what is qualitative research advantages and disadvantages

23 Advantages and Disadvantages of Qualitative Research

Investigating methodologies. Taking a closer look at ethnographic, anthropological, or naturalistic techniques. Data mining through observer recordings. This is what the world of qualitative research is all about. It is the comprehensive and complete data that is collected by having the courage to ask an open-ended question.

Print media has used the principles of qualitative research for generations. Now more industries are seeing the advantages that come from the extra data that is received by asking more than a “yes” or “no” question.

The advantages and disadvantages of qualitative research are quite unique. On one hand, you have the perspective of the data that is being collected. On the other hand, you have the techniques of the data collector and their own unique observations that can alter the information in subtle ways.

That’s why these key points are so important to consider.

What Are the Advantages of Qualitative Research?

1. Subject materials can be evaluated with greater detail. There are many time restrictions that are placed on research methods. The goal of a time restriction is to create a measurable outcome so that metrics can be in place. Qualitative research focuses less on the metrics of the data that is being collected and more on the subtleties of what can be found in that information. This allows for the data to have an enhanced level of detail to it, which can provide more opportunities to glean insights from it during examination.

2. Research frameworks can be fluid and based on incoming or available data. Many research opportunities must follow a specific pattern of questioning, data collection, and information reporting. Qualitative research offers a different approach. It can adapt to the quality of information that is being gathered. If the available data does not seem to be providing any results, the research can immediately shift gears and seek to gather data in a new direction. This offers more opportunities to gather important clues about any subject instead of being confined to a limited and often self-fulfilling perspective.

3. Qualitative research data is based on human experiences and observations. Humans have two very different operating systems. One is a subconscious method of operation, which is the fast and instinctual observations that are made when data is present. The other operating system is slower and more methodical, wanting to evaluate all sources of data before deciding. Many forms of research rely on the second operating system while ignoring the instinctual nature of the human mind. Qualitative research doesn’t ignore the gut instinct. It embraces it and the data that can be collected is often better for it.

4. Gathered data has a predictive quality to it. One of the common mistakes that occurs with qualitative research is an assumption that a personal perspective can be extrapolated into a group perspective. This is only possible when individuals grow up in similar circumstances, have similar perspectives about the world, and operate with similar goals. When these groups can be identified, however, the gathered individualistic data can have a predictive quality for those who are in a like-minded group. At the very least, the data has a predictive quality for the individual from whom it was gathered.

5. Qualitative research operates within structures that are fluid. Because the data being gathered through this type of research is based on observations and experiences, an experienced researcher can follow-up interesting answers with additional questions. Unlike other forms of research that require a specific framework with zero deviation, researchers can follow any data tangent which makes itself known and enhance the overall database of information that is being collected.

6. Data complexities can be incorporated into generated conclusions. Although our modern world tends to prefer statistics and verifiable facts, we cannot simply remove the human experience from the equation. Different people will have remarkably different perceptions about any statistic, fact, or event. This is because our unique experiences generate a different perspective of the data that we see. These complexities, when gathered into a singular database, can generate conclusions with more depth and accuracy, which benefits everyone.

7. Qualitative research is an open-ended process. When a researcher is properly prepared, the open-ended structures of qualitative research make it possible to get underneath superficial responses and rational thoughts to gather information from an individual’s emotional response. This is critically important to this form of researcher because it is an emotional response which often drives a person’s decisions or influences their behavior.

8. Creativity becomes a desirable quality within qualitative research. It can be difficult to analyze data that is obtained from individual sources because many people subconsciously answer in a way that they think someone wants. This desire to “please” another reduces the accuracy of the data and suppresses individual creativity. By embracing the qualitative research method, it becomes possible to encourage respondent creativity, allowing people to express themselves with authenticity. In return, the data collected becomes more accurate and can lead to predictable outcomes.

9. Qualitative research can create industry-specific insights. Brands and businesses today need to build relationships with their core demographics to survive. The terminology, vocabulary, and jargon that consumers use when looking at products or services is just as important as the reputation of the brand that is offering them. If consumers are receiving one context, but the intention of the brand is a different context, then the miscommunication can artificially restrict sales opportunities. Qualitative research gives brands access to these insights so they can accurately communicate their value propositions.

10. Smaller sample sizes are used in qualitative research, which can save on costs. Many qualitative research projects can be completed quickly and on a limited budget because they typically use smaller sample sizes that other research methods. This allows for faster results to be obtained so that projects can move forward with confidence that only good data is able to provide.

11. Qualitative research provides more content for creatives and marketing teams. When your job involves marketing, or creating new campaigns that target a specific demographic, then knowing what makes those people can be quite challenging. By going through the qualitative research approach, it becomes possible to congregate authentic ideas that can be used for marketing and other creative purposes. This makes communication between the two parties to be handled with more accuracy, leading to greater level of happiness for all parties involved.

12. Attitude explanations become possible with qualitative research. Consumer patterns can change on a dime sometimes, leaving a brand out in the cold as to what just happened. Qualitative research allows for a greater understanding of consumer attitudes, providing an explanation for events that occur outside of the predictive matrix that was developed through previous research. This allows the optimal brand/consumer relationship to be maintained.

What Are the Disadvantages of Qualitative Research?

1. The quality of the data gathered in qualitative research is highly subjective. This is where the personal nature of data gathering in qualitative research can also be a negative component of the process. What one researcher might feel is important and necessary to gather can be data that another researcher feels is pointless and won’t spend time pursuing it. Having individual perspectives and including instinctual decisions can lead to incredibly detailed data. It can also lead to data that is generalized or even inaccurate because of its reliance on researcher subjectivisms.

2. Data rigidity is more difficult to assess and demonstrate. Because individual perspectives are often the foundation of the data that is gathered in qualitative research, it is more difficult to prove that there is rigidity in the information that is collective. The human mind tends to remember things in the way it wants to remember them. That is why memories are often looked at fondly, even if the actual events that occurred may have been somewhat disturbing at the time. This innate desire to look at the good in things makes it difficult for researchers to demonstrate data validity.

3. Mining data gathered by qualitative research can be time consuming. The number of details that are often collected while performing qualitative research are often overwhelming. Sorting through that data to pull out the key points can be a time-consuming effort. It is also a subjective effort because what one researcher feels is important may not be pulled out by another researcher. Unless there are some standards in place that cannot be overridden, data mining through a massive number of details can almost be more trouble than it is worth in some instances.

4. Qualitative research creates findings that are valuable, but difficult to present. Presenting the findings which come out of qualitative research is a bit like listening to an interview on CNN. The interviewer will ask a question to the interviewee, but the goal is to receive an answer that will help present a database which presents a specific outcome to the viewer. The goal might be to have a viewer watch an interview and think, “That’s terrible. We need to pass a law to change that.” The subjective nature of the information, however, can cause the viewer to think, “That’s wonderful. Let’s keep things the way they are right now.” That is why findings from qualitative research are difficult to present. What a research gleans from the data can be very different from what an outside observer gleans from the data.

5. Data created through qualitative research is not always accepted. Because of the subjective nature of the data that is collected in qualitative research, findings are not always accepted by the scientific community. A second independent qualitative research effort which can produce similar findings is often necessary to begin the process of community acceptance.

6. Researcher influence can have a negative effect on the collected data. The quality of the data that is collected through qualitative research is highly dependent on the skills and observation of the researcher. If a researcher has a biased point of view, then their perspective will be included with the data collected and influence the outcome. There must be controls in place to help remove the potential for bias so the data collected can be reviewed with integrity. Otherwise, it would be possible for a researcher to make any claim and then use their bias through qualitative research to prove their point.

7. Replicating results can be very difficult with qualitative research. The scientific community wants to see results that can be verified and duplicated to accept research as factual. In the world of qualitative research, this can be very difficult to accomplish. Not only do you have the variability of researcher bias for which to account within the data, but there is also the informational bias that is built into the data itself from the provider. This means the scope of data gathering can be extremely limited, even if the structure of gathering information is fluid, because of each unique perspective.

8. Difficult decisions may require repetitive qualitative research periods. The smaller sample sizes of qualitative research may be an advantage, but they can also be a disadvantage for brands and businesses which are facing a difficult or potentially controversial decision. A small sample is not always representative of a larger population demographic, even if there are deep similarities with the individuals involve. This means a follow-up with a larger quantitative sample may be necessary so that data points can be tracked with more accuracy, allowing for a better overall decision to be made.

9. Unseen data can disappear during the qualitative research process. The amount of trust that is placed on the researcher to gather, and then draw together, the unseen data that is offered by a provider is enormous. The research is dependent upon the skill of the researcher being able to connect all the dots. If the researcher can do this, then the data can be meaningful and help brands and progress forward with their mission. If not, there is no way to alter course until after the first results are received. Then a new qualitative process must begin.

10. Researchers must have industry-related expertise. You can have an excellent researcher on-board for a project, but if they are not familiar with the subject matter, they will have a difficult time gathering accurate data. For qualitative research to be accurate, the interviewer involved must have specific skills, experiences, and expertise in the subject matter being studied. They must also be familiar with the material being evaluated and have the knowledge to interpret responses that are received. If any piece of this skill set is missing, the quality of the data being gathered can be open to interpretation.

11. Qualitative research is not statistically representative. The one disadvantage of qualitative research which is always present is its lack of statistical representation. It is a perspective-based method of research only, which means the responses given are not measured. Comparisons can be made and this can lead toward the duplication which may be required, but for the most part, quantitative data is required for circumstances which need statistical representation and that is not part of the qualitative research process.

The advantages and disadvantages of qualitative research make it possible to gather and analyze individualistic data on deeper levels. This makes it possible to gain new insights into consumer thoughts, demographic behavioral patterns, and emotional reasoning processes. When a research can connect the dots of each information point that is gathered, the information can lead to personalized experiences, better value in products and services, and ongoing brand development.

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10 Advantages and Disadvantages of Qualitative Research

  — August 5th, 2021

Research is about gathering data so that it can inform meaningful decisions. In the workplace, this can be invaluable in allowing informed decision-making that will meet with wider strategic organizational goals.

However, research comes in a variety of guises and, depending on the methodologies applied, can achieve different ends. There are broadly two key approaches to research -- qualitative and quantitative.

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Qualitative v quantitative – what’s the difference.

Qualitative Research is at the touchy-feely end of the spectrum. It’s not so much about bean-counting and much more about capturing people’s opinions and emotions.

“Research following a qualitative approach is exploratory and seeks to explain ‘how’ and ‘why’ a particular phenomenon, or behavior, operates as it does in a particular context.” (simplypsychology.org)

Examples of the way qualitative research is often gathered includes:

Interviews are a conversation based inquiry where questions are used to obtain information from participants. Interviews are typically structured to meet the researcher’s objectives.

Focus Groups

Focus group discussions are a common qualitative research strategy . In a focus group discussion, the interviewer talks to a group of people about their thoughts, opinions, beliefs, and attitudes towards a topic. Participants are typically a group who are similar in some way, such as income, education, or career. In the context of a company, the group dynamic is likely their common experience of the workplace.

Observation

Observation is a systematic research method in which researchers look at the activity of their subjects in their typical environment. Observation gives direct information about your research. Using observation can capture information that participants may not think to reveal or see as important during interviews/focus groups.

Existing Documents

This is also called secondary data. A qualitative data collection method entails extracting relevant data from existing documents. This data can then be analyzed using a qualitative data analysis method called content analysis. Existing documents might be work documents, work email , or any other material relevant to the organization.

Quantitative Research is the ‘bean-counting’ bit of the research spectrum. This isn’t to demean its value. Now encompassed by the term ‘ People Analytics ’, it plays an equally important role as a tool for business decision-making.

Organizations can use a variety of quantitative data-gathering methods to track productivity. In turn, this can help:

• To rank employees and work units
• To award raises or promotions.
• To measure and justify termination or disciplining of staff
• To measure productivity
• To measure group/individual targets

Examples might include measuring workforce productivity. If Widget Makers Inc., has two production lines and Line A is producing 25% more per day than Line B, capturing this data immediately informs management/HR of potential issues. Is the slower production on Line B due to human factors or is there a production process issue?

Quantitative Research can help capture real-time activities in the workplace and point towards what needs management attention.

The Pros & Cons of the Qualitative approach

By its nature, qualitative research is far more experiential and focused on capturing people’s feelings and views. This undoubtedly has value, but it can also bring many more challenges than simply capturing quantitative data. Here are a few challenges and benefits to consider.

