Special limitations to anonymity, confidentiality and ability to remove or withdraw data

Because with qualitative research we are often meeting with people in person to gather data, either from interviews , focus groups , or observations , we clearly can’t guarantee them anonymity . This makes it all the more important to consider what you will do to protect the confidentiality of your participants. This may involve using steps like:

• Using pseudonyms or assigned study identification codes rather than names on study materials
• Stripping all potentially identifying information from transcripts
• Keeping signed informed consent forms separate from other data so the two can’t be linked
• Ensuring that when data is not being used it is appropriately stored and locked so that others outside the research team don’t have access to it
• Ensuring that when data is being used it is not in a space (in person or virtual) where people outside the research team can view it
• Making sure that all members of your research team have been approved by your IRB
• Being very clear in your informed consent who will have access to data and for what purposes

Additionally, at times we will write into our informed consent that participants may withdraw from a study at any time. When a person expresses a desire to withdraw, we remove their data from the study. However, let’s say we conducted interviews and identified a theme that was present in their interview, but was also in a number of other interviews. Their ideas would still be represented in our findings, but we would make sure not to use any quotes or unique contributions from that individual. Also, if a person participates in a focus group, they are part of an interactive dialogue and the discussion is often connected to ideas shared by others as the conversation evolves, making it very hard to completely remove their data. Again, we would respect their wishes by not using any of their direct words, but their presence and contributions shaped the discussion in ways that we won’t be able to excise. It is best to be upfront about this as you are seeking informed consent.

• What steps will you be taking to protect the qualitative data that is shared with you?

Prepare with competence, enter with humility

When we ask people to share their thoughts, feelings, and experiences with us, we need to do so in a way that demonstrates respect and authenticity . This means that we approach participants in a professional manner that reflects both competence as a researcher and that illustrates we have done some preparation to learn about the population ahead of time (that we are not “coming in cold”). Activities that can help to demonstrate this are:

• Speaking with knowledgeable community members regarding the topic, our research design, and important aspects of the community (contemporary and historical) before beginning our data collection)
• Examining previous research and other sources of information regarding the group/community we are interested in work with, or if not available, groups/communities that may be similar
• Using data from the first two bullet points, we design our data collection in a way that is culturally sensitive (e.g. where we ask people to provide data, what tools we use, our wording)
• Preparing research materials (e.g. informed consent forms, recruitment materials, informational sheets) that are accessible and understandable for participants
• Providing information and education about research in general and our research topic specifically

This needs to be tempered with humility. Participants grant us the privilege of allowing us to witness some piece of their life. We need to have humility in knowing that we can never fully understand their experiences because we are not them. In a real sense, we are the learners and they are the teachers. Despite us doing the pre-work discussed above to become more competent in our approach, humility means we will ask the participant directly what is acceptable in respect to our data collection. I believe that when taking a culturally humble approach that we should take at least a little bit of time to understand what research means to the participant and what this particular topic means to the them, again, by asking them directly.

Key Takeaways

• Qualitative data collection involves special considerations to help ensure the privacy, confidentiality, or anonymity of participants because of the the often intimate and detailed information that we are collecting as qualitative researchers.
• Preparing for qualitative data collection requires that we educate ourselves as researchers in advance about the population we will be working with to guide and develop our data collection plan. Furthermore, from the standpoint of cultural humility, we don’t assume that these preparations are adequate. We need to verify with participants what is culturally acceptable to them as individuals.
• As you prepare for data collection planning, what actions do you plan to take to demonstrate preparations for cultural sensitivity and cultural humility?

18.2 Critical considerations

• Assess factors that may impact community members’ perceptions of researchers and their intentions
• Identify opportunities to support greater reciprocity in researcher-participant relationships (especially as it relates to your proposal)

What/whose interests are represented?

Data is a resource that participants own that they choose to share with us. Think about it: When a smartphone app or computer program wants your personal data, you’re usually asked to read a privacy statement and agree to certain terms. Companies are legally required to notify you about their intentions to use the data you may share. And many companies certainly recognize that your data is a valuable resource and seek it out. As researchers, we have similar responsibilities, but with higher ethical standards.

If we are going to ask participants to share this resource, we need to consider why we need it. Clearly, we are invested in this research for some reason, otherwise we wouldn’t be spending our time doing it. Being upfront and genuine with our participants about why this topic is important to us and what we hope comes out of this research is a good first step. We also need to describe to other stakeholders (such as funders or sponsors) who might be involved why we are interested in it. In addition, it is helpful to consider what this research might represent to our participants.

• They may be unsure what to think about the research—This especially may be true if they have had limited exposure to research and/or academia.
• They might be nervous or apprehensive that it could have consequences, either for them individually or for their community
• They might be excited to share their story and may feel as though they are contributing to something larger or some beneficial change

Considering these factors can help us to be more sensitive as we prepare to enter the field for data collection.

Think about your study. Put yourself in the role of research participant.

What information would you want to know?

• About research in general
• About the researcher
• About the research topic

How reciprocal is the arrangement?

Building off the preceding discussion about what research might mean to participants, it is also important to consider the reciprocity in the researcher – participant relationship. We know that we are benefiting from the exchange – we are getting data, research findings, research products and any other advantages or opportunities that might be attached to these. However, the benefits are not always as clear on the participant side of this relationship. Sometimes we are able to provide incentives to honor a participant’s time and contribution to a project, but these are often relatively limited. Participants may also intrinsically value making a contribution to a research project that can eventually help to change or build awareness around something that is important to them, but these are often distant and intangible benefits. While we may not be able to change the fact that we may benefit more from this exchange than our participants, it is important for us to acknowledge this and to consider how this can affect the power differential. We may be asking for a lot, with relatively little to offer in return. This is in contrast to participatory research approaches (which have been discussed elsewhere), in which there is much more of an intentional effort to more equally distribute the benefits of these relationships.

• As a means of developing empathy as a researcher, it is worth considering what the significance or meaning of research is to the populations we are interested in working with. What do we (as researchers) and our projects represent to community members?
• As critical researchers, we need to be considered with the power differences that often exist as we conduct research, especially in the act of asking for data from participants. The request is often lop-sided, with us benefiting considerably more than the participant.

18.3 Preparations for the data gathering process

• Explain important influences to account for in qualitative data gathering
• Organize and document preparatory steps to plan data gathering activities for your qualitative proposal

As you may have guessed from our discussion regarding qualitative research planning and sampling, you have a number of options available for qualitative data gathering, and consequently, a number of choices to make. Your decisions should be driven by your research question and research design, including the resources that are at your disposal for conducting your study. Remember, qualitative research is a labor-intensive venture. While it may not require lots of fancy equipment, it requires a significant investment of people’s time and potentially other resources (e.g. space, incentives for participants, transportation). Each source of data (interviews, focus groups, observations, other artifacts), will require separate planning as you approach data gathering.

Our impact on the data gathering process

In the last chapter, you were introduced to the tool of reflexive journaling as a means of encouraging you to reflect on and document your role in the research process. Since qualitative researchers generally play a very active and involved role in the data gathering process (e.g. conducting interviews, facilitating focus groups, selecting artifacts), we need to consider ways to capture our influence on this part of the qualitative process. Let’s say you are conducting interviews. As you head into the interview, you might be bringing in thoughts about a previous interview, a conversation you just had with your research professor, or worries about finishing all your assignments by the end of the semester! During the interview, you are likely to be surprised by some things that are said or some parts may evoke strong emotions. These responses may lead you to consider pursuing a slightly different line of questioning, and potentially highlighting or de-emphasizing certain aspects. Understanding and being aware of your personal reactions during the data collection process is very important. As part of your design and planning, you may specify that you will reflexively journal before and after each interview in an attempt to capture pre- and post-interview thoughts and feelings. This can help us to consider how we influence and are influenced by the research process. Towards the end of this chapter, after we have had a chance to talk about some of these data gathering strategies, there is a reflexive journal prompt to help you consider how to begin to reflect on the way you as a researcher might impact your work and how you work might impact you.

Decision Point

How will you account for your role in the research process?

• This may be your reflexive journal or you may have other thoughts about how you can account for this.
• Whatever you choose, how will you develop a routine/habit around this to ensure that you are regularly implementing this?

Reflexive Journal Entry Prompt

This is going to be a bit meta, but for this prompt, I want you reflect on the reflecting you are doing for your reflexive journaling.

• Do you see this as a potentially helpful tool for tracking your influence and reactions? What appeals to you? What puts you off?
• If so, how did you develop this mindset?
• If not, how can you strengthen this skill?

When are we done

Finally, as you plan for your data collection you need to consider when to stop. As suggested previously in our discussion on sampling, the concept of saturation is important here. As a reminder, saturation is the point at which no new ideas or concepts are being presented as you continue to collect new pieces of data. Again, as qualitative researchers, we are often collecting and analyzing our data simultaneously. This is what enables us to continue screening for the point of saturation. Of course, not all studies utilize the point of saturation as their determining factor for the amount of data they will collect. This may be predetermined by other factors, such as restricted access or other limitations to the scope of the investigation. While there is no hard and fast rule for the quantity of data you gather, the quality is important; you want to be comprehensive, consistent, and systematic in your approach.

Next, we will discuss some of the different approaches to gathering qualitative data. I’m going to start out with Table 18.1 that allows us to compare these different approaches, providing you with a general framework that will allow us to dive a bit deeper into each one. After you finish reading this chapter, it might be helpful to come back to this table as you continue with your proposal planning.

• As you are preparing to initiate data collection, make sure that you have a plan for how you will capture and document your influence on the process. Reflexive journaling can be a useful tool to accomplish this.
• Be sure to take some time to think about when you will end your data collection. Make this an intentional, justified decisions, rather than a haphazard one.

18.4 Interviews

• Identify key considerations when planning to use interviewing as a strategy for qualitative data gathering, including preparations, tools, and skills to support it
• Assess whether interviewing is an effective approach to gather data for your qualitative research proposal

A common form of qualitative data gathering involves conducting interviews . Interviews offer researchers a way to gather data directly from participants by asking them to share their thoughts on a range of questions related to a research topic. Interviews are generally conducted individually, although occasionally couples (or other dyads , which consist of a combination of two people) may be interviewed. Interviews are a particularly good strategy for capturing unique perspectives and exploring experiences in detail. People may have a host of responses to the request to be interviewed, ranging from flat out rejection to excitement at the opportunity to share their story. As you plan to conduct your interviews you will need to decide on your delivery method, how you will capture the data, you will construct your interview guide , and hone your research interviewing skills.

Delivery method

As technology has advanced, so too have our options for conducting interviews. While in-person interviews are generally still the mainstay of the qualitative researcher, phone or video-based interviews have expanded the reach of many studies, allowing us to gain access to participants across vast distances with relatively few resources. Interviewing in-person allows you to capture important non-verbal and contextual information that will likely be limited if you choose to conduct your interview via phone or video. For instance, if we conduct an interview by phone, we miss the opportunity to see how our participant interacts with their surroundings and we can’t see if their arms are crossed or their foot is fidgety. This may indicate that a certain topic might make them particularly uncomfortable. Alternatively, we may pose a question that makes a smile come across their face. If we are interviewing in person, we can ask a follow-up question noting the smile as a change in their expression, however, it’s hard to hear a smile over the phone! Additionally, there is something to be said for the ability to make a personal connection with your interviewee that may help them to engage more easily in the interview process. This personal connection can be challenging over the phone or mediated by technology. As an example, I often offer to my students that we can meet for “virtual” office hours using Zoom if it is hard for them to get to campus. However, they will often prefer to come to campus, despite the inconvenience because they would prefer to avoid the technology.

Regardless of which method you select, make sure you are well prepared. If you are meeting in person, know where you are going and allow plenty of time to get there. Remember, you are asking someone to give up their time to speak with you, and time is precious! When determining where you will meet for your interview, you may choose to meet at your office, their home, or a neutral setting in the community. If meeting somewhere in the community, do consider that you want to choose a place where you can reasonably assure the participant’s privacy and confidentiality as they are speaking with you. In most instances, I try to ask participants where they would feel most comfortable meeting. If you are speaking over phone or video, make sure to test your equipment ahead of time so that you are comfortable using it, and make sure that both you and the participant have access to a private space as you are speaking. If participants have minor children, plan ahead for whether the children should stay in the same space as the interview. If not, you may need to arrange child care or at least discuss child care with participants in advance. We also want to be mindful of how we are situated during an interview, ideally minimizing any power imbalances. This may be especially important when meeting in an office, making sure to sit across from our participants rather than behind a desk.

Capturing the data

You will also need to consider how you plan to physically capture your data. Some researchers record their interviews, using either a smartphone or a digital recording device. Recording the exchange allows you to have a verbatim record, which can allow the researcher to more fully participate in the interview, instead of worrying about capturing everything in writing. However, if there is a problem with recording – either the quality of the recording or some other equipment malfunction, the researcher can be up the proverbial creek without a paddle. Additionally, using a recording device may be perceived as a barrier between the researcher and the participant, as the participant may not feel comfortable being recorded. If you do plan to record, you should always ask permission first and announce clearly when you are starting and stopping the recording. If you will use recording equipment, be sure to test it carefully in advance, and bring backup batteries/phone charger with you.

The alternative to recording is taking field notes. Field notes consist of a written record of the interview, completed during the interview. You may elect to take field notes even if you are recording the interview, and most people do. This allows us to capture main ideas that stand out to us as researchers, nonverbal information that won’t show up in a recording, and some of our own reactions as the interview is being conducted. These field notes become invaluable if you have a problem with your recording. Even if you don’t, they provide helpful information as you interpret the data you do have in your transcript (the typed version of your recording).

If you are not recording and are relying completely on your notes, it is important to know that you are not going to capture every word and that you shouldn’t try. You want to plan in advance how you will structure your notes so that they make sense to you and are easy to follow. Try to capture all main ideas, important quotes that stand out, and whenever possible, use the participant’s own words. We need to recognize that when we paraphrase what the person is stating, we are introducing our ‘spin’ on it – their ideas go through our filter. We likely can’t avoid some of this, but we do want to minimize it as much as possible. Part of how we do this when we are relying on field notes is to take our interview notes and create expanded field notes , ideally within 24 hours of the interview. The longer you wait to expand your field notes, the less reliable they become, as our memory fades quickly! Much like they sound, expanded field notes take our jottings from the interview and expand them, providing more detail regarding the context or meaning of the statements that were captured. Expanded field notes may also contain questions, comments, or reactions that we, as the researcher, may have had to the data, which are usually kept in the margins, rather than in the body of the notes.

Below are a few resources to learn more about taking quality field notes. Along with the reading, practice, practice, practice!

Resources to learn more about capturing your Field Notes:

Deggs, D., & Hernandez, F. (2018). Enhancing the value of qualitative field notes through purposeful reflection .

Robert Wood Johnson Foundation (2008). Qualitative guidelines project: Fieldnotes .

University of Southern California Libraries. (2019). Research guides: Organizing your social sciences research paper, writing field notes .

Wolfinger, N. (2002). On writing fieldnotes: Collection strategies and background expectancies.

Interview guide

The questions that you ask during your interview will be outlined in a tool called an interview guide . Along with your interview questions, your interview guide will also often contain a brief introduction reminding the participant of the topics that will be covered in the interview and any other instructions you want to provide them (note: much of this will simply serve as a reminder of what you already went over in your informed consent, but it is good practice to remind them right before you get started as well). In addition, the guide often ends with a debriefing statement that thanks the participant for their contribution, inquires whether they have any questions or concerns, and provides contact and resource information as appropriate. Below is a brief interview guide for a study that I was involved with, in which we were interviewing alumni regarding their perceptions of advanced educational needs in the field of social work and specifically their thoughts about practice doctorate of social work (DSW) degrees/programs.

Some interviews are prescribed or structured, with a rigid set of questions that are asked consistently each time, with little to no deviation. This is called a structured interview . More often however, we are dealing with semi-structured interviews , which provide a general framework for the questions that will be asked, but- contain more flexibility to pursue related topics that are brought up by participants. This often leads to researchers asking unplanned follow-up questions to help explore new ideas that are introduced by participants. Sometimes we also use unstructured interviews . These interview guides usually just contain a very open-ended talking prompt that we want participants to respond to. If we are using a highly structured interview guide, this suggests we are leaning toward deductive reasoning apporach—we have a pretty good idea based on existing evidence what we are looking for and what questions we want to ask to help us test our existing understanding. If we are using an unstructured guide, this suggests we are leaning toward an inductive reasoning approach—we start by trying to get people to elaborate extensively on open-ended questions to provide us with data that we will use to develop our understanding of this topic.

An important concept related to the contents of your interview guide is the idea of emergent design . With qualitative research we often treat our interview guide as dynamic, meaning that as new ideas are brought up, we may integrate these new questions into our interview guide for future interviews. This reflects emergent design, as our interview guide shifts to accommodate our emerging understanding of the research topic as we are gathering data. If you do plan to use an emergent design approach in your interviews, it is important to acknowledge this in your IRB application. When you submit your application, you will need to provide the IRB with your interview guide so that they have an idea of the questions you will be discussing with participants. While using an emergent approach to some of your questions is generally acceptable (and even expected), these questions still should be clearly relevant and related to what was presented in your IRB application. If you find that you begin diverging into new areas that are substantively different from this, you should consider submitting an IRB addendum that reflects the changes, and it may be a good idea to consult with your IRB to see if this is necessary.

Designing interview questions and probes

Making up questions, it sounds easy right? Little kids are running around asking questions all the time! However, what you quickly find when conducting research is that it takes skills, ingenuity and practice to craft good interview questions. If you are conducting an unstructured interview, you will generally have fewer questions and they will be quite broad. Depending on your topic, you might ask questions like:

• Tell me about a time…
• What was it like to…
• What should people understand about…
• What does it mean to…

If your interview is more structured, your questions will be a bit more focused, but with qualitative interviewing, we are still generally trying to get people to open up about their experiences with something, so you will want to design questions that will help them to do this. Probes can be important tools to help us accomplish this. You can think of probes as brief follow-ups that are attached to a particular question that will help you explore a topic a bit further. We usually develop probes either through existing literature or knowledge on a topic, or we might add probes to our interview guide as we begin data collection based on what previous participants tell us. As an example, I’m very interested in research on the concept of wellness. I know that the Substance Abuse and Mental Health Services Administration (SAMHSA) has adopted a heuristic tool, The Wheel of Wellness , that outlines eight dimensions of wellness based on research by Swarbrick (2006). [1] When interviewing participants with the broad, unstructured question “What does wellness mean in your life?”, I might use these eight dimensions that are spokes of this wheel (i.e. emotional, spiritual, intellectual, physical, environmental, financial, occupational, and social) as probes to explore if/how these dimensions might be relevant in the lives of these participants. Probes suggest that we are anticipating that certain areas may be relevant to our question.

Here are a few general guidelines to consider when crafting your interview questions.

Make them approachable

We are usually relatively unfamiliar with our participants, at least on a personal level. This can make sitting down for an interview where we might be asking some deep questions a bit awkward and uncomfortable, at least at first. Because of this, we want to craft our questions in such a way that they are not off-putting, inadvertently accusatory or judgmental, or culturally insensitive. To accomplish this, we want to make sure we phrase questions in a neutral tone (e.g. “Tell me what that was like”, as opposed to, “That sounds horrible, what was that like”). To accomplish this, we can shift perspectives and think about what it would be like for us to be asked these questions (especially by a stranger). Pilot testing is especially important here. You should plan in time for this, both conducting pilot testing and incorporating feedback on questions. Pilot testing involves you taking your questions on a dry-run with a few people outside of your sample. You might consider testing these out with peers, colleagues, or friends to get their perspective. You might want to get feedback on:

• Did the question make sense to them?
• Did they know what information you were looking for and how to respond?
• What was it like to be asked that question?
• What suggestions do they have for rephrasing the question (if it wasn’t clear)?

Also, if we are conducting interviews on topics that may be particularly hard for people to talk about, we will likely want to start out with some questions that are easier to address prior to getting into the heavier topics.

Make them relatable

Unlike surveys, where researchers may not be able to explain the meaning of a question, with interviews, we are present to help clarify questions if needed. However, ideally, our questions are as clear as possible from the beginning. This means that we avoid jargon or technical terms, we anticipate areas that might be hard to explain and try to provide some examples or a metaphor that might help get the point across, and we do our homework to relay our questions in an appropriate cultural context. Like the discussion above, pilot testing our questions can be very helpful for ensuring the relatability of our questions, especially with community representatives. When pilot testing, do your best to test questions with a person/people from the same culture and educational level as the future participants. What sounds good in our heads might make little sense to our intended audience.

Make them individually distinct, but collectively comprehensive

Just like when we are developing survey questions, you don’t want to ask more than one question at the same time. This is confusing and hard to respond to for the participant, so make sure you are only asking about one idea in each question. However, when you are thinking about your list of questions, or about your interview guide collectively, ensure that you have comprehensively included all the ideas related to your topic. It’s extremely disheartening for a qualitative researcher that has concluded their interviews to realize there was a really important area that was not included in the guide. To avoid this, make sure to know the literature in your area well and talk to other people who study this area to get their perspective on what topics need to be included. Additional topics may come up when you pilot test your interview questions.

Interview skills

As social workers, we receive much training regarding interviewing and related interpersonal skills. Many of these skills certainly transfer to interviewing for research purposes, such as attending to both verbal and non-verbal communication, active listening, and clarification. However, it is also important to understand how a practice-related interview differs from a research interview.

The most important difference has to do with providing clarity around the purpose of the interview. For a practice-related interview, we are gathering information to help understand our client’s situation and better meet their needs. The interview is a means to provide quality services to our clients, and the emphasis is on the client and resources flowing to them. However, the research interview is ideologically much different. The interview is the means and the end. The purpose of the interview is to help answer the research question, but most often, there is little or limited direct benefit to the participant. The researcher is largely the beneficiary of the exchange, as the participant provides us with data. If the participant does become upset or is negatively affected by their participation, we may help facilitate their connection with appropriate support services to address this, such as counseling or crisis numbers (and indeed, this is our ethical obligation as a competent researcher). However, counseling and treatment is not our responsibility when conducting research interviews and we should be very careful not to confuse it as such. If we do act in this way, it creates the potential for a dual relationship with the interviewee (participant and client) and puts them in a vulnerable situation. Make sure you are clear what your role is in this encounter.

Along with recognizing the focus of your role, here is a checklist of general tips for qualitative interviewing skills:

• Approach the interview in a relaxed, but professional manner
• Be observant of verbal, nonverbal, and contextual information
• Exhibit a non-judgmental stance
• Explain information clearly and check for comprehension
• Demonstrate respect for your participants and be polite
• Utilize much more listening and much less talking
• Check for understanding when you are unclear, rather than making assumptions
• Know your materials and technology (e.g. informed consent, interview guide, recording equipment)
• Be concise, clear and organized as you are taking notes
• Have a structured approach for what you need to cover and redirect if the conversation is losing focus
• Be flexible enough so that the interview does not become impersonal and disengaging due to rigidity of your agenda
• Data collection through interviewing requires careful planning for both how we will conduct our interviews (e.g. in person, over the phone, online) and the nature of the interview questions themselves. An interview guide is an important document to develop in planning this.
• Qualitative interviewing uses similar skills to clinical interviewing, but is markedly different. This difference is due in large part to the very different purpose of these two activities.

Let’s get some practice!

Thinking about your topic, if you were to use interviewing as an approach for data collection, identify 4 interview questions that you would consider asking about your topic. Make sure these are open-ended questions so that your participants can elaborate on them.

• Interview question 1:
• Interview question 2:
• Interview question 3:
• Interview question 4:

Now pilot these. Ask a peer to read these questions and think about trying to answer them. You aren’t interested in their actual answers, you want feedback about how these questions were.

• Were they understandable and clear?
• Were they potentially culturally insensitive or offensive in any way?
• Are they something that it seems reasonable that someone could answer (especially with a researcher they likely don’t know previously)?
• Are they asked in a way that are likely to get people to elaborate (rather than just give a one-word answer)?
• What suggestions do they have to address all/any of these areas?

Based on your peer feedback, re-write your four questions incorporating their suggestions.

• Revised interview question 1:
• Revised interview question 2:
• Revised interview question 3:
• Revised interview question 4:

Resources for learning more about conducting Qualitative Interviews.

Baker, S. E., & Edwards, R. (2012) National Centre for Research Methods review paper: How many qualitative interviews is enough?

Clifford, S. Duke University Initiative on Survey Methodology at the Social Science Research Institute (n.d.). Tipsheet: Qualitative interviews.

Harvard University Sociology Dept. (n.d.). Strategies for qualitative interviews .

McGrath et al., (2018). Twelve tips for conducting qualitative research interviews .

Oltmann, S. M. (2016). Qualitative interviews: A methodological discussion of the interviewer and respondent contexts .

A few exemplars of studies employing Interview Data:

Ewart‐Boyle, S., Manktelow, R., & McColgan, M. (2015). Social work and the shadow father: Lessons for engaging fathers in Northern Ireland .

Flashman, S. H. (2015). Exploration into pre-clinicians’ views of the use of role-play games in group therapy with adolescents .

Irvin, K. (2016). Maintaining community roots: understanding gentrification through the eyes of long-standing African American residents in West Oakland .

18.5 Focus groups

• Identify key considerations when planning to use focus groups as a strategy for qualitative data gathering, including preparations, tools, and skills to support it
• Assess whether focus groups are an effective approach to gather data for your qualitative research proposal

Focus groups offer the opportunity to gather data from multiple participants at once. As you have likely learned in some of your practice coursework, groups can help facilitate an environment where people feel (more) comfortable sharing common experiences which can often allow them to delve deeper into topics than they may have individually. As people relate to what others in the group say, they often go on to share their responses to these new ideas – offering a collaborative synergy. Of course, similar to the research vs. clinical interview described above, the purpose of the focus group is much different than that of the therapeutic, psychoeducational, or support group. While other elements (e.g. information sharing, encouragement) may take place, the aim of the focus group must remain anchored in the collection of data and that should be made explicitly clear so participants have accurate expectations. As a cautionary note, the advantages discussed above should be the reason you choose to use a focus group to collect data. You should not choose to conduct a focus group solely out of convenience. Focus groups require a considerable amount of planning and skill to execute well, so it is not reasonable to think that just because a focus group allows you to collect data from multiple participants at once that it is an easier option for data gathering.

Group assembly

Assembling your focus group is an important part of your planning process. Generally speaking, focus groups shouldn’t exceed 10-12 participants. When thinking about size, there are a couple things to consider. On the lower end, you do want enough participants so that they don’t feel pressure to be constantly speaking. I f you only have a couple of focus group members, it loses most of the collective benefit of the focus group approach, as there are few people to generate and share ideas. On the higher end, you want to avoid having so many participants that not everyone gets to be heard and the group conversation becomes unwieldy and hard to manage.

