Artificial Intelligence as a Training Tool in Clinical Psychology: A Comparison of Text-Based and Avatar Simulations
- URL: http://arxiv.org/abs/2601.11533v1
- Date: Fri, 21 Nov 2025 10:09:20 GMT
- Title: Artificial Intelligence as a Training Tool in Clinical Psychology: A Comparison of Text-Based and Avatar Simulations
- Authors: V. El Sawah, A. Bhardwaj, A. Pryke-Hobbes, D. Gamaleldin, C. S. Ang, A. K. Martin,
- Abstract summary: This study examined postgraduate clinical psychology students' perceptions of two AI-based simulations.<n>Twenty-four students completed two brief cognitive-behavioural role-plays.<n>Both AI tools were evaluated positively across dimensions.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Clinical psychology students frequently report feeling underprepared for the interpersonal demands of therapeutic work, highlighting the need for accessible opportunities to practise core counselling skills before seeing real clients. Advances in artificial intelligence (AI) now enable simulated interaction partners that may support early skills development. This study examined postgraduate clinical psychology students' perceptions of two AI-based simulations: a text-based chatbot (ChatGPT) and a voice-based avatar (HeyGen). Twenty-four students completed two brief cognitive-behavioural role-plays (counterbalanced), one with each tool, and provided both quantitative ratings and qualitative feedback on perceived usefulness, skill application, responsiveness and engagement, and perceived skill improvement. Both AI tools were evaluated positively across dimensions. However, the avatar was rated significantly higher than the chatbot for perceived usefulness, skill application, and perceived skill improvement, and qualitative comments highlighted the added value of voice-based interaction for conveying social and emotional cues. These findings suggest that AI-driven simulation may supplement early-stage clinical skills training, with voice-based avatars offering additional benefits. Future work should test whether such simulated interactions translate to objective improvements in real therapeutic performance.
Related papers
- CLiVR: Conversational Learning System in Virtual Reality with AI-Powered Patients [0.0]
CLiVR is a Conversational Learning system in Virtual Reality that integrates large language models, speech processing, and 3D avatars.<n>Developed in Unity and deployed on the Meta Quest 3 platform, CLiVR enables trainees to engage in natural dialogue with virtual patients.
arXiv Detail & Related papers (2025-10-21T19:19:55Z) - When Avatars Have Personality: Effects on Engagement and Communication in Immersive Medical Training [35.4537858155201]
This paper introduces a framework that integrates large language models (LLMs) into immersive VR to create medically coherent virtual patients with distinct, consistent personalities.<n>Results demonstrate that the approach is not only feasible but is also perceived by physicians as a highly rewarding and effective training enhancement.
arXiv Detail & Related papers (2025-09-17T16:13:37Z) - Explainable AI for Automated User-specific Feedback in Surgical Skill Acquisition [38.38538970682482]
We examine the effectiveness of explainable AI (XAI)-generated feedback in surgical training through a human-AI study.<n>We compare the impact of XAI-guided feedback against traditional video-based coaching on task outcomes, cognitive load, and trainees' perceptions of AI-assisted learning.
arXiv Detail & Related papers (2025-08-04T16:48:44Z) - Reframe Your Life Story: Interactive Narrative Therapist and Innovative Moment Assessment with Large Language Models [72.36715571932696]
Narrative therapy helps individuals transform problematic life stories into empowering alternatives.<n>Current approaches lack realism in specialized psychotherapy and fail to capture therapeutic progression over time.<n>Int (Interactive Narrative Therapist) simulates expert narrative therapists by planning therapeutic stages, guiding reflection levels, and generating contextually appropriate expert-like responses.
arXiv Detail & Related papers (2025-07-27T11:52:09Z) - Virtual Agent-Based Communication Skills Training to Facilitate Health Persuasion Among Peers [1.8408516054528479]
We present an approach that uses virtual agents to coach community-based volunteers in health counseling techniques.<n>We use this approach in a virtual agent-based system to increase COVID-19 vaccination.
arXiv Detail & Related papers (2024-12-16T18:34:32Z) - CBT-Bench: Evaluating Large Language Models on Assisting Cognitive Behavior Therapy [67.23830698947637]
We propose a new benchmark, CBT-BENCH, for the systematic evaluation of cognitive behavioral therapy (CBT) assistance.<n>We include three levels of tasks in CBT-BENCH: I: Basic CBT knowledge acquisition, with the task of multiple-choice questions; II: Cognitive model understanding, with the tasks of cognitive distortion classification, primary core belief classification, and fine-grained core belief classification; III: Therapeutic response generation, with the task of generating responses to patient speech in CBT therapy sessions.<n> Experimental results indicate that while LLMs perform well in reciting CBT knowledge, they fall short in complex real-world scenarios
arXiv Detail & Related papers (2024-10-17T04:52:57Z) - PsychoGAT: A Novel Psychological Measurement Paradigm through Interactive Fiction Games with LLM Agents [68.50571379012621]
Psychological measurement is essential for mental health, self-understanding, and personal development.
PsychoGAT (Psychological Game AgenTs) achieves statistically significant excellence in psychometric metrics such as reliability, convergent validity, and discriminant validity.
arXiv Detail & Related papers (2024-02-19T18:00:30Z) - Real-time Addressee Estimation: Deployment of a Deep-Learning Model on
the iCub Robot [52.277579221741746]
Addressee Estimation is a skill essential for social robots to interact smoothly with humans.
Inspired by human perceptual skills, a deep-learning model for Addressee Estimation is designed, trained, and deployed on an iCub robot.
The study presents the procedure of such implementation and the performance of the model deployed in real-time human-robot interaction.
arXiv Detail & Related papers (2023-11-09T13:01:21Z) - Estimating Presentation Competence using Multimodal Nonverbal Behavioral
Cues [7.340483819263093]
Public speaking and presentation competence plays an essential role in many areas of social interaction.
One approach that can promote efficient development of presentation competence is the automated analysis of human behavior during a speech.
In this work, we investigate the contribution of different nonverbal behavioral cues, namely, facial, body pose-based, and audio-related features, to estimate presentation competence.
arXiv Detail & Related papers (2021-05-06T13:09:41Z) - You Impress Me: Dialogue Generation via Mutual Persona Perception [62.89449096369027]
The research in cognitive science suggests that understanding is an essential signal for a high-quality chit-chat conversation.
Motivated by this, we propose P2 Bot, a transmitter-receiver based framework with the aim of explicitly modeling understanding.
arXiv Detail & Related papers (2020-04-11T12:51:07Z) - Continuous Emotion Recognition via Deep Convolutional Autoencoder and
Support Vector Regressor [70.2226417364135]
It is crucial that the machine should be able to recognize the emotional state of the user with high accuracy.
Deep neural networks have been used with great success in recognizing emotions.
We present a new model for continuous emotion recognition based on facial expression recognition.
arXiv Detail & Related papers (2020-01-31T17:47:16Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.