用AI系统个性化冥想体验，提升用户参与度与心理效益。
MindfulAgents: Personalizing Mindfulness Meditation via an Expert-Aligned Multi-Agent System
- 基于专家框架的多智能体生成冥想脚本，实时适配用户需求。
- 实验室研究显示参与度提升、自我觉察增强，压力水平下降。
- 适合希望长期坚持冥想、追求个性化心理支持的人群。
正念冥想是广泛可及且有实证支持的心理健康干预手段。尽管冥想类应用众多，用户持续参与仍是一大挑战。个性化冥想体验是提升参与度的可行策略，但常需高昂的人工成本且难以扩展。本文提出MindfulAgents——一个由大语言模型驱动的多智能体系统，能（1）依据专家确立的正念框架生成引导式冥想脚本，（2）引导用户反思情绪状态与正念技能，（3）实现每位用户的实时个性化冥想体验。在一项初步实验室研究中（N=13），该系统显著提升了在场参与度（p = 0.011）和自我觉察能力（p = 0.014），并降低了即时压力（p = 0.020）。此外，为期四周的部署研究（N=62）显示，长期参与度显著提高（p = 0.002），正念水平也明显上升（p = 0.023）。参与者反馈称，系统提供的冥想内容更具针对性，能适应不同情境下的个人需求，有助于持续练习。研究结果表明，基于LLM的个性化策略在提升数字正念干预用户参与度方面具有巨大潜力。
原文摘要 · Abstract (English)
Mindfulness meditation is a widely accessible and evidence-based method for supporting mental health. Despite the proliferation of mindfulness meditation apps, sustaining user engagement remains a persistent challenge. Personalizing the meditation experience is a promising strategy to improve engagement, but it often requires costly and unscalable manual effort. We present MindfulAgents, a multi-agent system powered by large language models that (1) generates guided meditation scripts based on an expert-established mindfulness framework, (2) encourages users' reflection on emotional states and mindfulness skills, and (3) enables real-time personalization of the mindfulness meditation experience for each user. In a formative lab study (N=13), MindfulAgents significantly improved in-session engagement (p = 0.011) and self-awareness (p = 0.014), and reduced momentary stress (p = 0.020). Furthermore, a four-week deployment study (N=62) demonstrated a notable increase in long-term engagement (p = 0.002) and level of mindfulness (p = 0.023). Participants reported that MindfulAgents offered more relevant meditation sessions personalized to individual needs in various contexts, supporting sustained practice. Our findings highlight the potential of LLM-driven personalization for enhancing user engagement in digital mindfulness meditation interventions.
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