The Role of Mock Reviewing Sessions in the National Research Mentoring Network Strategic Empowerment Tailored for Health Equity Investigators: A Randomized Controlled Study.

The National Research Mentoring Network (NRMN) Strategic Empowerment Tailored for Health Equity Investigators (SETH) study evaluates the value of adding Developmental Network to Coaching in the career advancement of diverse Early-Stage Investigators (ESIs). Focused NIH-formatted Mock Reviewing Sessions (MRS) prior to the submission of grants can significantly enhance the scientific merits of an ESI's grant application. We evaluated the most prevalent design, analysis-related factors, and the likelihood of grant submissions and awards associated with going through MRS, using descriptive statistics, Chi-square, and logistic regression methods. A total of 62 out of 234 applications went through the MRS. There were 69.4% that pursued R grants, 22.6% career development (K) awards, and 8.0% other grant mechanisms. Comparing applications that underwent MRS versus those that did not (N = 172), 67.7% vs. 38.4% were submitted for funding (i.e., unadjusted difference of 29.3%; OR = 4.8, 95% CI = (2.4, 9.8), p-value < 0.0001). This indicates that, relative to those who did not undergo MRS, ESIs who did, were 4.8 times as likely to submit an application for funding. Also, ESIs in earlier cohorts (1-2) (a period that coincided with the pre COVID-19 era) as compared to those who were recruited at later cohorts (3-4) (i.e., during the peak of COVID-19 period) were 3.8 times as likely to submit grants (p-value < 0.0001). The most prevalent issues that were identified included insufficient statistical design considerations and plans (75%), conceptual framework (28.3%), specific aims (11.7%), evidence of significance (3.3%), and innovation (3.3%). MRS potentially enhances grant submissions for extramural funding and offers constructive feedback allowing for modifications that enhance the scientific merits of research grants.

Impact of COVID-19 on the Research Career Advancement of Health Equity Scholars from Diverse Backgrounds.

The COVID-19 pandemic has significantly taxed scientific research and seems to have exacerbated existing inequities within the research field, particularly for early-stage investigators (ESIs). This study examines the effects of the COVID-19 pandemic on traditionally underrepresented ESIs enrolled in an NIH-supported study evaluating the effectiveness of developmental networks, grant writing coaching, and mentoring on research career advancement. The survey consisted of 24 closed-ended (quantitative) and 4 open-ended questions (qualitative) linked to a participant's ability to meet grant submission deadlines, research and professional development disruptions, stress level, career transition level, self-efficacy and management of scholarly tasks, and familial responsibilities. Results from 32 respondents (53%) suggest that COVID-19 adversely impacted the continuity of research (81%) and grant submissions (63%). On average, grant submissions were delayed by 6.69 months (i.e., greater than one grant cycle). We also conducted additional analyses characterizing nonresponse and found that there were no significant predictors of nonresponse, indicating a limited threat to the validity of our findings. The disruption caused by COVID-19 to the careers of ESIs from underrepresented groups in the biomedical workforce has been profound in the short term. The long-term consequences to the future success of these groups are unknown but is a worthwhile area of research and potential innovation.

Randomized Controlled Study to Test the Effectiveness of Developmental Network Coaching in the Career Advancement of Diverse Early-Stage Investigators (ESIs): Implementation Challenges and Lessons Learned.

Introduction: Adding developmental networks (DN) to grant-writing coaching can significantly enhance ESIs' research careers. Herein, we present study design, ESIs' characteristics and encountered challenges/lessons learned and their resolutions when deploying/implementing (a) NCR algorithm(s), (b) recruitment/retention and (c) implementing DN intervention. Methods: Nested Cluster Randomization (NCR) design governs this study implementation. The sample size is 220 ESIs intending to submit an NIH K, R, U, and/or Minority Supplement application(s). Primary outcome: intensity/sustainability of grant submission(s)/funding(s), measured by time to/between application(s). Outcome(s) analyses modes: summaries, Kaplan Meir and Cox proportional hazard models as a function of randomization groups and other predictors of outcomes. Results: In the present study, we recruited two cohorts of ESIs (N = 85): 39% African Americans, 18% Latinx, 18% Whites, 20% Asians and 6% Hawaiian/Pacific Islander/other ethnicities; 65% are women; 73% are assistant professors, 4% are Associate Professors and 23% are instructors/scientists/post-doctoral. Participants' disciplines: 32% basic/biomedical, 36% clinical/translational and 32% social/behavioral. Proposal(s) mechanisms: 61% research grants (R series), 31% career development (K series), 7% support of competitive research (SCORE) and 1% National Science Foundation applications. NCR did produce balance in the distribution of ESIs' demographics, sex at birth, ethnicity, professional appointments, background disciplines, and mechanism of sought funding. Lessons learned/challenges: NCR implementation was methodologically challenged during implementation by added constraints (e.g., assigning coaches to the same randomization arm of their participants as well as blinding them to ESIs' randomization group). Recruitment and retention were hampered by the COVID-19 pandemic and more progressive and innovative strategies were needed to heighten the visibility and outreach of this program. DN delivery was also affected by the pandemic and monitoring of ESIs' engagement and facilitation of communications interventions were needed. Resolution of these challenges effectively reconfigured NCR algorithms, recruitment/retention plans, and DN intervention delivery. We intend to recruit an additional 135 ESIs focusing on underrepresented scholars from RCMIs, CTSAs, and other programs. COVID-19 rendered this program 100% virtual, with recruitment/retention challenges and substantial disruption of ESIs' research. We may extend the grant writing period, coaching, and Mock Study Section support.

