The National Study of Mental Health and Wellbeing provides key statistics on mental health issues in Australia, including the prevalence of mental disorders, consultations with health professionals, and the use of mental health-related medications. The study covers a wide range of mental health conditions and offers insights into the impact of mental health on individuals and society.
The National Study of Mental Health and Wellbeing is a comprehensive survey conducted by the Australian Bureau of Statistics (ABS) to understand the mental health status of the Australian population. Key findings include the prevalence of mental disorders, the most common types of disorders, and the use of mental health services. The study also provides data on the co-occurrence of mental and physical health conditions, consultations with health professionals, and the use of digital technologies for mental health support. This data is crucial for policymakers, researchers, and healthcare providers to develop and implement effective mental health strategies.
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 dataset contains 20,000 labelled English tweets of depressed and non-depressed users. The data is collected using the Twitter API and includes feature extraction techniques such as topic modelling and emoji sentiment analysis. It is designed for mental health classification at the tweet level.
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.