Unraveling Fatigue in Hemodialysis Patients: comparing retrospective reports to real-time assessments with an mHealth Experienced Sampling Method

Astrid DH. Brys*, Frank Stifft, Caroline M. Van Heugten, Maurizio Bossola, Giovanni Gambaro, Bert Lenaert

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

106 Downloads (Pure)


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 due to 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 (PsyMateTM).

METHODS: Forty HD patients used the PsyMateTM for one week to assess real-time fatigue and mood. Additionally, they retrospectively evaluated their symptom experience completing end-of-day and end-of-week questionnaires; and the conventional Fatigue Severity Scale (FSS) and Hospital Anxiety and Depression Scale (HADS).

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, d=0.57. FSS and HADS 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.

Original languageEnglish
Pages (from-to)1100-1108.e2
Number of pages11
JournalJournal of Pain and Symptom Management
Issue number6
Early online date6 Jul 2020
Publication statusPublished - Dec 2020


  • mHealth
  • ESM
  • measurement instrument
  • fatigue
  • depressive symptoms
  • hemodialysis

Cite this