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.
The ISSP is a cross-national collaboration program conducting annual surveys on diverse topics relevant to social sciences. Established in 1984, it includes members from various cultures around the globe. Over one million respondents have participated in ISSP surveys, and all collected data and documentation are available free of charge.
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.
This repository provides code and data for automatic depression detection using a GRU/BiLSTM-based model. It includes an emotional audio-textual corpus designed to support the diagnosis of psychological distress conditions such as anxiety, depression, and post-traumatic stress disorder.