Qualitative and mixed methods studies
Why this level?
This hierarchy places a design by the kind of question it answers: intervention, diagnostic accuracy, prognosis, aetiology and screening intervention. This design answers a different kind of question, so no level on this scale describes it. That is a statement about the scale, not about the quality of the evidence such a study can produce. NHMRC 2009 sourceThe hierarchy rates quantitative designs against a quantitative question. A qualitative study asks a different kind of question, and a ladder built to compare effect estimates has no rung that describes it. That is not a statement about rigour: COREQ and SRQR are how this work is appraised.
What question does this help answer?
Why something happens, how people understand it, what gets in the way, and what an intervention actually looks like from inside. These are questions of mechanism and meaning, not frequency.
It is not a smaller quantitative study
The sampling is purposive: participants are chosen because of what they can say about the phenomenon, not to represent a population. So the findings are not estimates and do not have margins of error, and reporting them as percentages of a small purposive sample gives a false impression of both precision and generalisability.
Choose an approach that fits the question
Name the qualitative approach and why it suits the question, before recruitment. A descriptive approach stays close to what participants report about an experience or service. Grounded theory aims to build an explanation of a social process from the data. Phenomenology examines the meaning of a lived experience. Ethnography studies practices and culture in their setting. The approach shapes who is sampled, how data are collected and how the analysis proceeds, so a label chosen afterwards to describe what was done does not supply that coherence.
Plan the sample
- Define the phenomenon and who can speak to it, then choose a purposive strategy: maximum variation to capture a range of views, criterion sampling for people meeting a defined condition, or theoretical sampling that follows the emerging analysis.
- Plan separately for perspectives that matter, such as patients, carers and staff, rather than assuming one sample covers them all.
- Estimate an initial sample from information power: a narrow aim, a highly specific sample, established theory, rich dialogue and a focused analysis each reduce the number of participants needed.
- Decide in advance how you will judge that data collection can stop. Saturation has several meanings, so define the one being used rather than simply claiming it.
- Record who declined or could not be reached, because who is missing shapes what the findings can say.
Mixed methods
A mixed methods study combines qualitative and quantitative components, and the design must say how. Sequential exploratory work uses qualitative findings to build a measure. Sequential explanatory work uses qualitative work to explain a quantitative result. Convergent designs run both and compare. The integration is the point, and a study that reports two separate results side by side without integrating them has done two studies rather than one.
Key assumptions and design requirements
- The sampling strategy is purposive and stated, with the reasoning for who was included.
- The analytic approach is named (thematic analysis, framework, grounded theory, content analysis) and applied as that method describes.
- Coding involves more than one analyst, or the single analyst's reflexivity is addressed explicitly.
- Saturation, if claimed, is defined in advance rather than asserted after recruitment stopped.
- The research team's relationship to participants is disclosed, since it shapes what people say.
Why Mallard may recommend it
Mallard may point here when a description asks about barriers, experience, acceptability or process, or when a planned trial needs to understand a mechanism before it can be designed.
How it is sized
Mallard does not produce a sample size for a qualitative study, and a power calculation would be meaningless here. Adequacy is judged by information power: how specific the sample is, how strong the theory is, how rich the dialogue is, and how focused the analysis is. State the expected range with its reasoning, and be willing to revise it.
What to watch out for
Qualitative findings are not weak quantitative findings and should not be reported with counts as though they were. Sampling is purposive rather than representative, so generalising a theme to a population is a category error, and saturation should be defined in advance rather than declared after the fact.
Clinical example
Question: Why is a discharge medicines service under-used? Design: Purposively sample pharmacists, ward nurses and patients across contrasting wards, interview to a prespecified saturation definition, and analyse thematically with two coders and a documented reflexivity statement.
How to report it
COREQ is the guideline for interview and focus-group studies, and SRQR covers qualitative research more broadly. They ask who the researchers were and what they brought to the work, how participants were selected and approached, how the analysis reached its categories, and enough data for a reader to judge the interpretation for themselves. Where the study mixes qualitative and quantitative methods, which this page also covers, GRAMMS is the guideline for the mixed-methods design, with COREQ or SRQR still applied to the qualitative strand. A reporting guideline is not a design manual: use it to make the study transparent, not as a substitute for careful design. Check the target journal's own requirements as well, which this page cannot know.
- Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups (opens in a new tab) · Int J Qual Health Care · doi 10.1093/intqhc/mzm042
- Standards for reporting qualitative research: a synthesis of recommendations (opens in a new tab) · Acad Med · doi 10.1097/ACM.0000000000000388
- Sample Size in Qualitative Interview Studies: Guided by Information Power (opens in a new tab) · Qual Health Res · doi 10.1177/1049732315617444
- Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research (opens in a new tab) · Adm Policy Ment Health · doi 10.1007/s10488-013-0528-y
- Saturation in qualitative research: exploring its conceptualization and operationalization (opens in a new tab) · Qual Quant · doi 10.1007/s11135-017-0574-8
- The quality of mixed methods studies in health services research (opens in a new tab) · J Health Serv Res Policy · doi 10.1258/jhsrp.2007.007074