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.
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.
| 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 organisations 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. |
Each of the research approaches involve using one or more data collection methods. These are some of the most common qualitative methods:
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:
There are several specific approaches to analysing qualitative data. Although these methods share similar processes, they emphasise different concepts.
| Approach | When to use | Example |
|---|---|---|
| Content analysis | To describe and categorise 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. |
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.
Data collection occurs in real-world contexts or in naturalistic ways.
Detailed descriptions of people’s experiences, feelings and perceptions can be used in designing, testing or improving systems or products.
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:
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 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.
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.
Although software can be used to manage and record large amounts of text, data analysis often has to be checked or performed manually.
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:
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:
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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