As you are forming your group, you want to strike up a balance between heterogeneity (difference) and homogeneity (sameness) between your group members. If the group is too heterogeneous, then opinions may be so polarized that it is hard to have a productive conversation about the topic. People may not feel comfortable sharing their opinion or it may be difficult to gain a common understanding across the data. If the group is too homogeneous, then it may be hard to get much depth from the data. People may see the topic so similarly that we don’t gain much information about how differing perspectives think about the issue. You generally want your group composition to be different enough to be interesting and produce good conversation, but similar enough that members can relate to each other and have a cohesive conversation. Along these lines, you also need to consider whether or not your participants know each other. Do they have existing relationships? If they do know each other, we need to anticipate that there may be existing group dynamics. This may influence how people engage in discussion with us. On one hand, they may find it easy to share more freely. However, these dynamics may inhibit them from speaking their mind, as they might be concerned about repercussions for sharing within their social network.

As a final note on group composition, sometimes we make decisions on group members’ characteristics based on our topic. For instance, if we are asking questions about help-seeking and common experiences after (heterosexual) sexual assault, it may be challenging to host a mixed-gender group, where participants may feel triggered or guarded having members of the opposite gender present and therefore potentially less open to sharing. It is important to consider the population you are working with and the types of questions you are asking, as this can help you to be sensitive to their perceptions and facilitate the creation of a safe space. Other issues, such as race, age, levels of education, may require consideration as you think about your group composition.

Related to feelings of safety, the setting you select for your focus group is an important decision. Much like with interviews, we want participants to feel as comfortable and at-ease as possible, however, it is perhaps less common to use someone’s home for the purpose of a focus group because we are often bringing together people who may not know one another. As such, try to select a place that feels neutral (e.g. some people may not feel comfortable in a church or a courthouse), accessible, convenient, and that offers privacy for participants. If you are working with a particular group or community, there may be a space that is especially relevant or familiar for people that may work well for this purpose. A c ommunity gatekeeper or other knowledgeable community member can be an excellent resource in helping to identify where a good spa ce might be. Seating in a circle will help participants to share more easily. Focus group organizers often provide refreshments as an incentive and to make participants feel more comfortable. If you decide to provide refreshments, be sensitive to issues like common dietary restrictions and cultural preferences.

Roles of the researcher(s)

Ideally, you are conducting your focus group with a co-researcher. This is important because it allows you to divide up the tasks and makes the process more manageable. Most often, one of you will take on the main facilitator role, with responsibilities for providing information and instructions, introducing topics, asking follow-up questions and generally structuring the encounter. The other person takes on a note-taking/processing role. While not necessarily silent, they likely say very little during the focus group. Instead, they are focused on capturing the context of the encounter. This may include taking notes about what is said, how people respond or react, other details about the space and the overall exchange as a whole. They will also often be especially attentive to group dynamics and capturing these whenever possible. Along with this, if they see that certain group members are dominating or being left out of the conversation, they may help the facilitator to address or shift these dynamics so that the sharing is more equitable. Finally, if something arises where a participant becomes upset or there is an emergency where they need to leave the room, having a co-researcher allows one of you to remain with the group, while the other can attend to the person in distress. For consistency sake, you may want to maintain roles throughout data collection. If you do decide to alternate roles as you conduct multiple focus groups, it is important that you both conduct the respective roles as similarly as possible. Remember, research is about the systematic collection of data, so you want your data collection to follow a consistent process. Below is a chart that offers some tips for each of these roles.

Focus group guide and preparations

As in your preparation for an interview, you will want to spend considerable time developing your focus group guide and the questions it contains. Be sure the language you use in your questions is appropriate for the educational level of your participants; you will need to use vocabulary that is clear and not “jargon”. At the same time, you also want to avoid talking down to your participants. You will probably want to start with some easier, non-threatening questions to help break the ice for the group and help get folks comfortable talking and sharing their input. Be prepared to ask questions in a different way or follow up with probes to help prod the conversation along if a question falls flat or fails to elicit a dialogue. In addition, you will want to plan introductions, both to the study and to one another. Usually we stick to first names, and occasionally during introductions, participants will share how they are connected to the topic of the research. Just like in many practice-related groups, facilitators usually take time to review group norms and expectations before getting started with questions. Some common norms to discuss are:

• Not talking over other participants
• Being respectful of other participants’ contributions
• All people are expected to participate in the conversation
• Not pressuring people to respond to a question if they are uncomfortable
• Using respectful language and avoiding derogatory, discriminatory or accusatory language or tone
• Not using electronic devices and silencing cell-phones during the focus group
• Allowing others ample time to contribute to the conversation and not dominating the discussion

Another expectation to address that is especially important to include is confidentiality . It is important to make clear to participants that what is shared in the group should be kept confidential and not discussed outside the context of the focus group. Additionally, it is important to let participants know that while the researchers ask all participants to protect the confidentiality of what is shared, they can’t guarantee that will be honored. Below figure 18.4 offers an example of a focus group guide template to help you think about how to structure this type of document.

Capturing your data

Finally, as with interviews, you will need to plan how you will capture the data from your focus group(s). Again, you may choose to record the focus groups, take fie ld notes, or use a combination of both. There are some special considerations that apply to these choices when using a focus group, however. First, if recording, anticipate that it may be especially challenging when transcribing the recording to determine who said what. In addition, the quality of the recording can become a challenge. Despite requests for individuals to speak one at a time, inevitably there will be spots where there are multi ple people talking at once, especially with an animated group. Additionally, do test the recording devices, ideally in the space you will be using them. You want to make sure that it can pick up everyone’s voice, even if they are soft-spoken and seated a distance from the device. If you are relying solely on a recordi ng and there is a problem with it, it can be difficult to surmount the barriers this can pose . If this occurs with an interview, while not ideal, you can re-interview a person to replace the information, but re-creating a focus group can be a logistical night mare. When taking field notes , it is a good practice to make a quick seating chart at the beginning so you can make quick references for yourself of who is saying what (see Figure 18.5). Regardl ess of what system you use to stay organize d in taking these notes, make sure to have one that works for you. The conversations will likely happen more rapidly and will include multiple voices, so you will want to be prepared in advance.

• Focus groups offer a valuable tool for qualitative data collection when the topic we are exploring might best be understood through a group discussion that helps participants verbally process and consider their experiences, thoughts, and opinions with others.
• Details like focus group composition, roles of co-facilitators, and anticipation of group norms or guidelines require our attention as we prepare to host a focus group.

Reflexive journal prompt

How do you feel about conducting a focus group?

• What about it is appealing
• What about it seems challenging
• Would you prefer to be the main facilitator or the observer (and why)?
• What might make using a focus group a good choice for your specific research question?
• What might make using a focus group a poor choice for your specific research question?

Resources to learn more about conducting Focus Groups.

Leung, F. H., & Savithiri, R. (2009). Spotlight on focus groups .

Duke, ModU (2016, October 19). Powerful concepts in social science: Preparing for focus groups, qualitative research methods

Onwuegbuzie et al. (2009). A qualitative framework for collecting and analyzing data in focus group research .

Nyumba et al. (2018). The use of focus group discussion methodology: Insights from two decades of application in conservation .

Robert Wood Johnson Foundation (2008). Qualitative Guidelines Project: Focus groups.

A few exemplars of studies employing Focus Groups:

Foote, W. L. (2015). Social work field educators’ views on student specific learning needs .

Hoover, S. M., & Morrow, S. L. (2016). A qualitative study of feminist multicultural trainees’ social justice development .

Kortes-Miller, K., Wilson, K., & Stinchcombe, A. (2019). Care and LGBT aging in Canada: A focus group study on the educational gaps among care workers .

18.6 Observations

• Identify key considerations when planning to use observations as a strategy for qualitative data gathering, including preparations, tools, and skills to support it
• Assess whether observations are an effective approach to gather data for your qualitative research proposal

Observational data can also be very important to the qualitative researcher. As discussed in Chapter 17 , observations can provide important information about context, rea ctions, behaviors, exchanges, and expressions. The focus of observations may be indi viduals, i nteractions between people or within groups, environments or settings, or events like artistic expressions (e.g. plays, poetry readings, art shows), public forums (e.g. town hall meetings, community festivals), private forums (e.g. board meetings, family reunions), and finally, your reactions or responses as the researcher to any and all of these. We will be discussing a variety of different types of qualitative designs in Chapter 22 , including ethnography. Observational data is especially important for ethnographic research designs. 

Researcher engagement

Observational data gathering is a more indirect form of data collection when compared with previous methods we have discussed. With both interviews and focus groups, you are gathering data directly from participants. When making observations, we are relying on our interpretation of what is going on. Even though we are often not directly interacting with people, we generally have an ethical responsibility to disclose that we are gathering data by making observations and gain consent to do so. That being said, there are some instances where we are making observations in public spaces, and in these instances disclosure may not be necessary because we are not gathering any identifiable information about specific people. These instances are rare, but if you are in doubt, consult with your IRB.

Even though I just suggested that making observations is often a more indirect form of data gathering, it does exist on a continuum. If utilizing observational data, you will need to consider where you fall on this continuum. Some research designs situate the researcher as an active participant in the community or group that they are studying, while other designs have the researcher as an independent and detached onlooker. In either case, you need to consider how your presence, either involved or detached, may influence the data you are gathering. This requires us to think of this on a more individual or micro level (how do the individuals we are directly observing perceive us) and a more mezzo or even macro level (how does the community or group of people we are studying collectively feel about our presence and our research)? Are people changing their behavior because of your presence? Are people monitoring or censoring what they say? We can’t always know the answers to these questions, but we can try to reduce these concerns by making repeated observations over time, rather than using a one-time, in-and-out data gathering mission. This means actually spending time within the community that is the focus of your observation. Taking the time to make repeated observations will allow you to develop a reasonable framework of understanding, which in turn will empower you to better interpret what you see and help you determine whether your observations and interpretation are consistent.

Observational skills

When gathering observational data, you are often attending to or taking in many different dimensions. You are potentially observing:

• the context of the environment
• the content of what is being said
• behaviors of people
• affective or emotional aspects of interactions
• sequences of events
• your own reactions to what is being observed

To capture this information, you will need to be keenly aware, focused, and organized. Additionally, you need to make sure you are capturing clear descriptions of what is going on. Remember, notes that seem completely logical and easy to understand at the time you are taking them can become vague and confusing with the passage of time and as you gather more and more data. Part of the clarity of your description often involves taking a non-judgmental approach to documenting your observations. While this may seem easy, judgments or biases frequently slip into our thinking and writing (unbeknownst to us). Along with a non-judgmental stance, researchers making observations also attempt to be as unobtrusive as possible. This means being conscious of your behaviors, your dress and overall appearance. If you show up wearing a suit and tie, and carrying a clipboard while everyone else is wearing jeans and t-shirts, you are likely to stick out like a sore thumb. This is also likely to influence how participants respond and interact with you. Know the environment that you are making your observations in, with a goal of blending in as much as possible.

Observational data is most often captured using field notes. Using recordings for observational data is infrequently used in social work research. This is especially true because of the potential for violations of privacy and threats to confidentiality that recordings (video or audio) may pose to participants. Mirroring our discussion above, when taking field notes, make sure to be organized and have a plan for how you will structure your notes so they are easy to interpret and make sense to you. Creswell (2013) [2] suggests capturing ‘descriptive’ and ‘reflective’ aspects in your observational field notes. Table 18.3 offers some more detailed description of what to include as you capture your data and corresponding examples.

For the purposes of qualitative research, our observations are generally unstructured or more naturalistic . However, you may also see mention of more systematic or structured observations. This is more common for quantitative data collection, where we may be attempting to capture or count the frequency with which a specific behavior or event occurs.

• Observational data collection can be an effective tool for gathering information about settings, interactions, and general human behavior. However, since this is gathered strictly through the researchers own direct observation, it is not a source of data on people’s thoughts, perceptions, values, opinions, beliefs or interpretations.
• There are a range of aspects that we may want to take note of while we are observing (e.g. the setting, interactions, descriptions of people, etc.).
• While we are making our observations, we generally want to do so as inconspicuously and non-judgmentally as possible.

Resources for learning more about conducting Qualitative Observations.

Kawulich, B.B. (2005, May) Participant observation as a data collection method .

Kawulich, B.B. (2012). Collecting data through observation . In C. Wagner, B. Kawulich, & M. Garner (Eds.), Doing social research: A global context ( 150-160). New York: McGraw Hill.

Robert Wood Johnson Foundation (2008). Qualitative Guidelines Project: Observations .

Sliter, M. (2014, June 30). Observational methods: Research methods.

A few exemplars of studies employing qualitative observations:

Avby et al. (2017). Knowledge use and learning in everyday social work practice: A study in child investigation work .

Wilkins et al. (2018). A golden thread? The relationship between supervision, practice, and family engagement in child and family social work .

Wood et al. (2017). The “gray zone” of police work during mental health encounters: Findings from an observational study in Chicago .

18.7 Documents and other artifacts

• Identify key considerations when planning to analyze documents and other artifacts as a strategy for qualitative data gathering, including preparations, tools, and skills to support it
• Assess whether analyzing documents and other artifacts is an effective approach to gather data for your qualitative research proposal

Qualitative researchers may also elect to utilize existing documents (e.g. reports, newspapers, blogs, minutes) or other artifacts (e.g. photos, videos, performances, works of art) as sources of data. Artifact analysis can provide important information on a specific topic, for instance, how same-sex couples are portrayed in the media. They also may provide contextual information regarding the values and popular sentiments of a given time and/or place. When choosing to utilize documents and other artifacts as a source of data for your project, remember that you are approaching these as a researcher, not just as a consumer of media. You need to thoughtfully plan what artifacts you will include, with a clear justification for their selection that is solidly linked to your research question, as well as a plan for systematically approaching these artifacts to identify and obtain relevant information from them.

Obtaining your artifacts

As you begin considering what artifacts you will be using for your research study, there are two points to consider: what will help you to answer your research question and what can you gain access to. In addressing the first of these considerations, you may already have a good idea about what artifacts are needed because you have done a substantial amount of preliminary work and you know this area well. However, if you are unsure, or you need to supplement your existing knowledge, some general sources can include: librarians, historians, community experts, topical experts, organizations or agencies that address the issue or serve the population you will be studying, and other researchers who study this area. In considering access, if the artifacts are public the answer may be a straightforward yes, but if the documents are privately held, you may need to be granted permission – and remember, this is permission to use them for research purposes, not just to view them. When obtaining permission, get something in writing, so that you have this handy to submit with your IRB application. While the types of artifacts you might include are almost endless (given they are relevant to your research question), Table 18.4 offers a list of some ideas for different sources you might consider:

Artifact analysis skills

Consistent with other areas of research, but perhaps especially salient to the use of artifacts, you will require organizational skills. Depending on what sources you choose to include, you may literally have volumes of data. Furthermore, you might not just be dealing with a large amount of data, but also a variety of types of data. Regardless of whether you are using physical or virtual data, you need to have a way to label and catalog (or file) each artifact so that you can easily track it down. As you collect specific information from each piece, make sure it is tagged with the appropriate label so that you can track it back down, as you very well may need to reference it later. This is also very important for honest and transparency in your work as a qualitative researcher – documenting a way to trace your findings back to the raw data .

In addition to staying organized, you also need to think specifically about what you are looking for in the artifacts. This might seem silly, but depending on the amount of data you are dealing with and how broad your research topic is, it might be hard to ‘separate the wheat from the chaff’ and figure out what is important or relevant information. Sometimes this is more clearly defined and we have a prescribed list of things we are looking for. This prescribed list may come from existing literature on the topic. This prescribed list may be based on peer-reviewed literature that is more conceptual, meaning that it focuses on defining concepts, putting together propositions, formulating early stage theories, and laying out professional wisdom, rather than reporting research findings. Drawing on this literature, we can then examine our data to see if there is evidence of these ideas and what this evidence tells us about these concepts. If this is the case, make sure you document this list somewhere, and on this list define each item and provide a code that you can attach when you see it in each document. This document then becomes your codebook .

However, if you aren’t clear ahead of time what this list might be, you may take an emergent approach, meaning that you have some general ideas of what you are seeking. In this event, you will actively create a codebook as you go, like the one described above, as you encounter these ideas in your artifacts. This helps you to gain a better understanding of what items should be included in your list, rather than coming in with preconceived notions about what they should be. There will be more about tracking this in our next chapter on qualitative analysis. Whether you have a prescribed list or use a more emergent design to develop your codebook, you will likely make modifications or corrections to it along the way as your knowledge evolves. When you make these changes, it is very important to have a way to document what changes you made, when, and why. Again, this helps to keep you honest, organized, and transparent. Just as another reminder, if you are using predetermined codes that you are looking for, this is reflective of a more deductive approach, whereas seeking emergent codes is more inductive .

Finally, when using artifacts, you may also need to bring in some creative, out-of-the-box thinking. You may be bringing together many different pieces of data that look and sound nothing alike, yet you are seeking information from them that will allow you tell a cohesive story. You may need to be fluid or flexible in how you are looking at things, and potentially challenge your preconceived notions.

As alluded to above, you may have physical artifacts that you are dealing with, digital artifacts or representations of these artifacts (e.g. videos, photos, recordings), or even field notes about artifacts (for instance, if you take notes of a dramatic performance that can’t be recorded). A large part of what may drive your decisions about how to capture your data may be related to your level of access to those artifacts: can you look at it? Can you touch it, can you take it home with you, can you take a picture of it? Depending on what artifacts we are talking about, some of these may be important questions. Regardless of the answers to these questions, you will need to have a clearly articulated and well-documented plan for how you are obtaining the data and how you will reference it in the future. Table 18.4 provides a list of data gathering activities you might consider, both for documents and for other audiovisual materials.

What types of artifacts might you have access to that might help to answer your research question(s)?

• These could be artifacts available at your field placement, publically available media, through school, or through public institutions
• These can be documents or they can be audiovisual materials
• Think outside the box, how can you gather direct or indirect indications of the thing you are studying

Generate a list of at least 3

Again, drawing on Creswell’s (2013) suggestion of capturing ‘descriptive’ and ‘reflective’ aspects in your field notes, Table 18.5 offers some more detailed description of what to include as your capture your data and corresponding examples when focusing on an artifact.

Resources to learn more about qualitative research with artifacts.

Bowen, G. A. (2009). Document analysis as a qualitative research method .

Rowsell, J. (2011). Carrying my family with me: Artifacts as emic perspectives .

Hammond, J., & McDermott, I. (n.d.). Policy document analysis .

Wang et al. (2017). Arts-based methods in socially engaged research practice: A classification framework .

A few exemplars of studies utilizing documents and other artifacts.

Casey, R. C. (2018). Hard time: A content analysis of incarcerated women’s personal accounts .

Green, K. R. (2018). Exploring the implications of shifting HIV prevention practice Ideologies on the Work of Community-Based Organizations: A Resource dependence perspective . 

Sousa, P., & Almeida, J. L. (2016). Culturally sensitive social work: promoting cultural competence .

Secondary data analysis

I wanted to briefly provide some special attention to secondary data analysis at the end of this chapter. In the past two chapters we have focused our sights most often on what we would call raw data sources . However, you can of course conduct qualitative research with secondary data , which is data that was collected previously for another research project or other purpose; data is not originating from your research process. If you are fortunate enough to have access and permission to use qualitative data that had already been collected, you can pose a new research question that may be answered by analyzing this data. This saves you the time and energy from having to collect the data yourself!

You might procure this data because you know the researcher that collected the original data. For instance, as a student, perhaps there is a faculty member that allows you access to data they had previously collected for another project. Alternatively, maybe you locate a source of qualitative data that is publicly available. Examples of this might include interviews previously conducted with Holocaust survivors. Finally, you might register and join a research data repository . These are sites where contributing researchers can house data that other researchers can view and request permission to use. Syracuse University hosts a repository that is explicitly dedicated to qualitative data . While there are more of these emerging, it may be a challenge to find the specific data you are looking for in a repository. You should also anticipate that data from repositories will have all identifiable information removed. Sharing data you have collected with a repository is a good way to extend the potential usefulness and impact of data, but it also should be anticipated before you collect your data so that you can build it into any informed consent so participants are made aware of the possibility.

Computer Assisted Qualitative Data Analysis Software (CAQDAS)

Some qualitative researchers use software packages known as Computer Assisted Qualitative Data Analysis Software (CAQDAS) in their work. These are tools that can aid researchers in managing, organizing and manipulating/analyzing their data. Some of the more common tools include NVivo, Atlas.ti, and MAXQDA, which have licensing fees attached to them (although many have discounted student rates). However, there are also some free options available if you do some hunting. Taguette Project is the only free and open source CAQDAS project that is currently receiving updates, as previous projects like RQDA which built from the R library are not in active development. Taguette is a young project, and unlike the free alternatives for quantitative data analysis, it lacks the sophisticated analytical tools of commercial CAQDAS programs.

It is unlikely that you will be using a CAQDAS for a student project, mostly because of the additional time investment it will take to become familiar with the software and associated costs (if applicable). In fact the best way to avoid spending money on qualitative data analysis software is to do your analysis by hand or using word processing or spreadsheet software. If you continue on with other qualitative research projects, it may be worth some additional study to learn more about CAQDAS tools. If you do choose to use one of these products, it won’t magically do the analysis for you. You need to be clear about what you are using the software for and how it supports your analysis plan, which will be the focus of our next chapter.

Resources to learn more about CAQDAS.

Maher et al. (2018). Ensuring rigor in qualitative data analysis: A design research approach to coding combining NVivo with traditional material methods .

Woods et al. (2016). Advancing qualitative research using qualitative data analysis software (QDAS)? Reviewing potential versus practice in published studies using ATLAS. ti and NVivo, 1994–2013 .

Zamawe, F. C. (2015). The implication of using NVivo software in qualitative data analysis: Evidence-based reflections .

As you continue to plan your research proposal, make sure to give practical thought to how you will go about collecting your qualitative data. Hopefully this chapter helped you to consider which methods are appropriate and what skills might be required to apply that particular method well. Revisit the table in section 18.3 that summarizes each of these approaches and some of the strengths and challenges associated with each of them. Collecting qualitative data can be a labor-intensive process, to be sure. However, I personally find it very rewarding. In its very forms, we are bearing witness to people’s stories and experiences.

• Artifact analysis can be particularly useful for qualitative research as a means of studying existing data; meaning we aren’t having to collect the data ourselves, but we do have to gather it. As a limitation, we don’t have any control over how the data was created, since we weren’t involved in it.
• There are many sources of existing data that we can consider for artifact analysis. Think of all the things around us that can help to tell some story! Artifact analysis may be especially appealing as a potential time saver for student researchers if you can gain permission to use existing artifacts or use artifacts that are publicly available.
• Artifact analysis still requires a systematic and premeditated approach to how you will go about extract information from your artifacts.

Here are a few questions to get you thinking about the role that you play as you gather qualitative data.

• What are your initial thoughts about qualitative data collection?
• Why might that be?
• What excites you about this process?
• What worries you about this process?
• What aspects of yourself will strengthen or enhance this process?
• What aspects of yourself may hinder or challenge this process?

Decision Point: How will you go about qualitative data collection?

• Justify your choice(s) here in relation to your research question and availability of resources at your disposal
• who will be collecting data
• what will be involved
• how will it be safely stored and organized
• how are you protecting human participants
• if you have a team, how is communication being established so everyone is “on the same page”
• how will you know you are done
• What additional information do you need to know to use this approach?

Media Attributions

• checklist © mohamed_hassan is licensed under a CC0 (Creative Commons Zero) license
• start and finish line © Andrew Hurley is licensed under a CC BY-SA (Attribution ShareAlike) license
• field notes © Tom Carmony is licensed under a CC BY-NC-ND (Attribution NonCommercial NoDerivatives) license
• group talking © Enoz is licensed under a CC BY-NC (Attribution NonCommercial) license
• children watching penguins © Amelia Beamish is licensed under a CC BY-NC (Attribution NonCommercial) license
• Swarbrick, M. (2006). A wellness approach. Psychiatric Rehabilitation Journal, 29 (4), 311. ↵
• Creswell, J. W. (2013). Chapter 7. Data collection. In J. W. Creswell, Qualitative Inquiry & Research Design: Choosing Among Five Approaches (3rd ed.), Los Angeles: Sage ↵
• Harris, M. and Fallot, R. (2001). Using trauma theory to design service systems. New Directions for Mental Health Service s. Jossey Bass; Farragher, B. and Yanosy, S. (2005). Creating a trauma-sensitive culture in residential treatment. Therapeutic Communities, 26 (1), 93-109. ↵

A form of data gathering where researchers ask individual participants to respond to a series of (mostly open-ended) questions.

A form of data gathering where researchers ask a group of participants to respond to a series of (mostly open-ended) questions.

Observation is a tool for data gathering where researchers rely on their own senses (e.g. sight, sound) to gather information on a topic.

The identity of the person providing data cannot be connected to the data provided at any time in the research process, by anyone.

For research purposes, confidentiality means that only members of the research team have access potentially identifiable information that could be associated with participant data. According to confidentiality, it is the research team's responsibility to restrict access to this information by other parties, including the public.

Fake names assigned in research to protect the identity of participants.

Numbers or a series of numbers, symbols and letters assigned in research to both organize data as it is collected, as well as protecting the identity of participants.

A process through which the researcher explains the research process, procedures, risks and benefits to a potential participant, usually through a written document, which the participant than signs, as evidence of their agreement to participate.

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

For the purposes of research, authenticity means that we do not misrepresent ourselves, our interests or our research; we are genuine in our interactions with participants and other colleagues.

An approach to research that more intentionally attempts to involve community members throughout the research process compared to more traditional research methods. In addition, participatory approaches often seek some concrete, tangible change for the benefit of the community (often defined by the community).

A research journal that helps the researcher to reflect on and consider their thoughts and reactions to the research process and how it may be shaping the study

The point where gathering more data doesn't offer any new ideas or perspectives on the issue you are studying.  Reaching saturation is an indication that we can stop qualitative data collection.

A combination of two people or objects

An interview guide is a document that outlines the flow of information during your interview, including a greeting and introduction to orient your participant to the topic, your questions and any probes, and any debriefing statement you might include. If you are part of a research team, your interview guide may also include instructions for the interviewer if certain things are brought up in the interview or as general guidance.

Context is the circumstances surrounding an artifact, event, or experience.

Notes that are taken by the researcher while we are in the field, gathering data.

Expanded field notes represents the field notes that we have taken during data collection after we have had time to sit down and add details to them that we were not able to capture immediately at the point of collection.

A statement at the end of data collection (e.g. at the end of a survey or interview) that generally thanks participants and reminds them what the research was about, what it's purpose is, resources available to them if they need them, and contact information for the researcher if they have questions or concerns.

Interview that uses a very prescribed or structured approach, with a rigid set of questions that are asked very consistently each time, with little to no deviation

An interview that has a general framework for the questions that will be asked, but there is more flexibility to pursue related topics that are brought up by participants than is found in a structured interview approach.