• Qualitative Research can capture changing attitudes within a target group such as consumers of a product or service, or attitudes in the workplace.
• Qualitative approaches to research are not bound by the limitations of quantitative methods. If responses don’t fit the researcher’s expectation that’s equally useful qualitative data to add context and perhaps explain something that numbers alone are unable to reveal .
• Qualitative Research provides a much more flexible approach . If useful insights are not being captured researchers can quickly adapt questions, change the setting or any other variable to improve responses.
• Qualitative data capture allows researchers to be far more speculative about what areas they choose to investigate and how to do so. It allows data capture to be prompted by a researcher’s instinctive or ‘gut feel’ for where good information will be found.

Qualitative research can be more targeted . If you want to compare productivity across an entire organization, all parts, process, and participants need to be accounted for. Qualitative research can be far more concentrated, sampling specific groups and key points in a company to gather meaningful data. This can both speed the process of data capture and keep the costs of data-gathering down.

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• Sample size can be a big issue. If you seek to infer from a sample of, for example, 200 employees, based upon a sample of 5 employees, this raises the question of whether sampling will provide a true reflection of the views of the remaining 97.5% of the company?
• Sample bias - HR departments will have competing agendas. One argument against qualitative methods alone is that HR tasked with finding the views of the workforce may be influenced both consciously or unconsciously, to select a sample that favors an anticipated outcome .
• Self-selection bias may arise where companies ask staff to volunteer their views . Whether in a paper, online survey , or focus group, if an HR department calls for participants there will be the issue of staff putting themselves forward. The argument goes that this group, in self-selecting itself, rather than being a randomly selected snapshot of a department, will inevitably have narrowed its relevance to those that typically are willing to come forward with their views. Quantitative data is gathered whether someone volunteered or not.
• The artificiality of qualitative data capture. The act of bringing together a group is inevitably outside of the typical ‘norms ’ of everyday work life and culture and may influence the participants in unforeseen ways.
• Are the right questions being posed to participants? You can only get answers to questions you think to ask . In qualitative approaches, asking about “how” and “why” can be hugely informative, but if researchers don’t ask, that insight may be missed.

The reality is that any research approach has both pros and cons. The art of effective and meaningful data gathering is thus to be aware of the limitations and strengths of each method.

In the case of Qualitative research, its value is inextricably linked to the number-crunching that is Quantitative data. One is the Ying to the other’s Yang. Each can only provide half of the picture, but together, you get a more complete view of what’s occurring within an organization.

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16 Key Advantages and Disadvantages of Qualitative Research Methods

Qualitative research is the process of natural inquisitiveness which wants to find an in-depth understanding of specific social phenomena within a regular setting. It is a process that seeks to find out why people act the way that they do in specific situations. By relying on the direct experiences that each person has every day, it becomes possible to define the meaning of a choice – or even a life.

Researchers who use the qualitative process are looking at multiple methods of inquiry to review human-related activities. This process is a way to measure the very existence of humanity. Multiple options are available to complete the work, including discourse analysis, biographies, case studies, and various other theories.

This process results in three primary areas of focus, which are individual actions, overall communication, and cultural influence. Each option must make the common assumption that knowledge is subjective instead of objective, which means the researchers must learn from their participants to understand what is valuable and what is not in their studies.

List of the Pros of Qualitative Research

1. Qualitative research is a very affordable method of research. Qualitative research is one of the most affordable ways to glean information from individuals who are being studied. Focus groups tend to be the primary method of collecting information using this process because it is fast and effective. Although there are research studies that require an extensive period of observation to produce results, using a group interview session can produce usable information in under an hour. That means you can proceed faster with the ideas you wish to pursue when compared to other research methods.

2. Qualitative research provides a predictive element. The data which researchers gather when using the qualitative research process provides a predictive element to the project. This advantage occurs even though the experiences or perspectives of the individuals participating in the research can vary substantially from person-to-person. The goal of this work is not to apply the information to the general public, but to understand how specific demographics react in situations where there are challenges to face. It is a process which allows for product development to occur because the pain points of the population have been identified.

3. Qualitative research focuses on the details of personal choice. The qualitative research process looks at the purpose of the decision that an individual makes as the primary information requiring collection. It does not take a look at the reasons why someone would decide to make the choices that they do in the first place. Other research methods preferred to look at the behavior, but this method wants to know the entire story behind each individual choice so that the entire population or society can benefit from the process.

4. Qualitative research uses fluid operational structures. The qualitative research process relies on data gathering based on situations that researchers are watching and experiencing personally. Instead of relying on a specific framework to collect and preserve information under rigid guidelines, this process finds value in the human experience. This method makes it possible to include the intricacies of the human experience with the structures required to find conclusions that are useful to the demographics involved – and possible to the rest of society as well.

5. Qualitative research uses individual choices as workable data. When we have an understanding of why individual choices occurred, then we can benefit from the diversity that the human experience provides. Each unique perspective makes it possible for every other person to gather more knowledge about a situation because there are differences to examine. It is a process which allows us to discover more potential outcomes because there is more information present from a variety of sources. Researchers can then take the perspectives to create guidelines that others can follow if they find themselves stuck in a similar situation.

6. Qualitative research is an open-ended process. One of the most significant advantages of qualitative research is that it does not rely on specific deadlines, formats, or questions to create a successful outcome. This process allows researchers to ask open-ended questions whenever they feel it is appropriate because there may be more data to collect. There are not the same time elements involved in this process either, as qualitative research can continue indefinitely until those working on the project feel like there is nothing more to glean from the individuals participating.

Because of this unique structure, researchers can look for data points that other methods might overlook because a greater emphasis is often placed on the interview or observational process with firm deadlines.

7. Qualitative research works to remove bias from its collected information. Unconscious bias is a significant factor in every research project because it relies on the ability of the individuals involved to control their thoughts, emotions, and reactions. Everyone has preconceived notions and stereotypes about specific demographics and nationalities which can influence the data collected. No one is 100% immune to this process. The format of qualitative research allows for these judgments to be set aside because it prefers to look at the specific structures behind each choice of person makes.

This research method also collects information about the events which lead up to a specific decision instead of trying to examine what happens after the fact. That’s why this advantage allows the data to be more accurate compared to the other research methods which are in use.

8. Qualitative research provides specific insight development. The average person tends to make a choice based on comfort, convenience, or both. We also tend to move forward in our circumstances based on what we feel is comfortable to our spiritual, moral, or ethical stances. Every form of communication that we use becomes a potential foundation for researchers to understand the demographics of humanity in better ways. By looking at the problems we face in everyday situations, it becomes possible to discover new insights that can help us to solve do you need problems which can come up. It is a way for researchers to understand the context of what happens in society instead of only looking at the outcomes.

9. Qualitative research requires a smaller sample size. Qualitative research studies wrap up faster that other methods because a smaller sample size is possible for data collection with this method. Participants can answer questions immediately, creating usable and actionable information that can lead to new ideas. This advantage makes it possible to move forward with confidence in future choices because there is added predictability to the results which are possible.

10. Qualitative research provides more useful content. Authenticity is highly demanded in today’s world because there is no better way to understand who we are as an individual, a community, or a society. Qualitative research works hard to understand the core concepts of how each participant defines themselves without the influence of outside perspectives. It wants to see how people structure their lives, and then take that data to help solve whatever problems they might have. Although no research method can provide guaranteed results, there is always some type of actionable information present with this approach.

List of the Cons of Qualitative Research

1. Qualitative research creates subjective information points. The quality of the information collected using the qualitative research process can sometimes be questionable. This approach requires the researchers to connect all of the data points which they gather to find the answers to their questions. That means the results are dependent upon the skills of those involved to read the non-verbal cues of each participate, understand when and where follow-up questions are necessary, and remember to document each response. Because individuals can interpret this data in many different ways, there can sometimes be differences in the conclusion because each researcher has a different take on what they receive.

2. Qualitative research can involve significant levels of repetition. Although the smaller sample sizes found in qualitative research can be an advantage, this structure can also be a problem when researchers are trying to collect a complete data profile for a specific demographic. Multiple interviews and discovery sessions become necessary to discover what the potential consequences of a future choice will be. When you only bring in a handful of people to discuss a situation, then these individuals may not offer a complete representation of the group being studied. Without multiple follow-up sessions with other participants, there is no way to prove the authenticity of the information collected.

3. Qualitative research is difficult to replicate. The only way that research can turn into fact is through a process of replication. Other researchers must be able to come to the similar conclusions after the initial project publishers the results. Because the nature of this work is subjective, finding opportunities to duplicate the results are quite rare. The scope of information which a project collects is often limited, which means there is always some doubt found in the data. That is why you will often see a margin of error percentage associated with research that uses this method. Because it never involves every potential member of a demographic, it will always be incomplete.

4. Qualitative research relies on the knowledge of the researchers. The only reason why opportunities are available in the first place when using qualitative research is because there are researchers involved which have expertise that relates to the subject matter being studied. When interviewers are unfamiliar with industry concepts, then it is much more challenging to identify follow-up opportunities that would be if the individual conducting the session was familiar with the ideas under discussion. There is no way to correctly interpret the data if the perspective of the researcher is skewed by a lack of knowledge.

5. Qualitative research does not offer statistics. The goal of qualitative research is to seek out moments of commonality. That means you will not find statistical data within the results. It looks to find specific areas of concern or pain points that are usable to the organization funding to research in the first place. The amount of data collected using this process can be extreme, but there is no guarantee that it will ever be usable. You do not have the same opportunities to compare information as you would with other research methods.

6. Qualitative research still requires a significant time investment. It is true that there are times when the qualitative research process is significantly faster than other methods. There is also the disadvantage in the fact that the amount of time necessary to collect accurate data can be unpredictable using this option. It may take months, years, or even decades to complete a research project if there is a massive amount of data to review. That means the researchers involve must make a long-term commitment to the process to ensure the results can be as accurate as possible.

These qualitative research pros and cons review how all of us come to the choices that we make each day. When researchers understand why we come to specific conclusions, then it becomes possible to create new goods and services that can make our lives easier. This process then concludes with solutions which can benefit a significant majority of the people, leading to better best practices in the future.

Qualitative vs Quantitative Research Methods & Data Analysis

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.

Learn about our Editorial Process

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.

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What is the difference between quantitative and qualitative?

The main difference between quantitative and qualitative research is the type of data they collect and analyze.

Quantitative research collects numerical data and analyzes it using statistical methods. The aim is to produce objective, empirical data that can be measured and expressed in numerical terms. Quantitative research is often used to test hypotheses, identify patterns, and make predictions.

Qualitative research , on the other hand, collects non-numerical data such as words, images, and sounds. The focus is on exploring subjective experiences, opinions, and attitudes, often through observation and interviews.

Qualitative research aims to produce rich and detailed descriptions of the phenomenon being studied, and to uncover new insights and meanings.

Quantitative data is information about quantities, and therefore numbers, and qualitative data is descriptive, and regards phenomenon which can be observed but not measured, such as language.

What Is Qualitative Research?

Qualitative research is the process of collecting, analyzing, and interpreting non-numerical data, such as language. Qualitative research can be used to understand how an individual subjectively perceives and gives meaning to their social reality.

Qualitative data is non-numerical data, such as text, video, photographs, or audio recordings. This type of data can be collected using diary accounts or in-depth interviews and analyzed using grounded theory or thematic analysis.

Qualitative research is multimethod in focus, involving an interpretive, naturalistic approach to its subject matter. This means that qualitative researchers study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them. Denzin and Lincoln (1994, p. 2)

Interest in qualitative data came about as the result of the dissatisfaction of some psychologists (e.g., Carl Rogers) with the scientific study of psychologists such as behaviorists (e.g., Skinner ).

Since psychologists study people, the traditional approach to science is not seen as an appropriate way of carrying out research since it fails to capture the totality of human experience and the essence of being human.  Exploring participants’ experiences is known as a phenomenological approach (re: Humanism ).

Qualitative research is primarily concerned with meaning, subjectivity, and lived experience. The goal is to understand the quality and texture of people’s experiences, how they make sense of them, and the implications for their lives.

Qualitative research aims to understand the social reality of individuals, groups, and cultures as nearly as possible as participants feel or live it. Thus, people and groups are studied in their natural setting.

Some examples of qualitative research questions are provided, such as what an experience feels like, how people talk about something, how they make sense of an experience, and how events unfold for people.

