SAMHDA: Substance Abuse and Mental Health Data Archive
The Substance Abuse and Mental Health Data Archive (SAMHDA) provides a comprehensive collection of data sets related to mental health and substance use. It includes ongoing studies, population surveys, treatment facility surveys, and client-level data, offering valuable insights for researchers and policymakers.
مقدمة مفصلة
SAMHDA is a valuable resource for researchers and professionals interested in mental health and substance use data. It provides a wide range of data sets, including the National Mental Health Services Survey (N-MHSS), Mental Health Client-Level Data (MH-CLD), and the National Survey on Drug Use and Health (NSDUH). These data sets cover various aspects of mental health and substance use, from treatment facilities to individual-level data, and are essential for understanding and addressing related issues.
المزيدمجموعة البيانات
Emotional First Aid Dataset: Psychological Counseling QA Corpus
The Emotional First Aid Dataset is a comprehensive Chinese psychological counseling QA corpus, featuring 20,000 multi-turn dialogues. It is designed to support the development of AI applications in the field of psychological counseling and is available for research purposes.
Cam-CAN Data Access Portal | Cambridge Centre for Ageing and Neuroscience (Cam-CAN) | University of Cambridge
The Cambridge Centre for Ageing and Neuroscience (Cam-CAN) uses epidemiological, behavioral, and neuroimaging data to understand how individuals can best retain cognitive abilities into old age. The Cam-CAN Data Access Portal provides access to datasets from the Cambridge Centre for Ageing and Neuroscience, including neuroimaging and cognitive data from participants aged 18-90.
Chinese Psychological QA DataSet - GitHub Repository
The Chinese Psychological QA DataSet is a collection of 102,845 community Q&A pairs related to psychological topics., providing a rich source of data for research and development in psychological counseling and AI applications. Each entry includes detailed question and answer information, making it a valuable resource for understanding user queries and generating appropriate responses.