听从人工智能还是人类医生的医疗建议?基于临床医生与患者沟通途径模型的实验证据。

IF 3 3区 医学 Q1 COMMUNICATION Health Communication Pub Date : 2024-11-04 DOI:10.1080/10410236.2024.2423114
Shuoshuo Li, Meng Chen, Piper Liping Liu, Jian Xu
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引用次数: 0

摘要

在政府、医疗机构和人工智能(AI)研究人员的合作下,医疗大语言模型正在向公众推出。然而,一个关键问题依然存在:患者会听从人工智能医生提供的医疗建议吗?由于缺乏用户研究,很难给出明确的答案。基于临床医生与患者沟通路径模型,本研究进行了一项因子实验,采用 2(医疗提供者,人工智能与人类)×2(信息支持,低与高) ×2(响应延迟,慢与快) 的主体间设计(n = 535)。结果显示,参与者对人工智能医生建议的依从性明显低于对人类医生建议的依从性。此外,交互效应表明,在慢反应潜伏期条件下,受试者从人类医生那里感知到更多的健康益处和以病人为中心的态度,而对人工智能医生则相反。
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Following Medical Advice of an AI or a Human Doctor? Experimental Evidence Based on Clinician-Patient Communication Pathway Model.

Medical large language models are being introduced to the public in collaboration with governments, medical institutions, and artificial intelligence (AI) researchers. However, a crucial question remains: Will patients follow the medical advice provided by AI doctors? The lack of user research makes it difficult to provide definitive answers. Based on the clinician-patient communication pathway model, this study conducted a factorial experiment with a 2 (medical provider, AI vs. human) × 2 (information support, low vs. high) × 2 (response latency, slow vs. fast) between-subjects design (n = 535). The results showed that participants exhibited significantly lower adherence to AI doctors' advice than to human doctors. In addition, the interaction effect suggested that, under the slow-response latency condition, subjects perceived greater health benefits and patient-centeredness from human doctors, while the opposite was observed for AI doctors.

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来源期刊
CiteScore
8.20
自引率
10.30%
发文量
184
期刊介绍: As an outlet for scholarly intercourse between medical and social sciences, this noteworthy journal seeks to improve practical communication between caregivers and patients and between institutions and the public. Outstanding editorial board members and contributors from both medical and social science arenas collaborate to meet the challenges inherent in this goal. Although most inclusions are data-based, the journal also publishes pedagogical, methodological, theoretical, and applied articles using both quantitative or qualitative methods.
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