Gauging treatment impact: The development of exposure variables in a large-scale evaluation study

评估治疗效果:大规模评估研究中暴露变量的开发

阅读:2

Abstract

While guidance on how to design rigorous evaluation studies abounds, prescriptive guidance on how to include critical process and context measures through the construction of exposure variables is lacking. Capturing nuanced intervention dosage information within a large-scale evaluation is particularly complex. The Building Infrastructure Leading to Diversity (BUILD) initiative is part of the Diversity Program Consortium, which is funded by the National Institutes of Health. It is designed to increase participation in biomedical research careers among individuals from underrepresented groups. This chapter articulates methods employed in defining BUILD student and faculty interventions, tracking nuanced participation in multiple programs and activities, and computing the intensity of exposure. Defining standardized exposure variables (beyond simple treatment group membership) is crucial for equity-focused impact evaluation. Both the process and resulting nuanced dosage variables can inform the design and implementation of large-scale, diversity training program, outcome-focused, evaluation studies.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。