Interviews that contain very open-ended talking prompt that we want participants to respond to, with much flexibility to follow the conversation where it leads.

starts by reading existing theories, then testing hypotheses and revising or confirming the theory

when a researcher starts with a set of observations and then moves from particular experiences to a more general set of propositions about those experiences

Emergent design is the idea that some decision in our research design will be dynamic and change as our understanding of the research question evolves as we go through the research process. This is (often) evident in qualitative research, but rare in quantitative research.

Probes a brief prompts or follow up questions that are used in qualitative interviewing to help draw out additional information on a particular question or idea.

Testing out your research materials in advance on people who are not included as participants in your study.

Someone who has the formal or informal authority to grant permission or access to a particular community.

A document that will outline the instructions for conducting your focus group, including the questions you will ask participants. It often concludes with a debriefing statement for the group, as well.

Ethnography is a qualitative research design that is used when we are attempting to learn about a culture by observing people in their natural environment.

Making qualitative observations that attempt to capture the subjects of the observation as unobtrusively as possible and with limited structure to the observation.

The analysis of documents (or other existing artifacts) as a source of data.

unprocessed data that researchers can analyze using quantitative and qualitative methods (e.g., responses to a survey or interview transcripts)

A code is a label that we place on segment of data that seems to represent the main idea of that segment.

A document that we use to keep track of and define the codes that we have identified (or are using) in our qualitative data analysis.

study publicly available information or data that has been collected by another person

in a literature review, a source that describes primary data collected and analyzed by the author, rather than only reviewing what other researchers have found

Data someone else has collected that you have permission to use in your research.

These are sites where contributing researchers can house data that other researchers can view and request permission to use

These are software tools that can aid qualitative researchers in managing, organizing and manipulating/analyzing their data.

Graduate research methods in social work Copyright © 2021 by Matthew DeCarlo, Cory Cummings, Kate Agnelli is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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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.

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Saul McLeod, PhD

Editor-in-Chief for Simply Psychology

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

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

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

On This Page:

Qualitative research is a type of research methodology that focuses on gathering and analyzing non-numerical data to gain a deeper understanding of human behavior, experiences, and perspectives.

It aims to explore the “why” and “how” of a phenomenon rather than the “what,” “where,” and “when” typically addressed by quantitative research.

Unlike quantitative research, which focuses on gathering and analyzing numerical data for statistical analysis, qualitative research involves researchers interpreting data to identify themes, patterns, and meanings.

Qualitative research can be used to:

• Gain deep contextual understandings of the subjective social reality of individuals
• To answer questions about experience and meaning from the participant’s perspective
• To design hypotheses, theory must be researched using qualitative methods to determine what is important before research can begin. 

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? 

Characteristics 

Naturalistic setting.

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

Naturalistic settings provide valuable contextual information to help researchers better understand and interpret the data they collect.

The environment, social interactions, and cultural factors can all influence behavior and experiences, and these elements are more easily observed in real-world settings.

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).

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). 

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 research setting (Scarduzio, 2017).

Interpretive analysis

In qualitative research, interpretive analysis is crucial in making sense of the collected data.

This process involves examining the raw data, such as interview transcripts, field notes, or documents, and identifying the underlying themes, patterns, and meanings that emerge from the participants’ experiences and perspectives.

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.

1. 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). 

2. 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). 

3. 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).

4. 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. 

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

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. 

While individual qualitative studies are often limited in their generalizability due to factors such as sample size and context, metasynthesis enables researchers to synthesize findings from multiple studies, potentially leading to more generalizable conclusions.

By integrating findings from studies conducted in diverse settings and with different populations, metasynthesis can provide broader insights into the phenomenon of interest.

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.

What is narrative analysis?

Narrative analysis is a qualitative research method used to understand how individuals create stories from their personal experiences.

There is an emphasis on understanding the context in which a narrative is constructed, recognizing the influence of historical, cultural, and social factors on storytelling.

Researchers can use different methods together to explore a research question.

Some narrative researchers focus on the content of what is said, using thematic narrative analysis, while others focus on the structure, such as holistic-form or categorical-form structural narrative analysis. Others focus on how the narrative is produced and performed.

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• What Is Qualitative Research? | Methods & Examples

What Is Qualitative Research? | Methods & Examples

Published on 4 April 2022 by Pritha Bhandari . Revised on 30 January 2023.

Qualitative research involves collecting and analysing non-numerical data (e.g., text, video, or audio) to understand concepts, opinions, or experiences. It can be used to gather in-depth insights into a problem or generate new ideas for research.

Qualitative research is the opposite of quantitative research , which involves collecting and analysing numerical data for statistical analysis.

Qualitative research is commonly used in the humanities and social sciences, in subjects such as anthropology, sociology, education, health sciences, and history.

• How does social media shape body image in teenagers?
• How do children and adults interpret healthy eating in the UK?
• What factors influence employee retention in a large organisation?
• How is anxiety experienced around the world?
• How can teachers integrate social issues into science curriculums?

Table of contents

Approaches to qualitative research, qualitative research methods, qualitative data analysis, advantages of qualitative research, disadvantages of qualitative research, frequently asked questions about qualitative research.

Qualitative research is used to understand how people experience the world. While there are many approaches to qualitative research, they tend to be flexible and focus on retaining rich meaning when interpreting data.

Common approaches include grounded theory, ethnography, action research, phenomenological research, and narrative research. They share some similarities, but emphasise different aims and perspectives.

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Each of the research approaches involve using one or more data collection methods . These are some of the most common qualitative methods:

• Observations: recording what you have seen, heard, or encountered in detailed field notes.
• Interviews:  personally asking people questions in one-on-one conversations.
• Focus groups: asking questions and generating discussion among a group of people.
• Surveys : distributing questionnaires with open-ended questions.
• Secondary research: collecting existing data in the form of texts, images, audio or video recordings, etc.
• You take field notes with observations and reflect on your own experiences of the company culture.
• You distribute open-ended surveys to employees across all the company’s offices by email to find out if the culture varies across locations.
• You conduct in-depth interviews with employees in your office to learn about their experiences and perspectives in greater detail.

Qualitative researchers often consider themselves ‘instruments’ in research because all observations, interpretations and analyses are filtered through their own personal lens.

For this reason, when writing up your methodology for qualitative research, it’s important to reflect on your approach and to thoroughly explain the choices you made in collecting and analysing the data.

Qualitative data can take the form of texts, photos, videos and audio. For example, you might be working with interview transcripts, survey responses, fieldnotes, or recordings from natural settings.

Most types of qualitative data analysis share the same five steps:

• Prepare and organise your data. This may mean transcribing interviews or typing up fieldnotes.
• Review and explore your data. Examine the data for patterns or repeated ideas that emerge.
• Develop a data coding system. Based on your initial ideas, establish a set of codes that you can apply to categorise your data.
• Assign codes to the data. For example, in qualitative survey analysis, this may mean going through each participant’s responses and tagging them with codes in a spreadsheet. As you go through your data, you can create new codes to add to your system if necessary.
• Identify recurring themes. Link codes together into cohesive, overarching themes.

There are several specific approaches to analysing qualitative data. Although these methods share similar processes, they emphasise different concepts.

Qualitative research often tries to preserve the voice and perspective of participants and can be adjusted as new research questions arise. Qualitative research is good for:

• Flexibility

The data collection and analysis process can be adapted as new ideas or patterns emerge. They are not rigidly decided beforehand.

• Natural settings

Data collection occurs in real-world contexts or in naturalistic ways.

• Meaningful insights

Detailed descriptions of people’s experiences, feelings and perceptions can be used in designing, testing or improving systems or products.

• Generation of new ideas

Open-ended responses mean that researchers can uncover novel problems or opportunities that they wouldn’t have thought of otherwise.

Researchers must consider practical and theoretical limitations in analysing and interpreting their data. Qualitative research suffers from:

• Unreliability

The real-world setting often makes qualitative research unreliable because of uncontrolled factors that affect the data.

• Subjectivity

Due to the researcher’s primary role in analysing and interpreting data, qualitative research cannot be replicated . The researcher decides what is important and what is irrelevant in data analysis, so interpretations of the same data can vary greatly.

• Limited generalisability

Small samples are often used to gather detailed data about specific contexts. Despite rigorous analysis procedures, it is difficult to draw generalisable conclusions because the data may be biased and unrepresentative of the wider population .

• Labour-intensive

Although software can be used to manage and record large amounts of text, data analysis often has to be checked or performed manually.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to test a hypothesis by systematically collecting and analysing data, while qualitative methods allow you to explore ideas and experiences in depth.

There are five common approaches to qualitative research :

• Grounded theory involves collecting data in order to develop new theories.
• Ethnography involves immersing yourself in a group or organisation to understand its culture.
• Narrative research involves interpreting stories to understand how people make sense of their experiences and perceptions.
• Phenomenological research involves investigating phenomena through people’s lived experiences.
• Action research links theory and practice in several cycles to drive innovative changes.

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organisations.

There are various approaches to qualitative data analysis , but they all share five steps in common:

• Prepare and organise your data.
• Review and explore your data.
• Develop a data coding system.
• Assign codes to the data.
• Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

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Qualitative research: methods and examples

Last updated

13 April 2023

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Qualitative research involves gathering and evaluating non-numerical information to comprehend concepts, perspectives, and experiences. It’s also helpful for obtaining in-depth insights into a certain subject or generating new research ideas. 

As a result, qualitative research is practical if you want to try anything new or produce new ideas.

There are various ways you can conduct qualitative research. In this article, you'll learn more about qualitative research methodologies, including when you should use them.

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• What is qualitative research?

Qualitative research is a broad term describing various research types that rely on asking open-ended questions. Qualitative research investigates “how” or “why” certain phenomena occur. It is about discovering the inherent nature of something.

The primary objective of qualitative research is to understand an individual's ideas, points of view, and feelings. In this way, collecting in-depth knowledge of a specific topic is possible. Knowing your audience's feelings about a particular subject is important for making reasonable research conclusions.

Unlike quantitative research , this approach does not involve collecting numerical, objective data for statistical analysis. Qualitative research is used extensively in education, sociology, health science, history, and anthropology.

• Types of qualitative research methodology

Typically, qualitative research aims at uncovering the attitudes and behavior of the target audience concerning a specific topic. For example,  “How would you describe your experience as a new Dovetail user?”

Some of the methods for conducting qualitative analysis include:

Focus groups

Hosting a focus group is a popular qualitative research method. It involves obtaining qualitative data from a limited sample of participants. In a moderated version of a focus group, the moderator asks participants a series of predefined questions. They aim to interact and build a group discussion that reveals their preferences, candid thoughts, and experiences.

Unmoderated, online focus groups are increasingly popular because they eliminate the need to interact with people face to face.

Focus groups can be more cost-effective than 1:1 interviews or studying a group in a natural setting and reporting one’s observations.

Focus groups make it possible to gather multiple points of view quickly and efficiently, making them an excellent choice for testing new concepts or conducting market research on a new product.

However, there are some potential drawbacks to this method. It may be unsuitable for sensitive or controversial topics. Participants might be reluctant to disclose their true feelings or respond falsely to conform to what they believe is the socially acceptable answer (known as response bias).

Case study research

A case study is an in-depth evaluation of a specific person, incident, organization, or society. This type of qualitative research has evolved into a broadly applied research method in education, law, business, and the social sciences.

Even though case study research may appear challenging to implement, it is one of the most direct research methods. It requires detailed analysis, broad-ranging data collection methodologies, and a degree of existing knowledge about the subject area under investigation.

Historical model

The historical approach is a distinct research method that deeply examines previous events to better understand the present and forecast future occurrences of the same phenomena. Its primary goal is to evaluate the impacts of history on the present and hence discover comparable patterns in the present to predict future outcomes.

Oral history

This qualitative data collection method involves gathering verbal testimonials from individuals about their personal experiences. It is widely used in historical disciplines to offer counterpoints to established historical facts and narratives. The most common methods of gathering oral history are audio recordings, analysis of auto-biographical text, videos, and interviews.

Qualitative observation

One of the most fundamental, oldest research methods, qualitative observation , is the process through which a researcher collects data using their senses of sight, smell, hearing, etc. It is used to observe the properties of the subject being studied. For example, “What does it look like?” As research methods go, it is subjective and depends on researchers’ first-hand experiences to obtain information, so it is prone to bias. However, it is an excellent way to start a broad line of inquiry like, “What is going on here?”

Record keeping and review

Record keeping uses existing documents and relevant data sources that can be employed for future studies. It is equivalent to visiting the library and going through publications or any other reference material to gather important facts that will likely be used in the research.

Grounded theory approach

The grounded theory approach is a commonly used research method employed across a variety of different studies. It offers a unique way to gather, interpret, and analyze. With this approach, data is gathered and analyzed simultaneously.  Existing analysis frames and codes are disregarded, and data is analyzed inductively, with new codes and frames generated from the research.

Ethnographic research

Ethnography  is a descriptive form of a qualitative study of people and their cultures. Its primary goal is to study people's behavior in their natural environment. This method necessitates that the researcher adapts to their target audience's setting. 

Thereby, you will be able to understand their motivation, lifestyle, ambitions, traditions, and culture in situ. But, the researcher must be prepared to deal with geographical constraints while collecting data i.e., audiences can’t be studied in a laboratory or research facility.

This study can last from a couple of days to several years. Thus, it is time-consuming and complicated, requiring you to have both the time to gather the relevant data as well as the expertise in analyzing, observing, and interpreting data to draw meaningful conclusions.

Narrative framework

A narrative framework is a qualitative research approach that relies on people's written text or visual images. It entails people analyzing these events or narratives to determine certain topics or issues. With this approach, you can understand how people represent themselves and their experiences to a larger audience.

Phenomenological approach

The phenomenological study seeks to investigate the experiences of a particular phenomenon within a group of individuals or communities. It analyzes a certain event through interviews with persons who have witnessed it to determine the connections between their views. Even though this method relies heavily on interviews, other data sources (recorded notes), and observations could be employed to enhance the findings.

• Qualitative research methods (tools)

Some of the instruments involved in qualitative research include:

Document research: Also known as document analysis because it involves evaluating written documents. These can include personal and non-personal materials like archives, policy publications, yearly reports, diaries, or letters.

Focus groups:  This is where a researcher poses questions and generates conversation among a group of people. The major goal of focus groups is to examine participants' experiences and knowledge, including research into how and why individuals act in various ways.

Secondary study: Involves acquiring existing information from texts, images, audio, or video recordings.

Observations:   This requires thorough field notes on everything you see, hear, or experience. Compared to reported conduct or opinion, this study method can assist you in getting insights into a specific situation and observable behaviors.

Structured interviews :  In this approach, you will directly engage people one-on-one. Interviews are ideal for learning about a person's subjective beliefs, motivations, and encounters.

Surveys:  This is when you distribute questionnaires containing open-ended questions

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• What are common examples of qualitative research?

Everyday examples of qualitative research include:

Conducting a demographic analysis of a business

For instance, suppose you own a business such as a grocery store (or any store) and believe it caters to a broad customer base, but after conducting a demographic analysis, you discover that most of your customers are men.

You could do 1:1 interviews with female customers to learn why they don't shop at your store.

In this case, interviewing potential female customers should clarify why they don't find your shop appealing. It could be because of the products you sell or a need for greater brand awareness, among other possible reasons.

Launching or testing a new product

Suppose you are the product manager at a SaaS company looking to introduce a new product. Focus groups can be an excellent way to determine whether your product is marketable.

In this instance, you could hold a focus group with a sample group drawn from your intended audience. The group will explore the product based on its new features while you ensure adequate data on how users react to the new features. The data you collect will be key to making sales and marketing decisions.

Conducting studies to explain buyers' behaviors

You can also use qualitative research to understand existing buyer behavior better. Marketers analyze historical information linked to their businesses and industries to see when purchasers buy more.

Qualitative research can help you determine when to target new clients and peak seasons to boost sales by investigating the reason behind these behaviors.

• Qualitative research: data collection

Data collection is gathering information on predetermined variables to gain appropriate answers, test hypotheses, and analyze results. Researchers will collect non-numerical data for qualitative data collection to obtain detailed explanations and draw conclusions.

To get valid findings and achieve a conclusion in qualitative research, researchers must collect comprehensive and multifaceted data.

Qualitative data is usually gathered through interviews or focus groups with videotapes or handwritten notes. If there are recordings, they are transcribed before the data analysis process. Researchers keep separate folders for the recordings acquired from each focus group when collecting qualitative research data to categorize the data.

• Qualitative research: data analysis

Qualitative data analysis is organizing, examining, and interpreting qualitative data. Its main objective is identifying trends and patterns, responding to research questions, and recommending actions based on the findings. Textual analysis is a popular method for analyzing qualitative data.

Textual analysis differs from other qualitative research approaches in that researchers consider the social circumstances of study participants to decode their words, behaviors, and broader meaning. 

Learn more about qualitative research data analysis software

• When to use qualitative research

Qualitative research is helpful in various situations, particularly when a researcher wants to capture accurate, in-depth insights. 

Here are some instances when qualitative research can be valuable:

Examining your product or service to improve your marketing approach

When researching market segments, demographics, and customer service teams

Identifying client language when you want to design a quantitative survey

When attempting to comprehend your or someone else's strengths and weaknesses

Assessing feelings and beliefs about societal and public policy matters

Collecting information about a business or product's perception

Analyzing your target audience's reactions to marketing efforts

When launching a new product or coming up with a new idea

When seeking to evaluate buyers' purchasing patterns

• Qualitative research methods vs. quantitative research methods

Qualitative research examines people's ideas and what influences their perception, whereas quantitative research draws conclusions based on numbers and measurements.

Qualitative research is descriptive, and its primary goal is to comprehensively understand people's attitudes, behaviors, and ideas.

In contrast, quantitative research is more restrictive because it relies on numerical data and analyzes statistical data to make decisions. This research method assists researchers in gaining an initial grasp of the subject, which deals with numbers. For instance, the number of customers likely to purchase your products or use your services.

What is the most important feature of qualitative research?

A distinguishing feature of qualitative research is that it’s conducted in a real-world setting instead of a simulated environment. The researcher is examining actual phenomena instead of experimenting with different variables to see what outcomes (data) might result.

Can I use qualitative and quantitative approaches together in a study?

Yes, combining qualitative and quantitative research approaches happens all the time and is known as mixed methods research. For example, you could study individuals’ perceived risk in a certain scenario, such as how people rate the safety or riskiness of a given neighborhood. Simultaneously, you could analyze historical data objectively, indicating how safe or dangerous that area has been in the last year. To get the most out of mixed-method research, it’s important to understand the pros and cons of each methodology, so you can create a thoughtfully designed study that will yield compelling results.

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Collecting and Analyzing Qualitative Data

Brent Wolff, Frank Mahoney, Anna Leena Lohiniva, and Melissa Corkum

• Choosing When to Apply Qualitative Methods
• Commonly Used Qualitative Methods in Field Investigations
• Sampling and Recruitment for Qualitative Research
• Managing, Condensing, Displaying, and Interpreting Qualitative Data
• Coding and Analysis Requirements

Qualitative research methods are a key component of field epidemiologic investigations because they can provide insight into the perceptions, values, opinions, and community norms where investigations are being conducted ( 1,2 ). Open-ended inquiry methods, the mainstay of qualitative interview techniques, are essential in formative research for exploring contextual factors and rationales for risk behaviors that do not fit neatly into predefined categories. For example, during the 2014–2015 Ebola virus disease outbreaks in parts of West Africa, understanding the cultural implications of burial practices within different communities was crucial to designing and monitoring interventions for safe burials ( Box 10.1 ). In program evaluations, qualitative methods can assist the investigator in diagnosing what went right or wrong as part of a process evaluation or in troubleshooting why a program might not be working as well as expected. When designing an intervention, qualitative methods can be useful in exploring dimensions of acceptability to increase the chances of intervention acceptance and success. When performed in conjunction with quantitative studies, qualitative methods can help the investigator confirm, challenge, or deepen the validity of conclusions than either component might have yielded alone ( 1,2 ).

Qualitative research was used extensively in response to the Ebola virus disease outbreaks in parts of West Africa to understand burial practices and to design culturally appropriate strategies to ensure safe burials. Qualitative studies were also used to monitor key aspects of the response.

In October 2014, Liberia experienced an abrupt and steady decrease in case counts and deaths in contrast with predicted disease models of an increased case count. At the time, communities were resistant to entering Ebola treatment centers, raising the possibility that patients were not being referred for care and communities might be conducting occult burials.

To assess what was happening at the community level, the Liberian Emergency Operations Center recruited epidemiologists from the US Department of Health and Human Services/Centers for Disease Control and Prevention and the African Union to investigate the problem.

Teams conducted in-depth interviews and focus group discussions with community leaders, local funeral directors, and coffin makers and learned that communities were not conducting occult burials and that the overall number of burials was less than what they had experienced in previous years. Other key findings included the willingness of funeral directors to cooperate with disease response efforts, the need for training of funeral home workers, and considerable community resistance to cremation practices. These findings prompted the Emergency Operations Center to open a burial ground for Ebola decedents, support enhanced testing of burials in the private sector, and train private-sector funeral workers regarding safe burial practices.

Source: Melissa Corkum, personal communication.

Similar to quantitative approaches, qualitative research seeks answers to specific questions by using rigorous approaches to collecting and compiling information and producing findings that can be applicable beyond the study population. The fundamental difference in approaches lies in how they translate real-life complexities of initial observations into units of analysis. Data collected in qualitative studies typically are in the form of text or visual images, which provide rich sources of insight but also tend to be bulky and time-consuming to code and analyze. Practically speaking, qualitative study designs tend to favor small, purposively selected samples ideal for case studies or in-depth analysis ( 1 ). The combination of purposive sampling and open-ended question formats deprive qualitative study designs of the power to quantify and generalize conclusions, one of the key limitations of this approach.

Qualitative scientists might argue, however, that the generalizability and precision possible through probabilistic sampling and categorical outcomes are achieved at the cost of enhanced validity, nuance, and naturalism that less structured approaches offer ( 3 ). Open-ended techniques are particularly useful for understanding subjective meanings and motivations underlying behavior. They enable investigators to be equally adept at exploring factors observed and unobserved, intentions as well as actions, internal meanings as well as external consequences, options considered but not taken, and unmeasurable as well as measurable outcomes. These methods are important when the source of or solution to a public health problem is rooted in local perceptions rather than objectively measurable characteristics selected by outside observers ( 3 ). Ultimately, such approaches have the ability to go beyond quantifying questions of how much or how many to take on questions of how or why from the perspective and in the words of the study subjects themselves ( 1,2 ).

Another key advantage of qualitative methods for field investigations is their flexibility ( 4 ). Qualitative designs not only enable but also encourage flexibility in the content and flow of questions to challenge and probe for deeper meanings or follow new leads if they lead to deeper understanding of an issue (5). It is not uncommon for topic guides to be adjusted in the course of fieldwork to investigate emerging themes relevant to answering the original study question. As discussed herein, qualitative study designs allow flexibility in sample size to accommodate the need for more or fewer interviews among particular groups to determine the root cause of an issue (see the section on Sampling and Recruitment in Qualitative Research). In the context of field investigations, such methods can be extremely useful for investigating complex or fast-moving situations where the dimensions of analysis cannot be fully anticipated.

Ultimately, the decision whether to include qualitative research in a particular field investigation depends mainly on the nature of the research question itself. Certain types of research topics lend themselves more naturally to qualitative rather than other approaches ( Table 10.1 ). These include exploratory investigations when not enough is known about a problem to formulate a hypothesis or develop a fixed set of questions and answer codes. They include research questions where intentions matter as much as actions and “why?” or “why not?” questions matter as much as precise estimation of measured outcomes. Qualitative approaches also work well when contextual influences, subjective meanings, stigma, or strong social desirability biases lower faith in the validity of responses coming from a relatively impersonal survey questionnaire interview.

The availability of personnel with training and experience in qualitative interviewing or observation is critical for obtaining the best quality data but is not absolutely required for rapid assessment in field settings. Qualitative interviewing requires a broader set of skills than survey interviewing. It is not enough to follow a topic guide like a questionnaire, in order, from top to bottom. A qualitative interviewer must exercise judgment to decide when to probe and when to move on, when to encourage, challenge, or follow relevant leads even if they are not written in the topic guide. Ability to engage with informants, connect ideas during the interview, and think on one’s feet are common characteristics of good qualitative interviewers. By far the most important qualification in conducting qualitative fieldwork is a firm grasp of the research objectives; with this qualification, a member of the research team armed with curiosity and a topic guide can learn on the job with successful results.

Semi-Structured Interviews

Semi-structured interviews can be conducted with single participants (in-depth or individual key informants) or with groups (focus group discussions [FGDs] or key informant groups). These interviews follow a suggested topic guide rather than a fixed questionnaire format. Topic guides typically consist of a limited number ( 10– 15 ) of broad, open-ended questions followed by bulleted points to facilitate optional probing. The conversational back-and-forth nature of a semi-structured format puts the researcher and researched (the interview participants) on more equal footing than allowed by more structured formats. Respondents, the term used in the case of quantitative questionnaire interviews, become informants in the case of individual semi-structured in-depth interviews (IDIs) or participants in the case of FGDs. Freedom to probe beyond initial responses enables interviewers to actively engage with the interviewee to seek clarity, openness, and depth by challenging informants to reach below layers of self-presentation and social desirability. In this respect, interviewing is sometimes compared with peeling an onion, with the first version of events accessible to the public, including survey interviewers, and deeper inner layers accessible to those who invest the time and effort to build rapport and gain trust. (The theory of the active interview suggests that all interviews involve staged social encounters where the interviewee is constantly assessing interviewer intentions and adjusting his or her responses accordingly [ 1 ]. Consequently good rapport is important for any type of interview. Survey formats give interviewers less freedom to divert from the preset script of questions and formal probes.)

Individual In-Depth Interviews and Key-Informant Interviews

The most common forms of individual semi-structured interviews are IDIs and key informant interviews (KIIs). IDIs are conducted among informants typically selected for first-hand experience (e.g., service users, participants, survivors) relevant to the research topic. These are typically conducted as one-on-one face-to-face interviews (two-on-one if translators are needed) to maximize rapport-building and confidentiality. KIIs are similar to IDIs but focus on individual persons with special knowledge or influence (e.g., community leaders or health authorities) that give them broader perspective or deeper insight into the topic area ( Box 10.2 ). Whereas IDIs tend to focus on personal experiences, context, meaning, and implications for informants, KIIs tend to steer away from personal questions in favor of expert insights or community perspectives. IDIs enable flexible sampling strategies and represent the interviewing reference standard for confidentiality, rapport, richness, and contextual detail. However, IDIs are time-and labor-intensive to collect and analyze. Because confidentiality is not a concern in KIIs, these interviews might be conducted as individual or group interviews, as required for the topic area.

