Qualitative research asks how and why: how nurses experience moral distress, why first-generation students leave university, how a community makes sense of a new policy.
Its data are words, images and observations rather than numbers, and its strength is depth. A good qualitative study shows the reader something about people's experience that a survey could not capture.
That depth comes with responsibilities. Examiners expect you to justify your approach, explain how you chose participants, show how you moved from raw transcripts to themes, and demonstrate that your findings are trustworthy.
This guide works through each of those decisions, with examples and tables you can adapt for a proposal, thesis, dissertation or capstone.
Fitting the approach to the question
Choose a qualitative approach that fits your question (phenomenology for lived experience, grounded theory for building theory, ethnography for culture, case study for a bounded system, narrative inquiry for stories over time). Use purposive sampling until you reach saturation, collect rich data through interviews, focus groups or observation, and analyze it systematically, most often with thematic analysis. Demonstrate trustworthiness through credibility, transferability, dependability and confirmability.
When a Qualitative Design Fits
| Choose qualitative when... | Choose quantitative when... |
|---|---|
| The topic is new or poorly understood | Variables and measures are well established |
| You want to understand experiences, meanings or processes | You want to measure size, frequency or relationships |
| Context matters to the answer | You want to generalize to a population |
| Your question starts with "how" or "what is it like" | Your question starts with "how much" or "is there a difference" |
Many applied questions benefit from both. A mixed-methods design might survey staff about burnout and then interview a smaller group to understand why scores were high. If that is your plan, our quantitative research guide covers the numerical strand.
Choosing an Approach
| Approach | Focus | Typical question | Typical sample | Analysis |
|---|---|---|---|---|
| Phenomenology | Lived experience of a phenomenon | What is it like for new graduate nurses to experience their first patient death? | 6 to 15 people who share the experience | Interpretative phenomenological analysis, Colaizzi or Giorgi methods |
| Grounded theory | Developing a theory of a process | How do mid-career teachers decide to leave the profession? | 15 to 30, sampled theoretically | Open, axial and selective coding; constant comparison |
| Ethnography | Culture and shared practices | How do staff on a busy emergency unit manage informal handovers? | A group or setting, observed over time | Field notes, thick description, thematic coding |
| Case study | A bounded system in context | How did one hospital implement a sepsis protocol? | One or a few cases, multiple data sources | Within-case and cross-case analysis |
| Narrative inquiry | Stories and how people make sense of them | How do refugees narrate their educational journeys? | A small number of participants | Narrative and structural analysis |
| Generic or descriptive qualitative | Straight description of views or experiences | What are patients' views of a new telehealth clinic? | 10 to 20 | Thematic or qualitative content analysis |
Descriptive qualitative designs are common and entirely respectable in student research, especially in health and education. What matters is that your analysis matches the approach you claim; calling a study phenomenological and then analyzing it with simple content analysis invites criticism.
Sampling and Saturation
Qualitative studies sample for richness, not representativeness. Purposive sampling selects people who have experienced what you are studying; maximum variation sampling deliberately includes different perspectives; snowball sampling uses participants' contacts to reach hard-to-access groups; theoretical sampling, used in grounded theory, chooses participants based on emerging concepts.
Sample size is usually justified by saturation: the point at which new interviews add no new codes or themes relevant to the question.
In practice many interview studies with a fairly homogeneous group reach it with somewhere between 9 and 17 interviews, but this depends on the scope of the question and the diversity of participants. State your planned range, explain how you will judge saturation, and report when it was reached.
Collecting Rich Data
| Method | Strengths | Watch out for |
|---|---|---|
| Semi-structured interviews | Depth, flexibility, private setting for sensitive topics | Leading questions; interviews that become surveys |
| Focus groups | Interaction reveals shared and contested views | Dominant voices; less suitable for sensitive topics |
| Observation | Shows what people do, not just what they say | Observer effect; ethical access |
| Documents and artifacts | Unobtrusive; historical or organizational context | Documents were written for other purposes |
| Open-ended survey responses | Reach many people | Short answers with little depth |
Writing an Interview Guide
A good guide has six to ten open questions that move from easy to sensitive, each with follow-up prompts. Avoid yes/no questions and questions that assume the answer.
Leading: "How stressful was your first night shift?"
Open: "Tell me about your first night shift. What stands out for you?" Prompts: "What did you do then?" "How did that feel?" "Can you give me an example?"
Pilot the guide with one or two people, record interviews with consent, and transcribe them verbatim. Keep reflexive notes after each interview about your reactions and early ideas.
Example Interview Guide
This guide is for a descriptive study of new graduate nurses' first six months in practice. It moves from neutral to more personal questions, and each question has prompts to deepen the answer.
| Question | Prompts |
|---|---|
| Can you tell me how you came to work on this unit? | What were you expecting before you started? |
| Describe a typical shift in your first month. | What stood out? What surprised you? |
| Tell me about a time you felt unsure what to do. | What happened next? Who, if anyone, did you turn to? |
| How would you describe the support you have received? | Can you give an example of support that helped, or did not? |
| How has your confidence changed since you started? | What contributed to that change? |
| What advice would you give a nurse starting on this unit next year? | What would you want managers to know? |
| Is there anything else you would like to tell me? |
The final open question often produces some of the richest data, because participants raise what matters to them rather than to the researcher.
