Purposeful sampling is widely used in qualitative research for the identification and selection of information-rich cases related to the phenomenon of interest. Although there are several different purposeful sampling strategies, criterion sampling appears to be used most commonly in implementation research. However, combining sampling strategies may be more appropriate to the aims of implementation research and more consistent with recent developments in quantitative methods. This paper reviews the principles and practice of purposeful sampling in implementation research, summarizes types and categories of purposeful sampling strategies and provides a set of recommendations for use of single strategy or multistage strategy designs, particularly for state implementation research.

Many theoretical frameworks seek to describe the dynamic process of the implementation of innovations. Little is known, however, about factors related to decisions to adopt innovations and how the likelihood of adoption of innovations can be increased. Using a narrative synthesis approach, this paper compared constructs theorized to be related to adoption of innovations proposed in existing theoretical frameworks in order to identify characteristics likely to increase adoption of innovations. The overall goal was to identify elements across adoption frameworks that are potentially modifiable and, thus, might be employed to improve the adoption of evidence-based practices. The review identified 20 theoretical frameworks that could be grouped into two broad categories: theories that mainly address the adoption process (N = 10) and theories that address adoption within the context of implementation, diffusion, dissemination, and/or sustainability (N = 10). Constructs of leadership, operational size and structure, innovation fit with norms and values, and attitudes/motivation toward innovations each are mentioned in at least half of the theories, though there were no consistent definitions of measures for these constructs. A lack of precise definitions and measurement of constructs suggests further work is needed to increase our understanding of adoption of innovations.

The Network for the Improvement of Addiction Treatment (NIATx) teaches participating treatment centers to use process improvement strategies. A cross-site evaluation monitored impacts on days between first contact and first treatment and percent of patients who started treatment and completed two, three and four units of care (i.e., one outpatient session, one day of intensive outpatient care, and one week of residential treatment). The analysis included 13 agencies that began participation in August 2003, submitted 10 to 15 months of data, and attempted improvements in outpatient (n = 7), intensive outpatient (n = 4) or residential treatment services (n = 4) (two agencies provided data for two levels of care). Days to treatment declined 37% (from 19.6 to 12.4 days) across levels of care; the change was significant overall and for outpatient and intensive outpatient services. Significant overall improvement in retention in care was observed for the second unit of care (72% to 85%; 18% increase) and the third unit of care (62% to 73%; 17% increase); when level of care was assessed, a significant gain was found only for intensive outpatient services. Small incremental changes in treatment processes can lead to significant reductions in days to treatment and consistent gains in retention.

Objectives Methodologically sound mixed methods research can improve our understanding of health services by providing a more comprehensive picture of health services than either method can alone. This study describes the frequency of mixed methods in published health services research and compares the presence of methodological components indicative of rigorous approaches across mixed methods, qualitative, and quantitative articles. Data Sources All empirical articles (n = 1,651) published between 2003 and 2007 from four top-ranked health services journals. Study Design All mixed methods articles (n = 47) and random samples of qualitative and quantitative articles were evaluated to identify reporting of key components indicating rigor for each method, based on accepted standards for evaluating the quality of research reports (e.g., use of p-values in quantitative reports, description of context in qualitative reports, and integration in mixed method reports). We used chi-square tests to evaluate differences between article types for each component. Principal Findings Mixed methods articles comprised 2.85 percent (n = 47) of empirical articles, quantitative articles 90.98 percent (n = 1,502), and qualitative articles 6.18 percent (n = 102). There was a statistically significant difference (χ2(1) = 12.20, p = .0005, Cramer's V = 0.09, odds ratio = 1.49 [95% confidence interval = 1,27, 1.74]) in the proportion of quantitative methodological components present in mixed methods compared to quantitative papers (21.94 versus 47.07 percent, respectively) but no statistically significant difference (χ2(1) = 0.02, p = .89, Cramer's V = 0.01) in the proportion of qualitative methodological components in mixed methods compared to qualitative papers (21.34 versus 25.47 percent, respectively). Conclusion Few published health services research articles use mixed methods. The frequency of key methodological components is variable. Suggestions are provided to increase the transparency of mixed methods studies and the presence of key methodological components in published reports.