Assessing the impact of AI on physician decision-making for mental health treatment in primary care.

Katie Ryan, Hyun-Joon Yang, Bohye Kim, Jane Paik Kim
{"title":"Assessing the impact of AI on physician decision-making for mental health treatment in primary care.","authors":"Katie Ryan, Hyun-Joon Yang, Bohye Kim, Jane Paik Kim","doi":"10.1038/s44184-025-00124-y","DOIUrl":null,"url":null,"abstract":"<p><p>AI models may soon be poised to recommend mental health treatments or referrals in primary care, yet little is known regarding their impact on physician decision-making. In this web-based study, primary care physicians (n = 420) were presented with a clinical scenario describing a patient with psychiatric symptoms, an AI tool for referring or prescribing, and the recommendation of the AI. A sequentially randomized vignette method was used to test the impact of initial assessments and AI output on physician decision-making patterns. Physicians were significantly more likely to change their decisions when the AI recommendation was misaligned with their initial assessment, especially when AI recommended treatment. There was no difference between the change-in-decision rate of physicians who received an AI recommendation to not treat, indicating that the direction of AI recommendations may influence physician decision-making, and raising important considerations for how physician decisions may be anticipated in the context of AI.</p>","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":"4 1","pages":"16"},"PeriodicalIF":0.0000,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12065820/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Npj mental health research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1038/s44184-025-00124-y","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

AI models may soon be poised to recommend mental health treatments or referrals in primary care, yet little is known regarding their impact on physician decision-making. In this web-based study, primary care physicians (n = 420) were presented with a clinical scenario describing a patient with psychiatric symptoms, an AI tool for referring or prescribing, and the recommendation of the AI. A sequentially randomized vignette method was used to test the impact of initial assessments and AI output on physician decision-making patterns. Physicians were significantly more likely to change their decisions when the AI recommendation was misaligned with their initial assessment, especially when AI recommended treatment. There was no difference between the change-in-decision rate of physicians who received an AI recommendation to not treat, indicating that the direction of AI recommendations may influence physician decision-making, and raising important considerations for how physician decisions may be anticipated in the context of AI.

评估人工智能对初级保健中心理健康治疗医生决策的影响。
人工智能模型可能很快就会在初级保健中推荐心理健康治疗或转诊,但它们对医生决策的影响尚不清楚。在这项基于网络的研究中,向初级保健医生(n = 420)提供了一个临床场景,描述了一个有精神症状的患者,一个用于转诊或开处方的人工智能工具,以及人工智能的建议。采用顺序随机小片段法来测试初始评估和人工智能输出对医生决策模式的影响。当人工智能的建议与他们最初的评估不一致时,医生更有可能改变他们的决定,尤其是当人工智能推荐治疗时。收到人工智能建议不治疗的医生的决策变化率之间没有差异,这表明人工智能建议的方向可能会影响医生的决策,并提出了在人工智能背景下如何预测医生决策的重要考虑因素。
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
自引率
0.00%
发文量
0
×
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:481959085
Book学术官方微信