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Objective The Rapid Acceleration of Diagnostics-Underserved Populations (RADx-UP) program is a consortium of community-engaged research projects with the goal of increasing access to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) tests in underserved populations. To accelerate clinical research, common data elements (CDEs) were selected and refined to standardize data collection and enhance cross-consortium analysis. Materials and Methods The RADx-UP consortium began with more than 700 CDEs from the National Institutes of Health (NIH) CDE Repository, Disaster Research Response (DR2) guidelines, and the PHENotypes and eXposures (PhenX) Toolkit. Following a review of initial CDEs, we made selections and further refinements through an iterative process that included live forums, consultations, and surveys completed by the first 69 RADx-UP projects. Results Following a multistep CDE development process, we decreased the number of CDEs, modified the question types, and changed the CDE wording. Most research projects were willing to collect and share demographic NIH Tier 1 CDEs, with the top exception reason being a lack of CDE applicability to the project. The NIH RADx-UP Tier 1 CDE with the lowest frequency of collection and sharing was sexual orientation. Discussion We engaged a wide range of projects and solicited bidirectional input to create CDEs. These RADx-UP CDEs could serve as the foundation for a patient-centered informatics architecture allowing the integration of disease-specific databases to support hypothesis-driven clinical research in underserved populations. Conclusion A community-engaged approach using bidirectional feedback can lead to the better development and implementation of CDEs in underserved populations during public health emergencies. [ABSTRACT FROM AUTHOR]

Studies of long-term cognitive change should account for the potential effects of education on the outcome, since some studies have demonstrated an association of education with dementia risk. Evaluating cognitive change is more ideal than evaluating cognitive performance at a single time point, because it should be less susceptible to confounding. In this analysis of 14,020 persons from a US cohort study, the Atherosclerosis Risk in Communities (ARIC) Study, we measured change in performance on 3 cognitive tests over a 20-year period, from ages 48–67 years (1990–1992) through ages 70–89 years (2011–2013). Generalized estimating equations were used to evaluate the association between education and cognitive change in unweighted adjusted models, in models incorporating inverse probability of attrition weighting, and in models using cognitive scores imputed from the Telephone Interview for Cognitive Status for participants not examined in person. Education did not have a strong relationship with change in cognitive test performance, although the rate of decline was somewhat slower among persons with lower levels of education. Methods used to account for selective dropout only marginally changed these observed associations. Future studies of risk factors for cognitive impairment should focus on cognitive change, when possible, to allow for reduction of confounding by social or cultural factors. [ABSTRACT FROM PUBLISHER]