flowchart TB MA["MACRO — society, national policy,<br/>global networks, environment, economy"] ME["MESO — communities, families,<br/>institutions, social groups"] MI["MICRO — the individual"] MA --> ME --> MI
Qualitative Research
Understanding the ‘why’ and ‘how’ behind health and behaviour
Dr Arun Mitra
Dept of Community and Family Medicine, AIIMS, Bibinagar
2026-06-09
Learning Objectives
- Map the types of research in healthcare and where qualitative inquiry sits
- Appreciate health research as interdisciplinary: at micro, meso & macro levels
- Describe the orientations, approaches and methods of qualitative research
- Outline how qualitative data are collected and analysed
A clinical puzzle
You run a free hypertension clinic. Your data show:
- BP control rate: only 28%
- Drug adherence: almost never complete
- Distance to clinic: < 2 km for most patients
The numbers tell you what is happening. They do not tell you why patients stop their tablets.
Two kinds of questions
Quantitative asks
- How many?
- How often?
- How strong is the association?
- Does the drug work?
Qualitative asks
- Why?
- How? In what way?
- What does it mean to them?
- What is the lived experience?
Healthcare research can be classified in several overlapping ways:
By purpose
- Basic / fundamental
- Applied
By data & logic
- Quantitative
- Qualitative
- Mixed methods
By field
- Biomedical / laboratory
- Clinical (trials, diagnostics)
- Epidemiological (observational)
- Health systems & policy
- Social & behavioural
Three methodological families
| Family | Core question | Typical designs |
|---|---|---|
| Quantitative | How many? How strong? | RCT, cohort, survey |
| Qualitative | Why? How? What meaning? | Interviews, FGDs, ethnography |
| Mixed methods | Both — numbers and meaning | Sequential / concurrent designs |
Health is more than biology
Why do people fall ill, seek care, or refuse treatment? The answers lie across many disciplines:
Social structures and inequalities — the social determinants of health. How does caste or class shape access to care?
Culture, belief and meaning — the difference between disease (biology) and illness (lived experience). What does “fever” mean in this community?
Power, policy and resources — who decides, and who benefits. Why is health spending distributed the way it is?
How diseases, institutions and ideas evolved over time. How did TB become a stigmatised disease?
Behaviour, cognition, emotion and coping. Why do people delay seeking help for symptoms?
One problem, many lenses
Take the example of TB:
| Lens | The question it asks |
|---|---|
| Biomedical | Is the regimen adequate? Drug resistance? |
| Psychological | Does the patient feel better and stop early? |
| Sociological | Do stigma or poverty drive dropout? |
| Anthropological | What does taking medicines mean to them? |
| Political / policy | Are services truly accessible and free? |
Three levels of the social world
The same problem raises different questions at each level
What each level asks
Micro · individual
- Beliefs, experiences
- Symptoms & their meaning
- Patient–doctor talk
Meso · groups
- Families, communities
- Clinics, workplaces
- Norms & networks
Macro · structure
- National policies
- Economy & inequality
- Global networks
- Environment
Example: child undernutrition:
- Micro: a mother’s feeding beliefs and practices
- Meso: the village anganwadi, food sharing within the family
- Macro: food prices, poverty, ICDS policy
Definition of Qualitative Research
A systematic, naturalistic inquiry that seeks to understand phenomena in their real-world setting, using non-numerical data (words, images, observations) to explore meaning, experience and social processes.
Key features of Qualitative Research
- Studies people in context, not in a controlled lab
- Data are text-rich: interviews, narratives, field notes
- The researcher is the main instrument of data collection
- Analysis is inductive — themes emerge from the data
- Aims for depth and understanding, not statistical generalisation
When to choose Qualitative Research?
- Explore a poorly understood problem (no good theory yet)
- Understand perceptions, beliefs, motivations and barriers
- Hear the patient / community voice in their own words
- Study sensitive or complex issues (stigma, grief, decision-making)
- Generate hypotheses that a later survey or trial can test
- Explain why an intervention worked — or failed
Orientations of Qualitative Research
Study people in their real-world settings, not artificial labs: behaviour and talk in their natural context.
The researcher is part of the research. We reflect on how our presence, identity and assumptions shape the data we get.
We care how people interpret and make sense of their world: their own words, categories and explanations.
Designs are emergent and iterative: questions and sampling adapt as understanding grows, rather than being fixed at the start.
We question the taken-for-granted — power, inequality, and whose voice gets heard or silenced.
Where Does Qualitative Research Fit In?
Done first, to map an unfamiliar area and generate hypotheses, items or tools for a later survey or trial.
Done with or after quantitative work to add depth : explaining why the numbers came out the way they did.
A complete study in its own right, answering questions side-by-side.
