Background: Korea, as one of the fastest-aging countries worldwide, requires an improved healthcare service model for older adults. We evaluated the current healthcare system and developed a service model based on information and communication technologies (ICT) for use in older patients in long-term care facilities (LTCF).
Methods: We conducted a qualitative literature review, focus group interviews (FGIs), and structured survey to identify the current technology use and status of healthcare systems.
Background: Health care technologies can help improve workers' health and productivity by supporting workplace health promotion. A personal health record app is used to manage medical data such as results from medical checkups, which facilitates decision making for medical personnel. However, an analysis of users' technology acceptance is required to provide appropriate services based on personal health record apps.
View Article and Find Full Text PDFBackground: To investigate the relationship between hand grip strength (HGS) and self-rated health in middleand old-aged Korean subjects.
Methods: The data used for this study were derived from the Korean Longitudinal Study of Aging. A total of 9,132 participants were enrolled using the year 2006 as the baseline, with additional data collected throughout the followup period until 2016.
Introduction: Epilepsy is a chronic neurological disorder characterized by recurrent spontaneous seizures. Over 70% epilepsy patients can live normally if their seizures can be controlled. For this, many factors should be tracked and managed, but doing so is hard because of individual differences.
View Article and Find Full Text PDFBackground: Aging causes both structural and functional changes in the skeletal muscle, and is associated with changes in body composition form, which results in an increased incidence of cardiovascular death. Handgrip strength (HGS) is a simple, fast, reliable, and cost-effective tool for measuring muscle strength.
Objective: We aimed to investigate which index was most suitable for predicting cardiovascular disease (CVD), and suggested the optimal cut-off points based on the handgrip strength index.