影响可穿戴设备继续使用的因素和设计特征。

IF 5.9 Q1 Computer Science
Journal of Healthcare Informatics Research Pub Date : 2023-07-13 eCollection Date: 2023-09-01 DOI:10.1007/s41666-023-00135-4
Omar El-Gayar, Ahmed Elnoshokaty
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引用次数: 0

摘要

可穿戴设备的最初健康使用并不一定伴随着持续或持续使用。因此,本研究调查了影响可穿戴设备持续使用的因素,特别强调了设计特征。我们用各种设计特征,如信任、可读性、对话支持、个性化、设备电池、吸引力和社会支持,补充了预期确认模型(ECM)的理论基础。该研究采用了一种同时混合的方法研究设计,表示为QUANT+qual。定量分析利用从可穿戴设备用户收集的调查数据,利用偏最小二乘结构方程建模(PLS-SEM)。定性分析通过深入了解定量分析的结果,补充了研究的定量重点。我们发现,受试者倾向于每天(60%)或每周使用几次可穿戴设备(33%),91%的人计划更多地使用它们。受试者表示可穿戴设备有多种用途。大多数受试者将可穿戴设备用于医疗保健(61%)或体育健身(54%),并拥有可穿戴型智能手表(74%)。该模型解释了24.1%(p<0.01)的持续使用意愿方差。作为一项理论贡献,这些发现支持将ECM作为解释可穿戴设备持续使用的理论基础。偏最小二乘法(PLS)和定性数据分析强调了可穿戴用户对感知有用性的相对重要性。最值得注意的是跟踪功能和设计功能,如设备电池、与其他应用程序/设备的集成、对话支持和吸引力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Factors and Design Features Influencing the Continued Use of Wearable Devices.

The initial healthy uptake of wearable devices is not necessarily accompanied by sustained or continued use. Accordingly, this study investigates the factors influencing the continuous use of wearable devices with a particular emphasis on design features. We complemented the expectation-confirmation model (ECM) theoretical foundation with various design features such as trust, readability, dialogue support, personalization, device battery, appeal, and social support. The study employs a simultaneous mixed method research design denoted as QUANT + qual. The quantitative analysis leverages partial least squares structural equation modeling (PLS-SEM) using survey data collected from wearable device users. The qualitative analysis complements the quantitative focus of the research by providing insights into the results obtained from the quantitative analysis. We found that subjects tend to use wearables daily (60%) or several times a week (33%), and 91% plan to use them even more. Subjects indicated multiple usages for wearables. Most subjects were using wearables for healthcare and wellness (61%) or sports and fitness (54%) and had smartwatches wearable type (74%). The model explains 24.1% (p < 0.01) of the variance of continued intention to use. As a theoretical contribution, the findings support using the ECM as a theoretical foundation for explaining the continued use of wearables. Partial least squares (PLS) and qualitative data analysis highlight the relative importance that wearable users place on perceived usefulness. Most notable are tracking functions and design features such as device battery, integration with other apps/devices, dialogue support, and appeal.

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来源期刊
Journal of Healthcare Informatics Research
Journal of Healthcare Informatics Research Computer Science-Computer Science Applications
CiteScore
13.60
自引率
1.70%
发文量
12
期刊介绍: Journal of Healthcare Informatics Research serves as a publication venue for the innovative technical contributions highlighting analytics, systems, and human factors research in healthcare informatics.Journal of Healthcare Informatics Research is concerned with the application of computer science principles, information science principles, information technology, and communication technology to address problems in healthcare, and everyday wellness. Journal of Healthcare Informatics Research highlights the most cutting-edge technical contributions in computing-oriented healthcare informatics.  The journal covers three major tracks: (1) analytics—focuses on data analytics, knowledge discovery, predictive modeling; (2) systems—focuses on building healthcare informatics systems (e.g., architecture, framework, design, engineering, and application); (3) human factors—focuses on understanding users or context, interface design, health behavior, and user studies of healthcare informatics applications.   Topics include but are not limited to: ·         healthcare software architecture, framework, design, and engineering;·         electronic health records·         medical data mining·         predictive modeling·         medical information retrieval·         medical natural language processing·         healthcare information systems·         smart health and connected health·         social media analytics·         mobile healthcare·         medical signal processing·         human factors in healthcare·         usability studies in healthcare·         user-interface design for medical devices and healthcare software·         health service delivery·         health games·         security and privacy in healthcare·         medical recommender system·         healthcare workflow management·         disease profiling and personalized treatment·         visualization of medical data·         intelligent medical devices and sensors·         RFID solutions for healthcare·         healthcare decision analytics and support systems·         epidemiological surveillance systems and intervention modeling·         consumer and clinician health information needs, seeking, sharing, and use·         semantic Web, linked data, and ontology·         collaboration technologies for healthcare·         assistive and adaptive ubiquitous computing technologies·         statistics and quality of medical data·         healthcare delivery in developing countries·         health systems modeling and simulation·         computer-aided diagnosis
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