In recent years, the move toward a more holistic perspective in health care has led to social scientists investigating psychosocial factors in chronic illness, such as the different languages used by health professionals when talking about nonhealth. However, there has been little inquiry into caregivers' illness experiences of stroke and Alzheimer's disease (AD). This study therefore explores the illness experiences of seven caregivers whose spouses are stroke or AD patients. A hermeneutic approach was adopted and two relatively unstructured interviews were conducted with each caregiver. Using Kleinman's work on illness narratives as an interpretive framework, it was found that - except for people questioning the authenticity of AD caregivers' experiences - similarities in caregivers' experiences outweighed differences. All described the extent to which their lives had been damaged by the illness and their reparation attempts. Critique of the research is presented and the findings' implications for treatment are suggested / M.A. (Clinical Psychology)

Indiana University-Purdue University Indianapolis (IUPUI) / Alzheimer's disease (AD) is a neurodegenerative disorder characterized by gradual loss of brain functions, usually preceded by memory impairments. It has been widely affecting aging Americans over 65 old and listed as 6th leading cause of death. More importantly, unlike other diseases, loss of brain function in AD progression usually leads to the significant decline in self-care abilities. And this will undoubtedly exert a lot of pressure on family members, friends, communities and the whole society due to the time-consuming daily care and high health care expenditures. In the past decade, while deaths attributed to the number one cause, heart disease, has decreased 16 percent, deaths attributed to AD has increased 68 percent. And all of these situations will continue to deteriorate as the population ages during the next several decades. To prevent such health care crisis, substantial efforts have been made to help cure, slow or stop the progression of the disease. The massive data generated through these efforts, like multimodal neuroimaging scans as well as next generation sequences, provides unprecedented opportunities for researchers to look into the deep side of the disease, with more confidence and precision. While plenty of efforts have been made to pull in those existing machine learning and statistical models, the correlated structure and high dimensionality of imaging and genetics data are generally ignored or avoided through targeted analysis. Therefore their performances on imaging genetics study are quite limited and still have plenty to be improved. The primary contribution of this work lies in the development of novel prior knowledge-guided regression and association models, and their applications in various neurobiological problems, such as identification of cognitive performance related imaging biomarkers and imaging genetics associations. In summary, this work has achieved the following research goals: (1) Explore the multimodal imaging biomarkers toward various cognitive functions using group-guided learning algorithms, (2) Development and application of novel network structure guided sparse regression model, (3) Development and application of novel network structure guided sparse multivariate association model, and (4) Promotion of the computation efficiency through parallelization strategies.

The purpose of this study was to evaluate the recreational activities provided in special care units located in the Inland Empire. The population that this study sought to assist was patients diagnosed with Alzheimer's disease and living in an Alzheimer's special care unit.