Research following a qualitative approach is exploratory and seeks to explain ‘how’ and ‘why’ a particular phenomenon, or behavior, operates as it does in a particular context. It can be used to generate hypotheses and theories from the data.

Qualitative Methods

There are different types of qualitative research methods, including diary accounts, in-depth interviews , documents, focus groups , case study research , and ethnography.

The results of qualitative methods provide a deep understanding of how people perceive their social realities and in consequence, how they act within the social world.

The researcher has several methods for collecting empirical materials, ranging from the interview to direct observation, to the analysis of artifacts, documents, and cultural records, to the use of visual materials or personal experience. Denzin and Lincoln (1994, p. 14)

Here are some examples of qualitative data:

Interview transcripts : Verbatim records of what participants said during an interview or focus group. They allow researchers to identify common themes and patterns, and draw conclusions based on the data. Interview transcripts can also be useful in providing direct quotes and examples to support research findings.

Observations : The researcher typically takes detailed notes on what they observe, including any contextual information, nonverbal cues, or other relevant details. The resulting observational data can be analyzed to gain insights into social phenomena, such as human behavior, social interactions, and cultural practices.

Unstructured interviews : generate qualitative data through the use of open questions.  This allows the respondent to talk in some depth, choosing their own words.  This helps the researcher develop a real sense of a person’s understanding of a situation.

Diaries or journals : Written accounts of personal experiences or reflections.

Notice that qualitative data could be much more than just words or text. Photographs, videos, sound recordings, and so on, can be considered qualitative data. Visual data can be used to understand behaviors, environments, and social interactions.

Qualitative Data Analysis

Qualitative research is endlessly creative and interpretive. The researcher does not just leave the field with mountains of empirical data and then easily write up his or her findings.

Qualitative interpretations are constructed, and various techniques can be used to make sense of the data, such as content analysis, grounded theory (Glaser & Strauss, 1967), thematic analysis (Braun & Clarke, 2006), or discourse analysis.

For example, thematic analysis is a qualitative approach that involves identifying implicit or explicit ideas within the data. Themes will often emerge once the data has been coded .

Key Features

• Events can be understood adequately only if they are seen in context. Therefore, a qualitative researcher immerses her/himself in the field, in natural surroundings. The contexts of inquiry are not contrived; they are natural. Nothing is predefined or taken for granted.
• Qualitative researchers want those who are studied to speak for themselves, to provide their perspectives in words and other actions. Therefore, qualitative research is an interactive process in which the persons studied teach the researcher about their lives.
• The qualitative researcher is an integral part of the data; without the active participation of the researcher, no data exists.
• The study’s design evolves during the research and can be adjusted or changed as it progresses. For the qualitative researcher, there is no single reality. It is subjective and exists only in reference to the observer.
• The theory is data-driven and emerges as part of the research process, evolving from the data as they are collected.

Limitations of Qualitative Research

• Because of the time and costs involved, qualitative designs do not generally draw samples from large-scale data sets.
• The problem of adequate validity or reliability is a major criticism. Because of the subjective nature of qualitative data and its origin in single contexts, it is difficult to apply conventional standards of reliability and validity. For example, because of the central role played by the researcher in the generation of data, it is not possible to replicate qualitative studies.
• Also, contexts, situations, events, conditions, and interactions cannot be replicated to any extent, nor can generalizations be made to a wider context than the one studied with confidence.
• The time required for data collection, analysis, and interpretation is lengthy. Analysis of qualitative data is difficult, and expert knowledge of an area is necessary to interpret qualitative data. Great care must be taken when doing so, for example, looking for mental illness symptoms.

Advantages of Qualitative Research

• Because of close researcher involvement, the researcher gains an insider’s view of the field. This allows the researcher to find issues that are often missed (such as subtleties and complexities) by the scientific, more positivistic inquiries.
• Qualitative descriptions can be important in suggesting possible relationships, causes, effects, and dynamic processes.
• Qualitative analysis allows for ambiguities/contradictions in the data, which reflect social reality (Denscombe, 2010).
• Qualitative research uses a descriptive, narrative style; this research might be of particular benefit to the practitioner as she or he could turn to qualitative reports to examine forms of knowledge that might otherwise be unavailable, thereby gaining new insight.

What Is Quantitative Research?

Quantitative research involves the process of objectively collecting and analyzing numerical data to describe, predict, or control variables of interest.

The goals of quantitative research are to test causal relationships between variables , make predictions, and generalize results to wider populations.

Quantitative researchers aim to establish general laws of behavior and phenomenon across different settings/contexts. Research is used to test a theory and ultimately support or reject it.

Quantitative Methods

Experiments typically yield quantitative data, as they are concerned with measuring things.  However, other research methods, such as controlled observations and questionnaires , can produce both quantitative information.

For example, a rating scale or closed questions on a questionnaire would generate quantitative data as these produce either numerical data or data that can be put into categories (e.g., “yes,” “no” answers).

Experimental methods limit how research participants react to and express appropriate social behavior.

Findings are, therefore, likely to be context-bound and simply a reflection of the assumptions that the researcher brings to the investigation.

There are numerous examples of quantitative data in psychological research, including mental health. Here are a few examples:

Another example is the Experience in Close Relationships Scale (ECR), a self-report questionnaire widely used to assess adult attachment styles .

The ECR provides quantitative data that can be used to assess attachment styles and predict relationship outcomes.

Neuroimaging data : Neuroimaging techniques, such as MRI and fMRI, provide quantitative data on brain structure and function.

This data can be analyzed to identify brain regions involved in specific mental processes or disorders.

For example, the Beck Depression Inventory (BDI) is a clinician-administered questionnaire widely used to assess the severity of depressive symptoms in individuals.

The BDI consists of 21 questions, each scored on a scale of 0 to 3, with higher scores indicating more severe depressive symptoms. 

Quantitative Data Analysis

Statistics help us turn quantitative data into useful information to help with decision-making. We can use statistics to summarize our data, describing patterns, relationships, and connections. Statistics can be descriptive or inferential.

Descriptive statistics help us to summarize our data. In contrast, inferential statistics are used to identify statistically significant differences between groups of data (such as intervention and control groups in a randomized control study).

• Quantitative researchers try to control extraneous variables by conducting their studies in the lab.
• The research aims for objectivity (i.e., without bias) and is separated from the data.
• The design of the study is determined before it begins.
• For the quantitative researcher, the reality is objective, exists separately from the researcher, and can be seen by anyone.
• Research is used to test a theory and ultimately support or reject it.

Limitations of Quantitative Research

• Context: Quantitative experiments do not take place in natural settings. In addition, they do not allow participants to explain their choices or the meaning of the questions they may have for those participants (Carr, 1994).
• Researcher expertise: Poor knowledge of the application of statistical analysis may negatively affect analysis and subsequent interpretation (Black, 1999).
• Variability of data quantity: Large sample sizes are needed for more accurate analysis. Small-scale quantitative studies may be less reliable because of the low quantity of data (Denscombe, 2010). This also affects the ability to generalize study findings to wider populations.
• Confirmation bias: The researcher might miss observing phenomena because of focus on theory or hypothesis testing rather than on the theory of hypothesis generation.

Advantages of Quantitative Research

• Scientific objectivity: Quantitative data can be interpreted with statistical analysis, and since statistics are based on the principles of mathematics, the quantitative approach is viewed as scientifically objective and rational (Carr, 1994; Denscombe, 2010).
• Useful for testing and validating already constructed theories.
• Rapid analysis: Sophisticated software removes much of the need for prolonged data analysis, especially with large volumes of data involved (Antonius, 2003).
• Replication: Quantitative data is based on measured values and can be checked by others because numerical data is less open to ambiguities of interpretation.
• Hypotheses can also be tested because of statistical analysis (Antonius, 2003).

Antonius, R. (2003). Interpreting quantitative data with SPSS . Sage.

Black, T. R. (1999). Doing quantitative research in the social sciences: An integrated approach to research design, measurement and statistics . Sage.

Braun, V. & Clarke, V. (2006). Using thematic analysis in psychology . Qualitative Research in Psychology , 3, 77–101.

Carr, L. T. (1994). The strengths and weaknesses of quantitative and qualitative research : what method for nursing? Journal of advanced nursing, 20(4) , 716-721.

Denscombe, M. (2010). The Good Research Guide: for small-scale social research. McGraw Hill.

Denzin, N., & Lincoln. Y. (1994). Handbook of Qualitative Research. Thousand Oaks, CA, US: Sage Publications Inc.

Glaser, B. G., Strauss, A. L., & Strutzel, E. (1968). The discovery of grounded theory; strategies for qualitative research. Nursing research, 17(4) , 364.

Minichiello, V. (1990). In-Depth Interviewing: Researching People. Longman Cheshire.

Punch, K. (1998). Introduction to Social Research: Quantitative and Qualitative Approaches. London: Sage

Further Information

• Designing qualitative research
• Methods of data collection and analysis
• Introduction to quantitative and qualitative research
• Checklists for improving rigour in qualitative research: a case of the tail wagging the dog?
• Qualitative research in health care: Analysing qualitative data
• Qualitative data analysis: the framework approach
• Using the framework method for the analysis of
• Qualitative data in multi-disciplinary health research
• Content Analysis
• Grounded Theory
• Thematic Analysis

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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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Pritha Bhandari

19 Advantages and Disadvantages of Qualitative Research

Qualitative research is a method that involves collecting and analyzing non-numerical data to understand social phenomena.

This approach allows researchers to explore and gain in-depth insights into complex issues that cannot be easily measured or quantified.

However, like any research method, there are both advantages and disadvantages associated with qualitative research.

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Advantages of Qualitative Research

• Rich and In-Depth Data : Qualitative research provides rich and detailed data, allowing researchers to explore complex social phenomena, experiences, and contexts in depth.
• Contextual Understanding : It emphasizes the importance of context, enabling researchers to understand the social, cultural, and environmental factors that influence behavior and perceptions.
• Flexibility : Qualitative research is flexible and adaptable, allowing researchers to change their research focus, questions, or methods based on emerging insights during the study.
• Exploratory Nature : It is well-suited for generating hypotheses and theories by exploring new or under-researched topics. Researchers can uncover unexpected findings.
• Participant Perspectives : Qualitative research prioritizes the voices and perspectives of participants, providing insight into their lived experiences, beliefs, and worldviews.
• Holistic Understanding : Researchers can capture the complexity of human behavior and experiences, including emotions, motivations, and interpersonal dynamics.
• Useful for Small Sample Sizes : Qualitative research can be effective with small sample sizes when a deep understanding of a specific group or context is required.
• Complementary to Quantitative Research : It can complement quantitative research by providing qualitative insights that help explain or interpret numerical data.
• Validity and Authenticity : Qualitative research often focuses on establishing the validity and authenticity of findings, emphasizing the importance of rigor and transparency in the research process.

Disadvantages of Qualitative Research

• Subjectivity : Qualitative research is subjective in nature, and findings can be influenced by the researcher's biases, interpretations, and values.
• Limited Generalizability : The small sample sizes and context-specific nature of qualitative research may limit the generalizability of findings to broader populations or contexts.
• Time-Consuming : Qualitative research can be time-consuming, as it involves data collection methods such as interviews, participant observation, and content analysis, which require significant time and effort.
• Data Analysis Complexity : Analyzing qualitative data can be complex, requiring skills in coding, thematic analysis, and interpretation. It can be challenging to ensure intercoder reliability.
• Resource-Intensive : Qualitative research may require more resources than quantitative research, particularly when conducting in-depth interviews or ethnographic fieldwork.
• Ethical Considerations : Researchers must navigate ethical considerations, such as informed consent, confidentiality, and ensuring the well-being of participants, which can be complex in qualitative studies.
• Interpretation Challenges : Qualitative research findings are open to interpretation, and different researchers may draw different conclusions from the same data.
• Limited Quantification : Qualitative research does not produce numerical data, which can make it challenging to quantify and compare findings across studies.
• Potential for Researcher Influence : Researchers may inadvertently influence participant responses or behaviors through their presence or questioning, leading to potential bias.
• Difficulty in Sampling : Choosing a representative sample can be challenging in qualitative research, as the emphasis is on depth rather than breadth.

In practice, the choice between qualitative and quantitative research methods depends on the research objectives, questions, and the nature of the phenomenon being studied. 

Often, researchers use mixed methods, combining both qualitative and quantitative approaches, to gain a more comprehensive understanding of a research topic.

