Award Date
8-1-2020
Degree Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Psychology
First Committee Member
Daniel Allen
Second Committee Member
Bradley Donohue
Third Committee Member
Murray Millar
Fourth Committee Member
Andrew Freeman
Fifth Committee Member
Jennifer Keene
Number of Pages
140
Abstract
Alzheimer’s Disease (AD) is a degenerative neurological disease process that results in cognitive and functional declines and ultimately results in death. The pattern and course of cognitive and functional decline has been well characterized in AD, however little is known about the interactions between the symptoms. Network Analysis is a recently developed mathematical approach of examining the interactions between symptoms, by exploring the covariance of symptoms. The current study utilized network analysis to examine the multivariate structural dependencies among cognitive domains known to be affected in Alzheimer’s disease. The sample consisted of 864 older adults (60-90 years old), selected from the National Alzheimer’s Coordinating Center (NACC) Database, that were assessed over four serial cognitive assessments, each conducted approximately one year apart. The sample was divided into two groups (432 per group). Both groups were cognitively normal at baseline assessment, with one group remaining cognitively normal (Control group) and one going on to develop either Mild Cognitive Impairment (MCI) or Dementia due to AD (Converter group) over the course of the four assessments. The participants completed a neuropsychological assessment with tests known to be sensitive to AD, which included a global screener, measures of attention, processing speed, executive function, episodic memory, and language. The relationship between performance on these measures was examined using Network Analysis. The Converter group was also subdivided by sex and the networks of men and women were compared. It was hypothesized that there would be differences in the network structure of these cognitive test between the groups both before criteria for a cognitive diagnosis was made, as well as after the Converter group was diagnosed with AD. It was also hypothesized that the network structure of cognitive tests would differ for men and women with AD. Finally, it was hypothesized that the network structure of these cognitive tests would differ over time for the Converter group. Results indicate that there are differences in the network structure of cognitive tests between the Control and Converter groups even before diagnosis and that this difference becomes more significant over time. However there is not a significant difference between men and women in the Converter group, in terms of network structure. Finally within the Converter group, while the difference in network structure appears to become more prominent over time, they are not significantly different over the four years assessed in the current study. These findings provide a clearer understanding the impact of AD on the changes in cognitive functioning and further efforts of early detection, with the goals of improved intervention and prevention.
Keywords
Alzheimer's Disease; Dementia; Network Analysis; Neuropsychology
Disciplines
Psychology
File Format
File Size
4799 KB
Degree Grantor
University of Nevada, Las Vegas
Language
English
Repository Citation
Baily, Abigail Rose, "Network Analysis of Cognitive Symptom Domains in Alzheimer's Disease (AD)" (2020). UNLV Theses, Dissertations, Professional Papers, and Capstones. 3986.
http://dx.doi.org/10.34917/22086612
Rights
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