6
Implementation and Accountability
[This] conversation has been going on for a long time without much resolution—that suggests that perhaps we’re asking the wrong question or that there are some important structural barriers in the practices of science that have prevented us from making progress. Standardization of population descriptors is a misguided goal. It creates a false sense of comparability across data sets, and it might actually also be disrespectful to participants. Instead of standardization of population descriptors, I think we ought to spend much more time in our genome science collecting data about culture, social experience, social status, and environmental exposures. I think if we have good measures of those things, we’re much more likely to have replicable genome science.
—Pilar Ossorio, testimony to the committee
in a public session on April 4, 2022
INTRODUCTION
As was noted in Chapter 1, this is not the first report, publication, or conference proceedings to recommend ways to change how descent-associated population descriptors should be used in genetics and genomics. Nor should it be the final word in an evolving field. There are a few elements, though, that make this report distinct. One is the political climate in which it is proffered. In the time following the historic social events of 2020, there has arisen an urgency in research and health care institutions to examine, address, and change the structural racism that is embedded in many systems (Bailey et al., 2020; Churchwell et al., 2020). Another is the committee’s attempt to examine the entire research ecosystem, from funders, research-
ers, and their institutions to study participants, journals, and professional societies. A third defining feature of the report is the subject of this chapter. The committee strongly believes that for this report to change both individual and collective behavior, the recommendations need to be actionable, the implementation processes should contain incentives, and the people and institutions involved need to be held accountable on an ongoing basis and in meaningful ways to demonstrate progress toward specific goals.
IMPLEMENTATION ACROSS THE GENOMICS RESEARCH ECOSYSTEM
There are many players in the genomics research ecosystem. To make the changes recommended in this report, there is a need for partnership among all of these interested parties to support the researchers during this process of implementation; working together across the research enterprise offers part of the solution. Moreover, there is a shared responsibility for making these changes across an interdisciplinary research community. Without support for these changes throughout the community, the burden of implementation will likely fall disproportionately on individual researchers, who typically lack the personnel and funding resources to adhere to noncompulsory guidelines in a sustainable fashion.
The recommendations and the strategies to implement them presented in Chapters 4 and 5 are directed primarily to researchers. In this chapter, the focus is on the other relevant parties who are equally responsible in effecting lasting change in how population descriptors are used in genetics and genomics research. It will be evident that all of these recommendations and strategies also involve or affect research scientists. To fully implement these recommendations as well as create structures and systems that enable and incentivize researchers to collect and include environmental data and engage communities, support from institutions and funding agencies is needed to facilitate collaborations between genetics researchers and researchers in other disciplines such as the social sciences.
Study Participants and their Communities
While study participants are essential to a research project probing human genetics or genomics, these individuals or communities typically have little say in how their data are used and reported, though that is changing with platforms such as LunaDNA1 and Genetic Alliance Registry2 that place people at the center of the decision making about when and how their
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1https://www.lunadna.com/ (accessed January 3, 2023).
2https://geneticalliance.org/registries/ga-registry (accessed January 3, 2023).
health information is used. Traditionally, individual study participants often are given a limited list of population labels to choose from, and these often fail to capture how they identify themselves (Kaplan and Bennett, 2003), as evidenced by the increase in the checking of the “some other race” box or of multiple boxes in the current census categories (Roman, 2022). Moreover, research staff responsible for recruitment may guess or assume population labels for the study participants (Borrell et al., 2021) to avoid having missing data. And even if participants self-identify to their own satisfaction, researchers may later combine them into categories with labels that no longer capture the identity that participants would have selected themselves (Hunt and Megyesi, 2008). These issues violate the guiding principles of respect, beneficence, and equity and justice (see Chapter 3).
To improve this misalignment of identities, researchers working in close partnership with individual study participants, and especially communities, can work to better understand how individuals identify themselves and, in some cases, why these are the descriptors or group labels they will use. When individuals are empowered to identify themselves on their terms, and have input into the research study design, they are more likely to have trust and investment in the study and its outcomes (CTSA Consortium, 2011). A more person-centered model is adopted in some community-based studies investigating population genetics, because in these studies, getting to know the community is already understood and accepted as a necessary prerequisite to collecting data. Without this partnership, some communities may refuse to participate, as they have in the past. A person-centered model is not typically the case in larger studies (e.g., long-term studies of health and disease) and becomes especially problematic when data from multiple studies, often collected at different times, are merged for analysis. It should be noted that community engagement may add additional costs as well as burden to participants and the community, specifically of their time, which could reduce participation by diverse communities.