Conclusion of Pros and Cons of Qualitative Research Method

In conclusion, qualitative research offers several advantages, such as capturing rich, detailed data, providing flexibility in data collection methods, and allowing for exploratory studiesfrom market research, focus group, interviews with follow-up questions and open-ended questions by the interviewer.

However, it also has limitations, including small sample sizes, subjective data analysis, resource-intensiveness, and challenges in establishing validity and reliability, as in contrast from quantitative methods with quantitative data. 

Therefore, researchers should consider both the strengths and weaknesses of qualitative research and advantages and disadvantages of quantitative research approach when selecting the appropriate type of research methodology for their study. 

By understanding these advantages and disadvantages, researchers can make informed decisions and maximize the potential of qualitative research in generating meaningful insights.

Read more here on how to write a Master Thesis .

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What is Qualitative in Qualitative Research

Patrik aspers.

1 Department of Sociology, Uppsala University, Uppsala, Sweden

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

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

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

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

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

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

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

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

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

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

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

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

Towards a Definition of Qualitative Research

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Analysis – What is Qualitative Research?

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

Qualitative and Quantitative

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

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

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

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

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

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

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

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

Qualitative Research

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

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

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

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

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

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

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

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

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

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

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

Grounded Theory

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

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

Defining Qualitative Research

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

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

Distinctions

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

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

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

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

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

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

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

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

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

Improved Understanding

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

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

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

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

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

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

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

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

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

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

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

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

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

Acknowledgements

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

Biographies

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

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

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Patrik Aspers, Email: [email protected] .

Ugo Corte, Email: [email protected] .

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

• Introduction and overview
• What is qualitative research?

What is qualitative data?

Advantages and disadvantages of qualitative data, qualitative and quantitative data, qualitative data collection, ethical considerations for 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

When you think of the word "data," you might think about numbers and tables and organized spreadsheets. Qualitative data, on the other hand, can take on so many forms and serve so many purposes that it's important to examine the topic in greater detail.

Qualitative research methods collect unstructured or unorganized data that is often difficult to define statistically or numerically. There are many uses for collecting and analyzing qualitative data, such as understanding social phenomena, gathering people's opinions on various subjects, and building evidence for recommendations. Ultimately, researchers will need to organize and categorize qualitative data in order to perform qualitative data analysis .

Why collect qualitative data?

Qualitative and quantitative data are almost always juxtaposed against each other. Data generated from quantitative research lends itself to statistical analysis, while qualitative data contextualizes a concept or phenomenon by describing its constituent elements.

For example, consider the difference between comparing the average temperatures of two different cities and comparing the innate beauty of those two cities. The former can be quantified so that researchers can reach a quick conclusion about the differences in the climate. On the other hand, the latter is rather difficult to reduce to numbers. Even if beauty can be placed on a ten-point scale, what does "7 points" or "4 points" on the beauty scale mean? How does someone determine such a score? Understanding the beauty of a particular city requires collecting qualitative data.

Where is qualitative data used?

Many different kinds of researchers, such as anthropologists, professionals engaged in health services research, and market researchers, collect and analyze qualitative data . While the method of collecting data in each area may differ, fields that commonly utilize qualitative data have research questions that an analysis of numerical data cannot easily answer.

Researchers often perceive a divide between qualitative data and quantitative data and get into debates about which form of data is "better." The more important task is to collect relevant data for your research. Let's consider the pros and cons of qualitative data.

Qualitative data helps offer in-depth analysis and a more nuanced understanding of phenomena than quantitative data can provide. For example, statistics can tell us the average test scores for each school whose students took a standardized test. Comparisons of average scores can give us information about which schools are more successful or are struggling. Further statistical analysis can indicate a correlation between school funding and test performance.

However, these statistics are less likely to point out the causes leading to these test results. A qualitative study gathers data that can supplement those test scores with further context, such as teachers' instructional practices, students' opinions about learning activities, and funding for educational resources.

An analysis of qualitative data can allow researchers to draw relationships between ideas. This is accomplished by "coding" the data for ideas. Coding qualitative data involves looking at your data and applying short, descriptive labels called codes to segments of text, images, audio, or video for later analysis. With systematic coding, you can turn your raw data into an organized, meaningful data set from which you can draw insightful conclusions.

Suppose the study above involves interviewing students about their test performance and teachers. A researcher can code all of the instances where students describe their teacher as "nice," "helpful," or "strict." Qualitative data analysis software like ATLAS.ti helps researchers with the coding process so that themes emerging from the data become easier to understand.

Researchers can then conduct qualitative data analysis by determining whether the well-performing or struggling students have a specific set of keywords that describe their teachers' personalities. If so, the researcher can propose a connection between a teacher's personality characteristics and their students' test scores.

Disadvantages

The main disadvantage of using qualitative data is that the analysis can be complex and time-consuming. On the other hand, quantitative data is relatively straightforward to collect and analyze. Because qualitative data cannot easily be reduced to numbers or statistics, researchers need to reorganize the data in more structured and meaningful ways for analysis. A qualitative researcher often has to read their data line by line to determine what information to code and how.

Another concern that critics of qualitative research point to is researchers' potential biases and subjectivities when analyzing qualitative data. The reorganization and analysis of the data must be presented clearly and transparently so that research audiences can easily understand the analysis and assess the credibility of the subsequent conclusions themselves.

The research objectives you want to pursue will dictate how you should collect data and what data you should collect.

Quantitative data

Let's say you are conducting an experimental study to determine the effectiveness of a nutritional supplement in helping people lose weight. In this case, you will likely collect quantitative data such as weight, caloric intake, and time spent exercising. Quantitative data like these can be analyzed statistically to help you understand if research participants are losing weight because of the supplement.

Qualitative data

On the other hand, you may also want to gather opinions on whether people are satisfied with the supplement. Qualitative data collection methods such as interviews or focus groups might ask research participants what they think the supplement tastes like, how they feel after taking it, and why they believe it is effective or not effective. Answers to these questions don't provide easy numbers or simple statistics.

Still, these insights are just as important to product researchers because even if the supplement is effective, people may choose not to buy it if it leads to unpleasant experiences. Qualitative data is valuable to researchers when they need to know more about an unfamiliar phenomenon and when understanding the phenomenon requires more complexity than a simple yes/no binary or a numerical scale can provide. Instead, a thematic analysis of qualitative data on the subject might explore the emotions (e.g., happy, frustrated) associated with each particular taste (e.g., sweet, sour, bitter).

Mixed methods research

You may want to consider a mixed methods approach to research and thus combine quantitative and qualitative data collection methods. Researchers can best understand a complex problem by collecting various types of data collected on the subject. In the example above, the successful launch of a nutritional supplement depends on its effectiveness and customer satisfaction. One is only particularly helpful if the other is also present. Ultimately, it is essential to consider whether you are collecting the right kinds of data for the research inquiry you want to pursue.

In-depth data analysis is right at your fingertips with ATLAS.ti!

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A researcher can employ various qualitative methods to collect qualitative data . As a result, numerous types of qualitative data can be used for data analysis .

Questionnaires

Questionnaires or surveys are among the easiest methods for collecting large-scale qualitative and quantitative data. In addition to capturing quantitative data for statistical analysis, questionnaires can also be used to collect open-ended answers from respondents.

For example, researchers can ask respondents to rate their satisfaction with a particular product on a scale of 1 to 5 and then write down their reasons for their ratings. Qualitative data analysis can reveal sentiments about a product among respondents who are very satisfied with it and compare sentiments among unsatisfied respondents.

Qualitative data from in-depth interviews often involve transcripts and audio or video recordings . Transcription converts interviews into text that can be read and cited in documents and presentations when you want the audience to see what research respondents have said.

Recordings are also valuable as they allow researchers to see respondents' facial expressions and gestures or hear their non-verbal utterances. This qualitative data analysis helps researchers better understand how respondents feel (e.g., excited, upset, confused) during interviews.

Focus groups are similar to interviews except that multiple respondents talk simultaneously with the interviewer. Similarly to interviews , qualitative data from focus groups can be analyzed from transcripts or multimedia recordings. The recordings can have significant value for qualitative research because they can capture how focus group respondents interact or collaborate.

Observations

An observational research method can conduct data collection on a particular social phenomenon in a less controlled environment than where interviews or focus groups would be conducted. Collecting such naturalistic qualitative data in the field can help researchers who want to see the social world outside of a confined experiment. Researchers can collect various forms of data, such as audio or video recordings, the observers' field notes , and photographs. The type of research you want to conduct will help you determine which data collection methods to employ.

For example, if you are at a train station, you may want to record audio of train station announcements or record field notes about how easy or difficult it may be to navigate the station. Additionally, taking pictures or videos while walking around the train station may be valuable to later analyze what you see.

Document analysis

Any textual data , such as medical records, journal articles, and website pages, can be analyzed qualitatively. Collecting documents is useful to researchers looking to conduct a comparative analysis, thematic review, or user research. Researchers can analyze documents for their text, images, or other features depending on the inquiry they want to conduct.

Social media analysis

Content from Twitter, Instagram, and other similar platforms can provide abundant opportunities for qualitative analysis. ATLAS.ti allows researchers to import tweets directly into their project as well as comments from any social media post , such as Instagram, TikTok, Facebook, and so on. Researchers can easily search and incorporate any tweets or comments as qualitative data instantly.

Researchers should always be careful with collecting and handling qualitative data, especially if it contains personal information or needs to be obtained with consent. People's perspectives are simplified and aggregated into numbers when quantitative analysis is pursued, but qualitative data collection often preserves the words, circumstances, and behaviors of people, and participants may feel uncomfortable with how such data might be used. An important consideration is how the researcher should present the data to their audiences while not revealing any clues about participants' identities.

Medical records, for example, are especially sensitive as people can connect names to health conditions that patients may prefer to keep secret. In observations , people may not want their pictures taken if they don't want to be associated with being in a particular place. Respondents in interviews and focus groups may choose to withdraw from research after having said something about which they feel embarrassed or uncomfortable.

Before collecting any data, researchers should obtain informed consent from participants to ensure that participants understand their rights and how their privacy is protected. This might be a challenge in observations, especially when they occur outside a controlled environment. When collecting data in the field, researchers might consider avoiding taking pictures or videos of people's faces, recognizable clothing, or possessions. As a result, field notes might be the most appropriate form of data to collect while observing in the field.

Even if research participants give informed consent, there is always the possibility they might say something sensitive or provide information that they later wish they hadn’t. Researchers should always take precautions when collecting data from research participants to ensure that potentially damaging information isn't disseminated in research presentations or academic publications.

By thoughtfully engaging with rigorous data collection methods , researchers can collect rich data that provides novel insights and offers participants a chance to meaningfully express themselves.

Ready to try ATLAS.ti?

Let ATLAS.ti guide you through the complexities of qualitative data analysis. Try our software for free by clicking here.

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Quantitative vs. Qualitative Research in Psychology

Anabelle Bernard Fournier is a researcher of sexual and reproductive health at the University of Victoria as well as a freelance writer on various health topics.

Emily is a board-certified science editor who has worked with top digital publishing brands like Voices for Biodiversity, Study.com, GoodTherapy, Vox, and Verywell.

• Key Differences

Quantitative Research Methods

Qualitative research methods.

• How They Relate

In psychology and other social sciences, researchers are faced with an unresolved question: Can we measure concepts like love or racism the same way we can measure temperature or the weight of a star? Social phenomena⁠—things that happen because of and through human behavior⁠—are especially difficult to grasp with typical scientific models.

At a Glance

Psychologists rely on quantitative and quantitative research to better understand human thought and behavior.

• Qualitative research involves collecting and evaluating non-numerical data in order to understand concepts or subjective opinions.
• Quantitative research involves collecting and evaluating numerical data. 

This article discusses what qualitative and quantitative research are, how they are different, and how they are used in psychology research.

Qualitative Research vs. Quantitative Research

In order to understand qualitative and quantitative psychology research, it can be helpful to look at the methods that are used and when each type is most appropriate.

Psychologists rely on a few methods to measure behavior, attitudes, and feelings. These include:

• Self-reports , like surveys or questionnaires
• Observation (often used in experiments or fieldwork)
• Implicit attitude tests that measure timing in responding to prompts

Most of these are quantitative methods. The result is a number that can be used to assess differences between groups.

However, most of these methods are static, inflexible (you can't change a question because a participant doesn't understand it), and provide a "what" answer rather than a "why" answer.

