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To understand factors influencing adherence to recommended treatment for insomnia and obstructive sleep apnea (OSA) among Veterans with mild traumatic brain injury (mTBI). Semi-structured interviews (n = 49) with 29 clinical stakeholders and 20 Veterans were conducted. Clinical stakeholders included Veterans Health Administration providers and policymakers involved in the management of mTBI and/or sleep disorders. Veterans included those with a clinician-confirmed mTBI with a recent history of insomnia disorder and/or OSA treatment. Themes were identified using a Descriptive and Interpretive approach. Barriers to sleep disorder treatment adherence included factors associated with the patient (e.g., negative appraisal of treatment benefit), intervention (e.g., side effects), health conditions (e.g., cognitive challenges), health care system (e.g., limited availability of care), and socioeconomic status (e.g., economic instability). Similarly, facilitators of adherence included patient- (e.g., positive appraisal of treatment benefit), intervention- (e.g., flexible delivery format), condition- (e.g., accommodating cognitive impairments), health care system- (e.g., access to adherence support), and socioeconomic-related factors (e.g., social support). Interviews revealed the multi-faceted nature of factors influencing adherence to sleep disorder treatment among Veterans with mTBI. Findings can inform the development of novel interventions and care delivery models that meet the complex needs of this population. [ABSTRACT FROM AUTHOR]

Background: TBI is a leading cause of disability among veterans and active duty military personnel, and presents an obstacle to community reintegration. Prior studies examining adult survivors of TBI pursuing postsecondary education have methodological flaws that limit the understanding the scope and severity of sequelae experienced by persons with TBI who attend college. Objective: To describe (a) physical and cognitive functioning, and (b) postconcussion and mental health symptoms in veterans and military personnel (V/M) with traumatic brain injury (TBI) enrolled in postsecondary education programs after discharge from rehabilitation. Method: Cross-sectional study. Participants were recruited from five Veterans Affairs (VA) Polytrauma Rehabilitation Centers, enrolled in the VA TBI Model Systems parent study, and attending school during follow-up (N = 155). Outcome measures included the Functional Independence Measure (FIM), Neurobehavioral Symptom Inventory (NSI), Post-traumatic Stress Disorder (PTSD) Checklist-Civilian version (PCL-C), Patient Health QuestionnaireDepression (PHQ-9), and Generalized Anxiety Disorder Questionnaire (GAD-7). Findings: Participants were mostly male (92.9%) and White (81.4%), with mild (40.0%), moderate (11.5%), severe (34.5%), or very severe TBI (23.0%). Depression, anxiety, PTSD, and postconcussion symptoms were lowest in participants with very severe TBI and highest in those with mild TBI. There were no significant differences in FIM across TBI severity levels. Conclusion: This study supports the need for rehabilitation counselors, educators, and administrators to prepare future practitioners to deliver tailored services to student V/M with TBI. These services can facilitate successful community reintegration and transition into civilian school settings. Symptom profiling may inform personalized cognitive interventions to enhance these students' academic success.

Background: There is a limited evidence‐base describing clinical features of delirium in youth. What is known is largely extrapolated from studies of adults or samples with heterogeneous etiologies. It is unclear if the symptoms experienced by adolescents differ from those experienced by adults, or the degree to which delirium impacts the ability of adolescents to return to school or work. Objective: To describe delirium symptomatology among adolescents following a severe traumatic brain injury (TBI). Symptoms were compared by adolescent delirium status and across age groups. Delirium and its relationship with adolescent employability 1 year post‐injury was also examined. Design: Exploratory secondary analysis of prospectively collected data. Setting: Free‐standing rehabilitation hospital. Patients: Severely injured TBI Model Systems neurorehabilitation admissions (n = 243; median Glasgow Coma Scale = 7). The sample was divided into three age groups (adolescents, 16–21 years, n = 63; adults 22–49 years, n = 133; older adults ≥50 years, n = 47). Interventions: Not applicable. Measures: We assessed patients using Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM‐IV) diagnostic criteria and the Delirium Rating Scale‐Revised 98 (DRS‐R‐98). The employability item from the Disability Rating Scale was the primary 1‐year outcome. Results: Most items on the DRS‐R‐98 differentiated delirious from non‐delirious adolescents. Only "delusions" differed among age groups. Among adolescents, delirium status 1 month post‐TBI provided acceptable classification of employability prediction 1 year later (area under the curve [AUC]: 0.80, 95% confidence interval [CI]: 0.69–0.91, p <.001). Delirium symptom severity (AUC: 0.86, 95% CI: 0.68–1.03, SE: 0.09; p <.001) and days of post‐traumatic amnesia (AUC: 0.85, 95% CI: 0.68–1.01, SE: 0.08; p <.001) provided excellent prediction of outcomes for TBI patients in delirium. Conclusions: Delirium symptomatology was similar among age groups and useful in differentiating the delirium status within the adolescent TBI group. Delirium and symptom severity at 1 month post‐TBI were highly predictive of poor outcomes. Findings from this study support the utility of DRS‐R‐98 at 1 month post‐injury to inform treatment and planning. [ABSTRACT FROM AUTHOR]

