Approaches for Measuring Inclusive Demographics Across Youth Enjoy Science Cancer Research Training Programs.

Journal of STEM outreach Pub Date : 2022-08-01 Epub Date: 2023-01-23 DOI:10.15695/jstem/v5i2.12
Megan A Mekinda, Sunita Chaudhary, Nathan L Vanderford, Karen Burns White, Linda S Kennedy, Lisa K Marriott
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Abstract

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.

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衡量青年包容性人口的方法享受科学癌症研究培训计划。
国家癌症研究所(NCI)的青年享受科学计划(YES)资助了支持癌症研究培训和中学本科生的职业抱负的举措,这些本科生来自生物医学科学领域代表性不足的人群。截至2022年1月,该项目已资助了全国16个机构。鉴于该项目的重点是增加癌症研究人员的多样性,YES受训人员的人口统计特征提供了有关所服务人群和项目有效性的基本信息。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受赠人的人口统计数据实践。15个项目(94%)完成了调查。调查数据通过描述性统计和主题编码进行分析。研究结果显示,项目处理人口统计数据的方法存在相当大的可变性,包括测量哪些人口统计数据,如何操作这些数据,以及何时以及如何收集数据。一半的YES项目(53%)可以使用一致的定义报告受训人员在生物医学研究中的代表性不足的人群。大多数项目描述了改进人口统计数据实践的努力;然而,绝大多数人仍然面临挑战。考虑到这些发现,我们提出了包容性人口统计数据实践的建议,以更好地定义和保留生物医学科学中代表性不足的人群。
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