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虚拟 BUILD 研究协作实验室:使用创新教学法进行生物医学数据科学培训,以解决有色人种本科生面临的种族主义结构和不平等压力问题。

Virtual BUILD Research Collaboratory: A biomedical data science training using innovative pedagogy to address structures of racism and inequitable stress for undergraduates of color.

机构信息

Department of Biology, San Francisco State University, San Francisco, California, United States of America.

Applied Physics and Material Sciences, Northern Arizona University, Flagstaff, Arizona, United States of America.

出版信息

PLoS One. 2024 Feb 27;19(2):e0294307. doi: 10.1371/journal.pone.0294307. eCollection 2024.

Abstract

OBJECTIVE

The unprecedented events of 2020 required a pivot in scientific training to better prepare the biomedical research workforce to address global pandemics, structural racism, and social inequities that devastate human health individually and erode it collectively. Furthermore, this pivot had to be accomplished in the virtual environment given the nation-wide lockdown.

METHODS

These needs and context led to leveraging of the San Francisco Building Infrastructure Leading to Diversity (SF BUILD) theories of change to innovate a Virtual BUILD Research Collaboratory (VBRC). The purpose of VBRC was to train Black, Indigenous, and people of color (BIPOC) students to apply their unique perspectives to biomedical research. These training activities were evaluated using a pre-post survey design that included both validated and new psychosocial scales. A new scale was piloted to measure culturally relevant pedagogy.

RESULTS

VBRC scholars increased science identity on two items: thinking of myself as a scientist (+1point, p = 0.006) and belonging to a community of scientists (+1point, p = 0.069). Overall, scholars perceived stress also decreased over VBRC (-2.35 points, p = 0.02). Post VBRC, scholars had high agency scores (μ = 11.02, Md = 12, range = 6-12, σ = 1.62) and cultural humility scores (μ = 22.11, Md = 23, range = 12-24, σ = 2.71). No notable race/ethnic differences were found in any measures.

CONCLUSIONS

Taken together, our innovative approach to data science training for BIPOC in unprecedented times shows promise for better preparing the workforce critically needed to address the fundamental gaps in knowledge at the intersection of public health, structural racism, and biomedical sciences.

摘要

目的

2020 年发生的前所未有的事件要求我们调整科学培训,以更好地培养生物医学研究人员的工作队伍,以应对全球性大流行病、结构性种族主义和社会不平等问题,这些问题单独破坏人类健康,集体损害人类健康。此外,由于全国范围的封锁,这种调整必须在虚拟环境中完成。

方法

这些需求和背景促使我们利用旧金山建立多样性基础设施(SF BUILD)变革理论来创新虚拟 BUILD 研究协作实验室(VBRC)。VBRC 的目的是培训黑人和有色人种(BIPOC)学生,让他们将自己独特的观点应用于生物医学研究。这些培训活动使用了预-后调查设计进行评估,其中包括经过验证的和新的心理社会量表。还试点了一个新的量表来衡量文化相关的教学法。

结果

VBRC 学者在两个项目上增加了科学认同感:认为自己是一名科学家(+1 分,p = 0.006)和属于一个科学家社区(+1 分,p = 0.069)。总的来说,学者们的感知压力在 VBRC 期间也有所降低(-2.35 分,p = 0.02)。VBRC 之后,学者们的能动性评分较高(μ=11.02,Md=12,范围=6-12,σ=1.62),文化谦逊评分较高(μ=22.11,Md=23,范围=12-24,σ=2.71)。在任何措施中都没有发现明显的种族/民族差异。

结论

总之,我们在前所未有的时期为 BIPOC 提供数据科学培训的创新方法表明,有希望更好地培养劳动力,以解决公共卫生、结构性种族主义和生物医学科学交叉点上知识差距的根本问题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c758/10898773/cf9b04fee8e6/pone.0294307.g001.jpg

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