Fall risk in community-dwelling elderly cancer survivors: a predictive model for gerontological nurses.
The aim of this predictive study was to test a structural model to establish predictors of fall risk in elderly cancer survivors. An aging and nursing model of care was synthesized and used to examine the Minimum Data Set for 6,912 low-income older adult participants in a community setting in the midwestern United States. Data analysis established relationships among fall risk and age, race/ethnicity, history of a previous fall, depression, pain, activities of daily living, instrumental activities of daily living, incontinence, vision, and cognitive status. Factors leading to fall risk can direct nursing activities that have the potential to prevent falls, thus improving older adults' quality of life.
Michigan State University College of Nursing, East Lansing, Michigan 48824, USA. spoelst5@msu.edu
Sandra
S
Spoelstra
Barbara
B
Given
Alexander
A
von Eye
Charles
C
Given
D000058:Accidental Falls / Q000517:prevention & control / Q000706:statistics & numerical data*; D000203:Activities of Daily Living; D000368:Aged; D000369:Aged, 80 and over; D015984:Causality; D003430:Cross-Sectional Studies; D005260:Female; D015577:Geriatric Assessment / Q000379:methods*; D005851:Geriatric Nursing / Q000379:methods; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D008824:Michigan / Q000453:epidemiology; D016294:Models, Nursing; D015999:Multivariate Analysis; D009369:Neoplasms / Q000150:complications*; D009730:Nursing Assessment; D015403:Nursing Evaluation Research; D011237:Predictive Value of Tests; D012044:Regression Analysis; D018570:Risk Assessment / Q000379:methods*; D017741:Survivors / Q000706:statistics & numerical data