The present study investigates the predictive accuracy of a key approach to interpretation of the verbal-spatialcognitive (VSC) and sensorimotor (SM) factors of the McCarron-Dial System (MDS). The subjects include 99 brain damaged and 30 normal adults. The following research questions are addressed: (a) Does the neuropsychological key classify brain damaged and non-brain damaged subjects at a level significantly above chance? (b) Among the brain damaged subjects, does the neuropsychological key identify right brain damage, left brain damage and diffuse brain damage at an accuracy level significantly above chance? (c) Is the neuropsychological key approach superior to the empirical model derived from discriminant function analysis in predictive accuracy? The neuropsychological key correctly classifies 90% of the cases as brain damaged and 90% of the cases as non-brain damaged, for a total of 89.9% predictive accuracy. The obtained Kappa coefficient of .74 is statistically significant. The key accurately classifies 71.4% of the brain damaged group as right damage, 70% as left damage, and 93.8% as diffuse damage, for a total predictive accuracy of 7 9.5%. The Kappa coefficient of .68 is statistically significant. Chi square analysis of the difference between the key approach and multiple discriminant function analysis reveals that no significant difference is present between the accuracy of the two approaches in differentiating between brain damaged and non-brain damaged, or in differentiating among left, right and diffuse brain damage. The results support the validity of a neuropsychological key approach to interpretation of the McCarron-Dial System, although cross-validation is indicated to confirm the stability of these results. Differences in sex, educational level and racial composition of the comparison groups may have affected the results obtained. Refinement of the key in future research and the addition of test instruments assessing memory, auditory processing, attention and emotional/behavioral variables are recommended.
C-reactive protein (CRP) is a protein found in the blood that is synthesized by the liver and has been extensively studied due to its role in inflammatory and atherosclerotic processes. The importance of this biomarker in its role in vascular risk factors is increased with several lines of evidence pointing to its association with cognitive decline. The association between CRP and depression has been increasingly analyzed by various cross-sectional studies. The research between CRP and depressive symptoms in older women has yet to generate consistent trends. In the present study, a series of regression analyses was used to explore the association between CRP and both cognitive function and depressive symptomatology among a group of rural-dwelling women. Associations were evaluated through the use of data from Project FRONTIER, a rural-based research looking at both physical and cognitive aspects of health in rural-dwelling adults and elders. Comparisons were made between Mexican American women and a group of non-Hispanic Caucasian women. CRP was a significant independent predictor of total depression (beta = -.11, t = -1.99, p =.048). CRP was also a significant independent predictor of symptoms associated with meaningless within depression (beta = -.16, t = -2.94, p =.004). Contrary to prediction, CRP was not a significant independent predictor of overall cognitive function or performance in five specific cognitive domains. There is still needed evaluation on racial/ethnic differences present in regard to the impact of varied health factors on mental health within a culturally rich, rural cohort. It is recommended that future studies utilize standardized measurement of cognitive function to facilitate a more thorough understanding and comparison of change in this particular population.
The purpose of this study was to validate a stress inventory which would differentiate between a normative group and a patient population suffering from environmental illness. The hypotheses of this study were: (1) the Total Stress Load Inventory would be predictive in discriminating between clinical ecology patients and a normative group; (2) each section or subscale of the Total Stress Load Inventory would be predictive of psychological, cognitive, nutritional, and/or medical factors.
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