The Saint Louis University Mental Status (SLUMS) Examination is a relatively new brief cognitive screening measure developed for use with veterans. To date, there has been a paucity of research on its psychometric properties. Using a sample of 148 male veterans referred to a VA Mild Cognitive Impairment (MCI) Clinic for evaluation, the SLUMS’ ability to discriminate between MCI versus other diagnoses or no diagnosis was compared to results from a more comprehensive neuropsychological battery. Approximately 51% of the sample was diagnosed with MCI, 16% with Major Depressive Disorder (MDD), 17% did not meet criteria for a diagnosis, and 16% were given some other DSM-IV-TR diagnosis. The SLUMS demonstrated poor internal consistency (Cronbach’s alpha = .57), but scores were significantly correlated with scores on every neuropsychological measure, except for Trails B. Diagnostic discriminability was comparable to that of the more time intensive neuropsychological battery for discriminating between MCI and no diagnosis, and MCI and MDD. In the current sample, a cutoff score of 25 was optimal for discriminating between MCI and no diagnosis, whereas a slightly lower cutoff score of 24 is recommended for discriminating between MCI and those with MDD. Diagnostic indicators were poor for the SLUMS and the battery when discriminating between MCI and a heterogeneous group of other disorders. Possible reasons for low reliability in such a screening measure in the context of convergent validity are discussed. It is concluded that the SLUMS may be a viable brief cognitive screening measure in such veteran populations, particularly when discriminating between MCI and MDD; however, additional studies should be completed to evaluate other forms of consistency, such as test-retest reliability.

There is two different ways to react to a disease like Mild cognitive impairment and Alzheimer’s disease, pathological and clinical. What if there was a way to delay the clinical expression of a disease through pathology? The cognitive reserve has been proven to show a more rapid decline in the individuals that had higher reserve. The purpose of this study was to see if the cognitive reserve actually had an impact on the outcome of Dementia and Alzheimer’s disease. A total of 53 patients with varying degrees of disease pathology and clinical symptoms participated in the study. The results demonstrated that the cognitive reserve makes an impact on the clinical expression, the individuals with high cognitive reserve have a delayed clinical expression comparatively with those with low reserve. Studies of the cognitive reserve may point the way to successful interventions that can help maintain successful aging and slow the onset of dementia.

Thesis (Ph.D.)--George Mason University, 2008. / Vita: p. 125. Thesis director: Frederick J. Brigham. Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Education. Title from PDF t.p. (viewed July 3, 2008). Includes bibliographical references (p. 118-124). Also issued in print.

Thesis (M.S.)--University of Michigan, 1981.

Thesis (M.S.)--University of Michigan, 1981.

Thesis (Ph.D.) - University of Queensland, 2005. / Includes bibliography.

Thesis (Ph.D.)--York University, 2002. Graduate Programme in Psychology. / Typescript. Includes bibliographical references (leaves 63-76). Also available on the Internet. MODE OF ACCESS via web browser by entering the following URL: http://wwwlib.umi.com/cr/yorku/fullcit?pNQ99177

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This thesis presents a performance evaluation system for cognitive radio. It considers performance as a complex, multi-dimensional function. Typically such a function would take some record of actions as an argument; however, a key contribution of this work is the addition of background information to the domain of the performance function. Including this information generalizes the performance function across many radios and applications, with the additional cost of complicating the domain. Thus the presented evaluation system organizes the domain information into sets. These sets are divided into two categories, one capturing necessary information that is external to the radio and on capturing necessary information that internal to the radio. These categories highlight the fact that neither the true actions nor the true performance is directly observable at the onset of evaluation. This arises because a cognitive radio can only express its actions in terms of the available knobs and meters, which together form the radio's language. Some understanding of this language and its limitations is required to fully understand the radio's expression of its actions. This parallelism of actions and performance suggests implementing the evaluation method as a composite form of the performance function. The composite performance function is made up of two sub-functions, one of which producing action information and one of which producing performance information. Specifically, the first sub-function is used to determine general measures of the actions' influence on performance; these are labeled Measures of Effectiveness. The second sub-function uses these Measures of Effectiveness to determine application specific performance values, called Measures of Performance. This work covers both these measures in detail. Each measure is determined as the result of a neural network based interpolation. This thesis also provides an examination of artificial neural networks in the scope of performance evaluation. Once these concepts are explored, a walk-through evaluation is presented. The four phases are the Setup Phase, the Logging Phase, the Training Phase, and the Evaluation Phase. Each phase is structured to provide the information necessary to determine the final performance. These phases detail the process of evaluation and discuss the realization of concepts explored earlier. This work concludes with a comparative evaluation example that proves the worth of the presented approach. A full evaluation system is outlined by this thesis and the foundational details for the system are explored in detail. / Master of Science

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