The big idea: Primary or secondary is about WHO collected the data. Qualitative or quantitative is about WHAT KIND of data it is.
They are separate questions, so they make a grid. Primary research can be either kind, and so can secondary.
Two axes, four cells, and a real example in each. Step through to see why the two questions cannot be collapsed into one.
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The statement calls research an ongoing activity throughout the process. It is not a chapter at the start of a folder — it is what you do every time a decision cannot be made from what you already know.
| Stage | What you research there | Type |
|---|---|---|
| Empathize | Who the users are, what really happens on the ward, what already exists | Primary observation and interviews; secondary standards and statistics |
| Define the project | Anthropometric reach data, hygiene regulations, comparable products | Mostly secondary, to set numbers you cannot measure yourself |
| Ideation | How other industries solve the same problem; what materials allow | Secondary, plus product analysis of unrelated products |
| Designing a solution | Whether the model meets each criterion, with real users | Primary, and increasingly quantitative |
| Presenting | The measurements that prove each criterion was met | Primary and quantitative |
The order that saves time: Secondary first, primary second.
Find out what is already known — it is fast and free — then spend your limited hours of primary research on the questions nobody has answered for your users and your context.
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Qualitative — the why
- Reasons, feelings, priorities, and the words users use
- Explains a behaviour you have already seen
- Finds problems you had not thought to ask about
- But: cannot tell you how COMMON any of it is
Quantitative — the how many
- Times, counts, dimensions, forces, percentages
- Shows how widespread a problem is
- Lets you prove an improvement by measuring twice
- But: never explains itself
A number plus a reason: "Nine of the twelve patients could not reach the water jug, and every one of them said they would not press the call button for a drink."
The number makes it matter. The reason tells you what to change. Either half alone is a weaker finding.
What secondary data cannot do: It was collected to answer somebody else's question, about a population that is probably not yours.
Use it to set context, to find numbers you cannot measure, and to check whether what you found is normal — never as a substitute for talking to your own users.
How this is tested — distinguishing primary from secondary and qualitative from quantitative, and saying what each is for. It comes up two ways:
Paper 1 — multiple choice
- Classify a named source as primary or secondary.
- Identify which type of data a stated finding is.
Paper 2 — analysing a product
- Explain what primary and secondary research each contribute to a named product.
- Justify collecting quantitative as well as qualitative data.
The trap: Treating primary as a synonym for qualitative. A stopwatch and a tally chart are primary AND quantitative, and a published case study is secondary AND qualitative.
A team redesigning a hospital bedside table uses both primary and secondary research. Explain what each contributes, giving an example of qualitative and of quantitative data from each.
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