测量治疗影响:大规模评估研究中的暴露变量的发展
Nicole M G Maccalla1, Dawn Purnell1, Heather E McCreath1
1University of California Los Angeles, Los Angeles, California, USA.
概括
本研究介绍了在多样性培训计划中测量细微干预暴露的方法. 定义暴露变量是公平评估大规模举措的关键.
科学领域:
- 生物医学研究培训培训
- 项目评估 项目评估
- 多样性和包容性倡议 多样性和包容性倡议
背景情况:
- 严格的评估研究设计得到了充分的记录,但缺乏将过程和上下文措施纳入暴露变量的方法.
- 在大规模评估中准确地捕捉干预剂量存在重大挑战.
- 国家卫生研究院资助的"致使多样性形成的建筑基础设施" (BUILD) 计划旨在增强代表性不足的群体在生物医学研究职业生涯中的参与.
研究的目的:
- 阐明在BUILD倡议中定义干预措施的方法.
- 详细介绍追踪多个项目和活动中细微参与的方法.
- 提出一个计算干预暴露强度的框架.
主要方法:
- 开发超出简单组分配的标准化暴露变量.
- 追踪学生和教师参与各种BUILD计划和活动的情况.
- 计算微妙的剂量指标来量化干预暴露强度.
主要成果:
- 定义和测量细微干预暴露的既定方法.
- 展示了在大型计划中捕获详细参与数据的复杂性.
- 创建了可计算的暴露变量,反映了不同程度的参与.
结论:
- 定义标准化,细微的风险变量对于以股权为重点的影响评估至关重要.
- 开发的方法和变量可以为未来的多样性培训计划的设计和实施提供信息.
- 这种方法增强了对大规模多样性和包容性倡议的以结果为中心的评估.
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