# Using the multiphase optimization strategy (MOST) to optimize an intervention to increase COVID-19 testing for Black and Latino/Hispanic frontline essential workers

> **NIH NIH U01** · NEW YORK UNIVERSITY · 2022 · $1,200,348

## Abstract

PROJECT SUMMARY. The proposed study responds to RFA-OD-21-008 which calls for community-engaged
interventions to support COVID-19 testing in underserved and vulnerable populations. 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. The CDC recommends testing for all those experiencing symptoms of COVID-19. For those
not vaccinated, testing is recommended after exposure to individuals with a COVID-19 diagnosis, and 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 at individual/attitudinal- (e.g., lack of knowledge of guidelines, distrust), social- (e.g., social norms), and
structural-levels of influence (e.g., poor access to testing). Indeed, testing rates are lower among BLH than
White populations and only 25-50% of BLH-FEW are currently vaccinated. 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. The
candidate components are informed by critical race theory and guided by the theory of triadic influence, are
brief or do not require substantial staff time, and will be tested in a highly efficient factorial experimental design.
They are A) motivational interview counseling, B) a text message component grounded in behavioral
economics, C) peer education, and D) access to testing (via navigation to a test appointment vs. a self-test kit).
All participants receive the standard of care, namely, health education on COVID-19 testing, and referrals. The
specific aims of the study are to: identify which of four candidate components contribute meaningfully to
improvement in the primary outcome, COVID-19 testing with medical confirmation; the most effective
combination of components will comprise the “optimized” intervention (Aim 1), identify mediators (e.g., distrust,
access) and moderators (e.g., sociodemographic characteristics) of the effects of each component (Aim 2),
and use a mixed-methods approach to explore relationships among barriers to, facilitators of, and uptake of
COVID-19 testing and COVID-19 vaccination (Aim 3). 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; N=50 participants will engage in
qualitative in-depth ...

## Key facts

- **NIH application ID:** 10447429
- **Project number:** 1U01MD017418-01
- **Recipient organization:** NEW YORK UNIVERSITY
- **Principal Investigator:** Marya Gwadz
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $1,200,348
- **Award type:** 1
- **Project period:** 2022-01-01 → 2023-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10447429

## Citation

> US National Institutes of Health, RePORTER application 10447429, Using the multiphase optimization strategy (MOST) to optimize an intervention to increase COVID-19 testing for Black and Latino/Hispanic frontline essential workers (1U01MD017418-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10447429. Licensed CC0.

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