تقرير
Perspectives on Privacy in the Post-Roe Era: A Mixed-Methods of Machine Learning and Qualitative Analyses of Tweets
| العنوان: | Perspectives on Privacy in the Post-Roe Era: A Mixed-Methods of Machine Learning and Qualitative Analyses of Tweets |
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| المؤلفون: | Guo, Yawen, Zehrung, Rachael, Genuario, Katie, Lu, Xuan, Mei, Qiaozhu, Chen, Yunan, Zheng, Kai |
| سنة النشر: | 2023 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Human-Computer Interaction |
| الوصف: | Abortion is a controversial topic that has long been debated in the US. With the recent Supreme Court decision to overturn Roe v. Wade, access to safe and legal reproductive care is once again in the national spotlight. A key issue central to this debate is patient privacy, as in the post-HITECH Act era it has become easier for medical records to be electronically accessed and shared. This study analyzed a large Twitter dataset from May to December 2022 to examine the public's reactions to Roe v. Wade's overruling and its implications for privacy. Using a mixed-methods approach consisting of computational and qualitative content analysis, we found a wide range of concerns voiced from the confidentiality of patient-physician information exchange to medical records being shared without patient consent. These findings may inform policy making and healthcare industry practices concerning medical privacy related to reproductive rights and women's health. Comment: Paper accepted for the proceedings of the 2023 American Medical Informatics Association Annual Symposium (AMIA) |
| نوع الوثيقة: | Working Paper |
| الوصول الحر: | http://arxiv.org/abs/2311.11486Test |
| رقم الانضمام: | edsarx.2311.11486 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |