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Depressive Symptomatology and Functional Status Among Stroke Survivors: A Network Analysis

  • Stephen C.L. Lau
    Affiliations
    Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO
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  • Lisa Tabor Connor
    Affiliations
    Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO

    Department of Neurology, Washington University School of Medicine, St. Louis, MO
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  • Jin-Moo Lee
    Affiliations
    Department of Neurology, Washington University School of Medicine, St. Louis, MO
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  • Carolyn M. Baum
    Correspondence
    Corresponding author Carolyn M. Baum, PhD, Program in Occupational Therapy, Department of Neurology, Brown School of Social Work, Washington University School of Medicine, 600 S. Taylor Ave 00163, St Louis, MO 63110.
    Affiliations
    Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO

    Department of Neurology, Washington University School of Medicine, St. Louis, MO

    Brown School of Social Work, Washington University in St Louis, St Louis, MO, United States
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Published:January 27, 2022DOI:https://doi.org/10.1016/j.apmr.2022.01.143

      Abstract

      Objective

      To (1) characterize poststroke depressive symptom network and identify the symptoms most central to depression and (2) examine the symptoms that bridge depression and functional status.

      Design

      Secondary data analysis of the Stroke Recovery in Underserved Population database. Networks were estimated using regularized partial correlation models. Topology, network stability and accuracy, node centrality and predictability, and bridge statistics were investigated.

      Setting

      Eleven inpatient rehabilitation facilities across 9 states of the United States.

      Participants

      Patients with stroke (N=1215) who received inpatient rehabilitation.

      Interventions

      Not applicable.

      Main Outcome Measures

      The Center for Epidemiologic Studies Depression Scale and FIM were administered at discharge from inpatient rehabilitation.

      Results

      Depressive symptoms were positively intercorrelated within the network, with stronger connections between symptoms within the same domain. “Sadness” (expected influence=1.94), “blues” (expected influence=1.14), and “depressed” (expected influence=0.97) were the most central depressive symptoms, whereas “talked less than normal” (bridge expected influence=−1.66) emerged as the bridge symptom between depression and functional status. Appetite (R2=0.23) and sleep disturbance (R2=0.28) were among the least predictable symptoms, whose variance was less likely explained by other symptoms in the network.

      Conclusions

      Findings illustrate the potential of network analysis for discerning the complexity of poststroke depressive symptomology and its interplay with functional status, uncovering priority treatment targets and promoting more precise clinical practice. This study contributes to the need for expansion in the understanding of poststroke psychopathology and challenges clinicians to use targeted intervention strategies to address depression in stroke rehabilitation.

      Keywords

      List of abbreviations:

      CBT (cognitive behavioral therapy), CESD (Center for Epidemiological Studies Depression Scale)
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