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Currently accepted at: JMIR Human Factors

Date Submitted: Jan 5, 2026
Date Accepted: Oct 6, 2026

This paper has been accepted and is currently in production.

It will appear shortly on 10.2196/90855

The final accepted version (not copyedited yet) is in this tab.

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

User Engagement Strategies in Digital Mental Health Interventions for Stress Management: A Narrative Review

  • Munesu Maminimini; 
  • Silvia Gabrielli; 
  • Sofia Asteria Piffer

ABSTRACT

Background:

Stress is a ubiquitous public health concern associated with increased risk of cardiovascular disease, depression, anxiety, and reduced quality of life. Digital mental health interventions (DMHIs), delivered via smartphones, web platforms and wearables, offer scalable support for stress management but often struggle to sustain user engagement which is a prerequisite for their effectiveness. Emerging adaptive mechanisms, such as personalisation and gamification, aim to enhance contextual relevance, emotional resonance and user adherence but the evidence describing how these mechanisms function together within stress focused DMHIs, remains fragmented.

Objective:

This review aims to synthesise evidence on engagement strategies in stress-focused DMHIs, identifying effective adherence techniques, the influence of personalisation, biometric feedback, Just-In-Time Adaptive Interventions (JITAIs), gamification and Artificial Intelligence (including large language models, LLMs), and methodological approaches to studying engagement.

Methods:

This narrative review was informed by a systematic search of PubMed, IEEE Xplore, and Scopus (January 2018–April 2025) for peer‑reviewed studies on stress‑focused DHIs reporting at least one engagement feature. Eligible studies included randomised controlled trials, qualitative investigations, simulation or modelling work, and implementation research. Data were extracted using a structured analysis capturing study characteristics, engagement strategies, outcomes, and alignment with the research questions. Descriptive statistics summarised study types and feature frequencies, while a narrative synthesis integrated descriptive mapping with interpretive, theory‑informed analysis organised by research question.

Results:

22 studies met the inclusion criteria. Randomised controlled trials (10) were most common, followed by qualitative investigations (5) and design or simulation studies (7). 14 studies incorporated personalisation and JITAI features, 2 included biometric feedback, and 3 used gamification elements. 11 studies integrated AI, 7 of which employed generative LLM chatbots. Interventions combining tailored content with contextually timed delivery achieved higher adherence than static programmes. Personalisation often co‑occurred with AI, while biometric and JITAI features appeared mainly in technologically advanced systems. Adaptive components enhanced perceived relevance and emotional engagement but raised concerns about transparency, privacy, and burden. Wearable‑triggered prompts and reinforcement learning demonstrated potential, yet remained sensitive to privacy risks. Gamification boosted short‑term motivation when embedded in meaningful narratives, but showed mixed results when poorly implemented. Qualitative analyses further identified barriers related to power dynamics, cultural relevance, and data transparency.

Conclusions:

Adaptive personalisation and timely delivery were the most effective engagement strategies, while biometric feedback and gamification remain underused. AI and reinforcement learning enable contextual support, but require safeguards for transparency and fairness. Diverse methods across RCTs, qualitative and implementation research provided complementary insights. Stress management DHIs are evolving toward intelligent, user-centred systems that adapt to emotional and contextual states. Future work should emphasise interpretable AI, culturally grounded co-design and longitudinal, mixed-methods evaluation to sustain engagement and equitable stress reduction.


 Citation

Please cite as:

Maminimini M, Gabrielli S, Piffer SA

User Engagement Strategies in Digital Mental Health Interventions for Stress Management: A Narrative Review

JMIR Preprints. 05/01/2026:90855

DOI: 10.2196/preprints.90855

URL: https://preprints.jmir.org/preprint/90855

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