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B D Manz

Publications and source records attributed to B D Manz.

2 recordsLinked to original sources

Pain assessment in the cognitively impaired and unimpaired elderly.

The purpose of this study was to determine the self-report pain rating scale(s) that can be used to quantify pain in elderly persons across cognitive functioning levels. Randomly selected elderly subjects (N = 100) completed the Short Portable Mental Status Questionnaire to categorize their level of cognitive impairment: intact (n = 36), mild (n = 9), moderate (n = 15), and severe (n = 40). Pain was measured with the Memorial Pain Assessment Card verbal subscale, FACES, COOP pain subscale, a numeric rating scale, and the Present Pain Intensity subscale of the McGill Pain Questionnaire. Receiver operator characteristic curves indicated that participants categorized with moderate to no cognitive impairment were able to complete 1 or more of the pain assessment tools. Of the severely impaired, 30% were able to complete 1 or more pain assessment tools. Intraclass correlations showed a high degree of consistency among all pairs of tools (intraclass correlation > 0.74). We conclude that most elderly, with normal to moderately impaired cognitive functioning, as well as some severely impaired elderly, are capable of using self-report tools to rate their pain.

Aged↗

Modeling categorical variables by logistic regression.

OBJECTIVE: To demonstrate the use of logistic regression in health care research. METHOD: Forward and backward stepwise logistic regression algorithms were systematically applied to a real-world data set comprising 301 cancer patients and a set of explanatory variables. RESULTS: Four variables were identified as effective predictors of pain reporting by cancer patients during chemotherapy: fatigue, depression, severity of colds or viral infections, and insomnia. The 4-predictor model was validated by (a) significance tests of regression coefficients at p<0.05, (b) significant improvement of this model over competing models, and (c) goodness of fit indices. CONCLUSIONS: Logistic regression is useful for health-related research in which outcomes of interest are often categorical.

Adolescent↗