Using the Multiphase Optimization Strategy (MOST) to Optimize an Intervention to Increase COVID-19 Testing for Black and Latino/Hispanic Frontline Essential Workers
收藏DataCite Commons2024-05-15 更新2024-07-13 收录
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https://radxdatahub.nih.gov/study/181
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资源简介:
Among those at highest risk for exposure to COVID-19 is the large population of frontline essential workers
(FEW) in lower status occupations (e.g., retail, in-home health care), among whom Black and Latino/Hispanic
(BLH) persons are over-represented. For those not vaccinated for COVID, regular COVID-19 screening
testing is recommended even when asymptomatic for those with frequent close contact with others in indoor
settings such as FEW. However, BLH-FEW experience serious impediments to COVID-19 testing and testing
rates are lower among BLH than White populations. The proposed community-engaged study is led by a
collaborative team at New York University and the Northern Manhattan Improvement Corporation (NMIC). Its
main goal is to optimize a behavioral intervention to boost COVID-19 testing rates for BLH-FEW. Consistent
with RFA-OD-21-008, the proposed study uses the multiphase optimization strategy (MOST) framework to
test four candidate intervention components grounded in our past research. Participants will be N=448
BLH-FEW who have not been tested for COVID-19 in the past six months and who are not vaccinated for
COVID-19, randomly assigned to an intervention condition, and assessed at 6- and 12-weeks post-baseline.
提供机构:
NIH Rapid Acceleration of Diagnostics Data Hub (RADx Data Hub)
创建时间:
2024-05-15



