Citation

Kearns WD, Fozard JL, Becker M, Jasiewicz JM, Craighead JD, Holtsclaw L, Dion C. J. Am. Med. Dir. Assoc. 2012; 13(7): 665.e7-665.e13.

Affiliation

Department of Rehabilitation and Mental Health Counseling, USF College of Behavioral and Community Sciences, Tampa, FL.

Copyright

(Copyright © 2012, Lippincott Williams and Wilkins)

DOI

10.1016/j.jamda.2012.06.010

PMID

22884091

Abstract

OBJECTIVES: We hypothesized that variability in voluntary movement paths of assisted living facility (ALF) residents would be greater in the week preceding a fall compared with residents who did not fall. DESIGN: Prospective, observational study using telesurveillance technology. SETTING: Two ALFs. PARTICIPANTS: The sample consisted of 69 older ALF residents (53 female) aged 76.9 (SD ± 11.9 years). MEASUREMENT: Daytime movement in ALF common use areas was automatically tracked using a commercially available ultra-wideband radio real-time location sensor network with a spatial resolution of approximately 20 cm. Movement path variability (tortuosity) was gauged using fractal dimension (fractal D). A logistic regression was performed predicting movement related falls from fractal D, presence of a fall in the prior year, psychoactive medication use, and movement path length. Fallers and non-fallers were also compared on activities of daily living requiring supervision or assistance, performance on standardized static and dynamic balance, and stride velocity assessments gathered at the start of a 1-year fall observation period. Fall risk due to cognitive deficit was assessed by the Mini Mental Status Examination (MMSE), and by clinical dementia diagnoses from participant's activities of daily living health record. RESULTS: Logistic regression analysis revealed odds of falling increased 2.548 (P = .021) for every 0.1 increase in fractal D, and having a fall in the prior year increased odds of falling by 7.36 (P = .006). There was a trend for longer movement paths to reduce the odds of falling (OR .976 P = .08) but it was not significant. Number of psychoactive medications did not contribute significantly to fall prediction in the model. Fallers had more variable stride-to-stride velocities and required more activities of daily living assistance. CONCLUSIONS: High fractal D levels can be detected using commercially available telesurveillance technologies and offers a new tool for health services administrators seeking to reduce falls at their facilities.

Language: en