D R Royall1, M Cabello, M J Polk. 1. Department of Psychiatry, The Audie L. Murphy VA Geriatric Research Education and Clinical Center, University of Texas Health Science Center at San Antonio 78264-7792, USA.
Abstract
OBJECTIVES: To examine the relative contributions of Executive Control Function (ECF), general cognition, mood, problem behavior, physical disability, demographic variables, and the number of prescribed medications to the level of care received by older retirees. DESIGN: Multivariate regression and discriminant modeling. SETTING: A single Continuing Care Retirement Community (CCRC) in San Antonio, Texas. PARTICIPANTS: A total of 107 older retirees (mean age = 83.7+/-7.2 years), including 17 community-dwelling, well, older controls and 90 CCRC residents. CCRC subjects represented a convenience sample of consecutive referrals for geropsychiatric assessment. Sixty-one subjects resided at a noninstitutionalized level of care, and 46 were institutionalized. MEASUREMENTS: Tests of ECF (the Executive Interview (EXIT25)), general cognition (the Mini-Mental State Examination (MMSE)), mood (the Geriatric Depression Scale short-form (sGDS)), problem behavior (the Nursing Home Behavior Problem Scale (NHBPS)), physical disability (the Cumulative Illness Rating Scale (CIRS)), age, gender, years of education, and the number of prescribed medications were studied. RESULTS: All variables except gender and education varied significantly across level of care. Four variables made significant independent contributions; EXIT25 score (r2 = .48, P< .001), medication usage (partial r2 = .11, P<.001), sGDS score (partial r2 = .06, P = .001), and problem behavior (partial NHBPS r2 = .04, P<.04). These variables accounted for 69% of the total variance in level of care (R2 = .69; F (df 7,99) = 32.1, P<.001). A discriminant model based on the number of prescribed medications, EXIT25, sGDS, and NHBPS scores classified 83.2% of cases correctly (Wilke's lambda = .50, F(5,101) = 20.1; P<.001). The MMSE enters but fails to contribute significantly, independent of the other variables. Age and CIRS scores fail to enter. CONCLUSIONS: Cognitive (particularly ECF) impairment contributes most to the observed variance in level of care received by older retirees in this CCRC. In contrast, markers of general cognition, depression, and physical illness contributed relatively little additional variance. ECF is not detected well by traditional cognitive measures and must be sought by specific tests. Further study is needed to replicate these findings in other populations.
OBJECTIVES: To examine the relative contributions of Executive Control Function (ECF), general cognition, mood, problem behavior, physical disability, demographic variables, and the number of prescribed medications to the level of care received by older retirees. DESIGN: Multivariate regression and discriminant modeling. SETTING: A single Continuing Care Retirement Community (CCRC) in San Antonio, Texas. PARTICIPANTS: A total of 107 older retirees (mean age = 83.7+/-7.2 years), including 17 community-dwelling, well, older controls and 90 CCRC residents. CCRC subjects represented a convenience sample of consecutive referrals for geropsychiatric assessment. Sixty-one subjects resided at a noninstitutionalized level of care, and 46 were institutionalized. MEASUREMENTS: Tests of ECF (the Executive Interview (EXIT25)), general cognition (the Mini-Mental State Examination (MMSE)), mood (the Geriatric Depression Scale short-form (sGDS)), problem behavior (the Nursing Home Behavior Problem Scale (NHBPS)), physical disability (the Cumulative Illness Rating Scale (CIRS)), age, gender, years of education, and the number of prescribed medications were studied. RESULTS: All variables except gender and education varied significantly across level of care. Four variables made significant independent contributions; EXIT25 score (r2 = .48, P< .001), medication usage (partial r2 = .11, P<.001), sGDS score (partial r2 = .06, P = .001), and problem behavior (partial NHBPS r2 = .04, P<.04). These variables accounted for 69% of the total variance in level of care (R2 = .69; F (df 7,99) = 32.1, P<.001). A discriminant model based on the number of prescribed medications, EXIT25, sGDS, and NHBPS scores classified 83.2% of cases correctly (Wilke's lambda = .50, F(5,101) = 20.1; P<.001). The MMSE enters but fails to contribute significantly, independent of the other variables. Age and CIRS scores fail to enter. CONCLUSIONS: Cognitive (particularly ECF) impairment contributes most to the observed variance in level of care received by older retirees in this CCRC. In contrast, markers of general cognition, depression, and physical illness contributed relatively little additional variance. ECF is not detected well by traditional cognitive measures and must be sought by specific tests. Further study is needed to replicate these findings in other populations.
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