Evidence map›Paper›PMID 35729622›Full record

ArticleBMC public health2022

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, Charles M Cleland, Maria Lizardo, Robert L Hawkins, Greg Bangser, Lalitha Parameswaran, Victoria Stanhope, Jennifer A Robinson, Shristi Karim, Tierra Hollaway and 5 more

Registry-linked trialAbstract readClinical Trial Protocol
In one paragraph

Article in BMC public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05139927 (Using the Multiphase Optimization Strategy), which is not on this map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT05139927 nacompletednot on this map

Using the Multiphase Optimization Strategy (MOST) to Optimize an Intervention to Increase COVID-19 Testing for Black and Latino/Hispanic Frontline Essential Workers

TypeinterventionalSponsorNew York UniversityRan2022 to 2024Enrolled438ConditionsCOVID-19, COVID-19 TestingArmsMotivational interviewing (MI) counseling, Text messages (TMs) and quiz questions (QQs), Peer education, Access to COVID testing
3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Marya GwadzIntervention Innovations Team Lab (IIT-Lab), NYU Silver School of Social Work, 1 Washington Square North, New York, NY, 10003, USA. mg2890@nyu.edu.ORCID 0000-0002-2386-9409
Charles M ClelandCenter for Drug Use and HIV Research (CDUHR), NYU School of Global Public Health, 708 Broadway, New York, NY, 10003, USA.
Maria LizardoNorthern Manhattan Improvement Corporation (NMIC), 45 Wadsworth Avenue, New York, NY, 10033, USA.
Robert L HawkinsIntervention Innovations Team Lab (IIT-Lab), NYU Silver School of Social Work, 1 Washington Square North, New York, NY, 10003, USA.
Greg BangserNorthern Manhattan Improvement Corporation (NMIC), 45 Wadsworth Avenue, New York, NY, 10033, USA.
Lalitha ParameswaranDepartment of Medicine, NYU Grossman School of Medicine, New York, NY, 10016, USA.
Victoria StanhopeIntervention Innovations Team Lab (IIT-Lab), NYU Silver School of Social Work, 1 Washington Square North, New York, NY, 10003, USA.
Jennifer A RobinsonIntervention Innovations Team Lab (IIT-Lab), NYU Silver School of Social Work, 1 Washington Square North, New York, NY, 10003, USA.
Shristi KarimIntervention Innovations Team Lab (IIT-Lab), NYU Silver School of Social Work, 1 Washington Square North, New York, NY, 10003, USA.
Tierra HollawayIntervention Innovations Team Lab (IIT-Lab), NYU Silver School of Social Work, 1 Washington Square North, New York, NY, 10003, USA.
Paola G RamirezIntervention Innovations Team Lab (IIT-Lab), NYU Silver School of Social Work, 1 Washington Square North, New York, NY, 10003, USA.
Prema L FilipponeIntervention Innovations Team Lab (IIT-Lab), NYU Silver School of Social Work, 1 Washington Square North, New York, NY, 10003, USA.
Amanda S RitchieIntervention Innovations Team Lab (IIT-Lab), NYU Silver School of Social Work, 1 Washington Square North, New York, NY, 10003, USA.
Angela BanfieldIndependent Consultant, New York, NY, 10031, USA.
Elizabeth SilvermanSUNY Research Foundation, Downstate Medical Center, 450 Clarkson Ave, Brooklyn, NY, 11203, USA.

Funding

Transdisciplinary Theoretical Svnthesis and Development CoreP30DA011041 · NIDA · NEW YORK UNIVERSITY · PI Holly Hagan · 1998 to 2026
$38.9M
Using the multiphase optimization strategy (MOST) to optimize an intervention to increase COVID-19 testing for Black and Latino/Hispanic frontline essential workersU01MD017418 · NIMHD · NEW YORK UNIVERSITY · PI GWADZ, MARYA · 2022 to 2023
$2.4M
NIDA NIH HHS P30 DA011041NIMHD NIH HHS U01 MD017418
6 · The paper itself

Abstract

backgroundAmong 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/

designThe 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 registrationClinicalTrials.gov: NCT05139927 ; Registered on 11/29/2021. Protocol version 1.0. May 2, 2022, Version 1.0.

Indexed as

COVID-19COVID-19 TestingBlack PeopleHispanic or LatinoHumansPandemicsRandomized Controlled Trials as TopicCommunity-engagedCOVID-19Essential workersFactorial designFrontline workersHealth inequalityInterventionMultiphase optimization strategyRacial/ethnic disparitiesRADx-UPTesting

Identifiers

PMID35729622
PMCPMC9210062

What OpenQuestion holds

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LicenceCC BY
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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.