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. 2022 Jun 21;22(1):1235.
doi: 10.1186/s12889-022-13576-0.

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

Marya Gwadz  1   2 , Charles M Cleland  3   4 , Maria Lizardo  5 , Robert L Hawkins  6 , Greg Bangser  5 , Lalitha Parameswaran  7 , Victoria Stanhope  6 , Jennifer A Robinson  6 , Shristi Karim  6 , Tierra Hollaway  6 , Paola G Ramirez  6 , Prema L Filippone  6 , Amanda S Ritchie  6 , Angela Banfield  8 , Elizabeth Silverman  9
Affiliations

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

Marya Gwadz et al. BMC Public Health. .

Abstract

Background: Among those at highest risk for COVID-19 exposure is the large population of frontline essential workers in occupations such food service, retail, personal care, and in-home health services, among whom Black and Latino/Hispanic persons are over-represented. For those not vaccinated and at risk for exposure to COVID-19, including frontline essential workers, regular (approximately weekly) COVID-19 testing is recommended. However, Black and Latino/Hispanic frontline essential workers in these occupations experience serious impediments to COVID-19 testing at individual/attitudinal- (e.g., lack of knowledge of guidelines), social- (e.g., social norms), and structural-levels of influence (e.g., poor access), and rates of testing for COVID-19 are insufficient.

Methods/design: The proposed community-engaged study uses the multiphase optimization strategy (MOST) framework and an efficient factorial design to test four candidate behavioral intervention components informed by an integrated conceptual model that combines critical race theory, harm reduction, and self-determination theory. They are A) motivational interview counseling, B) text messaging grounded in behavioral economics, C) peer education, and D) access to testing (via navigation to an appointment vs. a self-test kit). All participants receive health education on COVID-19. The specific aims are to: identify which components contribute meaningfully to improvement in the primary outcome, COVID-19 testing confirmed with documentary evidence, with the most effective combination of components comprising an "optimized" intervention that strategically balances effectiveness against affordability, scalability, and efficiency (Aim 1); identify mediators and moderators of the effects of components (Aim 2); and use a mixed-methods approach to explore relationships among COVID-19 testing and vaccination (Aim 3). Participants will be N = 448 Black and Latino/Hispanic frontline essential workers not tested for COVID-19 in the past six months and not fully vaccinated for COVID-19, randomly assigned to one of 16 intervention conditions, and assessed at 6- and 12-weeks post-baseline. Last, N = 50 participants will engage in qualitative in-depth interviews.

Discussion: This optimization trial is designed to yield an effective, affordable, and efficient behavioral intervention that can be rapidly scaled in community settings. Further, it will advance the literature on intervention approaches for social inequities such as those evident in the COVID-19 pandemic.

Trial registration: ClinicalTrials.gov: NCT05139927 ; Registered on 11/29/2021. Protocol version 1.0. May 2, 2022, Version 1.0.

Keywords: COVID-19; Community-engaged; Essential workers; Factorial design; Frontline workers; Health inequality; Intervention; Multiphase optimization strategy; RADx-UP; Racial/ethnic disparities; Testing.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Conceptual Model Grounded in the Intervention Innovations Team Integrated Conceptual Model (IIT-ICM)
Fig. 2
Fig. 2
Intervention conditions in the factorial design
Fig. 3
Fig. 3
Sequence of study activities
See this image and copyright information in PMC

References

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