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Many of the failures to replicate clinical findings of treatment efficacy in more realistic field and community settings can be attributed to inappropriate research designs and other methodological shortcomings. In order to increase research designers' awareness of existing methodologies that may be better suited to answer the critical questions inherent in health services research on alcohol-related issues, the National Institute on Alcohol Abuse and Alcoholism (NIAAA) convened an expert conference with three specific goals; (1) to identify the critical issues involved in alcohol services research; (2) to develop a primer that explicated each key area; and (3) to compile the resulting primers into an accessible resource for researchers, policy makers and consumers. The 9 papers in this special supplement are the product of that conference and are organized broadly around three phases of the research process: study design and implementation, data collection and use, and the analysis and interpretation of data. A final summary paper discusses the issues and offers a synthesis of key themes as well as some direction for the future.

Like measures of outcome, measures of implementation are most useful and analytically powerful when measured at client-level and are quantitative. However, high-quality, individual-level, quantitative service utilization data can be expensive, intrusive, or otherwise impractical to obtain. Cruder data--for example, presence versus absence of a given service--are often more feasible to collect, as well as more likely to be available. Consequently, evaluators can benefit by finding ways to better exploit such data at the analysis phase to compensate for shortcomings at the collection phase. This article documents one such instance in which this was done. Specifically, it describes how quantitative, client-level implementation scales were derived from qualitative (categorical) data and used to support a cross-site synthesis of implementation and outcome analyses in a multisite evaluation. It also suggests additional scenarios in which quantitative implementation scales might be derived form qualitative services data.