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J Gerontol A Biol Sci Med Sci. 2005 Feb;60(2):258-64.

Predictors of functional impairment in residents of assisted-living facilities: the Maryland Assisted Living study.

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Division of Geriatric Psychiatry, Department of Psychiatry and Behavioral Sciences, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.



Assisted living is a popular residential option for older individuals, yet little research has been done on people choosing this option. This study examines predictors of functional impairment in assisted living residents in the domains of cognition, mood, and health.


An experienced team of neuropsychiatrists, nurses, and technicians using a number of cognitive, behavioral, health, and functional status tests and a cross-sectional study design assessed 198 residents of 22 assisted living facilities in Maryland. Data from these evaluations were used in univariate and multiple regression models to identify predictors of functional impairment, operationalized as the sum of the scores on two scales, one measuring impairment in basic activities of daily living and one measuring impairment in instrumental activities of daily living.


Greater cognitive impairment, worse depression, and worse medical health were significant independent predictors of functional impairment, together explaining a sizeable portion of the variance (adjusted R2=0.434). None of the demographic variables examined individually, including age and education, was predictive of functional impairment. In an analysis of specific cognitive domains, executive dysfunction, impairment of visuospatial skills, and amnesia were significant predictors of impairment, whereas inattention was not.


Executive dysfunction, apraxia, memory impairment, depression, and general medical health are all significant predictors of functional impairment in assisted living residents, with executive dysfunction being the strongest. These results may be instrumental in developing a more efficient model of care for residents of assisted living facilities, one based on having accurate predictive models of degree of impairment.

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