以用户为中心的帕金森病患者赋权框架

IF 3.6 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Pub Date : 2024-01-12 DOI:10.1145/3631430
Wasifur Rahman, Abdelrahman Abdelkader, Sangwu Lee, Phillip T. Yang, Md Saiful Islam, Tariq Adnan, Masum Hasan, Ellen Wagner, Sooyong Park, E. R. Dorsey, Catherine Schwartz, Karen Jaffe, Ehsan Hoque
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引用次数: 0

摘要

我们介绍了一个以用户为中心的远程神经病学平台验证,评估其在传递筛查信息、方便用户查询以及提供资源以增强用户能力方面的有效性。这一验证过程是与美国一家大型医疗中心的神经科合作,在帕金森病(PD)的背景下实施的。我们的目标是,通过这一平台,全球任何拥有网络摄像头和麦克风的电脑用户都能完成一系列语言、运动和面部模仿任务。我们的验证方法向用户展示了模拟的帕金森病风险评估,并提供了访问相关资源的途径,包括由 GPT 驱动的聊天机器人、当地神经科医生的位置,以及可操作且有科学依据的帕金森病预防和管理建议。我们分享了 91 位参与者(48 位患有帕金森病,43 位没有帕金森病)的调查结果,旨在评估用户体验并收集反馈意见。80.85%(标准差 ± 8.92%)的参与者对我们的框架给予了积极评价,其系统可用性量表(SUS)得分高于平均水平 70.42(标准差 ± 13.85)。我们还对开放式反馈进行了专题分析,以便为今后的工作提供更多信息。当参与者可以向聊天机器人提出任何问题时,他们通常会询问有关神经科医生、筛查结果和社区支持小组的信息。我们还提供了一个路线图,说明如何通过设计适当的记录环境、适当的任务和量身定制的用户界面,将本文中生成的知识推广到其他疾病的筛查框架中。
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A User-Centered Framework to Empower People with Parkinson's Disease
We present a user-centric validation of a teleneurology platform, assessing its effectiveness in conveying screening information, facilitating user queries, and offering resources to enhance user empowerment. This validation process is implemented in the setting of Parkinson's disease (PD), in collaboration with a neurology department of a major medical center in the USA. Our intention is that with this platform, anyone globally with a webcam and microphone-equipped computer can carry out a series of speech, motor, and facial mimicry tasks. Our validation method demonstrates to users a mock PD risk assessment and provides access to relevant resources, including a chatbot driven by GPT, locations of local neurologists, and actionable and scientifically-backed PD prevention and management recommendations. We share findings from 91 participants (48 with PD, 43 without) aimed at evaluating the user experience and collecting feedback. Our framework was rated positively by 80.85% (standard deviation ± 8.92%) of the participants, and it achieved an above-average 70.42 (standard deviation ± 13.85) System-Usability-Scale (SUS) score. We also conducted a thematic analysis of open-ended feedback to further inform our future work. When given the option to ask any questions to the chatbot, participants typically asked for information about neurologists, screening results, and the community support group. We also provide a roadmap of how the knowledge generated in this paper can be generalized to screening frameworks for other diseases through designing appropriate recording environments, appropriate tasks, and tailored user-interfaces.
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来源期刊
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Computer Science-Computer Networks and Communications
CiteScore
9.10
自引率
0.00%
发文量
154
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