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Objective Describe who is able to return to driving (RTD) after moderate-to-severe traumatic brain injury (TBI), when this occurs, who maintains that activity, and the association with outcome. Design Cross-sectional descriptive study. Setting Eight follow-up sites of the TBI Model Systems (TBIMS) program. Participants 618 participants enrolled in the TBIMS and 88 caregivers (N=706). Interventions Not applicable. Main Outcome Measures A survey was completed from 1-30 years postinjury focusing on RTD. Descriptors included demographic information, injury severity, and current employment status. Outcome was assessed at the time of the interview, including depression, quality of life, functional status, and community participation. Results Of 706 respondents, 78% (N = 552) RTD, but 14% (N = 77) of these did not maintain that activity. Of those who RTD, 43% (N = 192) did so within 6 months of the injury and 92% did so within 24 months postinjury. The percentage of people driving after TBI did not differ significantly based on age at time of injury or follow-up. There were significant differences between drivers and nondrivers with respect to severity of injury, seizures, race, education, employment, rural vs urban setting, marital status, and family income. We performed a multivariate logistic regression to examine the association between driving status and demographic variables, adjusting for other variables in the model. The strongest associations were with current employment, family income, race, seizures, and severity of injury. Driving was associated with greater community participation, better functional outcomes, fewer symptoms of depression, and greater life satisfaction. Conclusions Over a span of 30 years, three-quarters of people experiencing moderate-to-severe TBI return to driving a personal vehicle, although not everyone maintains this activity. Employment, race, family income, and seizures are strongly associated with RTD.

To describe the association between unmet rehabilitation needs and life satisfaction 5 years after traumatic brain injury (TBI).Prospective observational cohort.Five Veterans Affairs (VA) Polytrauma Rehabilitation Centers.VA TBI Model Systems participants (N=301); 95% male; 77% white; average age, 39±14y).Not applicable.Satisfaction With Life Scale (SWLS).Average SWLS score was 22±8. Univariable analyses demonstrated several statistically significant predictors of life satisfaction, including employment status, participation, psychiatric symptom severity, past year mental health treatment, and total number of unmet rehabilitation needs (all P.05). Multivariable analyses revealed that depression and participation were each associated with life satisfaction. An ad hoc mediation model suggested that unmet rehabilitation needs total was indirectly related to life satisfaction. Total unmet rehabilitation needs ranged from 0-21 (mean, 2.0±3.4). Correlational analyses showed that 14 of the 21 unmet rehabilitation needs were associated with life satisfaction.Findings support the need for rehabilitation engagement in later stages of TBI recovery. Ongoing assessment of and intervention for unmet rehabilitation needs in the chronic phase of recovery have the potential to mitigate decline in life satisfaction.

Objective To determine the diagnostic sensitivity and specificity and comparative effectiveness of traditional sleep apnea screening tools in traumatic brain injury (TBI) neurorehabilitation admissions. Design Prospective diagnostic comparative effectiveness trial of sleep apnea screening tools relative to the criterion standard, attended level 1 polysomnography including encephalography. Setting Six TBI Model System Inpatient Rehabilitation Centers. Participants Between May 2017 and February 2019, 449 of 896 screened were eligible for the trial with 345 consented (77% consented). Additional screening left 263 eligible for and completing polysomnography with final analyses completed on 248. Intervention Not applicable. Main Outcome Measures Area under the curve (AUC) of screening tools relative to total apnea hypopnea index≥15 (AHI, moderate to severe apnea) measured at a median of 47 days post-TBI (interquartile range, 29-47). Results The Berlin high-risk score (receiving operating curve [ROC] AUC=0.634) was inferior to the Multivariable Apnea Prediction Index (MAPI) (ROC AUC=0.780) (P=.0211; CI, 0.018-0.223) and Snoring, Tired, Observed, Blood Pressure, Body Mass Index, Age, Neck Circumference, and Gender (STOPBANG) score (ROC AUC=0.785) (P=.001; CI, 0.063-0.230), both of which had comparable AUC (P=.7245; CI, −0.047 to 0.068). Findings were similar for AHI≥30 (severe apnea); however, no differences across scales was observed at AHI≥5. The pattern was similar across TBI severity subgroups except for posttraumatic amnesia (PTA) status wherein the MAPI outperformed the Berlin. Youden's index to determine risk yielded lower sensitivities but higher specificities relative to non-TBI samples. Conclusion This study is the first to provide clinicians with data to support a choice for which sleep apnea screening tools are more effective during inpatient rehabilitation for TBI (STOPBANG, MAPI vs Berlin) to help reduce comorbidity and possibly improve neurologic outcome.

Objective To investigate the association between insurance provider and reported assistive technology (AT) use to access computers and electronic devices 1 year after sustaining tetraplegia. Design Multicenter cross-sectional study. Setting Participants enrolled in the Spinal Cord Injury Model Systems (SCIMS) National Database. Interventions Not applicable. Participants Men and women with tetraplegia (N=498) enrolled in the SCIMS National Database were included in the analysis. Main Outcome Measures The primary study outcome was the use of AT when operating a computer or other mobile electronic device. The primary predictor was the subject’s principal health insurance provider, which was grouped into the 3 categories: government (Medicare, Medicaid, and other government), private (private insurance, private funds, and other), and workers’ compensation. Results Overall, 34.7% of participants reported using AT to access computers and electronic devices. Results of logistic regression analysis revealed sex, injury level, injury completeness, self-perceived health status, and 12-month history of pressure ulcer were all significantly associated with AT use. After adjusting for these factors, participants with workers’ compensation were more likely to report AT use than individuals with either government or private insurance. Conclusions Despite significant technological advances, AT is not readily available to the people who might benefit most from its use. Findings from the present study are the first to shed light on AT funding sources and reveal that individuals with workers’ compensation are more likely use AT than individuals with either government or private insurance. Additional work focused on AT use and functional outcomes is needed to assess the effect of barriers to use. Collectively, this work may inform insurers of the importance of having AT available for this unique population to potentially improve quality of life and participation.