Real-Time Assessment of Fatigue in Patients With Multiple Sclerosis: How Does It Relate to Commonly Used Self-Report Fatigue Questionnaires?

Abstract

OBJECTIVES: (1) To assess real-time patterns of fatigue; (2) to assess the association between a real-time fatigue score and 3 commonly used questionnaires (Checklist Individual Strength [CIS] fatigue subscale, Modified Fatigue Impact Scale (MFIS), and Fatigue Severity Scale [FSS]); and (3) to establish factors that confound the association between the real-time fatigue score and the conventional fatigue questionnaires in patients with multiple sclerosis (MS). DESIGN: Cross-sectional study. SETTING: MS-specialized outpatient facility. PARTICIPANTS: Ambulant patients with MS (N=165) experiencing severe self-reported fatigue. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: A real-time fatigue score was assessed by sending participants 4 text messages on a particular day (How fatigued do you feel at this moment?; score range, 0-10). Latent class growth mixed modeling was used to determine diurnal patterns of fatigue. Regression analyses were used to assess the association between the mean real-time fatigue score and the CIS fatigue subscale, MFIS, and FSS. Significant associations were tested for candidate confounders (eg, disease severity, work status, sleepiness). RESULTS: Four significantly different fatigue profiles were identified by the real-time fatigue score, namely a stable high (n=79), increasing (n=57), stable low (n=16), and decreasing (n=13). The conventional questionnaires correlated poorly (r<.300) with the real-time fatigue score. The Epworth Sleepiness Scale significantly reduced the regression coefficient between the real-time fatigue score and conventional questionnaires, ranging from 15.4% to 35%. CONCLUSIONS: Perceived fatigue showed 4 different diurnal patterns in patients with MS. Severity of sleepiness is an important confounder to take into account in the assessment of fatigue.