American National Mental Health Services Survey
The American National Mental Health Services Survey (N-MHSS) is an annual survey conducted by the Substance Abuse and Mental Health Services Administration (SAMHSA) to collect data on mental health treatment facilities across the United States. The survey provides detailed information on the services and characteristics of these facilities, helping to inform policy and improve mental health care.
Detalyadong Panimula
The N-MHSS is a valuable resource for researchers, policymakers, and mental health professionals. It includes data on psychiatric hospitals, nonfederal general hospitals with separate psychiatric units, residential treatment centers, community mental health centers, and more. The survey aims to provide a comprehensive picture of the mental health treatment landscape in the United States.
Higit paDataset
Tobii Pro Lab: Eye Tracking Software for Behavior Research
Tobii Pro Lab is a comprehensive eye tracking software designed for behavioral research, offering a complete solution for researchers to conduct experiments from test design to data analysis.
Hugging Face Dataset - NamelessAI Helply
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.
IC-AnnoMI: In-Context MI Dialogues - GitHub Repository
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.