From separate streams to confluence: A framework for meaningful mixed methods integration in African primary care research

Mixed methods research is becoming more common in African primary care studies, yet systematic reviews show most mixed methods studies demonstrate low methodological rigour in integrating qualitative and quantitative components. This integration failure undermines addressing complex health challenges facing African primary care systems, where medical pluralism, resource constraints, and diverse disease burdens demand sophisticated methodological synthesis. This article describes a framework for achieving meaningful mixed methods integration in African primary care research contexts, addressing key challenges and providing practical strategies for transformative synthesis. Drawing on recent methodological advances, including the Mixed Methods Integration Quality Framework, systematic reviews of African mixed methods studies, and exemplar cases from primary care research, the framework integrates theoretical foundations with practical applications in resource-constrained settings. The framework encompasses: temporal considerations for integration decisions; identification of interface points; practical strategies including joint displays and data transformation; team-based approaches to synthesis; and solutions to common integration pitfalls. It addresses epistemological tensions, institutional barriers, and resource constraints in African research contexts. The framework enables researchers to move from separate methodological streams to genuine confluence, generating transformative insights transcending individual methodological contributions. By addressing context-specific challenges while maintaining methodological rigour, it supports producing nuanced understanding necessary for strengthening African health systems. This framework addresses integration challenges in African primary care research, offering practical tools for doctoral researchers and established investigators navigating complex health phenomena in resource-constrained settings.