Methoden vergleichen

	Quantitativ-dominantes Mixed-Methods-Design für Interventionen	Multiphase Mixed Methods Design
Fachgebiet	Forschungsdesign	Forschungsdesign
Familie	Process / pipeline	Process / pipeline
Entstehungsjahr	2007–2011 (codified in Creswell & Plano Clark editions)	2007 (first edition of Designing and Conducting Mixed Methods Research)
Urheber	Creswell & Plano Clark (intervention MMD); weighting framework systematized in mixed methods typologies	John W. Creswell & Vicki L. Plano Clark
Typ	Mixed methods research design	Mixed methods research design
Wegweisende Quelle	Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). Sage. ISBN: 978-1483344379	Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). Sage. ISBN: 978-1483substitute
Aliasnamen	QUAN-dominant intervention MMD, quantitatively weighted intervention mixed methods, QUAN+qual intervention design, quantitative-priority intervention mixed methods	multiphase design, multiproject mixed methods, programmatic mixed methods, multistage mixed methods
Verwandt	6	6
Zusammenfassung	Quantitative-dominant intervention mixed methods design embeds a qualitative component within a predominantly quantitative intervention study — typically a randomized controlled trial or quasi-experiment — where the quantitative strand carries the primary weight in determining efficacy, while the qualitative strand explains the processes, mechanisms, or participant experiences that illuminate why and how the intervention works.	The multiphase mixed methods design is a sustained research program in which quantitative and qualitative strands are combined across three or more sequential phases — or across multiple related projects — to address a central program objective. Each phase builds on the prior phase's findings, making the design well-suited to long-term evaluation, intervention development, and large-scale program assessment where a single data-collection cycle cannot fully address the complexity of the research problem.