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

arXiv: https://arxiv.org/abs/2503.03532 · HTML: https://mlsanity.com/paper/2503.03532/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 23 of its 125 references that are in the map.
- First posted on arXiv 5 Mar 2025.

## Builds on (most cited first, 23 of 23)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [GPT-4 Technical Report](https://mlsanity.com/paper/2303.08774/) (2023)
- [HuggingFace's Transformers: State-of-the-art Natural Language Processing](https://mlsanity.com/paper/1910.03771/) (2019)
- [Meta-learning via Language Model In-context Tuning](https://mlsanity.com/paper/2110.07814/) (2021)
- [What makes a good conversation? How controllable attributes affect human judgments](https://mlsanity.com/paper/1902.08654/) (2019)
- [Optimization Methods for Personalizing Large Language Models through Retrieval Augmentation](https://mlsanity.com/paper/2404.05970/) (2024)
- [Rasa: Open Source Language Understanding and Dialogue Management](https://mlsanity.com/paper/1712.05181/) (2017)
- [MindfulDiary: Harnessing Large Language Model to Support Psychiatric Patients' Journaling](https://mlsanity.com/paper/2310.05231/) (2023)
- [Leveraging Large Language Models to Power Chatbots for Collecting User Self-Reported Data](https://mlsanity.com/paper/2301.05843/) (2023)
- [Prompting Is All You Need: Automated Android Bug Replay with Large Language Models](https://mlsanity.com/paper/2306.01987/) (2023)
- [DIET: Lightweight Language Understanding for Dialogue Systems](https://mlsanity.com/paper/2004.09936/) (2020)
- [ChaCha: Leveraging Large Language Models to Prompt Children to Share Their Emotions about Personal Events](https://mlsanity.com/paper/2309.12244/) (2023)
- [Protecting Users From Themselves: Safeguarding Contextual Privacy in Interactions with Conversational Agents](https://mlsanity.com/paper/2502.18509/) (2025)
- [If I Hear You Correctly: Building and Evaluating Interview Chatbots with Active Listening Skills](https://mlsanity.com/paper/2002.01862/) (2020)
- [How do you Converse with an Analytical Chatbot? Revisiting Gricean Maxims for Designing Analytical Conversational Behavior](https://mlsanity.com/paper/2203.08420/) (2022)
- [Investigating Robustness of Dialog Models to Popular Figurative Language Constructs](https://mlsanity.com/paper/2110.00687/) (2021)
- [Understanding the Impact of Long-Term Memory on Self-Disclosure with Large Language Model-Driven Chatbots for Public Health Intervention](https://mlsanity.com/paper/2402.11353/) (2024)
- [Contextual AI Journaling: Integrating LLM and Time Series Behavioral Sensing Technology to Promote Self-Reflection and Well-being using the MindScape App](https://mlsanity.com/paper/2404.00487/) (2024)
- [Designing Effective Interview Chatbots: Automatic Chatbot Profiling and Design Suggestion Generation for Chatbot Debugging](https://mlsanity.com/paper/2104.04842/) (2021)
- [Ensemble-Based Deep Reinforcement Learning for Chatbots](https://mlsanity.com/paper/1908.10422/) (2019)
- [Empathic Chatbot: Emotional Intelligence for Empathic Chatbot: Emotional Intelligence for Mental Health Well-being](https://mlsanity.com/paper/2012.09130/) (2020)
- [Communicating Patient Health Data: A Wicked Problem](https://mlsanity.com/paper/2110.07806/) (2021)

## Built on by (most cited first, 4 of 4)

- [The Impact of a Chatbot's Ephemerality-Framing on Self-Disclosure Perceptions](https://mlsanity.com/paper/2505.20464/) (2025)
- [Does My Chatbot Have an Agenda? Understanding Human and AI Agency in Human-Human-like Chatbot Interaction](https://mlsanity.com/paper/2601.22452/) (2026)
- [AI and My Values: User Perceptions of LLMs' Ability to Extract, Embody, and Explain Human Values from Casual Conversations](https://mlsanity.com/paper/2601.22440/) (2026)
- [From 'What' to 'How' and 'Why': Sharing LLM-Generated Retrospective Summaries of Older Adults' Passive Tracking Data with Remote Family Members](https://mlsanity.com/paper/2606.03876/) (2026)

## 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.