In some situations, though, researchers may have to limit the number of population categories they can use for their study in order to have groups that are large enough to yield statistically robust answers, or to properly address a specific question within the study with adequate statistical power (IOM, 2009). In these cases, consent should be sought to aggregate individuals in particular ways, with a dialogue between researchers and participants as to why it may involve altering their population identities. Clear information should be provided to study participants about the study design, methods, objectives, and possible outcomes and impact. This information should be supplied by the researchers or, perhaps in larger studies, by the funding agency. Respect for participants can also be evoked by recognizing and including mechanisms in a study for nondisclosure of data as well as the possibility for participants to exit the study or revoke consent.
Conclusion 6-1. Forging partnerships between researchers and study participants and their communities is critically important and has benefits beyond building trust and mutual respect between relevant parties. By working collaboratively with study participants, researchers will better understand the identities, cultures, traditions, and practices of communities, thus improving the understanding of the types of information that should and could be collected for a strong study where the outcomes could, in turn, have the ability to improve the health of the communities who participate.
Funders of Genetics and Genomics Research
Funding agencies and organizations can play a major role in changing how population descriptors are used. For example, they could establish requirements to follow the recommendations in this report for all funding requests, reviews, and decisions. When developing funding concepts, requests for information or proposals could promote the recommendations and encourage adherence to them. One tool to assist researchers as they prepare their proposals would be a checklist, such as the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA),3 Consolidated criteria for Reporting Qualitative research (COREQ),4 and Consolidated Standards of Reporting Trials (CONSORT)5 checklists used for systematic reviews, qualitative research, and clinical trials, respectively. A simple and clear checklist can be a useful tool for changing behavior and being proactive about avoiding commonly made errors (e.g., World Health Organization (WHO) surgical safety checklist).6 A sample of what a checklist might contain for researchers using population descriptors in genetics research is in Box 6-1. As with other checklists, the intent is to make clear to researchers at the beginning of the study development or application process what they need to include. It promotes transparency and enables researchers to carefully evaluate the role and need for specific population descriptors in their proposal. A variation of the checklist is a decision tree, another tool for assisting the researcher in evaluating whether to use population descriptors, and if so, which ones are appropriate to use based on the objectives of their research and the characteristics of their data, among other features (see Appendix D and Chapter 5 for more detail). A checklist or decision tree
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3https://prisma-statement.org/prismastatement/Checklist.aspx (accessed January 3, 2023).
4https://cdn.elsevier.com/promis_misc/ISSM_COREQ_Checklist.pdf (accessed January 3, 2023).
5https://www.consort-statement.org/media/default/downloads/CONSORT%202010%20Checklist.pdf (accessed January 3, 2023).
6https://www.who.int/teams/integrated-health-services/patient-safety/research/safe-surgery/tool-and-resources (accessed January 3, 2023).
supports the guiding principles of validity, reproducibility, and replicability (see Chapter 3).
Funding agencies can further support this report’s recommendations during the review of grant applications. For example, currently, researchers are not required to explain why a certain category of population descriptors was chosen and how they will be treated in statistical analysis, nor is this systematically evaluated in the study section. Desirable change would be greatly motivated if a study section were to consider how researchers intend to use population descriptors during the procedural checks for human research protocols. To assist both researchers and reviewers, a table or form would permit a more objective determination as to whether a proposal has addressed the necessary issues around using and reporting population descriptors and can be equally applied across all proposals. A similar form could assist in the poststudy reporting process, since many times the anticipated labels may change depending on the sample composition and how individuals self-identify.
One of the challenges for researchers in adopting the report’s recommendations is that the Office of Management and Budget (OMB) Directive
15 has confounded the way that population descriptors are used and reported in genetics and genomics research (see the section “Population Classification Schemes in Genetics and Genomics Research” in Chapter 1).
Conclusion 6-2. It would be a helpful step in implementing this report’s recommendations if funding agencies instructed researchers that they do not have to use the OMB categories to group individuals in their scientific work. Researchers need to know that, in general, they only have to use these categories when reporting study participant demographics of those they recruited. That is, the need and rationale for reporting to funding agencies is distinct from how researchers design their study and analyze their data. In the latter cases, researchers should use the most appropriate population descriptors for the questions they are probing instead of using the OMB categories reflexively.
