Abstract
Background: Effective data integration is a daunting task in mixed methods research. Several frameworks for data integration exist, but the choice of and the technique for integration depend upon the research question and design. Innovative integration techniques continuously need to be developed to tackle the integration challenge and provide alternative ways for researchers to generate plausible mixed meta-inferences.
Objectives: The purpose of this study was to describe a new data analysis technique, tripartite analysis (TriPA), and illustrate its use in a convergent mixed-methods study.
Methods: This technique was developed based on a convergent mixed-methods study underpinned by dialectical pluralism aimed to understand Pakistani nursing students' perspectives about compassion and compassionate care and how these perspectives are consistent with the conceptualizations of compassion in nursing literature.
Results: TriPA entails analysis and integration using joint displays at three levels: case-by-case integrated analysis, separate and then merged quantitative and qualitative analysis, and comparative and integrated analysis of Levels I and II findings.
Discussion: TriPA can enable researchers to develop a more nuanced understanding of a given phenomenon through integration at various levels by identifying linkages within cases and across the whole data set and recognizing relational connections and emerging patterns.