Mixed methods research offers powerful tools for investigating complex processes and systems in health and health care. This article describes integration principles and practices at three levels in mixed methods research and provides illustrative examples. Integration at the study design level occurs through three basic mixed method designs—exploratory sequential, explanatory sequential, and convergent—and through four advanced frameworks—multistage, intervention, case study, and participatory. Integration at the methods level occurs through four approaches. In connecting, one database links to the other through sampling. With building, one database informs the data collection approach of the other. When merging, the two databases are brought together for analysis. With embedding, data collection and analysis link at multiple points. Integration at the interpretation and reporting level occurs through narrative, data transformation, and joint display. The fit of integration describes the extent the qualitative and quantitative findings cohere. Understanding these principles and practices of integration can help health services researchers leverage the strengths of mixed methods.

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Achieving Integration in Mixed Methods Designs—Principles and Practices

In this study, we develop a model of science identity to make sense of the science experiences of 15 successful women of color over the course of their undergraduate and graduate studies in science and into science-related careers. In our view, science identity accounts both for how women make meaning of science experiences and how society structures possible meanings. Primary data included ethnographic interviews during students' undergraduate careers, follow-up interviews 6 years later, and ongoing member-checking. Our results highlight the importance of recognition by others for women in the three science identity trajectories: research scientist; altruistic scientist; and disrupted scientist. The women with research scientist identities were passionate about science and recognized themselves and were recognized by science faculty as science people. The women with altruistic scientist identities regarded science as a vehicle for altruism and created innovative meanings of ''science,'' ''recognition by others,'' and ''woman of color in science.'' The women with disrupted scientist identities sought, but did not often receive, recognition by meaningful scientific others. Although they were ultimately successful, their trajectories were more difficult because, in part, their bids for recognition were disrupted by the interaction with gendered, ethnic, and racial factors. This study clarifies theoretical conceptions of science identity, promotes a rethinking of recruitment and retention efforts, and illuminates various ways women of color experience, make meaning of, and negotiate the culture of science. 2007 Wiley Periodicals, Inc. J Res Sci Teach 44: 1187-1218, 2007.

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Understanding the Science Experiences of Successful Women of Color: Science Identity as an Analytic Lens.

One of the most important steps in the qualitative research process is analysis of data. The purpose of this article is to provide elements for understanding multiple types of qualitative data analysis techniques available and the importance of utilizing more than one type of analysis, thus utilizing data analysis triangulation, in order to understand phenomenon more fully for school psychology research and beyond. The authors describe seven qualitative analysis tools: methods of constant comparison, keywords-in-context, word count, classical content analysis, domain analysis, taxonomic analysis, and componential analysis. Then, the authors outline when to use each type of analysis. In so doing, the authors use real qualitative data to help distinguish the various types of analyses. Furthermore, flowcharts and tables are provided to help delineate when to choose each type of analysis. Finally, the role of computer-assisted software in the qualitative data-analytic process is discussed. As such, use of the analyses outlined in this article should help to promote rigor in qualitative research.

An Array of Qualitative Data Analysis Tools: A Call for Data Analysis Triangulation.

Despite the abundance of published material on conducting focus groups, scant specific information exists on how to analyze focus group data in social science research. Thus, the authors provide a ...

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A Qualitative Framework for Collecting and Analyzing Data in Focus Group Research

Implementation science is growing in importance among funders, researchers, and practitioners as an approach to bridging the gap between science and practice. We addressed three goals to contribute to the understanding of the complex and dynamic nature of implementation. Our first goal was to provide a conceptual overview of the process of implementation by synthesizing information from 25 implementation frameworks. The synthesis extends prior work by focusing on specific actions (i.e., the “how to”) that can be employed to foster high quality implementation. The synthesis identified 14 critical steps that were used to construct the Quality Implementation Framework (QIF). These steps comprise four QIF phases: Initial Considerations Regarding the Host Setting, Creating a Structure for Implementation, Ongoing Structure Once Implementation Begins, and Improving Future Applications. Our second goal was to summarize research support for each of the 14 QIF steps and to offer suggestions to direct future research efforts. Our third goal was to outline practical implications of our findings for improving future implementation efforts in the world of practice. The QIF’s critical steps can serve as a useful blueprint for future research and practice. Applying the collective guidance synthesized by the QIF to the Interactive Systems Framework for Dissemination and Implementation (ISF) emphasizes that accountability for quality implementation does not rest with the practitioner Delivery System alone. Instead, all three ISF systems are mutually accountable for quality implementation.

http://nrepp.samhsa.gov/Docs/The%20Quality%20Implementation%20Framework_%20A%20Synthesis%20of%20Critical%20Steps%20in%20the%20Implementation%20Process%20.pdf

Joseph A. Maxwell

Papers

Qualitative Research Design: An interactive approach, 2nd ed.