Objective: To examine the relationship between extreme pain phenotypes (interference and improvement) and psychosocial outcomes among those with chronic pain after traumatic brain injury (TBI). Setting: Community. Participants: In total, 1762 TBI Model Systems (TBIMS) participants 1 to 30 years postinjury reporting chronic pain. Design: Multisite, cross-sectional, observational cohort study. Primary Measure(s): Life satisfaction, posttraumatic stress, depression and anxiety symptoms, sleep and participation, the Brief Pain Inventory (BPI) interference scale, and the Patient’s Global Impression of Change (PGIC). Results: Persons in the extreme high interference phenotype (vs extreme low interference phenotype) and/or extreme no change phenotype (vs extreme improvement phenotype) had poorer psychosocial outcomes, with extreme pain interference phenotypes having a larger effect on outcomes than extreme perceived improvement phenotypes. After controlling for covariates, large effect sizes (ES) related to pain interference were observed for posttraumatic stress symptoms (ES = −1.14), sleep quality (ES = −1.10), depression (ES = −1.08), anxiety (ES = −0.82), and life satisfaction (ES = 0.76); effect sizes for participation outcomes, although significant, were relatively small (ES = 0.21-0.36). Effect sizes related to perceived improvement were small for life satisfaction (ES = 0.20) and participation (ES = 0.16-0.21) outcomes. Pain intensity was identified as a meaningful confounding factor of the relationships between extreme phenotypes and posttraumatic stress, depression, anxiety, and sleep quality. Conclusions: Examination of extreme phenotypes provides important insights into the experience of individuals living with chronic pain and TBI. Results suggest that the relationships among a variety of characteristics of the person, their experience with pain, and treatment of pain are complex. Further research is needed to better understand these complex relationships and how differences in pain interference and perceived improvement from treatment can assist in assessment and treatment of chronic pain after TBI. [ABSTRACT FROM AUTHOR]

Objective: To define and characterize extreme phenotypes based on perceived improvement in pain for persons with chronic pain following traumatic brain injury (TBI). Setting: Eighteen Traumatic Brain Injury Model System (TBIMS) Centers. Participants: A total of 1762 TBIMS participants 1 to 30 years post-injury reporting chronic pain at their most recent follow-up interview. Primary Measures: The Patient’s Global Impression of Change (PGIC) related to pain treatment. Sociodemographic, injury, functional outcome, pain, and pain treatment characteristics. Results: Participants were mostly male (73%), White (75%), middle-aged (mean 46 years), injured in motor vehicle accidents (53%), or falls (20%). Extreme phenotypes were created for an extreme improvement phenotype (n = 512, 29.8%) defined as “moderately better” or above on the PGIC and an extreme no-change group (n = 290, 16.9%) defined as no change or worse. Least absolute shrinkage and selection operator (LASSO) regression combined with logistic regression identified multivariable predictors of improvement versus no-change extreme phenotypes. Higher odds of extreme improvement phenotype were significantly associated with being female (odds ratio [OR] = 1.85), married versus single (OR = 2.02), better motor function (OR = 1.03), lower pain intensity (OR = 0.78), and less frequent pain, especially chest pain (OR = 0.36). Several pain treatments were associated with higher odds of being in the extreme improvement versus no-change phenotypes including pain medication (OR = 1.85), physical therapy (OR = 1.51), yoga (OR = 1.61), home exercise program (OR = 1.07), and massage (OR = 1.69). Conclusion: Investigation of extreme phenotypes based on perceived improvement with pain treatment highlights the ability to identify characteristics of individuals based on pain treatment responsiveness. A better understanding of the biopsychosocial characteristics of those who respond and do not respond to pain treatments received may help inform better surveillance, monitoring, and treatment. With further research, the identification of risk factors (such as pain intensity and frequency) for treatment response/nonresponse may provide indicators to prompt changes in care for individuals with chronic pain after TBI. [ABSTRACT FROM AUTHOR]

Objective: To define and characterize extreme phenotypes based on pain interference for persons with chronic pain following traumatic brain injury (TBI). Setting: Eighteen Traumatic Brain Injury Model System (TBIMS) Centers. Participants: A total of 1762 TBIMS participants 1 to 30 years post-injury reporting chronic pain at their most recent follow-up interview. Primary Measures: The Brief Pain Inventory (BPI) interference scale, sociodemographic, injury, functional outcome, pain, and treatment characteristics. Results: Participants were predominantly male (73%), White (75%), middle-aged (mean 46 years), and who were injured in motor vehicle accidents (53%) or falls (20%). Extreme phenotypes were identified based on upper and lower 25th percentiles to create low-interference (n = 441) and high-interference (n = 431) extreme phenotypes. Bivariate comparisons found several sociodemographic, injury, function, pain, and treatment differences between extreme phenotype groups, including significant differences (P < .001) on all measures of concurrent function with those in the low-interference extreme phenotype experiencing better function than those in the high-interference extreme phenotype. Lasso regression combined with logistic regression identified multivariable predictors of low- versus high-interference extreme phenotypes. Reductions in the odds of low- versus high-interference phenotypes were significantly associated with higher pain intensity (odds ratio [OR] = 0.33), having neuropathic pain (OR = 0.40), migraine headache (OR = 0.41), leg/feet pain (OR = 0.34), or hip pain (OR = 0.46), and more pain catastrophizing (OR = 0.81). Conclusion: Results suggest that for those who experience current chronic pain, there is high variability in the experience and impact of pain. Future research is needed to better understand how pain experience impacts individuals with chronic pain and TBI given that pain characteristics were the primary distinguishing factors between phenotypes. The use of extreme phenotypes for pain interference may be useful to better stratify samples to determine efficacy of pain treatment for individuals with TBI. [ABSTRACT FROM AUTHOR]