Sometimes, researchers are more interested in the "why" and the "how." That's where qualitative methods come in.

Qualitative research is about speaking to people directly and hearing their words. It is grounded in the philosophy that the social world is ultimately unmeasurable, that no measure is truly ever "objective," and that how humans make meaning is just as important as how much they score on a standardized test.

Used to develop theories

Takes a broad, complex approach

Answers "why" and "how" questions

Explores patterns and themes

Used to test theories

Takes a narrow, specific approach

Answers "what" questions

Explores statistical relationships

Quantitative methods have existed ever since people have been able to count things. But it is only with the positivist philosophy of Auguste Comte (which maintains that factual knowledge obtained by observation is trustworthy) that it became a "scientific method."

The scientific method follows this general process. A researcher must:

• Generate a theory or hypothesis (i.e., predict what might happen in an experiment) and determine the variables needed to answer their question
• Develop instruments to measure the phenomenon (such as a survey, a thermometer, etc.)
• Develop experiments to manipulate the variables
• Collect empirical (measured) data
• Analyze data

Quantitative methods are about measuring phenomena, not explaining them.

Quantitative research compares two groups of people. There are all sorts of variables you could measure, and many kinds of experiments to run using quantitative methods.

These comparisons are generally explained using graphs, pie charts, and other visual representations that give the researcher a sense of how the various data points relate to one another.

Basic Assumptions

Quantitative methods assume:

• That the world is measurable
• That humans can observe objectively
• That we can know things for certain about the world from observation

In some fields, these assumptions hold true. Whether you measure the size of the sun 2000 years ago or now, it will always be the same. But when it comes to human behavior, it is not so simple.

As decades of cultural and social research have shown, people behave differently (and even think differently) based on historical context, cultural context, social context, and even identity-based contexts like gender , social class, or sexual orientation .

Therefore, quantitative methods applied to human behavior (as used in psychology and some areas of sociology) should always be rooted in their particular context. In other words: there are no, or very few, human universals.

Statistical information is the primary form of quantitative data used in human and social quantitative research. Statistics provide lots of information about tendencies across large groups of people, but they can never describe every case or every experience. In other words, there are always outliers.

Correlation and Causation

A basic principle of statistics is that correlation is not causation. Researchers can only claim a cause-and-effect relationship under certain conditions:

• The study was a true experiment.
• The independent variable can be manipulated (for example, researchers cannot manipulate gender, but they can change the primer a study subject sees, such as a picture of nature or of a building).
• The dependent variable can be measured through a ratio or a scale.

So when you read a report that "gender was linked to" something (like a behavior or an attitude), remember that gender is NOT a cause of the behavior or attitude. There is an apparent relationship, but the true cause of the difference is hidden.

Pitfalls of Quantitative Research

Quantitative methods are one way to approach the measurement and understanding of human and social phenomena. But what's missing from this picture?

As noted above, statistics do not tell us about personal, individual experiences and meanings. While surveys can give a general idea, respondents have to choose between only a few responses. This can make it difficult to understand the subtleties of different experiences.

Quantitative methods can be helpful when making objective comparisons between groups or when looking for relationships between variables. They can be analyzed statistically, which can be helpful when looking for patterns and relationships.

Qualitative data are not made out of numbers but rather of descriptions, metaphors, symbols, quotes, analysis, concepts, and characteristics. This approach uses interviews, written texts, art, photos, and other materials to make sense of human experiences and to understand what these experiences mean to people.

While quantitative methods ask "what" and "how much," qualitative methods ask "why" and "how."

Qualitative methods are about describing and analyzing phenomena from a human perspective. There are many different philosophical views on qualitative methods, but in general, they agree that some questions are too complex or impossible to answer with standardized instruments.

These methods also accept that it is impossible to be completely objective in observing phenomena. Researchers have their own thoughts, attitudes, experiences, and beliefs, and these always color how people interpret results.

Qualitative Approaches

There are many different approaches to qualitative research, with their own philosophical bases. Different approaches are best for different kinds of projects. For example:

• Case studies and narrative studies are best for single individuals. These involve studying every aspect of a person's life in great depth.
• Phenomenology aims to explain experiences. This type of work aims to describe and explore different events as they are consciously and subjectively experienced.
• Grounded theory develops models and describes processes. This approach allows researchers to construct a theory based on data that is collected, analyzed, and compared to reach new discoveries.
• Ethnography describes cultural groups. In this approach, researchers immerse themselves in a community or group in order to observe behavior.

Qualitative researchers must be aware of several different methods and know each thoroughly enough to produce valuable research.

Some researchers specialize in a single method, but others specialize in a topic or content area and use many different methods to explore the topic, providing different information and a variety of points of view.

There is not a single model or method that can be used for every qualitative project. Depending on the research question, the people participating, and the kind of information they want to produce, researchers will choose the appropriate approach.

Interpretation

Qualitative research does not look into causal relationships between variables, but rather into themes, values, interpretations, and meanings. As a rule, then, qualitative research is not generalizable (cannot be applied to people outside the research participants).

The insights gained from qualitative research can extend to other groups with proper attention to specific historical and social contexts.

Relationship Between Qualitative and Quantitative Research

It might sound like quantitative and qualitative research do not play well together. They have different philosophies, different data, and different outputs. However, this could not be further from the truth.

These two general methods complement each other. By using both, researchers can gain a fuller, more comprehensive understanding of a phenomenon.

For example, a psychologist wanting to develop a new survey instrument about sexuality might and ask a few dozen people questions about their sexual experiences (this is qualitative research). This gives the researcher some information to begin developing questions for their survey (which is a quantitative method).

After the survey, the same or other researchers might want to dig deeper into issues brought up by its data. Follow-up questions like "how does it feel when...?" or "what does this mean to you?" or "how did you experience this?" can only be answered by qualitative research.

By using both quantitative and qualitative data, researchers have a more holistic, well-rounded understanding of a particular topic or phenomenon.

Qualitative and quantitative methods both play an important role in psychology. Where quantitative methods can help answer questions about what is happening in a group and to what degree, qualitative methods can dig deeper into the reasons behind why it is happening. By using both strategies, psychology researchers can learn more about human thought and behavior.

Gough B, Madill A. Subjectivity in psychological science: From problem to prospect . Psychol Methods . 2012;17(3):374-384. doi:10.1037/a0029313

Pearce T. “Science organized”: Positivism and the metaphysical club, 1865–1875 . J Hist Ideas . 2015;76(3):441-465.

Adams G. Context in person, person in context: A cultural psychology approach to social-personality psychology . In: Deaux K, Snyder M, eds. The Oxford Handbook of Personality and Social Psychology . Oxford University Press; 2012:182-208.

Brady HE. Causation and explanation in social science . In: Goodin RE, ed. The Oxford Handbook of Political Science. Oxford University Press; 2011. doi:10.1093/oxfordhb/9780199604456.013.0049

Chun Tie Y, Birks M, Francis K. Grounded theory research: A design framework for novice researchers .  SAGE Open Med . 2019;7:2050312118822927. doi:10.1177/2050312118822927

Reeves S, Peller J, Goldman J, Kitto S. Ethnography in qualitative educational research: AMEE Guide No. 80 . Medical Teacher . 2013;35(8):e1365-e1379. doi:10.3109/0142159X.2013.804977

Salkind NJ, ed. Encyclopedia of Research Design . Sage Publishing.

Shaughnessy JJ, Zechmeister EB, Zechmeister JS.  Research Methods in Psychology . McGraw Hill Education.

By Anabelle Bernard Fournier Anabelle Bernard Fournier is a researcher of sexual and reproductive health at the University of Victoria as well as a freelance writer on various health topics.

• Sep 9, 2020

Pros And Cons Of Qualitative Research vs Quantitative Research

Updated: May 27

In this post, you will learn the pros and cons of qualitative research vs quantitative research along with the differences and discover how both types of research can help and be applied to different business situations from ethnographic research to online surveys.

Table of contents:

The difference between qualitative and quantitative research

Pros and cons of qualitative research, pros and cons of quantitative research, so when can qualitative and quantitative research be applied, main types of qualitative research methods, key types of quantitative research methods.

The table above shows the advantages and disadvantages of using qualitative research and quantitative research.

[Disclosure: This post contains affiliate links, meaning we get a commission if you decide to make a purchase through these links at no additional cost to you.]

The main purpose of qualitative research is to explore the in-depth behaviour, opinions and attitudes of a small group of individuals in a more open manner instead of strictly following a set of questions. These tend to be face to face in-depth interviews or focus groups, where people can discuss the subject at hand openly with guidance from the interviewer.

While quantitative research is where results can be measured by numbers, which is easy to pick up and understand for those making the decisions . These quantified results are gathered by interviewing a large group of people (from 50 running into the 1000s) that is a reflection of the whole population you are targeting. Hence with a larger sample size, statistical analysis can be applied to provide better consumer insights such as predicted behaviour, best price levels and key drivers of buyers’ decisions.

Other than exploring attitudes and behaviour in detail, qualitative research is also used to test adverts, develop concepts and new products and build a picture of the market. Whereas quantitative research is used more for market measurements such as the number of people who use a product or service, awareness, consideration, preference, segmenting the market and how likely are they to buy.

Pros of qualitative research

Explores attitudes and behaviour in-depth.

Explores attitudes and behaviour in-depth as it’s more on a personal level and can delve in detail to gain a better understanding of their views and actions to generate or examine a hypothesis in more detail.

Encourages discussion

Encourages discussion as it’s more in an open manner instead of strictly following a fixed set of questions. In this way, it gives the research some context rather than just numbers.

Flexibility

Flexibility, where the interviewer can probe and is able to ask any questions around the subject matter, they feel is relevant or had not thought of before during the discussions and can even change the setting.

Cons of qualitative research

The sample size can be an issue.

The sample size can be an issue if you are taking the opinion of 5 people out of 300 of your customers or subscribers as a generalisation.

Bias in the sample selection

Bias in the sample selection, meaning the people you are selecting to take part in the qualitative research may all have a certain opinion of the subject matter rather than a group of people with mixed views, which is more valuable particularly if they are debating with opposing views during focus groups.

Lack of privacy

Lack of privacy, if you are covering sensitive topics then people taking part may not be comfortable in sharing their thoughts and opinions of the subject with others.

Whether you are using a skilled moderator or not

It is of vital importance; the moderator is skilled and experienced in managing the conversations of groups as well as being knowledgeable enough of the subject matter to ask relevant questions that may have not been thought of.

Pros of quantitative research

Larger sample sizes.

Larger sample sizes allowing for robust analysis of the results, so you are able to make more generalisations of your target audience.

Impartiality and accuracy of data

Impartiality and accuracy of the data as it based on the survey questions for screening, grouping and other hard number facts.

Faster and easier to run

Faster and easier to run particularly online and mobile surveys , where you can see the results in real time.

Data is anonymous

Data is anonymous especially with sensitive topics through self-completion exercises like online surveys.

Offers reliable and continuous information

Offers reliable and continuous information where you can repeat the survey again and again weekly, monthly, quarterly, yearly to gain consistent trend data to help you plan ahead or investigate and address issues.

Cons of quantitative research

Limited by the set answers on a survey.

Limited by the set answers on a survey, so you are unable to go beyond that in delving in more detail the behaviours, attitudes and reasons as you do with qualitative research. This is particularly true with self-completion surveys (online), where there is no interviewer probing you even if you include a couple of open-ended questions.

Research is not carried out in their normal environment

Research is not carried out in their normal environment, so can seem artificial and controlled. Answers given by participants are claimed and may not be their actual behaviour in real life.

Unable to follow-up any answers given following completion of survey

Unable to follow-up any answers given after they have completed the survey due to the anonymity of the participants. This is especially true for validity of the findings if the results are inconclusive. Although you can ask at the end of the survey if they would like to do a follow-up survey but not all participants may agree to do so.

Generally qualitative research is used for exploratory purposes to get a picture of what is going on or examining a hypothesis that can be tested later on. Although it can be used independently through a series of depth interviews and focus groups to explore concepts such as ideas for advertising or new products.

While with quantitative research you can gather measurable results that you can draw insights from and take action where needed like there is a drop in the number of visitors to your website page, which may be tackled through redesign of the webpage or promotions.

