Research for all: building a diverse researcher community for the All of Us Research Program.

IF 4.7 2区 医学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS Journal of the American Medical Informatics Association Pub Date : 2024-11-14 DOI:10.1093/jamia/ocae270
Rubin Baskir, Minnkyong Lee, Sydney J McMaster, Jessica Lee, Faith Blackburne-Proctor, Romuladus Azuine, Nakia Mack, Sheri D Schully, Martin Mendoza, Janeth Sanchez, Yong Crosby, Erica Zumba, Michael Hahn, Naomi Aspaas, Ahmed Elmi, Shanté Alerté, Elizabeth Stewart, Danielle Wilfong, Meag Doherty, Margaret M Farrell, Grace B Hébert, Sula Hood, Cheryl M Thomas, Debra D Murray, Brendan Lee, Louisa A Stark, Megan A Lewis, Jen D Uhrig, Laura R Bartlett, Edgar Gil Rico, Adolph Falcón, Elizabeth Cohn, Mitchell R Lunn, Juno Obedin-Maliver, Linda Cottler, Milton Eder, Fornessa T Randal, Jason Karnes, KiTani Lemieux, Nelson Lemieux, Nelson Lemieux, Lilanta Bradley, Ronnie Tepp, Meredith Wilson, Monica Rodriguez, Chris Lunt, Karriem Watson
{"title":"Research for all: building a diverse researcher community for the All of Us Research Program.","authors":"Rubin Baskir, Minnkyong Lee, Sydney J McMaster, Jessica Lee, Faith Blackburne-Proctor, Romuladus Azuine, Nakia Mack, Sheri D Schully, Martin Mendoza, Janeth Sanchez, Yong Crosby, Erica Zumba, Michael Hahn, Naomi Aspaas, Ahmed Elmi, Shanté Alerté, Elizabeth Stewart, Danielle Wilfong, Meag Doherty, Margaret M Farrell, Grace B Hébert, Sula Hood, Cheryl M Thomas, Debra D Murray, Brendan Lee, Louisa A Stark, Megan A Lewis, Jen D Uhrig, Laura R Bartlett, Edgar Gil Rico, Adolph Falcón, Elizabeth Cohn, Mitchell R Lunn, Juno Obedin-Maliver, Linda Cottler, Milton Eder, Fornessa T Randal, Jason Karnes, KiTani Lemieux, Nelson Lemieux, Nelson Lemieux, Lilanta Bradley, Ronnie Tepp, Meredith Wilson, Monica Rodriguez, Chris Lunt, Karriem Watson","doi":"10.1093/jamia/ocae270","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong>The NIH All of Us Research Program (All of Us) is engaging a diverse community of more than 10 000 registered researchers using a robust engagement ecosystem model. We describe strategies used to build an ecosystem that attracts and supports a diverse and inclusive researcher community to use the All of Us dataset and provide metrics on All of Us researcher usage growth.</p><p><strong>Materials and methods: </strong>Researcher audiences and diversity categories were defined to guide a strategy. A researcher engagement strategy was codeveloped with program partners to support a researcher engagement ecosystem. An adapted ecological model guided the ecosystem to address multiple levels of influence to support All of Us data use. Statistics from the All of Us Researcher Workbench demographic survey describe trends in researchers' and institutional use of the Workbench and publication numbers.</p><p><strong>Results: </strong>From 2022 to 2024, some 13 partner organizations and their subawardees conducted outreach, built capacity, or supported researchers and institutions in using the data. Trends indicate that Workbench registrations and use have increased over time, including among researchers underrepresented in the biomedical workforce. Data Use and Registration Agreements from minority-serving institutions also increased.</p><p><strong>Discussion: </strong>All of Us built a diverse, inclusive, and growing research community via intentional engagement with researchers and via partnerships to address systemic data access issues. Future programs will provide additional support to researchers and institutions to ameliorate All of Us data use challenges.</p><p><strong>Conclusion: </strong>The approach described helps address structural inequities in the biomedical research field to advance health equity.</p>","PeriodicalId":50016,"journal":{"name":"Journal of the American Medical Informatics Association","volume":" ","pages":""},"PeriodicalIF":4.7000,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the American Medical Informatics Association","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1093/jamia/ocae270","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0

Abstract

Objectives: The NIH All of Us Research Program (All of Us) is engaging a diverse community of more than 10 000 registered researchers using a robust engagement ecosystem model. We describe strategies used to build an ecosystem that attracts and supports a diverse and inclusive researcher community to use the All of Us dataset and provide metrics on All of Us researcher usage growth.

