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AbstractPublic administration scholars have publicized the benefits of mixed methods research and exhorted researchers to embrace mixed methods research design. Despite increasing calls for and numbers of mixed methods publications, thus far there has been no rigorous assessment of the value added by mixed methods research designs. This article provides an assessment of mixed methods articles published in leading public administration and public policy journals. The authors assess methodological quality, study purpose, and research design in order to determine the added value of mixed methods research designs. Findings highlight the promise of mixed methods research in public administration and public policy. Realizing this promise will require better appreciation of the added benefits of mixed methods designs, dedicated effort to improve the qualitative component of mixed methods studies, and greater attention to integrating the qualitative and quantitative components of mixed methods studies.

This paper describes how mixed methods can improve the value and policy relevance of impact evaluations, paying particular attention to how mixed methods can be used to address external validity and generalization issues. We briefly review the literature on the rationales for using mixed methods; provide documentation of the extent to which mixed methods have been used in impact evaluations in recent years; describe how we developed a list of recent impact evaluations using mixed methods and the process used to conduct full-text reviews of these articles; summarize the findings from our analysis of the articles; discuss three exemplars of using mixed methods in impact evaluations; and discuss how mixed methods have been used for studying and improving external validity and potential improvements that could be made in this area. We find that mixed methods are rarely used in impact evaluations, and we believe that increased use of mixed methods would be useful because they can reinforce findings from the quantitative analysis (triangulation), and they can also help us understand the mechanism by which programs have their impacts and the reasons why programs fail.

This study asks how much and why the productivity of advanced practice clinicians (APCs; nurse practitioners and physician assistants) varies across community health centers (CHCs), as measured in their marginal contribution to overall patient visits. We found APCs in the 90th percentile CHCs provide about 1,840 adjusted-visits per year, whereas APCs in the 10th percentile CHCs provide about 978 adjusted-visits per year. We interviewed leadership at 14 high APC and 16 low APC productivity CHCs to elicit organizational conditions that could explain the difference. Using content analysis and then qualitative comparative analysis, we found several important conditions were more common among high productivity CHCs, including scheduling APCs and physicians for the same number of visits, parity in terms of any financial incentives, and formal education programs for new APCs during onboarding/transition to practice.

AbstractMixed methods research (MMR) designs are well suited for answering policy‐relevant questions, yet they remain underutilized in public policy and public administration scholarship. To provide a deeper understanding of the effective use of such designs, this article examines the prevalence of MMR in public policy and public administration journals, drawing a key distinction between "canonical" and "non‐canonical" MMR. Canonical mixed methods studies are characterized by (1) an explicit rationale for using mixed methods (i.e., a clear connection between methodological decisions and research questions), (2) effective integration of qualitative and quantitative strands, and (3) design transparency. We demonstrate the value of a canonical approach in public policy and public administration research by highlighting differences in quality between canonical and non‐canonical mixed methods studies. Our findings indicate that a canonical approach to mixed methods research makes positive contributions to methodological quality and knowledge development.