Li Wenyu, Liu Xueen
School of Marxism, Capital Normal University, Beijing, China.
Beijing Hepingli Hospital, Beijing, China.
Patient Educ Couns. 2025 Apr;133:108619. doi: 10.1016/j.pec.2024.108619. Epub 2024 Dec 22.
OBJECTIVE: This paper investigates the anxiety surrounding the integration of artificial intelligence (AI) in doctor-patient interactions, analyzing the perspectives of both patients and healthcare providers to identify key concerns and potential solutions. METHODS: The study employs a comprehensive literature review, examining existing research on AI in healthcare, and synthesizes findings from various surveys and studies that explore the attitudes of patients and doctors towards AI applications in medical settings. RESULTS: The analysis reveals that patient anxiety encompasses algorithm aversion, robophobia, lack of humanistic care, challenges in human-machine interaction, and concerns about AI's universal applicability. Doctors' anxieties stem from fears of replacement, legal liabilities, emotional impacts of work environment changes, and technological apprehension. The paper highlights the need for patient participation, humanistic care, improved interaction methods, educational training, and policy guidelines to foster public understanding and trust in AI. CONCLUSION: The paper concludes that addressing AI anxiety in doctor-patient relationships is crucial for successfully integrating AI in healthcare. It emphasizes the importance of respecting patient autonomy, addressing the lack of humanistic care, and improving patient-AI interaction to enhance the patient experience and reduce medical errors. PRACTICE IMPLICATIONS: The study suggests that future research should focus on understanding the needs and concerns of patients and doctors, strengthening medical humanities education, and establishing policies to guide the ethical use of AI in medicine. It also recommends public education to enhance understanding and trust in AI to improve medical services and ensure professional development and stable work environment for doctors.
目的:本文探讨了医患互动中围绕人工智能(AI)整合的焦虑情绪,分析了患者和医疗服务提供者的观点,以确定关键问题和潜在解决方案。 方法:该研究采用全面的文献综述,审视医疗保健领域中有关人工智能的现有研究,并综合各种调查和研究的结果,这些调查和研究探讨了患者和医生对医疗环境中人工智能应用的态度。 结果:分析表明,患者的焦虑包括算法厌恶、机器恐惧症、缺乏人文关怀、人机交互挑战以及对人工智能普遍适用性的担忧。医生的焦虑源于对被取代的恐惧、法律责任、工作环境变化的情感影响以及技术恐惧。本文强调需要患者参与、人文关怀、改进交互方式、教育培训以及政策指导方针,以促进公众对人工智能的理解和信任。 结论:本文得出结论,解决医患关系中的人工智能焦虑对于在医疗保健领域成功整合人工智能至关重要。它强调尊重患者自主权、解决人文关怀缺失问题以及改善患者与人工智能交互的重要性,以提升患者体验并减少医疗错误。 实践意义:该研究表明,未来的研究应侧重于了解患者和医生的需求与担忧,加强医学人文教育,并制定政策以指导人工智能在医学中的伦理使用。它还建议进行公众教育,以增强对人工智能的理解和信任,改善医疗服务,并确保医生的专业发展和稳定的工作环境。
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