Ali A Weinstein1,2,3, Guoqing Diao4, Heibatollah Baghi5, Carey Escheik6, Lynn H Gerber6,7,8, Zobair M Younossi6,8. 1. Betty and Guy Beatty Center for Integrated Research, Inova Health System, 3300 Gallows Road, Falls Church, VA, 22042, USA. aweinst2@gmu.edu. 2. Center for the Study of Chronic Illness and Disability, College of Health and Human Services, George Mason University, Fairfax, VA, USA. aweinst2@gmu.edu. 3. Department of Global and Community Health, College of Health and Human Services, George Mason University, Fairfax, VA, USA. aweinst2@gmu.edu. 4. Department of Statistics, Volgenau School of Engineering, George Mason University, Fairfax, VA, USA. 5. Department of Global and Community Health, College of Health and Human Services, George Mason University, Fairfax, VA, USA. 6. Betty and Guy Beatty Center for Integrated Research, Inova Health System, 3300 Gallows Road, Falls Church, VA, 22042, USA. 7. Center for the Study of Chronic Illness and Disability, College of Health and Human Services, George Mason University, Fairfax, VA, USA. 8. Center for Liver Diseases, Department of Medicine, Inova Fairfax Hospital, Falls Church, VA, USA.
Abstract
PURPOSE: The purpose of this investigation was to determine if it was possible to separate fatigue self-reports into two distinct types of fatigue symptom clusters in research subjects with chronic liver disease (CLD). It was hypothesized that when items from the Medical Outcomes Study Short-Form (SF-36v2) are combined with items from the Fatigue Severity Scale (FSS), these distinct factors will emerge. METHODS: Confirmatory and exploratory factor analyses from data collected in a prospective, natural history study of CLD patients were conducted. Items were selected from the SF-36v2 and the FSS for entry into the factor analyses. In order to establish convergent and discriminant validity, derived factor scores were correlated with subscale scores of the Human Activity Profile (HAP), Mental Component Score (MCS) from the SF-36v2, and the Emotional Functioning Subscale of the Chronic Liver Disease Questionnaire (CLDQ-EF). RESULTS: 106 participants with CLD were included (50% female; age: 51 ± 10). Two factors were identified. The factors included one that clustered around questions addressing fatigue related to physical activity (peripheral fatigue) and the other to the questions addressing generalized fatigue that did not require physical tasks to produce the fatigue (central fatigue). The standardized factor loadings of all items were greater than 0.6 on their underlying constructs. Moreover, all factor loadings are significant at p < 0.01. Peripheral fatigue was related to HAP (r = 0.26, r = 0.24, p < 0.01), as was central fatigue (r = -0.34, r = -0.33, p < 0.01). Central fatigue was related to MCS and CLDQ-EF (r = -0.60; r = -0.63, p < 0.01), whereas peripheral fatigue was not (r = 0.07, p > 0.40). We then tested the original scales to determine if the newly created factors correlated better with the validity measures. The full FSS did not correlate as well as the newly created central fatigue scale, while the original peripheral fatigue scale (the SF-36v2 physical functioning) was more related to HAP than the newly created scale. CONCLUSIONS: In individuals with CLD, two separate factors pertaining to fatigue were identified. This recognition of the multifaceted nature of fatigue may help increase the specificity of self-reports of fatigue and lead to treatments that can specifically address the underlying factors contributing to fatigue.
PURPOSE: The purpose of this investigation was to determine if it was possible to separate fatigue self-reports into two distinct types of fatigue symptom clusters in research subjects with chronic liver disease (CLD). It was hypothesized that when items from the Medical Outcomes Study Short-Form (SF-36v2) are combined with items from the Fatigue Severity Scale (FSS), these distinct factors will emerge. METHODS: Confirmatory and exploratory factor analyses from data collected in a prospective, natural history study of CLD patients were conducted. Items were selected from the SF-36v2 and the FSS for entry into the factor analyses. In order to establish convergent and discriminant validity, derived factor scores were correlated with subscale scores of the Human Activity Profile (HAP), Mental Component Score (MCS) from the SF-36v2, and the Emotional Functioning Subscale of the Chronic Liver Disease Questionnaire (CLDQ-EF). RESULTS: 106 participants with CLD were included (50% female; age: 51 ± 10). Two factors were identified. The factors included one that clustered around questions addressing fatigue related to physical activity (peripheral fatigue) and the other to the questions addressing generalized fatigue that did not require physical tasks to produce the fatigue (central fatigue). The standardized factor loadings of all items were greater than 0.6 on their underlying constructs. Moreover, all factor loadings are significant at p < 0.01. Peripheral fatigue was related to HAP (r = 0.26, r = 0.24, p < 0.01), as was central fatigue (r = -0.34, r = -0.33, p < 0.01). Central fatigue was related to MCS and CLDQ-EF (r = -0.60; r = -0.63, p < 0.01), whereas peripheral fatigue was not (r = 0.07, p > 0.40). We then tested the original scales to determine if the newly created factors correlated better with the validity measures. The full FSS did not correlate as well as the newly created central fatigue scale, while the original peripheral fatigue scale (the SF-36v2 physical functioning) was more related to HAP than the newly created scale. CONCLUSIONS: In individuals with CLD, two separate factors pertaining to fatigue were identified. This recognition of the multifaceted nature of fatigue may help increase the specificity of self-reports of fatigue and lead to treatments that can specifically address the underlying factors contributing to fatigue.
Authors: Daniel S J Costa; Rebecca Mercieca-Bebber; Claudia Rutherford; Margaret-Ann Tait; Madeleine T King Journal: Qual Life Res Date: 2021-04-01 Impact factor: 4.147