Materials and methods: Researcher audiences and diversity categories were defined to guide a strategy. A researcher engagement strategy was codeveloped with program partners to support a researcher engagement ecosystem. An adapted ecological model guided the ecosystem to address multiple levels of influence to support All of Us data use. Statistics from the All of Us Researcher Workbench demographic survey describe trends in researchers' and institutional use of the Workbench and publication numbers.

Results: From 2022 to 2024, some 13 partner organizations and their subawardees conducted outreach, built capacity, or supported researchers and institutions in using the data. Trends indicate that Workbench registrations and use have increased over time, including among researchers underrepresented in the biomedical workforce. Data Use and Registration Agreements from minority-serving institutions also increased.

Discussion: All of Us built a diverse, inclusive, and growing research community via intentional engagement with researchers and via partnerships to address systemic data access issues. Future programs will provide additional support to researchers and institutions to ameliorate All of Us data use challenges.

Conclusion: The approach described helps address structural inequities in the biomedical research field to advance health equity.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
全民研究:为 "全民研究计划 "建立一个多元化的研究人员社区。
目标:美国国立卫生研究院的 "我们所有人研究计划"(All of Us)正在利用一个强大的参与生态系统模式吸引一个由 10,000 多名注册研究人员组成的多元化社区。我们描述了为建立一个吸引和支持多元化、包容性研究人员社区使用 All of Us 数据集的生态系统所采用的策略,并提供了有关 All of Us 研究人员使用量增长的指标:定义研究人员受众和多样性类别,为战略提供指导。与项目合作伙伴共同制定了研究人员参与战略,以支持研究人员参与生态系统。一个经过调整的生态模型为生态系统提供指导,以解决多层次的影响问题,支持 "我们所有 "数据的使用。来自 "我们所有 "研究人员工作台人口调查的统计数据描述了研究人员和机构使用工作台的趋势以及发表论文的数量:从 2022 年到 2024 年,约有 13 个合作伙伴组织及其次级受款人开展了外联活动、能力建设或支持研究人员和机构使用数据。趋势表明,随着时间的推移,Workbench 的注册量和使用量都在增加,其中包括在生物医学队伍中代表性不足的研究人员。来自少数民族服务机构的数据使用和注册协议也有所增加:讨论:"我们所有人 "计划通过有意识地与研究人员接触,并通过合作伙伴关系来解决系统性数据访问问题,从而建立了一个多样化、包容性和不断发展的研究社区。未来的计划将为研究人员和机构提供更多支持,以改善 "我们所有 "数据使用方面的挑战:结论:所述方法有助于解决生物医学研究领域的结构性不平等问题,从而促进健康公平。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Journal of the American Medical Informatics Association
Journal of the American Medical Informatics Association 医学-计算机:跨学科应用
CiteScore
14.50
自引率
7.80%
发文量
230
审稿时长
3-8 weeks
期刊介绍: JAMIA is AMIA''s premier peer-reviewed journal for biomedical and health informatics. Covering the full spectrum of activities in the field, JAMIA includes informatics articles in the areas of clinical care, clinical research, translational science, implementation science, imaging, education, consumer health, public health, and policy. JAMIA''s articles describe innovative informatics research and systems that help to advance biomedical science and to promote health. Case reports, perspectives and reviews also help readers stay connected with the most important informatics developments in implementation, policy and education.
期刊最新文献
Efficacy of the mLab App: a randomized clinical trial for increasing HIV testing uptake using mobile technology. Machine learning-based prediction models in medical decision-making in kidney disease: patient, caregiver, and clinician perspectives on trust and appropriate use. Research for all: building a diverse researcher community for the All of Us Research Program. Learning health system linchpins: information exchange and a common data model. Oncointerpreter.ai enables interactive, personalized summarization of cancer diagnostics data.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1