Focus Group Discussions and Group Key Informant Interviews

FGDs are semi-structured group interviews in which six to eight participants, homogeneous with respect to a shared experience, behavior, or demographic characteristic, are guided through a topic guide by a trained moderator ( 6 ). (Advice on ideal group interview size varies. The principle is to convene a group large enough to foster an open, lively discussion of the topic, and small enough to ensure all participants stay fully engaged in the process.) Over the course of discussion, the moderator is expected to pose questions, foster group participation, and probe for clarity and depth. Long a staple of market research, focus groups have become a widely used social science technique with broad applications in public health, and they are especially popular as a rapid method for assessing community norms and shared perceptions.

Focus groups have certain useful advantages during field investigations. They are highly adaptable, inexpensive to arrange and conduct, and often enjoyable for participants. Group dynamics effectively tap into collective knowledge and experience to serve as a proxy informant for the community as a whole. They are also capable of recreating a microcosm of social norms where social, moral, and emotional dimensions of topics are allowed to emerge. Skilled moderators can also exploit the tendency of small groups to seek consensus to bring out disagreements that the participants will work to resolve in a way that can lead to deeper understanding. There are also limitations on focus group methods. Lack of confidentiality during group interviews means they should not be used to explore personal experiences of a sensitive nature on ethical grounds. Participants may take it on themselves to volunteer such information, but moderators are generally encouraged to steer the conversation back to general observations to avoid putting pressure on other participants to disclose in a similar way. Similarly, FGDs are subject by design to strong social desirability biases. Qualitative study designs using focus groups sometimes add individual interviews precisely to enable participants to describe personal experiences or personal views that would be difficult or inappropriate to share in a group setting. Focus groups run the risk of producing broad but shallow analyses of issues if groups reach comfortable but superficial consensus around complex topics. This weakness can be countered by training moderators to probe effectively and challenge any consensus that sounds too simplistic or contradictory with prior knowledge. However, FGDs are surprisingly robust against the influence of strongly opinionated participants, highly adaptable, and well suited to application in study designs where systematic comparisons across different groups are called for.

Like FGDs, group KIIs rely on positive chemistry and the stimulating effects of group discussion but aim to gather expert knowledge or oversight on a particular topic rather than lived experience of embedded social actors. Group KIIs have no minimum size requirements and can involve as few as two or three participants.

Egypt’s National Infection Prevention and Control (IPC) program undertook qualitative research to gain an understanding of the contextual behaviors and motivations of healthcare workers in complying with IPC guidelines. The study was undertaken to guide the development of effective behavior change interventions in healthcare settings to improve IPC compliance.

Key informant interviews and focus group discussions were conducted in two governorates among cleaning staff, nursing staff, and physicians in different types of healthcare facilities. The findings highlighted social and cultural barriers to IPC compliance, enabling the IPC program to design responses. For example,

• Informants expressed difficulty in complying with IPC measures that forced them to act outside their normal roles in an ingrained hospital culture. Response: Role models and champions were introduced to help catalyze change.
• Informants described fatalistic attitudes that undermined energy and interest in modifying behavior. Response: Accordingly, interventions affirming institutional commitment to change while challenging fatalistic assumptions were developed.
• Informants did not perceive IPC as effective. Response: Trainings were amended to include scientific evidence justifying IPC practices.
• Informants perceived hygiene as something they took pride in and were judged on. Response: Public recognition of optimal IPC practice was introduced to tap into positive social desirability and professional pride in maintaining hygiene in the work environment.

Qualitative research identified sources of resistance to quality clinical practice in Egypt’s healthcare settings and culturally appropriate responses to overcome that resistance.

____________________ Source: Anna Leena Lohiniva, personal communication.

Visualization Methods

Visualization methods have been developed as a way to enhance participation and empower interviewees relative to researchers during group data collection ( 7 ). Visualization methods involve asking participants to engage in collective problem- solving of challenges expressed through group production of maps, diagrams, or other images. For example, participants from the community might be asked to sketch a map of their community and to highlight features of relevance to the research topic (e.g., access to health facilities or sites of risk concentrations). Body diagramming is another visualization tool in which community members are asked to depict how and where a health threat affects the human body as a way of understanding folk conceptions of health, disease, treatment, and prevention. Ensuing debate and dialogue regarding construction of images can be recorded and analyzed in conjunction with the visual image itself. Visualization exercises were initially designed to accommodate groups the size of entire communities, but they can work equally well with smaller groups corresponding to the size of FGDs or group KIIs.

Selecting a Sample of Study Participants

Fundamental differences between qualitative and quantitative approaches to research emerge most clearly in the practice of sampling and recruitment of study participants. Qualitative samples are typically small and purposive. In-depth interview informants are usually selected on the basis of unique characteristics or personal experiences that make them exemplary for the study, if not typical in other respects. Key informants are selected for their unique knowledge or influence in the study domain. Focus group mobilization often seeks participants who are typical with respect to others in the community having similar exposure or shared characteristics. Often, however, participants in qualitative studies are selected because they are exceptional rather than simply representative. Their value lies not in their generalizability but in their ability to generate insight into the key questions driving the study.

Determining Sample Size

Sample size determination for qualitative studies also follows a different logic than that used for probability sample surveys. For example, whereas some qualitative methods specify ideal ranges of participants that constitute a valid observation (e.g., focus groups), there are no rules on how many observations it takes to attain valid results. In theory, sample size in qualitative designs should be determined by the saturation principle , where interviews are conducted until additional interviews yield no additional insights into the topic of research ( 8 ). Practically speaking, designing a study with a range in number of interviews is advisable for providing a level of flexibility if additional interviews are needed to reach clear conclusions.

Recruiting Study Participants

Recruitment strategies for qualitative studies typically involve some degree of participant self-selection (e.g., advertising in public spaces for interested participants) and purposive selection (e.g., identification of key informants). Purposive selection in community settings often requires authorization from local authorities and assistance from local mobilizers before the informed consent process can begin. Clearly specifying eligibility criteria is crucial for minimizing the tendency of study mobilizers to apply their own filters regarding who reflects the community in the best light. In addition to formal eligibility criteria, character traits (e.g., articulate and interested in participating) and convenience (e.g., not too far away) are legitimate considerations for whom to include in the sample. Accommodations to personality and convenience help to ensure the small number of interviews in a typical qualitative design yields maximum value for minimum investment. This is one reason why random sampling of qualitative informants is not only unnecessary but also potentially counterproductive.

Analysis of qualitative data can be divided into four stages: data management, data condensation, data display, and drawing and verifying conclusions ( 9 ).

Managing Qualitative Data

From the outset, developing a clear organization system for qualitative data is important. Ideally, naming conventions for original data files and subsequent analysis should be recorded in a data dictionary file that includes dates, locations, defining individual or group characteristics, interviewer characteristics, and other defining features. Digital recordings of interviews or visualization products should be reviewed to ensure fidelity of analyzed data to original observations. If ethics agreements require that no names or identifying characteristics be recorded, all individual names must be removed from final transcriptions before analysis begins. If data are analyzed by using textual data analysis software, maintaining careful version control over the data files is crucial, especially when multiple coders are involved.

Condensing Qualitative Data

Condensing refers to the process of selecting, focusing, simplifying, and abstracting the data available at the time of the original observation, then transforming the condensed data into a data set that can be analyzed. In qualitative research, most of the time investment required to complete a study comes after the fieldwork is complete. A single hour of taped individual interview can take a full day to transcribe and additional time to translate if necessary. Group interviews can take even longer because of the difficulty of transcribing active group input. Each stage of data condensation involves multiple decisions that require clear rules and close supervision. A typical challenge is finding the right balance between fidelity to the rhythm and texture of original language and clarity of the translated version in the language of analysis. For example, discussions among groups with little or no education should not emerge after the transcription (and translation) process sounding like university graduates. Judgment must be exercised about which terms should be translated and which terms should be kept in vernacular because there is no appropriate term in English to capture the richness of its meaning.

Displaying Qualitative Data

After the initial condensation, qualitative analysis depends on how the data are displayed. Decisions regarding how data are summarized and laid out to facilitate comparison influence the depth and detail of the investigation’s conclusions. Displays might range from full verbatim transcripts of interviews to bulleted summaries or distilled summaries of interview notes. In a field setting, a useful and commonly used display format is an overview chart in which key themes or research questions are listed in rows in a word processer table or in a spreadsheet and individual informant or group entry characteristics are listed across columns. Overview charts are useful because they allow easy, systematic comparison of results.

Drawing and Verifying Conclusions

Analyzing qualitative data is an iterative and ideally interactive process that leads to rigorous and systematic interpretation of textual or visual data. At least four common steps are involved:

• Reading and rereading. The core of qualitative analysis is careful, systematic, and repeated reading of text to identify consistent themes and interconnections emerging from the data. The act of repeated reading inevitably yields new themes, connections, and deeper meanings from the first reading. Reading the full text of interviews multiple times before subdividing according to coded themes is key to appreciating the full context and flow of each interview before subdividing and extracting coded sections of text for separate analysis.
• Coding. A common technique in qualitative analysis involves developing codes for labeling sections of text for selective retrieval in later stages of analysis and verification. Different approaches can be used for textual coding. One approach, structural coding , follows the structure of the interview guide. Another approach, thematic coding , labels common themes that appear across interviews, whether by design of the topic guide or emerging themes assigned based on further analysis. To avoid the problem of shift and drift in codes across time or multiple coders, qualitative investigators should develop a standard codebook with written definitions and rules about when codes should start and stop. Coding is also an iterative process in which new codes that emerge from repeated reading are layered on top of existing codes. Development and refinement of the codebook is inseparably part of the analysis.
• Analyzing and writing memos. As codes are being developed and refined, answers to the original research question should begin to emerge. Coding can facilitate that process through selective text retrieval during which similarities within and between coding categories can be extracted and compared systematically. Because no p values can be derived in qualitative analyses to mark the transition from tentative to firm conclusions, standard practice is to write memos to record evolving insights and emerging patterns in the data and how they relate to the original research questions. Writing memos is intended to catalyze further thinking about the data, thus initiating new connections that can lead to further coding and deeper understanding.
• Verifying conclusions. Analysis rigor depends as much on the thoroughness of the cross-examination and attempt to find alternative conclusions as on the quality of original conclusions. Cross-examining conclusions can occur in different ways. One way is encouraging regular interaction between analysts to challenge conclusions and pose alternative explanations for the same data. Another way is quizzing the data (i.e., retrieving coded segments by using Boolean logic to systematically compare code contents where they overlap with other codes or informant characteristics). If alternative explanations for initial conclusions are more difficult to justify, confidence in those conclusions is strengthened.

Above all, qualitative data analysis requires sufficient time and immersion in the data. Computer textual software programs can facilitate selective text retrieval and quizzing the data, but discerning patterns and arriving at conclusions can be done only by the analysts. This requirement involves intensive reading and rereading, developing codebooks and coding, discussing and debating, revising codebooks, and recoding as needed until clear patterns emerge from the data. Although quality and depth of analysis is usually proportional to the time invested, a number of techniques, including some mentioned earlier, can be used to expedite analysis under field conditions.

• Detailed notes instead of full transcriptions. Assigning one or two note-takers to an interview can be considered where the time needed for full transcription and translation is not feasible. Even if plans are in place for full transcriptions after fieldwork, asking note-takers to submit organized summary notes is a useful technique for getting real-time feedback on interview content and making adjustments to topic guides or interviewer training as needed.
• Summary overview charts for thematic coding. (See discussion under “Displaying Data.”) If there is limited time for full transcription and/or systematic coding of text interviews using textual analysis software in the field, an overview chart is a useful technique for rapid manual coding.
• Thematic extract files. This is a slightly expanded version of manual thematic coding that is useful when full transcriptions of interviews are available. With use of a word processing program, files can be sectioned according to themes, or separate files can be created for each theme. Relevant extracts from transcripts or analyst notes can be copied and pasted into files or sections of files corresponding to each theme. This is particularly useful for storing appropriate quotes that can be used to illustrate thematic conclusions in final reports or manuscripts.
• Teamwork. Qualitative analysis can be performed by a single analyst, but it is usually beneficial to involve more than one. Qualitative conclusions involve subjective judgment calls. Having more than one coder or analyst working on a project enables more interactive discussion and debate before reaching consensus on conclusions.
• Systematic coding.
• Selective retrieval of coded segments.
• Verifying conclusions (“quizzing the data”).
• Working on larger data sets with multiple separate files.
• Working in teams with multiple coders to allow intercoder reliability to be measured and monitored.

The most widely used software packages (e.g., NVivo [QSR International Pty. Ltd., Melbourne, VIC, Australia] and ATLAS.ti [Scientific Software Development GmbH, Berlin, Germany]) evolved to include sophisticated analytic features covering a wide array of applications but are relatively expensive in terms of license cost and initial investment in time and training. A promising development is the advent of free or low-cost Web-based services (e.g., Dedoose [Sociocultural Research Consultants LLC, Manhattan Beach, CA]) that have many of the same analytic features on a more affordable subscription basis and that enable local research counterparts to remain engaged through the analysis phase (see Teamwork criteria). The start-up costs of computer-assisted analysis need to be weighed against their analytic benefits, which tend to decline with the volume and complexity of data to be analyzed. For rapid situational analyses or small scale qualitative studies (e.g. fewer than 30 observations as an informal rule of thumb), manual coding and analysis using word processing or spreadsheet programs is faster and sufficient to enable rigorous analysis and verification of conclusions.

Qualitative methods belong to a branch of social science inquiry that emphasizes the importance of context, subjective meanings, and motivations in understanding human behavior patterns. Qualitative approaches definitionally rely on open-ended, semistructured, non-numeric strategies for asking questions and recording responses. Conclusions are drawn from systematic visual or textual analysis involving repeated reading, coding, and organizing information into structured and emerging themes. Because textual analysis is relatively time-and skill-intensive, qualitative samples tend to be small and purposively selected to yield the maximum amount of information from the minimum amount of data collection. Although qualitative approaches cannot provide representative or generalizable findings in a statistical sense, they can offer an unparalleled level of detail, nuance, and naturalistic insight into the chosen subject of study. Qualitative methods enable investigators to “hear the voice” of the researched in a way that questionnaire methods, even with the occasional open-ended response option, cannot.

Whether or when to use qualitative methods in field epidemiology studies ultimately depends on the nature of the public health question to be answered. Qualitative approaches make sense when a study question about behavior patterns or program performance leads with why, why not , or how . Similarly, they are appropriate when the answer to the study question depends on understanding the problem from the perspective of social actors in real-life settings or when the object of study cannot be adequately captured, quantified, or categorized through a battery of closed-ended survey questions (e.g., stigma or the foundation of health beliefs). Another justification for qualitative methods occurs when the topic is especially sensitive or subject to strong social desirability biases that require developing trust with the informant and persistent probing to reach the truth. Finally, qualitative methods make sense when the study question is exploratory in nature, where this approach enables the investigator the freedom and flexibility to adjust topic guides and probe beyond the original topic guides.

Given that the conditions just described probably apply more often than not in everyday field epidemiology, it might be surprising that such approaches are not incorporated more routinely into standard epidemiologic training. Part of the answer might have to do with the subjective element in qualitative sampling and analysis that seems at odds with core scientific values of objectivity. Part of it might have to do with the skill requirements for good qualitative interviewing, which are generally more difficult to find than those required for routine survey interviewing.

For the field epidemiologist unfamiliar with qualitative study design, it is important to emphasize that obtaining important insights from applying basic approaches is possible, even without a seasoned team of qualitative researchers on hand to do the work. The flexibility of qualitative methods also tends to make them forgiving with practice and persistence. Beyond the required study approvals and ethical clearances, the basic essential requirements for collecting qualitative data in field settings start with an interviewer having a strong command of the research question, basic interactive and language skills, and a healthy sense of curiosity, armed with a simple open-ended topic guide and a tape recorder or note-taker to capture the key points of the discussion. Readily available manuals on qualitative study design, methods, and analysis can provide additional guidance to improve the quality of data collection and analysis.

• Patton MQ. Qualitative research and evaluation methods: integrating theory and practice . 4th ed. Thousand Oaks, CA: Sage; 2015.
• Hennink M, Hutter I, Bailey A. Qualitative research methods . Thousand Oaks, CA: Sage; 2010.
• Lincoln YS, Guba EG. The constructivist credo . Walnut Creek, CA: Left Coast Press; 2013.
• Mack N, Woodsong C, MacQueen KM, Guest G, Namey E. Qualitative research methods: a data collectors field guide. https://www.fhi360.org/sites/default/files/media/documents/Qualitative%20Research%20Methods%20-%20A%20Data%20Collector%27s%20Field%20Guide.pdf
• Kvale S, Brinkmann S. Interviews: learning the craft of qualitative research . Thousand Oaks, CA: Sage; 2009:230–43.
• Krueger RA, Casey MA. Focus groups: a practical guide for applied research . Thousand Oaks, CA: Sage; 2014.
• Margolis E, Pauwels L. The Sage handbook of visual research methods . Thousand Oaks, CA: Sage; 2011.
• Mason M. Sample size and saturation in PhD studies using qualitative interviews. Forum : Qualitative Social Research/Sozialforschung. 2010;11(3).
• Miles MB, Huberman AM, Saldana J. Qualitative data analysis: a methods sourcebook . 3rd ed. Thousand Oaks, CA: Sage; 2014.
• Silver C, Lewins A. Using software in qualitative research: a step-by-step guide . Thousand Oaks, CA; Sage: 2014.

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9 Data Collection Methods in Qualitative Research

Explore top methods for collecting qualitative data, from interviews to social media monitoring, to gain deeper customer insights for your strategy.

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In the world of customer insights, having access to the right data is crucial. Numbers and metrics can provide valuable direction, but they often fail to capture the full picture of how your customers truly feel, what they need, or why they behave in certain ways.

That’s where qualitative research shines. Using multiple qualitative data collection methods is like casting a wider net for insights — the more varied your approach, the better your chances of capturing nuanced feedback that standard surveys might miss.

Whether it’s through in-depth interviews or mining customer chat logs, the diversity of data sources can help build a robust understanding of your customers’ experiences.

In this article, we’ll cover the top methods you can use to collect qualitative data to inform your customer experience strategy .

Table of contents

Qualitative vs quantitative methods, 9 essential qualitative data collection methods.

In-depth Interviews

Focus Groups

Observational Research

Case Studies

Surveys with Open-ended Questions

Ethnographic Research

Customer Support Center Chat History

Social Media Conversation Monitoring

Review Sites

Pitfalls to Avoid in Qualitative Data Collection

Analyzing qualitative data.

When it comes to gathering customer insights, there are two main avenues: qualitative and quantitative research. Both are crucial, but they serve different purposes.

Quantitative methods rely on numerical data. Think of it as your go-to for answering “how many?” and “how much?” questions. It’s all about measurable facts, trends, and patterns. For example, you might run a large-scale survey asking customers to rate their satisfaction on a 1-10 scale, and you’ll get hard numbers to analyze. This kind of data is easy to visualize in graphs and charts, which helps you track customer satisfaction metrics like NPS or CSAT scores over time.

But qualitative methods ? This is where you dig deeper. These methods focus on the “why” and “how,” uncovering insights into the emotions, motivations, and thought processes behind customer behaviors. Instead of numerical data, qualitative research gives you rich, detailed feedback in the form of words. The qualitative data collected through these methods provides detailed and nuanced insights into individuals' or groups' experiences, perspectives, and behaviors. It’s an excellent way to get to the heart of customer experiences and understand their pain points on a human level.

Why Qualitative Research Is Critical for Customer Experience Strategy

Quantitative data can tell you what’s happening, but qualitative data tells you why it’s happening. The qualitative data collected through various methods can explain the underlying reasons behind customer satisfaction scores. If your quantitative research shows a drop in customer satisfaction scores, qualitative research can explain why. By diving into customer stories, open-ended survey responses, or even analyzing chat logs, you gain invaluable insights into where things might be going wrong (or right!).

Let’s dive into the most impactful methods you can use to gather valuable customer insights. Each of these methods offers a unique lens into the customer experience, helping you build a comprehensive understanding of your audience. Understanding both qualitative and quantitative data is essential for building a comprehensive understanding of your audience.

1. In-Depth Interviews

In-depth interviews are one-on-one conversations where the researcher asks open-ended questions , allowing the customer to share their thoughts and experiences in detail. These interviews are incredibly useful when you want to understand the “why” behind customer behavior or preferences. The qualitative data collected through in-depth interviews provides rich, detailed insights into customer behavior and preferences.

Maximizing the method: To get the most out of in-depth interviews, focus on creating a comfortable environment where participants feel free to express their honest opinions. Listen actively, ask follow-up questions, and don’t shy away from allowing the conversation to go off-script if it leads to richer insights.

Example: Imagine you’re an insights manager at a retail brand conducting an in-depth interview with a frequent shopper. By asking about their shopping habits, you can uncover that the customer values sustainability and chooses brands with eco-friendly packaging. This insight could inform future product packaging decisions.

2. Focus Groups

A focus group is a facilitated discussion with a small group of customers – usually around 6-10 people. The goal is to encourage interaction between participants, sparking conversations that reveal insights through group dynamics. The collective experience of a focus group can surface opinions that may not emerge in individual interviews. The qualitative data collected through focus groups can reveal collective opinions and insights that may not emerge in individual interviews.

Maximizing the method: Ensure that the focus group facilitator is skilled at guiding discussions without leading them. It’s important to let the conversation flow naturally, but the facilitator should know when to probe deeper or refocus the group when necessary.

Example: Let’s say a tech company runs a focus group with power users of their app. During the session, one participant mentions a feature they find confusing, which prompts others to agree. This shared feedback provides the company with a clear signal to revisit that feature for usability improvements.

3. Observational Research

Observational research (sometimes called field research) involves observing customers in their natural environment, whether it’s a store, website, or another setting. Instead of asking questions, researchers watch how customers interact with products, services, or environments in real-time. The qualitative data collected through observational research provides real-time insights into customer interactions and behaviors.

Maximizing the method: The key to observational research is to remain unobtrusive. Customers should behave naturally without being influenced by the researcher’s presence. It’s also crucial to take detailed notes on both the behaviors you expected, and any surprising actions that arise.

Example: A coffee shop chain might use observational research to see how customers navigate their in-store experience. Do they head straight to the counter or linger at the menu? Are they confused about the ordering process? These observations could highlight ways to improve the store layout or ordering flow.

4. Case Studies

Case studies are in-depth analyses of individual customer experiences, often focusing on how a product or service has solved a specific problem for them. By following a single customer’s journey from problem to solution, case studies offer detailed narratives that can illustrate the broader impact of your offerings. The qualitative data collected through case studies offers detailed narratives that illustrate the broader impact of your offerings.

Maximizing the method: Choose case study subjects that reflect common challenges or experiences within your customer base. The more relatable the story, the more likely other customers will see themselves in the narrative.

Example: A B2B SaaS company could create a case study around a client that successfully used their software to reduce employee churn. By detailing the challenges, implementation, and results, the case study could serve as a powerful testimonial for potential clients.

5. Surveys with Open-Ended Questions

While many surveys are typically quantitative, surveys with open-ended questions provide a qualitative element by allowing customers to write out their responses in their own words. This method bridges the gap between structured data and personal insights, making it easier to spot recurring themes or unique perspectives. The qualitative data collected through open-ended survey questions bridges the gap between structured data and personal insights.

Maximizing the method: Be strategic with the placement of open-ended questions. Too many can overwhelm respondents, but including one or two at key points in your survey allows for deeper insights without causing survey fatigue.

Example: A travel company might send out a post-trip survey asking, “What was the most memorable part of your experience?” The open-ended responses could reveal customer preferences that the company wasn’t previously aware of, informing future offerings or services.

6. Ethnographic Research

Ethnographic research takes immersion to a new level. In this method, researchers embed themselves in the customer’s environment for extended periods to observe and experience their behaviors firsthand. It’s about gaining a deep understanding of customer culture, motivations, and interactions. The qualitative data collected through ethnographic research provides a deep understanding of customer culture and interactions.

Maximizing the method: This method works best when researchers fully integrate into the customer’s world, whether that’s living among a target community or spending time on-site with customers in their daily routines. It’s a time-intensive process, but the insights can be incredibly rich.

Example: A researcher for a clothing brand might spend several weeks with a group of customers, observing how they shop for and wear clothes in their daily lives. This immersive research could uncover nuanced preferences about fabric types, fit, and style that surveys alone wouldn’t reveal.

7. Customer Support Center Chat History

Your customer support center chat history can be a treasure trove of qualitative data. By analyzing conversations between customers and support agents, you can identify recurring issues, concerns, and sentiments that might not surface in formal surveys or interviews. This method provides an authentic view of how customers feel in real-time as they interact with your brand for problem-solving. The qualitative data collected from chat histories provides an authentic view of customer sentiments in real-time.

Maximizing the method: Use text analysis tools to sift through large volumes of chat data, identifying common themes and patterns. Pay special attention to moments of frustration or satisfaction, as these often hold the key to customer experience improvements.

Example: A software company analyzes its chat history and notices that many customers express confusion about a particular feature. This insight leads the product team to create clearer in-app tutorials, ultimately reducing the number of support requests related to that feature.

8. Social Media Conversation Monitoring

Social media platforms are filled with candid, unsolicited customer feedback. Social media conversation monitoring involves tracking brand mentions, hashtags, and keywords to gauge customer sentiment and uncover insights about your audience. This method gives you access to a wide range of voices, including those who may never participate in formal research. The qualitative data collected from social media conversations offers a wide range of customer insights.

Maximizing the method: Leverage social listening tools to automate the process of monitoring and analyzing conversations across platforms like Instagram, Meta, or X. Be sure to track both direct mentions of your brand and broader industry-related conversations that could reveal trends or shifting customer preferences.

Example: A beauty brand might notice that customers are frequently discussing a competitor’s eco-friendly packaging on social media. By monitoring this trend, the brand could introduce more sustainable packaging solutions to align with emerging customer values.

9. Review Sites

Review sites such as Yelp, Google Reviews, and Trustpilot are another goldmine for qualitative data. Customers who leave reviews are often highly motivated to share their experiences, whether positive or negative. By mining these reviews, you can gather insights into customer satisfaction, product issues, and potential areas for improvement. The qualitative data collected from review sites provides insights into customer satisfaction and areas for improvement.

Maximizing the method: Don’t just focus on star ratings—read through the text of each review to extract the underlying emotions and motivations. Look for patterns in the language used and the specific aspects of your product or service that are frequently mentioned.

Example: A restaurant chain may notice through online reviews that customers often comment on the long wait times during dinner hours. This feedback prompts management to reassess staffing levels during peak times, improving both operational efficiency and customer satisfaction.

As with any research process, there are a few key pitfalls to watch out for when collecting qualitative data. Avoiding these three common mistakes will ensure that your insights are both accurate and actionable.

