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Diversity and inclusion for the All of Us research program: A scoping review.

ABSTRACT: The All of Us Research Program (All of Us) is a national effort to accelerate health research by exploring the relationship between lifestyle, environment, and genetics. It is set to become one of the largest research efforts in U.S. history, aiming to build a national resource of data from at least one million participants. All of Us aims to address the need for more diversity in research and set the stage for that diversity to be leveraged in precision medicine research to come. This paper describes how the program assessed demographic characteristics of participants who have enrolled in other U.S. biomedical research cohorts to better understand which groups are traditionally represented or underrepresented in biomedical research. We 1) reviewed the enrollment characteristics of national cohort studies like All of Us, and 2) surveyed the literature, focusing on key diversity categories essential to the program's enrollment aims. Based on these efforts, All of Us emphasizes enrollment of racial and ethnic minorities, and has formally designated the following additional groups as historically underrepresented: individuals-with inadequate access to medical care; under the age of 18 or over 65; with an annual household income at or below 200% of the federal poverty level; who have a cognitive or physical disability; have less than a high school education or equivalent; are intersex; identify as a sexual or gender minority; or live in rural or non-metropolitan areas. Research accounting for wider demographic variability is critical. Only by ensuring diversity and by addressing the very barriers that limit it, can we position All of Us to better understand and tackle health disparities.

SUBMITTER: Mapes BM

PROVIDER: S-EPMC7329113 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Diversity and inclusion for the All of Us research program: A scoping review.

Mapes Brandy M BM Foster Christopher S CS Kusnoor Sheila V SV Epelbaum Marcia I MI AuYoung Mona M Jenkins Gwynne G Lopez-Class Maria M Richardson-Heron Dara D Elmi Ahmed A Surkan Karl K Cronin Robert M RM Wilkins Consuelo H CH Pérez-Stable Eliseo J EJ Dishman Eric E Denny Joshua C JC Rutter Joni L JL

PloS one 20200701 7

The All of Us Research Program (All of Us) is a national effort to accelerate health research by exploring the relationship between lifestyle, environment, and genetics. It is set to become one of the largest research efforts in U.S. history, aiming to build a national resource of data from at least one million participants. All of Us aims to address the need for more diversity in research and set the stage for that diversity to be leveraged in precision medicine research to come. This paper des ...[more]

PMID: 32609747

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Project description:Background: Research on disparities in traumatic injury has not been well characterized, limiting understanding of gaps in research and development of successful interventions. We conducted a scoping review to identify and synthesize research on disparities in intentional and unintentional traumatic injuries. Methods: The review was guided by PRISMA Extension for Scoping Reviews. PubMed, PsycINFO, Web of Science, and CINAHL and systematic reviews from 2007 to 2017 were searched. Eligible articles were peer reviewed; conducted in the United States; and reported on clearly defined physical trauma and disparity, defined by Cochrane PROGRESS-Plus criteria. One reviewer assessed article titles and a second reviewer validated the inclusion with a random sample. Abstract and full-text review by two reviewers determined final inclusion. Results: Of 7382 unique articles screened, 653 articles were included; inter-rater agreement was high (K=0.995). Studies reported on disparities in the acute hospital setting (104) or postacute/rehabilitation (86), with fewer focused on prevention (57) and policy development (6). Research methods used were quantitative (593) with 25 intervention studies, qualitative (45), qualitative/quantitative (7), and community-based participatory research (8). Age ranges of included studies were all ages (124), adults (318), pediatric/youth/adolescents (172), and older adults (40). Racial disparities were most commonly measured (439 studies); 38 created a white/nonwhite binary. Other commonly measured disparities were place of residence (122), insurance (111 studies), gender (89), age (75), and socioeconomic status measures (61). Disparities were noted in all of the categories. Studies commonly aggregated all types of traumatic injuries (129) or all types of violence (105). Conclusions: The extant injury literature lacks research on prevention and policy to address disparities. Many studies aggregated types of trauma and patient groups, preventing an understanding of distinctions between groups and potential interventions. Intervention and community-based research strategies were limited. Future research can better specify measurement of understudied equity categories, trauma types and intent, and racial groups.

Project description:IntroductionArtificial intelligence (AI) has the potential to improve efficiency and quality of care in healthcare settings. The lack of consideration for equity, diversity and inclusion (EDI) in the lifecycle of AI within healthcare settings may intensify social and health inequities, potentially causing harm to under-represented populations. This article describes the protocol for a scoping review of the literature relating to integration of EDI in the AI interventions within healthcare setting. The objective of the review is to evaluate what has been done on integrating EDI concepts, principles and practices in the lifecycles of AI interventions within healthcare settings. It also aims to explore which EDI concepts, principles and practices have been integrated into the design, development and implementation of AI in healthcare settings.Method and analysisThe scoping review will be guided by the six-step methodological framework developed by Arksey and O'Malley supplemented by Levac et al, and Joanna Briggs Institute methodological framework for scoping reviews. Relevant literature will be identified by searching seven electronic databases in engineering/computer science and healthcare, and searching the reference lists and citations of studies that meet the inclusion criteria. Studies on AI in any healthcare and geographical settings, that have considered aspects of EDI, published in English and French between 2005 and present will be considered. Two reviewers will independently screen titles, abstracts and full-text articles according to inclusion criteria. We will conduct a thematic analysis and use a narrative description to describe the work. Any disagreements will be resolved through discussion with the third reviewer. Extracted data will be summarised and analysed to address aims of the scoping review. Reporting will follow the Preferred Reporting Items for Systematic Reviews and Meta-analyses Extension for Scoping Reviews. The study began in April 2022 and is expected to end in September 2023. The database initial searches resulted in 5,745 records when piloted in April 2022.Ethics and disseminationEthical approval is not required. The study will map the available literature on EDI concepts, principles and practices in AI interventions within healthcare settings, highlight the significance of this context, and offer insights into the best practices for incorporating EDI into AI-based solutions in healthcare settings. The results will be disseminated through open-access peer-reviewed publications, conference presentations, social media and 2-day workshops with relevant stakeholders.

