Despite the rapidly growing need to understand mental health challenges faced by refugee subpopulations, there is a dearth of literature exploring mental health conceptualization through the unique refugee lens. Guided by historical trauma theory, we gathered data using a two-phase explanatory sequential mixed-methods study (quantitative: n = 40; qualitative: n = 6) in a Midwestern U.S. region to understand mental health conceptualization from the Bhutanese refugee perspective by examining the cultural meaning and perception of mental health, describing experiences of mental health problems, and examining cultural protective factors and coping strategies. We argue that recognition of refugees' conceptualization of mental health and identification of cultural protective factors is paramount to healing. Findings emphasize the need to understand historical and cultural perspectives in cross-cultural contexts for the development and implementation of culturally responsive services. Our study also contributes to emerging knowledge on methodological rigor in research among understudied, hard-to-reach, small populations.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8123927 | PMC |
http://dx.doi.org/10.1007/s10597-021-00835-4 | 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.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!