Werder Karl, Cao Lan, Park Eun Hee, Ramesh Balasubramaniam
Digital Business Innovation, IT University of Copenhagen, Copenhagen, Denmark.
Information Technology & Decision Sciences, Strome College of Business, Old Dominion University, Norfolk, VA, United States.
J Med Internet Res. 2025 Jan 31;27:e51785. doi: 10.2196/51785.
Continuous monitoring of patients' health facilitated by artificial intelligence (AI) has enhanced the quality of health care, that is, the ability to access effective care. However, AI monitoring often encounters resistance to adoption by decision makers. Healthcare organizations frequently assume that the resistance stems from patients' rational evaluation of the technology's costs and benefits. Recent research challenges this assumption and suggests that the resistance to AI monitoring is influenced by the emotional experiences of patients and their surrogate decision makers. We develop a framework from an emotional perspective, provide important implications for healthcare organizations, and offer recommendations to help reduce resistance to AI monitoring.
由人工智能（AI）推动的对患者健康的持续监测提高了医疗保健的质量，即获得有效护理的能力。然而，人工智能监测在决策者采用时常常遇到阻力。医疗保健组织通常认为这种阻力源于患者对技术成本和收益的理性评估。最近的研究对这一假设提出了挑战，并表明对人工智能监测的阻力受到患者及其替代决策者的情感体验的影响。我们从情感角度构建了一个框架，为医疗保健组织提供了重要启示，并提出了有助于减少对人工智能监测阻力的建议。
