ABSTRACT
Background. Opioid use disorder (OUD) affects millions in the United States. Emerging technologies like home motion sensors offer the potential for relapse prediction. The study evaluates the feasibility and acceptability of such technology in OUD patients. Methods. Participants were recruited through local OUD treatment centers in Columbus, Ohio. The study involved installing passive monitoring sensors in participants' homes and required participants to wear a Fitbit and complete daily surveys. The target was to enroll 25 patients, with incentives provided for participation. Results. Out of 170 evaluated records, 50 met the inclusion criteria, and only 14 consented to participate, with four completing the study. Main recruitment challenges included housing instability, privacy concerns, and the COVID-19 pandemic's impact. Most participants were willing to use sensor devices, especially in less private home areas. Conclusions. The study faced significant barriers in recruiting and retaining participants, highlighting the complexities of OUD research. Despite methodological adaptations like virtual follow-ups, the retention rate remained low. This suggests the need for more flexible, patient-centric approaches in future research, particularly for populations experiencing instability or distrust. The study underscores the potential of technology in treatment but emphasizes the importance of building trust and understanding within target communities.