Read this post if you want run a survey - 5 Best Survey Maker Platforms To Consider Using

Qualitative and quantitative research is best utilised when they are combined and split into phases. For example, phase 1 could be exploratory research with qualitative research and then in phase 2 this is followed up with quantitative research to test the hypothesis that came up in the first phase. A post phase of qualitative research can be applied if there has been redesigns of the concept or to identify experiences after an event.

There are advantages in combining data and information from both methods where you can reap the benefits from the advantages that both methods have as well as countering the limitations through this hybrid approach. This is achieved through:

Enrichment by identifying issues not found in quantitative research

Examination via generating a hypothesis that can be tested.

Explanation through bringing the results to life by understanding any surprising results from the quantitative data.

Below are the most popular types of research within qualitative and quantitative research that you can use to achieve your objectives and answer questions you may have.

The three key tools of qualitative research are:

Focus groups – this is where a group of 5 to 10 people at a set location or on a private online forum discuss a topic of interest who have been pre-selected via screening to take part in. These group discussions are led by a person moderating the group.

Depth interviews – are one to one interviews that are either conducted face to face, over the phone or through video conferencing apps like Skype and Zoom. This allows the participant to talk at length in a more open manner and is especially good for sensitive topics. The interviewer will use a discussion guide to follow a relatively unstructured list of topics.

Ethnography and observation – are a fly on the wall way of listening and observing the behaviour of participants in certain real environments like shopping at a supermarket. Is great to capture the actual actions of participants rather than what they claim to do in a survey.

The 3 most popular methods of quantitative research:

Online surveys – is without a doubt the most popular type of research especially amongst consumer research as it’s quick, easy to do and relatively cheap compared to other methods. The great thing with online surveys is it easily accessible for everyone to take part in whether that’s on a laptop, mobile or tablet and can be on a website or survey links through social media and email. Plus, you can check out the results in real time.

If you are interested in creating a survey, quiz or online forms you can try JotForm which is a easy to use interactive platform to set up surveys from scratch or have customisable templates to get you started with.

Also there is free eBook available called Jotform for Beginners that you can download and will explain the different features available to save time and boost productivity with all kinds of online forms for apps, stores, pdf, tables and more.

Telephone interviews – due to advancements in technology this is now used more for business to business research and interviews tend to last between 15 to 30 minutes. The advantage of this method is you have an interviewer who can probe or clarify any answers to open ended questions.

Face to face interviews – these are normally conducted in specific situations like shopping malls, exhibitions and the high street. As it’s more time consuming, costly and higher a security risk for interviewers, makes it the least popular method to use.

Social listening - is a form of secondary research where you can track, listen and respond to mentions about a brand or key topic on social media and elsewhere on the web. You can read more about it in this post - 3 Social Listening Tools To Consider

If you want to find out more how market research can help you, check out the posts below:

Market Research Online Surveys In 6 Easy Steps

How To Do A Survey: Top 10 Tips

Market Research Online: Benefits, Methods & Tools

Conversational Forms: Discover What So Good About Them

Causal Research: Definition | Advantages | Examples | Components

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#qualitativevsquantitativeresearch #anparresearch

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Unlocking Insights: A Guide to Data Analysis Methods

The data collected already in this information age are what makes advancement possible. But by itself, raw data is a confused mess. We employ the performance of data analysis to clear this confusion, extracting valuable insights from the muck that’s gradually forming the base for key decisions and innovation. This article plunges into the methods used in data analysis, arming one with know-how for the dynamic field.

Table of Content

Understanding Data Analysis

Types of data analysis, quantitative data analysis methods, quantitative data analysis methods: when to use, advantages and disadvantages, qualitative data analysis methods, qualitative data analysis methods: when to use, advantages and disadvantages, data analysis mixed methods ( quantitative and qualitative), data analysis mixed methods : when to use, advantages and disadvantages.

Data analysis is the process of inspecting, cleaning, transforming, and modeling data to answer questions, make conclusions, and support decision-making. It is a multi-disciplinary field of study that involves deriving knowledge from raw data. Data analysis is used by companies in order to outcompete and get that cutting edge in understanding customer behaviors, optimizing campaigns for marketing, and predicting trends in the market.

Data analytic techniques have wide-ranging methodologies, roughly placed under two main approaches: quantitative analysis and qualitative analysis.

• Quantitative Analysis: This is where one begins to work with numbers and to use the power of statistics and mathematical models in order to determine patterns, trends, and relationships from which data could be drawn. It’s quite like using a ruler to measure and compare data points. Techniques under this level include regression analysis, hypothesis testing, and time series analysis. Just try and imagine using regression analysis in trying to understand how changes in the advertising budget are reflected in the sales numbers.
• Qualitative Analysis: This method should be reserved for non-numeric data, or data that does not easily translate into numbers. This refers to data such as customer reviews ; images, such as those contained within social media posts; and, in some cases, even the audio recording of responses to questions during a focus group. Some techniques used in qualitative analysis include but are not limited to content analysis, thematic analysis, and sentiment analysis to truly understand the meaning of the data and all the emotions and underlying concepts derived from it. For example, sentiment analysis is done on customer reviews to see overall levels of customer satisfaction.
• Mixed Methods: Research involves the integration of both quantitative and qualitative data collection and analysis techniques within a single study. This approach allows researchers to capitalize on the strengths of both methods while compensating for their weaknesses. By counting numerical data and analyzing descriptive data, researchers can achieve a more comprehensive understanding of the research problem. Mixed Methods is beneficial for exploring complex phenomena, providing both breadth and depth, and is widely used in fields like education, health sciences, and social sciences.

1. Descriptive Analysis

Descriptive analysis involves summarizing and organizing data to understand its basic features. It provides simple summaries about the sample and the measures. This can include measures of central tendency (mean, median, mode), measures of variability (standard deviation, range), and frequency distributions. Visual tools like histograms, pie charts, and box plots are often used. Descriptive analysis helps to identify patterns and trends within the data, offering a foundation for further statistical analysis.

2. Inferential Analysis

Inferential analysis allows researchers to make predictions or inferences about a population based on a sample of data. Techniques include hypothesis testing, confidence intervals, and analysis of variance (ANOVA). This method helps in determining the probability that an observed difference or relationship exists in the larger population. It goes beyond the data at hand, enabling generalizations and predictions about the broader group.

3. Regression Analysis

Regression analysis is used to understand the relationship between dependent and independent variables. The primary goal is to model the relationship and make predictions. Simple linear regression deals with one independent variable, while multiple regression involves several independent variables. The method quantifies the strength of the impact of the variables and can highlight significant predictors of the outcome variable.

4. Time Series Analysis

Time series analysis involves analyzing data points collected or recorded at specific time intervals. It focuses on identifying trends, seasonal patterns, and cyclical behaviors in data over time. Techniques include moving averages, exponential smoothing, and ARIMA models. Time series analysis is crucial for forecasting future values based on past observations, often used in economic forecasting, stock market analysis, and demand planning.

5. Factor Analysis

Factor analysis is a technique used to reduce data dimensionality by identifying underlying factors or constructs. It simplifies data by modeling the observed variables as linear combinations of potential factors. There are two main types: exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). This method is widely used in psychology, social sciences, and market research to identify latent variables that explain observed correlations.

6. Cluster Analysis

Cluster analysis groups a set of objects in such a way that objects in the same group (or cluster) are more similar to each other than to those in other groups. It is an unsupervised learning technique used in pattern recognition, image analysis, and market segmentation. Methods include k-means, hierarchical clustering, and DBSCAN. Cluster analysis helps in identifying distinct subgroups within a dataset, enhancing understanding of the data structure.

7. Classification Analysis

Classification analysis is a supervised learning technique used to assign data into predefined categories. It uses algorithms such as decision trees, support vector machines, and neural networks to classify data based on training datasets. Commonly applied in spam detection, credit scoring, and medical diagnosis, classification analysis aims to accurately predict the category to which new data points belong.

8. Predictive Analysis

Predictive analysis utilizes statistical techniques and machine learning algorithms to forecast future outcomes based on historical data. It includes methods like regression, time series analysis, and classification. Predictive analysis is used in various fields, such as finance for risk management, marketing for customer behavior prediction, and healthcare for predicting disease outbreaks. It helps organizations make informed decisions by anticipating future trends and behaviors.

9. Prescriptive Analysis

Prescriptive analysis goes beyond predicting future outcomes by recommending actions to achieve desired results. It uses optimization and simulation algorithms to suggest the best course of action among various alternatives. Techniques often involve a combination of data analytics, operations research, and decision science. Prescriptive analysis is used in supply chain management, financial planning, and resource allocation to improve decision-making and optimize outcomes.

10. Diagnostic Analysis

Diagnostic analysis examines data to understand the causes of past outcomes. It delves into historical data to identify patterns and correlations that explain why something happened. Techniques include drill-down, data mining, and correlation analysis. Diagnostic analysis is crucial for root cause analysis in various industries, helping organizations to understand underlying issues and improve processes and performance.

11. Statistical Analysis

Statistical analysis involves collecting, exploring, and presenting large amounts of data to discover underlying patterns and trends. It includes descriptive statistics, inferential statistics, and multivariate techniques. Statistical analysis is fundamental in hypothesis testing, estimating population parameters, and making data-driven decisions. It is widely used across disciplines, including economics, psychology, medicine, and engineering, to validate research findings and support evidence-based practices.

1. Content Analysis

Content Analysis is a systematic, quantitative approach to analyzing the presence, meanings, and relationships of certain words, themes, or concepts within qualitative data. This method involves counting and coding the content into manageable categories, which can then be used to draw inferences about the data. By counting the frequency and context of words or phrases, researchers can identify patterns, trends, and biases. Content Analysis is widely used in media studies, psychology, and social sciences to examine communication patterns, such as speeches, interviews, and social media posts.

2. Thematic Analysis

Thematic Analysis is a method for identifying, analyzing, and reporting patterns (themes) within qualitative data. It involves counting, coding the data, and organizing codes into themes, which are then reviewed and refined. This approach provides a flexible and accessible way to understand data, allowing researchers to interpret various aspects of the research topic. Thematic Analysis is particularly useful for exploring participants’ perspectives, experiences, and social contexts, making it popular in psychology, health studies, and social research.

3. Narrative Analysis

Narrative Analysis focuses on the stories people tell and the ways they tell them. It involves examining the structure, content, and context of narratives to understand how individuals make sense of their experiences and convey meaning. This method includes counting and paying attention to the sequencing and coherence of narratives, as well as the socio-cultural factors influencing them. Narrative Analysis is often used in fields such as sociology, psychology, and education to explore identity, culture, and human behavior through personal stories and biographies.

4. Grounded Theory

Grounded Theory is a systematic methodology in social science research for constructing theory from data. It involves iterative data collection and analysis, where the researcher counts instances, develops concepts, and theories through continuous comparison of data. This method emphasizes inductive reasoning, allowing theories to emerge directly from the data rather than being imposed by pre-existing frameworks. Grounded Theory is widely used in sociology, nursing, education, and other fields to generate substantive or formal theories that are deeply rooted in empirical evidence.

5. Discourse Analysis

Discourse Analysis examines how language is used in texts and contexts to construct meaning and social reality. It involves counting and analyzing written, spoken, or signed language to understand how discourse shapes and is shaped by social, political, and cultural contexts. This method explores power dynamics, ideologies, and identities embedded in language. Discourse Analysis is commonly applied in linguistics, sociology, media studies, and communication studies to study everything from political speeches and media content to everyday conversations.

6. Interpretive Phenomenological Analysis (IPA)

Interpretive Phenomenological Analysis (IPA) is a qualitative research approach focused on exploring how individuals make sense of their personal and social experiences. It involves detailed examination and counting of participants’ lived experiences, emphasizing their perceptions and interpretations. IPA is idiographic, meaning it aims to provide in-depth insights into individual cases before identifying broader patterns. This method is popular in psychology, health, and social sciences, particularly for studying complex, sensitive, or deeply personal phenomena.

7. Case Study Analysis

Case Study Analysis is an in-depth examination of a single case or a small number of cases within a real-life context. This method involves counting and analyzing various types of data, such as interviews, observations, and documents, to gain a comprehensive understanding of the case(s). Case Study Analysis allows for detailed exploration of complex issues, processes, and relationships, providing rich insights that can inform theory and practice. It is widely used in fields like business, education, social sciences, and medicine.

