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Smart home technology to support engagement in everyday activities while ageing: A focus group study with current and future generations of older adults.
PLoS One
January 2025
Faculty of Medicine, Department of Health Sciences, Lund University, Lund, Sweden.
Despite the potential of smart home technologies (SHT) to support everyday activities, the implementation rate of such technology in the homes of older adults remains low. The overall aim of this study was to explore factors involved in the decision-making process in adopting SHT among current and future generations of older adults. We also aimed to identify and understand barriers and facilitators that can better support older adults' engagement in everyday activities.
View Article and Find Full Text PDFImportant factors in municipality-based pediatric palliation from healthcare professionals' perspective: A qualitative study.
Palliat Care Soc Pract
January 2025
Center for Crisis Psychology, Faculty of Psychology, University of Bergen, Postbox 7807, Bergen 5020, Norway.
Background: Municipality-based pediatric palliative care (PPC) is recommended to promote the quality of life for the child and family by enabling them to stay at home as much as possible. However, municipality-based PPC presents complex challenges and places significant demands on healthcare professionals. Yet, it remains an underexplored field.
View Article and Find Full Text PDFAn Algorithmic Overview of Advanced Pain Therapies: A Narrative Review.
Curr Pain Headache Rep
January 2025
Department of Pain Medicine, Division of Anesthesiology, Critical Care & Pain Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
Purpose Of Review: Quickly referenceable, streamlined, algorithmic approaches for advanced pain management are lacking for patients, trainees, non-pain specialists, and interventional specialists. This manuscript aims to address this gap by proposing a comprehensive, evidence-based algorithm for managing neuropathic, nociceptive, and cancer-associated pain. Such an algorithm is crucial for pain medicine education, offering a structured approach for patient care refractory to conservative management.
View Article and Find Full Text PDFAI for all: bridging data gaps in machine learning and health.
Transl Behav Med
January 2025
Slone Epidemiology Center at Boston University, 72 E Concord St, Boston, MA, USA.
Artificial intelligence (AI) and its subset, machine learning, have tremendous potential to transform health care, medicine, and population health through improved diagnoses, treatments, and patient care. However, the effectiveness of these technologies hinges on the quality and diversity of the data used to train them. Many datasets currently used in machine learning are inherently biased and lack diversity, leading to inaccurate predictions that may perpetuate existing health disparities.
View Article and Find Full Text PDFDepression-related innate immune genes and pan-cancer gene analysis and validation.
Front Genet
January 2025
Department of Pharmacology, The Key Laboratory of Neural and Vascular Biology, The Key Laboratory of New Drug Pharmacology and Toxicology, Ministry of Education, Collaborative Innovation Center of Hebei Province for Mechanism, Diagnosis and Treatment of Neuropsychiatric Diseases, Hebei Medical University, Shijiazhuang, Hebei, China.
Background: Depression, a prevalent chronic mental disorder, presents complexities and treatment challenges that drive researchers to seek new, precise therapeutic targets. Additionally, the potential connection between depression and cancer has garnered significant attention.
Methods: This study analyzed depression-related gene expression data from the GEO database.
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