Why do Family Members Reject AI in Health Care? Competing Effects of Emotions

• 成果类型: Article
• 署名作者: Park, Eun Hee; Werder, Karl; Cao, Lan; Ramesh, Balasubramaniam
• 署名单位: Old Dominion University; University of Cologne; University System of Georgia; Georgia State University
• 刊物名称: JOURNAL OF MANAGEMENT INFORMATION SYSTEMS
• ISSN/ISSBN: 0742-1222
• DOI: 10.1080/07421222.2022.2096550
• 发表日期: 2022
• 页码: 765-792
• 关键词: information-technology; decision-making; ANXIETY; resistance; RISK; adoption; people; INNOVATION; QUALITY; perceptions

摘要

Artificial intelligence (AI) enables continuous monitoring of patients' health, thus improving the quality of their health care. However, prior studies suggest that individuals resist such innovative technology. In contrast to prior studies that investigate individuals' decisions for themselves, we focus on family members' rejection of AI monitoring, as family members play a significant role in health care decisions. Our research investigates competing effects of emotions toward the rejection of AI monitoring for health care. Based on two scenario-based experiments, our study reveals that emotions play a decisive role in family members' decision making on behalf of their parents. We find that anxiety about health care monitoring and anxiety about health outcomes reduce the rejection of AI monitoring, whereas surveillance anxiety and delegation anxiety increase rejection. We also find that for individual-level risks, perceived controllability moderates the relationship between surveillance anxiety and the rejection of AI monitoring. We contribute to the theory of Information System rejection by identifying the competing roles of emotions in AI monitoring decision making. We extend the literature on decision making for others by suggesting the influential role of anxiety. We also contribute to healthcare research in Information System by identifying the important role of controllability, a design factor, in AI monitoring rejection.