The CaiTI_dataset repository contains datasets for Motivational Interviewing and Cognitive Behavioral Therapy, curated by therapists to train CaiTI.
The CaiTI_dataset repository is a valuable resource for researchers and developers working in the field of mental health and therapeutic interventions. It provides a collection of datasets specifically curated for training CaiTI, a conversational AI system designed to assist in Motivational Interviewing and Cognitive Behavioral Therapy. These datasets are essential for developing and improving AI-driven therapeutic tools, ensuring they are effective and aligned with clinical practices.
This paper discusses Helply - a synthesized ML training dataset focused on psychology and therapy, created by Alex Scott and published by NamelessAI. The dataset developed by Alex Scott is a comprehensive collection of synthesized data designed to train LLMs in understanding psychological and therapeutic contexts. This dataset aims to simulate real-world interactions between therapists and patients, enabling ML models to learn from a wide range of scenarios and therapeutic techniques.
APA PsycInfo is the premier abstracting and indexing database covering the behavioral and social sciences. It provides over 5,000,000 peer-reviewed records, 144 million cited references, and spans 600 years of content. The database is updated twice-weekly and includes research in 30 languages from 50 countries.
The IC-AnnoMI repository contains source code and a synthetic dataset generated through in-context zero-shot LLM prompting for mental health and therapeutic counselling. IC-AnnoMI is a project that generates contextual MI dialogues using large language models (LLMs). The project contains source code and a synthetic dataset generated through zero-shot prompts, aiming to address the data scarcity and inherent bias problems in mental health and therapeutic consultation.