The Gerontologist · 2003
Environmental correlates to behavioral health outcomes in Alzheimer's special care units.
СтатьяПоддержка службы здравоохранения СШАНазвание и аннотация: Перевод в очереди
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Zeisel John, Silverstein Nina M, Hyde Joan, Levkoff Sue, Lawton M Powell, Holmes William
Аннотация
PURPOSE: We systematically measured the associations between environmental design features of nursing home special care units and the incidence of aggression, agitation, social withdrawal, depression, and psychotic problems among persons living there who have Alzheimer's disease or a related disorder.
DESIGN AND METHODS: We developed and tested a model of critical health-related environmental design features in settings for people with Alzheimer's disease. We used hierarchical linear modeling statistical techniques to assess associations between seven environmental design features and behavioral health measures for 427 residents in 15 special care units. Behavioral health measures included the Cohen-Mansfield physical agitation, verbal agitation, and aggressive behavior scales, the Multidimensional Observation Scale for Elderly Subjects depression and social withdrawal scales, and BEHAVE-AD (psychotic symptom list) misidentification and paranoid delusions scales. Statistical controls were included for the influence of, among others, cognitive status, need for assistance with activities of daily living, prescription drug use, amount of Alzheimer's staff training, and staff-to-resident ratio. Although hierarchical linear modeling minimizes the risk of Type II-false positive-error, this exploratory study also pays special attention to avoiding Type I error-the failure to recognize possible relationships between behavioral health characteristics and independent variables.
RESULTS: We found associations between each behavioral health measure and particular environmental design features, as well as between behavioral health measures and both resident and nonenvironmental facility variables.
IMPLICATIONS: This research demonstrates the potential that environment has for contributing to the improvement of Alzheimer's symptoms. A balanced combination of pharmacologic, behavioral, and environmental approaches is likely to be most effective in improving the health, behavior, and quality of life of people with Alzheimer's disease.
DESIGN AND METHODS: We developed and tested a model of critical health-related environmental design features in settings for people with Alzheimer's disease. We used hierarchical linear modeling statistical techniques to assess associations between seven environmental design features and behavioral health measures for 427 residents in 15 special care units. Behavioral health measures included the Cohen-Mansfield physical agitation, verbal agitation, and aggressive behavior scales, the Multidimensional Observation Scale for Elderly Subjects depression and social withdrawal scales, and BEHAVE-AD (psychotic symptom list) misidentification and paranoid delusions scales. Statistical controls were included for the influence of, among others, cognitive status, need for assistance with activities of daily living, prescription drug use, amount of Alzheimer's staff training, and staff-to-resident ratio. Although hierarchical linear modeling minimizes the risk of Type II-false positive-error, this exploratory study also pays special attention to avoiding Type I error-the failure to recognize possible relationships between behavioral health characteristics and independent variables.
RESULTS: We found associations between each behavioral health measure and particular environmental design features, as well as between behavioral health measures and both resident and nonenvironmental facility variables.
IMPLICATIONS: This research demonstrates the potential that environment has for contributing to the improvement of Alzheimer's symptoms. A balanced combination of pharmacologic, behavioral, and environmental approaches is likely to be most effective in improving the health, behavior, and quality of life of people with Alzheimer's disease.