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Poststroke Fatigue and Daily Activity Patterns During Outpatient Rehabilitation: An Experience Sampling Method Study

  • Author Footnotes
    ∗ Lenaert and Neijmeijer contributed equally to this work.
    Bert Lenaert
    Correspondence
    Corresponding author Bert Lenaert, PhD, Limburg Brain Injury Center, Maastricht University, Department of Neuropsychology and Psychopharmacology, Faculty of Psychology and Neuroscience, PO Box 616, Universiteitssingel 40, Box 34, 6200 MD Maastricht, the Netherlands.
    Footnotes
    ∗ Lenaert and Neijmeijer contributed equally to this work.
    Affiliations
    Limburg Brain Injury Center, Maastricht, the Netherlands

    School for Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands

    Department of Neuropsychology and Psychopharmacology, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands

    Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, the Netherlands
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  • Author Footnotes
    ∗ Lenaert and Neijmeijer contributed equally to this work.
    Mathea Neijmeijer
    Footnotes
    ∗ Lenaert and Neijmeijer contributed equally to this work.
    Affiliations
    Department of Neuropsychology and Psychopharmacology, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands
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  • Nadine van Kampen
    Affiliations
    Adelante Rehabilitation Center, Hoensbroek, the Netherlands
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  • Caroline van Heugten
    Affiliations
    Limburg Brain Injury Center, Maastricht, the Netherlands

    School for Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands

    Department of Neuropsychology and Psychopharmacology, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands

    Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, the Netherlands
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  • Rudolf Ponds
    Affiliations
    Limburg Brain Injury Center, Maastricht, the Netherlands

    School for Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands

    Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, the Netherlands

    Adelante Rehabilitation Center, Hoensbroek, the Netherlands
    Search for articles by this author
  • Author Footnotes
    ∗ Lenaert and Neijmeijer contributed equally to this work.
Published:January 27, 2020DOI:https://doi.org/10.1016/j.apmr.2019.12.014

      Abstract

      Objective

      To advance our understanding of poststroke fatigue by investigating its momentary and time-lagged relationship with daily activities.

      Design

      Longitudinal observational study using the experience sampling method (ESM).

      Setting

      Outpatient rehabilitation care.

      Participants

      Thirty individuals with stroke (N=30).

      Interventions

      Not applicable.

      Main Outcome Measures

      ESM is a structured diary method that allows assessing real-time symptoms, behavior, and environment characteristics in the flow of daily life, thereby capturing moment-to-moment variations in fatigue and related factors. Using a mobile application, individuals with stroke were followed during 6 consecutive days, and were prompted at 10 random moments daily to fill in a digital questionnaire about their momentary fatigue and current activity: type of activity, perceived effort and enjoyment, and physical activity levels.

      Results

      Based on all completed digital questionnaires (N=1013), multilevel regression analyses showed that fatigue was significantly associated with type of activity and that fatigue was higher when participants had engaged in physical activity. Fatigue was also higher during activities perceived as more effortful and during less enjoyable activities. Time-lagged analyses showed that fatigue was also predicted by physical activity and perceived effort earlier during the day. Importantly, the relationship between these daily activity characteristics and fatigue differed substantially across individuals.

      Conclusions

      This study illustrates the need for ESM to design personalized rehabilitation programs and to capture fatigue and other patient-reported outcomes in daily life.

      Keywords

      List of abbreviations:

      ESM (experience sampling method), FSS (Fatigue Severity Scale), HADS (Hospital Depression Anxiety Scale), PSF (poststroke fatigue)
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      References