8. Ethnographic Analysis

Ethnographic Analysis involves the systematic study of people and cultures through immersive observation and participation. Researchers spend extended periods in the field, counting and collecting data through participant observation, interviews, and other qualitative methods. The goal is to understand the social dynamics, behaviors, and meanings from the insider’s perspective. Ethnographic Analysis provides detailed, context-rich insights into cultural practices, making it a valuable method in anthropology, sociology, and other social sciences.

1. Triangulation

Triangulation is a strategy used in research to enhance the validity and reliability of the findings by combining multiple methodologies, data sources, theories, or investigators. By counting and comparing different data points or perspectives, researchers can cross-verify the consistency of their results. This method reduces biases and increases the robustness of the conclusions. Triangulation is commonly employed in qualitative research, mixed methods studies, and evaluation research to corroborate findings and provide a fuller picture of the phenomenon under study.

2. Convergent Parallel Design

Convergent Parallel Design is a type of Mixed Methods design where quantitative and qualitative data are collected simultaneously but analyzed separately. After the independent analysis, the results are merged to see how they corroborate, diverge, or complement each other. This design involves counting and coding quantitative data and thematic analysis of qualitative data concurrently. The purpose is to provide a comprehensive understanding by comparing and relating both sets of results. It is often used in social sciences, education, and health research to address complex research questions from multiple angles.

3. Explanatory Sequential Design

Explanatory Sequential Design is a Mixed Methods approach that begins with the collection and analysis of quantitative data, followed by the collection and analysis of qualitative data to explain or build upon the initial results. This sequential process involves first counting numerical data and identifying significant patterns, then exploring these findings in-depth through qualitative methods. This design is useful for studies where the researcher seeks to explain quantitative results in more detail. It is commonly used in educational research, program evaluation, and health studies.

4. Exploratory Sequential Design

Exploratory Sequential Design is a Mixed Methods approach that starts with qualitative data collection and analysis, followed by quantitative data collection and analysis. The initial qualitative phase involves thematic analysis to uncover patterns and generate hypotheses, which are then tested through quantitative methods. This sequential process involves coding qualitative data and then counting and analyzing numerical data to validate or expand on the initial findings. Exploratory Sequential Design is particularly useful for developing new theories, instruments, or interventions and is frequently used in social sciences, education, and health research.

Data analysis is crucial for transforming raw data into actionable insights. Each method, whether quantitative, qualitative, or mixed, has its specific applications, advantages, and disadvantages. By understanding and applying these methods, one can effectively navigate the vast amounts of data available today, fostering innovation and informed decision-making.

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Abortion in the US: What you need to know

Subscribe to the center for economic security and opportunity newsletter, isabel v. sawhill and isabel v. sawhill senior fellow emeritus - economic studies , center for economic security and opportunity @isawhill kai smith kai smith research assistant - the brookings institution, economic studies.

May 29, 2024

Key takeaways:

One in every four women will have an abortion in their lifetime.

• The vast majority of abortions (about 95%) are the result of unintended pregnancies.
• Most abortion patients are in their twenties (61%), Black or Latino (59%), low-income (72%), unmarried (86%), between six and twelve weeks pregnant (73%), and already have given birth to one or more children (55%).
• Despite state bans, U.S. abortion totals increased in the first full year after the Supreme Court overturned Roe v. Wade.

Introduction

Two years after the Supreme Court overturned Roe v. Wade, abortion remains one of the most hotly contested issues in American politics. The abortion landscape has become highly fractured, with some states implementing abortion bans and restrictions and others increasing protections and access. The Supreme Court heard two more cases on abortion this term and will likely release those decisions in June. Beyond the Supreme Court, pro-choice and pro-life advocates are fiercely battling it out in the voting booths, state legislatures, and courts. If the 2022 midterm elections are any indication , abortion will be one of the most influential issues of the 2024 election. So what are the basic facts about abortion in America? This primer is designed to tell you most of what you need to know.

What are the different types of abortion?

There are two main types of abortion: procedural abortions and medication abortions. Procedural abortions (also called in-clinic or surgical abortions) are provided by health care professionals in a clinical setting. Medication abortions (also called medical abortions or the abortion pill) typically involve the oral ingestion of two drugs in succession, mifepristone and misoprostol.

Most women discover they are pregnant in the first five to six weeks of pregnancy, but about a third of women do not learn they are pregnant until they are beyond six weeks of gestation. 1 Women with unintended pregnancies detect their pregnancies later than women with intended pregnancies, between six and seven weeks of gestation on average. Even if a woman discovers she is pregnant relatively early, for many it takes time to decide what to do and how to arrange for an abortion if that is her preference.

Why do women have abortions?

The vast majority of abortions (about 95%) are the result of unintended pregnancies. That includes pregnancies that are mistimed as well as those that are unwanted.

Women’s reasons for not wanting a child—or not wanting one now—include finances, partner-related issues, the need to focus on other children, and interference with future education or work opportunities.

In short, if there were fewer unintended pregnancies, there would be fewer abortions.

How common are abortions?

About two in every five pregnancies are unintended (40% in 2015). Roughly the same share of these unintended pregnancies end in abortion (42% in 2011). About one in every five pregnancies are aborted (21% in 2020).

How have abortion totals changed over time?

The number of abortions occurring in the U.S. jumped up after the Roe v. Wade decision in 1973. After peaking in 1990, the number of abortions declined steadily for two and a half decades until reaching its lowest point since 1973 in 2017. 2 Possible contributing factors explaining this long-term decline include delays in sexual activity amongst young people, improvements in the use of effective contraception , and overall declines in pregnancy rates , including those that are unintended . In addition, state restrictions which became more prevalent beginning in 2011 prevented at least some individuals in certain states from having abortions.

In 2018 (four years before the Supreme Court overturned Roe v. Wade), the number of abortions in the U.S. began to increase. The causes of this uptick are not yet fully understood, but researchers have identified multiple potential contributing factors. These include greater coverage of abortions under Medicaid that made abortions more affordable in certain states, regulations issued by the Trump administration in 2019 which decreased the size of the Title X network and therefore reduced the availability of contraception to low-income individuals, and increased financial support from privately-financed abortion funds to help pay for the costs associated with getting an abortion.

Another contributing factor, whose importance bears emphasizing, is the surging popularity of medication abortions .

The use of medication abortions has increased steadily since becoming available in the U.S. in 2000. However, in 2016, the FDA increased the gestational limit for the use of mifepristone from seven to ten weeks and thereby doubled the share of abortion patients eligible for medication abortions from 37% to 75%.

Later, during the COVID-19 pandemic, the FDA revised its policy in 2021 so that clinicians are no longer required to dispense medication abortion pills in person. Patients can now have medication abortion pills mailed to their homes after conducting remote consultations with clinicians via telehealth. In January 2023, the FDA issued another change which allows retail pharmacies like CVS and Walgreens to dispense medication abortion pills to patients with a prescription. Previously only doctors, clinics, or some mail-order pharmacies could dispense abortion pills.

Although access varies widely by state , medication abortions are now the most commonly used abortion method in the U.S. and account for nearly two-thirds of all abortions (63% in 2023). 3

This is why the Supreme Court’s upcoming decision in the Mifepristone case (FDA v. Alliance for Hippocratic Medicine) is so consequential. Among other issues, at stake is whether access to medication abortion will be sharply curtailed and whether regulations regarding medication abortions will revert to pre-2016 rules when abortion pills were not authorized for use after seven weeks of pregnancy and could not be prescribed via telemedicine, sent to abortion patients by mail, or dispensed by retail pharmacies.

Who has abortions?

Most abortion patients are in their twenties (61%), Black or Latino  (59%), low-income (72%), unmarried (86%), and between six and twelve weeks pregnant (73%). 4

The majority of abortion patients have already given birth to one or more children (55%) and have not previously had an abortion (57%). 5 Among abortion patients twenty years old or older, most had attended at least some college (63%). The vast majority of abortions occur during the first trimester of pregnancy (91%). So-called “late-term abortions” performed at or after 21 weeks of pregnancy are very rare and represent less than 1% of all abortions in the U.S.

The abortion rate per 1,000 women of reproductive age is disproportionately high for certain population groups. Among women living in poverty, for example, the abortion rate was 36.6 abortions per 1,000 women of reproductive age in 2014, compared to 14.6 abortions per 1,000 women among all women of reproductive age.

How much does an abortion cost?

The cost of an abortion varies depending on what kind of abortion is administered, how far along the patient is in their pregnancy, where the patient lives, where the patient is seeking an abortion, and whether health insurance or financial assistance is available. In 2021, the median self-pay cost for abortion services was $625 for a procedural abortion in the first trimester of pregnancy and $568 for a medication abortion.

Since 1977, the Hyde Amendment has banned the use of federal funds to pay for abortions except in cases of rape, incest, or life endangerment. Today, among the 36 states that have not banned abortion, fewer than half (17 as of March 2024) allow the use of state Medicaid funds to pay for abortions. 6 Many insurance plans do not cover abortions, often due to state limitations. Most abortion patients pay for abortions out of pocket (53%). State Medicaid funding is the second-most-commonly used method of payment (30%), followed by financial assistance (15%) and private insurance (13%). 7

Whether state law allows state Medicaid funds to cover abortions has a very large impact on the difficulty of paying for abortions and the methods used by women to pay for them. In the year before the Dobbs Supreme Court decision, 50% of women residing in states where state Medicaid funds did not cover abortion reported it was very or somewhat difficult to pay for their abortions, compared to only 17% of women residing in states where abortions were covered.

How has the Supreme Court handled abortion?

In Roe v. Wade (1973), the Supreme Court established that states could not ban abortions before fetal viability, the point at which a fetus can survive outside the womb. Under the three-trimester framework established by Roe, states were not allowed to ban abortions during the first two trimesters of pregnancy but were allowed to regulate or prohibit abortions in the third trimester, except in cases where abortions were necessary to protect the life or health of a pregnant person. The Court ruled that the fundamental right to have an abortion is included in the right to privacy implicit in the “liberty” guarantee of the Due Process Clause of the Fourteenth Amendment.

Since it was decided, Roe v. Wade has faced legal criticism. Notwithstanding these critiques, the Court upheld Roe multiple times over the next half-century including in Planned Parenthood v. Casey (1992). But after former President Trump appointed three new Justices to the Supreme Court, a new conservative supermajority overturned Roe v. Wade in Dobbs v. Jackson Women’s Health Organization (2022) and established that there is no Constitutional right to have an abortion.

In his Dobbs majority opinion , Justice Alito concluded “Roe was egregiously wrong from the start.” Writing for the majority, he underscored that “[t]he Constitution makes no reference to abortion,” and while he recognized there are constitutional rights not expressly enumerated in the Constitution, he concluded the right to have an abortion is not one of them. Justice Alito reasoned that the only legitimate rights not explicitly stated in the Constitution are those “deeply rooted in the nation’s history and traditions,” and he found no evidence of this for abortion.

Because the Court determined there is no Constitutional right to abortion, it allowed the Mississippi state law which banned abortion after 15 weeks of pregnancy with limited exceptions to go into effect. The Court ruled that states have the authority to restrict access to abortion or ban it completely and that the power to regulate or prohibit abortions would be “returned to the people and their elected representatives.”

The Court’s three liberal Justices criticized the majority’s decision in a withering joint dissent . The dissenting Justices argued the right to abortion established in Roe and upheld in Casey is necessary to respect the autonomy and equality of women and prevent the government from controlling “a woman’s body or the course of a woman’s life.” They lamented “one result of today’s decision is certain: the curtailment of women’s rights, and of their status as free and equal citizens.”

How did the states respond to the overturning of Roe v. Wade?

Since Roe v. Wade was overturned, many states have implemented abortion bans or restrictions, while others have added protections and expanded access. The abortion landscape in America is now fractured and highly variegated .

As of May 2024, abortion is banned completely in almost all circumstances in 14 states. In 7 states, abortion is banned at or before 18 weeks of gestation. Many states with abortion bans do not include exceptions in cases where the health of the pregnant person is at risk, the pregnancy is the result of rape or incest, or there is a fatal fetal anomaly.

Access to abortion varies widely even among states without bans since many states have restrictions such as waiting periods, gestational limits, or parental consent laws making it more difficult to get an abortion.

Many state bans and restrictions are still being litigated in court. The interjurisdictional issues and legal questions arising from the post-Dobbs abortion landscape have not been fully resolved.