Variation in Reporting of the Race and Ethnicity of COVID-19 Cases and Deaths Across US States: April 12, 2020, and November 9, 2020.

Despite growing evidence that COVID-19 is disproportionately affecting communities of color, state-reported racial/ethnic data are insufficient to measure the true impact.We found that between April 12, 2020, and November 9, 2020, the number of US states reporting COVID-19 confirmed cases by race and ethnicity increased from 25 to 50 and 15 to 46, respectively. However, the percentage of confirmed cases reported with missing race remained high at both time points (29% on April 12; 23% on November 9). Our analysis demonstrates improvements in reporting race/ethnicity related to COVID-19 cases and deaths and highlights significant problems with the quality and contextualization of the data being reported.We discuss challenges for improving race/ethnicity data collection and reporting, along with opportunities to advance health equity through more robust data collection and contextualization. To mitigate the impact of COVID-19 on racial/ethnic minorities, accurate and high-quality demographic data are needed and should be analyzed in the context of the social and political determinants of health.

Population-Level Disparities in COVID-19: Measuring the Independent Association of the Proportion of Black Population on COVID-19 Cases and Deaths in US Counties.

CONTEXT: There is a need to understand population race and ethnicity disparities in the context of sociodemographic risk factors in the US experience of the COVID-19 pandemic. OBJECTIVE: Determine the association between county-level proportion of non-Hispanic Black (NHB) on county COVID-19 case and death rates and observe how this association was influenced by county sociodemographic and health care infrastructure characteristics. DESIGN AND SETTING: This was an ecologic analysis of US counties as of September 20, 2020, that employed stepwise construction of linear and negative binomial regression models. The primary independent variable was the proportion of NHB population in the county. Covariates included county demographic composition, proportion uninsured, proportion living in crowded households, proportion living in poverty, population density, state testing rate, Primary Care Health Professional Shortage Area status, and hospital beds per 1000 population. MAIN OUTCOME MEASURES: Outcomes were exponentiated COVID-19 cases per 100 000 population and COVID-19 deaths per 100 000 population. We produced county-level maps of the measures of interest. RESULTS: In total, 3044 of 3142 US counties were included. Bivariate relationships between the proportion of NHB in a county and county COVID-19 case (Exp ß = 1.026; 95% confidence interval [CI], 1.024-1.028; P < .001) and death rates (rate ratio [RR] = 1.032; 95% CI, 1.029-1.035; P < .001) were not attenuated in fully adjusted models. The adjusted association between the proportion of NHB population in a county and county COVID-19 case was Exp ß = 1.025 (95% CI, 1.023-1.027; P < .001) and the association with county death rates was RR = 1.034 (95% CI, 1.031-1.038; P < .001). CONCLUSIONS: The proportion of NHB people in a county was positively associated with county COVID-19 case and death rates and did not change in models that accounted for other socioecologic and health care infrastructure characteristics that have been hypothesized to account for the disproportionate impact of COVID-19 on racial and ethnic minority populations. Results can inform efforts to mitigate the impact of structural racism of COVID-19.

Percentage of Black Population and Primary Care Shortage Areas Associated with Higher COVID-19 Case and Death Rates in Georgia Counties.

OBJECTIVES: We hypothesized that the proportion of Black individuals in a county would be associated with higher rates of coronavirus disease 2019 (COVID-19) cases and deaths, even after accounting for other high-risk socioecologic factors such as poverty, population density, and household crowding, and uninsured rates. We also expected that counties designated as primary care health professional shortage areas (PCHPSAs) would be associated with higher COVID-19 death rates, and the lack of primary care access would exacerbate racial disparities in death rates. We undertook this study to test these hypotheses and discern the independent effects of racial composition, socioecologic characteristics, and healthcare system factors on COVID-19 cases and deaths in Georgia counties. METHODS: We used county-level COVID-19 cases and deaths on April 23, 2020 from the Johns Hopkins Coronavirus Resource Center and estimates of 2019 county-level populations from the US Census Bureau to calculate the cumulative event rates for the state of Georgia. We used multiple regression models to examine crude and adjusted associations of socioecologic and health system variables with county-level COVID-19 case and mortality rates. RESULTS: After adjustment, a 1% increase in the proportion of Black people in the county resulted in a 2.3% increase in the county COVID-19 confirmed case rate and a 3.0% increase in the death rate (relative risk 1.03, 95% confidence interval 1.01-1.05, P < 0.001). Primary care shortage areas had a 74% higher death rate (relative risk 1.74, 95% confidence interval 1.00-3.00, P = 0.049). CONCLUSIONS: These results highlight the impact of racial disparities on the spatial patterns of COVID-19 disease burden in Georgia, which can guide interventions to mitigate racial disparities. The results also support the need for robust primary care infrastructure throughout the state.