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.
বিস্তারিত পরিচিতি
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.
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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.
Mental Health in Tech Survey
This dataset contains survey responses from individuals in the tech industry about their mental health, including questions about treatment, workplace resources, and attitudes towards discussing mental health in the workplace. By analyzing this dataset, we can better understand how prevalent mental health issues are among those who work in the tech sector—and what kinds of resources they rely upon to find help—so that more can be done to create a healthier working environment for all.
iBVP Dataset: RGB-Thermal rPPG Dataset
The iBVP dataset is a collection of synchronized RGB and thermal infrared videos with PPG ground-truth signals acquired from an ear. It includes manual signal quality labels and dense signal-quality assessment using the SQA-PhysMD model. The dataset is designed to induce real-world variations in psycho-physiological states and head movement.