Depression Trajectories during the First Year after Traumatic Brain Injury

Charles H Bombardier, T. Hoekstra, Sureyya Dikmen, Jesse R Fann

Research output: Contribution to JournalArticleAcademicpeer-review


Major depression is prevalent after traumatic brain injury (TBI) and associated with poor outcomes. Little is known about the course of depression after TBI. Participants were 559 consecutively admitted patients with mild to severe TBI recruited from inpatient units at Harborview Medical Center, a Level I trauma center in Seattle, WA. Participants were assessed with the Patient Health Questionnaire-9 (PHQ-9) depression measure at months 1-6, 8, 10, and 12 post-injury. We used linear latent class growth mixture modeling (LCGMM) of PHQ-9 total scores to identify homogeneous subgroups with distinct longitudinal trajectories. A four-class LCGMM had good fit indices and clinical interpretability. Trajectory groups were: low depression (70.1%), delayed depression (13.2%), depression recovery (10.4%), and persistent depression (6.3%). Multinomial logistic regression analyses were used to distinguish trajectory classes based on baseline demographic, psychiatric history, and clinical variables. Relative to the low depression group, the other three groups were consistently more likely to have a pre-injury history of other mental health disorders or major depressive disorder, a positive toxicology screen for cocaine or amphetamines at the time of injury, and a history of alcohol dependence. They were less likely to be on Medicare versus commercial insurance. Trajectories based on LCGMM are an empirical and clinically meaningful way to characterize distinct courses of depression after TBI. When combined with baseline predictors, this line of research may improve our ability to predict prognosis and target groups who may benefit from treatment or secondary prevention efforts (e.g., proactive telephone counseling).

Original languageEnglish
Pages (from-to)2115-2124
Number of pages10
JournalJournal of Neurotrauma
Issue number23
Publication statusPublished - 1 Dec 2016


  • Journal Article


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