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Research studies involving human subjects require collection of and reporting on demographic data related to race and ethnicity. However, existing practices lack standardized guidelines, leading to misrepresentation and biased inferences and conclusions for underrepresented populations in research studies. For instance, sometimes there is a misconception that self-reported racial or ethnic identity may be treated as a biological variable with underlying genetic implications, overlooking its role as a social construct reflecting lived experiences of specific populations. In this manuscript, we use the We All Count data equity framework, which organizes data projects across seven stages: Funding, Motivation, Project Design, Data Collection, Analysis, Reporting, and Communication. Focusing on data collection and analysis, we use examples – both real and hypothetical – to review common practice and provide critiques and alternative recommendations. Through these examples and recommendations, we hope to provide the reader with some ideas and a starting point as they consider embedding a lens of justice, equity, diversity, and inclusivity from research conception to dissemination of findings.

Medical researchers are increasingly prioritizing the inclusion of underserved communities in clinical studies. However, mere inclusion is not enough. People from underserved communities frequently experience chronic stress that may lead to accelerated biological aging and early morbidity and mortality. It is our hope and intent that the medical community come together to engineer improved health outcomes for vulnerable populations. Here, we introduce Health Equity Engineering (HEE), a comprehensive scientific framework to guide research on the development of tools to identify individuals at risk of poor health outcomes due to chronic stress, the integration of these tools within existing healthcare system infrastructures, and a robust assessment of their effectiveness and sustainability. HEE is anchored in the premise that strategic intervention at the individual level, tailored to the needs of the most at-risk people, can pave the way for achieving equitable health standards at a broader population level. HEE provides a scientific framework guiding health equity research to equip the medical community with a robust set of tools to enhance health equity for current and future generations.

Racism shapes the distribution of the social determinants of health (SDoH) along racial lines. Racism determines the environments in which people live, the quality of housing, and access to healthcare. Extensive research shows racism in its various forms negatively impacts health status, yet few studies and interventions seriously interrogate the role of racism in impacting health. The C2DREAM framework illuminates how exposure to racism, in multiple forms, connects to cardiovascular disease, hypertension, and obesity. The goal of the C2DREAM framework is to guide researchers to critically think about and measure the role of racism across its many levels of influence to better elucidate the ways it contributes to persistent health inequities. The conceptual framework highlights the interconnectedness between forms of racism, SDoH, and the lifecourse to provide a greater context to individual health outcomes. Utilizing this framework and critically contending with the effects of racism in its multiple and cumulative forms will lead to better research and interventions.

The hidden curriculum (HC), or implicit norms and values within a field or institution, affects faculty at all career stages. This study surveyed affiliates of a junior faculty training program (n = 12) to assess the importance of HC topics for junior faculty, mentors, and institutional leaders. For non-diverse junior faculty and their mentors, work-life balance, research logistics, and resilience were key HC topics. Coping with bias and assertive communication were emphasized for diverse junior faculty and mentors. Institutional norms and vision were essential for leaders, while networking was important for all groups. Future research should explore HC needs and potential interventions.

This paper outlines the development, deployment and use, and testing of a tool for measuring and improving healthcare researcher embeddedness – i.e., being connected to and engaged with key leverage points and stakeholders in a health system. Despite the widely acknowledged importance of embeddedness for learning health systems and late-stage translational research, we were not aware of useful tools for addressing and improving embeddedness in scholar training programs. We developed the MN-LHS Embeddedness Tool covering connections to committees, working groups, leadership, and other points of contact across four domains: patients and caregivers; local practice (e.g., operations and workflows); local institutional research (e.g., research committees and agenda- or initiative-setting groups); and national (strategic connections within professional groups, conferences, etc.). We used qualitative patterns and narrative findings from 11 learning health system training program scholars to explore variation in scholar trajectories and the embeddedness tool’s usefulness in scholar professional development. Tool characteristics showed moderate evidence of construct validity; secondarily, we found significant differences in embeddedness, as a score, from baseline through program completion. The tool has demonstrated simple, practical utility in making embeddedness an explicit (rather than hidden) part of applied and learning health system researcher training, alongside emerging evidence for validity.

