Approaches for Measuring Inclusive Demographics Across Youth Enjoy Science Cancer Research Training Programs.
Approaches for Measuring Inclusive Demographics Across Youth Enjoy Science Cancer Research Training Programs.
复制标题
DOI：
10.15695/jstem/v5i2.12
复制
发表时间：
2022-08
期刊：
影响因子：
--
通讯作者：
中科院分区：
文献类型：
--
作者：
美国国家癌症研究所（NCI）的青年享受科学计划（YES）资助的举措，以支持癌症研究培训和职业抱负的中学通过本科生的人口在生物医学科学中代表性不足。截至2022年1月，该计划已资助全国16个机构。鉴于该计划的重点是增加癌症研究工作人员的多样性，YES学员的人口统计学特征提供了有关所服务的人群和计划有效性的重要信息。六个项目组成了一个关注受训人员人口统计的兴趣小组，并调查了所有YES受赠者的人口统计数据做法。15个方案（94%）完成了调查。调查数据采用描述性统计和主题编码进行分析。调查结果显示，相当大的变化方案的人口数据的方法，包括哪些人口进行了测量，他们是如何操作，以及何时和如何收集数据。一半的YES项目（53%）可以报告使用一致定义的学员中生物医学研究中代表性不足的人群。大多数方案介绍了为改进人口数据做法所做的努力;然而，绝大多数方案仍然面临挑战。考虑到这些发现，我们提出了包容性人口数据实践的建议，以更好地定义和保留生物医学科学中代表性不足的人群。
The National Cancer Institute’s (NCI) Youth Enjoy Science Program (YES) funds initiatives to support the cancer research training and career ambitions of middle school through undergraduate students from populations underrepresented in the biomedical sciences. The program has funded 16 institutions nationally as of January 2022. Given the program’s focus on increasing diversity within the cancer research workforce, demographic characteristics of YES trainees provide essential information about the populations being served and program effectiveness. Six programs formed an interest group focused on trainee demographics and surveyed all YES grantees about their demographic data practices. Fifteen programs (94%) completed the survey. Survey data were analyzed through descriptive statistics and thematic coding. Findings revealed considerable variability in programs’ approach to demographic data, including which demographics were measured, how they were operationalized, and when and how the data were collected. Half of YES programs (53%) could report underrepresented populations in biomedical research among trainees using consistent definitions. Most programs described efforts to improve their demographic data practices; however, challenges remained for the vast majority. In consideration of these findings, we offer recommendations for inclusive demographic data practices to better define and retain underrepresented populations in biomedical sciences.