Decision tree for identifying pertinent integration procedures and joint displays in mixed methods research

Aims: To propose a decision tree for identifying appropriate integration procedures and joint displays for achieving integration in mixed methods studies. Design: A methodological discussion. Data Sources: Methodological literature including mixed methods textbooks, methodological reviews and studies published in the last 10 years (2012–2022). Implications for Nursing: Mixed methods are instrumental to study complex nursing care processes and health-human phenomena. Nurse researchers can use this decision tree to choose the most appropriate integration procedures to overcome the integration challenge when designing and conducting mixed methods nursing studies. Conclusion: Integration procedures and joint displays are the most widely used methods for tackling the integration challenge in mixed methods research (MMR). The multifaceted and contingent nature of these methods are beneficial for their tailored and adapted use at the data collection, analysis, interpretation and reporting levels. The use of the most pertinent integration procedures and joint displays is critical for ensuring quality in MMR. Impact: A growing methodological literature on MMR offers a wide range of integration procedures and techniques. Therefore, choosing appropriate integration procedures and analysis methods can be challenging for nurse researchers interested in conducting mixed methods studies. A decision tree is developed outlining 14 integration procedures and their corresponding mixed methods designs, purposes and joint displays. Examples of mixed methods studies in the discipline of nursing are presented to illustrate the implementation of the integration procedures. The decision tree can serve as a straightforward methodological tool for decision making in MMR. Nurse researchers can effectively use this decision tree for research and teaching purposes. Patient or Public Contribution: No direct patient or public contribution