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| Auteurs principaux: | , , , , , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| Sujets: | |
| Accès en ligne: | https://arxiv.org/abs/2503.03532 |
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| _version_ | 1866909525568651264 |
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| author | Rashik, Mashrur Sweth, Shilpa Agrawal, Nishtha Kochar, Saiyyam Smith, Kara M Rajabiyazdi, Fateme Setlur, Vidya Mahyar, Narges Sarvghad, Ali |
| author_facet | Rashik, Mashrur Sweth, Shilpa Agrawal, Nishtha Kochar, Saiyyam Smith, Kara M Rajabiyazdi, Fateme Setlur, Vidya Mahyar, Narges Sarvghad, Ali |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_03532 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | AI-Enabled Conversational Journaling for Advancing Parkinson's Disease Symptom Tracking Rashik, Mashrur Sweth, Shilpa Agrawal, Nishtha Kochar, Saiyyam Smith, Kara M Rajabiyazdi, Fateme Setlur, Vidya Mahyar, Narges Sarvghad, Ali Human-Computer Interaction Artificial Intelligence 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. |
| title | AI-Enabled Conversational Journaling for Advancing Parkinson's Disease Symptom Tracking |
| topic | Human-Computer Interaction Artificial Intelligence |
| url | https://arxiv.org/abs/2503.03532 |