mlsanityData to 7 Oct 2026

AI-Enabled Conversational Journaling for Advancing Parkinson's Disease Symptom Tracking

arXiv 2503.03532 ↗First posted 5 Mar 2025cs.HC cs.AIcited by 4

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Abstract (arXiv)

Journaling plays a crucial role in managing chronic conditions by allowing patients to document symptoms and medication intake, providing essential data for long-term care. While valuable, traditional journaling methods often rely on static, self-directed entries, lacking interactive feedback and real-time guidance. This gap can result in incomplete or imprecise information, limiting its usefulness for effective treatment. To address this gap, we introduce PATRIKA, an AI-enabled prototype designed specifically for people with Parkinson's disease (PwPD). The system incorporates cooperative conversation principles, clinical interview simulations, and personalization to create a more effective and user-friendly journaling experience. Through two user studies with PwPD and iterative refinement of PATRIKA, we demonstrate conversational journaling's significant potential in patient engagement and collecting clinically valuable information. Our results showed that generating probing questions PATRIKA turned journaling into a bi-directional interaction. Additionally, we offer insights for designing journaling systems for healthcare and future directions for promoting sustained journaling.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 23 of its 125 references that are in the map. First posted on arXiv 5 Mar 2025.

Builds on

23 of 125 references.

References · 23

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11 more
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 1; 2026: 3.

4 papers.

  1. 2025The Impact of a Chatbot's Ephemerality-Framing on Self-Disclosure Perceptionscited by 6
  2. 2026Does My Chatbot Have an Agenda? Understanding Human and AI Agency in Human-Human-like Chatbot Interactioncited by 3
  3. 2026AI and My Values: User Perceptions of LLMs' Ability to Extract, Embody, and Explain Human Values from Casual Conversationscited by 2
  4. 2026From 'What' to 'How' and 'Why': Sharing LLM-Generated Retrospective Summaries of Older Adults' Passive Tracking Data with Remote Family Memberscited by 0