@article{ref1,
title="A research proposal testing a new model of ambulation activity among long-term care residents with dementia/cognitive impairment: the study protocol of a prospective longitudinal natural history study",
journal="BMC research notes",
year="2019",
author="Bowen, Mary Elizabeth and Rowe, Meredeth A. and Ji, Ming and Cacchione, Pamela",
volume="12",
number="1",
pages="e557-e557",
abstract="BACKGROUND: Excessive and patterned ambulation is associated with falls, urinary tract infections, co-occurring delirium and other acute events among long-term care residents with cognitive impairment/dementia. This study will test a predictive longitudinal data model that may lead to the preservation of function of this vulnerable population. <br><br>METHODS/DESIGN: This is a single group, longitudinal study with natural observations. Data from a real-time locating system (RTLS) will be used to objectively and continuously measure ambulation activity for up to 2 years. These data will be combined with longitudinal acute event and functional status data to capture patterns of change in health status over time. Theory-driven multilevel models will be used to test the trajectories of falls and other acute conditions as a function of the ambulation activity and demographic, functional status, gait quality and balance ability including potential mediation and/or moderation effects. Data-driven machine learning algorithms will be applied to run screening of the high dimensional RTLS data together with other variables to discover new and robust predictors of acute events. <br><br>DISCUSSION: The findings from this study will lead to the early identification of older adults at risk for falls and the onset of acute medical conditions and interventions for individualized care.<p /> <p>Language: en</p>",
language="en",
issn="1756-0500",
doi="10.1186/s13104-019-4585-5",
url="http://dx.doi.org/10.1186/s13104-019-4585-5"
}