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Chin MK, Đoàn LN, Russo RG, Roberts T, Persaud S, Huang E, Fu L, Kui KY, Kwon SC, Yi SS. Methods for retrospectively improving race/ethnicity data quality: a scoping review. Epidemiol Rev 2023; 45:127-139. [PMID: 37045807 DOI: 10.1093/epirev/mxad002] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 02/27/2023] [Accepted: 04/04/2023] [Indexed: 04/14/2023] Open
Abstract
Improving race and ethnicity (hereafter, race/ethnicity) data quality is imperative to ensure underserved populations are represented in data sets used to identify health disparities and inform health care policy. We performed a scoping review of methods that retrospectively improve race/ethnicity classification in secondary data sets. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, searches were conducted in the MEDLINE, Embase, and Web of Science Core Collection databases in July 2022. A total of 2 441 abstracts were dually screened, 453 full-text articles were reviewed, and 120 articles were included. Study characteristics were extracted and described in a narrative analysis. Six main method types for improving race/ethnicity data were identified: expert review (n = 9; 8%), name lists (n = 27, 23%), name algorithms (n = 55, 46%), machine learning (n = 14, 12%), data linkage (n = 9, 8%), and other (n = 6, 5%). The main racial/ethnic groups targeted for classification were Asian (n = 56, 47%) and White (n = 51, 43%). Some form of validation evaluation was included in 86 articles (72%). We discuss the strengths and limitations of different method types and potential harms of identified methods. Innovative methods are needed to better identify racial/ethnic subgroups and further validation studies. Accurately collecting and reporting disaggregated data by race/ethnicity are critical to address the systematic missingness of relevant demographic data that can erroneously guide policymaking and hinder the effectiveness of health care practices and intervention.
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Affiliation(s)
- Matthew K Chin
- Section for Health Equity, Department of Population Health, NYU Grossman School of Medicine, New York, NY 10016, United States
| | - Lan N Đoàn
- Section for Health Equity, Department of Population Health, NYU Grossman School of Medicine, New York, NY 10016, United States
| | - Rienna G Russo
- Section for Health Equity, Department of Population Health, NYU Grossman School of Medicine, New York, NY 10016, United States
| | - Timothy Roberts
- NYU Langone Health Sciences Library, NYU Grossman School of Medicine New York, NY 10016, United States
| | - Sonia Persaud
- Section for Health Equity, Department of Population Health, NYU Grossman School of Medicine, New York, NY 10016, United States
- Department of Health Policy and Management, CUNY School of Public Health & Health Policy, New York, NY 10027, United States
| | - Emily Huang
- Section for Health Equity, Department of Population Health, NYU Grossman School of Medicine, New York, NY 10016, United States
| | - Lauren Fu
- Section for Health Equity, Department of Population Health, NYU Grossman School of Medicine, New York, NY 10016, United States
- Georgetown University, Washington DC 20007, United States
| | - Kiran Y Kui
- Section for Health Equity, Department of Population Health, NYU Grossman School of Medicine, New York, NY 10016, United States
- Department of Epidemiology, Columbia Mailman School of Public Health, New York, NY 10032, United States
| | - Simona C Kwon
- Section for Health Equity, Department of Population Health, NYU Grossman School of Medicine, New York, NY 10016, United States
| | - Stella S Yi
- Section for Health Equity, Department of Population Health, NYU Grossman School of Medicine, New York, NY 10016, United States
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Boyle EA, Goldberg G, Schmok JC, Burgado J, Izidro Layng F, Grunwald HA, Balotin KM, Cuoco MS, Chang KC, Ecklu-Mensah G, Arakaki AKS, Ahmed N, Garcia Arceo X, Jagannatha P, Pekar J, Iyer M, Yeo GW. Junior scientists spotlight social bonds in seminars for diversity, equity, and inclusion in STEM. PLoS One 2023; 18:e0293322. [PMID: 37917746 PMCID: PMC10621980 DOI: 10.1371/journal.pone.0293322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Accepted: 10/10/2023] [Indexed: 11/04/2023] Open
Abstract
Disparities for women and minorities in science, technology, engineering, and math (STEM) careers have continued even amidst mounting evidence for the superior performance of diverse workforces. In response, we launched the Diversity and Science Lecture series, a cross-institutional platform where junior life scientists present their research and comment on diversity, equity, and inclusion in STEM. We characterize speaker representation from 79 profiles and investigate topic noteworthiness via quantitative content analysis of talk transcripts. Nearly every speaker discussed interpersonal support, and three-fifths of speakers commented on race or ethnicity. Other topics, such as sexual and gender minority identity, were less frequently addressed but highly salient to the speakers who mentioned them. We found that significantly co-occurring topics reflected not only conceptual similarity, such as terms for racial identities, but also intersectional significance, such as identifying as a Latina/Hispanic woman or Asian immigrant, and interactions between concerns and identities, including the heightened value of friendship to the LGBTQ community, which we reproduce using transcripts from an independent seminar series. Our approach to scholar profiles and talk transcripts serves as an example for transmuting hundreds of hours of scholarly discourse into rich datasets that can power computational audits of speaker diversity and illuminate speakers' personal and professional priorities.
