Study case description
COMPLICATIONS
The rapid worldwide spread and impact of COVID-19 underlined the need for interventions that effectively increase adherence to public health recommendations (e.g., testing, vaccination, social distancing, and mask wearing). Returning safely to pre-pandemic routines and practices depends on governments’ and providers’ ability to streamline the delivery of these effective interventions to the individuals who need them. To this end, the National Institutes of Health (NIH) launched the Rapid Acceleration of Diagnostic-Underserved Populations (RADx-UP) program, designed to ensure that all Americans have access to COVID-19 testing, with a focus on communities disproportionately affected by the pandemic. Projects funded by RADx-UP include new applications of existing technologies that make tests easier to use, easier to access, and more accurate. As delineated in the study protocol document [This study case used a SMART with 670 people who are medically/socially vulnerable to COVID-19 to: (a) optimize an adaptive intervention to increase rates of COVID-19 testing among high-risk populations; and (b) identify predictors of COVID-19 testing uptake (ClinicalTrials.gov NCT05305443). The total analytic sample size of 582 had 85% to detect a difference of 15% in testing rates between the two interventions being tested for optimization. The study was not powered to detect changes in the second-stage interventions. Figure 1 shows the SMART design implemented of the study. The study took place at the North Jersey Community Research Initiative (NJCRI, The following were the inclusion criteria:
Over 18 years of age.Having a high risk to contract COVID or develop related complications.Able to speak English.Able and willing to provide informed consent.The following were the exclusion criteria:
Under 18 years of age.Not at a high risk to contract COVID or develop related complications.Unable to speak English.Unable or unwilling to provide informed consent.A hallmark of the SMART design is that it requires multiple randomizations at multiple timepoints. For instance, consider the current COVID-19 Optimization Trial study case, which seeks to increase COVID-19 testing in a marginalized community. Research questions in this trial include :
Will navigation services intervention lead to higher rates of COVID-19 testing compared to an electronic informational brochure intervention?Among those who complete COVID-19 testing, will continuing with navigation services intervention lead to higher rates of adherence to CDC recommendations than changing to brief counseling treatment?Among those who did not complete COVID-19 testing, will continuing with information brochure intervention lead to more people getting tested afterwards, compared to changing the intervention to critical dialogue intervention?Participants are randomized for the first time to 