A glance into the future of artificial intelligence-enhanced scalable personalized training: A response to Kopelovich, Brian, et al. (2025) and Kopelovich, Slevin, et al. (2025).

IF 2.6 2区 心理学 Q2 PSYCHOLOGY, CLINICAL
Psychotherapy Pub Date : 2025-03-01 DOI:10.1037/pst0000547
Sigal Zilcha-Mano
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引用次数: 0

Abstract

The two articles by Kopelovich, Brian, et al. (2025) and Kopelovich, Slevin, et al. (2025) mark a new era in psychotherapy research and practice. The articles detail the development and validation of one of the first conversational artificial intelligence- (AI-) enhanced psychotherapy training tools, with profound implications for the future of clinical training. Following the new trail blazed by Kopelovich, Brian, et al. (2025) and Kopelovich, Slevin, et al. (2025), this commentary traces some of the most promising future directions for clinical training and research. In clinical training, trainees will be able to practice therapeutic skills and techniques with virtual clients before working with real ones. After mastering common therapeutic skills and treatment-specific techniques, they will begin treating real clients and receive detailed, immediate, and constructive AI-based feedback on their work to augment supervision sessions. Posttraining, clinicians can maintain and enhance their clinical expertise, acquire new skills, and incorporate the latest evidence-based knowledge into their practice through AI-based solutions. In research, it will be possible to explore the most effective techniques to be used by trainees and therapists at certain moments in a therapeutic session with individual patients, enabling the development of more precise and personalized therapeutic interventions. It will also be possible to explore the most effective trainee-specific supervision approaches to enhance a transformative experience and serve as a catalyst for the trainee's professional identity development within the supervisor-supervisee relationship, augmented by a systematic mapping of the trainee's strengths and areas for improvement. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

展望人工智能增强的可扩展个性化培训的未来:对Kopelovich, Brian等人(2025)和Kopelovich, Slevin等人(2025)的回应。
Kopelovich, Brian等人(2025)和Kopelovich, Slevin等人(2025)的两篇文章标志着心理治疗研究和实践的新时代。文章详细介绍了第一个会话人工智能(AI)增强心理治疗培训工具之一的开发和验证,对临床培训的未来具有深远的影响。在Kopelovich, Brian等人(2025)和Kopelovich, Slevin等人(2025)开辟的新道路之后,本评论追溯了临床培训和研究的一些最有希望的未来方向。在临床培训中,学员将能够在与真实客户合作之前与虚拟客户一起练习治疗技巧和技术。在掌握了常见的治疗技巧和特定的治疗技术后,他们将开始治疗真正的客户,并获得详细、即时和建设性的基于人工智能的工作反馈,以增加监督会议。培训后,临床医生可以通过基于人工智能的解决方案保持和提高他们的临床专业知识,获得新的技能,并将最新的循证知识纳入他们的实践。在研究中,将有可能探索最有效的技术,供受训者和治疗师在治疗个体患者的特定时刻使用,从而开发出更精确和个性化的治疗干预措施。还可以探索最有效的针对受训人员的监督方法,以加强变革经验,并在主管-被主管关系中促进受训人员的职业认同发展,并通过系统地绘制受训人员的优势和有待改进的领域加以加强。(PsycInfo Database Record (c) 2025 APA,版权所有)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Psychotherapy
Psychotherapy PSYCHOLOGY, CLINICAL-
CiteScore
4.60
自引率
12.00%
发文量
93
期刊介绍: Psychotherapy Theory, Research, Practice, Training publishes a wide variety of articles relevant to the field of psychotherapy. The journal strives to foster interactions among individuals involved with training, practice theory, and research since all areas are essential to psychotherapy. This journal is an invaluable resource for practicing clinical and counseling psychologists, social workers, and mental health professionals.
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