JMIR Publications

ABSTRACT

Background:

Stress is a widespread public health concern associated with cardiovascular disease, depression, anxiety and reduced quality of life. Digital mental health interventions (DMHIs), delivered through smartphones, web platforms and wearables, offer scalable support for stress management but often struggle to sustain user engagement. Evidence describing how adaptive, conversational and context-aware mechanisms function together within stress-focused DMHIs remains fragmented.

Objective:

This review aims to synthesise evidence on engagement-supportive mechanisms in stress-focused DMHIs, with attention to personalisation, biometric feedback, Just-in-Time Adaptive Interventions (JITAIs), gamification, artificial intelligence (AI), including large language models (LLMs), and methodological approaches to studying engagement. It also examines methodological, motivational and experiential dimensions of engagement.

Methods:

This narrative review was informed by a structured search of PubMed, IEEE Xplore and Scopus for peer-reviewed studies published between January 2018 and April 2025, followed by an evidence update through August 2026. Eligible studies described stress-focused DMHIs or related affective-support interventions reporting at least one engagement-supportive mechanism. Randomised controlled trials, qualitative investigations, simulation or modelling studies and implementation research were included. Data were extracted using a structured form capturing study characteristics, engagement mechanisms, outcomes and alignment with the review domains. Descriptive mapping summarised study types and mechanism frequencies, while narrative synthesis integrated behavioural, experiential, methodological and theory-informed findings.

Results:

Thirty-two studies met the inclusion criteria. Randomised or microrandomised controlled trials were the most common design (17/32), followed by qualitative investigations (6/32), design or implementation studies (3/32), mixed-methods studies (3/32), simulation or modelling studies (2/32) and one quasi-experimental study (1/32). Dynamic adaptation was identified in 14 studies, conversational support in 10, static tailoring in 9, social or co-design mechanisms in 9, context-aware prompting in 7, gamified reinforcement in 5, biometric-responsive adaptation in 4 and narrative immersion in 2. These mechanisms frequently overlapped within layered adaptive architectures rather than functioning as isolated engagement features. AI-enabled systems included conversational agents, LLM-supported systems, recommender systems, reinforcement learning (RL) and computational modelling approaches. Outcomes included behavioural indicators such as adherence, retention and prompt receptivity, alongside experiential indicators such as perceived relevance, trust, emotional support and immersion. Evidence strength varied substantially; many AI-enabled systems contributed feasibility, acceptability or optimisation-oriented evidence rather than definitive comparative effectiveness evidence.

Conclusions:

Stress-focused DMHIs are increasingly adopting adaptive, conversational and context-aware engagement-supportive mechanisms, but the evidence base remains heterogeneous and methodologically uneven. Dynamic adaptation, conversational support and static tailoring were most frequently represented, whereas biometric-responsive adaptation, narrative immersion and deeply integrated gamified systems were less common. AI-enabled systems may support contextual responsiveness and personalised interaction, but require transparent adaptive logic, privacy safeguards and human-centred evaluation. Future work should prioritise longitudinal, mixed-methods research capable of distinguishing behavioural engagement, experiential engagement, feasibility, acceptability and sustained stress-related outcomes.