Mixed methods

Why choose between numbers and narratives when you can have both? Mixed-methods research deliberately combines quantitative and qualitative data in a single study, on the logic that each covers the other's blind spots — the stats tell you what and how much, the words tell you why and how it feels.

The testable part is the logic of timing — how the two strands relate. Two families to know:

Convergent (concurrent/parallel) design: collect quantitative and qualitative data at roughly the same time, analyze each separately, then compare and merge the results to see if they converge (agree) or diverge. Picture two strands running side by side, then meeting at the end. The purpose is triangulation — corroborating findings across data types so you trust the conclusion more. Keyword: at the same time, then merge.

Sequential designs: collect the data in phases, where one builds on the other — order is everything, so watch which strand comes first:

• Explanatory sequential: QUANtitative first, then QUALitative. You get numerical results, then use interviews to explain the surprising or unclear findings. Memory hook: numbers first, then explain them with words.
• Exploratory sequential: QUALitative first, then QUANtitative. You explore a topic qualitatively (say, to build a survey or instrument), then test or generalize it with numbers. Memory hook: explore with words first, then measure.

So the whole discrimination reduces to two questions: When? (same time = convergent; phases = sequential) and, if sequential, which came first? (quant-then-qual = explanatory; qual-then-quant = exploratory).

Clinical Pearl: Convergent = collect both at once and merge (triangulation). For sequential, let the first strand name the design: explanatory = QUANT→qual (numbers, then explain them); exploratory = QUAL→quant (explore, then measure). "Explanatory" starts by explaining numbers; "exploratory" starts by exploring with words.