1. Bias in Data Collection

Bias can creep into qualitative research in many forms, from how questions are phrased in interviews or surveys to how data is interpreted. For example, leading questions might push respondents toward a specific answer. Similarly, during observational research or focus groups, the presence or behavior of the researcher could unintentionally influence participants.

How to avoid it: Ensure your research methods are designed to be neutral and that questions are open-ended. It’s also important to train researchers to minimize their influence during interviews or observations. Using standardized protocols can help maintain consistency across different data collection methods.

2. Over-reliance on a Single Method

While one method may seem like the easiest or most convenient to implement, relying solely on one form of data collection can lead to incomplete or skewed insights. For example, in-depth interviews might provide detailed information, but they won’t capture broad patterns across your entire customer base.

How to avoid it: Combine multiple data collection methods, like surveys, focus groups, and social media monitoring, to get a fuller picture. Each method will reveal different aspects of customer experience, and when analyzed together, they provide more comprehensive insights.

3. Failing to Document the Research Process

One of the easiest ways to undermine the quality of your qualitative data is by failing to document the research process adequately. Without a clear record of how data was collected, analyzed, and interpreted, it becomes difficult to validate findings or replicate the study in the future.

How to avoid it: Keep detailed notes, records, and transcriptions of every stage of the research process. Having a clear audit trail ensures that your findings are credible and can be trusted by decision-makers.

With these qualitative data collection methods at your disposal, you’ll find yourself with a wealth of unstructured qualitative data. While an abundance of data is valuable, it also presents a significant challenge: how to make sense of it all efficiently.

This is where advanced tools and technology come into play.

The Challenge of Unstructured Data

Qualitative research methods produce, by their nature, unstructured data. Whether you’re working with transcripts from focus groups, feedback from review sites, or social media conversations, the data doesn’t neatly fit into rows and columns like quantitative data does. Instead, you’re dealing with text—rich, narrative-driven, and full of context. This makes it incredibly insightful but also hard to analyze manually.

Manually categorizing themes, identifying patterns, and summarizing key takeaways from large datasets is time-consuming and prone to human error. It’s easy to miss out on emerging trends or nuances that could offer strategic value, especially if you're dealing with diverse data sources.

How Kapiche’s AI-Powered Auto-Theming Can Help

Kapiche’s automatic theming feature is designed to solve this problem. By leveraging AI-powered technology, Kapiche cleans, categorizes, and analyzes your text data quickly and accurately. The platform automatically identifies themes, clusters related data points, and even provides summaries that help you interpret what your customers are saying.

For example, Kapiche can scan through customer support chat histories or social media mentions and instantly group similar pieces of feedback together—whether customers are talking about product performance, customer service, or price sensitivity. With these insights readily available, you can take faster action to improve your customer experience.

Benefits of Auto-Theming for Insights Managers

Here's how an auto-theming can transform your qualitative data analysis:

Speed and Efficiency: Automating the process saves you countless hours of manual work.

Comprehensive Analysis: By aggregating data from multiple sources, you get a fuller picture of customer sentiment across various touchpoints.

Uncover Hidden Insights: The AI detects patterns that you might not notice through manual analysis, offering deeper insights into customer behavior.

Actionable Summaries: Instead of wading through raw text, Kapiche provides concise summaries of key themes and trends, enabling you to act on insights faster.

With tools like this at your disposal, the overwhelming task of analyzing qualitative data becomes manageable, empowering your insights team to make data-driven decisions more effectively.

Let Us Help You

Navigating the complexities of qualitative data collection and analysis can be challenging, but you don’t have to do it alone. At Kapiche, we’re committed to helping insights teams like yours make the most of your qualitative customer data.

Our AI-powered auto-theming capabilities simplify the process by automatically categorizing, analyzing, and summarizing your data. This means you can quickly uncover key insights and trends without getting bogged down by the sheer volume of unstructured information.

Ready to see how Kapiche can transform your research process? Click the link below to watch an on-demand demo and discover how our platform can enhance your customer insights strategy.

Book a Demo with Kapiche

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Research MethodologyOverview of Qualitative Research

Daniel h grossoehme.

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Address correspondence to Daniel H. Grossoehme, Division of Pulmonary Medicine, Department of Pastoral Care, Cincinnati Children's Hospital Medical Center, MLC 2021, 3333 Burnet Avenue, Cincinnati, OH 45229, USA. [email protected]

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Qualitative research methods are a robust tool for chaplaincy research questions. Similar to much of chaplaincy clinical care, qualitative research generally works with written texts, often transcriptions of individual interviews or focus group conversations and seeks to understand the meaning of experience in a study sample. This article describes three common methodologies: ethnography, grounded theory, and phenomenology. Issues to consider relating to the study sample, design, and analysis are discussed. Enhancing the validity of the data, as well reliability and ethical issues in qualitative research are described. Qualitative research is an accessible way for chaplains to contribute new knowledge about the sacred dimension of people's lived experience.

Keywords: chaplaincy , ethnography , grounded theory , phenomenology , qualitative research

INTRODUCTION

Qualitative research is, “the systematic collection, organization, and interpretation of textual material derived from talk or conversation. It is used in the exploration of meanings of social phenomena as experienced by individuals themselves, in their natural context” ( Malterud, 2001 , p. 483). It can be the most accessible means of entry for chaplains into the world of research because, like clinical conversations, it focuses on eliciting people's stories. The stories can actually be expressed in almost any medium: conversations (interviews or focus groups), written texts (journal, prayers, or letters), or visual forms (drawings, photographs). Qualitative research may involve presenting data collected from a single person, as in a case study ( Risk, 2013 ), or from a group of people, as in one of my studies of parents of children with cystic fibrosis (CF) ( Grossoehme et al., 2013 ). Whole books are devoted to qualitative research methodology and, indeed, to the individual methods themselves. This article is intended to present, in rather broad brushstrokes, some of the “methods of choice” and to suggest some issues to consider before embarking on a qualitative research project. Helpful texts are cited to provide resources for more complete information.

Although virtually anything may be data, spoken mediums are the most common forms of collecting data in health research, so the focus of this article will mainly be on interviews and to a lesser extent, focus groups. Interviews explore experiences of individuals, and through a series of questions and answers, the meaning individuals give to their experiences ( Tong, Sainsbury, & Craig, 2007 ). They may be “structured” interviews, in which an interview guide is used with pre-determined questions from which no deviation is permitted by the interviewer, or semi-structured interviews, in which an interview guide is used with pre-determined questions and potential follow-up questions. The latter allows the interviewer to pursue topics that arise during the interview that seem relevant ( Cohen & Crabtree, 2006 ). Writing good questions is harder than it appears! In my first unit of CPE, the supervisor returned verbatims, especially our early efforts, with “DCFQ” written in the margin, for “direct, closed, factual question.” We quickly learned to avoid DCFQs in our clinical conversations because they did not create the space for reflection on illness and the sacred the way open-ended questions did. To some extent, writing good open-ended questions that elicit stories can come more readily to chaplains, due perhaps to our training, than to investigators from other disciplines. This is not to say writing an interview guide is easy or an aspect of research that can be taken lightly, as the quality of the data you collect, and hence the quality of your study, depends on the quality of your interview questions.

Data may also be collected using focus groups. Focus groups are normally built around a specific topic. They almost always follow a semi-structured format and include open discussion of responses among participants, which may range from four to twelve people ( Tong et al., 2007 ). They provide an excellent means to gather data on an entire range of responses to a topic, or on the social interactions between participants, or to clarify a process. Once the data are collected, the analytic approach is typically similar to that of interview data.

Qualitative investigators are not disinterested outsiders who merely observe without interacting with participants, but affect and are affected by their data. The investigator's emotions as they read participants' narratives are data to be included in the study. Simply asking “research” questions can itself be a chaplaincy intervention: what we ask affects the other person and can lead them to reflect and change ( Grossoehme, 2011 ). It is important to articulate our biases and understand how they influence us when we collect and analyze data. Qualitative research is often done by a small group of researchers, especially the data coding. This minimizes the bias of an individual investigator. Inevitably, two or more people will code passages differently at times. It is important to establish at the outset how such discrepancies will be handled.

Ensuring Rigor, Validity, and Reliability

Some people do not think qualitative research is not very robust or significant. This attitude is due, in part, to the poor quality of some early efforts. Increasingly, however, qualitative studies have improved in rigor, and reviewers of qualitative manuscripts expect investigators to have addressed problematic issues from the start of the project. Two important areas are validity and reliability. Validity refers to whether or not the final product (usually referred to a “model”) truly portrays what it claims to portray. If you think of a scale on which you weigh yourself, you want a valid reading so that you know your correct weight. Reliability refers to the extent to which the results are repeatable; if someone else repeated this study, would they obtain the same result? To continue the scale analogy, a reliable scale gives the same weight every time I step on it. A scale can be reliable without being valid. The scale could reliably read 72 pounds every time I step on it, but that value is hardly correct, so the measure is not valid.

Swinton and Mowat (2006) discussed ensuring the “trustworthiness” of the data. N narrative data which are “rich” in their use of metaphor and description, and which express deeper levels of meaning and nuance compared to everyday language are likely to yield a trustworthy final model because the investigators have done a credible job of completely describing and understanding the topic that is under study. Validity is also enhanced by some methodologies, such as grounded theory, which use participants' own words to name categories and themes, instead of using labels given by the investigator. The concept of “member checking” also enhances validity. Once the analyses are complete and a final model has been developed, these findings are shown to all or some of the participants (the members) who are invited to check the findings and give feedback. Do they see themselves in the words or conceptual model that is presented? Do they offer participants a new insight, or do they nod agreement without really reengaging the findings?

Reliability

One means of demonstrating reliability is to document the research decisions made along the way, as they were made, perhaps in a research diary ( Swinton & Mowat, 2006 ). Qualitative methodologies accept that the investigator is part of what is being studied and will influence it, and that this does not devalue a study but, in fact, enhances it. Simply deciding what questions to ask or not ask, and who you ask them to (and not) reflect certain decisions that should be consciously made and documented. Another researcher should be able to understand what was done and why from reading the research diary.

ETHNOGRAPHIC RESEARCH

Elisa Sobo (2009) defines ethnography as the presentation of, “… a given group's conceptual world, seen and experienced from the inside” (p. 297). Ethnography answers the question, “what's it like to be this person?” One example of this kind of study comes from the work of Fore and colleagues ( Fore, Goldenhar, Margolis, & Seid, 2013 ). In order to design tools that would enable clinicians and persons with pediatric inflammatory bowel disease (IDB) to work together more efficiently, an ethnographic study was undertaken to learn what it was like for a family when a child had IDB. After 36 interviews, the study team was able to create three parent-child dyad personas: archetypes of parents and children with IDB based directly on the data they gathered. These personas were used by the design team to think about how different types of parents and children adapted to the disease and to think what tools should be developed to help different types of parents and children with IDB. An ethnographic study is the method of choice when the goal is to understand a culture, and to present, or explain, its spoken and unspoken nature to people who are not part of the culture, as in the example above of IDB. Before “outsiders” could think about the needs of people with IDB, it was necessary to learn what it is like to live with this disease.

Determining the sample in ethnographic studies typically means using what is called a purposive sample ( Newfield, Sells, Smith, Newfield, & Newfield, 1996 ). Purposive samples are based on criteria that the investigator establishes at the outset, which describe participant characteristics. In the aforementioned IDB example, the criteria were: (1) being a person with IDB who was between 12 and 22 years old or the parent of such a child; (2) being or having a child whose IDB care was provided at one of a particular group of treatment centers; (3) being a pediatric gastrointestinal nurse at one of the centers; or (4) a physician/researcher at one of five treatment centers. Having a sample that is representative of the larger population, always the goal in quantitative research, is not the point in ethnographic studies. Here, the goal is to recruit participants who have the experience to respond to the questions. Out of their intimate knowledge of their culture, the investigator can build a theory, or conceptual model, which could later be tested for generalizability in an entire population.

Ethnographic study designs typically involve a combination of data collection methods. Whenever possible, observing the participants in the midst of whatever experience is the study's focus is desirable. In the process of an ethnographic project on CF, for instance, two students spent a twelve-hour period at the home of a family with a child who had CF, taking notes about what they saw and heard. Interviews with participants are frequently employed to learn more about the experience of interest. An example of this is the work of Sobo and colleagues, who interviewed parents of pediatric patients in a clinic to ask about the barriers they experienced obtaining health care for their child ( Seid, Sobo, Gelhard, & Varni, 2004 ). Diaries and journals detailing people's lived experience may also be used, alone, or in combination with other methods.

Analysis of ethnographic data is variable, depending on the study's goal. One common analytic approach is to begin analysis after the first few interviews have been completed, and to read them to get a sense of their content. The next step is to name the seemingly important words or phrases. At this point, one might begin to see how the names relate to each other; this is the beginning of theory development. This process continues until all the data are collected. At that point, the data are sorted by the names, with data from multiple participants clustered under each topic name ( Boyle, 1994 ). Similar names may be grouped together, or placed under a larger label name (i.e., category). In a sense, what happens is that each interviewer's voice is broken into individual fragments, and everyone's fragments that have the same name are put together. From individual voices speaking on multiple topics, there is now one topic with multiple voices speaking to it.

GROUNDED THEORY RESEARCH

Grounded theory is “grounded” in its data; this inductive approach collects data while simultaneously analyzing it and using the emerging theory to inform data collection ( Rafuls & Moon, 1996 ). This cycle continues until the categories are said to be “saturated,” which typically means the point when no new information is being learned ( Morse, 1995 ). This methodology is generally credited to Glaser and Strauss, who wanted to create a means of developing theoretical models from empirical data ( Charmaz, 2005 ). Perhaps, more than in any other qualitative methodology, the person of the investigator is the key. The extent to which the investigator notices subtle nuances in the data and responds to them with new questions for future participants, or revises an emerging theory, is the extent to which a grounded theory research truly presents a theory capturing the fullness of the data from which it was built. It is also the extent to which the theory is capable of being used to guide future research or alter clinical practice. Grounded theory is the method of choice when there is no existing hypothesis to test. For instance, there was no published data on how parents use faith to cope after their child's diagnosis with CF. Using grounded theory allowed us to develop a theory, or a conceptual model, of how parents used faith to cope ( Grossoehme, Ragsdale, Wooldridge, Cotton, & Seid, 2010 ). An excellent discussion of this method is provided by Charmaz (2006) .

The nature of the research question should dictate the sample description, which should be defined before beginning the data collection. In some cases, the incidence of the phenomena may set some limits on the sample. For example, a study of religious coping by adults who were diagnosed with CF after age 18 years began with a low incidence: this question immediately limited the number of eligible adults in a four-state area to approximately 25 ( Grossoehme et al., 2012 ). Knowing that between 12 and 20 participants might be required in order to have sufficient data to convince ourselves that our categories were indeed saturated, limiting our sample in other ways: for example, selecting representative individuals spread across the number of years since diagnosis would not have made sense. In some studies, the goal is to learn what makes a particular subset of a larger sample special; these subsets are known as “positive deviants” ( Bradley et al., 2009 ).

Once the sample is defined and data collection begins, the analytic process begins shortly thereafter. As will be described in the following paragraphs, interviews and other forms of spoken communication are nearly always transcribed, typically verbatim. Unlike most other qualitative methods, grounded theory uses an iterative design. Sometime around the third or fourth interview has been completed and transcribed and before proceeding with further interviews, it is time to begin analyzing the transcripts. There are two aspects to this. The first is to code the data that you have. Grounded theory prefers to use the participants' own words as the code, rather than having the investigator name it. For example, in the following transcript excerpt, we coded part of the following except:

INTERVIEWER: OK. Have your beliefs or perhaps relationship with God changed at all because of what you've gone through the last nine and 10 months with N.?

INTERVIEWEE: Yeah, I mean, I feel that I'm stronger than I was before actually.

INTERVIEWER: Hmm-hmm. How so? Can you put that into words? I know some of these could be hard to talk about but …

INTERVIEWEE: I don't know, I feel like I'm putting his life more in God's hands than I ever was before.

We labeled, or coded, these data as, “I'm putting his life more in God's hands,” whereas in a different methodology we might have simply named it “Trusting God.” Focus on the action in the narrative. Although it can be difficult, you as a researcher must try very hard to set your own ideas aside. Remember you are doing this because there is no pre-existing theory about what you are studying, so you should not be guided by a theory you have in your mind. You must let the data speak for themselves.

The second point is to reflect on the codes and what they are already telling you. What questions are eliciting the narrative data you want? Which ones are not? Questions that are not leading you to the data you want probably need to be changed. Interesting, novel ideas may emerge from the data, or topics that you want to know more about that you did not anticipate and so the interviewer did not' follow up on them. What are the data not telling you that you are seeking? All of this information flows back to revising the semi-structured interview guide ( Charmaz, 2006 ). This issue raised mild concern with the IRB reviewer who had not encountered this methodology before. This concern was overcome by showing that this is an accepted method with voluminous literature behind it, and by showing that the types of item revisions were not expected to significantly alter the study's effect on the participants. From this point onward you collect data, code it, and analyze it simultaneously. As you code a new transcript and come across a statement similar to others, you can begin to put them together. If you are using qualitative analysis software such as NVivo ( “NVivo qualitative data analysis software,” 2012 ), you can make these new codes “children” of a “parent” node (the first statement you encountered on this topic). The next step is called “focused coding” and in this phase you combine what seems to you to be the most significant codes ( Charmaz, 2006 ). These may also be the most frequently occurring, or the topic with the most duplicates, but not necessarily. This is not a quantitative approach in which having large amounts of data is important. You combine codes at this stage in such a way that your new, larger, categories begin to give shape to aspects of the theory you think is going to emerge. As you collect and code more data, and revise your categories, your idea of the theory will change.

Axial coding follows, as you look at your emerging themes or categories, and begin to associate coded data that explains that category. Axial coding refers to coding the words or quotations that are around the category's “axis,” or core. For example, in a study of parental faith and coping in the first year after their child's diagnosis with CF ( Grossoehme et al., 2010 ), one of the categories which emerged was, “Our beliefs have changed.” There were five axial codes which explain aspects of this category. The axial codes were, “Unchanged,” “We've learned how fragile life is,” “Our faith has been strengthened,” “We've gotten away from our parents' viewpoints,” and “I'm better in tune with who I am.” Each of these axial codes had multiple explanatory phrases or sentences under them; together they explain the breadth and dimensions of the category, “Our beliefs have changed.”

The next step is theoretical coding, and here the categories generated during focused coding are synthesized into a theory. Some grounded theorists, notably one of the two most associated with it (Glaser), do not use axial coding but proceed directly to this step as the means of creating coherence out of the data ( Charmaz, 2006 ). As your emerging theory crystallizes, you may pause to see if it has similarities with other theoretical constructs you encountered in your literature search. Does your emerging theory remind you of anything? It would be appropriate to engage in member-checking at this point. In this phase, you show your theoretical model and its supporting categories to participants and ask for their feedback. Does your model make sense to them? Does it help them see this aspect of their experience differently ( Charmaz, 2005 ). Use their feedback to revise your theory and put it in its final form. At this point, you have generated new knowledge: a theory no one has put forth previously, and one that is ready to be tested.

PHENOMENOLOGY RESEARCH

Perhaps the most chaplain-friendly qualitative research approach is phenomenology, because it is all about the search for meaning. Its roots are in the philosophical work of Husserl, Heidegger and Ricoeur ( Boss, Dahl, & Kaplan, 1996 ; Swinton & Mowat, 2006 ). This approach is based on several assumptions: (1) meaning and knowing are social constructions, always incomplete and developing; (2) the investigator is a part of the experience being studied and the investigator's values play a role in the investigation; (3) bias is inherent in all research and should be articulated at the beginning; (4) participants and investigators share knowledge and are partners; (5) common forms of expression (e.g., words or art) are important; and (6) meanings may not be shared by everyone (Boss et al.). John Swinton and Harriet Mowat (2006) described the process of carrying out a phenomenological study of depression and spirituality in adults and reading their book is an excellent way to gain a sense of the whole process. Phenomenology may be the method of choice when you want to study what an experience means to a particular group of people. May not be the best choice when you want to be able to generalize your findings. An accurate presentation of the experience under study is more important in this approach than the ability to claim that the findings apply to across situations or people (Boss et al.). A study of the devil among predominately Hispanic horse track workers is unlikely to be generalizable to experiences of the devil among persons of Scandinavian descent living in Minnesota. Care must be taken not to overstate the findings from a study and extend the conclusions beyond what the data support.

The emphasis on accurately portraying the phenomenon means that large numbers of participants are not required. In fact, relatively small sample sizes are required compared to most quantitative, clinical studies. The goal is to gather descriptions of their lived experience which are rich in detail and imagery, as well as reflection on its theological or psychological meaning. The likelihood of achieving this goal can be enhanced by using a purposeful sample. That is, decide in the beginning approximately how large and how diverse your sample needs to be. For example, CF can be caused by over 1,000 different genetic mutations; some cause more pulmonary symptoms while others cause more gastrointestinal problems. Some people with CF have diabetes and others do not; some have a functioning pancreas and others need to take replacement enzymes before eating or drinking anything other than water. Some CF adolescents may have lung function that is over 100% of what is expected for healthy adolescents of their age and gender, whereas others, with severe pulmonary disease, may have lung function that is just 30% of what is expected for their age and gender. A study of what it is like for an adolescent to live with a life-shortening genetic disease using this approach might benefit from purposive sampling. For example, lung disease severity in CF is broadly described as mild, moderate or severe. A purposeful sample might call for 18 participants divided into 3 age groups (11–13 years; 14–16 years; and 17–19 years old) and disease severity (mild, moderate, and severe). In each of those nine groups there would be one male and one female. In actual practice, one might want to have more than 18 to allow for attrition, but this breakdown gives the basic idea of defining a purposive sample. One could reasonably expect that having the experience of both genders across the spectrum of disease severity and the developmental range of adolescence would permit an accurate, multi-dimensional understanding to emerge of what living with this life-shortening disease means to adolescents. In fact, such an accurate description is more likely to emerge with this purposeful sample of 18 adolescents than with a convenience sample of the first 18 adolescents who might agree to participate in the study during their outpatient clinic appointment. Defining the sample to be studied requires some forethought about what is likely to be needed to gain the fullest understanding of the topic.

Any research design may be used. The design will be dictated by what data are required to understand the phenomena and its meaning. Interviews are by far the most common means of gathering data, although one might also use written texts, such as prayers written in open prayer books in hospital chapels, for example ( ap Sion, 2013 ; Grossoehme, 1996 ), or drawings ( Pendleton, Cavalli, Pargament, & Nasr, 2002 ), or photographs/videos ( Olausson, Ekebergh, & Lindahl, 2012 ). Although the word “text” appears, it should be with the understanding that any form of data is implied.

The theoretical underpinnings of phenomenology, which are beyond the scope of this article, suggest to users that “a method” is unnecessary or indeed, contrary, to phenomenology. However, one phenomenological researcher did articulate a method ( Giorgi, 1985 ), which consists of the following steps. First, the research team immerses themselves in the data. They do this by reading and re-reading the transcribed interviews and listening to the recorded interviews so that they can hear the tone and timbre of the voices. The goal at this stage is to get a sense of the whole. Second, the texts are coded, in which the words, phrases or sentences that stand out as describing the experience or phenomena under study, or which express outright its meaning for the participant are extracted or highlighted. Each coded bit of data is sometimes referred to as a “meaning unit.” Third, similar meaning units are placed into categories. Fourth, for each meaning unit the meaning of the participants' own words is spelled out. For chaplains, this may mean articulating what the experience means in theological language. Other disciplines might transform the participants' words into psychological, sociological or anthropological language. Here the investigators infer the meaning behind the participants' words and articulate it. Finally, each of the transformed statements of meaning are combined into a few thematic statements that describe the experience ( Bassett, 2004 ; Boss et al., 1996 ). After this, it would be appropriate to do member-checking and a subsequent revision of the final model based on participants' responses and feedback.

PRACTICAL CONCERNS

Just as questionnaires or blood samples contain data, in qualitative research it is the recording of people's words, whether in an audio, video, or paper format which hold the data. Interviews, either in-person or by telephone should be recorded using audio, video or both. It is important to have a device with suitable audio quality and fresh batteries. Experience has shown me the benefit of using two audio recorders so that you do not lose data if one of them fails. There are several small recorders available that have USB connections that allow the audio file to be uploaded to a computer easily. To protect participants' privacy, all data should be anonymized by removing any information that could identify individuals. The Standard Operating Procedure in my research group is to replace all participants' names with an “ N .” During the transcription process, all other individuals are identified by their role in square brackets, “[parent].” Depending on the study's goal and the analytic method you have selected, you may want to include symbols for pauses before participants respond, or non-fluencies (e.g., “ummm. …”, “well … uh …”) or non-verbal gestures (if you are video recording). Decide before beginning whether it is important to capture these as data or not. There are conventional symbols which are inserted into transcriptions which capture these data for you. After the initial transcription, these need to be verified by comparing the written copy against the original recording. Verification should be done by someone other than the transcriptionist. There are several tasks at this stage. Depending on the quality of your recording, the clarity of participants' speech and other factors, some words or phrases may have been unintelligible to the transcriptionist, and this is the time to address them. In my research group our Standard Operating Procedure is to highlight unintelligible text during the transcription phase, and a “verifier” attempts three times to clarify the words on the original recording before leaving them marked “unintelligible” in the transcript. No transcriptionist is perfect and if they are unfamiliar with the topic, they may transcribe the recording inaccurately. I recently verified a transcript where a commercial medical transcriptionist changed the participant's gender from “he” to “she” when the word prior to the pronoun ended with an “s.” If this pattern had not been caught during the verification process, it would have been very difficult during the coding to know whether the pronoun referred to the participant or to their daughter.

ETHICAL ISSUES IN QUALITATIVE RESEARCH

Study design.

The issue of power and the possibility of subtle coercion is the concern here. There is an inherent power differential between a research participant and the investigator, which is exacerbated when the investigator is a chaplain. Despite our attempts to be non-threatening, the very words, "chaplain," or "clergy" connote power. For this reason, the chaplain-investigator should not approach potential participants regarding a study. Potential participants may be informed regarding their eligibility to participate by their physician or a chaplain, but the recruitment and informed consent process should be handled by someone else, perhaps a clinical research coordinator. However, as the chaplain-investigator, you will need to teach them how to talk with potential participants about your study and answer their questions. Choose a data collection method that is best-suited to the level of sensitivity of your research topic. Focus groups can provide data with multiple perspectives, and they are a poor choice when there may be pressure to provide socially correct responses, or when disclosures may be stigmatizing. In such cases, it is better to collect data using individual semi-structured interviews.

