To assess the effectiveness of smart home technologies (SHTs) in preventing and detecting falls among older adults in community and residential care settings.
To explore a comprehensive overview of digital technologies used for fall detection in older adults, categorizing the types, functions, and usability of these systems.
Ambulatory measurements of trunk accelerations can provide valuable insight into the amount and quality of daily life activities. Such information has been used to create models to identify individuals at high risk of falls. However, external validation of such prediction models is lacking, yet crucial for...
To determine whether physical performance measures commonly used in clinical settings can discriminate fallers from nonfallers and predict falls in older adults with dementia.
To examine the relationship between changes in nursing staff-hours per resident-day and injury-related emergency department (ED) visits among assisted living (AL) residents with Alzheimer disease and related dementias (ADRD).
The older population of United States is growing, with more adults having complicated medical conditions being admitted into nursing facilities and assisted living facilities. With the COVID-19 pandemic, the biggest challenge has been falls prevention, with an increasing number of patients being placed in ...
Fall-risk-increasing drugs (FRIDs)—psychotropics and cardiovascular disease (CVD) drugs—may elevate the risk of falling, with strong evidence observed in psychotropic FRIDs, whereas findings from cardiovascular disease (CVD) FRIDs remain inconclusive. Existing studies on FRIDs and falls are often hampered ...
Previous studies demonstrated that discrepancies between subjective and objective health measures are associated with physical and mental health–related outcomes in older adults. We investigate whether such discrepancies are also associated with risk of injurious falls in community-dwelling Swedish older a...