Evidotes: Integrating Scientific Evidence and Anecdotes to Support Uncertainties Triggered by Peer Health Posts

要旨

Peer health posts surface new uncertainties, such as questions and concerns for readers. Prior work focused primarily on improving relevance and accuracy fails to address users' diverse information needs and emotions triggered. Instead, we propose directly addressing these by information augmentation. We introduce Evidotes, an information support system that augments individual posts with relevant scientific and anecdotal information retrieved using three user-selectable lenses (dive deeper, focus on positivity, and big picture). In a mixed-methods study with 17 chronic illness patients, Evidotes improved self-reported information satisfaction (3.2->4.6) and reduced self-reported emotional cost (3.4->1.9) compared to participants' baseline browsing. Moreover, by co-presenting sources, Evidotes unlocked information symbiosis: anecdotes made research accessible and contextual, while research helped filter and generalize peer stories. Our work enables an effective integration of scientific evidence and human anecdotes to help users better manage health uncertainty.

受賞
Honorable Mention
著者
Shreya Bali
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Riku Arakawa
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Peace Odiase
University of Pittsburgh, Pittsburgh, Pennsylvania, United States
Tongshuang Wu
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Mayank Goel
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States

会議: CHI 2026

ACM CHI Conference on Human Factors in Computing Systems

セッション: Physical Activity and Behavior Change Technologies

P1 - Room 134
7 件の発表
2026-04-15 20:15:00
2026-04-15 21:45:00