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Patients' Trust in Health Systems to Use Artificial Intelligence.患者对医疗系统使用人工智能的信任。
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2
Generative artificial intelligence writing open notes: A mixed methods assessment of the functionality of GPT 3.5 and GPT 4.0.生成式人工智能撰写开放式病历:对GPT 3.5和GPT 4.0功能的混合方法评估
Digit Health. 2024 Oct 29;10:20552076241291384. doi: 10.1177/20552076241291384. eCollection 2024 Jan-Dec.
3
"It happened to be the perfect thing": experiences of generative AI chatbots for mental health.“这碰巧是件完美的事”:生成式人工智能聊天机器人在心理健康方面的应用体验
Npj Ment Health Res. 2024 Oct 27;3(1):48. doi: 10.1038/s44184-024-00097-4.
4
Generative artificial intelligence in primary care: an online survey of UK general practitioners.初级保健中的生成式人工智能:英国全科医生的在线调查。
BMJ Health Care Inform. 2024 Sep 17;31(1):e101102. doi: 10.1136/bmjhci-2024-101102.
5
ChatGPT-4 generates orthopedic discharge documents faster than humans maintaining comparable quality: a pilot study of 6 cases.ChatGPT-4 生成骨科出院文件的速度快于人类,且保持相同质量:6 例初步研究。
Acta Orthop. 2024 Mar 21;95:152-156. doi: 10.2340/17453674.2024.40182.
6
AI can help people feel heard, but an AI label diminishes this impact.人工智能可以帮助人们感到被倾听,但人工智能的标签会削弱这种影响。
Proc Natl Acad Sci U S A. 2024 Apr 2;121(14):e2319112121. doi: 10.1073/pnas.2319112121. Epub 2024 Mar 29.
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Artificial intelligence and social intelligence: preliminary comparison study between AI models and psychologists.人工智能与社会智能:人工智能模型与心理学家之间的初步比较研究
Front Psychol. 2024 Feb 2;15:1353022. doi: 10.3389/fpsyg.2024.1353022. eCollection 2024.
8
Psychiatrists' experiences and opinions of generative artificial intelligence in mental healthcare: An online mixed methods survey.精神科医生在精神卫生保健中对生成式人工智能的体验与看法:一项在线混合方法调查。
Psychiatry Res. 2024 Mar;333:115724. doi: 10.1016/j.psychres.2024.115724. Epub 2024 Jan 11.
9
Generative Language Models and Open Notes: Exploring the Promise and Limitations.生成式语言模型与开放病历:探索其前景与局限。
JMIR Med Educ. 2024 Jan 4;10:e51183. doi: 10.2196/51183.
10
In praise of empathic AI.赞美共情 AI。
Trends Cogn Sci. 2024 Feb;28(2):89-91. doi: 10.1016/j.tics.2023.12.003. Epub 2023 Dec 29.

安慰剂、反安慰剂与机器学习:生成式人工智能如何塑造精神卫生保健中的患者认知。

Placebo, Nocebo, and Machine Learning: How Generative AI Could Shape Patient Perception in Mental Health Care.

作者信息

Blease Charlotte

机构信息

Department of Women's and Children's Health, Faculty of Medicine, Uppsala University, MTC‑huset (MTC Building), Dag Hammarskjölds väg 14B, 1 tr, Uppsala, 75237, Sweden, 46 18 471 00 00.

出版信息

JMIR Ment Health. 2025 Aug 15;12:e78663. doi: 10.2196/78663.

DOI:10.2196/78663
PMID:40815809
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12356606/
Abstract

The emergence of generative artificial intelligence (GenAI) in clinical settings-particularly in health documentation and communication-presents a largely unexplored but potentially transformative force in shaping placebo and nocebo effects. These psychosocial phenomena are especially potent in mental health care, where outcomes are closely tied to patients' expectations, perceived provider competence, and empathy. Drawing on conceptual understanding of placebo and nocebo effects and the latest research, this Viewpoint argues that GenAI may amplify these effects, both positive and negative. Through tone, assurance, and even the rapidity of responses, GenAI-generated text-either co-written with clinicians or peers, or fully automated-could influence patient perceptions in ways that mental health clinicians may not currently fully anticipate. When embedded in clinician notes or patient-facing summaries, AI language may strengthen expectancies that underlie placebo effects, or conversely, heighten nocebo effects through subtle cues, inaccuracies, or potentially via loss of human nuance. This article explores the implications of AI-mediated clinical communication particularly in mental health care, emphasizing the importance of transparency, ethical oversight, and psychosocial awareness as these technologies evolve.

摘要

生成式人工智能(GenAI)在临床环境中的出现,尤其是在医疗记录和沟通方面,在塑造安慰剂和反安慰剂效应方面呈现出一股基本上未被探索但可能具有变革性的力量。这些心理社会现象在精神卫生保健中尤为显著,因为治疗结果与患者的期望、对医疗服务提供者能力的认知以及同理心密切相关。基于对安慰剂和反安慰剂效应的概念理解以及最新研究,本观点认为GenAI可能会放大这些效应,包括积极和消极的效应。通过语气、保证甚至回复的速度,GenAI生成的文本——无论是与临床医生或同行共同撰写,还是完全自动化生成的——都可能以精神卫生临床医生目前可能尚未完全预料到的方式影响患者的认知。当人工智能语言嵌入临床医生记录或面向患者的总结中时,可能会强化构成安慰剂效应基础的期望,或者相反,通过微妙的线索、不准确之处或可能因失去人类的细微差别而加剧反安慰剂效应。本文探讨了人工智能介导的临床沟通的影响,特别是在精神卫生保健方面,强调了随着这些技术的发展,透明度、伦理监督和心理社会意识的重要性。