Professional Societies and Research Journals
Over the past several decades, a number of professional societies have developed statements or guidelines on race, ethnicity, human diversity, and multicultural practices. Statements, such as the one on race published by the American Association of Physical Anthropologists (AAPA, 1996), were intended for their members and colleagues and not specifically focused on genetics. During the Office of Management and Budget’s review of Directive 15, the American Anthropological Association (AAA) submitted a set of recommendations in response to the OMB–requested comment period for the recommendations from the Interagency Committee (AAA, 1997) based on the similar scientific thinking espoused by the AAPA the previous year. The next year, the AAA prepared a statement on race for its members (AAA, 1998). Twenty years ago, the American Psychological Association (APA) prepared an extensive set of guidelines intended to assist their members and fellow psychologists in improving their cross-cultural interactions (APA, 2003). Recognizing that the concepts of race, ethnicity, and culture are dynamic, several of these societies have updated their guidelines recently (APA, 2017, 2019; Fuentes et al., 2019). Other organizations, like the American Medical Association (AMA), have followed suit (AMA, 2020a,b).
In every case, the guidelines have been aspirational and intended to encourage their professional colleagues to become educated and informed about how they view race, ethnicity, ancestry, and other descriptors, and to be aware of how they use these descriptors and associated language in their research, practice, writing, and conversation. For example, the AMA recommends “that clinicians and researchers focus on genetics and biology, the experience of racism, and social determinants of health when describing risk factors for disease” (AMA, 2020b). However, these factors are conflated.
In some cases, the guidelines of a professional society inform the guidelines or standards of their journals. For example, American Psychologist, the APA’s flagship journal, requires authors to use “bias-free and community-driven language” (APA, 2022), which is explained in the APA Publication Manual. Genetics in Medicine, which is an official journal of the American College of Medical Genetics and Genomics, provides author guidelines for reporting on diversity, race, ethnicity, sex, and gender.7 Likewise, the Journal of the American Medical Association (JAMA) has detailed guidance on reporting on race and ethnicity (Flanagin et al., 2021). JAMA’s guidelines have been adopted by other publications, such as the American Journal of Human Genetics (B. Korf, AJHG, personal communication, September 16, 2022).
The difficulty these societies and their journals face is how to get members and authors to abide by these guidelines. Journals can require that certain types of language be used or avoided, and they can memorialize that in their style guides and have their editors enforce the standards (e.g., Nature Human Behavior)8 (Flanagin et al., 2021). But this is insufficient. What is necessary is an understanding of the underlying issues during study design and long before data analyses: the moment of publication is far too late.
As was suggested to funding agencies to facilitate the submission of grant applications, journals could create a checklist focused on population descriptors and how researchers should present them in the methods and results sections, in tables and figures, and what explanatory information is needed concerning why certain descriptors were chosen for or left out of an analysis (for example, see Box 6-2). Journals could come together to adopt the principles and recommendations in this report through organizations that are set up to change the publishing culture such as the Committee on Publication Ethics. This committee provides both best practices and education modules to set a new standard for adopting ethical publishing practices across a variety of disciplines internationally.
Among their other uses, publications are an essential measure of a researcher’s productivity. As such, “getting published” can be a powerful incentive, so journal editors have leverage that could encourage researchers, and perhaps other entities within the research ecosystem such as research institutions, to change how they understand and use descent-associated population descriptors. For example, a journal could adopt the recommendations in this report by creating editorial review checks to ensure that authors whose papers are sent out for peer review have adhered to these recommendations.
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7https://www.elsevier.com/journals/genetics-in-medicine/1098-3600/guide-for-authors (accessed January 3, 2023).
8https://www.nature.com/nathumbehav/editorial-policies/ethics-and-biosecurity#race-ethnicity-racism (accessed January 3, 2023).
Research Institutions
The climate and infrastructure of research institutions greatly influence the ways in which research is carried out within their organizations. Thus, universities, private research centers, and government agencies are key partners in assisting researchers as they strive to implement this report’s recommendations and adhere to its guiding principles.
This report was created by an interdisciplinary team of geneticists and social scientists. This combination of expertise and points of view has been essential in developing the recommendations, guiding principles, and strategies for implementation. The committee feels strongly that research in human genetics and genomics would benefit from collaborations between social scientists (such as anthropologists, sociologists, and demographers), historians, ethicists, epidemiologists, and biologists. Institutions can facilitate these interactions through the development of infrastructure that makes collaborations easy to start, supporting them financially, and encouraging researchers to form and sustain collaborations. There are several examples that could serve as models: Northwestern University’s Institute for Policy
Research’s Cells to Society–The Center on Social Disparities and Health9; UCLA’s Institute for Society and Genetics10; Duke University’s Office of Interdisciplinary Studies11; and University of Wisconsin-Madison’s Center for Demography of Health and Aging,12 to name a few.
One of the confounding issues in studying trait variation is distinguishing between genetic and environmental factors (see Chapter 2). Geneticists focus on understanding the causes and consequences of human genetic variation. Factors that interfere with accurately determining these effects create barriers to optimal genetics research that may be addressed through study design and analysis. Geneticists and researchers using genetic and genomic tools may lack the social and environmental data they need to analyze the most appropriate nongenetic variables. They may also lack the training and expertise to design and carry out a study that will collect those data. Collaborations among geneticists, epidemiologists, demographers, and other social scientists can therefore improve study design and statistical analysis of the data to better differentiate between genetic and nongenetic factors and their effects.
Researchers, from undergraduate students to principal investigators, could benefit from continuing education on the bias and misuse of population descriptors in scientific and medical research. New York University (NYU), for example, developed a workshop in 2021 called Race and Racism in the Sciences, hosted by the departments of biology and psychology and the NYU Center for Neural Science.13 It is compulsory for some graduate students and strongly recommended for all other members of these three communities. Funding agencies could collaborate with research institutions on developing and holding training and continuing education about the proper use of population descriptors.
In addition, researchers could be required to complete training about the use of population descriptors before engaging in research with human participants and before being granted access to data sets. NIH’s All of Us Research Program requires training on “responsible and ethical research” prior to using the Researcher Workbench (All of Us, 2022). These trainings could contain information about the labels that are used within the data set, explaining how they can or cannot be used within research projects using the data set.
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9https://www.ipr.northwestern.edu/what-we-study/social-disparities-and-health/ (accessed January 3, 2023).
10https://socgen.ucla.edu/ (accessed January 3, 2023).
11https://sites.duke.edu/interdisciplinary/ (accessed January 3, 2023).
12https://cdha.wisc.edu/ (accessed January 3, 2023).
13https://as.nyu.edu/departments/cns/events/EventDescriptions/WorkshopRace.html (accessed January 3, 2023).
The committee encourages the development of computational tools able to compare studies and identify differences in the metadata related to population descriptors. The tools could then assist a researcher in deciding whether merging the data sets would corrupt the metadata and enable them to use the merged data to address a question of interest. In addition, research on frameworks for the development and dissemination of genetic data resources, such as allele frequencies, should prioritize the use of genetic similarity, rather than other population descriptors (race, ethnicity, geography), which may be poor proxies for genetic backgrounds that form the basis of these groupings. The committee hopes that educating investigators on the use of population descriptors will facilitate the development of these computational and other methodological tools.
Journalists, Media, and Researchers: An Important Partnership for Clearly Communicating Research Findings
Sometimes scientific findings create new knowledge that is relevant not only to specialized audiences but also to the general population. Conveying that information accurately and effectively to the lay public is the purview of science journalists and other science communication specialists. As the genomics research ecosystem evolves in how it uses descent-associated population descriptors, and as genetics and genomics research advances common understanding of human health and disease and becomes more popular, partnerships between science journalists and basic and clinical scientists will be ever more important. One way to facilitate this partnership is for the press offices of research institutions to receive training on best practices for the use of population descriptors, since it is typically the people in these offices who interact directly with scientists to translate their research findings and technical terminology into language that is understandable by the general public while retaining the accuracy and nuances of the science. In addition, researchers should be trained to produce easily understandable summaries of their research findings that properly convey the subtleties of using population descriptors in genomics research. These summaries could be provided to newspaper and other popular media reporters when they write about relevant research findings (Takezawa et al., 2014).
For this report to reach full penetrance in society and for its recommendations to have a lasting effect, what this committee has written will need to weave its way into the general consciousness alongside the many other conversations about diversity, inclusion, equity, and justice. It would thus be beneficial if journalists and reporters became familiar with both this report’s main messages and the committee’s rationale for its decisions. Broadly disseminating this report’s messages through their many different
media outlets will be a powerful way to effect change and drive implementation of the committee’s recommendations.
RECOMMENDATIONS
The effectiveness of the following recommendations in advancing trust in and improving the quality of results from genomics research will depend upon how they are implemented. Many aspects of the current systems that fund, support, evaluate, and reward genomics research may impede rather than facilitate their implementation. Changing these systems will, over time, lead to more effective implementation of these recommendations.
Funding agencies, research institutions (including associated institutional review boards and other activities with research participants), research journals, professional societies, and lay media professionals should evaluate their processes and structures related to the use of population descriptors in genomics research and report to their communities whether or not they are facilitating the recommendations in this report. A plan should be provided, along with a timeline, to change processes and structures that are not aligned with these recommendations. If processes and structures cannot be changed, this should be made transparent, along with a justification as to why the changes cannot be made and how this misalignment will be mitigated in the context of this committee’s report recommendations.
