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Interrelationships Between Post-TBI Employment and Substance Abuse: A Cross-lagged Structural Equation Modeling Analysis

  • Author Footnotes
    ∗ Awan and DiSanto contributed equally to this work.
    Nabil Awan
    Footnotes
    ∗ Awan and DiSanto contributed equally to this work.
    Affiliations
    Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, Pennsylvania

    Department of Biostatistics, University of Pittsburgh, Pittsburgh, Pennsylvania

    Institute of Statistical Research and Training, University of Dhaka, Dhaka, Bangladesh
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  • Author Footnotes
    ∗ Awan and DiSanto contributed equally to this work.
    Dominic DiSanto
    Footnotes
    ∗ Awan and DiSanto contributed equally to this work.
    Affiliations
    Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, Pennsylvania
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  • Shannon B. Juengst
    Affiliations
    Department of Physical Medicine & Rehabilitation, University of Texas-Southwestern Medical Center, Dallas, Texas

    Department of Rehabilitation Counseling, University of Texas-Southwestern Medical Center, Dallas, Texas
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  • Raj G. Kumar
    Affiliations
    Department of Rehabilitation Medicine, Brain Injury Research Center, Icahn School of Medicine at Mount Sinai, New York, New York
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  • Hilary Bertisch
    Affiliations
    Department of Psychology, NYU Rusk Rehabilitation, New York, New York
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  • Janet Niemeier
    Affiliations
    Department of Physical Medicine and Rehabilitation, UAB Spain Rehabilitation Center, Birmingham, Alabama
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  • Jesse R. Fann
    Affiliations
    Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, Washington

    Department of Epidemiology, University of Washington, Seattle, Washington

    Department of Rehabilitation Medicine, University of Washington, Seattle, Washington
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  • Jason Sperry
    Affiliations
    Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania
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  • Amy K. Wagner
    Correspondence
    Corresponding author Amy K. Wagner, MD, University of Pittsburgh, 3471 Fifth Ave Suite 202, Pittsburgh, PA 15213.
    Affiliations
    Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, Pennsylvania

    Center for Neuroscience, University of Pittsburgh, Pittsburgh, Pennsylvania

    Safar Center of Resuscitation Research, University of Pittsburgh, Pittsburgh, Pennsylvania

    Department of Neuroscience, University of Pittsburgh, Pittsburgh, Pennsylvania

    Clinical and Translational Science Institute, University of Pittsburgh, Pittsburgh, Pennsylvania
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  • Author Footnotes
    ∗ Awan and DiSanto contributed equally to this work.
Published:December 07, 2019DOI:https://doi.org/10.1016/j.apmr.2019.10.189

      Abstract

      Objective

      To describe the interrelationship of postinjury employment and substance abuse (SA) among individuals with traumatic brain injury.

      Design

      Structural equation model (SEM) and logistic regression analytic approach using a merged database of the National Trauma Data Bank (NTDB) and Traumatic Brain Injury Model Systems (TBIMS) National Database, with acute care and rehabilitation hospitalization data and 1, 2, and 5 year follow-up data.

      Setting

      United States Level I/II trauma centers and inpatient rehabilitation centers with telephone follow-up.

      Participants

      Individuals in the TBIMS National Database successfully matched to their NTDB data, aged 18-59 years, with trauma severity, age, sex, employment, and SA data at 1, 2, and/or 5 years postinjury (N=2890).

      Interventions

      Not applicable.

      Main Outcome Measure

      Employment status (employed/unemployed) and SA (present/absent) at year 1, year 2, and year 5 postinjury.

      Results

      SEM analysis showed older age at injury predicted lower likelihood of employment at all time points postinjury (βYR1=−0.016; βYR2=−0.006; βYR5=−0.016; all P<.001), while higher injury severity score (ISS) predicted lower likelihood of employment (β=−0.008; P=.027) and SA (β=−0.007; P=.050) at year 1. Male sex predicted higher likelihood of SA at each follow-up (βYR1=0.227; βYR2=0.184; βYR5=0.161; all P<.100). Despite associations of preinjury unemployment with higher preinjury SA, postinjury employment at year 1 predicted SA at year 2 (β=0.118; P=.028). Employment and SA during the previous follow-up period predicted subsequent employment and SA, respectively.

      Conclusions

      Employment and SA have unique longitudinal interrelationships and are additionally influenced by age, sex, and ISS. The present work suggests the need for more research on causal, confounding, and mediating factors and appropriate screening and intervention tools that minimize SA and facilitate successful employment-related outcomes.

      Keywords

      List of abbreviations:

      ECI (extracranial injury), FIM-Cog (FIM–Cognitive Subscale), FIM-Mot (FIM–Motor Subscale), ISS (injury severity score), NTDB (National Trauma Data Bank), OR (odds ratio), QOL (quality of life), SA (substance abuse), SEM (structural equation model), TBI (traumatic brain injury), TBIMS (Traumatic Brain Injury Model Systems)
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