Sivathamboo Shobi, Nhu Duong, Piccenna Loretta, Yang Anthony, Antonic-Baker Ana, Vishwanath Swarna, Todaro Marian, Yap Lim Wei, Kuhlmann Levin, Cheng Wenlong, O'Brien Terence J, Lannin Natasha A, Kwan Patrick
From the Department of Neuroscience (S.S., L.P., A.Y., A.A.-B., S.V., M.T., T.J.O.B., N.A.L., P.K.), Central Clinical School, Monash University, Melbourne; Department of Neurology (S.S., L.P., A.Y., M.T., T.J.O.B., P.K.), Alfred Health, Melbourne; Department of Medicine (S.S., L.P., A.Y., M.T., T.J.O.B., P.K.), The Royal Melbourne Hospital, The University of Melbourne; Department of Neurology (S.S., M.T., T.J.O.B., P.K.), The Royal Melbourne Hospital; Department of Data Science and AI (D.N., L.K.), Faculty of Information Technology, and Department of Chemical and Biological Engineering (L.W.Y., W.C.), Monash University, Clayton; and Alfred Health (Allied Health Directorate) (N.A.L.), Melbourne, Victoria, Australia.
Neurology. 2022 Sep 27;99(13):e1380-e1392. doi: 10.1212/WNL.0000000000200794. Epub 2022 Jun 15.
To examine the preferences and user experiences of people with epilepsy and caregivers regarding automated wearable seizure detection devices.
We performed a mixed-methods systematic review. We searched electronic databases for original peer-reviewed publications between January 1, 2000, and May 26, 2021. Key search terms included "epilepsy," "seizure," "wearable," and "non-invasive." We performed a descriptive and qualitative thematic analysis of the studies included according to the technology acceptance model. Full texts of the discussion sections were further analyzed to identify word frequency and word mapping.
Twenty-two observational studies were identified. Collectively, they comprised responses from 3,299 participants including patients with epilepsy, caregivers, and healthcare workers. Sixteen studies examined user preferences, 5 examined user experiences, and 1 examined both experiences and preferences. Important preferences for wearables included improving care, cost, accuracy, and design. Patients desired real-time detection with a latency of ≤15 minutes from seizure occurrence, along with high sensitivity (≥90%) and low false alarm rates. Device-related costs were a major factor for device acceptance, where device costs of <$300 USD and a monthly subscription fee of <$20 USD were preferred. Despite being a major driver of wearable-based technologies, sudden unexpected death in epilepsy was rarely discussed. Among studies evaluating user experiences, there was a greater acceptance toward wristwatches. Thematic coding analysis showed that attitudes toward device use and perceived usefulness were reported consistently. Word mapping identified "specificity," "cost," and "battery" as key single terms and "battery life," "insurance coverage," "prediction/detection quality," and the effect of devices on "daily life" as key bigrams.
User acceptance of wearable technology for seizure detection was strongly influenced by accuracy, design, comfort, and cost. Our findings emphasize the need for standardized and validated tools to comprehensively examine preferences and user experiences of wearable devices in this population using the themes identified in this study. Greater efforts to incorporate perspectives and user experiences in developing wearables for seizure detection, particularly in community-based settings, are needed.
PROSPERO Registration CRD42020193565.
探讨癫痫患者及其照料者对可穿戴式自动癫痫发作检测设备的偏好和使用体验。
我们进行了一项混合方法的系统评价。检索了电子数据库，查找2000年1月1日至2021年5月26日期间经同行评审的原始出版物。关键检索词包括“癫痫”“发作”“可穿戴设备”和“非侵入性”。我们根据技术接受模型对纳入的研究进行了描述性和定性主题分析。对讨论部分的全文进行了进一步分析，以确定词频和词汇映射。
共纳入22项观察性研究。这些研究总共收集了3299名参与者的反馈，包括癫痫患者、照料者和医护人员。16项研究考察了用户偏好，5项研究考察了用户体验，1项研究同时考察了体验和偏好。对可穿戴设备的重要偏好包括改善护理、成本、准确性和设计。患者希望实现实时检测，发作发生后延迟≤15分钟，同时具有高灵敏度（≥90%）和低误报率。设备相关成本是影响设备接受度的主要因素，人们更倾向于设备成本低于300美元且月订阅费低于20美元的产品。尽管癫痫猝死是可穿戴技术的一个主要驱动因素，但在研究中很少被提及。在评估用户体验的研究中，对手表的接受度更高。主题编码分析表明，对设备使用的态度和感知有用性的报告较为一致。词汇映射确定“特异性”“成本”和“电池”为关键单字，“电池寿命”“保险覆盖范围”“预测/检测质量”以及设备对“日常生活”的影响为关键双字。
用户对用于癫痫发作检测的可穿戴技术的接受度受到准确性、设计、舒适度和成本的强烈影响。我们的研究结果强调需要使用本研究确定的主题，采用标准化和经过验证的工具，全面考察该人群对可穿戴设备的偏好和用户体验。在开发用于癫痫发作检测的可穿戴设备时，需要做出更大努力，纳入不同的观点和用户体验，尤其是在社区环境中。
PROSPERO注册编号CRD42020193565。
