Guide
Qualitative research
Qualitative research investigates how people understand and experience the world, using non-numerical data such as words and images to build rich, contextual insight rather than to measure or quantify.
The step most authors miss
Doing CRediT right? Don’t stop at the statement.
A CRediT statement credits you inside one paper. The recognition CRediT was built for happens when those roles are tied to you, persistently. Sign in with your ORCID — free — and claim your CRediT contributions on casrai.org, the home of the standard. They become a verified, portable part of your identity, not a line that disappears into one PDF.
Free: claim your contributions, then export a journal-ready CRediT statement, schema.org structured data, JATS XML, CSV or BibTeX — and preview your public profile. A membership publishes that profile publicly and verifies the journals you serve.
What qualitative research is
Qualitative research is a family of approaches that seeks to understand social phenomena from the perspective of the people who experience them. Rather than counting or measuring, it works with non-numerical data — spoken and written words, images, observed behaviour and documents — to interpret meaning, motivation and context. The logic is typically inductive: researchers begin with open questions and let patterns, concepts and theory emerge from the data, instead of testing a fixed hypothesis defined in advance. Studies are usually conducted in naturalistic settings, where participants live and work, so that behaviour and talk are understood in their real context. Because the goal is depth rather than breadth, qualitative research draws on smaller, purposively selected samples and treats the researcher as an active instrument of enquiry whose interpretation is part of the analytic process.
Defining characteristics
Several features distinguish qualitative work. Sampling is purposive — participants are chosen because they can illuminate the question, not to represent a population statistically. Designs are flexible and emergent, evolving as understanding deepens rather than being fixed before data collection. Data are rich and detailed, capturing nuance, ambiguity and the participant’s own language. The researcher’s reflexivity — awareness of how their background and assumptions shape interpretation — is treated as a strength to be examined, not a flaw to be eliminated. Crucially, rigour is judged not by statistical validity but by trustworthiness. Lincoln and Guba’s widely used framework sets out four criteria: credibility (findings ring true and are well grounded), transferability (enough context is given for readers to judge relevance elsewhere), dependability (the process is consistent and auditable) and confirmability (interpretations are anchored in the data, not the researcher’s bias).
Common methods of data collection
Qualitative researchers draw on a recognised toolkit. Semi-structured and in-depth interviews use a flexible guide of open questions, allowing the researcher to follow the participant’s account and probe for meaning. Focus groups bring several participants together so that interaction and disagreement surface shared understandings and points of tension. Participant observation and ethnography involve sustained immersion in a setting — a clinic, a classroom, an organisation — to record practices and culture through detailed fieldnotes. Document and content analysis examines existing texts, policies, records or media to understand how meaning is constructed and communicated. Many studies, especially case studies, combine several of these to build a layered, well-corroborated account of a bounded situation.
Analysing qualitative data
Analysis turns raw words and observations into structured insight. The most common approach is thematic analysis: researchers read and re-read the data, apply codes (short labels) to meaningful segments, then group codes into themes that capture patterns across the dataset. Coding can be inductive (driven by the data) or deductive (guided by an existing framework). Grounded theory goes further, using systematic, iterative coding and constant comparison to generate new theory directly from the data. Other traditions — narrative analysis, discourse analysis, interpretative phenomenological analysis — suit particular questions about stories, language or lived experience. Throughout, researchers keep an audit trail and often use techniques such as member checking and triangulation across sources to strengthen credibility and confirmability.
Strengths, limitations and when to use it
The strengths of qualitative research are depth and context: it explains how and why people act, surfaces unexpected factors, gives voice to participants and is well suited to new or poorly understood topics. Its limitations are the mirror image. Findings are not generalisable in the statistical sense — small, purposive samples cannot estimate prevalence — and the researcher’s subjectivity, while managed through reflexivity and trustworthiness criteria, means another analyst might emphasise different themes. Analysis is also time-intensive. Choose qualitative methods when you need to explore meaning, experience, process or context; to develop concepts, theory or hypotheses; or to interpret a phenomenon in its setting. Where you instead need to measure how much, how many or test relationships across a population, a quantitative design fits better — and a mixed methods approach can bridge the two, pairing rich understanding with measurable scope.
Key facts
At a glance
- Definition: studies meaning, experience and context using non-numerical data
- Logic: inductive — concepts and theory emerge from the data
- Sampling: smaller, purposive samples in naturalistic settings
- Methods: interviews, focus groups, observation, ethnography, document analysis
- Analysis: thematic analysis, coding, grounded theory
- Rigour: trustworthiness — credibility, transferability, dependability, confirmability
Common questions
FAQ
Is qualitative research subjective?+
It openly acknowledges the researcher’s role in interpreting data, which makes it interpretive rather than purely objective. Quality is not judged by removing the researcher but by managing their influence through reflexivity and Lincoln and Guba’s trustworthiness criteria — credibility, transferability, dependability and confirmability — supported by audit trails, triangulation and member checking.
How many participants does qualitative research need?+
There is no fixed number. Samples are purposive and usually small — often a handful to a few dozen — because the aim is depth, not statistical representativeness. Many researchers continue collecting data until they reach saturation, the point at which new participants add little fresh insight to the emerging themes.
What is the difference between qualitative and quantitative research?+
Qualitative research explores meaning and context through non-numerical data and inductive analysis, while quantitative research measures variables numerically to test hypotheses and quantify relationships using larger, representative samples and statistics. They answer different questions, and mixed methods research deliberately combines both to gain depth and measurable scope together.
