arXiv 2409.095702024-09-15cs.HCcs.AI

MindScape研究：整合大语言模型与行为感知以实现个性化AI驱动的日记体验

MindScape Study: Integrating LLM and Behavioral Sensing for Personalized AI-Driven Journaling Experiences

Dartmouth College（达特茅斯学院）；Colby College（科尔比学院）；Brown University（布朗大学）；Cornell Tech（康奈尔科技学院）；Massachusetts Institute of Technology（麻省理工学院）；University College London（伦敦大学学院）；Biocogniv Inc（比奥认知公司）；University of California, San Diego（加利福尼亚大学圣迭戈分校）；Microsoft Research（微软研究院）

Subigya Nepal, Arvind Pillai, William Campbell, Talie Massachi, Michael V. Heinz, Ashmita Kunwar, Eunsol Soul Choi, Orson Xu, Joanna Kuc, Jeremy Huckins, Jason … 展开作者

Subigya Nepal, Arvind Pillai, William Campbell, Talie Massachi, Michael V. Heinz, Ashmita Kunwar, Eunsol Soul Choi, Orson Xu, Joanna Kuc, Jeremy Huckins, Jason Holden, Sarah M. Preum, Colin Depp, Nicholas Jacobson, Mary Czerwinski, Eric Granholm, Andrew T. Campbell

备注：: arXiv admin note: text overlap with arXiv:2404.00487

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AI总结：

针对大学生心理健康问题，本研究推出整合行为感知数据与LLM的个性化情境AI日记应用MindScape，经8周20人实验验证其可改善情绪、降低焦虑抑郁等，为校园心理健康干预提供新方向。

摘要：

心理健康问题在大学生群体中普遍存在，凸显了对能提升自我认知与整体幸福感的有效干预手段的需求。MindScape开创了AI赋能日记的全新路径，将对话参与度、睡眠、位置等被动收集的行为模式与大语言模型（Large Language Models, LLM）相融合。这种整合打造了高度个性化且具备情境感知能力的日记体验，通过将行为智能嵌入AI系统来提升自我认知与幸福感。我们开展了一项为期8周、招募20名大学生的探索性研究，结果证明MindScape应用可有效提升积极情绪（7%），降低消极情绪（11%）、孤独感（6%）以及焦虑与抑郁水平，其PHQ-4评分呈显著的逐周下降趋势（系数为-0.25），同时正念水平（7%）与自我反思能力（6%）也有所提升。该研究凸显了情境化AI日记的优势，参与者尤其认可MindScape应用提供的定制化提示与洞察。我们的分析还包括了对AI驱动的情境化提示与通用提示的反馈对比、参与者反馈洞察，以及利用情境化AI日记提升大学校园幸福感的策略建议。通过展示情境化AI日记在心理健康支持方面的潜力，本研究为进一步探究情境化AI日记对心理健康与幸福感的影响奠定了基础。

英文摘要：

Mental health concerns are prevalent among college students, highlighting the need for effective interventions that promote self-awareness and holistic well-being. MindScape pioneers a novel approach to AI-powered journaling by integrating passively collected behavioral patterns such as conversational engagement, sleep, and location with Large Language Models (LLMs). This integration creates a highly personalized and context-aware journaling experience, enhancing self-awareness and well-being by embedding behavioral intelligence into AI. We present an 8-week exploratory study with 20 college students, demonstrating the MindScape app's efficacy in enhancing positive affect (7%), reducing negative affect (11%), loneliness (6%), and anxiety and depression, with a significant week-over-week decrease in PHQ-4 scores (-0.25 coefficient), alongside improvements in mindfulness (7%) and self-reflection (6%). The study highlights the advantages of contextual AI journaling, with participants particularly appreciating the tailored prompts and insights provided by the MindScape app. Our analysis also includes a comparison of responses to AI-driven contextual versus generic prompts, participant feedback insights, and proposed strategies for leveraging contextual AI journaling to improve well-being on college campuses. By showcasing the potential of contextual AI journaling to support mental health, we provide a foundation for further investigation into the effects of contextual AI journaling on mental health and well-being.

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