Investigating Users' Attitudes Toward Automated Smartwatch Cardiac Arrest Detection: Cross-Sectional Survey Study.

IF 2.6 Q2 HEALTH CARE SCIENCES & SERVICES JMIR Human Factors Pub Date : 2024-07-25 DOI:10.2196/57574
Wisse M F van den Beuken, Hans van Schuppen, Derya Demirtas, Vokko P van Halm, Patrick van der Geest, Stephan A Loer, Lothar A Schwarte, Patrick Schober
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Abstract

Background: Out-of-hospital cardiac arrest (OHCA) is a leading cause of mortality in the developed world. Timely detection of cardiac arrest and prompt activation of emergency medical services (EMS) are essential, yet challenging. Automated cardiac arrest detection using sensor signals from smartwatches has the potential to shorten the interval between cardiac arrest and activation of EMS, thereby increasing the likelihood of survival.

Objective: This cross-sectional survey study aims to investigate users' perspectives on aspects of continuous monitoring such as privacy and data protection, as well as other implications, and to collect insights into their attitudes toward the technology.

Methods: We conducted a cross-sectional web-based survey in the Netherlands among 2 groups of potential users of automated cardiac arrest technology: consumers who already own a smartwatch and patients at risk of cardiac arrest. Surveys primarily consisted of closed-ended questions with some additional open-ended questions to provide supplementary insight. The quantitative data were analyzed descriptively, and a content analysis of the open-ended questions was conducted.

Results: In the consumer group (n=1005), 90.2% (n=906; 95% CI 88.1%-91.9%) of participants expressed an interest in the technology, and 89% (n=1196; 95% CI 87.3%-90.7%) of the patient group (n=1344) showed interest. More than 75% (consumer group: n= 756; patient group: n=1004) of the participants in both groups indicated they were willing to use the technology. The main concerns raised by participants regarding the technology included privacy, data protection, reliability, and accessibility.

Conclusions: The vast majority of potential users expressed a strong interest in and positive attitude toward automated cardiac arrest detection using smartwatch technology. However, a number of concerns were identified, which should be addressed in the development and implementation process to optimize acceptance and effectiveness of the technology.

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调查用户对智能手表心脏骤停自动检测的态度:横断面调查研究。
背景:在发达国家,院外心脏骤停(OHCA)是导致死亡的主要原因。及时发现心脏骤停并迅速启动紧急医疗服务(EMS)至关重要,但也极具挑战性。利用智能手表的传感器信号自动检测心脏骤停有可能缩短心脏骤停与启动紧急医疗服务之间的时间间隔,从而提高存活的可能性:本横断面调查研究旨在调查用户对隐私和数据保护等持续监测方面的看法以及其他影响,并收集他们对该技术的态度:我们在荷兰对两类心脏骤停自动监测技术的潜在用户进行了横向网络调查:已拥有智能手表的消费者和有心脏骤停风险的患者。调查主要由封闭式问题和一些开放式问题组成,以提供补充见解。对定量数据进行了描述性分析,并对开放式问题进行了内容分析:在消费者组(人数=1005)中,90.2%(人数=906;95% CI 88.1%-91.9%)的参与者表示对该技术感兴趣;在患者组(人数=1344)中,89%(人数=1196;95% CI 87.3%-90.7%)的参与者表示对该技术感兴趣。两组参与者中均有 75% 以上(消费者组:756 人;患者组:1004 人)表示愿意使用该技术。参与者对该技术提出的主要关切包括隐私、数据保护、可靠性和可访问性:绝大多数潜在用户对使用智能手表技术进行心脏骤停自动检测表示出浓厚的兴趣和积极的态度。但也发现了一些问题,应在开发和实施过程中加以解决,以优化该技术的接受度和有效性。
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来源期刊
JMIR Human Factors
JMIR Human Factors Medicine-Health Informatics
CiteScore
3.40
自引率
3.70%
发文量
123
审稿时长
12 weeks
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