Juliane Menting1, Cees J Tack2, Gijs Bleijenberg1, Rogier Donders3, Hal A Droogleever Fortuyn4, Jaap Fransen5, Martine M Goedendorp6, Joke S Kalkman7, Riet Strik-Albers2, Nens van Alfen8, Sieberen P van der Werf9, Nicol C Voermans8, Baziel G van Engelen8, Hans Knoop1. 1. Expert Center for Chronic Fatigue, Department of Medical Psychology, Amsterdam Public Health Research Institute, VU University Medical Center. 2. Department of Internal Medicine, Radboud University Medical Center. 3. Department of Health Evidence, Radboud University Medical Center. 4. Department of Psychiatry, Radboud University Medical Center. 5. Department of Rheumatology, Radboud University Medical Center. 6. Department of Health Psychology, University Medical Center Groningen. 7. Department of Medical Psychology, Radboud University Medical Center. 8. Neuromuscular Centre Nijmegen, Department of Neurology, Donders Center for Neuroscience, Radboud University Medical Center. 9. Brain and Cognition, Department of Psychology, University of Amsterdam.
Abstract
OBJECTIVE: Severe fatigue is highly prevalent in various chronic diseases. Disease-specific fatigue models have been developed, but it is possible that fatigue-related factors in these models are similar across diseases. The purpose of the current study was to determine the amount of variance in fatigue severity explained by: (a) the specific disease, (b) factors associated with fatigue across different chronic diseases (transdiagnostic factors), and (c) the interactions between these factors and specific diseases. METHOD: Data from 15 studies that included 1696 patients with common chronic diseases and disorders that cause long-term disabilities were analyzed. Linear regression analysis with the generalized least-squares technique was used to determine fatigue-related factors associated with fatigue severity, that is, demographic variables, health-related symptoms and psychosocial variables. RESULTS: Type of chronic disease explained 11% of the variance noted in fatigue severity. The explained variance increased to 55% when the transdiagnostic factors were added to the model. These factors were female sex, age, motivational and concentration problems, pain, sleep disturbances, physical functioning, reduced activity and lower self-efficacy concerning fatigue. The predicted variance increased to 61% when interaction terms were added. Analysis of the interactions revealed that the relationship between fatigue severity and relevant predictors mainly differed in strength, not in direction. CONCLUSIONS: Fatigue severity can largely be explained by transdiagnostic factors; the associations vary between chronic diseases in strength and significance. This suggests that severely fatigued patients with different chronic diseases can probably benefit from a transdiagnostic fatigue-approach which focuses on individual patient needs rather than a specific disease. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
OBJECTIVE: Severe fatigue is highly prevalent in various chronic diseases. Disease-specific fatigue models have been developed, but it is possible that fatigue-related factors in these models are similar across diseases. The purpose of the current study was to determine the amount of variance in fatigue severity explained by: (a) the specific disease, (b) factors associated with fatigue across different chronic diseases (transdiagnostic factors), and (c) the interactions between these factors and specific diseases. METHOD: Data from 15 studies that included 1696 patients with common chronic diseases and disorders that cause long-term disabilities were analyzed. Linear regression analysis with the generalized least-squares technique was used to determine fatigue-related factors associated with fatigue severity, that is, demographic variables, health-related symptoms and psychosocial variables. RESULTS: Type of chronic disease explained 11% of the variance noted in fatigue severity. The explained variance increased to 55% when the transdiagnostic factors were added to the model. These factors were female sex, age, motivational and concentration problems, pain, sleep disturbances, physical functioning, reduced activity and lower self-efficacy concerning fatigue. The predicted variance increased to 61% when interaction terms were added. Analysis of the interactions revealed that the relationship between fatigue severity and relevant predictors mainly differed in strength, not in direction. CONCLUSIONS:Fatigue severity can largely be explained by transdiagnostic factors; the associations vary between chronic diseases in strength and significance. This suggests that severely fatiguedpatients with different chronic diseases can probably benefit from a transdiagnostic fatigue-approach which focuses on individual patient needs rather than a specific disease. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Authors: Kim F E van de Loo; Nander T van Zeijl; Mirian C H Janssen; Christianne M Verhaak; José A E Custers Journal: Orphanet J Rare Dis Date: 2022-07-15 Impact factor: 4.303
Authors: Kelly A Hyland; Ashley M Nelson; Sarah L Eisel; Aasha I Hoogland; Javier Ibarz-Pinilla; Kendra Sweet; Paul B Jacobsen; Hans Knoop; Heather S L Jim Journal: Ann Behav Med Date: 2022-02-11
Authors: Merel M Nap-van der Vlist; Jan Houtveen; Geertje W Dalmeijer; Martha A Grootenhuis; Cornelis K van der Ent; Martine van Grotel; Joost F Swart; Joris M van Montfrans; Elise M van de Putte; Sanne L Nijhof Journal: Internet Interv Date: 2021-04-20
Authors: Ingrid Banovic; Louise Montreuil; Marie Derrey-Bunel; Fabrizio Scrima; Guillaume Savoye; Laurent Beaugerie; Marie-Claire Gay Journal: Front Psychol Date: 2020-04-30