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

项目总结。建议的研究回应了RFA-OD-21-008号文件，该文件呼吁社区参与 在服务不足和弱势人群中支持新冠肺炎检测的干预措施。在那些最高的人中 接触新冠肺炎的风险是大量处于较低地位的一线基本工作者(少数) 职业(例如，零售、家庭保健)，其中黑人和拉丁裔/拉美裔(BLH)人 代表人数过多。疾控中心建议对所有出现新冠肺炎症状的人进行检测。对于那些 未接种疫苗，建议在接触新冠肺炎确诊患者后进行检测，并定期进行 对于经常密切接触的人，即使没有症状，也建议进行新冠肺炎筛查测试 和其他人在室内环境中，比如很少。然而，BLH-很少有人遇到严重的新冠肺炎障碍 测试个人/态度--(例如，缺乏指导方针、不信任)、社会--(例如，社会规范)，以及 结构--影响程度(例如，很难获得测试)。事实上，BLH的检测率低于 白人人口和只有25%-50%的BLH--目前接种疫苗的人很少。建议的社区参与 这项研究是由纽约大学和北曼哈顿改进中心的一个合作团队领导的 公司(NMIC)。其主要目标是优化行为干预，以提高新冠肺炎的检测率 BLH-很少。与RFA-OD-21-008一致，建议的研究使用多阶段优化策略 (MOST)框架，以测试基于我们过去研究的四个候选干预组件。这个 候选组件由关键种族理论通知，并由三元影响理论指导，包括 缩短或不需要大量工作人员的时间，并将在高效的析因实验设计中进行测试。 它们是A)激励性面试咨询，B)基于行为的文本消息组件 经济学，C)同伴教育，D)获得测试(通过导航到测试预约与自我测试套件)。 所有参与者都接受标准的护理，即关于新冠肺炎检测的健康教育和转诊。这个 这项研究的具体目标是：确定四个候选成分中哪些对 主要结果改善，新冠肺炎检测与医学确认；最有效 这些组件的组合将包括“优化的”干预(目标1)，识别调解人(例如，不信任， 获取)和调节(例如，社会人口学特征)每个组成部分的影响(目标2)， 并使用混合方法来探索障碍、促进者和接受 新冠肺炎检测和新冠肺炎疫苗接种(目标3)。参与者将是N=448 BLH--没有参加过的人很少 在过去六个月内接受新冠肺炎检测且未接种新冠肺炎疫苗的人，随机分配到 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 定性深度访谈。我们还将发现、描述和计划实施问题，以便 NMIC和其他以社区为基础的组织可以快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.