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Changes in Motor Behavior Predict Falls and Identify Acute Events.

Mary Elizabeth Bowen1,2, Pamela Cacchione3,4

  • 1School of Nursing, University of Delaware, Newark, DE, USA.

Western Journal of Nursing Research
|July 20, 2021
PubMed
Summary

Subtle changes in motor behavior, like reduced gait speed, can predict falls and acute events such as delirium and urinary tract infections (UTIs) in nursing home residents. Continuous monitoring may help prevent these adverse outcomes.

Keywords:
BalanceDeliriumGaitRadio frequency identification deviceUrinary tract infection

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Area of Science:

  • Gerontology
  • Clinical Nursing
  • Biomedical Engineering

Background:

  • Falls, delirium, and urinary tract infections (UTIs) are common adverse events in skilled nursing facilities, significantly impacting resident health and quality of life.
  • Traditional methods for detecting these events may not capture early, subtle physiological changes.
  • Motor behavior, encompassing gait speed, time, and distance traveled, offers a potential window into underlying health status.

Purpose of the Study:

  • To investigate the association between objective measures of motor behavior and the occurrence of falls, delirium, and UTIs in skilled nursing residents.
  • To determine if changes in motor behavior can serve as early warning indicators for these adverse health events.

Main Methods:

  • A longitudinal study involving 23 skilled nursing residents (128 observations) over 18 months.
  • Real-time locating systems (RTLS) were employed to continuously monitor motor behaviors, including time and distance traveled and gait speed.
  • Multilevel statistical models were utilized to analyze the relationship between motor behavior metrics and the incidence of falls, delirium, and UTIs.

Main Results:

  • Decreased gait speed and path distance were significantly associated with an increased risk of falls.
  • Delirium was linked to increased distance traveled and path distance, alongside decreased time traveled and path time.
  • Urinary tract infections (UTIs) showed associations with increased distance traveled, decreased time traveled, and a reduced number of paths.

Conclusions:

  • Subtle alterations in motor behavior, as measured by RTLS, may serve as early predictive indicators for falls and acute health events like delirium and UTIs.
  • Continuous monitoring of motor behavior presents a promising non-invasive strategy for early detection and potential prevention or delay of adverse health outcomes in long-term care settings.
  • Integrating objective motor behavior data into clinical practice could enhance proactive resident care and safety.