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

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. 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. 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.

Changes in Motor Behavior Predict Falls and Identify Acute Events

“…The independent variable of interest in this study is motor behavior, calculated using the x - and y -coordinates provided by the real-time locating system (RTLS, Ubisense series 7000 IP Sensor, and Series 700 Tag) with ultra-wideband radio frequency identification, UWB RFID technology (Ubisense, 2021). Previous work details the protocol, measures, and benefits of using a real-time objective and continuous measuring system in health care (Bowen, 2020; Bowen, Kearns, et al, 2019; Bowen, Rowe, et al, 2019). Briefly, participants wore an RTLS tag on their wrist continuously (24/7) at update rates of up to 6 times/s.…”

“…This longitudinal natural history study aims to examine how changes in motor behavior (using RTLS) may be an early indicator of a fall, delirium, and/or UTI. The RTLS used here is an objective and continuous (e.g., 24/7) wrist-worn sensor that measures multiple residents’ location and movement simultaneously around the unit with an accuracy of 6 cm (Bowen, Kearns, et al, 2019; Bowen, Rowe, et al, 2019; Bowen et al, 2013). It is expected that intra-individual changes in motor behavior (distance traveled, gait speed, and path characteristics (continuous walking with little/no breaks) will be associated with acute events.…”