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Children With Chronic Pain: Response Trajectories After Intensive Pain Rehabilitation Treatment

  • Laura E. Simons
    Correspondence
    Address reprint requests to Laura E. Simons, PhD, Stanford University School of Medicine, 1070 Arastradero Road, Palo Alto, CA 94304.
    Affiliations
    Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, California
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  • Christine B. Sieberg
    Affiliations
    Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Boston Children's Hospital, Boston, Massachusetts

    Department of Psychiatry, Harvard Medical School, Boston, Massachusetts
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  • Caitlin Conroy
    Affiliations
    Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Boston Children's Hospital, Boston, Massachusetts

    Department of Psychiatry, Harvard Medical School, Boston, Massachusetts
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  • Edin T. Randall
    Affiliations
    Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Boston Children's Hospital, Boston, Massachusetts

    Department of Psychiatry, Harvard Medical School, Boston, Massachusetts
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  • Julie Shulman
    Affiliations
    Department of Physical and Occupational Therapy, Boston Children's Hospital, Boston, Massachusetts
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  • David Borsook
    Affiliations
    Department of Psychiatry, Harvard Medical School, Boston, Massachusetts

    P.A.I.N. Group, Boston Children's Hospital and Center for Pain and the Brain, Boston, Massachusetts
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  • Charles Berde
    Affiliations
    Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Boston Children's Hospital, Boston, Massachusetts
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  • Navil F. Sethna
    Affiliations
    Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Boston Children's Hospital, Boston, Massachusetts
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  • Deirdre E. Logan
    Affiliations
    Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Boston Children's Hospital, Boston, Massachusetts

    Department of Psychiatry, Harvard Medical School, Boston, Massachusetts
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Published:November 01, 2017DOI:https://doi.org/10.1016/j.jpain.2017.10.005

      Highlights

      • Three pain response trajectories emerged: responder, late responder and nonresponder.
      • The strongest predictor of pain nonresponse was lower readiness to change.
      • The social milieu benefits patients with social difficulties.
      • Targeted treatment of key factors could maximize responsivity.

      Abstract

      Intensive pain rehabilitation programs for children with chronic pain are effective for many patients. However, characteristics associated with treatment response have not been well documented. In this article we report trajectories of pain and functional impairment in patients with chronic pain up to 1 year after intensive pain rehabilitation and examine baseline factors associated with treatment response. Patients (n = 253) with chronic pain and functional disability were assessed at 5 time points (admission, discharge, 1-month, 4-month, and 12-month follow-ups). Individual trajectories were empirically grouped using SAS PROC TRAJ. For functional disability, 2 groups emerged: treatment responders (88%) and nonresponders (12%). Using a binomial logistic regression model to predict disability trajectory group, no baseline variables were significant predictors for the disability trajectory group. For pain, 3 groups emerged: early treatment responders (35%), late treatment responders (38%), and nonresponders (27%). Using multinomial regression analyses to predict pain trajectory group, older age, higher pain scores, fewer social difficulties, higher anxiety levels, and lower readiness to change were characteristics that distinguished nonresponders from responders; no significant predictors distinguished the late responders from the early responders. These results provide key information on the baseline factors that influence intensive pain rehabilitation outcomes, including risk factors that predict treatment nonresponse. Our findings have implications for developing more targeted treatment interventions.

      Perspective

      Deriving groups of individuals with differing treatment response trajectories stimulates new thinking regarding potential mechanisms that may be driving these outcomes.

      Key words

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