Liu Yongtai, Yan Chao, Yin Zhijun, Wan Zhiyu, Xia Weiyi, Kantarcioglu Murat, Vorobeychik Yevgeniy, Clayton Ellen Wright, Malin Bradley A
Vanderbilt University, Nashville, TN.
University of Texas at Dallas, Richardson, Texas.
AMIA Annu Symp Proc. 2020 Mar 4;2019:607-616. eCollection 2019.
To accelerate medical knowledge discovery, an increasing number of research programs are gathering and sharing data on a large number of participants. Due to the privacy concerns and legal restrictions on data sharing, these programs apply various strategies to mitigate privacy risk. However, the activities of participants and research program sponsors, particularly on social media, might reveal an individual's membership in a study, making it easier to recognize participants' records and uncover the information they have yet to disclose. This behavior can jeopardize the privacy of the participants themselves, the reputation of the projects, sponsors, and the research enterprise. To investigate the dangers of self-disclosure behavior, we gathered and analyzed 4,020 tweets, and uncovered over 100 tweets disclosing the individuals' memberships in over 15 programs. Our investigation showed that self-disclosure on social media can reveal participants' membership in research cohorts, and such activity might lead to the leakage of a person's identity, genomic, and other sensitive health information.
为加速医学知识发现，越来越多的研究项目正在收集和共享大量参与者的数据。由于对数据共享存在隐私担忧和法律限制，这些项目采用各种策略来降低隐私风险。然而，参与者和研究项目赞助商的活动，尤其是在社交媒体上的活动，可能会暴露个人参与某项研究的情况，从而更容易识别参与者的记录并揭露他们尚未披露的信息。这种行为可能会危及参与者自身的隐私、项目、赞助商以及研究机构的声誉。为了调查自我披露行为的危险性，我们收集并分析了4020条推文，发现有100多条推文披露了个人参与15多个项目的情况。我们的调查表明，在社交媒体上的自我披露可能会暴露参与者在研究队列中的身份，而这种活动可能会导致个人身份、基因组和其他敏感健康信息的泄露。