Project description:PurposeRestorative Justice (RJ) as a practice and mindset is growing within academic medicine and health care. The authors aim to categorize the extent to which RJ training and practices have been researched, explored, and applied within health care, medicine, and academic contexts.MethodsIn July 2021, the authors conducted a scoping literature review, searching four databases for peer-reviewed articles and book chapters discussing RJ. Authors also used bibliography searches and personal knowledge to add relevant work. Reviewers independently screened article titles and abstracts, assessing the full texts of potentially eligible articles with inclusion and exclusion criteria. From each included article, authors extracted the publication year, first author's country of origin, specific screening criteria met, and the depth with which it discussed RJ.ResultsFrom 599 articles screened, 39 articles, and books were included (published 2001-2021). Twenty-five (64%) articles discussed RJ theory with few describing application practices with substantial depth. Ten (26%) articles only referenced the term "restorative justice" and seven (18%) discussed legal applications in health care. Fifty-four percent were from outside the United States. Articles tended to describe RJ uses to address harm and often missed the opportunity to explore RJ's capacity to proactively build community and culture that helps prevent harm.ConclusionsRJ in health care is a rapidly expanding field that offers a framework capable of building stronger communities, authentically preventing and responding to harm, inviting radical inclusion of diverse participants to build shared understanding and culture, and ameliorate some of the most toxic and unproductive hierarchical practices in academics and medicine. Most literature calls to RJ for help to respond to harm, although there are very few well-designed and evaluated implementations. Investment in RJ practices holds significant promise to steer our historically hierarchical, "othering" and imperfect systems to align with values of justice (vs. punishment), equity, diversity, and inclusion.

Project description:INTRODUCTION:The rising popularity of social media, since their inception around 20 years ago, has been echoed in the growth of health-related research using data derived from them. This has created a demand for literature reviews to synthesise this emerging evidence base and inform future activities. Existing reviews tend to be narrow in scope, with limited consideration of the different types of data, analytical methods and ethical issues involved. There has also been a tendency for research to be siloed within different academic communities (eg, computer science, public health), hindering knowledge translation. To address these limitations, we will undertake a comprehensive scoping review, to systematically capture the broad corpus of published, health-related research based on social media data. Here, we present the review protocol and the pilot analyses used to inform it. METHODS:A version of Arksey and O'Malley's five-stage scoping review framework will be followed: (1) identifying the research question; (2) identifying the relevant literature; (3) selecting the studies; (4) charting the data and (5) collating, summarising and reporting the results. To inform the search strategy, we developed an inclusive list of keyword combinations related to social media, health and relevant methodologies. The frequency and variability of terms were charted over time and cross referenced with significant events, such as the advent of Twitter. Five leading health, informatics, business and cross-disciplinary databases will be searched: PubMed, Scopus, Association of Computer Machinery, Institute of Electrical and Electronics Engineers and Applied Social Sciences Index and Abstracts, alongside the Google search engine. There will be no restriction by date. ETHICS AND DISSEMINATION:The review focuses on published research in the public domain therefore no ethics approval is required. The completed review will be submitted for publication to a peer-reviewed, interdisciplinary open access journal, and conferences on public health and digital research.

Project description:BackgroundData provenance refers to the origin, processing, and movement of data. Reliable and precise knowledge about data provenance has great potential to improve reproducibility as well as quality in biomedical research and, therefore, to foster good scientific practice. However, despite the increasing interest on data provenance technologies in the literature and their implementation in other disciplines, these technologies have not yet been widely adopted in biomedical research.ObjectiveThe aim of this scoping review was to provide a structured overview of the body of knowledge on provenance methods in biomedical research by systematizing articles covering data provenance technologies developed for or used in this application area; describing and comparing the functionalities as well as the design of the provenance technologies used; and identifying gaps in the literature, which could provide opportunities for future research on technologies that could receive more widespread adoption.MethodsFollowing a methodological framework for scoping studies and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines, articles were identified by searching the PubMed, IEEE Xplore, and Web of Science databases and subsequently screened for eligibility. We included original articles covering software-based provenance management for scientific research published between 2010 and 2021. A set of data items was defined along the following five axes: publication metadata, application scope, provenance aspects covered, data representation, and functionalities. The data items were extracted from the articles, stored in a charting spreadsheet, and summarized in tables and figures.ResultsWe identified 44 original articles published between 2010 and 2021. We found that the solutions described were heterogeneous along all axes. We also identified relationships among motivations for the use of provenance information, feature sets (capture, storage, retrieval, visualization, and analysis), and implementation details such as the data models and technologies used. The important gap that we identified is that only a few publications address the analysis of provenance data or use established provenance standards, such as PROV.ConclusionsThe heterogeneity of provenance methods, models, and implementations found in the literature points to the lack of a unified understanding of provenance concepts for biomedical data. Providing a common framework, a biomedical reference, and benchmarking data sets could foster the development of more comprehensive provenance solutions.

Dataset Information

Diversity and inclusion for the All of Us research program: A scoping review.

Publications

Diversity and inclusion for the All of Us research program: A scoping review.

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