ArticlePsychotherapy (Chicago, Ill.)2025
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).
Article in Psychotherapy (Chicago, Ill.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Cerina-Cognitive Behavioral Therapy-Based Mobile App for Managing Generalized Anxiety Disorder Symptoms Among University Students: Results From a Pilot Feasibility Randomized Controlled Trial.JMIR mHealth and uHealth · 2025Trial
- From Theory to Therapy: The Evolution and Future of Cognitive-Behavioral Therapy for Psychosis in U.S. Mental Health Care.Focus (American Psychiatric Publishing) · 2025Article
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1 author.
Funding
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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).
Indexed as
Identifiers
40095966What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.