Late-life depression has attracted considerable attention in the social work literature. This study examined levels of knowledge and self-efficacy (confidence) in evaluation of depression in late life among a random sample of social workers (N = 168) from the National Association of Social Workers. Relationships among knowledge on aging, job-related variables, and predictors of knowledge of geriatric depression were examined. Participants ranked depression as one of the most frequent clinical problems seen in practice, scored at the lower end on knowledge about aging, and experienced great difficulty on the items pertaining to suicide in the older adults.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1080/01634372.2010.494196 | DOI Listing |
HIV Res Clin Pract
December 2025
Division of Infectious Diseases and Global Public Health, School of Medicine, University of California San Diego (UCSD), La Jolla, CA, USA.
Background: HIV remains a major challenge in KwaZulu-Natal, South Africa, particularly for young women who face disproportionate risks and barriers to prevention and treatment. Most HIV cure trials, however, occur in high-income countries.
Objective: To examine the perspectives of young women diagnosed with acute HIV in a longitudinal study, focusing on their perceptions on ATI-inclusive HIV cure trials and the barriers and facilitators to participation.
Arch Public Health
January 2025
Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Gran Via de les Corts Catalanes, 587 attic., Barcelona, 08007, Spain.
Objective: To analyze the sociostructural determinants associated with mental health problems during the lockdown period among populations residing in Brazil, Chile, Ecuador, Mexico, Peru, and Spain who lived with minors or dependents, approached from a gender perspective.
Methods: A cross-sectional study was conducted in six participating countries via an adapted, self-managed online survey. People living with minors and/or dependents were selected.
BMC Health Serv Res
January 2025
Australian Centre for Health Services Innovation and Centre for Healthcare Transformation, School of Public Health and Social Work, Faculty of Health, Queensland University of Technology, Brisbane, QLD, Australia.
Background: Unwarranted clinical variation presents a major challenge in contemporary healthcare, indicating potential inequalities and inefficiencies, and unrealised potential for better outcomes. Despite an increasing focus on unwarranted clinical variation, and consideration of efforts to address this challenge, evidence-based strategies which achieve this are limited. Audit and feedback of healthcare processes (process auditing) and clinician engagement are important tools which may help to reduce unwarranted clinical variation, however their application in maternity care is yet to be thoroughly explored.
View Article and Find Full Text PDFBMC Psychiatry
January 2025
Division of Epidemiology and Social Sciences, Institute for Health and Equity, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA.
Background: During adolescence, a critical developmental phase, cognitive, psychological, and social states interact with the environment to influence behaviors like decision-making and social interactions. Depressive symptoms are more prevalent in adolescents than in other age groups which may affect socio-emotional and behavioral development including academic achievement. Here, we determined the association between depression symptom severity and behavioral impairment among adolescents enrolled in secondary schools of Eastern and Central Uganda.
View Article and Find Full Text PDFSci Rep
January 2025
College of Physical Education and Health Sciences, Zhejiang Normal University, Jinhua, 321004, China.
Athlete engagement is influenced by several factors, including cohesion, passion and mental toughness. Machine learning methods are frequently employed to construct predictive models as a result of their high efficiency. In order to comprehend the effects of cohesion, passion and mental toughness on athlete engagement, this study utilizes the relevant methods of machine learning to construct a prediction model, so as to find the intrinsic connection between them.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!