The WHO report on adolescent mental health describes actions undertaken by international development organizations to address adolescents’ mental health needs at the country level. It highlights the inadequacy of current efforts and the need for more coordinated and comprehensive interventions.
The report 'Adolescent mental health: mapping actions of nongovernmental organizations and other international development organizations' was produced in collaboration with UNICEF. It emphasizes the need for mainstreaming adolescent mental health in education, health, and child protection programs. The report aims to facilitate coordinated actions towards improved programming on adolescent mental health in countries.
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.
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.
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.