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Traumatic brain injury (TBI) is often experienced under stressful circumstances that can lead to symptoms of post-traumatic stress disorder (PTSD) and neurobehavioral symptoms of brain injury. There is considerable symptom overlap in the behavioral expression of these conditions. Psychometric network analysis is a useful approach to investigate the role of specific symptoms in connecting these two disorders and is well suited to explore their interrelatedness. This study applied network analysis to examine the associations among PTSD and TBI symptoms in a sample of Service Members and Veterans (SM/Vs) with a history of TBI one year after injury. Responses to the Neurobehavioral Symptom Inventory (NSI) and PTSD Checklist-Civilian version (PCL-C) were obtained from participants who completed comprehensive inpatient rehabilitation services across five Veterans Affairs polytrauma rehabilitation centers. Participants (N = 612) were 93.1% male with an average age of 36.98 years at injury. The analysis produced a stable network. Within the NSI symptom groups, the frustration symptom was an important bridge between the affective and cognitive TBI symptoms. The PCL-C nodes formed their own small cluster with hyperarousal yielding connections with the affective, cognitive, and somatic symptom groups. Consistent with this observation, the hyperarousal node had the second strongest bridge centrality in the network. Hyperarousal appears to play a key role in holding together this network of distress and thus represents a prime target for intervention among individuals with elevated symptoms of PTSD and a history of TBI. Network analysis offers an empirical approach to visualizing and quantifying the associations among symptoms. The identification of symptoms that are central to connecting multiple conditions can inform diagnostic precision and treatment selection.

Identifying the principal determinants of life satisfaction following mild TBI (mTBI) may inform efforts to improve subjective well-being in this population. We examined life satisfaction among participants in the Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) study who presented with mTBI (Glasgow Coma Scale [GCS] score = 13–15; n = 1152). An L1-regularization path algorithm was used to select optimal sets of baseline and concurrent symptom measures for prediction of scores on the Satisfaction with Life Scale (SWLS) at 2 weeks and 3, 6, and 12 months post-injury. Multi-variable linear regression models (all n = 744–894) were then fit to evaluate associations between the empirically selected predictors and SWLS scores at each follow-up visit. Results indicated that emotional post-TBI symptoms (all b = −1.27 to −0.77, all p