Introduction

The Neurobehavioral Symptom Inventory (NSI - 22) is a validated, self-reported questionnaire designed to assess Post-Concussion Syndrome (PCS) symptoms. Though used in various settings, this scale is widely used in TBI evaluations within the Veterans Health Administration and the Department of Defense. Studies have shown that psychological and behavioral measures are strong predictors of persistent neurobehavioral symptom reporting in veterans; however, there is still a gap in knowledge about these associations in a civilian population presenting for treatment. This study seeks to identify the predictors of increased neurobehavioral symptom reporting on the NSI-22 in a treatment seeking population with MTBI, in order to continue developing strategies for the treatment of patients with PCS.

Methods

Retrospective data analysis of 80 participants between 2014 and 2018, with a diagnosis of probable (consistent with mild) or possible (consistent with concussive) MTBI, classified using the Mayo Classification System for traumatic brain injury severity.  All participants received interdisciplinary outpatient rehabilitation, with the specific therapy and duration determined by clinical need.  On admission, participants were given assessment measures of neurobehavioral symptoms (NSI – 22), depression (PHQ-9), satisfaction with life (SWLS), and participation (M2PI). The primary outcome of interest was NSI – 22 scores on admission. Predictor variables used in a univariate analysis were PHQ-9, SWLS, M2PI, age at injury, prior history of MTBI, premorbid history of PTSD, mood disorder, ADHD, sleep disorder, chronic pain, substance abuse, migraine disorder, employment at time of assessment, education years, and method of injury. Predictor variables identified by univariate analysis were entered into a multivariable regression model, which was adjusted for demographic variables, time since the injury, marital status, as well as the mechanism of injury. 

Results

Increased NSI 22 total scores, as well as all subsets within the NSI-22, were significantly correlated with increased level of depressive complaints (PHQ-9), higher disability (M2PI), lower satisfaction with life (SWLS), prior MTBI, fewer years of education, and unemployment at time of assessment. When those variables were used in a multivariable linear regression model, the PHQ 9, M2PI, and years of education remained statistically significant. 

Conclusions

Within a treatment-seeking civilian sample diagnosed with mild TBI, increased endorsement of depressive symptoms, greater level of disability, and lower level of education predicted increased neurobehavioral symptoms.  These results further support the need for comprehensive assessment and interdisciplinary treatment that assist with the management of physical, cognitive, behavioral, and emotional symptoms that impact quality of life in persons with mild TBI presenting for treatment.

Predictors of Neurobehavioral Symptom Reporting in a Community Based Sample with Mild Traumatic Brain Injury (MTBI)