- •Most patients with multiple sclerosis experience high levels of fatigue throughout the day, or low levels of fatigue in the morning and high levels of fatigue in the afternoon; a minority of patients show high levels of fatigue in the morning and low levels of fatigue in the afternoon, or low levels of fatigue throughout the day.
- •There is a poor agreement between the level of fatigue assessed in real time and fatigue assessed using conventional recall fatigue questionnaires.
- •An important factor that may explain the poor agreement is the feeling of sleepiness; this may indicate that in real time, the level of fatigue is associated with the feeling of sleepiness, and not captured within the conventional recall fatigue questionnaires.
(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).
MS-specialized outpatient facility.
Ambulant patients with MS (N=165) experiencing severe self-reported fatigue.
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).
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%.
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.
List of abbreviations:CIS (Checklist Individual Strength), ESS (Epworth Sleepiness Scale), FSS (Fatigue Severity Scale), MFIS (Modified Fatigue Impact Scale), MS (multiple sclerosis), TREFAMS-ACE (Treating Fatigue in Multiple Sclerosis – Aerobic training, Cognitive behavioral therapy, Energy conservation management)
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- Fatigue and multiple sclerosis: evidence-based management strategies for fatigue in multiple sclerosis.Paralyzed Veterans of America, Washington (DC)1998
- Atlas of multiple sclerosis 2013: a growing global problem with widespread inequity.Neurology. 2014; 83: 1022-1024
- Exercise therapy for fatigue in multiple sclerosis.Cochrane Database Syst Rev. 2015; 9: CD009956
- Effectiveness of energy conservation treatment in reducing fatigue in multiple sclerosis: a systematic review and meta-analysis.Arch Phys Med Rehabil. 2013; 94: 1360-1376
- Novel method for measurement of fatigue in multiple sclerosis: Real-Time Digital Fatigue Score.J Rehabil Res Dev. 2010; 47: 477-484
- Ecological momentary assessment.Annu Rev Clin Psychol. 2008; 4: 1-32
- Variability of momentary pain predicts recall of weekly pain: a consequence of the peak (or salience) memory heuristic.Pers Soc Psychol Bull. 2005; 31: 1340-1346
- A medical definition of fatigue in multiple sclerosis.QJM. 2008; 101: 49-60
- A longitudinal study of variations in and predictors of fatigue in multiple sclerosis.J Neurol Neurosurg Psychiatry. 2008; 79: 454-457
- Changes in gait and fatigue from morning to afternoon in people with multiple sclerosis.J Neurol Neurosurg Psychiatry. 2002; 72: 361-365
- Self-report fatigue questionnaires in multiple sclerosis, Parkinson's disease and stroke: a systematic review of measurement properties.Qual Life Res. 2012; 21: 925-944
- Measuring fatigue in patients with multiple sclerosis: reproducibility, responsiveness and concurrent validity of three Dutch self-report questionnaires.Disabil Rehabil. 2010; 32: 1870-1876
- The effectiveness of aerobic training, cognitive behavioural therapy, and energy conservation management in treating MS-related fatigue: the design of the TREFAMS-ACE programme.Trials. 2013; 14: 250
- The measurement of fatigue in patients with multiple sclerosis. A multidimensional comparison with patients with chronic fatigue syndrome and healthy subjects.Arch Neurol. 1996; 53: 642-649
- The fatigue severity scale. Application to patients with multiple sclerosis and systemic lupus erythematosus.Arch Neurol. 1989; 46: 1121-1123
- Assessing fatigue in multiple sclerosis: Dutch modified fatigue impact scale.Acta Neurol Belg. 2003; 103: 185-191
- Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS).Neurology. 1983; 33: 1444-1452
- Validation of the Hospital Anxiety and Depression Scale for use with multiple sclerosis patients.Mult Scler. 2009; 15: 1518-1524
- A new method for measuring daytime sleepiness: the Epworth sleepiness scale.Sleep. 1991; 14: 540-545
- The self-efficacy scale: construction and validation.Psychol Rep. 1982; 51: 663-671
- The physical activity scale for individuals with physical disabilities: development and evaluation.Arch Phys Med Rehabil. 2002; 83: 193-200
- Integrating person-centered and variable-centered analyses: growth mixture modeling with latent trajectory classes.Alcohol Clin Exp Res. 2000; 24: 882-891
- An introduction to latent variable mixture modeling (part 1): overview and cross-sectional latent class and latent profile analyses.J Pediatr Psychol. 2014; 39: 174-187
- An introduction to latent variable mixture modeling (part 2): longitudinal latent class growth analysis and growth mixture models.J Pediatr Psychol. 2014; 39: 188-203
- Deciding on the number of classes in latent class analysis and growth mixture modeling: a Monte Carlo simulation study.Struct Equ Model. 2007; 14: 535-569
- Statistical power analysis for the behavioral sciences.Academic Press, Inc, New York1988
- Community ambulation in patients with chronic stroke: how is it related to gait speed?.J Rehabil Med. 2008; 40: 23-27
- Fatigue, sleepiness, and physical activity in patients with multiple sclerosis.J Neurol. 2011; 258: 74-79
- Fatigue, depression and sleep disturbances in Iranian patients with multiple sclerosis.Acta Med Iran. 2012; 50: 244-249
- The underdiagnosis of sleep disorders in patients with multiple sclerosis.J Clin Sleep Med. 2014; 10: 1025-1031
- Obstructive sleep apnea is associated with fatigue in multiple sclerosis.Mult Scler. 2012; 18: 1159-1169
- Association between OSA and severe fatigue in patients with multiple sclerosis (MS).J Clin Sleep Med. 2014; 10: 707
- Obstructive sleep apnea and fatigue in patients with multiple sclerosis.J Clin Sleep Med. 2014; 10: 155-162
Published online: May 24, 2016
The TREFAMS-ACE study is supported by the Fonds NutsOhra (ZonMw grant no. 89000005).
The participants in the present study were a convenience sample of participants of the following Clinical Trial Registration Nos.: ISRCTN69520623, ISRCTN58583714, and ISRCTN82353628.
© 2016 by the American Congress of Rehabilitation Medicine