The sequential cohort randomized clinical trial: A study design for community-engaged clinical research in a rural American Indian community
- Skewes, Monica C [ Montana State University: Psychology ]
- Gonzalez, Vivian M
- Webber, Eliza [ Montana State University: Center for American Indian and Rural Health Equity ]
- Gameon, Julie A [ Montana State University: Psychology ]
- Oosterhoff, Benjamin
- Adams, Alexandra K [ Montana State University: Center for American Indian and Rural Health Equity ]
Health disparities facing American Indian and Alaska Native (AI/AN) populations warrant effective behavioral health interventions that are grounded in culture and Indigenous worldviews, but AI/AN people remain underrepresented in clinical trials. Rigorous scientific methods are needed to determine the efficacy of new interventions, particularly in small rural communities with high treatment need and low access to care. However, many AI/AN communities prefer study designs that ensure all participants receive an intervention, and logistical constraints, such as small population sizes and limited staffing, can impede fully powered randomized controlled trials. This manuscript presents the Sequential Cohort Randomized Clinical Trial (SC-RCT), a study design developed through an academic-community partnership to test the efficacy of a behavioral intervention for substance use disorders in a rural AI reservation community. The SC-RCT differs from existing staggered rollout designs (e.g., stepped wedge, dynamic wait-listed) by using sequential cohort enrollment with individual-level randomization, allowing sample size to accrue over time while standardizing waitlist duration and intervention dosage across participants. This approach preserves a randomized comparison between immediate and delayed treatment conditions while accommodating staffing and recruitment constraints. The SC-RCT offers a feasible and culturally responsive option when traditional designs are not practical, and may be especially useful in small or under-resourced populations where equitable access and limited implementation capacity are key considerations. In AI/AN and other communities, this design may help overcome logistical barriers to research and support ethical and effective interventions in community settings.