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M. Heine (Martin), van den Akker, L.E. (Lizanne Eva), L.J.M. Blikman (Lyan), T. Hoekstra (Trynke), E. Van Munster (Erik), Verschuren, O. (Olaf), Visser-Meily, A. (Anne), G. Kwakkel (Gert), V. de Groot (Vincent), H. Beckerman (Heleen), et al. A. Malekzadeh (Arjan), van den Akker, L.E., M. Looijmans (M.), Sanches, S.A., J. Dekker (Joost), E.H. Collette (E.), B.W. Van Oosten (Bob W.), C.E. Teunissen (Charlotte), M.A. Blankenstein (Marinus), L.M.T. Eijssen (Lars), M. Rietberg (M.), Heine, M., O. Verschuren (Olaf), Kwakkel, G., Visser-Meily, J.M.A., I.G.L. van de Port (I. G L), E. Lindeman (Eline), L.J.M. Blikman (Lyan), J. van Meeteren (Jetty), J.B.J. Bussmann (Hans), H.J. Stam (Henk), R.Q. Hintzen (Rogier), H.G.A. Hacking (H. G A), E. Hoogervorst (Erwin), S.T.F.M. Frequin (S. T F M), Knoop, H., de Jong, B.A., G. Bleijenberg (G.), F.A.J. de Laat (F. A J), Verhulsdonck, M.C., van Munster, E.T.L. (E.Th.L.), Oosterwijk, C.J. and G.J. Aarts (G.)

2016-11-01

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

Publication

Publication

Archives of Physical Medicine and Rehabilitation , Volume 97 - Issue 11 p. 1887- 1894

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.

Additional Metadata
Keywords Fatigue, Multiple Sclerosis, Rehabilitation, Surveys and questionnaires
Persistent URL doi.org/10.1016/j.apmr.2016.04.019, hdl.handle.net/1765/96714
Journal Archives of Physical Medicine and Rehabilitation
Organisation Department of Rehabilitation Medicine
Citation
Heine, M., van den Akker, L.E. (Lizanne Eva), Blikman, L., Hoekstra, T., Van Munster, E., Verschuren, O. (Olaf), … Aarts, G. (2016). Real-Time Assessment of Fatigue in Patients With Multiple Sclerosis: How Does It Relate to Commonly Used Self-Report Fatigue Questionnaires?. Archives of Physical Medicine and Rehabilitation, 97(11), 1887–1894. doi:10.1016/j.apmr.2016.04.019


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