Develop a plan for assessing participants' discomfort, anxiety, or even more severe reactions during the study. For instance, what will you do when someone discloses his/her current thoughts of self-harm, or experiences a flashback to a prior traumatic event that was triggered during an interview? How will you handle this if you are collecting data in person? By telephone? You will need to be specific who must be informed and who will make decisions about responding to the risk.

Privacy and Confidentiality

In addition to maintaining privacy and confidentiality of your actual data and other study documents, consider how you will protect participants' privacy when you write the study up for publication. Make sure that people cannot be identified by their quotations that you include as you publish data. The smaller the population you are working with, the more diligently you need to work on this. If the transcriptionist is not an employee of your institution and under the same privacy and confidentiality policies, it is up to you to ensure that an external transcriptionist takes steps to protect and maintain the privacy of participants' data.

Qualitative research is an accessible way for chaplains to contribute new knowledge regarding the sacred dimension of people's lived experience. Chaplains are already sensitive to and familiar with many aspects of qualitative research methodologies. Studies need to be designed to be valid and meaningful, and are best done collaboratively. They provide an excellent opportunity to develop working relationships with physicians, medical anthropologists, nurses, psychologists, and sociologists, all of whom have rich traditions of qualitative research. This article can only provide an overview of some of the issues related to qualitative research and some of its methods. The texts cited, as well as others, provide additional information needed before designing and carrying out a qualitative study. Qualitative research is a tool that chaplains can use to develop new knowledge and contribute to professional chaplaincy's ability to facilitate the healing of brokenness and disease.

Publisher's Disclaimer: Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content.

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Qualitative Research Methods: When Medium Matters (And When It Doesn't)

Qualitative research can be confusing, especially when deciding on the best approach. This article clarifies the difference between research methods and mediums, helping you design more effective studies.

October 30, 2024

Market researchers are no strangers to the ongoing debate about how best to conduct qualitative research methods. Should studies be in-person or remote? Text-based or video? We understand how frustrating it can be when conversations get bogged down in these details. But here's the key: many teams unknowingly conflate the medium of research with the method itself.

This isn't just about semantics. Clarifying the difference between method and medium can lead to more efficient research design, better processes, and ultimately better outcomes.

In this article, you'll learn when medium actually matters for research quality, how to make smart choices about research design, and how new advances in methodology are changing the way we collect and verify data. That way, you can get back to doing what you do best: uncovering insights that drive meaningful change.

Qualitative research method versus medium

Qualitative research methods and the mediums used to conduct them are fundamentally different things. A research method, like interviews, focus groups , or diary studies, defines how we gather information and insights. The medium is simply the channel through which we conduct that method. This might be in-person, over the phone, through video, or via text. This distinction matters because switching mediums doesn't change or advance the method itself.

"We moved from in-person to telephone to video," explains Suzanne Walsh , Research Consultant at Remesh . "We've changed the medium, but we didn't change the interview itself. The method remains the same."

When researchers analyze qualitative data , they work with transcripts , whether from one-on-one interviews, group discussions, or online forums. The words mean the same thing no matter how they were collected. For example, conducting interviews via video is absolutely more convenient than in-person, but it doesn't offer additional benefits than in-person

What pushes research forward

The real challenge in qualitative research isn't about medium, it's about achieving both breadth and depth while maintaining data quality . AI-powered platforms like Remesh represent true methodological progress by solving this longstanding challenge.

Remesh occupies a unique position as "quali-quant." It's neither purely qualitative nor quantitative, but a groundbreaking hybrid that offers capabilities previously impossible in market research. The platform's "percent agree" algorithm, for example, quantifies agreement on qualitative responses in real-time, something unattainable in traditional qualitative research methods.

"That's what's so unique about it and what makes it different from a bulletin board," Suzanne explains. "Every verbatim will have an agreement score attached to it. In a bulletin board, if participants interact with each other, they might say 'yeah, I agree with what he's saying,' but not everybody speaks up."

This tackles a persistent challenge in qualitative research. Many quantitative researchers find qualitative work daunting because, no matter the method, they can't measure it or put numbers to it. Remesh changes this by providing specific agreement scores for qualitative responses .

When medium matters

Most of the time, the medium you use to collect qualitative research doesn't affect your results, but choosing the right medium can affect your efficiency and practical outcomes. For instance, conducting interviews via video might be more convenient than coordinating in-person sessions. However, medium is sometimes integral to the method itself.

The best example is experiential research where video is integral to the method . This might include watching how customers shop in stores, seeing how people use products in their homes, or understanding how people interact with their environment. In these cases, researchers need visual observation via video to capture authentic behavior.

"If you're looking at experience research," Suzanne notes, "if it's place-based, like watching how someone looks at items on a shelf, how they read labels, what catches their eye, you can use video effectively." This type of observational research differs fundamentally from simply recording a conversation or interview.

The importance of data triangulation

Quality research depends on verified data. Researchers have long used data triangulation, verifying findings through multiple methods , to ensure quality. Observational insights from experiential video research, for instance, become more powerful when verified through other approaches.

After observing behaviors through video, researchers need to validate their observations across a larger population. The key question isn't how you collect data, but whether your method gives you reliable, verifiable insights.

"Good quality data is verified data," Suzanne emphasizes.

Remesh's ability to gather responses from many participants simultaneously offers one way to verify findings quickly. Researchers can confirm whether observed behaviors represent common patterns or outliers across a broader population. This combination of depth and scale allows researchers to make confident, actionable decisions based on verified insights.

Other key considerations for research success

In addition to ensuring data quality, it's vital to have a clear research question . Clear research questions shape everything that follows. While the pressure to move quickly can tempt researchers to rush ahead, taking time to develop strong research questions pays off.

Think beyond methodology and medium to purpose. What do you need this data to do for you? Whether it's answering strategic questions or developing new products that meet customer needs, the research objective should drive methodological choices.

Researchers should also remain open to new approaches . Sometimes you need to shake up traditional methods to get fresh insights. In a field with constant innovation, focusing too much on specific mediums might cause you to miss more effective ways to gather actionable insights.

Wrapping up qualitative research methods and mediums

Understanding the difference between qualitative research methods and mediums helps researchers make more strategic choices. Whether choosing between interviews, be it video or in-person, or focus groups, what matters most is matching your approach to your research objectives. Some methods, like observational research, require specific mediums. Others benefit more from scale and verification than from the medium used to collect data.

AI-driven platforms like Remesh represent one way that research continues to evolve , offering new possibilities for gathering and validating insights. The most effective research strategies often combine different approaches, using each method's strengths to build a complete, verified understanding of consumer behavior and opinions.

I want to validate my insights!

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How to Analyze Interview Transcripts in Qualitative Research

Transcription is a great method for interview data analysis — especially for qualitative research. Learn more about it and how Rev can help.

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Studies take time, accuracy, and a drive to provide excellent information, and qualitative research is a critical part of any successful study. You may be wondering how qualitative data adds to a paper or report, given that it’s not the hard “science” we often see highlighted the most often.

How Do You Analyze Qualitative Interviews?

There are two main approaches to qualitative analysis: inductive and deductive . What’s more, there are two types of inductive qualitative analysis to choose from. These are called thematic content analysis and narrative analysis, both of which call for an unstructured approach to research.

Inductive Methods of Analyzing Interview Transcripts

A thematic content analysis begins with weeding out biases and establishing your overarching impressions of the data. Rather than approaching your data with a predetermined framework, identify common themes as you search the materials organically. Your goal is to find common patterns across the data set.

A narrative analysis involves making sense of your interview respondents’ individual stories. Use this type of qualitative data analysis to highlight important aspects of their stories that will best resonate with your readers. And, highlight critical points you have found in other areas of your research.

Deductive Approach to Qualitative Analysis

Deductive analysis , on the other hand, requires a structured or predetermined approach. In this case, the researcher will build categories in advance of their analysis. Then, they’ll map connections in the data to those specific categories.

Each of these qualitative analysis methods lends its benefits to the research effort. Inductive analyses will produce more nuanced findings. Meanwhile, deductive analyses allow the researcher to point to key themes essential to their research.

Successful qualitative research hinges on the accuracy of your data. This can be harder to achieve than with quantitative research. It’s easy to lose important facts and meaning as you transition qualitative data from the source to your published content. This makes transcription a vital tool in maintaining integrity and relaying information in an unbiased way that’s useful for readers and adds appropriate context to the journal or study.

How to Transcribe a Qualitative Interview

Accurate transcription begins early in the interview process, even before you start interviewing. Here are the steps to transcribing a qualitative interview.

1. Collect Feedback for Qualitative Research

There are dozens of ways to gather qualitative data. Recording and accurately transcribing interviews is among the best methods to avoid inaccuracies and data loss, and researchers should consider this approach over simply taking notes firsthand.

Make sure you have a reliable way to record, whether the interview takes place in person, over the phone, or as part of a video call. Depending on the interview method, you may record a video or an audio-only format. Here are some tips depending on where the interview takes place:

• These apps can also be used for over-the-phone interviews.
• For video interviews , we recommend taking advantage of one of our transcription integrations , such as Zoom. Rev also has an API available for those who want to streamline their workflow even further by integrating Rev directly into their processes and platforms.

2. Organize Your Research Recordings

You should ensure that your audio or video files are easy to save, compile, and share. To do this, be sure to adopt easy-to-remember naming conventions as well to ensure they stay organized. An example of a naming convention that is simple to remember and recreate includes “Date.LastNameofSource.Topic”.

3. Transcribe All the Interviews and Focus Group Recordings

The next critical step is transcription. Done manually, this is a long and tedious process that can add hours, days, or even months to your report-writing process. There are dozens of pitfalls when performing transcriptions manually as well, as it can be hard to pick up words spoken in a heavy dialect or quiet tone. You also want to avoid having to transcribe all the “umms” and “ems” that occur when a source is speaking naturally.

Rev provides a variety of transcription services that take the tedium and guesswork out of the research process. You can choose to edit out all of the “umms,” while ensuring that heavy accents or muffled voices are picked up by the recording service.

You can order transcripts from Rev with both audio and video recordings. Once you’ve received your professional transcripts from Rev, you can begin your qualitative analysis.

The 6 Steps of Qualitative Interview Data Analysis

Among qualitative interview data analysis methods, thematic content analysis is perhaps the most common and effective method. It can also be one of the most trustworthy , increasing the traceability and verification of an analysis when done correctly. The following are the six main steps of a successful thematic analysis of your transcripts.

1. Read the Transcripts

By now, you will have accessed your transcript files as digital files in the cloud or have downloaded them to your computer for offline viewing. Start by browsing through your transcripts and making notes of your first impressions. You will be able to identify common themes. This will help you with your final summation of the data.

Next, read through each transcript carefully. Evidence of themes will become stronger, helping you to hone in on important insights.

You must identify bias during this step as well. Biases can appear in the data, among the interviewees, and even within your objectives and methodologies. According to SAGE Publishing , researchers should “acknowledge preconceived notions and actively work to neutralize them” at this early step.

2. Annotate the Transcripts

Annotation is the process of labeling relevant words, phrases, sentences, or sections with codes. These codes help identify important qualitative data types and patterns. Labels can be about actions, activities, concepts, differences, opinions, processes, or whatever you think is relevant.  Annotations will help you organize your data for dissemination .

Be generous with your annotations—don’t hold back. You will have an opportunity to eliminate or consolidate them later. It’s best to do more here, so you don’t have to come back to find more opportunities later.

3. Conceptualize the Data

Conceptualizing qualitative data is the process of aligning data with critical themes you will use in your published content. You will have identified many of these themes during your initial review of the transcripts.

To conceptualize,  create categories and subcategories  by grouping the codes you created during annotation. You may eliminate or combine certain codes rather than using all the codes you created. Keep only the codes you deem relevant to your analysis.

4. Segment the Data

Segmentation is the process of positioning and  connecting your categories . This allows you to establish the bulk of your data cohesively. Start by labeling your categories and then describe the connections between them.

You can use these descriptions to improve your final published content.

• Create a spreadsheet  to easily compile your data.
• Then, use the columns to structure important variables of your data analysis using codes as tools for reference.
• Create a separate tab for the front of the document that contains a coding table. This glossary contains important codes used in the segmentation process. This will help you and others quickly identify what the codes are referring to.

5. Analyze the Segments

You’re now ready to take a  deep dive into your data segments . Start by determining if there is a hierarchy among your categories. Determine if one is more important than the other, or draw a figure to summarize the results. At this stage, you may also want to align qualitative data with any quantitative data you collected.

6. Write the Results

Your analysis of the content is complete—you’re ready to transition your findings into the real body of your content. Use your insights to build and verify theories, answer key questions in your field, and back aims and objectives. Describe your categories and how they are connected using a neutral, objective voice.

Although you will pull heavily from your own research, be sure to publish content in the context of your field. Interpret your results in light of relevant studies, theories, and concepts related to your study.

Why Use Interviews for Qualitative Data

Unlike quantitative data, which is certainly important, a qualitative analysis adds color to academic and business reports. It offers perspective and can make a report more readable, add context, and inspire thoughtful discussion beyond the report.

As we’ve observed, transcribing qualitative interviews is crucial to getting less measurable data from direct sources. They allow researchers to provide relatable stories and perspectives and even quote important contributors directly. Lots of qualitative data from interviews enables authors to avoid embellishment and maintain the integrity of their content as well.

So, how do you conduct interview data analysis on qualitative data to pull key insights and strengthen your reports? Transcribing interviews is one of the most useful tools available for this task.

As a researcher, you need to make the most of recorded interviews . Interview transcripts allow you to use the best qualitative analysis methods. Plus, you can focus only on tasks that add value to your research effort.

Transcription is Essential to Qualitative Research Analysis

Qualitative data is often elusive to researchers. Transcripts allow you to capture original, nuanced responses from your respondents. You get their response naturally using their own words—not a summarized version in your notes.

You can also go back to the original transcript at any time to see what was said as you gain new context. The editable digital transcript files are incredibly easy to work with, saving you time and giving you speaker tags, time marks, and other tools to ensure you can find what you need within a transcript quickly.

When creating a report, accuracy matters, but efficiency matters, as well. Rev offers a seamless way of doing the transcription for you, saving you time and allowing you to focus on high-quality work instead. Consider Rev as your transcription service provider for qualitative research analysis — try Rev’s AI or Human Transcription services today.

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Using Responses to Likert-Type Items in Qualitative Research

• November 6, 2024
• John Bryan, DBA, and Donna Graham, MEd, PhD

Using Likert-type items in qualitative research is both common and a topic of debate among researchers. American social psychologist Rensis Likert (1932) developed the Likert scale, a popular tool for measuring attitudes and opinions in “A Technique for the Measurement of Attitudes,” seeking to create a more reliable and valid method for measuring attitudes, preferences, and perceptions. He proposed five response alternatives: strongly approve, approve, undecided, disapprove, and strongly disapprove. Unlike previous methods, the Likert scale allowed for the summation of individual Likert-type item scores to create a composite score representing an overall attitude. This summative approach was a significant innovation, providing a more comprehensive measure of attitudes. Likert sought to quantify inherently qualitative, subjective, unobservable constructs, responses, or attitudes (Tanujaya et al., 2022).

In this paper, Likert-type items will refer to the individual items in an instrument rated using an ordered set of alternative responses. Similarly, Likert-type responses will refer to the actual choice made by the research participant, e.g., strongly agree, undecided, or disagree. Likert scale will refer to a group of four or more Likert-type items that a researcher may use to measure a latent variable of interest. Likert-type items provide a structured way to collect data, offering a clear framework for respondents to express their attitudes, opinions, and perceptions, facilitating a more straightforward analysis and comparison of responses (Doğan & Demirbolat, 2021; Dwivedi & Pandey, 2021). Researchers argue that Likert-type items and Likert scales are similar and can only be used one way, with some saying that the analysis is strictly quantitative and others arguing that qualitative analysis is possible (Tanujaya et al., 2022). Proudfoot (2022) discussed integrating qualitative and quantitative methods through hybrid thematic analysis, highlighting the flexibility in using Likert-type items in qualitative research. In this paper, we present some of the main arguments for and against their use qualitatively and quantitatively, with some examples from each.

Likert Scale

The Likert scale is a series or battery of a minimum of four or more mutually inclusive Likert-type items that are combined into a single composite score variable during the data analysis process (Tanujaya et al., 2022), implying an assumption of an underlying continuous variable (Doğan & Demirbolat, 2021; Kleinheksel & Summy, 2020). Likert scales refer to the sum or average of responses to multiple Likert-type items designed to measure a single construct, e.g., a scale measuring job satisfaction. The Likert scale revolutionized the measurement of attitudes by providing a straightforward and effective method for quantifying subjective opinions (Tanujaya et al., 2022). Its adoption and continued use across various disciplines underscore its impact on social science research despite ongoing debates about its limitations and best practices (Tanujaya et al., 2022).

Over time, researchers developed variations of the original Likert scale, including different numbers of response categories, e.g., 5-point, 7-point scales, and alternative response formats, e.g., frequency scales (Tanujaya, 2022). Likert scales provide insight into dimensions of an attitude or perception related to a phenomenon (Tanujaya et al., 2022). The argument for considering Likert-type responses as qualitative or quantitative hinges on the research goals and the nature of the data analysis. Quantitative arguments emphasize numerical analysis, aggregation, and statistical testing, while qualitative arguments focus on the subjective meaning, context, and thematic interpretation of individual responses.

Some researchers advocate for a mixed-methods approach, combining quantitative analysis for general trends with qualitative interpretation for deeper understanding. The context in which the Likert-type scale is used can determine whether a qualitative or quantitative approach is more appropriate. For example, in exploratory research, the qualitative aspect may be emphasized, whereas, in hypothesis-testing research, the quantitative aspect may be prioritized. Combining both perspectives can provide a comprehensive understanding of the data. Researchers may also analyze the collected responses to the Likert-type items separately, as items rather than as scales or dimensions (Tanujaya et al., 2022).

Likert-Type Items

Researchers analyze Likert scales and Likert-type items differently due to their distinct characteristics (Tanujaya et al., 2022). Likert-type items are single questions or statements that are mutually exclusive among each other. In analyzing Likert-type items, the researcher does not create a composite score (Doğan & Demirbolat, 2021). Responses to Likert-type items are ordinal, meaning they represent an order but the intervals between categories are not necessarily equal (South et al., 2022); 

Likert-type responses may be qualitative, because the responses and their interpretation are inherently subjective. Each response represents an individual’s subjective experience, belief, or feeling, which can provide qualitative insights. Researchers can describe responses in terms of what they mean for the respondents, focusing on understanding the underlying meanings, contexts, and nuances of respondents’ choices rather than numerical value (Tanujaya et al., 2022). As qualitative data, each individual’s answer is examined in detail to understand what it signifies for that particular respondent. Likert-type items are appropriate to use to probe responses gathered from other data sources.

Analyzing the reasons behind the individual Likert-type item responses can provide deeper insights into and contexts for the attitudes and perceptions of respondents. A researcher might administer Likert-type items along with open-ended questions in surveys or interviews. After collecting additional qualitative data, e.g., interview transcripts, the researcher would review the Likert-type responses and associated qualitative data to get an overall sense of the patterns and themes, to delve deeper into the reasons behind a respondent’s Likert-type response (Li et al., 2023). This can reveal the motivations, attitudes, and feelings that led to the specific choice on the Likert-type item, to delve deeper into the reasons behind a respondent’s Likert-type response, analyzing responses for emerging patterns or themes without relying on numerical aggregation, similar to qualitative content analysis (Alabi & Jelili, 2023). Then, the researcher would code the individual Likert-type responses for key themes and patterns, potentially using qualitative data analysis software, e.g., NVivo, Atlas.ti, MaxQDA, to identify recurring themes or patterns.

Themes can emerge inductively from the data, providing insights into common factors influencing responses. Descriptions are created to capture the essence of each theme, illustrating how different respondents interpret and react to the same item, supplemented by illustrative direct quotes from respondents to exemplify specific themes, providing vivid illustrations of their perspectives. Following the coding, the researcher could interpret each response and the themes in the context of the respondents’ overall narratives and backgrounds, considering factors such as personal experiences, cultural background, and situational influences, and discuss how individual responses relate to broader trends and insights from the qualitative data.

Likert-type responses can be triangulated with other qualitative data sources such as interview transcripts, observational notes, or document analysis. This integration can provide a more holistic view of the research topic, enriching the analysis and interpretation of Likert-type responses. By focusing on narrative description, thematic analysis, comparative analysis, triangulation, and reflexive practices, researchers can gain rich, detailed insights into participants’ perspectives and experiences and reveal the deeper meanings and contexts behind each response.

Likert-type items facilitate the comparison of responses across different groups or over time (Doğan & Demirbolat, 2021). This comparability can be especially useful in mixed-methods research where qualitative insights need to be aligned with quantitative findings. The result would be a report of findings with rich descriptions, illustrative quotes, and contextual analysis and a discussion of the implications of the findings for the research question and broader field of study. Responses to individual Likert-type items can be useful in comparing responses across groups, e.g., demographic categories, experience levels, to explore variations in perceptions and attitudes. Understanding why different groups respond differently can highlight important contextual factors and social influences.

In conclusion, the use of Likert-type items in qualitative research offers a nuanced approach to exploring complex attitudes and perceptions, bridging the gap between quantitative precision and qualitative depth. While the traditional application of Likert scales has been predominantly quantitative, the integration of qualitative analysis allows for a richer understanding of the subjective meanings behind individual responses. By adopting a qualitative approach, researchers can leverage the structured nature of Likert type items to capture general trends while simultaneously delving into the contextual and thematic aspects of respondent choices. This dual approach not only enhances the interpretative richness of the data but also provides a more comprehensive framework for understanding the diverse factors influencing attitudes and perceptions. Ultimately, the flexibility of Liker-type items in qualitative research underscores their value as a versatile tool, capable of yielding insights that are deeply reflective of the human experience.

Dr. John Bryan is a university professor, editor, and dissertation chair. Bryan holds a BA in Chemistry from University of California, San Diego, an MBA in Operations and Marketing from Rutgers, the State University of New Jersey, and a DBA in Leadership from the University of Phoenix. 

Dr. Donna Graham is a university professor and dissertation chair. Graham holds a BA in Psychology and Education from Rosemont College, a MS in Counseling from Villanova University, a MEd in Educational Technology from Rosemont College, and a Doctorate in Philosophy from Capella University.  

Alabi, A. T., & Jelili, M. O. (2023). Clarifying likert scale misconceptions for improved application in urban studies. Quality & Quantity, 57 (2), 1337–1350.

Doğan, E., & Demirbolat, A. O. (2021). Data-driven decision-making in schools scale: A study of validity and reliability. International Journal of Curriculum and Instruction, 13 (1), 507–523.

Kleinheksel, A. J., & Summy, S. E. (2020). Establishing the psychometric properties of the EBPAS-36: A revised measure of evidence-based practice attitudes. Research in Social Work Practice, 30 (5), 539–548.

Li, X., Li, Q., & Wang, Q. (2023). Analysis of college students’ misconceptions of quantitative research in social sciences in China: Implications for teaching. Journal of Education and Educational Research, 2 (3), 28–31. https://doi.org/10.54097/jeer.v2i3.7140 

Likert, R. (1932). A technique for the measurement of attitudes. Arch Psychology, 22 (140), 55.

Proudfoot, J. (2022). Inductive and deductive hybrid thematic analysis in mixed-methods research. Journal of Mixed Methods Research, 17 (3), 308–326.

South, L., Saffo, D., Vitek, O., Dunne, C., & Borkin, M. A. (2022, June). Effective use of Likert scales in visualization evaluations: A systematic review. In Computer Graphics Forum, 41 (3), 43–55. Wiley.

Tanujaya, B., Prahmana, R. C. I., & Mumu, J. (2022). Likert scale in social sciences research: Problems and difficulties. FWU Journal of Social Sciences, 16 (4), 89–101.

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• Open access
• Published: 05 November 2024

Cultural adaptation of an internet-based self-help app for grieving Syrian refugees in Switzerland

• Anaïs Aeschlimann 1 ,
• Eva Heim 2 ,
• Anna Hoxha 1 ,
• Valentina Triantafyllidou 1 ,
• Clare Killikelly 1 ,
• Farhad Haji 3 ,
• Rilana Tanja Stoeckli 4 ,
• Monia Aebersold 3 &
• Andreas Maercker 1  

BMC Public Health volume  24 , Article number:  3048 ( 2024 ) Cite this article

45 Accesses

Metrics details

Loss and grief pose significant challenges for victims of armed conflicts, such as Syrian refugees. Internet-based interventions (IBIs) present a promising solution to address this treatment gap and provide adequate support. However, research on grief, grief support, and IBIs remain largely limited to Western cultural contexts, and culturally adapted IBIs for grief are needed. Following the Reporting Cultural Adaptation in Psychological Trials (RECAPT) framework, this study aimed to develop and further adapt a culturally sensitive IBI for bereaved Syrian refugees in Switzerland.

The study employed qualitative methods. Initially, formative research was conducted to create a first version of the intervention, including semi-structured interviews with 10 experts to identify necessary cultural adaptations. The preliminary version of the intervention was then presented to six potential users and three experts to gather feedback on additional cultural adaptations through two iterative feedback rounds. The first round involved semi-structured interviews using a “paper version” of the intervention, followed by a second round with a walk-through think-aloud protocol with a beta version. Data were analyzed using framework analysis.

The input from various key informants at different stages of development provided valuable feedback on surface and deep structure adaptation, which may enhance treatment adherence, acceptance, and motivation.

Conclusions

These findings provide important insights and recommendations for the cultural adaptation of interventions and may help address the treatment gap for bereaved Syrian refugees.

Peer Review reports

Introduction

Thirteen years into the devastating Syrian civil war, 13.8 million Syrians have been forcibly displaced, marking the highest proportion of displaced people relative to any national population worldwide [ 1 ]. As of the end of 2023, nearly 14,000 Syrian refugees have been recognized in Switzerland, making them the second largest group of recognized refugees in the country [ 2 ]. The war has caused extremely high humanitarian costs with over 16 million Syrians in need of humanitarian assistance in 2024 [ 3 ]. A central issue for victims of armed conflicts, such as Syrian refugees, is the experience of loss and grief [ 4 ]. These loss experiences, coupled with post-migration stressors, such as financial difficulties, discrimination, and being separated from one’s family [ 5 ], have been shown to increase the probability of developing prolonged grief disorder (PGD; 6). Accordingly, studies indicate much higher prevalence rates of PGD in refugees compared to the general population, with a pooled prevalence rate of approximately 33.2% in refugees as opposed to estimates of 3.3–4.2% in the general population [ 7 , 8 , 9 ].

PGD is a newly recognized diagnostic category for excessively prolonged and intense grief reactions, now included in the latest edition of the World Health Organization’s International Classification of Diseases (ICD-11; [ 10 ]). Diagnostic criteria emphasize cultural variations in grief expression, duration, and functional impairment, allowing for a diagnosis only if the grief response surpasses the intensity and duration expected within the individual’s socio-cultural context [ 11 ]. This culturally sensitive approach is in line with recent research indicating that directly translating mental health constructs developed in Western, Educated, Industrialized, Rich, and Democratic (WEIRD; [ 12 ]) contexts to other sociocultural settings can result in “category fallacy” [ 13 ]. This occurs because such translations often neglect culture- or context-specific factors that influence mental health issues.

