Clinical trial NCT06813066: Simulating Psychotherapeutic Sessions With Generative Artificial Intelligence
Official title: Simulating Psychotherapeutic Sessions With Generative Artificial Intelligence: A Proof-of-Concept Study of In Silico Psychotherapy Research
Study type: INTERVENTIONAL
Overall status: ACTIVE_NOT_RECRUITING
Phase: NA
Conditions: Mental Disorder
Keywords: In silico Psychotherapy
Artificial intelligence (AI) applications
Motivational Interviewing
Lead sponsor: University Hospital, Basel, Switzerland
Sponsor class: OTHER
Collaborators: name: Trier University
name: RWTH Aachen University
name: University of Basel
First posted: 2025-02-06
Enrollment: 520
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: NON_RANDOMIZED
Intervention model: PARALLEL
Primary purpose: OTHER

Brief summary: The study assesses the potential of using computational models, specifically large language models, to simulate psychotherapeutic sessions, aiming to improve therapy outcomes and advance therapist training through innovative technology.

Detailed description: Health research has evolved significantly, increasingly incorporating computational models that improve our understanding and effectiveness of medical interventions. This shift from traditional to computational methods represents a major advancement in medical research, offering a more sustainable and innovative approach for conceptual advances and therapeutic discovery. In silico models, based on scientific simulation, use computational algorithms to mimic real-world systems or processes. This virtual environment allows researchers to explore phenomena impractical, unethical, dangerous, expensive, or impossible to study otherwise.

Psychotherapy is widely acknowledged as a primary treatment for a variety of mental health conditions, from depression and anxiety to personality disorders, offering significant pathways to recovery and improved quality of life. Yet current methods have shown limited effectiveness, prompting a need for innovative research approaches. In silico psychotherapy research leverages computational simulations, large language models (LLMs), and generative artificial intelligence to explore and refine psychotherapeutic interventions. By simulating human-like conversations, this approach provides insights into therapy dynamics and holds promise for revolutionizing therapist training and expanding treatment techniques.

This study aims to establish a proof-of-concept for simulating psychotherapeutic sessions using LLMs, focusing specifically on motivational interviewing. It involves the simulation of 512 psychotherapy sessions using LLMs as well as 8 real-world psychotherapy transcripts. By modeling human interactions, the study seeks to enhance healthcare delivery, therapist training, and personalized psychotherapy.

Eligibility criteria: Inclusion Criteria:

* Simulation of psychotherapy sessions of conversations between an adult person presenting with a mental or behavioral health problem and a psychotherapist using large language models and 8 real-world transcripts

Exclusion Criteria:

* Simulation protocols with severe simulation errors

Primary outcomes:
measure: Simulation's Accuracy in generating Psychotherapeutic Dialogues
timeFrame: 12 months
Secondary outcomes:
measure: Number of Errors/Deviations
timeFrame: 12 months
measure: Metric of Verbal Content (Therapist)
timeFrame: 12 months
measure: Metric of Verbal Content (Patient)
timeFrame: 12 months
measure: Turn-takings
timeFrame: 12 months
measure: Improvement of Patient
timeFrame: 12 months
measure: Credibility of Patient Behavior
timeFrame: 12 months
measure: Credibility of Therapist Behavior
timeFrame: 12 months
measure: Manipulation Check
timeFrame: 12 months
measure: Manipulation Check
timeFrame: 12 months
Other outcomes:
Locations:
city: Basel
country: Switzerland
facility: University Hospital Basel
Study officials:
affiliation: University Hospital and University of Basel
name: Gunther Meinlschmidt, Prof. Dr.
role: PRINCIPAL_INVESTIGATOR
References: