From Patient Burdens to User Agency: Designing for Real-Time Protection Support in Online Health Consultations
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866916875054612480 |
|---|---|
| author | Zhang, Shuning Ma, Ying Hu, Yongquan `Owen' Dang, Ting Jia, Hong Yi, Xin Li, Hewu |
| author_facet | Zhang, Shuning Ma, Ying Hu, Yongquan `Owen' Dang, Ting Jia, Hong Yi, Xin Li, Hewu |
| contents | Online medical consultation platforms, while convenient, are undermined by significant privacy risks that erode user trust. We first conducted in-depth semi-structured interviews with 12 users to understand their perceptions of security and privacy landscapes on online medical consultation platforms, as well as their practices, challenges and expectation. Our analysis reveals a critical disconnect between users' desires for anonymity and control, and platform realities that offload the responsibility of ``privacy labor''. To bridge this gap, we present SafeShare, an interaction technique that leverages localized LLM to redact consultations in real-time. SafeShare balances utility and privacy through selectively anonymize private information. A technical evaluation of SafeShare's core PII detection module on 3 dataset demonstrates high efficacy, achieving 89.64\% accuracy with Qwen3-4B on IMCS21 dataset. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_00328 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | From Patient Burdens to User Agency: Designing for Real-Time Protection Support in Online Health Consultations Zhang, Shuning Ma, Ying Hu, Yongquan `Owen' Dang, Ting Jia, Hong Yi, Xin Li, Hewu Human-Computer Interaction Online medical consultation platforms, while convenient, are undermined by significant privacy risks that erode user trust. We first conducted in-depth semi-structured interviews with 12 users to understand their perceptions of security and privacy landscapes on online medical consultation platforms, as well as their practices, challenges and expectation. Our analysis reveals a critical disconnect between users' desires for anonymity and control, and platform realities that offload the responsibility of ``privacy labor''. To bridge this gap, we present SafeShare, an interaction technique that leverages localized LLM to redact consultations in real-time. SafeShare balances utility and privacy through selectively anonymize private information. A technical evaluation of SafeShare's core PII detection module on 3 dataset demonstrates high efficacy, achieving 89.64\% accuracy with Qwen3-4B on IMCS21 dataset. |
| title | From Patient Burdens to User Agency: Designing for Real-Time Protection Support in Online Health Consultations |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2508.00328 |