As the pace of biomedical innovation rapidly evolves, there is a need to train researchers to understand regulatory science challenges associated with clinical translation. We describe a pilot course aimed at addressing this need delivered jointly through the Mayo Clinic Center for Clinical and Translational Science and the Yale-Mayo Center for Excellence in Regulatory Science and Innovation. Course design was informed by the Association for Clinical and Translational Science’s Regulatory Science Working Group’s competencies. The course used didactic, case-, and problem-based learning sessions to expose students to regulatory science concepts. Course evaluation focused on student satisfaction and learning. A total of 25 students enrolled in the first two course deliveries. Students represented several disciplines and career stages, from predoctoral to faculty. Students reported learning “an incredible amount” (7/19, 36.8%) or “a lot” (9/19, 47.4%); this was reflected in individual coursework and their course evaluations. Qualitative feedback indicated that assignments that challenged them to apply the content to their own research were appreciated. The heterogeneity of students enrolled, coupled with assessments and course evaluations, supports the statement that there is a growing need and desire for regulatory science-focused curricula. Future research will determine the long-term impact.

In recent years, there have been concerted efforts to better recruit, support, and retain diverse faculty, staff, and trainees in academic medicine. However, many institutions lack comprehensive and strategic plans to provide support to retain and recruit individuals from historically underrepresented groups. In this article, we itemize specific mechanisms through which institutions can support diverse individuals with the goal of improving inclusion and belonging in the workforce to better reflect the diversity of the intended patient and research participant population.

Abstract Introduction: Statistical literacy is essential in clinical and translational science (CTS). Statistical competencies have been published to guide coursework design and selection for graduate students in CTS. Here, we describe common elements of graduate curricula for CTS and identify gaps in the statistical competencies. Methods: We surveyed statistics educators using e-mail solicitation sent through four professional organizations. Respondents rated the degree to which 24 educational statistical competencies were included in required and elective coursework in doctoral-level and master’s-level programs for CTS learners. We report competency results from institutions with Clinical and Translational Science Awards (CTSAs), reflecting institutions that have invested in CTS training. Results: There were 24 CTSA-funded respondents representing 13 doctoral-level programs and 23 master’s-level programs. For doctoral-level programs, competencies covered extensively in required coursework for all doctoral-level programs were basic principles of probability and hypothesis testing, understanding the implications of selecting appropriate statistical methods, and computing appropriate descriptive statistics. The only competency extensively covered in required coursework for all master’s-level programs was understanding the implications of selecting appropriate statistical methods. The least covered competencies included understanding the purpose of meta-analysis and the uses of early stopping rules in clinical trials. Competencies considered to be less fundamental and more specialized tended to be covered less frequently in graduate courses. Conclusion: While graduate courses in CTS tend to cover many statistical fundamentals, learning gaps exist, particularly for more specialized competencies. Educational material to fill these gaps is necessary for learners pursuing these activities.

Abstract Objective: To mitigate the impact of racism, sexism, and other systemic biases, it is essential for organizations to develop strategies to address their diversity, equity and inclusion (DEI) climates. The objective of this formative evaluation was to assess Mayo Clinic Department of Health Sciences Research (HSR) faculty and staff perceptions toward a proposed departmental DEI plan and to explore findings by diversity and professional subgroups. Materials and methods: Key plan components include recruitment and support for diverse individuals; training for all HSR employees and leaders; and a review system to capture diversity and inclusion feedback for leaders. Additional activities include building inclusion “nudges” into existing performance reviews. To assess pre-implementation beliefs about specific plan components, we polled attendees at a departmental staff meeting in July 2020. Results: Overall, respondents (n = 162) commonly endorsed a blinded promotion review process and DEI training for all staff and leaders as most important. In contrast, respondents expressed less support for plan activities related to “nudges.” However, attitudes among certain diversity or professional groups toward specific plan activities diverged from their non-diversity group counterparts. Qualitative feedback indicated awareness of the need to address DEI issues. Discussion: Overall, HSR faculty and staff respondents conveyed support for the plan. However, some specific plan activities were perceived differently by members of certain diversity or professional subgroups. Conclusion: These findings present a DEI framework on which other institutions can build and point to future directions for how DEI activities may be differentially perceived by impacted faculty and staff.

The emphasis on team science in clinical and translational research increases the importance of collaborative biostatisticians (CBs) in healthcare. Adequate training and development of CBs ensure appropriate conduct of robust and meaningful research and, therefore, should be considered as a high-priority focus for biostatistics groups. Comprehensive training enhances clinical and translational research by facilitating more productive and efficient collaborations. While many graduate programs in Biostatistics and Epidemiology include training in research collaboration, it is often limited in scope and duration. Therefore, additional training is often required once a CB is hired into a full-time position. This article presents a comprehensive CB training strategy that can be adapted to any collaborative biostatistics group. This strategy follows a roadmap of the biostatistics collaboration process, which is also presented. A TIE approach (Teach the necessary skills, monitor the Implementation of these skills, and Evaluate the proficiency of these skills) was developed to support the adoption of key principles. The training strategy also incorporates a “train the trainer” approach to enable CBs who have successfully completed training to train new staff or faculty.

