Optimizing just-in-time adaptive interventions for interpersonal distress: mechanisms, prediction, and the challenge of engagement

Common mental health disorders (CMD) feature fluctuating emotional and interpersonal symptoms inadequately addressed by traditional weekly therapies. Ecological momentary interventions offer potential for timely support, yet their mechanisms and optimal delivery contexts remain unclear. This secondary analysis of a randomized trial (N = 77) compared mindfulness and mentalization micro-interventions triggered by personalized symptom thresholds. We examined dynamic symptom networks, proximal effectiveness, engagement predictors, and distress forecasting in adults with CMD. Dynamic networks revealed stable communities (interpersonal threat, social connection, affective states) with mood as a key bridge. No significant proximal intervention effects were observed. Non-engagement was significantly predicted by high stress (OR = 1.21), elevated mood (OR = 1.22), and perceived criticism (OR = 1.22). Conversely, cumulative symptom triggers (OR = 0.69) and social contact (OR = 0.83) facilitated engagement. The dynamic prediction model achieved fair performance (AUC = 0.66) for next-beep distress. Beyond autoregressive effects, perceived criticism (OR: 1.12) and paradoxically perceived support predicted future distress (OR = 1.14), while warmth was protective (OR = 0.87). Micro-interventions operate through stable networks and may yield cumulative rather than immediate benefits. High stress and criticism impede intervention use despite high need highlighting the necessity for context-sensitive, low-friction adaptive designs to align clinical need with receptivity.