用智能代理分析手机数据，提前发现癌症康复者情绪危机
PULSE: Agentic Investigation with Passive Sensing for Proactive Affective Intervention in Cancer Survivorship
- 用大模型代理主动查询手机传感数据，动态选择分析维度
- 在无日记记录时仍能以71.3%准确率预测干预需求
- 适合关注心理健康预警与被动感知技术的临床研究者
癌症康复者抑郁、焦虑和情绪困扰风险较高，但情绪低落时往往无法及时填写日记，形成‘日记悖论’。本文提出PULSE系统，通过配备八种专用工具的大模型代理，主动查询智能手机传感数据，比较当前行为与个人基线，并检索带结果标签的历史案例。代理可自主选择分析的模态与时长窗口，而非仅接收固定特征摘要。我们在50名癌症康复者中采用两因素实验设计，对比系统架构（单轮结构式 vs. 多轮代理式）与输入模态（无实时日记 vs. 感知数据+实时日记）。结果显示，多轮代理结合多模态数据条件下，情绪调节意愿预测的平衡准确率达0.743；在无实时日记情况下，自我报告干预可用性预测准确率为0.713。该研究为交互式感知调查提供了系统级基准，推动在用户无法写日记时刻的前瞻性评估。
原文摘要 · Abstract (English)
Cancer survivors face elevated rates of depression, anxiety, and emotional distress, yet self-report may be unavailable at some moments when support is relevant, a challenge we term the diary paradox. We present PULSE, a system for agentic sensing investigation: LLM agents equipped with eight purpose-built tools query smartphone sensing data, compare current behavior with personal baselines, and retrieve outcome-labeled historical cases. Rather than receiving only a fixed feature summary, agents choose which modalities and time windows to inspect. We evaluate PULSE through a two-by-two evaluation design crossing system architecture (structured single-pass vs. multi-turn agentic) with concurrent input modality (no current diary vs. sensing plus current diary) on 50 cancer survivors. The agentic multimodal condition achieves balanced accuracy of 0.743 for emotion-regulation desire; the agentic no-current-diary condition achieves 0.713 for self-reported intervention availability. This is a system-level comparison because the architecture conditions also differ in tool-mediated information access. The results provide a retrospective benchmark for interactive sensing investigation and motivate prospective evaluation at diary non-response moments.
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