Some nurses describe individuals diagnosed with borderline personality disorder (BPD) as among the most challenging and difficult patients encountered in their practice. As a result, the argument has been made for nursing staff to receive clinical supervision to enhance therapeutic effectiveness and treatment outcomes for individuals with BPD. Formal clinical supervision can focus on the stresses of working in a demanding environment within the work place and enable nurses to accept accountability for their own practice and development (Pesut & Herman, 1999). A psychiatric-mental health clinical nurse specialist can provide individual and/or group supervision for the nursing staff, including education about patient dynamics, staff responses, and treatment team decisions. A clinical nurse specialist also can provide emotional support to nursing staff, which enhances job satisfaction, as they struggle to maintain professional therapeutic behavior with these individuals.
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http://dx.doi.org/10.1080/01612840590931957 | DOI Listing |
Paediatr Anaesth
January 2025
Flinders University, College of Medicine and Public Health, Adelaide, South Australia, Australia.
Background: After-hours pediatric anesthesia may pose increased risks, with a heightened potential for sudden cardio-respiratory decline. While mortality rates are low in Australia and New Zealand, critical events and morbidity occur more frequently and present ongoing challenges. However, little is known about how trainees are supervised during these high-risk periods.
View Article and Find Full Text PDFDement Geriatr Cogn Dis Extra
December 2024
Division of Clinical Medicine, Department of Psychiatry, Institute of Medicine, University of Tsukuba, Tsukuba, Japan.
Introduction: After Alzheimer's disease, frontotemporal lobar degeneration (FTLD) is the second most common form of early-onset dementia. Despite the heavy burden of care for FTLD, pharmacological and non-pharmacological treatments with sufficient efficacy remain scarce. This study aimed to evaluate the feasibility of a multimodal exercise program for FTLD and to examine preliminary changes in the clinical outcomes of the program in FTLD.
View Article and Find Full Text PDFQuant Imaging Med Surg
January 2025
Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
Background: Echocardiography can conveniently, rapidly, and economically evaluate the structure and function of the heart, and has important value in the diagnosis and evaluation of cardiovascular diseases (CVDs). However, echocardiography still exhibits significant variability in image acquisition and diagnosis, with a heavy dependency on the operator's experience. Image quality affects disease diagnosis in the later stage, and even image quality assessment still has variability in human evaluation.
View Article and Find Full Text PDFAnn Med
December 2025
Clinical Center for Intelligent Rehabilitation Research, Shanghai YangZhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), Tongji University School of Medicine, Tongji University, Shanghai, China.
Background: Cardiovascular disease (CVD) is the top cause of death in China. We aimed to identify trends in cause-specific CVD mortality in a rapidly developing country, thereby providing evidence for CVD prophylaxis.
Materials And Methods: Using raw data from the Chinese National Mortality Surveillance (CNMS) system, we assessed the mortalities of all CVD and cause-specific CVD during 2009-2019.
BMC Bioinformatics
January 2025
Department of Applied Computer Science, University of Winnipeg, Winnipeg, MB, R3B 2E9, Canada.
Background: Comprehensively mapping the hierarchical structure of breast cancer protein communities and identifying potential biomarkers from them is a promising way for breast cancer research. Existing approaches are subjective and fail to take information from protein sequences into consideration. Deep learning can automatically learn features from protein sequences and protein-protein interactions for hierarchical clustering.
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