        • World Health Organization
        Global health estimates (GHE).
        (Available at:)
        • Cumming T.B.
        • Packer M.
        • Kramer S.F.
        • English C.
        The prevalence of fatigue after stroke: a systematic review and meta-analysis.
        Int J Stroke. 2016; 11: 968-977
        • Choi-Kwon S.
        • Kim J.S.
        Reviews poststroke fatigue: an emerging, critical issue in stroke medicine.
        Int J Stroke. 2011; 6: 328-336
        • Glader E.
        • Stegmayr B.
        • Asplund K.
        Poststroke fatigue: a 2-year follow-up study of stroke patients in Sweden.
        Stroke. 2002; 33: 1327-1333
        • Lerdal A.
        • Bakken L.N.
        • Kouwenhoven S.E.
        • et al.
        Poststroke fatigue: a review.
        J Pain Symptom Manage. 2009; 38: 928-949
        • Kutlubaev M.A.
        • Duncan F.H.
        • Mead G.E.
        Biological correlates of post-stroke fatigue: a systematic review.
        Acta Neurol Scand. 2012; 125: 219-227
        • Chaudhuri A.
        • Behan P.O.
        Fatigue in neurological disorders.
        Lancet. 2004; 363: 978-988
        • Stephan K.E.
        • Manjaly Z.M.
        • Mathys C.D.
        • et al.
        Allostatic self-efficacy: a metacognitive theory of dyshomeostasis-induced fatigue and depression.
        Front Hum Neurosci. 2016; 10: 550
        • Kuppuswamy A.
        The fatigue conundrum.
        Brain. 2017; 140: 2240-2245
        • de Groot M.H.
        • Phillips S.J.
        • Eskes G.A.
        Fatigue associated with stroke and other neurologic conditions: implications for stroke rehabilitation.
        Arch Phys Med Rehabil. 2003; 84: 1714-1720
        • Snaphaan L.
        • van der Werf S.
        • de Leeuw F.E.
        Time course and risk factors of post-stroke fatigue: a prospective cohort study.
        Eur J Neurol. 2011; 18: 611-617
        • Wu D.
        • Wang L.
        • Teng W.
        • Huang K.
        • Shang X.
        Correlation of fatigue during the acute stage of stroke with serum uric acid and glucose levels, depression, and disability.
        Eur Neurol. 2014; 72: 223-227
        • Michael K.M.
        • Allen J.K.
        • Macko R.F.
        Fatigue after stroke: relationship to mobility, fitness, ambulatory activity, social support, and falls efficacy.
        Rehabil Nurs. 2006; 31: 210-217
        • Jean A.M.
        • Swendsen J.D.
        • Sibon I.
        • Fehér K.
        • Husky M.
        Daily life behaviors and depression risk following stroke: a preliminary study using ecological momentary assessment.
        J Geriatr Psychiatry Neurol. 2013; 26: 138-143
        • Powell D.J.
        • Liossi C.
        • Schlotz W.
        • Moss-Morris R.
        Tracking daily fatigue fluctuations in multiple sclerosis: ecological momentary assessment provides unique insights.
        J Behav Med. 2017; 40: 772-783
        • Van den Bergh O.
        • Walentynowicz M.
        Accuracy and bias in retrospective symptom reporting.
        Curr Opin Psychiatry. 2016; 29: 302-308
        • Hektner J.M.
        • Schmidt J.A.
        • Csikszentmihalyi M.
        Experience sampling method: measuring the quality of everyday life.
        Sage Publications Inc, Thousand Oaks2007
        • Johnson E.I.
        • Sibon I.
        • Renou P.
        • Rouanet F.
        • Allard M.
        • Swendsen J.
        Feasibility and validity of computerized ambulatory monitoring in stroke patients.
        Neurology. 2009; 73: 1579-1583
        • Juengst S.B.
        • Graham K.M.
        • Pulantara I.W.
        • et al.
        Pilot feasibility of an mHealth system for conducting ecological momentary assessment of mood-related symptoms following traumatic brain injury.
        Brain Inj. 2015; 29: 1351-1361
        • Lenaert B.
        • Colombi M.
        • van Heugten C.
        • Rasquin S.
        • Kasanova Z.
        • Ponds R.
        Exploring the feasibility and usability of the experience sampling method to examine the daily lives of patients with acquired brain injury.
        Neuropsychol Rehabil. 2019; 29: 754-766
        • Lewandowski L.
        • Rieger B.
        • Smyth J.
        • Perry L.
        • Gathje R.
        Measuring post-concussion symptoms in adolescents: feasibility of ecological momentary assessment.
        Arch Clin Neuropsychol. 2009; 24: 791-796
        • Mazure C.M.
        • Weinberger H.
        • Pittman B.
        • Sibon I.
        • Swendsen J.
        Gender and stress in predicting depressive symptoms following stroke.
        Cerebrovasc Dis. 2014; 38: 240-246
        • Sibon I.
        • Lassalle-Lagadec S.
        • Renou P.
        • Swendsen J.
        Evolution of depression symptoms following stroke: a prospective study using computerized ambulatory monitoring.
        Cerebrovasc Dis. 2012; 33: 280-285
        • van de Port I.G.
        • Kwakkel G.
        • Schepers V.P.
        • Heinemans C.T.
        • Lindeman E.
        Is fatigue an independent factor associated with activities of daily living, instrumental activities of daily living and health-related quality of life in chronic stroke?.
        Cerebrovasc Dis. 2007; 23: 40-45
        • Wichers M.
        • Peeters F.
        • Rutten B.P.
        • et al.
        A time-lagged momentary assessment study on daily life physical activity and affect.
        Heal Psychol. 2012; 31: 135-144
        • Krupp L.B.
        • Larocca N.G.
        • Muir-Nash J.
        • Steinberg A.D.
        The Fatigue Severity Scale. Application to patients with multiple sclerosis and systemic lupus erythematosus.
        Arch Neurol. 1989; 46: 1121-1123
        • Zigmond A.S.
        • Snaith R.P.
        The Hospital Anxiety and Depression Scale.
        Acta Psychiatr Scandinivica. 1983; 67: 361-370
        • Aben I.
        • Verhey F.
        • Lousberg R.
        • Lodder J.
        • Honig A.
        Validity of the Beck Depression Inventory, Hospital Anxiety and Depression Scale, SCL-90, and Hamilton Depression Rating Scale as screening instruments for depression in stroke patients.
        Psychosomatics. 2002; 43: 386-393
        • Lewis S.J.
        • Barugh A.J.
        • Greig C.A.
        • et al.
        Is fatigue after stroke associated with physical deconditioning? A cross-sectional study in ambulatory stroke survivors.
        Arch Phys Med Rehabil. 2011; 92: 295-298
        • Kramer I.
        • Simons C.J.
        • Hartmann J.A.
        • et al.
        A therapeutic application of the experience sampling method in the treatment of depression: a randomized controlled trial.
        World Psychiatry. 2014; 13: 68-77