Abstract Introduction: Research career development awards (CDAs) facilitate development of clinician-scientists. This study compared the academic achievements of individuals in a structured institutional “pre-K” CDA program, the Mayo Clinic Kern Scholars program, with individuals who applied for but were not admitted to the Kern program (“Kern applicants”), and awardees of other unstructured internal CDAs. Methods: This was a longitudinal cohort study of clinicians engaged in research at Mayo Clinic between 2010 and 2019. The primary outcome was time to the 15th new peer-reviewed publication after the program start, adjusted for baseline number of publications. Secondarily, we described successful awarding of federal funding by the NIH or VA. Results: The median (IQR) number of baseline publications was highest among Kern Scholars compared to Kern Applicants or other CDA awardees [16 (12, 29) vs 5 (1, 11) and 8 (5, 16); P < 0.001]. After adjustment for baseline publications, the time to 15th new publication was significantly shorter for Kern Scholars than for the two comparator groups (P

Abstract Introduction: The hidden curriculum encompasses the norms, values, and behaviors within a learning environment. Navigating the hidden curricula of academia is crucial for doctoral trainees, particularly those from underrepresented backgrounds. Faculty mentors have an important role in helping trainees uncover and cope with the hidden curriculum. The purpose of this paper is to explore perceptions of the hidden curriculum among diverse doctoral trainees and mentors. Methods: Following a presentation on the hidden curriculum at the Association for Clinical and Translational Science annual meeting in March 2021, attendees were asked to brainstorm ideas for diverse trainees and their mentors. Breakout room discussions were held for specific hidden curriculum topics; participants voted on which topics to discuss from a list of topics defined during the presentation. Ideas from these discussions were presented to the larger group to upvote. Results: Participants (n = 116) voted to discuss the following hidden curriculum topics: “coping with bias,” “assertive communication,” “knowing how things work,” and “developing a career.” Many suggestions emphasized the role of institutions in empowering mentors to help diverse trainees and, more generally, to meaningfully support policies and programs that facilitate the career success of trainees and faculty from underrepresented backgrounds. Conclusions: This work generated a list of suggested action items for trainees, mentors, and institutions to ameliorate the hidden curricula of academia, especially for diverse trainees. However, institutions need to support changes that will facilitate these discussions as well as more broadly enable the success of faculty and students from diverse backgrounds.

AbstractPurposeThis study examined the effectiveness of a formal postdoctoral education program designed to teach skills in clinical and translational science, using scholar publication rates as a measure of research productivity.MethodParticipants included 70 clinical fellows who were admitted to a master’s or certificate training program in clinical and translational science from 1999 to 2015 and 70 matched control peers. The primary outcomes were the number of publications 5 years post-fellowship matriculation and time to publishing 15 peer-reviewed manuscripts post-matriculation.ResultsClinical and translational science program graduates published significantly more peer-reviewed manuscripts at 5 years post-matriculation (median 8 vs 5, p=0.041) and had a faster time to publication of 15 peer-reviewed manuscripts (matched hazard ratio = 2.91, p=0.002). Additionally, program graduates’ publications yielded a significantly higher average H-index (11 vs. 7, p=0.013).ConclusionThese findings support the effectiveness of formal training programs in clinical and translational science by increasing academic productivity.

Introduction It is increasingly essential for medical researchers to be literate in statistics, but the requisite degree of literacy is not the same for every statistical competency in translational research. Statistical competency can range from ‘fundamental’ (necessary for all) to ‘specialized’ (necessary for only some). In this study, we determine the degree to which each competency is fundamental or specialized. Methods We surveyed members of 4 professional organizations, targeting doctorally trained biostatisticians and epidemiologists who taught statistics to medical research learners in the past 5 years. Respondents rated 24 educational competencies on a 5-point Likert scale anchored by ‘fundamental’ and ‘specialized.’ Results There were 112 responses. Nineteen of 24 competencies were fundamental. The competencies considered most fundamental were assessing sources of bias and variation (95%), recognizing one’s own limits with regard to statistics (93%), identifying the strengths, and limitations of study designs (93%). The least endorsed items were meta-analysis (34%) and stopping rules (18%). Conclusion We have identified the statistical competencies needed by all medical researchers. These competencies should be considered when designing statistical curricula for medical researchers and should inform which topics are taught in graduate programs and evidence-based medicine courses where learners need to read and understand the medical research literature.