Safeguarding Decentralized Research from Insincere Participants: Case Series and Review of Literature

Decentralized clinical trials (DCTs) and direct-to-participant recruitment have expanded opportunities for research participation, broadening the reach and accessibility.Traditional site-based research often requires in-person visits, limiting participation for individuals who live far from trial sites or have competing responsibilities.Without in-person verification, decentralized research may attract insincere participants, or individuals or bots who misrepresent themselves to gain study access, often motivated by compensation.This literature review explores the growing concern of insincere participation in decentralized research, drawing on real-world case studies from a large academic research institution and published literature.We examine how insincere participation threatens study integrity, increases burden for research teams, and poses ethical challenges, particularly in studies leveraging online and social media recruitment.Through analysis of patterns and behaviors, we discuss various mitigation strategies and propose a risk-based framework to help researchers align mitigation efforts with their study's needs and tolerance for data quality risk.As decentralized research expands, adaptable safeguards are important to preserve data integrity.These findings highlight a central challenge: determining how much verification is necessary without excluding genuine participants.