JMIR Publications

ABSTRACT

Digital mental-health tools typically rely on individual-level metrics and adaptive intervention logic, while the dyadic dynamics through which distress, support, escalation, and repair unfold remain under-specified. This paper introduces Relational Ecological Momentary Assessment (REMA), a bounded, transparent, and auditable framework for modeling moment-level dyadic co-regulation in digital mental health. REMA maps three low-burden inputs (Primary User Emotional Zone [Z], Supporter Contact Availability [Cp], and Supporter Emotional Surplus [Cs]) to 48 relational states. Each state is linked to a dominant Micro-Intervention Unit (MIU) category through explicit ethical constraints and a fixed rule hierarchy that prioritizes safety, access, and sustainability over relational elaboration. As a methodological framework paper, this article specifies REMA's decision architecture rather than reporting empirical outcomes. It presents the tri-code input model, the full 48-state mapping, bounded MIU categories, conservative fallback rules for incomplete dyadic input, and a staged validation roadmap covering feasibility, construct validation, and pilot testing. REMA offers a testable architecture for dyadic digital mental-health support. Its contribution is methodological: to make relational decision rules explicit enough to implement, inspect, criticize, and empirically evaluate without relying on opaque prediction or unconstrained personalization.