Despite the recognition of dementia as a major public health concern, the differential diagnosis of dementia subtypes remains problematic. Alzheimer's disease (AD) and vascular dementia (VAD) are the two most common subtypes of dementia, and clinicopathologic studies suggest that accuracy rates for the differential diagnosis of AD and VAD range from 60–95%. Higher rates of accuracy are achieved for AD than for VAD, but several questions remain unanswered regarding the differential diagnosis of dementia. Studies have not examined the accuracy with which neuropsychologists in particular make diagnoses of AD and VAD, nor have they examined the decision-making processes employed when neuropsychologists make diagnoses of dementia. The purpose of the present study was to develop and implement a new technology designed to investigate diagnostic accuracy and decision-making processes used in the differential diagnosis of AD, VAD, and normative age-related cognitive decline. Sixteen practicing neuropsychologists from Massachusetts and Rhode Island participated in this study, and all subjects rendered diagnoses for each of the three cases. Results revealed a high rate of accuracy with the diagnosis of AD, but suboptimal rates for VAD and no-impairment. Diagnostic accuracy correlated significantly with neuropsychologists' confidence ratings, but not with measures of training and experience. A qualitative analysis of information search and review strategies used by neuropsychologists indicated that systematic, comprehensive data reviews, and early attention to neuroimaging findings were associated with optimal diagnostic outcomes. The results of the present study also suggest that internet-based assessment programs may represent a viable and useful method of studying decision-making.
| Identifer | oai:union.ndltd.org:UMASS/oai:scholarworks.umass.edu:dissertations-3346 |
| Date | 01 January 2000 |
| Creators | Boyle, Patricia A |
| Publisher | ScholarWorks@UMass Amherst |
| Source Sets | University of Massachusetts, Amherst |
| Language | English |
| Detected Language | English |
| Type | text |
| Source | Doctoral Dissertations Available from Proquest |
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