Despite the Supreme Court’s stated intention in Dobbs to leave the abortion issue to elected officials, the Court will likely hear more cases on abortion in the near future. This term, in addition to the case about Mifepristone, the Court will decide in Moyle v. United States whether a federal law called the Emergency Medical Treatment and Labor Act (EMTLA) can require hospitals in states with abortion bans to perform abortions in emergency situations that demand “stabilizing treatment” for the health of pregnant patients.

What are the trends in abortion statistics post-Dobbs?

In 2023, the first full year since the Dobbs Supreme Court decision, states with abortion bans experienced sharp declines in the number of abortions occurring within their borders. But these declines were outweighed by increases in abortion totals in states where abortion remained legal. Nearly all states without bans witnessed increases in 2023. Taken together, abortions in non-ban states increased by 26% in 2023 compared to 2020 levels.

As a result, the nationwide abortion statistics from 2023 represent the highest total number (1,037,000 abortions) and abortion rate (15.9 abortions per 1,000 women of reproductive age) in the U.S. in over a decade. The 2023 U.S. total represents an 11% increase from 2020 levels.

It’s unclear why, despite Dobbs, abortions have continued to rise . It may be because of the increased use of medication abortions , especially after the FDA liberalized regulations related to telehealth and in-person visits. In addition, multiple states where abortion remains legal have implemented shield laws and other new protections for abortion patients and providers, increased insurance coverage, or otherwise expanded access . Abortion funds provided greater financial and practical assistance . Interstate travel for abortions doubled after the Dobbs decision.

In short, the impacts of Dobbs are being felt unevenly. Although most women who want abortions are still able to obtain them, a significant minority are instead carrying their pregnancies to term. In the first six months of 2023, state abortion bans led between one-fifth and one-fourth of women living in ban states who may have otherwise gotten an abortion not to have one.

Young, low-income, and minority women will be most affected by state bans and restrictions because they are disproportionately likely to have unintended pregnancies and less able to overcome economic and logistical barriers involved in travelling across state lines or receiving medication abortion pills through out-of-state networks.

What are the effects of expanding or restricting abortion access on women and their families?

Effects of abortion restrictions on women.

Abortion bans jeopardize the lives and health of women. The impacts on their health can be especially troublesome. Pregnancies can go wrong for many reasons—fetal abnormalities, complications of a miscarriage, ectopic pregnancies—and without access to emergency care, some women could face serious threats to their own health and future ability to bear children. Abortion restrictions can place doctors in difficult situations and undermine women’s health care.

Although medication abortions are safe and effective, abortion bans could also increase the number of women who use unsafe methods to induce self-managed abortions, thereby endangering their own health or even their lives. State abortion legalizations in the years before Roe reduced maternal mortality among non-white women by 30-40%.

Enforcement of state laws that restricted access to abortion in the years before Dobbs has even been associated with increases in intimate partner violence-related homicides of women and girls.

In addition, lack of access to abortion leads to worse economic outcomes for women. After a conservative group suggested that such effects have not been well documented, a group of economists filed an amicus brief to the Supreme Court in the Dobbs case, noting that in recent years methods for establishing the causal effects of abortion have shown that they do affect women’s life trajectories. Although there has been some difficulty in separating the effects of access to abortion from access to the Pill or other forms of birth control, an extensive literature shows that reducing unintended pregnancies increases educational attainment , labor force participation , earnings , and occupational prestige for women. These trends are especially pronounced for Black women .

One example that focuses solely on abortion is the Turnaway study, in which researchers compared the outcomes for women who were denied abortions on the basis of just being a little beyond the gestational cutoff for eligibility to the outcomes of otherwise similar women who were just under that cutoff. The study along with subsequent related research has shown that women who are denied abortions are nearly four times more likely to be living in poverty six months after being denied an abortion, a difference that persists through four years after denial. They are also more likely to be unemployed , rely on public assistance , and experience financial distress such as bankruptcies, evictions and court judgements.

Finally, increased access to abortion results in lower rates of single and teen parenthood. State abortion legalizations in the years before Roe reduced the number of teen mothers by 34%. The effects were especially large for Black teens.

Effects of abortion restrictions on children

Along with contraception, access to abortion reduces unplanned births. That means fewer children dying in infancy, growing up in poverty, needing welfare, and living with a single parent. One study suggests that if all currently mistimed births were aligned with the timing preferred by their mothers, children’s college graduation rates would increase by about 8 percentage points (a 36% increase), and their lifetime incomes would increase by roughly $52,000.

Despite this evidence that the denial of abortions to women who want them would be harmful to women and to children once born, those who are pro-life argue that these costs are well worth the price to save the lives of the unborn. As of April 2024, 36% of Americans believe abortion should be illegal in all (8%) or most (28%) cases, while 63% of Americans believe abortion should be legal in all (25%) or most (28%) cases.

Looking ahead

The abortion landscape in America is continually evolving. Whereas pro-choice advocates will seek to expand access and add additional protections for abortion patients and providers, opponents of abortion will continue to criminalize abortions and further restrict availability.

Abortion will be one of the top issues of the 2024 elections in November. Democratic candidates in particular believe abortion is a winning issue for them and will broadcast their pro-choice stance on the campaign trail. Some evidence suggests the overturning of Roe has galvanized a new class of abortion-rights voters. Multiple states will have abortion referenda on the ballot .

The Supreme Court’s Dobbs decision will not prevent women and other citizens from affecting the legislative process by voting, organizing, influencing public opinion, or running for office. What they do with that power in November remains to be seen.

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The Brookings Institution is financed through the support of a diverse array of foundations, corporations, governments, individuals, as well as an endowment. A list of donors can be found in our annual reports published online  here . The findings, interpretations, and conclusions in this report are solely those of its author(s) and are not influenced by any donation.

• We recognize people of all genders become pregnant and have abortions, including about 1% of abortion patients who do not identify as women or female. For concision, we use “women” and female pronouns in this piece when discussing individuals who become pregnant.
• The Guttmacher and CDC data produced in this primer only represent legal abortions that occur within the formal US healthcare system. They do not include self-managed which occur outside of the formal US healthcare system.
• As of March 2024, 29 states have laws that restrict access to medication abortion, for example by requiring ultrasound, counseling, or multiple in-person appointments.
• We define low-income as earnings below 200% of the federal poverty level.
• The CDC abortion data is less complete than the Guttmacher Institute data and omits abortion data from states which account for approximately one-fourth of all abortions in the U.S.
• Today, roughly 35% of women of reproductive age covered by Medicaid (5.5 million women) are living in states where abortion is legal but state funds are not allowed to cover abortions beyond the Hyde exceptions of rape, incest, or life endangerment.
• Respondents could indicate multiple payment methods.

Health Access & Equity Public Health Reproductive Health Care

Children & Families Human Rights & Civil Liberties

U.S. States and Territories

Economic Studies

North America U.S. States and Territories

Center for Economic Security and Opportunity

Election ’24: Issues at Stake

Stuart M. Butler

May 23, 2024

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May 21, 2024

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Qualitative Research – Advantages & Disadvantages

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Qualitative research, as a unique methodology , facilitates the gathering of information while simultaneously inwaistcoatigating the rationale behind the provided data. This piece illuminates the applications of this form of research, its primary users, the strategies for qualitative data acquisition and analysis, along with the headmaster benefits and potential drawbacks associated with this research approach.

Inhaltsverzeichnis

• 1 Qualitative Research – In a Nutshell
• 2 Qualitative Research – Definition
• 3 Qualitative Research Methods
• 4 Qualitative Research: How to analyse the Data?
• 5 Pros & cons

Qualitative Research – In a Nutshell

• Qualitative research collects complex data based on particitrousers’ opinions and the reasons behind these opinions.
• It can be used in any field but is found most commonly in subjects like the social sciences.
• The sample sizes are generally smaller than in other forms of research.
• The most popular methods are interviews, focus groups, and ethnographic research.
• Data analysis generally divided into developing codes, identifying themes, and creating summaries.

Qualitative Research – Definition

Qualitative research involves gathering and then analysing data tbonnet is recorded non-numerically, such as video, audio, or text. The data is used to understand complex concepts, experiences, and opinions. Qualitative research is used to develop new insights into problems or to generate new research ideas.

As such, qualitative research is the opposite of quantitative research . This latter form of research utilizes numerical data to search for patterns and perform statistical analysis.

Qualitative data can be used in any field, but it is most commonly employed by the humanities and social sciences. This research method is popular in subjects like anthropology, history, sociology, and so on.

Qualitative Research Methods

The most common types of qualitative research are interviews, focus groups, and ethnographic research.

1. Interviews Interviews are the most common form of qualitative research. They are generally conducted on a one-to-one basis and are purely conversational. During the interview, the interviewer aims to obtain detailed answers on specific topics from the research participant.

Interviews are an effective tool for gathering data on people’s beliefs and their motivations. Skilled researchers are capable of asking useful follow-up questions to gain more data on useful topics.

Interviews can be performed face-to-face, over the phone, or via a video cbonnet application. They generally last anywhere from 30 minutes to over two hours. Face-to-face interviews grant the most opportunities for gathering data since they provide opportunities to gain extra information from things like body language.

2. Focus Groups A focus group involves gathering around six to ten people and asking them questions as a collective. Particitrousers should be chosen based on their knowledge or experience with the research question.

Focus groups ask questions centred around ‘how’, ‘wbonnet’ and ‘why’. One of the advantages of these groups is tbonnet researchers can ask an initial question and then let the ensuing conversation between group members occur naturally.

Focus groups are one of the more difficult to organise qualitative research methods since they require a large number of people with similar experiences to be available at the same time. However, focus groups are an effective way of letting research particitrousers explore concepts tbonnet are too complex for individuals to grasp effectively.

3. Ethnographic Research

Ethnographic research is the most in-depth form of qualitative research and involved studying people in their natural environment. Researchers aim to observe their audiences while remaining undetected by adapting to their audiences’ environments.

Instead of relying on people’s testimonies about their experiences, ethnographic research seeks to interpret these experiences directly as they occur. Studying audiences this way makes ethnographic research one of the slowest ways to collect data. A study of this type can require anything from a few days to a few years. Ethnographic research is also heavily dependent on the capabilities of the researcher to infer useful data from their observations.

Qualitative Research: How to analyse the Data?

Qualitative data analysis can be carried out using these three steps:

1. Develop and Apply Codes. Codes can be thought of as categories of data. Every created code needs a nastyingful title consisting of a word or short phrase. Events, behaviours, activities nastyings, and more can all be assigned one of these three types of code.

Open coding. The initial sorting of all the raw data into some kind of order. Axial coding. Creating links between categories of codes. Selective coding. Connecting categories together in order to formulate a story.

2. Identify Themes, Patterns, and Relationships

There are no universal methods for identifying patterns in qualitative research data. However, there is a set of techniques for identifying common themes and relationships with reference to the previously created codes. These are the most popular techniques for interpreting qualitative data:

• Scanning the data for words or phrases tbonnet are commonly used during responses.
• Comparing results from primary data gathering sessions with results in secondary sources and analysing the differences between the two sets.
• Scanning the data for words or phrases tbonnet were expected but did not appear. The lack of a discussion about an aspect also provides information.
• Comparing the primary research data and comparing it to phenomena from a different area using relevant metaphors and analogues.

3. Summarize the Data

The final step is connecting the research data to the hypotheses. Highlight major themes and trends by utilizing noteworthy quotations from the data as well as possible contradictions.

One of the key aspects of qualitative data is tbonnet there is no unified, formal approach to collecting and analysing data. Each research project will require its own set of methods and techniques. The key lies in examining the unique requirements of each project and adjusting the research methodology accordingly.

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Pros & cons

Who uses qualitative research.

This type of research is used by people who seek subjective answers tbonnet will allow them to explore ideas. It is often used to explore the nastying behind quantitative data. Alternatively, qualitative data can provide direction before quantitative research is utilized.

Wbonnet are the advantages of qualitative research?

Qualitative research focuses on gaining as much data as possible from a relatively small sample size. It is a more flexible approach than quantitative research since it enables particitrousers to express themselves while providing data.

Wbonnet are the main approaches of qualitative research?

The most common approaches to qualitative data gathering include action research, ethnography, grounded theory, narrative research, and phenomenological research.

How big should the sample size be?

Qualitative research studies seek between 20 and 60 particitrousers. The research results are used to provide actionable direction and cannot be quantified.

How many questions should be asked?

The number of questions depends on the research format. When leading a focus group, there should be three to eight questions tbonnet guide the discussion.

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