Geospatial ecological momentary assessment (GEMA) for opioid use disorder: Protocol for a just-in-time adaptive...

Smartphone-delivered interventions have shown promise for behavior change in substance use contexts, yet their application to opioid use disorder (OUD) remains limited, particularly among rural and underserved populations. Geospatial ecological momentary assessment (GEMA)-which integrates real-time location monitoring with momentary self-report-has not yet been applied to OUD treatment but offers an approach to detecting and responding to environmental relapse risk. OptiMAT (Optimizing Medication-Assisted Treatment) is a smartphone application developed as an adjunctive therapy for individuals receiving medication for opioid use disorder (MOUD). This paper describes an exploratory aim embedded within a larger randomized controlled trial (RCT) of OptiMAT that evaluates the feasibility and acceptability of integrating GEMA and just-in-time adaptive intervention (JITAI) strategies to reduce relapse risk.

This is a two-arm, single-blind randomized controlled trial comparing outpatient MOUD with adjunctive OptiMAT versus MOUD alone among newly enrolled adults in the greater Little Rock, Arkansas area. Eligible participants are adults aged 18 years or older initiating or currently receiving outpatient MOUD who own a GPS-enabled smartphone. Participants randomized to the OptiMAT arm engage in a theory-informed GEMA protocol that monitors proximity to self-identified high-risk environments. Upon entry into predefined geofenced zones with sustained presence of at least 5 min, the application delivers tiered behavioral prompts, including motivational messages, craving check-ins, and optional escalation to social support. Primary outcomes for this exploratory aim include feasibility and acceptability, operationalized as app engagement metrics, responsiveness to GEMA-triggered alerts, and study retention. Recruitment began in May 2023, with follow-up assessments anticipated through September 2027.

This protocol describes one of the first applications of GPS-based GEMA and JITAI logic within a digital intervention for OUD. This work will inform the design of replicable, location-aware digital tools to support relapse prevention in MOUD care, with implications for extending these approaches to rural and underserved populations.

NCT05336188.