Mekinda Megan A, Chaudhary Sunita, Vanderford Nathan L, White Karen Burns, Kennedy Linda S, Marriott Lisa K
University of Chicago Medicine Comprehensive Cancer Center, Chicago, IL.
Rutgers Cancer Institute of New Jersey, Department of Surgery, Robert Wood Johnson Medical School, New Brunswick, NJ.
J STEM Outreach. 2022 Aug;5(2). doi: 10.15695/jstem/v5i2.12. Epub 2023 Jan 23.
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.
美国国立癌症研究所（NCI）的青年享受科学计划（YES）为各项举措提供资金，以支持来自生物医学领域代表性不足人群的中学生至本科生的癌症研究培训及职业抱负。截至2022年1月，该计划已在全国范围内资助了16所机构。鉴于该计划专注于增加癌症研究人员队伍的多样性，YES学员的人口统计学特征为所服务人群及计划成效提供了重要信息。六个项目组成了一个关注学员人口统计学的兴趣小组，并就其人口数据实践对所有YES受资助者进行了调查。15个项目（94%）完成了调查。通过描述性统计和主题编码对调查数据进行了分析。研究结果显示，各项目在人口数据处理方法上存在很大差异，包括测量哪些人口统计数据、如何进行操作以及何时以及如何收集数据。一半的YES项目（53%）能够使用一致的定义报告学员中生物医学研究领域代表性不足的人群。大多数项目描述了改进其人口数据实践的努力；然而，绝大多数项目仍面临挑战。考虑到这些研究结果，我们为包容性人口数据实践提供建议，以更好地界定和留住生物医学领域代表性不足的人群。
