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Moderators of Treatment Outcomes After Telehealth Self-Management and Education in Adults With Multiple Sclerosis: A Secondary Analysis of a Randomized Controlled Trial

  • Dawn M. Ehde
    Correspondence
    Corresponding author Dawn M. Ehde, PhD, Department of Rehabilitation Medicine, University of Washington, Box 359612, Seattle, WA 98104.
    Affiliations
    Department of Rehabilitation Medicine, School of Medicine, University of Washington, Seattle, Washington
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  • Anne Arewasikporn
    Affiliations
    Department of Rehabilitation Medicine, School of Medicine, University of Washington, Seattle, Washington

    Multiple Sclerosis Center of Excellence – West, VA Puget Sound Health Care System, Seattle Division, Seattle, Washington
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  • Kevin N. Alschuler
    Affiliations
    Department of Rehabilitation Medicine, School of Medicine, University of Washington, Seattle, Washington

    Department of Neurology, School of Medicine, University of Washington, Seattle, Washington
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  • Abbey J. Hughes
    Affiliations
    Department of Physical Medicine and Rehabilitation, Johns Hopkins University School of Medicine, Baltimore, Maryland
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  • Aaron P. Turner
    Affiliations
    Department of Rehabilitation Medicine, School of Medicine, University of Washington, Seattle, Washington

    Multiple Sclerosis Center of Excellence – West, VA Puget Sound Health Care System, Seattle Division, Seattle, Washington
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Published:January 11, 2018DOI:https://doi.org/10.1016/j.apmr.2017.12.012

      Abstract

      Objective

      To examine moderators of treatment effects in a randomized controlled trial comparing a telehealth self-management intervention with a telehealth multiple sclerosis (MS) education intervention for fatigue, pain, and mood in adults with MS.

      Design

      Secondary analysis of a single-blind randomized controlled trial.

      Setting

      Community.

      Participants

      Adults with MS and chronic fatigue, chronic pain, and/or moderate depressive symptoms (N=163) recruited from across the United States.

      Interventions

      Two 8-week, telephone-delivered symptom interventions delivered 1:1: a self-management intervention (n=75) and an MS education intervention (n=88).

      Main Outcome Measures

      Outcome measures were fatigue impact pain interference, and depressive symptom severity assessed at baseline and posttreatment. Potential moderators of treatment effects assessed at baseline were demographics (age, sex, and education), clinical characteristics (disease duration and disability severity), symptoms (perceived cognitive impairment and pain intensity), baseline levels of the treatment outcomes (pain interference, fatigue impact and depressive symptom severity), and cognitive behavioral factors (pain catastrophizing, fatigue catastrophizing, self-efficacy, and patient activation).

      Results

      Moderation analyses found significant moderation for fatigue impact but not for pain intensity or depressive symptom severity. Baseline patient activation interacted with treatment group to predict fatigue impact at posttreatment (P=.049). Among participants with high baseline patient activation, the self-management group reported significantly less fatigue at posttreatment than the education group. No other variables moderated the study outcomes.

      Conclusions

      At the group level, participants responded to both interventions, regardless of disease characteristics, demographics, symptom levels, and cognitive behavioral factors. Self-management and education are both potentially beneficial symptom treatments that may be recommended to individuals with MS and chronic pain, fatigue, and/or depressive symptoms.

      Keywords

      List of abbreviations:

      BPI (Brief Pain Inventory), MFIS (Modified Fatigue Impact Scale), MS (multiple sclerosis), NRS (numerical rating scale), PHQ-9 (Patient Health Questionnaire-9), RCT (randomized controlled trial)
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      References

