Artificial intelligence conversational agents in mental health: Patients see potential, but prefer humans in the loop.

IF 3.2 3区 医学 Q2 PSYCHIATRY Frontiers in Psychiatry Pub Date : 2025-01-31 eCollection Date: 2024-01-01 DOI:10.3389/fpsyt.2024.1505024
Hyein S Lee, Colton Wright, Julia Ferranto, Jessica Buttimer, Clare E Palmer, Andrew Welchman, Kathleen M Mazor, Kimberly A Fisher, David Smelson, Laurel O'Connor, Nisha Fahey, Apurv Soni
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Abstract

Background: Digital mental health interventions, such as artificial intelligence (AI) conversational agents, hold promise for improving access to care by innovating therapy and supporting delivery. However, little research exists on patient perspectives regarding AI conversational agents, which is crucial for their successful implementation. This study aimed to fill the gap by exploring patients' perceptions and acceptability of AI conversational agents in mental healthcare.

Methods: Adults with self-reported mild to moderate anxiety were recruited from the UMass Memorial Health system. Participants engaged in semi-structured interviews to discuss their experiences, perceptions, and acceptability of AI conversational agents in mental healthcare. Anxiety levels were assessed using the Generalized Anxiety Disorder scale. Data were collected from December 2022 to February 2023, and three researchers conducted rapid qualitative analysis to identify and synthesize themes.

Results: The sample included 29 adults (ages 19-66), predominantly under age 35, non-Hispanic, White, and female. Participants reported a range of positive and negative experiences with AI conversational agents. Most held positive attitudes towards AI conversational agents, appreciating their utility and potential to increase access to care, yet some also expressed cautious optimism. About half endorsed negative opinions, citing AI's lack of empathy, technical limitations in addressing complex mental health situations, and data privacy concerns. Most participants desired some human involvement in AI-driven therapy and expressed concern about the risk of AI conversational agents being seen as replacements for therapy. A subgroup preferred AI conversational agents for administrative tasks rather than care provision.

Conclusions: AI conversational agents were perceived as useful and beneficial for increasing access to care, but concerns about AI's empathy, capabilities, safety, and human involvement in mental healthcare were prevalent. Future implementation and integration of AI conversational agents should consider patient perspectives to enhance their acceptability and effectiveness.

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心理健康领域的人工智能对话代理:患者看到了潜力,但更喜欢人类参与其中。
背景:数字精神卫生干预措施,如人工智能(AI)对话代理,有望通过创新治疗和支持提供来改善获得护理的机会。然而,关于患者对AI会话代理的看法的研究很少,这对它们的成功实施至关重要。本研究旨在通过探索患者对人工智能对话代理在精神卫生保健中的看法和可接受性来填补这一空白。方法:从马萨诸塞大学纪念医疗系统招募自述轻度至中度焦虑的成年人。参与者参与了半结构化访谈,以讨论他们在精神卫生保健中对人工智能对话代理的经验、看法和可接受性。使用广泛性焦虑障碍量表评估焦虑水平。数据收集时间为2022年12月至2023年2月,三位研究人员进行了快速定性分析,以识别和综合主题。结果:样本包括29名成年人(年龄19-66岁),主要年龄在35岁以下,非西班牙裔,白人和女性。参与者报告了使用人工智能对话代理的一系列积极和消极经历。大多数人对人工智能对话代理持积极态度,赞赏它们的效用和潜力,以增加获得护理的机会,但一些人也表达了谨慎的乐观态度。大约一半的人支持负面观点,理由是人工智能缺乏同理心,在解决复杂的心理健康状况方面存在技术限制,以及数据隐私问题。大多数参与者希望人类参与人工智能驱动的治疗,并对人工智能对话代理被视为治疗替代品的风险表示担忧。一个小组更喜欢人工智能会话代理来完成管理任务,而不是提供护理。结论:人工智能对话代理被认为是有用的,有利于增加获得护理的机会,但对人工智能的同理心、能力、安全性和人类参与精神卫生保健的担忧普遍存在。未来人工智能对话代理的实施和集成应该考虑患者的观点,以提高其可接受性和有效性。
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来源期刊
Frontiers in Psychiatry
Frontiers in Psychiatry Medicine-Psychiatry and Mental Health
CiteScore
6.20
自引率
8.50%
发文量
2813
审稿时长
14 weeks
期刊介绍: Frontiers in Psychiatry publishes rigorously peer-reviewed research across a wide spectrum of translational, basic and clinical research. Field Chief Editor Stefan Borgwardt at the University of Basel is supported by an outstanding Editorial Board of international researchers. This multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics, clinicians and the public worldwide. The journal''s mission is to use translational approaches to improve therapeutic options for mental illness and consequently to improve patient treatment outcomes.
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