What Is Qualitative Research? | Methods & Examples
Qualitative research involves collecting and analyzing non-numerical data (e.g., text, video, or audio) to understand concepts, opinions, or experiences. It can be used to gather in-depth insights into a problem or generate new ideas for research.
Qualitative research is the opposite of quantitative research, which involves collecting and analyzing numerical data for statistical analysis.
Qualitative research is commonly used in the humanities and social sciences, in subjects such as anthropology, sociology, education, health sciences, history, etc.
Approaches to qualitative research
Qualitative research is used to understand how people experience the world. While there are many approaches to qualitative research, they tend to be flexible and focus on retaining rich meaning when interpreting data.
Common approaches include grounded theory, ethnography, action research, phenomenological research, and narrative research. They share some similarities, but emphasize different aims and perspectives.
|Approach||What does it involve?|
|Grounded theory||Researchers collect rich data on a topic of interest and develop theories inductively.|
|Ethnography||Researchers immerse themselves in groups or organizations to understand their cultures.|
|Action research||Researchers and participants collaboratively link theory to practice to drive social change.|
|Phenomenological research||Researchers investigate a phenomenon or event by describing and interpreting participants’ lived experiences.|
|Narrative research||Researchers examine how stories are told to understand how participants perceive and make sense of their experiences.|
Note that qualitative research is at risk for certain research biases including the Hawthorne effect, observer bias, recall bias, and social desirability bias. While not always totally avoidable, awareness of potential biases as you collect and analyze your data can prevent them from impacting your work too much.
Qualitative research methods
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.
Qualitative researchers often consider themselves “instruments” in research because all observations, interpretations and analyses are filtered through their own personal lens.
For this reason, when writing up your methodology for qualitative research, it’s important to reflect on your approach and to thoroughly explain the choices you made in collecting and analyzing the data.
Qualitative data analysis
Qualitative data can take the form of texts, photos, videos and audio. For example, you might be working with interview transcripts, survey responses, fieldnotes, or recordings from natural settings.
Most types of qualitative data analysis share the same five steps:
- Prepare and organize your data. This may mean transcribing interviews or typing up fieldnotes.
- Review and explore your data. Examine the data for patterns or repeated ideas that emerge.
- Develop a data coding system. Based on your initial ideas, establish a set of codes that you can apply to categorize your data.
- Assign codes to the data. For example, in qualitative survey analysis, this may mean going through each participant’s responses and tagging them with codes in a spreadsheet. As you go through your data, you can create new codes to add to your system if necessary.
- Identify recurring themes. Link codes together into cohesive, overarching themes.
There are several specific approaches to analyzing qualitative data. Although these methods share similar processes, they emphasize different concepts.
|Approach||When to use||Example|
|Content analysis||To describe and categorize common words, phrases, and ideas in qualitative data.||A market researcher could perform content analysis to find out what kind of language is used in descriptions of therapeutic apps.|
|Thematic analysis||To identify and interpret patterns and themes in qualitative data.||A psychologist could apply thematic analysis to travel blogs to explore how tourism shapes self-identity.|
|Textual analysis||To examine the content, structure, and design of texts.||A media researcher could use textual analysis to understand how news coverage of celebrities has changed in the past decade.|
|Discourse analysis||To study communication and how language is used to achieve effects in specific contexts.||A political scientist could use discourse analysis to study how politicians generate trust in election campaigns.|
Advantages of qualitative research
Qualitative research often tries to preserve the voice and perspective of participants and can be adjusted as new research questions arise. Qualitative research is good for:
The data collection and analysis process can be adapted as new ideas or patterns emerge. They are not rigidly decided beforehand.
- Natural settings
Data collection occurs in real-world contexts or in naturalistic ways.
- Meaningful insights
Detailed descriptions of people’s experiences, feelings and perceptions can be used in designing, testing or improving systems or products.
- Generation of new ideas
Open-ended responses mean that researchers can uncover novel problems or opportunities that they wouldn’t have thought of otherwise.
Disadvantages of qualitative research
Researchers must consider practical and theoretical limitations in analyzing and interpreting their data. Qualitative research suffers from:
The real-world setting often makes qualitative research unreliable because of uncontrolled factors that affect the data.
Due to the researcher’s primary role in analyzing and interpreting data, qualitative research cannot be replicated. The researcher decides what is important and what is irrelevant in data analysis, so interpretations of the same data can vary greatly.
- Limited generalizability
Small samples are often used to gather detailed data about specific contexts. Despite rigorous analysis procedures, it is difficult to draw generalizable conclusions because the data may be biased and unrepresentative of the wider population.
Although software can be used to manage and record large amounts of text, data analysis often has to be checked or performed manually.
Frequently asked questions about qualitative research
- What’s the difference between quantitative and qualitative methods?
Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.
Quantitative methods allow you to systematically measure variables and test hypotheses. Qualitative methods allow you to explore concepts and experiences in more detail.
- What are the main qualitative research approaches?
There are five common approaches to qualitative research:
- Grounded theory involves collecting data in order to develop new theories.
- Ethnography involves immersing yourself in a group or organization to understand its culture.
- Narrative research involves interpreting stories to understand how people make sense of their experiences and perceptions.
- Phenomenological research involves investigating phenomena through people’s lived experiences.
- Action research links theory and practice in several cycles to drive innovative changes.
- What is data collection?
Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.
- How do you analyze qualitative data?
There are various approaches to qualitative data analysis, but they all share five steps in common:
- Prepare and organize your data.
- Review and explore your data.
- Develop a data coding system.
- Assign codes to the data.
- Identify recurring themes.
The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis, thematic analysis, and discourse analysis.
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