Sample size estimation in mixed methods research: balancing quantitative power and qualitative saturation

Sample size estimation in mixed methods healthcare research combines quantitative and qualitative traditions, yet guidelines remain limited. Historically, quantitative studies have used statistical power and effect size calculations to determine sample sizes. In contrast, qualitative studies have relied on concepts such as saturation, typically with much smaller, purposive samples. Mixed methods designs must reconcile these approaches. One pragmatic strategy is to set the combined sample at the larger of the two required by each component, or as the minimum that satisfies both. Theoretical frameworks and research paradigms (eg, pragmatism, transformative approaches) influence sample decisions. In practice, mixed-methods studies in biomedical fields face challenges such as coordinating distinct sampling frames, ethical review of open-ended sample sizes and balancing breadth with depth. For example, one recent study paired a large survey (N=632) with a series of focus groups (five groups of five to seven participants) to achieve thematic saturation. Key factors affecting sample size choices include study design (sequential vs concurrent, embedded vs convergent), integration strategy (eg, connecting vs building phases), research questions and logistical constraints. This article reviews the historical context, conceptual foundations, practical methods and examples of determining sample size in mixed-methods biomedical research.