It is well-documented that culture shapes the way mental health problems are expressed (“cultural idioms of distress”; [ 14 ]) and individuals’ explanations for these issues, including their causes, course, and potential outcomes (explanatory models; e.g., [ 15 , 16 ]). To account for cultural differences in the phenomenology and etiology of mental health problems, the term “cultural concepts of distress” (CCD) was introduced in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM; [ 17 ]). Grief in particular is heavily saturated with cultural influence, including differences in grief expression, mourning rituals and practices, and beliefs about death [ 18 ]. While there might be commonalities in some grief responses, normal and clinically relevant grief symptoms can vary greatly across cultures [ 19 ]. For instance, emotional outbursts in the first days or weeks after the loss are considered normal by Syrian refugees [ 20 ], while for Palestinians, negative emotional outbursts are usually concealed [ 21 ].

The significantly elevated prevalence rates of PGD among refugees underscore the urgent need for comprehensive support and intervention. However, a substantial mental health support gap for refugee communities persists [ 22 , 23 ]. Bryant et al. [ 6 ], for instance, found that 43.7% of the refugee sample with probable PGD had not received any psychological assistance. Numerous barriers of both structural and socio-cultural nature have been recognized to prevent or hinder refugees from accessing mental health care services in their host countries [ 22 , 24 ]. In a study with Syrian refugees in Switzerland, these included language barriers, lack of resources, lack of trust in health professionals, and a fear of stigma [ 24 ]. In addition, the cultural incongruity between Western healthcare professionals and refugees relating to differences in mental health beliefs, explanations, and practices about mental health has been found to negatively affect help-seeking behavior [ 24 , 25 , 26 ].

This emphasizes the importance of developing and implementing accessible mental health care for refugee populations. Internet-based interventions (IBIs) are considered a viable solution to bridging this gap [ 27 ]. This approach aligns with recent recommendations from the American Psychological Association Summit [ 28 ], which emphasize the need to scale up effective individual-level interventions to the population level by leveraging innovative delivery systems such as online platforms and mobile applications. IBIs are easily accessible, are low in delivery cost, can be used flexibly independent of time and location at a self-determined pace, and provide anonymity to users [ 27 , 29 ]. Evidence provides support for the efficacy of IBIs in the treatment of mental health disorders [ 30 , 31 , 32 ]. A guided and scalable IBI for depression was evaluated for Syrian refugees in Lebanon with results showing a significant reduction in depression and anxiety symptoms [ 33 ]. Hence, IBIs have the potential to address many of the barriers to mental health care experienced by Syrian refugees in Switzerland and may improve access to support for those who are bereaved.

Although the results are promising, evidence for the effectiveness of IBIs for grief remains limited and largely confined to WEIRD contexts [ 34 , 35 , 36 ]. Given that culture significantly impacts grief reactions, it is crucial to consider these aspects when developing an IBI for bereaved refugees. Meta-analytic findings support the effectiveness and acceptability of culturally adapted psychological interventions over non-adapted ones [ 37 , 38 ]. In one meta-analysis, a higher number of adapted elements in IBIs was associated with higher effect sizes [ 39 ], and culturally adapting interventions also appears to increase adherence [ 40 ]. However, no culturally adapted IBI for bereaved individuals has been developed so far [ 41 ].

Cultural adaptation can be conceptually divided into surface and deep structure adaptation [ 42 ]. Surface structure adaptation relates to matching materials and treatment delivery to observable characteristics of the target group (e.g., language and illustrations). In the context of IBIs, this includes adaptation of user-interfaces and software functions to the intended users (e.g., 43). In contrast, deep structure adaptation considers social, cultural, environmental, and psychological factors that influence health behavior [ 42 ]. The latter includes considering a population’s CCD, which encompass idioms of distress and explanatory models [ 17 , 44 ]. One way to conceptualize this distinction is to think of deep structure as addressing the “what” and “why” of an intervention, while surface structure pertains to the “how” of its delivery. However, this is a simplification, and the separation is not always clear-cut.

Criticizing the lack of standardized criteria for documenting cultural adaptations in clinical trials, Heim et al. [ 45 ] proposed The Reporting Cultural Adaptation in Psychological Trials (RECAPT) criteria, which incorporate the dimension of deep and surface structure adaptation and can be used as a guideline to plan the cultural adaptation process of an intervention, as well as providing a template for documenting adaptations. This can be implemented for both top-down approaches, where an existing intervention is adapted, and bottom-up interventions, which are newly developed interventions within a specific cultural context [ 45 ].

To the best of our knowledge, no culturally adapted IBI for grieving Syrian refugees has been developed so far. Hence, the aim of the current project was the bottom-up development and cultural adaptation of such an IBI for future integration as a supplementary module into the “Sui app”, a digital psychosocial support app for refugees developed by the Swiss Red Cross [ 46 ]. Following the framework for cultural adaptation of scalable psychological interventions proposed by Heim and Kohrt [ 44 ] and the RECAPT-Criteria [ 45 ], this project encompasses three cultural adaptation phases:

The formative research phase aimed to gather information on context, target symptoms, and specific needs of Syrian refugees in Switzerland, as well as on aspects of the planned IBI, such as possible contents and structure, informing the development of the first version of the IBI.

The first cultural adaptation phase aimed to evaluate, adapt, and complement a first version of the IBI in terms of relevance, cultural acceptability, and comprehensibility of intervention contents regarding grief-related CCD, community needs, treatment components, structure and illustrations.

The second cultural adaptation phase aimed to evaluate and adapt a beta version of the IBI regarding cultural acceptability, relevance and comprehensibility.

As recommended in the RECAPT guidelines [ 45 ], the Consolidated Criteria for Reporting Qualitative research (COREQ) were followed to ensure transparency and research quality (see Additional File 3 ). The formative research commenced with a literature review as per Heim and colleagues [ 45 ] suggestions. A scoping review, which explored the scope and nature of culturally sensitive interventions addressing grief, was published recently [ 41 ]. Results of the literature review were supplemented with qualitative information gathered through three rounds of semi-structured, in-depth key informant interviews (KII) with potential users and experts in the accompaniment of grieving Syrian refugees. This qualitative design was employed for a thorough understanding of the participants’ individual experiences [ 47 ] and because it is ideal for acquiring detailed information on a specific topic within a target group from a different cultural background [ 20 ]. Based on findings from the literature review, the first key informant interviews with potential users (KIIU1) and experts (KIIE1), a first version of the IBI-content was developed. In the following two stages of interviews with potential users and experts (KIIUE2 and KIIUE3), the IBI was evaluated and further adapted in an iterative manner. An overview of the final version of the IBI content is available in Additional File 5 (see Fig.  1 for an overview of all chapters).

Overview of the chapters of the IBI in German and Arabic

As the three stages slightly differ regarding sample and recruitment as well as data collection, they will be described in individual subchapters. Methods and results from KIIU1 will not be detailed further, as these are published elsewhere [ 20 ]. The ethics proposals for KIIE1 and KIIUE2/KIIUE3 were accepted by the ethics committee of the Faculty of Arts and Social Sciences at the University of Zurich (UZH) in March 2022 and March 2023, respectively.

Sample and recruitment

Potential participants were recruited via purposive and snowball sampling [ 48 ] through e-mail or via phone call, and provided with initial information about the project. Participants had to be mental health experts, religious leaders, or interpreters working with or counseling Syrian refugees with PGD in Switzerland. In addition to that, potential participants had to be at least 18 years old and fluent in German. Individuals who met the inclusion criteria were given detailed information about the study, the opportunity to ask any additional questions, and were provided with two consent forms: one for study participation and another for the audio recording of the interviews. Interested participants then scheduled interview appointments. Interpreters received compensation at their standard hourly rate of 90 CHF, while other KI did not receive compensation due to limited financial resources. Sample size was estimated based on results of a systematic review by Hennink and Kaiser [ 49 ] which showed that data saturation in in-depth interview studies is normally reached between 9 and 17 interviews. Two potential participants dropped out before their interview appointment due to personal reasons. In total, n  = 10 key informants were included. Details on participant characteristics can be found in Additional File 4 .

Data collection

Data was collected between May and September 2022. Roles and background of the research team members for all KII can be found in Additional File 1 . The interviewer and participants had not met previously. Interview sessions were conducted either in person at the Psychological Department of the UZH or via video conference on a secure platform. Participants were provided with both written and oral information about the study, and written informed consent was obtained. Interviews were held in German, audio-recorded, and subsequently transcribed using f4 audio transcription software version 8.1.1 [ 50 ]. Two participants had a follow-up interview, as the subject of interest was initially not fully captured as intended. The interviews lasted from 62 min to 111 min.

The interviews were composed of a brief demographic questionnaire and a semi-structured interview guide featuring open-ended questions. The interview guide was developed in an iterative process following the guidelines by Fylan [ 51 ] and Kallio and colleagues [ 52 ], with the content being informed by the RECAPT criteria and further background literature. The first part of the guide included questions about the CCD concerning Syrian refugees’ grief, while the second part involved questions about the development, intended content and structure of the future IBI (see Additional File 2 ). Two pilot interviews were conducted to assess and refine the initial interview guide.

Based on the results from KIIE1, a first version of the IBI content was developed. This initial version was drafted on paper and included the texts (excluding vignettes and texts for audio-exercises) and the first sketches of illustrations. The texts were originally written in German, adapted to simple German, and then translated to Arabic. During the development of this first version, a desk review was conducted to gather additional information not previously covered by the scoping review or KIIE1 on various topics, including positive psychology and mindfulness in Arabic-speaking populations, internet-based interventions for grief, and psychological interventions for grief. KIIUE2 focuses on the evaluation and adaptation of this first version.

Two groups of participants were recruited. Experts had to meet the same inclusion criteria as in KIIE1, while potential users needed to be Syrian and at least 18 years old. Experts were recruited via e-mail and phone from the previous phase of the formative research. Interpreters were compensated at their standard hourly rate of 90 CHF, while other experts did not receive compensation due to limited financial resources. Potential users were recruited by the interpreter affiliated with the Swiss Red Cross (SRC) and were compensated with a supermarket voucher worth 150 CHF (including travel expenses). Those meeting the inclusion criteria received detailed study information, had the chance to ask questions, and were provided with two informed consent forms: one for study participation and one for audio recording. Interested participants then scheduled interview appointments. The aim was to include at least three experts and six potential users. No potential participants dropped out. In total, n  = 9 key informants participated, including three experts and six potential users. Details on participant characteristics can be found in Additional File 4 .

Data was collected between March and April 2023. Individual interviews were conducted in German with the experts either in person at the Department of Psychology at the UZH or online on a secure platform. In each interview with potential users, which were conducted at the premises of the SRC in Bern, two participants, one or two interviewers (with one person aiding with timekeeping), and a Syrian interpreter were present. The decision to have two participants interviewed at once, i.e. to combine focus groups and single key informant interviews, was made based on previous positive experiences with this format within the research group and resource limitations [ 53 ]. The interpreter translated between German and Arabic. The interviewer and participants had not previously met. However, the interpreter partially knew potential users. At the beginning of the interviews, the study was explained, and the informed consent was signed. Interviews were audio-recorded and transcribed in German using f4 audio transcription software version 8.3 [ 54 ]. The interviews with potential users included three main interviews and three follow-up interviews, during which additional feedback was gathered about the IBI contents that due to time constraints could not be discussed in the main interviews. Interviews lasted from 60 to 150 min.

The interview materials consisted of a demographic questionnaire and the semi-structured interview. Participants read selected chapters (the first, third, and fifth) of the IBI and were then asked to give feedback on specific content, which was displayed in a PowerPoint presentation (in Arabic and German). This approach was chosen due to time constraints, focusing on the most critical aspects, while chapters like resource activation, already used in similar interventions, were omitted. The interview guide was developed following guidelines by Kallio et al. [ 52 ] and based on background literature, the RECAPT criteria, the results of KIIE1 and the first version of the IBI. Requested feedback focused on the cultural relevance and appropriateness of IBI content, as well as suggestions for adapting less comprehensible, irrelevant, and potentially inappropriate IBI content and appearance (see Additional File 2 ). Two pilot interviews were conducted to assess and refine the initial interview guide.

Incorporating the results from KIIUE2, a beta-version of the app was developed in German and Arabic, which included all texts, vignettes, interactive exercises, audios, videos and illustrations. The beta-version contained two Arabic versions of the text and audio-exercises, one for female and one for male users (due to Arabic verbs being conjugated depending on the gender of the addressed person). KIIUE3 focuses on the evaluation and adaptation of this beta-version of the IBI (see Fig.  2 for a screenshot of the home screen).

Screenshots of the IBI in Arabic and German

The same two groups were recruited as for KIIUE2. Additional inclusion criteria were that participants were required to possess a smartphone with internet access and that they could read and write in either Arabic or German. Participants of both groups were recruited from previous project phases or via the interpreter of the SRC through e-mail and telephone. Those meeting the inclusion criteria received more comprehensive study details and were provided with informed consent for study participation. Interested participants then scheduled interview appointments. Interpreters received compensation at their standard hourly rate of 90 CHF, while other experts did not receive compensation due to limited financial resources. As a compensation for their participation, potential users received a supermarket voucher worth 150 CHF (including travel expenses). The aim was to include at least three experts and six potential users. No potential participants dropped out. In total, n  = 9 key informants, including three experts and six potential users were included. Details on participant characteristics can be found in Additional File 4 .

Data was collected between June and July 2023 in person at the Department of Psychology of the UZH for the experts and at the premises of the SRC in Bern for the potential users. In the interviews with the experts, one interviewer was present, while with the potential users, the interpreter was present like in KIIUE2. In the beginning, study procedures were explained, and the informed consent was signed. Interviews were audio-recorded, partly video-recorded for the think aloud walkthrough (see below) and transcribed in German using f4 audio transcription software version 8.3 [ 54 ]. No follow-up interviews were conducted. The interviews lasted from 120 min to 150 min.

After filling out a demographic questionnaire, the IBI was set up on the participant’s smartphone. Following this, the so-called think aloud walkthrough method was used. During this, insights into users’ cognitive processes were gathered as participants were instructed to vocalize their thoughts and feelings while testing the app [ 55 ]. Participants had 30 min to test the app on their own and 30 min in which they were instructed to test certain selected features. Following this, a semi-structured interview was conducted. The interview guide was developed following guidelines by Kallio et al. [ 52 ] and based on background literature, the RECAPT criteria and the results of the two previous KII rounds. Requested feedback focused on the cultural relevance and appropriateness of the IBI regarding design and illustrations, videos and interactive parts, content and topics, functions, as well as suggestions for adapting less comprehensible, potentially irrelevant, and inappropriate IBI content and appearance (see Additional File 2 ). Two pilot interviews were conducted to assess and refine the initial interview guide.

Data analysis

The KI interviews of all phases were analyzed employing the framework analysis method, a structured and adaptable procedure for examining qualitative data, systematically managing large data sets and analyzing data covering similar topics [ 56 ]. This method produces highly structured outputs of summarized data (framework matrix), with themes emerging through comparisons conducted within and between individual interviews [ 56 ]. In all stages of the cultural adaptation process, the analysis started with a deductive approach based on the RECAPT criteria [ 45 ], as the aim was to produce clear suggestions for adaptations based on the components suggested in RECAPT. During coding, this approach was combined with an inductive approach to include new aspects brought up by the individual KI experiences. Deductive codes were developed in the MAXQDA 2022 software [ 57 ]. Each interview transcript underwent independent parallel coding by two coders, ensuring consistency and increasing the reliability of the analysis [ 58 ]. Coding was followed by subsequent discussions among the coders and a third researcher to achieve consensus on conflicting codes and addressing any uncertainties that arose during the coding process. To efficiently meet the project timeline, we initially performed rapid qualitative analyses (RQA; [ 59 , 60 ]) for KIIUE2 and KIIUE3 to prepare for the decision-making meetings. This pragmatic approach enabled us to quickly evaluate feedback for implementation. Although RQA might sacrifice some scientific rigor compared to full qualitative analysis, it provided timely insights necessary for swift decision-making. Ultimately, we conducted full framework analyses for all three rounds to ensure no critical themes were overlooked.

Decision-making meetings

Two decision-making meetings led by the first author were held each, after KIIUE2 and KIIUE3 respectively, to assess the outcomes of the KI interviews, determine the feasibility of the proposed adaptations and explore subsequent actions. First, the research team members involved in data collection and analysis discussed the feedback received, shared their opinions on potential adaptations, and occasionally offered additional suggestions. Following this, a second meeting was held between the first author and two experienced researchers and psychotherapists in the field to discuss decisions particularly related to interventions and exercises. Please refer to Additional File 1 for information on the background and roles of the research team members. The final decisions were a combination of participants’ input, and considerations related to time and financial resources.

Monitoring and documentation of the adaptation procedure

The RECAPT monitoring sheet was employed to document every adaptation made. As the present project is the first to employ the monitoring sheet for a bottom-up development, several alterations were made. The most notable being the division into two sheets: one for the development of the first version of the IBI after KIIE1 and a second one for the adaptations made to this version following KIIUE2 and KIIUE3. Detailed reasoning for the adaptations made, including supporting literature from the desk review and the specific rationale behind each change, are documented in the appended RECAPT table (Additional File 1 ). Footnote 1

The following section highlights a selected subset of results to maintain clarity and conciseness. If no results are mentioned for a subject from a KII round, it is implied that no particularly noteworthy adaptations were made. The results are structured around the four main components of the RECAPT criteria: (1) Community needs, stigma and context, (2) Cultural concepts of distress, (3) Treatment components, and (4) Treatment delivery.

Community needs, stigma, and context

Various considerations related to community needs, stigma, and context were identified as critical for the adaptation and inclusion in the IBI. These encompass the refugee experience, heterogeneity/diversity, rituals, types of losses, “what matters most”, religion, and stigma.

In KIIE1, several post-migratory stressors were mentioned in relation to the refugee experience. These included being far away from the family and the graves of the deceased due to war, which entailed worry about the family left behind and feelings of guilt towards them ( n  = 9), problems directly related to the asylum situation including financial problems, living in an asylum center, not being able to work or mobility restrictions ( n  = 7), problems with integration like language learning or finding work ( n  = 6), social isolation ( n  = 5) and distrust/data privacy concerns (e.g., mistrust towards healthcare professionals and government institutions; n  = 4). Adaptations were made based on these results by incorporating them into contextually relevant treatment rationales and goals. For example, treatment goals included having more energy to focus on integration and future perspectives. The context was also considered in psychoeducational parts, acknowledging that certain factors can impede the capacity to perform rituals. Additionally, suggestions for behavioral activation, social activities, or rituals were adapted to be accessible and feasible within the constraints of the refugee context. This included options like free activities or opting for phone calls instead of in-person meetings. Further adaptations targeted feelings of guilt, such as not being able to visit graves or not being present when a loved one died. Cognitive restructuring and self-compassion techniques were employed to address these feelings. Finally, there was a strong emphasis on being transparent about data privacy and clearly communicating what the app can and cannot provide.

The heterogeneity/diversity within Syrians was mentioned as an important factor to consider by all ( n  = 9) participants in KIIE1 (e.g., “You could say that Syria is a mosaic country, a patchwork country.”, D3). It was mentioned that the grief and needs of bereaved Syrians for the app were highly individual and influenced by the diversity of religion (e.g., Muslim, Christian, Aramean Marronite, Jewish, Druz), education level, gender, ethnicity (e.g., Arab, Kurdish, Armenian) and type of loss present in the Syrian community. As a consequence, heterogeneity has been addressed in psychoeducation about grief reactions and emphasizing the fact that grief is highly individual. Furthermore, the wording of the app was kept as open as possible meaning that a focus on one subgroup (e.g., in religion) rather than another was avoided, and open formulations were used to provide space for heterogenous needs. Moreover, users have been provided with the option of adding their own entry to list-exercises. To cater to different educational levels, simple language was used (see Sect.  Treatment delivery 3.4). In KIIUE2 and KIIUE3, it was observed that suggestions for adapting rituals and social activities varied, with participants expressing conflicting opinions. These divergent views were seen as a reflection of the target group’s diversity, leading to the decision to include all suggestions to adequately cater to these heterogeneous preferences and perspectives.

In KIIE1, rituals were noted by most participants ( n  = 8), i.e., the most important rituals to Syrians ( n  = 7) and challenges/possibilities to performing rituals in Switzerland ( n  = 5). Important rituals were often connected to religion and included visiting the grave, praying, or speaking about positive memories of the deceased. Regarding rituals in Switzerland, the importance of suggesting to users to find space for grief in their everyday life and providing alternatives to certain rituals was outlined, with suggestions including creating an alternative to a tombstone such as an altar. Adaptations made based on these findings were emphasizing space for grief as a session topic, including exercises that reflect or adapt certain aspects of known grief rituals in the Syrian community (e.g., the “tree of legacy” exercise permitting to reflect on positive memories of the deceased, the “memory wall” exercise providing a sort of digital altar, or “choosing and planning a ritual”).

Furthermore, psychoeducation about rituals was included, and culturally relevant examples of rituals were featured in exercises and psychoeducation. In KIIUE2, the included rituals were considered clear and culturally appropriate by all participants ( n  = 9). However, it was suggested that in the exercise “choosing and planning a ritual”, two additions should be made to the list of suggested rituals: Donating money and doing good deeds in the name of the deceased (e.g., “Really the donation, that here is not mentioned, it‘s actually very well-known. That you donate something for the person, build something, do something, yes.”, U6). Furthermore, the suggestion “Have conversations with the deceased person in a beautiful setting, such as in nature” was criticized ( n  = 4) as this was seen as “crazy” and frightening (“For us, it’s like a mistake. One does not speak with the deceased.”, P1). No adaptations were made to this last suggestion in line with the decision to include all suggestions for rituals without removal, as mentioned in the previous paragraph.

Regarding types of losses, two main themes emerged in KIIE1: ambiguous loss ( n  = 4) and implications of different types of losses ( n  = 5), such as losing the support of the deceased person (e.g., “They feel weaker than before because they received support from someone who is no longer there, such as a father, an older son, a husband, or a wife.”, D1) or losing a role (e.g., being a parent). The implications of different types of losses were included with the topic of secondary losses, which includes several examples in psychoeducation and contains an exercise focused on reflecting and adjusting to secondary losses. Although considered important, the topic of ambiguous loss was not included at this stage of the project due to lack of resources, as it comprises several aspects that require different interventions or different framing of the interventions (e.g., concerning rituals). At a later stage, the app will be adapted for ambiguous loss, thus offering the users to choose either an option for ambiguous loss or loss due to death at start.

Concerning “what matters most”, family ( n  = 10) and work/education ( n  = 7) were mentioned as most important in KIIE1. To increase motivation, both topics were incorporated in different parts of the IBI, for instance in the treatment rationale (see 3.3) or in the rationale for different exercises (e.g., positive impact on social relationships and family when practicing self-compassion). Furthermore, the topics were included in psychoeducational parts, acknowledging for instance the impact of grief on work performance or social connections. See Sect. Cultural concepts of distress for further inclusion of family/social relationships.

Religion emerged as a highly relevant topic in KIIE1 with all ( n  = 10) participants mentioning the importance of religion as a resource in grief. Religion was included as a resource throughout the app (e.g., including prayer as suggestion in various exercises) and including religious counseling services in the “external resources and addresses” chapter. In KIIUE2 ( n  = 5) and KIIUE3 ( n  = 4), increasing the amount of religious content was advised. As a consequence, several Quran and Bible verses were included throughout psychoeducational parts of the app.

Mental health stigma (e.g., fear of speaking about/showing mental health problems, being labeled as crazy) within the Syrian community was mentioned by most participants in KIIE1 ( n  = 8). Although the anonymity of the IBI was seen as a potential solution to this, the importance of addressing stigmatizing beliefs in the app was underlined. Hence, normalizing and validating different grief reactions with psychoeducational texts and testimonials of affected individuals speaking about their experience was a main focus of the app.

Cultural concepts of distress

Several culturally relevant symptoms, metaphors and phrases, as well as cultural explanations emerged as relevant for inclusion or adaptation in the IBI.

As a result of KIIE1, the most commonly mentioned symptoms were emotion-related symptoms such as sadness/depressed mood ( n  = 5) and guilt ( n  = 3); cognitive symptoms including preoccupation ( n  = 3) and denial/being stuck in the past ( n  = 3); behavioral symptoms like withdrawal ( n  = 5); and somatic symptoms such as sleep problems ( n  = 5) and physical pain ( n  = 4). Symptoms were included as examples in psychoeducational parts of the IBI about grief reactions. On the other hand, the most common symptoms partly guided the choice of treatment components (e.g., behavioral activation for depressed mood or cognitive restructuring for preoccupation and guilt). Furthermore, symptoms were included in an exercise, where users select their own symptoms from a list (see Fig.  3 ). In KIIUE2, the included examples of symptoms were considered clear and culturally appropriate by all ( n  = 9) participants, with several suggestions made for additional symptoms to be included (e.g., shock, self-harm, remorse, apathy, forgetting to eat and drink).

Two types of metaphors were identified in KIIE1, one concerning grief and the other grief-related coping. Metaphors for grief can be broadly categorized into body-related metaphors ( n  = 4) related to eyes, heart, pain and heaviness (e.g., “Grief is like a backpack, that we carry with us”; S2); and community-related metaphors ( n  = 3) highlighting how the deceased is a missing link in their community (e.g., “The loss, that is in cultural circles, the family is a center, a navel. And we describe it like this with the navel, and if the navel is open, then the entire relationship with myself and my surroundings, with my family, almost the entire tribe, is not quite in order.”, P2), while metaphors for coping were mostly religious ( n  = 6; e.g., “God gave him as a gift, and God has taken him back, but life goes on.”; D2). Metaphors were included in psychoeducation about grief reactions and about secondary losses. Furthermore, an exercise asking users to describe their own grief reaction as a metaphor was added to promote engagement and self-reflection. Finally, the metaphor of heaviness and grief as a backpack was included in the description of the goal of the IBI and treatment goals. In KIIUE2 all participants ( n  = 9) deemed the included metaphors good and culturally appropriate, while suggestions were made to add a missing metaphor (“broken back”) and slightly adjust the wording of other metaphors for better comprehension.