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Affiliation(s)
- Evan A. Boyle
- Department of Cellular & Molecular Medicine, University of California San Diego, La Jolla, CA, United States of America
| | - Gabriela Goldberg
- Department of Cellular & Molecular Medicine, University of California San Diego, La Jolla, CA, United States of America
| | - Jonathan C. Schmok
- Department of Cellular & Molecular Medicine, University of California San Diego, La Jolla, CA, United States of America
| | - Jillybeth Burgado
- Molecular Neurobiology Laboratory, The Salk Institute for Biological Studies, San Diego, CA, United States of America
| | - Fabiana Izidro Layng
- Cancer Center, Sanford Burnham Prebys Medical Discovery Institute, San Diego, CA, United States of America
| | - Hannah A. Grunwald
- Department of Genetics, Harvard Medical School, Boston, MA, United States of America
| | - Kylie M. Balotin
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States of America
| | - Michael S. Cuoco
- Laboratory of Genetics, The Salk Institute for Biological Studies, San Diego, CA, United States of America
| | - Keng-Chi Chang
- Department of Political Science, University of California San Diego, La Jolla, CA, United States of America
| | - Gertrude Ecklu-Mensah
- Department of Pediatrics, University of California San Diego, La Jolla, CA, United States of America
| | - Aleena K. S. Arakaki
- Human Biology Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Noorsher Ahmed
- Department of Cellular & Molecular Medicine, University of California San Diego, La Jolla, CA, United States of America
| | - Ximena Garcia Arceo
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, CA, United States of America
| | - Pratibha Jagannatha
- Department of Cellular & Molecular Medicine, University of California San Diego, La Jolla, CA, United States of America
| | - Jonathan Pekar
- Department of Biomedical Informatics, University of California San Diego, La Jolla, CA, United States of America
| | - Mallika Iyer
- Graduate School of Biomedical Sciences, Sanford Burnham Prebys Medical Discovery Institute, San Diego, CA, United States of America
| | | | - Gene W. Yeo
- Department of Cellular & Molecular Medicine, University of California San Diego, La Jolla, CA, United States of America
- Stem Cell Program, University of California San Diego, La Jolla, CA, United States of America
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, United States of America
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Chicco D, Bourne PE. Ten simple rules for organizing a special session at a scientific conference. PLoS Comput Biol 2022; 18:e1010395. [PMID: 36006874 PMCID: PMC9409505 DOI: 10.1371/journal.pcbi.1010395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022] Open
Abstract
Special sessions are important parts of scientific meetings and conferences: They gather together researchers and students interested in a specific topic and can strongly contribute to the success of the conference itself. Moreover, they can be the first step for trainees and students to the organization of a scientific event. Organizing a special session, however, can be uneasy for beginners and students. Here, we provide ten simple rules to follow to organize a special session at a scientific conference.
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Affiliation(s)
- Davide Chicco
- Institute of Health Policy Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
- * E-mail:
| | - Philip E. Bourne
- School of Data Science, University of Virginia, Charlottesville, Virginia, United States of America
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