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

项目摘要。拟议的研究响应了RFA-OD-21-008，该研究呼吁社区参与 支持在服务不足和脆弱人群中进行COVID-19检测的干预措施。在那些最高 暴露于COVID-19的风险是大量处于较低地位的一线基本工作人员（FEW） 职业（例如，零售、家庭保健），其中黑人和拉丁裔/西班牙裔人 过度代表。CDC建议对所有出现COVID-19症状的人进行检测。对于那些 未接种疫苗，建议在接触确诊为COVID-19的个人后进行检测，并定期 对于经常密切接触者，即使无症状，也建议进行COVID-19筛查检测 与其他人在室内设置，如少数。然而，BLH-FEW经历了COVID-19的严重障碍 在个人/态度上的测试-（例如，缺乏指导方针的知识，不信任），社会-（例如，社会规范），以及 影响的结构水平（例如，不容易进行测试）。事实上，BLH的检测率低于 目前，白色人群和只有25-50%的BLH-FEW人群接种了疫苗。拟议的社区参与 这项研究是由纽约大学和北方曼哈顿改善项目的一个合作小组领导的 公司（NMIC）。其主要目标是优化行为干预，以提高COVID-19检测率， 很少。与RFA-OD-21-008一致，拟定研究使用多阶段优化策略 （MOST）框架来测试四个候选干预成分，这些成分是基于我们过去的研究。的 候选成分是由关键种族理论和三元影响理论指导， 简短或不需要大量的工作人员的时间，并将在一个高效的析因实验设计进行测试。 它们是A）动机性面试咨询，B）基于行为的短信部分 经济学，C）同伴教育，以及D）测试访问（通过导航到测试预约与自测套件）。 所有参与者都接受标准护理，即关于COVID-19检测的健康教育和转诊。的 研究的具体目标是：确定四个候选组成部分中的哪一个对以下方面有意义： 改善主要结局，经医学确认的COVID-19检测;最有效 组件的组合将包括“优化的”干预（目标1），识别介质（例如，不信任， 访问）和主持人（例如，社会人口特征）的影响（目标2）， 并使用混合方法的方法来探索障碍，促进者和吸收之间的关系， COVID-19检测和COVID-19疫苗接种（目标3）。参与者将为N=448名BLH-FEW， 在过去六个月内接受COVID-19检测且未接种COVID-19疫苗的人，随机分配至 干预条件，并在基线后6周和12周进行评估; N=50名参与者将参与 定性深入访谈。我们还将发现、描述和计划实施问题， NMIC和其他社区组织可以迅速扩大优化干预的规模。

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 interviews. We will also uncover, describe, and plan for implementation issues so the optimized intervention can be rapidly scaled up by NMIC and other community-based organizations.