Recommendation 9. Funding agencies, research institutions, research journals, and professional societies should offer tools widely to their communities to facilitate the implementation of these recommendations; these tools should be publicly available, especially when they are supported by public funds. Such tools could include:
- educational modules for inclusion in human research protection training14;
- manuscript submission and review guidelines;
- grant submission and review criteria;
- training and education of trainees at all levels;
- opportunities for continuing education for researchers; and
- informatics tools, such as data structure standards for sharing labels and labeling procedures used within a study.
Recommendation 10. Research institutions and funding agencies should embed incentives for fostering interdisciplinary collaboration among researchers with different areas of expertise, including genetics and ge
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14 Often called “human subjects” research training. See also https://www.hhs.gov/ohrp/education-and-outreach/human-research-protection-training/index.html (accessed January 3, 2023).
nomics, social sciences, epidemiology, and community-based research, to facilitate the inclusion of environmental measures and the engagement of diverse communities in genomics research. Funding agencies and research institutions should develop strategies to encourage and reward such collaborations.
The recommendations in this report have been developed from the committee’s collective experience researching, writing about, and using population descriptors. But there is more that can be done to understand how population descriptors are used in genetics and genomics research and the effects that these descriptors have in medicine and in health disparities studies.
Recommendation 11. Given the persistent need to address this dynamic, high-stakes component of genomics research, funders and research institutions should create new initiatives to advance the study and methods development of best practices for population descriptor usage in genetics and genomics research, including the public availability of resources.
Recommendation 12. Key partners, including funding agencies, research institutions, and scientific journals, should ensure that policies and procedures are aligned with these recommendations and invest in developing new strategies to support implementation when needed.
MECHANISMS OF ACCOUNTABILITY
The ability of this report to effect durable change rests on three principles: actionable recommendations, implementation procedures applied effectively across the genomics ecosystem, and, importantly, accountability mechanisms. Accountability serves multiple purposes. First, the committee recognizes that the usefulness of today’s population descriptors in research will not necessarily be valid in the future. Thus, there will be a need for a body to periodically evaluate current population descriptors and recommend changes based on both sociological and scientific data and ethical and empirical principles. In addition, this or a second oversight body needs sufficient powers to monitor and facilitate the implementation of the report’s recommendations. For example, this group could monitor what journals are doing; convene journal editors and publishers to formulate consistent, reasonable guidelines; and help them standardize their instructions to authors, so researchers recognize that all of the journals are following identical standards. This body could perform similar facilitative functions for funding agencies, and assist agencies, research institutions, and professional societies
in developing training as well as ways to measure the effectiveness of the training over time. To be respected, trusted, and effective, it would be best for this body (or these bodies) to comprise people from all of the relevant parties within the genetics and genomics ecosystem. Perhaps the National Institutes of Health’s Advisory Committee on Research on Women’s Health or the Novel and Exceptional Technology and Research Advisory Committee15 could serve as examples on which such a body could be modeled.
Recommendation 13. Because the understanding of population descriptors in genomics research is continuously evolving, responsibility for periodic reevaluation of these recommendations should be overseen by effective, multidisciplinary advisory groups. Such advisory groups could:
- periodically reevaluate established best practices on the use of descent-associated population descriptors to ensure they reflect the current state of the science and ongoing commitment to ethical and empirical principles;
- advise funders and other relevant parties on the use of population descriptors and their implementation;
- facilitate the coordination of international best practice sharing;
- provide a venue for input from the broader community, including research participants; and
- monitor and measure changes adopted by funders, researchers, journals, societies, and other relevant parties based on the uptake of best practices identified.
PARTING THOUGHTS
Despite the many recommendations, guidelines, and strategies promoting the ethically and empirically sound use of descent-associated population descriptors, there has been relatively little change in how any entities within the genetics and genomics research ecosystem use these descriptors or require them to be used. It will take a concerted and interdisciplinary effort by all interested parties, patience, and a good bit of time to reach a place where the proper use and reporting of population descriptors is routine. Individual researchers will bear the brunt of these changes, so it will be essential for their institutions and funders, along with journal editors and professional societies, to form a supportive and adequately resourced network that makes this transition feasible. The recommendations in this report will need to be implemented broadly and consistently, by all of the relevant parties,
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15https://orwh.od.nih.gov/about/advisory-committees/advisory-committee-on-research-on-womens-health (accessed January 3, 2023).
to generate lasting change. The committee hopes that by having identified the roles that each party plays and by developing mechanisms that facilitate transparency and good communication among all interested parties, the scale of the tasks will be manageable to meet the needs of this evolving field.
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