arXiv cs.CL· Tamunotonye Harry, Johanna Hidalgo, Matthew Price, Yuanyuan Feng, Kathryn Stanton, Connie Tompkins, Peter Sheridan Dodds, Mikaela Irene Fudolig, Laura Bloomfield, Christopher Danforth·· 9 天前AI 评分22
超简短情感文本能否补充可穿戴传感？基于 Oura 戒指的 458 名学生一年期研究
A Formative Study of Brief Affective Text as a Complement to Wearable Sensing for Longitudinal Student Health Monitoring
AI 导读
一项为期一年、覆盖 458 名大学生（3,610 人次）的研究用 Oura 戒指追踪睡眠与身体活动，并每两月让参与者用中位数仅 3 个词的开放式文本写下最担忧的事。结果显示，以学业担忧为主的周次与更低身体活动相关，出现情绪耗竭措辞的周次与更差睡眠质量和更低心率变异性相关；通用预训练嵌入在多数结果上不逊于领域适配模型，零样本担忧主题分类则未见一致关联。
正文 · 原文
Abstract:Wearable devices capture physiological and behavioral data with increasing fidelity, but the psychological context shaping these outcomes is difficult to recover from sensor data alone, limiting the utility of passive sensing for digital health goals such as early detection of distress, personalized intervention, and timely clinical outreach. We examined whether ultra-brief naturalistic concern text could serve as a scalable complement to passive sensing. In a year-long study of 458 university students (3,610 person-waves) tracked with Oura rings, participants responded bimonthly to an open-ended prompt about what concerned them most; responses had a median length of three words. We compared dictionary-based, general pretrained, and domain-adapted NLP approaches using within-person mixed-effects models across nine sleep and physical activity outcomes to determine which method best recovers physiologically relevant signal from brief naturalistic text. Weeks dominated by academic concern framing were associated with lower physical activity; weeks characterized by emotional exhaustion language were associated with poorer sleep quality and lower heart rate variability. General pretrained embeddings performed as well as or better than domain-adapted models across most outcomes, with differences between the two generally small and within the range of estimation noise. Zero-shot classification of concern topics showed no consistent evidence of association with outcomes; affective dimensions across all three methods showed more associations, though these did not survive correction for multiple comparisons, offering preliminary evidence that emotional register may carry more signal than topical content. These findings offer design guidance: ultra-brief affective prompts enrich the psychological interpretability of passive physiological data at minimal burden.
| Subjects: | Human-Computer Interaction (cs.HC); Computation and Language (cs.CL) |
| Cite as: | arXiv:2605.14360 [cs.HC] |
| (or arXiv:2605.14360v2 [cs.HC] for this version) | |
| https://doi.org/10.48550/arXiv.2605.14360 arXiv-issued DOI via DataCite |
|
| Journal reference: | Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 10, 4, Article 219 (December 2026) |
| Related DOI: | https://doi.org/10.1145/3857988
DOI(s) linking to related resources |
Submission history
From: Tamunotonye Harry [view email]
[v1]
Thu, 14 May 2026 04:36:29 UTC (5,866 KB)
[v2]
Wed, 7 Oct 2026 20:19:04 UTC (6,078 KB)
来源：arXiv cs.CL · arxiv.org