并非所有助推都能落地：AI辅助日记中的行为可控性与阐述质量
Not All Nudges Land: Behavioral Controllability and Elaboration Quality in AI-Supported Journaling
- University of Virginia（弗吉尼亚大学）
机构由 AI 辅助整理，请以论文原文为准。
中文总结 AI 辅助
该研究针对AI辅助日记，分析369篇条目后发现，涉及他人的行为改善率仅15%-22%，个人可独立实施的行为改善率达50%-63%，文本特征影响较小，为AI日记助推的适用方向提供了探索性结论。
中文摘要 AI 辅助
AI日记工具可根据个人感知到的行为定制提示，但目前尚不明确哪些行为会对这些提示产生响应。我们分析了一项为期八周的被动感知研究中的369篇日记条目，用一个LLM将每篇条目标记为是否表达了改变行为的意图，并通过为期3天的前后对比，依据26个传感器特征衡量后续执行情况。响应性主要取决于行为是否涉及他人：依赖他人的行为仅在15%至22%的案例中得到改善，而个人可独立实施的行为改善情况更频繁，达50%至63%，但存在不均衡性。用户的写作方式影响较小，没有单一文本特征可区分改善与未改善的条目；文本仅在特定行为中携带信号，最明显的是短信行为以及更长、更个人化的意图条目。由于样本量较小，我们将这些视为探索性模式，为AI日记助推最可能生效的方向提供了指向。
英文摘要
AI journaling tools can tailor prompts to a person's own sensed behavior, but it is unclear which behaviors respond to them. We analyzed 369 journal entries from an eight-week passive sensing study. An LLM labeled each entry as expressing an intention to change a behavior or not, and we measured follow-through against 26 sensor features with a 3-day before/after comparison. Responsiveness depended most on whether a behavior involves other people. Behaviors that depend on others improved in only 15 to 22% of cases, while behaviors a person can act on alone improved more often, up to 50 to 63%, though unevenly. How users wrote mattered less. No single text feature separated improved from unimproved entries; writing carried signal only within specific behaviors, most clearly for text messaging and for longer, more personal intention entries. The sample is small, so we treat these as exploratory patterns that point to where AI journaling nudges are most likely to work.
