Exploring the influence of privacy concerns, AI literacy, and perceived health stigma on AI chatbot use in healthcare: An uncertainty reduction approach

IF 3.1 2区医学 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Patient Education and Counseling Pub Date : 2025-07-22 DOI:10.1016/j.pec.2025.109271

Zikun Liu , Wenxue Zou , Cong Lin

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引用次数: 0

Abstract

Objective

Guided by Uncertainty Reduction Theory, this study aims to explore the influence of AI privacy concerns, AI literacy, and perceived health stigma on the preference for AI chatbots in Chinese healthcare contexts.

Method

We analyzed survey data from 1487 participants, employing frequency analyses to generate descriptive statistics and regression modeling to examine the relationships among key variables.

Results

The findings indicate that AI chatbots are most highly valued for their roles in health information dissemination and lifestyle guidance. Privacy concerns negatively affect perceptions of AI as a substitute for doctors, particularly regarding sensitive health issues. However, AI literacy mitigates these concerns across all functional domains. Additionally, perceived health stigma enhances the acceptance of AI chatbots as substitutes for doctors in sensitive areas and intensifies the adverse impact of privacy concerns on AI’s role in health information, decision-making, and lifestyle guidance.

Conclusion

The current study yields valuable insights into the role of AI chatbots in healthcare contexts, particularly in shaping users’ intentions to disclose personal information. It also advances the theoretical scope of Uncertainty Reduction Theory by extending its application to human-AI interactions.

Practical Implications

The findings underscore the need for healthcare providers, policymakers, and AI developers to prioritize privacy safeguards, promote AI literacy, and actively combat stigma. Such efforts are essential to fostering trust and encouraging meaningful patient engagement with AI-driven tools, especially in addressing sensitive health concerns.

查看原文本刊更多论文

探讨隐私问题、人工智能素养和感知到的健康耻辱感对人工智能聊天机器人在医疗保健中的使用的影响：一种减少不确定性的方法

在不确定性减少理论的指导下，本研究旨在探讨人工智能隐私问题、人工智能素养和感知健康污名对中国医疗保健背景下人工智能聊天机器人偏好的影响。方法对1487名参与者的调查数据进行分析，采用频率分析产生描述性统计，并采用回归模型检验关键变量之间的关系。结果研究结果表明，人工智能聊天机器人在健康信息传播和生活方式指导方面的作用最受重视。隐私问题对人工智能替代医生的看法产生了负面影响，尤其是在敏感的健康问题上。然而，人工智能素养减轻了所有功能领域的这些担忧。此外，人们对健康的耻辱感增强了人工智能聊天机器人在敏感领域替代医生的接受度，并加剧了隐私问题对人工智能在健康信息、决策和生活方式指导方面的作用的不利影响。目前的研究对人工智能聊天机器人在医疗保健环境中的作用，特别是在塑造用户披露个人信息的意图方面，提供了有价值的见解。它还通过将不确定性减少理论的应用扩展到人与人工智能的交互，从而扩大了不确定性减少理论的理论范围。研究结果强调了医疗服务提供者、政策制定者和人工智能开发人员需要优先考虑隐私保护，促进人工智能素养，并积极打击污名化。这些努力对于促进信任和鼓励患者有意义地使用人工智能驱动的工具至关重要，特别是在解决敏感的健康问题方面。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Patient Education and Counseling 医学-公共卫生、环境卫生与职业卫生

CiteScore

5.60

自引率

11.40%

发文量

384

审稿时长

46 days

期刊介绍： Patient Education and Counseling is an interdisciplinary, international journal for patient education and health promotion researchers, managers and clinicians. The journal seeks to explore and elucidate the educational, counseling and communication models in health care. Its aim is to provide a forum for fundamental as well as applied research, and to promote the study of organizational issues involved with the delivery of patient education, counseling, health promotion services and training models in improving communication between providers and patients.