Mixed methods (MM) involve combining qualitative (QUAL) and quantitative (QUAN) methods in program evaluation, primary research, and literature review (Creswell & Plano Clark, 2011;Johnson, Onwuegbuzie, & Turner, 2007;Pluye & Hong, 2014;. They are being increasingly used, specifically in health sciences. Over the years, several strategies to integrate QUAL and QUAN phases, results, and data have been proposed but rarely conceptualized and never tested in a comprehensive manner (Greene, 2008). For each MM researcher and teacher, one of the challenges is to plan, conduct, and report simply and clearly what are the applied specific MM strategies and their combinations. As a contribution for addressing this issue, the purpose of this article is to propose and test a conceptual framework of the combinations of strategies that are used in primary MM research.In this article, to be considered MM, studies had to meet the following criteria (Creswell & Plano Clark, 2011): (a) at least one QUAL method and one QUAN method are combined; (b) each method is used rigorously in accordance to the generally accepted criteria in the area (or tradition) of research invoked (e.g., ethnography and randomized controlled trial); and (c) the combination of the methods is carried out at minimum through a MM design (defined a priori, or emerging) and the integration of the QUAL and QUAN phases, results, and data. The QUAL and QUAN methods can be also combined (but not necessarily) with regard to the data collection (mixed instrumentation), the literature review (mixed studies review justifying the MM research questions and design), and the MM team members' interpretations of sciences in terms of epistemology, ontology, teleology, and methodology (hereafter termed worldview).
ABSTRACTMixed methods (MM) are increasingly popular. Researchers integrate qualitative (QUAL) and quantitative (QUAN) methods (e.g., research questions, data collections and analyses, and results). Several integration strategies have been proposed, but their conceptualization is usually design-driven, or fragmented, or not empirically tested. This is challenging for planning and conducting MM studies, and for training graduate students. Based on the methodological literature, we developed a conceptual framework including types of integration and practical strategies, and possible combinations. Then, we tested this framework using 93 health-related 2015 MM studies with a method-detailed description, which illustrated all types of combinations. Our work contributes to advance methodological knowledge on MM via (a) a call for better reporting healthrelated MM studies, and (b) a tested conceptualisation comprising 3 types of integration and 9 specific strategies, which explain current and future possibilities for combining strategies to integrate QUAL and QUAN phases, results, and data.