Thematic Analysis, Step by Step
Braun and Clarke's reflexive thematic analysis is the most widely used method in student research. Its six phases are not a strict sequence; you move back and forth between them.
| Phase | What you do | Output |
|---|---|---|
| 1. Familiarization | Read and re-read transcripts; note initial ideas | Familiarization notes |
| 2. Coding | Label meaningful segments across the whole dataset | Coded transcripts, code list |
| 3. Generating themes | Group related codes into candidate themes around a central idea | Thematic map |
| 4. Reviewing themes | Check themes against coded extracts and the full dataset | Refined themes |
| 5. Defining and naming | Write what each theme is about and what it is not | Theme definitions |
| 6. Writing up | Tell the analytic story with vivid extracts | Findings chapter |
From Code to Theme: An Example
| Extract | Code | Theme |
|---|---|---|
| "I didn't want to ask the senior nurse again, she already looked annoyed." | Fear of being a burden | Learning in silence: new graduates hide uncertainty to fit in |
| "I'd google things in the toilet so nobody saw." | Hidden help-seeking | |
| "You want to look like you've got it together." | Performing competence |
A theme is an interpretation, not a topic. "Communication" is a topic; "Learning in silence: new graduates hide uncertainty to fit in" is a theme, because it makes a claim about what is going on in the data.
Software
NVivo, ATLAS.ti and MAXQDA help you organize transcripts, apply codes, retrieve extracts and keep an audit trail. They do not analyze data for you; the interpretation is yours.
For small studies, a well-organized spreadsheet or Word document with comments works perfectly well. Whatever you use, keep dated versions of your code list so you can show how your analysis developed.
Trustworthiness: Showing Rigor
Lincoln and Guba's four criteria remain the standard way to describe rigor in qualitative research. Examiners expect you to name the strategies you used for each.
| Criterion | Means | Strategies |
|---|---|---|
| Credibility | Findings represent participants' experiences | Member checking, prolonged engagement, triangulation, peer debriefing |
| Transferability | Readers can judge whether findings apply elsewhere | Thick description of setting and participants |
| Dependability | The process is consistent and documented | Audit trail, clear procedures, dated code versions |
| Confirmability | Findings come from the data, not the researcher's bias | Reflexive journal, quotations supporting each theme, second coder |
Reflexivity deserves a paragraph of its own in your methodology. Explain your relationship to the topic and participants (for example, if you work on the unit you studied) and how you managed its influence.
Writing the Findings Chapter
- Open with a short overview and a table of themes and sub-themes.
- Give each theme its own section: define it, explain it, and support it with two or three well-chosen quotations from different participants.
- Use pseudonyms or participant codes (P1, P2), never real names.
- Show variation and contradictions within themes, not just agreement.
- Keep interpretation light and save comparison with the literature for the discussion, unless your program combines findings and discussion.
Example extract in context: Several participants described concealing gaps in their knowledge to avoid appearing incompetent. P4 recalled searching for drug information "in the toilet so nobody saw", while P9 explained that "you want to look like you've got it together". This performance of competence was strongest in the first three months and eased once participants had a trusted preceptor.
Ethics in Qualitative Research
Qualitative studies often involve sensitive topics and small samples, which makes confidentiality harder to protect. Plan how you will anonymize transcripts, store recordings securely, handle distress during interviews (including a referral route), and avoid identifying participants through unique details in quotations.
If you research your own workplace, address the power relationship and voluntary participation explicitly in your ethics application.
What a Qualitative Methodology Section Needs
- The approach and why it suits the research question, citing a methodological source.
- The setting and the participants, with inclusion and exclusion criteria.
- Sampling strategy, planned sample size and how saturation will be judged.
- Data collection: method, interview guide (in an appendix), length, recording and transcription.
- Analysis method, step by step, and any software used.
- Trustworthiness strategies for each of the four criteria.
- Reflexivity: your position and how you will manage its influence.
- Ethics: consent, confidentiality, data storage, managing distress.
Common Mistakes
- Choosing an approach by name without following its procedures.
- Themes that are really topics or interview questions ("Theme 1: Challenges").
- Too many themes (more than five or six main themes usually means they are not yet integrated).
- Quotations without analysis, or analysis without quotations.
- Claiming generalisability; qualitative findings are transferable, not statistically generalizable.
- No account of reflexivity or how saturation was judged.
Turn Your Interviews into Credible Findings
Send your transcripts, research questions and approved methodology. A qualitative researcher builds a codebook, develops themes and drafts a findings chapter with an audit trail.
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Frequently Asked Questions
There is no fixed number. Interview studies with a focused question and similar participants often reach saturation at around 9 to 17 interviews; phenomenological studies may use fewer, grounded theory more. Justify your number and explain how saturation was judged.
A code labels a single meaningful idea in the data. A theme is a broader pattern of shared meaning that brings several codes together and says something interpretive about the research question.
No. Software helps organize data but does not analyze it. Small projects can be coded in Word or a spreadsheet, as long as you keep a clear audit trail.
Not statistically. Qualitative findings are judged on transferability: give rich description of your setting and participants so readers can judge whether the findings apply to their context.
Sharing your interpretations or a summary of findings with participants to check that they reflect their experiences. It is one strategy for establishing credibility.
Yes. With your transcripts, research questions and approved methodology, a qualitative researcher can code the data, develop themes, and draft the findings chapter with supporting quotations and an audit trail.
Most semi-structured research interviews last 30 to 60 minutes. Shorter interviews rarely reach enough depth; much longer ones tire participants. Pilot your guide to check the timing.