In KIIE1, cultural explanations for grief and loss mainly related to religion ( n  = 8) and the community ( n  = 3), as well. Religious explanations were more fatalistic, suggesting that loss is divinely ordained and should be accepted as a test from God and in some cases, as a new beginning and an opportunity for growth. Meanwhile, community-based explanations emphasized the significant role of the community as a vital resource, highlighting that communal grieving alleviates the intensity of grief (e.g., “Grieving in our community is actually a collective experience. […] It is said that grief is shared and thus lessened, meaning it becomes lighter.“, D3). Cultural explanations influenced various adaptations throughout the app, such as incorporating religion and community as resources for grieving, emphasizing the importance of strengthening social relationships to alleviate grief as a session topic. Features like the “memory wall” exercise foster communal grieving, while psychoeducational sections address secondary losses and highlight the significance of social connections.

Treatment components

Results concerning treatment components are organized into two sections, one addressing the treatment goal and treatment rationale, and the other detailing the content, i.e. interventions, exercises, and supplementary resources.

Examples of Intervention Components

Note . (1) Vignette; (2) List exercise; (3) Interactive exercise (Resource-Lifeline); (4) Mindfulness audio-exercise

Regarding the treatment goal of the app, findings from KIIE1 indicated that both loss- and restoration- oriented components according to the dual process model of grief [ 61 ] should be included ( n  = 7), with most participants ( n  = 6) favoring moving from loss- to restoration-orientation throughout the app, ending on a focus on the now and future. Regarding loss-oriented components, it was mentioned that speaking about and finding a space for grief ( n  = 4), accepting and integrating the loss ( n  = 6) and continuing bonds ( n  = 9) were important. The latter included the importance of positive memories and rituals to feel close to the deceased ( n  = 7) and adapting the relationship with the deceased in balance with restoration orientation ( n  = 6). Concerning restoration-orientation, the importance of fostering joy ( n  = 4), encouraging future perspectives and becoming active ( n  = 4), focusing on the present and future by distracting oneself and focusing on family/education/work ( n  = 6) were noted.

Concerning the treatment rationale provided to the users, suggestions from KIIE1 emphasized the relevance of the app to break out of the isolation of grief, finding strength for integration and future perspectives, and being there for family ( n  = 2). These findings influenced the choice of chapter topics (see Additional File 5 ) and specific exercises (e.g., tree of legacy or words to the deceased to adapt relationship), as well as the ratio of loss- and restoration-oriented components and the order in which they are presented. The treatment rationale is introduced to the user explaining that the app will deal both with the pain of grief and with giving them more strength and energy to focus on their goals related to family/work/education in the present and future. The first chapter includes an exercise called “goal setting”, which prompts users to set a goal for themselves. The instructions to this exercise contain examples for treatment goals which are in line with the findings related to the treatment rationale (e.g., be there for family, improve concentration for language learning, goals for future). In KIIUE2 the examples received positive feedback from all ( n  = 9) participants and were considered clear and culturally appropriate ( n  = 6). Suggestions were made to add additional goals and to change the order to match the importance of certain goals in Syrian culture (e.g., family first, then future goals, etc.), both of which were implemented.

Topics related to content, which were suggested for inclusion in the app in KIEE1, were additional resources for points of contact outside the app ( n  = 8) and interventions and exercises. The latter included psychoeducation and normalizing ( n  = 7), cognitive restructuring for guilt and dysfunctional cognitions ( n  = 2), resource and behavioral activation, ( n  = 9) as well as mindfulness, relaxation and body-related exercises ( n  = 3). For resource and behavioral activation, multiple culturally appropriate resources and activities were listed (e.g., religion, social activities, physical activity, cooking). Based on these findings, a strong focus was set on psychoeducation and normalizing in the first chapter as a topic, resource and behavioral activation (including culturally relevant examples/suggestions) in the second chapter, and a partial focus on cognitive restructuring in chapter four. Mindfulness, relaxation and body-related exercises were used throughout the app. In KIIUE2 feedback was provided on specific exercises. Positive reactions were expressed towards the following exercises: “Sitting with difficult emotions and breathing exercise” (good exercise, n  = 5), “Tree of legacy” (good and clear exercise, n  = 9), “Pinboard/memory wall” (good and meaningful exercise, n  = 8), “Pick a legacy” (culturally relevant examples of legacies, n  = 9), “Visualizing your future” (meaningful and clear, n  = 7), “Reflecting difficult dates and how to cope with them” (good examples, n  = 7; relevant topic, n  = 6), “Looking back on goals and reflecting what was learnt in app” (good and helpful, n  = 8).

However, several critical reactions were voiced towards three exercises in particular. In response to the exercise “Sitting with difficult emotions and breathing exercise”, it was noted that some emotions should not be allowed ( n  = 2; “We practically destroyed the country because we allowed our feelings”, U5) and that the exercise was not considered helpful against sadness ( n  = 2). Since users expressed that knowing the exercise was conducted in a controlled setting would increase their comfort, the introduction was adjusted to acknowledge their fear of experiencing emotions, clarify the exercise’s context, reassure them that they could stop if uncomfortable, and further explain its proven benefits. The audio-exercise “Imaginary conversation with the deceased” prompted negative reactions from six participants. The idea of having a conversation with a deceased person sparked fear, incomprehension and rejection of the exercise with participants mentioning that this would be seen as “crazy” or as speaking to the devil (e.g., “A conversation is unthinkable. If this should ever happen […] it would simply be a conversation with the devil.”, U5). The exercise was renamed to “Words to the Deceased” to avoid implying a two-way conversation and an introduction was added to clarify its purpose and address religious concerns. Additionally, a disclaimer was included to warn about the emotional challenges, with frequent reminders that users can stop anytime, and the wording was adjusted to refer to an “image” or “memory” of the deceased to ensure user comfort and understanding. Finally, the two variations of the exercise “Visualizing your future” caused confusion. One version, which involved imagining speeches at one’s 80th birthday party, was considered unrealistic and participants suggested changing the age ( n  = 7). The other version, which entailed imagining one’s ideal day in the future and writing about it in a letter to the deceased, was deemed unclear about its future focus, who was writing to whom, and what they were imagining ( n  = 3). To address this, the description was adjusted to specify the time frame and include a clarifying picture. Additionally, introductions were added to explain that one version focuses on the near future and the other on the distant future. This adjustment aimed to help refugees, who may find it difficult to think about the future due to uncertainties, feel less intimidated by using a path/journey metaphor.

In KIIUE3, the overall content and exercises received generally positive feedback, being described as relaxing, simple, helpful, and positive. Self-compassion exercises were rated particularly well ( n  = 6). The “Words to Deceased” exercise elicited both hesitation ( n  = 7) and positive feedback, with some participants finding it fitting and helpful ( n  = 7). However, unclear instructions, especially regarding the aim and purpose of several exercises (“Resource-Lifeline”, “Memory wall” “Select your own grief reactions” “Finding a metaphor for your grief”) combined with technical issues (see 3.4), caused confusion. In reaction to these results, the aim and purpose of the exercises in question were explained in more detail. Furthermore, in the case of the “Resource-Lifeline” and the “Memory wall”, screenshots displaying an exemplary version of how to complete the exercise (with examples from the vignette protagonists) were included to clarify the instructions (see Fig.  3 for screenshot of the Resource-Lifeline). The exercise “Words to the deceased” was not removed or adapted as participants mentioned not being able to accurately judge the exercise without listening to it in full length.

Treatment delivery

Results concerning treatment delivery can be divided into audiovisual content, vignettes, language and technical features/design.

Audiovisual content comprises input on videos, audios, and illustrations. In KIIE1, the inclusion of videos was suggested by seven participants, with specific suggestions for testimonial videos of example cases ( n  = 2). This was implemented in chapter one by including short videos of a Syrian man and woman speaking about their own experience regarding grief symptoms and impact of these symptoms on their life. The feedback in KIIUE3 was positive from all participants, with participants finding the videos touching, impressed by the courage and openness of the individuals, representative of their own experiences, and feeling understood despite the sad content (“I am impressed by how courageously they can simply talk about their grief.”, U4). Despite only one participant suggesting audio-exercises in KIIE1, several audio-exercises recorded in Syrian dialect with a female speaker were included throughout the app due to their proven effectiveness in other studies for enhancing user engagement and providing mindfulness exercises. In KIIUE3, the feedback on audio-exercises was notably positive, with participants praising the pleasant voice of the speaker ( n  = 6) and finding the instructions comprehensible ( n  = 7).

The illustrations employed in the app were partly previously developed for the Sui app in close collaboration with the target group (see description here: [ 46 ]), with several newly developed illustrations created for the present app. To ensure consistency and maintain the visual integrity of the original content, significant alterations to the style or the depiction of characters were not possible, as it was essential to match the established aesthetic of the Sui app. In KIIUE2, the illustrations were highly praised by all participants for being appropriate, explanatory, and accurate. However, some illustrations were deemed unclear, and suggested adaptations were implemented. Overall, in KIIUE3, the illustrations received positive feedback by all participants for being helpful for understanding, including religion, having well-done facial expressions, and featuring nice colors. Nonetheless, some participants raised a critical point about the lack of diversity in religious representation, noting that Syrian society includes various religions and ethnicities, and not all women wear headscarves ( n  = 2) ("It could simply become a problem because Syrian society does not consist only of women with headscarves, it does not represent other religions and ethnicities", U3), and not all men have beards ( n  = 2). To address this feedback, the male vignette character in question was depicted with a mustache instead of a beard. Due to resource limitations, a new female vignette character without a headscarf could not be added, and the existing female character’s headscarf could not be removed entirely to maintain consistency with the Sui app, so she was shown without it only when indoors or with family, as is customary (see Fig.  4 ).

Adaptation of illustrations according to feedback

Note . (1) Depiction of Yasmin with headscarf and Yusef with beard. (2) Adapted version of the illustration after feedback

Vignette stories were introduced throughout the app for consistency with the Sui app, featuring the exemplary narrative of two fictional protagonists, Yasmin and Amir, both Syrian refugees coping with grief (see Fig.  5 ). Amir’s father Yusef passed away due to illness, and now Amir and Yasmin are learning to cope with their grief. Amir lives in Switzerland as a refugee, while Yasmin and their children remain in a refugee camp in Lebanon. These stories aim to incorporate various aspects relevant to the target group (e.g., symptoms, post-migratory living difficulties, religion as a resource), as presented in Sects.  Community needs, stigma, and context and Cultural concepts of distress . They are designed to illustrate how individuals might navigate the app and engage with different exercises (as detailed in Sect.  Treatment components ). The intent is to potentially provide motivation, encouragement, and role models, thereby making the content more engaging and relatable. In KIIUE3, all participants gave overwhelmingly positive feedback on the vignette stories, finding them interesting, motivating, realistic, and well-written, and felt they could identify with the narratives (“The story of Amir and his wife, and how they dealt with things, gave [me] motivation to keep going.”, U3).

Fictional vignette characters Amir and Yasmin

Regarding language, the importance of the app being in Syrian (spoken) dialect ( n  = 4) was mentioned in KIIE1 and different suggestions on the tone and characteristics of the language were made ( n  = 10). The latter included using simple language, with a motivating, benevolent and non-directive tone. These findings resulted in the use of a form of simple Levantine Arabic (see description of adaptation process: [ 46 ]), while aiming to use a non-directive tone (framing exercises as suggestions) and incorporating ample positive feedback for motivation and encouragement (e.g., congratulating users on taking the first step in the app). In KIIUE2, multiple translation errors were identified ( n  = 3) and subsequently corrected. In KIIUE3, the language was found to be clear and comprehensible ( n  = 8).

Although the general design ( n  = 2) and navigation ( n  = 8) of the app were praised in KIIUE3, technical issues and user-friendliness were considered the biggest problem. As this was a beta-version of the app, technical errors (e.g., instruction of exercise displayed in English instead of Arabic, no sound for videos, etc.) were experienced by nearly all participants ( n  = 8). Furthermore, some confusion about the navigation (e.g., skipping an exercise, closing a chapter, etc.) was observed for most participants ( n  = 7). Finally, difficulties in the technical navigation of the “Resource-Lifeline” ( n  = 7) and the “Memory wall” ( n  = 6) exercise in particular arose for a majority of participants. This may partly be because of the instructions being displayed in English. Technical issues were resolved when possible. To assist users struggling with navigation, two measures were implemented. Navigation points were made explicit in the text, such as instructing users to click the “next” button to proceed. Additionally, a “Technical Help” session was created, providing detailed explanations and screenshots of the app’s features. Adaptations made to assist with specific exercises have been detailed in Sect.  Treatment components .

This paper presents results from the bottom-up cultural adaptation of an IBI for bereaved Syrian refugees. The aim of this study was to collect feedback from different stakeholders throughout the iterative adaptation process regarding the dimensions of the RECAPT criteria, thus informing the decisions on the development of the IBI. To this end, three rounds of semi-structured interviews were held with a broad range of key informants, including usability testing with a beta-version in KIIUE3. Results provided valuable feedback regarding (1) Community needs, stigma, and context, (2) Cultural concepts of distress, (3) Treatment components, and (4) Treatment delivery.

Given that a bottom-up approach was employed, the majority of the adaptations were derived from the results of KIIE1. Notably, most decisions for the initial version of the IBI were influenced by components 1) and 2), while results from KIIUE2 predominantly guided adaptations related to component 3). Additionally, findings from KIIUE3 primarily led to adaptations concerning component 4). This underscores the importance of conducting multiple iterative rounds of feedback interviews using various methods (e.g., usability testing for KIIUE3 to detect technical problems) and involving diverse stakeholders as recommended by Heim and colleagues [ 45 ], as different relevant data emerged that would have been otherwise overlooked.

In line with previous findings on Syrian refugees [ 24 , 62 ], mental health stigma, such as the fear of being perceived as “crazy,” was identified as a significant barrier to treatment by many stakeholders. Participants found that the IBI format effectively addressed this barrier by providing anonymity. However, self-stigma, where individuals internalize stigmatizing beliefs [ 63 ], was also highlighted, emphasizing the need for psychoeducation. This aligns with prior research recommending psychoeducation to counteract stigma among Syrian refugees [ 62 , 64 ]. To address self-stigma, the IBI incorporates a strong focus on psychoeducation, normalization, including video testimonials, and vignette stories. Participants particularly appreciated the video testimonials, illustrations, and vignettes, noting they could identify with them. This approach mirrors that of Nickerson and colleagues [ 65 ], who found that integrating videos and case examples in their IBI reduced self-stigma and increased help-seeking behavior. Therefore, it is reasonable to speculate that these components may help reduce stigma in future users of the IBI.

As mentioned, the IBI format was deemed suitable, aligning with previous research indicating high technology use among Syrians [ 43 ]. However, participants in KIIUE3 reported significant technical issues and navigation challenges. While some issues may have arisen from the early prototype stage, they could also reflect the technical literacy challenges noted by Burchert and colleagues [ 43 ]. Despite widespread mobile technology use among Syrian refugees, familiarity often centers on specific applications like communication tools, which underscores the importance of intuitive interfaces for accessibility and ease of use [ 43 ]. To address these challenges, navigation points were made explicit and a “Technical Help” session with detailed explanations and screenshots of the app’s features was created.

A further barrier identified in this study is concerns about data privacy and mistrust in healthcare providers and government institutions, influenced by the political climate in Syria and experiences as refugees, consistent with previous research [ 66 , 67 , 68 ]. These studies suggest the need for refugees to feel they are in a secure environment. To address this, we aimed for transparency about the capabilities and limitations of the IBI. Interestingly, some participants expressed that certain emotions should not be allowed as they could be potentially dangerous in response to the “Sitting with difficult emotions and breathing exercise”. However, many indicated they would feel more comfortable knowing the exercise was in a controlled and safe setting. This suggests that concerns about emotional expression and data privacy may both stem from mistrust and an increased need for security and transparency.

Regarding the treatment goal of the app, the dual process model of grief [ 61 ] effectively reflected participants’ suggestions and proved valuable in conceptualizing the treatment goals. This model incorporates both loss-oriented and restoration-oriented elements, which were recommended for inclusion. Stroebe and Schut assert that the model’s flexibility makes it widely applicable across various cultural groups, allowing for different emphases on its two components. Interestingly, this study found that the target group placed a stronger emphasis on restoration orientation, specifically focusing on future perspectives and new beginnings. This aligns with previous research on coping strategies among Syrian refugees [ 62 ] and specifically with Arabic-speaking refugees dealing with bereavement [ 69 ]. The strong focus on moving forward and future-oriented thinking may also be linked to religious beliefs, as participants mentioned viewing death as God’s will, which necessitates facing loss with acceptance and patience according to Islamic teachings [ 70 ].

One prominent theme related to future orientation was the focus on family and community, frequently mentioned as what “matters most” in the IBI. This emphasis surfaced in connection with the treatment goals and rationale, such as the importance of being there for family. Including “what matters most” in a culture in interventions is strongly recommended to enhance motivation and reduce mental health stigma [ 45 , 71 ]. Consequently, the treatment goals and rationales in the present IBI were primarily formulated to benefit the community or family rather than the individual alone. Additionally, the importance of family and community emerged in metaphors, cultural explanations, and as a significant resource for coping with bereavement. Grief was described as an experience that profoundly affects the community through secondary losses but is also managed collectively, highlighting the crucial role of social relationships in coping. This observation aligns with previous research on mourning in collectivistic cultures, which underscores the communal nature of grieving in non-Western cultures, including the Syrian community [ 72 ]. In a study on prolonged grief disorder in Arabic-speaking populations, lower perceived social support was linked to greater symptom severity, underscoring the importance of social support in the grieving process [ 73 ]. In this context, the symptom of withdrawal noted in the present study may be particularly problematic for the target group, as it removes a crucial coping mechanism. Social isolation, exacerbated by the refugee experience, further intensifies this issue. Therefore, interventions for bereaved Syrian refugees must prioritize social relationships as a key component.

Similarly, the topic of religion emerged frequently throughout this study, appearing in metaphors, cultural explanations, comments on illustrations, in connection to rituals, and as a vital resource for dealing with bereavement. This aligns with previous research indicating that religion is a major source of support for Arabic-speaking refugees in bereavement [ 69 ]. Although religion is known to aid in coping with bereavement by facilitating meaning-making, it is rarely included in bereavement interventions, despite its relevance for culturally sensitive approaches [ 41 , 74 , 75 ]. To incorporate religious perspectives in this study, religious leaders were recruited as key informants. Efforts were made to include religious elements without focusing on any single religious subgroup.

Many rituals identified as relevant were connected to religion. Wojtkowiak and colleagues [ 76 ] suggest that incorporating rituals into grief therapy can enhance its effectiveness and cultural sensitivity. This is particularly significant for refugee communities, where the inability to perform traditional rituals may intensify grief symptoms [ 69 , 76 , 77 ]. Consequently, the study included various rituals and provided ways to adapt known rituals to the Swiss context or create new ones.

According to Wojtkowiak et al. [ 76 ], rituals in grief interventions can facilitate the expression of emotions and the creation of bonds with the deceased and other mourners, addressing ambivalent or problematic relationships. The topic of continuing bonds, the ongoing inner relationship the bereaved maintain with the deceased [ 78 ], emerged as important in interviews, particularly in connection to rituals and the exercise “Words to the Deceased”. Continuing bonds can involve behaviors such as telling stories about the deceased, looking at old photos, viewing the deceased as a role model, dreaming about the deceased, or engaging in direct communication with the deceased [ 79 ]. However, the idea of speaking with the deceased caused strong reactions, including fear and rejection, among participants. Cultural and religious beliefs significantly shape continuing bonds [ 70 ]. In this study, participants indicated that speaking to the deceased and them responding was viewed as speaking to the devil, whereas seeing and speaking to the deceased in dreams was considered normal. This aligns with literature on continuing bonds in Islam, which explains that the dead can hear but cannot reply, and dreaming about the deceased is common [ 70 , 80 ]. It is crucial to be mindful of such differences when applying common grief intervention techniques based on continuing bonds, such as imaginal dialogues, to diverse cultural groups. The present IBI aimed to reframe the exercise to clarify its purpose and allow users to complete it in a way that felt comfortable for them.

Finally, the diversity of the Syrian population in terms of religion, age, education levels, and other factors was frequently highlighted as a crucial consideration for addressing the needs of the target group in the IBI. While it is challenging to accommodate such varied needs without becoming impractical or overly resource-intensive, it remains a pertinent consideration. For instance, Heim and colleagues [ 53 ] found that insufficient attention to diversity within a cultural group, particularly age differences, contributed to the challenges in their RCT with an IBI for Albanian immigrants in Switzerland. To address these diverse needs, the present study aimed to recruit a heterogeneous stakeholder group and to incorporate a wide range of options and perspectives into the IBI. However, future evaluations are necessary to determine the success of this approach.

This study has several limitations that should be acknowledged. Firstly, we were unable to present the entire content of the IBI in KIIUE2 and KIIUE3 due to resource constraints. Consequently, participant feedback is limited to the parts of the intervention they experienced and may be biased by the research team’s selection. In a future pilot Randomized Controlled Trial (RCT), participants will have the opportunity to test the entire app, which will allow for more comprehensive feedback. Additionally, although our sample size was small, it is consistent with qualitative research norms. According to Hennink and Kaiser [ 49 ], data saturation is typically reached between nine and 17 interviews, supporting the adequacy of our sample. We conducted three rounds of interviews, with a large part of participants being unique in each round, which ensured a range of perspectives. Despite the small sample size, we believe sufficient data saturation was achieved, though generalizability may still be limited. Moreover, despite efforts to recruit participants from diverse cultural and religious backgrounds, the sample may not fully capture the extensive cultural, ethnic, and religious diversity present in Syria. As a result, while participants generally found the discussed elements—such as the rituals—to be clear and culturally appropriate, these perspectives may not reflect the experiences of all cultural or religious groups. This limitation affects the generalizability of the findings across Syria’s diverse population. Another limitation is the necessity of translation, which may have disrupted the natural flow of conversation and the spontaneity of participant responses. The need for translation inevitably resulted in some cultural nuances and idiomatic expressions being lost, posing a risk of information loss. Ideally, the research would be conducted entirely in the participants’ mother tongue to fully capture the depth of their responses [ 81 ]. Additionally, the recruitment of potential users through the interpreter, who knew them beforehand, may have introduced social desirability bias, as participants might have modified their responses to be viewed more favorably. Nonetheless, the interpreter, being a member of the target group, helped foster trust and had a deeper understanding of community challenges, which in turn ensured more cultural sensitivity. Furthermore, potential power imbalances between researchers and participants could also have influenced the responses, which is acknowledged as a limitation in the interpretation of the findings.

The present study offers several implications for both research and clinical practice. By reporting on the development of the first culturally adapted IBI for grief, it adds to the scarce body of research investigating grief in non-WEIRD populations [ 41 ]. Few studies in cultural adaptation research have transparently reported the adaptations made and the decisions leading to them, ensuring their replicability [ 64 , 82 ]. This study adds to the body of sufficiently documented cultural adaptation processes, which are needed to improve the overall quality of evidence regarding the cultural adaptation of psychological interventions [ 45 ]. Notably, this study is the first to apply the RECAPT framework using a bottom-up approach, potentially serving as a model for future projects employing the same approach. However, it is important to recognize that when culturally adapting an intervention bottom-up, it is not possible to determine if certain adaptations are unique to the specific culture (i.e., cultural adaptations) or if they are general factors for grief support applicable to other cultural groups. This underscores the need for future research to evaluate whether the feedback genuinely reflects cultural specificity and whether the adaptations would be applicable to other contexts. Additionally, by thoroughly and transparently documenting the adaptation process, this study may provide valuable information that can be leveraged by future researchers, whether they are targeting similar groups or focusing on bereaved individuals, thus reducing the need to start from scratch. Apart from providing insights for future research developing culturally sensitive interventions for similar target groups, it may also offer useful perspectives to clinical practitioners when working with bereaved Syrian refugees. In light of the substantial treatment gap for refugees, the findings from this study have contributed to the development of the culturally adapted IBI, which may offer crucial support to bereaved Syrians in need. Given its scalability, the app is well-suited for cultural adaptation to other refugee groups or contexts, potentially addressing similar support gaps. This would be an interesting avenue for future research. Additionally, future studies are necessary to evaluate the acceptability, feasibility, and effectiveness of the culturally adapted IBI.

Data availability

The datasets generated and analyzed in this study contain sensitive clinical information that could potentially identify participants and are therefore not publicly available. However, the framework matrices with summarized data, which support the study’s findings, can be obtained from the corresponding author upon reasonable request.

For brevity, only the part of the table related to Chap. 1 is included in Additional File 1 . The full documentation can be requested from the first author.

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Acknowledgements

We express our gratitude to Nicola Buser for his diligent data collection and analysis for KIIE1. We extend our thanks to Hannah Kuhn, Virginia Damm, and Mina Motadel for their meticulous transcription of the interviews. We also appreciate the significant contributions of Mina Motadel and Sandra Riad in the decision-making meetings and the implementation of adaptations to the IBI. We are indebted to Sebastian Burchert, Jessica Wabiszczewicz, and Michel Hosmann for their invaluable support and patience in guiding our technological decisions. Our thanks also go to Pixelfarm for creating the beautiful illustrations for the IBI. We are grateful to Costa Zbinden for his expert advice, the use of his recording studio, and for processing the audio exercises. Furthermore, we acknowledge Hadil Shurbahj and Vera Mosimann for lending their voices to the audio exercises in the IBI. Special thanks to Joelle Schenkel for her significant contribution in preparing the additional material for this paper.

The first author is funded by a doctoral scholarship from the Digital Society Initiative (DSI) of the University of Zurich. The overall project was funded by the Humanitarian Foundation of the SRC.

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Contributions

AA, EH, and CK conceived the study. AA designed the work. AA, AH, VT, and FH acquired the data, with analysis by AA, AH, and VT. Data interpretation was performed by AA, EH, AH, VT, CK, FH, RS, and MA. AA, AH, and VT drafted the manuscript, which was substantively revised by AA, EH, CK, FH, RS, MA, and AM. All authors read and approved the final manuscript.

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Correspondence to Anaïs Aeschlimann .

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The ethics proposals for KIIE1 and KIIUE2/KIIUE3 were accepted by the ethics committee of the Faculty of Arts and Social Sciences at the University of Zurich.

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Not applicable to the present study as the human faces used are animation/cartoon.

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The authors declare no competing interests.

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During the preparation of this work the author(s) used ChatGPT in order to improve the grammar and avoid spelling mistakes. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the publication.

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Additional File 1: RECAPT criteria

Additional file 2: semi-structured interview guides: kiie1, kiieu2 and kiieu3, additional file 3: coreq checklist, additional file 4: participant characteristics, additional file 5: description of the app outline and content, rights and permissions.

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Aeschlimann, A., Heim, E., Hoxha, A. et al. Cultural adaptation of an internet-based self-help app for grieving Syrian refugees in Switzerland. BMC Public Health 24 , 3048 (2024). https://doi.org/10.1186/s12889-024-20507-8

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Received : 25 July 2024

Accepted : 24 October 2024

Published : 05 November 2024

DOI : https://doi.org/10.1186/s12889-024-20507-8

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