Venkat Bhat

Efficacy and Safety of Psychedelic Microdosing on Psychological Outcomes in Healthy Adults: A Systematic Review and Meta-analysis

Multiagent Large Language Model Framework for Psychotherapy Fidelity Assessment in Motivational Interviewing and Cognitive Behavioral Therapy Training: Cross-Sectional, Simulation-Based Evaluation Study

This proof-of-concept study suggests that a rubric-guided multiagent LLM framework can score stylized synthetic MI and CBT transcripts along expected prompt-defined competence gradients and align with preliminary external and human-rater benchmarks.

The AWARE (AI Use, Why, Attachment, Reality and Risk, and Effect on Functioning) Framework for Assessing Patients’ Use of AI in Mental Health Care

The AWARE framework offers a structured educational starting point for integrating assessment of patient-AI interactions into routine psychiatric interviewing while supporting patient-centered, evidence-informed clinical practice and health professions education.

Zero-Shot Large Language Models for Preliminary Prediction of PTSD Symptoms From Clinical Interview Transcripts: Grands modèles de langage sans exemple pour la prédiction préliminaire des symptômes de TSPT à partir de transcriptions d'entrevues cliniques.

BackgroundPosttraumatic stress disorder (PTSD) is common yet frequently underdiagnosed, in part due to barriers to systematic screening and the reliance on self-report instruments. Large language models (LLMs) have shown promise in extracting clinically relevant information from unstructured language, but their ability...