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

IF 5.8 2区 医学 Q1 PSYCHIATRY
Jmir Mental Health Pub Date : 2025-08-15 DOI:10.2196/78663
Charlotte Blease
{"title":"Placebo, Nocebo, and Machine Learning: How Generative AI Could Shape Patient Perception in Mental Health Care.","authors":"Charlotte Blease","doi":"10.2196/78663","DOIUrl":null,"url":null,"abstract":"<p><strong>Unlabelled: </strong>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.</p>","PeriodicalId":48616,"journal":{"name":"Jmir Mental Health","volume":"12 ","pages":"e78663"},"PeriodicalIF":5.8000,"publicationDate":"2025-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12356606/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jmir Mental Health","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2196/78663","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHIATRY","Score":null,"Total":0}
引用次数: 0

Abstract

Unlabelled: 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.

安慰剂、反安慰剂和机器学习:生成式人工智能如何在精神卫生保健中塑造患者的感知。
未标记:生殖人工智能(GenAI)在临床环境中的出现——特别是在健康记录和交流方面——在塑造安慰剂和反安慰剂效应方面呈现出一种很大程度上未被探索但潜在的变革力量。这些社会心理现象在精神卫生保健中尤其有效,其结果与患者的期望、感知到的提供者能力和同理心密切相关。根据对安慰剂和反安慰剂效应的概念理解和最新研究,本观点认为GenAI可能会放大这些效应,无论是积极的还是消极的。通过语气、保证,甚至反应的速度,genai生成的文本——无论是与临床医生或同行共同编写的,还是完全自动化的——都可能以心理健康临床医生目前可能无法完全预料到的方式影响患者的看法。当嵌入到临床医生笔记或面向患者的总结中时,人工智能语言可能会加强安慰剂效应背后的预期,或者相反,通过微妙的提示、不准确或潜在地通过失去人类细微差别来增强反安慰剂效应。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、伦理监督和社会心理意识的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Jmir Mental Health
Jmir Mental Health Medicine-Psychiatry and Mental Health
CiteScore
10.80
自引率
3.80%
发文量
104
审稿时长
16 weeks
期刊介绍: JMIR Mental Health (JMH, ISSN 2368-7959) is a PubMed-indexed, peer-reviewed sister journal of JMIR, the leading eHealth journal (Impact Factor 2016: 5.175). JMIR Mental Health focusses on digital health and Internet interventions, technologies and electronic innovations (software and hardware) for mental health, addictions, online counselling and behaviour change. This includes formative evaluation and system descriptions, theoretical papers, review papers, viewpoint/vision papers, and rigorous evaluations.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信