Abstract
Objective
To characterize employment stability and identify predictive factors of employment
stability in working-age individuals after moderate-to-severe traumatic brain injury
(TBI) that may be clinically addressed.
Design
Longitudinal observational study of an inception cohort from the Traumatic Brain Injury
Model Systems National Database (TBIMS-NDB) using data at years 1, 2, and 5 post-TBI.
Setting
Inpatient rehabilitation centers with telephone follow-up.
Participants
Individuals enrolled in the TBIMS-NDB since 2001, aged 18-59, with employment data
at 2 or more follow-up interviews at years 1, 2, and 5 (N=5683).
Interventions
Not applicable.
Main Outcome Measure
Employment stability, categorized using post-TBI employment data as no paid employment
(53.25%), stably (27.20%), delayed (10.24%), or unstably (9.31%) employed.
Results
Multinomial regression analyses identified predictive factors of employment stability,
including younger age, white race, less severe injuries, preinjury employment, higher
annual earnings, male sex, higher education, transportation independence postinjury,
and no anxiety or depression at 1 year post-TBI.
Conclusions
Employment stability serves as an important measure of productivity post-TBI. Psychosocial,
clinical, environmental, and demographic factors predict employment stability post-TBI.
Notable predictors include transportation independence as well as the presence of
anxiety and depression at year 1 post-TBI as potentially modifiable intervention targets.
Keywords
List of abbreviations:
CVLT-II (California Verbal Learning Test II), O-LOG (Orientation Log), PTA (posttraumatic amnesia), RRR (relative risk ratio), TBI (traumatic brain injury), TBIMS-NDB (Traumatic Brain Injury Model Systems National Database), TMT (Trail Making Test)To read this article in full you will need to make a payment
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Article info
Publication history
Published online: July 26, 2018
Footnotes
Supported by the National Institute on Disability, Independent Living, and Rehabilitation Research (NIDILRR) for the collection of original data for this article. The content of this article was developed under NIDILRR (grant nos. 90DP0031, 90DP0041, 90DPTB0013-01-00, 90DP0044-01, 90DPTB0011-01-00, 90DP0037) and with postdoctoral fellow support by NIDILRR (grant no. 90AR5025).
Additional support was received from VA Central Office, VA TBI Model System Program of Research, and Subcontract from General Dynamics Health Solutions (grant no. W91YTZ-13-C-0015) and from the Defense and Veterans Brain Injury Center, US Department of Veterans Affairs Health Services Research and Development COIN (grant no. 1 I50 HX001233-01).
Disclosures: none.
Identification
Copyright
© 2018 by the American Congress of Rehabilitation Medicine
