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J Pain Symptom Manage · Dec 2020
Unravelling fatigue in hemodialysis patients: comparing retrospective reports to real-time assessments with an mHealth Experienced Sampling Method.
- Astrid D H Brys, Frank Stifft, Caroline M Van Heugten, Maurizio Bossola, Giovanni Gambaro, and Bert Lenaert.
- Faculty of Psychology and Neuroscience, Department of Neuropsychology and Psychopharmacology, Maastricht University, Maastricht, The Netherlands; Division of Nephrology, Department of Internal Medicine, Zuyderland Medical Centre, Sittard-Geleen, The Netherlands; Divisione di Nefrologia, Fondazione Policlinico Universitario A. Gemelli IRCCS, Roma, Italy; Università Cattolica del Sacro Cuore, Roma, Italy. Electronic address: astrid.brys@unicatt.it.
- J Pain Symptom Manage. 2020 Dec 1; 60 (6): 1100-1108.e2.
ContextFatigue is prevalent among hemodialysis (HD) patients and associated with depressive mood. To advance our understanding of its etiology and develop appropriate treatments, reliable measurement instruments are needed. However, conventional fatigue and mood questionnaires are prone to bias because of their retrospective nature and may misrepresent or overestimate actual symptom experience (i.e., the so-called memory-experience gap). Experience sampling methodology (ESM) overcomes this limitation through repeated real-time assessments in patients' natural environment, thereby providing reliable and ecologically valid data.ObjectivesWe investigated to what extent retrospective symptom reporting accurately represents real-time experiences of fatigue and mood in HD patients using an ESM mobile Health application (PsyMate™; smartHealth GmbH, Luxembourg).MethodsForty HD patients used the PsyMate for one week to assess real-time fatigue and mood. In addition, they retrospectively evaluated their symptom experience completing end-of-day and end-of-week questionnaires as well as the conventional Fatigue Severity Scale and Hospital Anxiety and Depression Scale.ResultsResults of real-time observations (N = 1777) showed that fatigue and mood varied between and within individuals. Retrospective end-of-week fatigue evaluation was significantly higher than the average real-time fatigue score; t(38) = 3.54, P = 0.001, and d = 0.57. Fatigue Severity Scale and Hospital Anxiety and Depression Scale correlated moderately to strong with the average ESM score for fatigue and mood: r = 0.66 and r = 0.77, respectively.ConclusionRetrospective fatigue assessment may lead to overestimation of real-time symptom experience. ESM provides detailed insight and personalized information about symptom experiences, which may be crucial for the design of more targeted and personalized interventions for fatigue and mood problems in HD patients.Copyright © 2020 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.
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