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

Shreya Bali, Riku Arakawa, Peace Odiase, Tongshuang Wu, Mayank Goel

TL;DR

Eidotes is introduced, an information support system that augments individual posts with relevant scientific and anecdotal information retrieved using three user-selectable lenses that enables an effective integration of scientific evidence and human anecdotes to help users better manage health uncertainty.

Abstract

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.

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

TL;DR

Eidotes is introduced, an information support system that augments individual posts with relevant scientific and anecdotal information retrieved using three user-selectable lenses that enables an effective integration of scientific evidence and human anecdotes to help users better manage health uncertainty.

Abstract

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.
Paper Structure (45 sections, 5 figures, 3 tables)

This paper contains 45 sections, 5 figures, 3 tables.

Table of Contents

  1. Introduction
  2. Contributions
  3. Related Work
  4. Uncertainty in Illness: Managing Health Unknowns
  5. Anecdotes as Catalysts that Surface Health Uncertainties
  6. Current Technological Responses: Strengths and Limitations
  7. Information Quality and Verification
  8. Anecdotes as Emotional and Social Infrastructure
  9. Formative Study
  10. Findings
  11. The Integration Paradox: Seeking Synthesis while Maintaining Separation.
  12. Anecdotes as Uncertainty Triggers.
  13. Serendipitous Discovery Competes with Focused Information Goals.
  14. Summary
  15. Proposed System: Evidotes
  16. ...and 30 more sections

Figures (5)

  • Figure 1: Evidotes supports patients in navigating health forums by combining scientific evidence with peer experiences. As a browser extension, it adds a button next to reddit posts and allows users to select different lenses (Dive Deeper, Focus on Positivity, and Big Picture) through a dropdown (A) based on their needs, and augments the original Reddit post with the synthesized information in an overlayed information pane (B) in form of claims. The figure shows a simplified view of Evidotes instantiation and the surfaced information across the three lenses.
  • Figure 2: Interface flow showing Evidotes' three lens options (A) and resulting information panels (B) . 1. Top Left: Original Post with Evidotes Button and Dropdown 2. Bottom Left: "Dive Deeper" panel with a claim expanded to show a detailed view with both Research Findings (scientific papers from PubMed) and User Anecdotes (Reddit posts) sections. 3. Top Right: "Focus on Positivity" panel displaying positive outcomes and success stories related to Metformin and PCOS. 4. Bottom Right: "Big Picture" panel providing a broader overview of PCOS management strategies, including lifestyle modifications and dietary changes.
  • Figure 3: Overview of the procedure of our user study, where 17 patients used Evidotes for their own illness navigation. Icons from The Noun Project: Advice Icon by Alzam, Interview by Adrien Coquet, Browser by Muhammad Shabraiz
  • Figure 4: User interaction trajectories showing lens selection and source expansion patterns. The Sankey diagram tracks flows from initial Evidotes clicks through lens selection, information consumption, and optional source expansion. "Sources Expanded" indicates clicks to view supporting materials—PubMed papers or Reddit posts. Flow thickness represents frequency. Key findings: Dive Deeper was most popular, 50% stopped at synthesized claims without expanding sources, and source expansion split roughly evenly between scientific and anecdotal materials. Users could view both source types per session; flows are separated for clarity.
  • Figure 5: Evidotes System Pre vs Post Study Results: Participants reported significant improvements in information satisfaction (3.2 to 4.6, p<.001, d=1.49) and reduced stress (3.4 to 1.9, p<.001, d=1.23) after using Evidotes compared to baseline browsing. The graph shows before/after comparisons for key outcome measures. The arrows on top of bar groups show the ideal direction of change.