公众能接受AI健康新闻吗?基于信任中介与负向预期违背调节的实验证据&#x0002A;

那宇翔; 刘映萱; 赖凯声

doi:10.16719/j.cnki.1671-6981.20250417

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心理科学 ›› 2025, Vol. 48 ›› Issue (4) : 972-984. DOI: 10.16719/j.cnki.1671-6981.20250417

计算建模与人工智能

公众能接受AI健康新闻吗?基于信任中介与负向预期违背调节的实验证据^*

那宇翔, 刘映萱, 赖凯声^**

作者信息 +

Can the Public Accept AI-Generated Health News?Experimental Evidence from Trust Mediation and Negative Expectancy Violation Moderation

Na Yuxiang, Liu Yingxuan, Lai Kaisheng

Author information +

文章历史 +

摘要

AI健康新闻在促进传递健康知识、提升医疗服务等健康传播领域存在巨大潜力,但目前缺乏直接探究公众接受AI健康新闻及其心理机制的实证证据。通过两项被试间实验检验了公众对AI健康新闻的信任与接受以及负向预期违背这一心理因素的调节作用。结果发现,相比人工新闻,公众对AI健康新闻的信息接受意愿更低,并且对AI健康新闻的感知信任中介了新闻代理类型（AI vs. 人类）影响信息接受意愿的作用。此外,负向预期违背调节了新闻代理类型与感知信任之间的关系,即公众的负向预期违背越高,对AI健康新闻与人工健康新闻的感知信任差距越大。

Abstract

The potential of artificial intelligence (AI) in health journalism is becoming increasingly recognized, offering promising opportunities to enhance information dissemination. By automating routine news production, AI enables journalists to allocate more time and resources to strategic health initiatives, policy development, and in-depth investigative reporting. However, the public’s trust in and acceptance of AI-generated health information remain underexplored. Prior research suggests that individuals may actively reject or avoid AI-provided information, known as “AI information avoidance”. This poses a significant challenge to the effectiveness of AI-driven health news. If the public distrusts or resists health information disseminated by AI systems, the potential benefits of AI in health communication could be severely undermined.
In this context, it is critical to examine the underlying psychological processes that influence the public’s engagement with AI health news. The expectation violation theory is a valuable framework for understanding these dynamics because it illuminates how deviations from psychological expectations can affect trust and acceptance. This study aims to explore the psychological mechanisms underlying the public’s perception of AI news in the context of expectation violation. By clarifying these relationships, we hope to strengthen the role of AI as a transformative tool for realizing the ideal vision of health journalism. Specifically, this study explores the effects of news agents (AI vs. human) on the public’s willingness to accept information and the moderating role of negative expectation violation through two between-subject experiments and a moderating mediator model based on expectation violation theory.
The results of experiment 1 showed a significant difference in subjects’ willingness to accept health news information written by AI agent and human agent (t = - 6.75, p < .001, Cohen’ s d = 1.49). Thus, Hypothesis 1 was supported. Perceived trust mediated the relationship between news agent and willingness to accept information. Type of news agent had a significant effect on perceived trust (β = - 1.28, t = - 7.41, p < .001), whereas perceived trust had a significant effect on willingness to accept information (β = .94, t = 23.27, p < .001). Results of the mediation analysis showed a nonsignificant direct effect and a significant indirect effect (β = - 1.20, 95% CI = [-1.54, -.88]). The mediation effect was a full mediation effect. Therefore, Hypothesis 2 was supported. Furthermore, negative expectation violation moderated the relationship between news agent type and perceived trust (β = -.22, t = - 2.34, p = .02), and the public’s negative expectation violation exacerbated the detrimental effect of AI authors as agents on their perceived trust. Hypothesis 3 was supported. Experiment 2 further validated the interaction effect between news agent type and negative expectation violation on perceived trust by manipulating the degree of negative expectation violation of the subjects in a more rigorous experimental design. The results showed that the results of experiment 1 were validated.
Our study reveals a significant public’s preference for health news authored by human agents over AI agents, underscoring the critical role of news agent in shaping information acceptance. Importantly, perceived trust emerges as a central mediating mechanism explaining this disparity in the public’s reception. Furthermore, our findings highlight the moderating role of negative expectation violation in the relationship between news agents (human vs. AI) and perceived trust. Negative expectation violation can further exacerbate the negative impact of AI news agent on perceived trust. These results emphasize the importance of strategically managing public’s expectations in the deployment of AI-driven health news.
At the theoretical level, this study expanded the scope of genre types in AI news research, focusing specifically on the public’s trust in and willingness to accept information in AI health news. Meanwhile, by revealing the moderating role of negative expectation violation in the relationship between news agent type and public perceived trust, this study provided an explanatory reference for the inconsistent findings that existed in previous studies on AI news trust. On the practical level, this study revealed the existence of negative expectation violation when the public is exposed to AI health news and confirmed the impact of negative feedback due to failed expectations on the public’s willingness to accept health information.

导出引用

那宇翔, 刘映萱, 赖凯声. 公众能接受AI健康新闻吗?基于信任中介与负向预期违背调节的实验证据^*[J]. 心理科学. 2025, 48(4): 972-984 https://doi.org/10.16719/j.cnki.1671-6981.20250417

Na Yuxiang, Liu Yingxuan, Lai Kaisheng. Can the Public Accept AI-Generated Health News?Experimental Evidence from Trust Mediation and Negative Expectancy Violation Moderation[J]. Journal of Psychological Science. 2025, 48(4): 972-984 https://doi.org/10.16719/j.cnki.1671-6981.20250417

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