Qualitative vs Quantitative
| Feature | Quantitative | Qualitative |
|---|---|---|
| Question | How many? How much? | Why? How? What meaning? |
| Data | Numbers | Words, images, observation |
| Reasoning | Deductive (test theory) | Inductive (build theory) |
| Sampling | Large, random, representative | Small, purposive, information-rich |
| Sample size | Powered by statistics | Decided by saturation |
| Analysis | Statistical | Thematic / interpretive |
| Output | Prevalence, RR, p-values | Themes, narratives, models |
| Generalises to | Population (statistical) | Concepts / settings (analytic) |
Example
A measles vaccination drive misses its target
- Quantitative: coverage 61%, lowest in two urban slums
- Qualitative: interviews reveal rumours about side-effects and clinic timings that clash with daily-wage work
- Together: redesign the drive → evening camps + trusted local messengers
Methodology vs method
Two words students often confuse:
Methodology / approach
- The overall research tradition & logic
- e.g. phenomenology, grounded theory, ethnography
Method
- The specific technique for collecting data
- e.g. interview, focus group, observation
Important
One approach can use several methods. Choose the approach to fit your question, then pick methods to suit.
Approaches & Methods
Studies the lived experience of a phenomenon.
“What is it like to live with newly diagnosed diabetes?”
Builds a theory grounded in data through iterative coding.
“How do families decide to seek care for a sick newborn?”
Immersive study of a culture or group in its natural setting. “Health-seeking practices in a tribal village over 6 months.”
In-depth study of a bounded case (a clinic, an outbreak, a person).
“How did one PHC achieve 95% institutional delivery?”
Analyses the stories people tell about their lives/illness.
“Illness narratives of TB survivors.”
Approach → method → output
| Approach | Focus | Typical method | Output |
|---|---|---|---|
| Phenomenology | Lived experience | In-depth interviews | Essence of an experience |
| Grounded theory | Social process | Interviews + constant comparison | A theory |
| Ethnography | Culture | Participant observation | Cultural account |
| Case study | A bounded case | Multiple sources | In-depth case account |
| Narrative | Stories | Biographical interviews | Narrative analysis |
Common Assumptions
Myth: It’s just anecdotes and opinion.
Reality: It is systematic and transparent: explicit methods, an audit trail and quality criteria (trustworthiness). A different logic from experiments, but rigorous all the same.
Myth: It just gives one person’s biased view.
Reality: Subjectivity is acknowledged and managed : through reflexivity, triangulation and team analysis. The aim is a credible, well-grounded interpretation, not a single “fact.”
Myth: It doesn’t inform practice or policy.
Reality: It shapes guidelines and policy (WHO and NICE use qualitative evidence syntheses), explains why interventions succeed or fail, and centres the patient and community voice.
Sampling in Qualitative Research
We deliberately select people who can give the richest information.
Common strategies
- Purposive: chosen for relevance
- Maximum variation: diverse views
- Snowball: participants refer others (good for hidden groups)
- Theoretical: sample to develop emerging themes
Important
Saturation decides the sample size.
We stop interviewing when no new themes emerge: typically after ~8–15 rich interviews, but it varies.
Data Collection
| Method | Best for | Typical size |
|---|---|---|
| In-depth interview (IDI) | Personal, sensitive experiences | 1 person |
| Focus group discussion (FGD) | Group norms, shared views, debate | 6–10 people |
| Participant observation | What people do vs say | A setting |
| Document / media analysis | Records, policies, social media | — |
Data Analysis
flowchart LR A[Transcripts] --> B[Codes<br/>label segments] B --> C[Categories<br/>group similar codes] C --> D[Themes<br/>patterns of meaning] D --> E[Interpretation<br/>answer the question]
This is iterative: you move back and forth, not in a straight line.
What coding looks like
“I stop the tablets when I feel fine. Buying them every month is hard when there’s no work, and the clinic is only open when I’m at the market.”
| Quote segment | Code |
|---|---|
| “stop the tablets when I feel fine” | Symptom-based adherence |
| “Buying them every month is hard… no work” | Cost / livelihood barrier |
| “clinic only open when I’m at the market” | Access / timing barrier |
Ethics
- Informed consent — including consent to audio-record
- Confidentiality & anonymity — remove identifiers, use pseudonyms
- Sensitive topics — risk of distress; have a referral plan
- Power imbalance — doctor vs patient, researcher vs community
- No coercion — voluntary participation, freedom to withdraw
- Data security — recordings and transcripts stored safely
Summary
- Health research spans many types & disciplines, at micro, meso and macro levels: qualitative inquiry runs across them
- Qualitative research explains the why & how through meaning, experience and context
- Its orientations: naturalism, reflexivity, meaning, flexibility, critique
- Data are words; sampling is purposive; size is set by saturation
- Analysis = coding → categories → themes; quality = trustworthiness
- It is scientific, rigorous and policy-relevant: the partner of quantitative research, not its rival
References
- Braun V, Clarke V. Using thematic analysis in psychology. Qual Res Psychol. 2006;3(2):77–101.
- Lincoln YS, Guba EG. Naturalistic Inquiry. Sage; 1985.
- Tong A, Sainsbury P, Craig J. COREQ: a 32-item checklist for interviews and focus groups. Int J Qual Health Care. 2007;19(6):349–357.
- Pope C, Mays N. Qualitative Research in Health Care. 4th ed. Wiley-Blackwell; 2020.
- Green J, Thorogood N. Qualitative Methods for Health Research. 4th ed. Sage; 2018.
Questions?
Thank You
