Mental disorders impose an enormous burden on society. In developing countries like India, there is a lack of adequate number of trained mental health professionals to provide specialized care and 75-85 % of affected individuals do not have access to appropriate mental health services. The National Mental Health Programme (NMHP) is being implemented by the Government of India to support state governments in providing mental health services in the country. The Urban Mental Health Programme (UMHP) is a pilot initiative that has attempted the integration of mental health services in primary health care settings in two municipal wards in Kolkata, West Bengal, India. The overarching aim of this paper is to describe the methodology used for the evaluation of the community based mental health programme and to understand the processes of the programme in terms of barriers and facilitators. The current evaluation is based on a concurrent nested design, where qualitative and quantitative data are both collected at the same time but analysed separately and priority was given to qualitative data. This experience will contribute in helping other researchers to make some evaluations more effective, useful and manageable. Ethics approval was obtained from an institutional ethics committee of an organization (Ekjut) based in Ranchi, Jharkhand, India. The evaluation was undertaken by the George Institute for Global Health, New Delhi from February- June 2016.
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http://dx.doi.org/10.1016/j.evalprogplan.2021.101931 | DOI Listing |
Brain
January 2025
Translational Neuroimaging Laboratory, Montreal Neurological Institute, H3A 2B4, Montreal, Canada.
Plasma phosphorylated tau biomarkers open unprecedented opportunities for identifying carriers of Alzheimer's disease pathophysiology in early disease stages using minimally invasive techniques. Plasma p-tau biomarkers are believed to reflect tau phosphorylation and secretion. However, it remains unclear to what extent the magnitude of plasma p-tau abnormalities reflects neuronal network disturbance in the form of cognitive impairment.
View Article and Find Full Text PDFJMIR Res Protoc
January 2025
Data and Web Science Group, School of Business Informatics and Mathematics, University of Manneim, Mannheim, Germany.
Background: The rapid evolution of large language models (LLMs), such as Bidirectional Encoder Representations from Transformers (BERT; Google) and GPT (OpenAI), has introduced significant advancements in natural language processing. These models are increasingly integrated into various applications, including mental health support. However, the credibility of LLMs in providing reliable and explainable mental health information and support remains underexplored.
View Article and Find Full Text PDFJMIR Ment Health
January 2025
Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States.
Background: Mental health concerns have become increasingly prevalent; however, care remains inaccessible to many. While digital mental health interventions offer a promising solution, self-help and even coached apps have not fully addressed the challenge. There is now a growing interest in hybrid, or blended, care approaches that use apps as tools to augment, rather than to entirely guide, care.
View Article and Find Full Text PDFJMIR Form Res
January 2025
School of Psychology, Ulster University, Coleraine, United Kingdom.
Background: Psychologists have developed frameworks to understand many constructs, which have subsequently informed the design of digital mental health interventions (DMHIs) aimed at improving mental health outcomes. The science of happiness is one such domain that holds significant applied importance due to its links to well-being and evidence that happiness can be cultivated through interventions. However, as with many constructs, the unique ways in which individuals experience happiness present major challenges for designing personalized DMHIs.
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