测量治疗影响:在大规模评估研究中暴露变量的发展。

Q2 Social Sciences New Directions for Evaluation Pub Date : 2022-01-01 DOI:10.1002/ev.20509
Nicole M G Maccalla, Dawn Purnell, Heather E McCreath, Robert A Dennis, Teresa Seeman
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引用次数: 0

摘要

虽然关于如何设计严格的评估研究的指导很多,但缺乏关于如何通过构建暴露变量包括关键过程和背景测量的说明性指导。在大规模评估中获取细微的干预剂量信息尤其复杂。建筑基础设施导致多样性(BUILD)倡议是多样性项目联盟的一部分,该联盟由美国国立卫生研究院资助。它旨在增加来自代表性不足群体的个人对生物医学研究事业的参与。本章阐述了用于定义BUILD学生和教师干预,跟踪多个项目和活动的细微参与以及计算暴露强度的方法。定义标准化的暴露变量(超越简单的治疗组成员)对于以公平性为重点的影响评估至关重要。过程和由此产生的细微剂量变量都可以为大规模、多样性培训计划、以结果为重点的评估研究的设计和实施提供信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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

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.

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New Directions for Evaluation
New Directions for Evaluation Social Sciences-Education
CiteScore
2.70
自引率
0.00%
发文量
36
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