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Author ORCID Identifier

https://orcid.org/0000-0002-7463-735X

AccessType

Open Access Dissertation

Document Type

dissertation

Degree Name

Doctor of Philosophy (PhD)

Degree Program

Nursing

Year Degree Awarded

2021

Month Degree Awarded

September

First Advisor

Cynthia Jacelon

Second Advisor

Joohyun Chung

Third Advisor

Sara Mamo

Subject Categories

Geriatric Nursing

Abstract

Fatigue is experienced by 40-74% of older individuals living with a chronic disease. Despite advances in scientific knowledge around risk factors and consequences associated with fatigue, a comprehensive model that can serve as a guide for healthcare providers caring for older individuals with fatigue is lacking. Thus, the purpose of this study was to examine a fatigue model based on the Theory of Unpleasant Symptoms (TUS). The model included psychological, physiological, and situational risk factors of fatigue, as well as fatigue outcomes, such as physical, social, and cognitive performances, perceived health, and quality of life (QOL). This was a secondary data analysis of the “Patient-Reported Outcomes Measurement Information System Profiles – Health Utilities Index” dataset. Multiple regression analysis and path analyses were used to examine the association between fatigue and the above-mentioned variables. Findings suggested that number of comorbidities, pain, sleep, depression, anxiety, education, and sensory impairment (SI) were significant predictors of fatigue. In their turn, higher fatigue scores predicted lower physical, social, and cognitive performance, as well as worse perceived health and QOL. Additionally, fatigue outcomes mediated the relationship between fatigue and QOL. Health care providers of older individuals with fatigue should closely monitor and manage the physiological, psychological, and situational risk factors of fatigue, which would, in turn, improve these individuals’ performance on all three levels, perceived health, as well as their QOL. Future research should be directed towards exploring other risk factors of fatigue, examining feedback loops depicted in the TUS, identifying whether neurodegenerative diseases moderate the relationship between CP and QOL, and identifying variables that mediate the relationship between certain risk factors and fatigue.

DOI

https://doi.org/10.7275/23570183

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