Common Data Element Collection in Underserved School Communities: Challenges and Recommendations.

OBJECTIVES: To provide recommendations for future common data element (CDE) development and collection that increases community partnership, harmonizes data interpretation, and continues to reduce barriers of mistrust between researchers and underserved communities. METHODS: We conducted a cross-sectional qualitative and quantitative evaluation of mandatory CDE collection among Rapid Acceleration of Diagnostics-Underserved Populations Return to School project teams with various priority populations and geographic locations in the United States to: (1) compare racial and ethnic representativeness of participants completing CDE questions relative to participants enrolled in project-level testing initiatives and (2) identify the amount of missing CDE data by CDE domain. Additionally, we conducted analyses stratified by aim-level variables characterizing CDE collection strategies. RESULTS: There were 15 study aims reported across the 13 participating Return to School projects, of which 7 (47%) were structured so that CDEs were fully uncoupled from the testing initiative, 4 (27%) were fully coupled, and 4 (27%) were partially coupled. In 9 (60%) study aims, participant incentives were provided in the form of monetary compensation. Most project teams modified CDE questions (8/13; 62%) to fit their population. Across all 13 projects, there was minimal variation in the racial and ethnic distribution of CDE survey participants from those who participated in testing; however, fully uncoupling CDE questions from testing increased the proportion of Black and Hispanic individuals participating in both initiatives. CONCLUSIONS: Collaboration with underrepresented populations from the early study design process may improve interest and participation in CDE collection efforts.

Duke Scholars

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