Unraveling Fatigue in Hemodialysis Patients: Comparing Retrospective Reports to Real-Time Assessments With an mHealth Experienced Sampling Method
| Autor: | Caroline M. van Heugten, Frank Stifft, Astrid D.H. Brys, Maurizio Bossola, Bert Lenaert, Giovanni Gambaro |
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| Přispěvatelé: | RS: FPN NPPP I, Section Neuropsychology, Psychiatrie & Neuropsychologie, RS: MHeNs - R1 - Cognitive Neuropsychiatry and Clinical Neuroscience |
| Rok vydání: | 2020 |
| Předmět: |
Experience sampling method
medicine.medical_specialty measurement instrument medicine.medical_treatment Ecological Momentary Assessment Psychological intervention Context (language use) HOSPITAL ANXIETY Hospital Anxiety and Depression Scale 03 medical and health sciences 0302 clinical medicine ESM depressive symptoms Renal Dialysis DIALYSIS Medicine Humans 030212 general & internal medicine mHealth General Nursing SCALE Fatigue Retrospective Studies hemodialysis business.industry MEMORY ASSOCIATION RECALL DEPRESSION Telemedicine Anesthesiology and Pain Medicine Mood 030220 oncology & carcinogenesis Etiology Physical therapy PATTERNS Neurology (clinical) Hemodialysis business |
| Zdroj: | Journal of Pain and Symptom Management, 60(6), 1100-1108.e2. Elsevier Science |
| ISSN: | 1873-6513 0885-3924 |
| Popis: | Context Fatigue 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. Objectives We 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). Methods Forty 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. Results Results 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. Conclusion Retrospective 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. |
| Databáze: | OpenAIRE |
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