        • Reynolds R.
        • Dennis S.
        • Hasan I.
        • et al.
        A systematic review of chronic disease management interventions in primary care.
        BMC Fam Pract. 2018; 19: 11
        • Norris S.L.
        • Engelgau M.M.
        • Narayan K.M.
        Effectiveness of self-management training in type 2 diabetes: a systematic review of randomized controlled trials.
        Diabetes Care. 2001; 24: 561-587
        • Wakefield B.J.
        • Boren S.A.
        • Groves P.S.
        • Conn V.S.
        Heart failure care management programs: a review of study interventions and meta-analysis of outcomes.
        J Cardiovasc Nurs. 2013; 28: 8-19
        • Brady T.J.
        • Murphy L.
        • O'Colmain B.J.
        • et al.
        A meta-analysis of health status, health behaviors, and health care utilization outcomes of the chronic disease self-management program.
        Prev Chronic Dis. 2013; 10: 120112
        • Rae-Grant A.D.
        • Turner A.P.
        • Sloan A.
        • Miller D.
        • Hunziker J.
        • Haselkorn J.K.
        Self-management in neurological disorders: systematic review of the literature and potential interventions in multiple sclerosis care.
        J Rehabil Res Dev. 2011; 48: 1087-1100
        • Finlayson M.
        • Preissner K.
        • Cho C.
        • Plow M.
        Randomized trial of a teleconference-delivered fatigue management program for people with multiple sclerosis.
        Mult Scler. 2011; 17: 1130-1140
        • Thomas S.
        • Thomas P.W.
        • Kersten P.
        • et al.
        A pragmatic parallel arm multi-centre randomised controlled trial to assess the effectiveness and cost-effectiveness of a group-based fatigue management programme (FACETS) for people with multiple sclerosis.
        J Neurol Neurosurg Psychiatry. 2013; 84: 1092-1099
        • Bombardier C.H.
        • Ehde D.M.
        • Gibbons L.E.
        • et al.
        Telephone-based physical activity counseling for major depression in people with multiple sclerosis.
        J Consult Clin Psychol. 2013; 81: 89-99
        • Lincoln N.B.
        • Yuill F.
        • Holmes J.
        • et al.
        Evaluation of an adjustment group for people with multiple sclerosis and low mood: a randomized controlled trial.
        Mult Scler. 2011; 17: 1250-1257
        • Ehde D.M.
        • Elzea J.L.
        • Verrall A.M.
        • Gibbons L.E.
        • Smith A.
        • Amtmann D.
        Efficacy of a telephone-delivered self-management intervention for persons with multiple sclerosis: a randomized controlled trial with a one-year follow-up.
        Arch Phys Med Rehabil. 2015; 96: 1945-1958
        • Turner A.P.
        • Hartoonian N.
        • Sloan A.P.
        • et al.
        Improving fatigue and depression in individuals with multiple sclerosis using telephone-administered physical activity counseling.
        J Consult Clin Psychol. 2016; 84: 297-309
        • Finlayson M.
        • Preissner K.
        • Cho C.
        Outcome moderators of a fatigue management program for people with multiple sclerosis.
        Am J Occup Ther. 2012; 66: 187-197
        • Broderick J.E.
        • Keefe F.J.
        • Schneider S.
        • et al.
        Cognitive behavioral therapy for chronic pain is effective, but for whom?.
        Pain. 2016; 157: 2115-2123
        • Pimontel M.A.
        • Rindskopf D.
        • Rutherford B.R.
        • Brown P.J.
        • Roose S.P.
        • Sneed J.R.
        A meta-analysis of executive dysfunction and antidepressant treatment response in late-life depression.
        Am J Geriatr Psychiatry. 2016; 24: 31-41
        • Julian L.J.
        • Mohr D.C.
        Cognitive predictors of response to treatment for depression in multiple sclerosis.
        J Neuropsychiatry Clin Neurosci. 2006; 18: 356-363
        • Day M.A.
        • Ehde D.M.
        • Jensen M.P.
        Psychosocial pain management moderation: the limit, activate, and enhance model.
        J Pain. 2015; 16: 947-960
        • Osborne T.L.
        • Jensen M.P.
        • Ehde D.M.
        • Hanley M.A.
        • Kraft G.
        Psychosocial factors associated with pain intensity, pain-related interference, and psychological functioning in persons with multiple sclerosis and pain.
        Pain. 2007; 127: 52-62
        • Day M.A.
        • Ehde D.M.
        • Ward L.C.
        • et al.
        An empirical investigation of a biopsychosocial model of pain in multiple sclerosis.
        Clin J Pain. 2016; 32: 155-163
        • Kroenke K.
        • Spitzer R.L.
        • Williams J.B.
        The PHQ-9-validity of a brief depression severity measure.
        J Gen Int Med. 2001; 16: 606-613
        • Dworkin R.H.
        • Turk D.C.
        • Farrar J.T.
        • et al.
        Core outcome measures for chronic pain clinical trials: IMMPACT recommendations.
        Pain. 2005; 113: 9-19
        • Tellez N.
        • Rio J.
        • Tintore M.
