Community-based Behavioral Intervention to Increase Vaccination Using MOST

Overview

The proposed study responds to the need for community-engaged interventions to increase vaccine uptake among populations experiencing health disparities. We focus on COVID-19 and influenza vaccination, both of which now require annual vaccines. Among those at highest risk for morbidity, hospitalization, and mortality are African American/Black and Latino (ABBL) persons who are not up-to-date on these vaccinations. Only 20-28% of adult AABL persons are up-to-date on COVID-19 vaccination, compared to 31% of White persons, and only 30-40% of AABL persons receive the influenza vaccine annually compared to \>55% among White persons. AABL experience serious impediments to COVID-19 (and to a lesser extent, influenza) vaccination at individual- (e.g., distrust, insufficient knowledge, low perceived risk, cognitive biases), social- (e.g., peer norms), and structural-levels of influence (e.g., poor access). Taken together, these comprise multi-level vaccine hesitancy. Factors that promote vaccination include trusted AABL health educators (peers, nurses), tapping into altruism and collective responsibility, circumventing cognitive biases, and reducing structural barriers. Without efforts to address multi-level vaccine hesitancy, rates of COVID-19 and influenza vaccination will remain unacceptably low and racial/ethnic health disparities in infectious disease morbidity and mortality will persist. The proposed study is led by a collaborative team at New York University and the Northern Manhattan Improvement Corporation. It uses the multiphase optimization strategy (MOST), an engineering-inspired framework, to test effects of individual candidate intervention components in a factorial design and then optimize a multi-component intervention made up of the most cost-effective combination of components. Staying up-to-date with COVID-19 vaccination (confirmed with documentary evidence) is the primary outcome, and influenza vaccination is the secondary outcome. We have identified four promising candidate components, with an emphasis on brevity, low-touch, and future scalability: A) nurse-led shared decision making, B) a text message intervention, C) modest lottery prizes for vaccination, and D) peer navigation to vaccination appointments. Participants will be N=560 community-residing adult English and Spanish-speaking AABL persons who are not up-to-date on COVID-19 and influenza vaccinations but with at least one COVID-19 vaccine dose.

The proposed study responds to the need for community-engaged interventions to increase vaccine uptake among populations experiencing health disparities. We focus on COVID-19 and influenza vaccination, both of which now require annual vaccines. Among those at highest risk for morbidity, hospitalization, and mortality are African American/Black and Latino (ABBL) persons who are not up-to-date on these vaccinations. Only 20-28% of adult AABL persons are up-to-date on COVID-19 vaccination, compared to 31% of White persons, and only 30-40% of AABL persons receive the influenza vaccine annually compared to \>55% among White persons. AABL experience serious impediments to COVID-19 (and to a lesser extent, influenza) vaccination at individual- (e.g., distrust, insufficient knowledge, low perceived risk, cognitive biases), social- (e.g., peer norms), and structural-levels of influence (e.g., poor access). Taken together, these comprise multi-level vaccine hesitancy. Factors that promote vaccination include trusted AABL health educators (peers, nurses), tapping into altruism and collective responsibility, circumventing cognitive biases, and reducing structural barriers. Without efforts to address multi-level vaccine hesitancy, rates of COVID-19 and influenza vaccination will remain unacceptably low and racial/ethnic health disparities in infectious disease morbidity and mortality will persist. The proposed study is led by a collaborative team at New York University and the Northern Manhattan Improvement Corporation. It uses the multiphase optimization strategy (MOST), an engineering-inspired framework, to test effects of individual candidate intervention components in a factorial design and then optimize a multi-component intervention made up of the most cost-effective combination of components. Staying up-to-date with COVID-19 vaccination (confirmed with documentary evidence) is the primary outcome, and influenza vaccination is the secondary outcome. We have identified four promising candidate components, with an emphasis on brevity, low-touch, and future scalability: A) nurse-led shared decision making, B) a text message intervention, C) modest lottery prizes for vaccination, and D) peer navigation to vaccination appointments. Participants will be N=560 community-residing adult English and Spanish-speaking AABL persons who are not up-to-date on COVID-19 and influenza vaccinations but with at least one COVID-19 vaccine dose. Specific aims are: Aim 1) identify which of four components contribute meaningfully to improvement in the outcomes; Aim 2) identify mediators (e.g., altruism, norms) and moderators (e.g., sociodemographic characteristics, distrust) of the effects of each component; and Aim 3) build the most cost-effective intervention package(s). Participants will be randomly assigned to an experimental condition, and assessed at 3- and 6-months post-baseline; N=45 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 community-based and outpatient health organizations.