文章基本信息

标题：Methods for Translating Evidence-Based Behavioral Interventions for Health-Disparity Communities
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作者：Anna Maria Nápoles ; Jasmine Santoyo-Olsson ; Anita L. Stewart 等
期刊名称：Preventing Chronic Disease
印刷版ISSN：1545-1151
出版年度：2013
卷号：10
页码：1
DOI：10.5888/pcd10.130133
出版社：Centers for Disease Control and Prevention
摘要：Populations composed of racial/ethnic minorities, disabled persons, and people with low socioeconomic status have worse health than their counterparts. Implementing evidence-based behavioral interventions (EBIs) to prevent and manage chronic disease and disability in community settings could help ameliorate disparities. Although numerous models of implementation processes are available, they are broad in scope, few offer specific methodological guidance, and few address the special issues in reaching vulnerable populations. Drawing from 2 existing models, we describe 7 methodological phases in the process of translating and implementing EBIs in communities to reach these vulnerable groups: establish infrastructure for translation partnership, identify multiple inputs (information gathering), review and distill information (synthesis), adapt and integrate program components (translation), build general and specific capacity (support system), implement intervention (delivery system), and develop appropriate designs and measures (evaluation). For each phase, we describe specific methodological steps and resources and provide examples from research on racial/ethnic minorities, disabled persons, and those with low socioeconomic status. Our methods focus on how to incorporate adaptations so that programs fit new community contexts, meet the needs of individuals in health-disparity populations, capitalize on scientific evidence, and use and build community assets and resources. A key tenet of our approach is to integrate EBIs with community best practices to the extent possible while building local capacity. We discuss tradeoffs between maintaining fidelity to the EBIs while maximizing fit to the new context. These methods could advance our ability to implement potentially effective interventions to reduce health disparities.