        • Nos C.
        • Galan I.
        • Montalbal X.
        Does the Modified Fatigue Impact Scale offer a more comprehensive assessment of fatigue in MS?.
        Mult Scler J. 2005; 11: 198-202
        • Callahan C.M.
        • Unverzagt F.W.
        • Hui S.L.
        • Perkins A.J.
        • Hendrie H.C.
        Six-item screener to identify cognitive impairment among potential subjects for clinical research.
        Med Care. 2002; 40: 771-781
        • Amtmann D.
        • Bamer A.M.
        • Noonan V.
        • Lang N.
        • Kim J.
        • Cook K.F.
        Comparison of the psychometric properties of two fatigue scales in multiple sclerosis.
        Rehabil Psychol. 2012; 57: 159-166
        • Rietberg M.B.
        • Van Wegen E.E.
        • Kwakkel G.
        Measuring fatigue in patients with multiple sclerosis: reproducibility, responsiveness and concurrent validity of three Dutch self-report questionnaires.
        Disabil Rehabil. 2010; 32: 1870-1876
        • Osborne T.L.
        • Raichle K.A.
        • Jensen M.P.
        • Ehde D.M.
        • Kraft G.
        The reliability and validity of pain interference measures in persons with multiple sclerosis.
        J Pain Symptom Manage. 2006; 32: 217-229
        • Tan G.
        • Jensen M.P.
        • Thornby J.I.
        • Shanti B.F.
        Validation of the Brief Pain Inventory for chronic nonmalignant pain.
        J Pain. 2004; 5: 133-137
        • Lowe B.
        • Kroenke K.
        • Herzog W.
        • Grafe K.
        Measuring depression outcome with a brief self-report instrument: sensitivity to change of the Patient Health Questionnaire (PHQ-9).
        J Affect Disord. 2004; 81: 61-66
        • Spitzer R.
        • Kroenke K.
        • Williams J.B.
        Validation and utility of a self-report version of PRIME-MD: the PHQ primary care study. Primary Care Evaluation of Mental Disorders. Patient Health Questionnaire.
        JAMA. 1999; 282: 1737-1744
        • Ehde D.M.
        • Nitsch K.P.
        • Smiley J.P.
        Measurement characteristics and clinical utility of the brief pain inventory-short form for individuals with multiple sclerosis.
        Rehabil Psychol. 2015; 60: 365-366
        • Amtmann D.
        • Bamer A.M.
        • Johnson K.L.
        • et al.
        A comparison of multiple patient reported outcome measures in identifying major depressive disorder in people with multiple sclerosis.
        J Psychosom Res. 2015; 79: 550-557
        • Bowen J.
        • Gibbons L.
        • Gianas A.
        • Kraft G.H.
        Self-administered Expanded Disability Status Scale with functional system scores correlates well with a physician-administered test.
        Mult Scler. 2001; 7: 201-206
        • Marrie R.A.
        • Goldman M.
        Validity of performance scales for disability assessment in multiple sclerosis.
        Mult Scler. 2007; 13: 1176-1182
        • Jensen M.P.
        • Karoly P.
        Self-report scales and procedures for assessing pain in adults.
        in: Turk D.C. Melzack R. Handbook of pain assessment. Guilford, New York1992: 135-151
        • Gershon R.C.
        • Lai J.S.
        • Bode R.
        • et al.
        Neuro-QOL: quality of life item banks for adults with neurological disorders: item development and calibrations based upon clinical and general population testing.
        Qual Life Res. 2012; 21: 475-486
        • Sullivan M.J.
        • Bishop S.R.
        • Pivik J.
        The Pain Catastrophizing Scale: development and validation.
        Psychol Assess. 1995; 7: 524-532
        • Jacobsen P.B.
        • Azzarello L.M.
        • Hann D.M.
        Relation of catastrophizing to fatigue severity in women with breast cancer.
        Cancer Research, Therapy, and Control. 1999; 8: 155-164
        • Amtmann D.
        • Bamer A.M.
        • Cook K.F.
        • Askew R.L.
        • Noonan V.K.
        • Brockway J.A.
        University of Washington self-efficacy scale: a new self-efficacy scale for people with disabilities.
        Arch Phys Med Rehabil. 2012; 93: 1757-1765
        • Hibbard J.H.
        • Stockard J.
        • Mahoney E.R.
        • Tusler M.
        Development of the Patient Activation Measure (PAM): conceptualizing and measuring activation in patients and consumers.
        Health Serv Res. 2004; 39: 1005-1026
        • Aiken L.S.
        • West S.G.
        Multiple regression: testing and interpreting interactions.
        Sage Publications, Thousand Oaks1991
        • Cohen J.
        A power primer.
        Psychol Bull. 1992; 112: 155-159
        • Faul F.
        • Erdfelder E.
        • Buchner A.
        • Lang A.G.
        Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses.
        Behav Res Methods. 2009; 41: 1149-1160
        • Plow M.A.
        • Finlayson M.
        • Rezac M.
        A scoping review of self-management interventions for adults with multiple sclerosis.
        PM R. 2011; 3: 251-262