Department of Business Analytics and Data Science, Florida Polytechnic University, Lakeland, FL, United States.
School of Systems and Enterprises, Stevens Institue of Technology, Hoboken, NJ, United States.
JMIR Hum Factors. 2023 Nov 6;10:e49788. doi: 10.2196/49788.
Artificial intelligence (AI)-based home care systems and devices are being gradually integrated into health care delivery to benefit patients with chronic diseases. However, existing research mainly focuses on the technical and clinical aspects of AI application, with an insufficient investigation of patients' motivation and intention to adopt such systems.
This study aimed to examine the factors that affect the motivation of patients with chronic diseases to adopt AI-based home care systems and provide empirical evidence for the proposed research hypotheses.
We conducted a cross-sectional web-based survey with 222 patients with chronic diseases based on a hypothetical scenario.
The results indicated that patients have an overall positive perception of AI-based home care systems. Their attitudes toward the technology, perceived usefulness, and comfortability were found to be significant factors encouraging adoption, with a clear understanding of accountability being a particularly influential factor in shaping patients' attitudes toward their motivation to use these systems. However, privacy concerns persist as an indirect factor, affecting the perceived usefulness and comfortability, hence influencing patients' attitudes.
This study is one of the first to examine the motivation of patients with chronic diseases to adopt AI-based home care systems, offering practical insights for policy makers, care or technology providers, and patients. This understanding can facilitate effective policy formulation, product design, and informed patient decision-making, potentially improving the overall health status of patients with chronic diseases.
基于人工智能（AI）的家庭护理系统和设备正逐渐融入医疗服务中，以造福慢性病患者。然而，现有研究主要集中在 AI 应用的技术和临床方面，对患者采用此类系统的动机和意愿的研究不足。
本研究旨在探讨影响慢性病患者采用基于 AI 的家庭护理系统的动机的因素，并为提出的研究假设提供经验证据。
我们基于假设情景，对 222 名慢性病患者进行了横断面网络调查。
结果表明，患者对基于 AI 的家庭护理系统总体持积极态度。他们对技术的态度、感知有用性和舒适度被发现是鼓励采用的重要因素，对问责制的清晰理解是影响患者对使用这些系统的动机的态度的一个特别有影响力的因素。然而，隐私问题仍然是一个间接因素，影响感知有用性和舒适度，从而影响患者的态度。
本研究首次探讨了慢性病患者采用基于 AI 的家庭护理系统的动机，为政策制定者、护理或技术提供者和患者提供了实用的见解。这种理解可以促进有效的政策制定、产品设计和知情患者决策，从而有可能改善慢性病患者的整体健康状况。
