OBJECTIVE:Traumatic brain injury (TBI) disproportionately affects Black Americans, who often experience poorer functional outcomes than their White counterparts. These disparities are exacerbated by limited access to rehabilitation and community-based services. Although current literature has examined the specific barriers Black TBI survivors face in accessing these services, few studies have identified alternative sources of support when services are unavailable. This study aimed to identify the barriers to care, existing support systems, and the services most highly prioritized by Black TBI survivors. SETTING:Academic research laboratory. DESIGN:We conducted surveys and qualitative interviews with Black TBI survivors (n = 8) and their family caregivers (n = 6). Survey data were analyzed using descriptive statistics, and qualitative data were analyzed with reflexive thematic analysis. The analysis was guided by the Community Cultural Wealth model, which describes 6 forms of capital that marginalized communities use to navigate systemic barriers. RESULTS:Survey findings revealed that most participants (62.5%) were unaware of community-based brain injury programs. Barriers to accessing services included lack of awareness (75.0%), financial considerations (37.5%), and difficulty understanding eligibility (37.5%). We identified 3 qualitative themes: (1) participants were rich in familial and social capital, relying heavily on family and community networks for support; (2) health care and social service systems undermined navigational capital through long wait times, appointment cancellations, inadequate follow-up, and restrictive insurance policies; and (3) participants prioritized holistic, personalized care and opportunities for peer connection with others who had similar experiences. CONCLUSIONS:Findings highlight the need for culturally informed interventions, enhanced navigational support, family-centered services, peer support programs, and policy reforms to improve recovery outcomes for Black TBI survivors.
OBJECTIVE:To examine whether depressive symptoms at 1 year postinjury are associated with all-cause mortality among individuals with moderate-to-severe traumatic brain injury (TBI) who received inpatient rehabilitation, accounting for sociodemographic, functional, and mental health factors. SETTING:Community. PARTICIPANTS:A total of 2812 individuals enrolled in the TBI Model Systems National Database with 1-year postinjury follow-up interviews between October 1, 2007, and October 1, 2013, and a follow-up within 5 years of injury. DESIGN:Prospective cohort study, using secondary analysis of longitudinal data. MAIN MEASURES:Depression (Patient Health Questionnaire-9) and all-cause mortality. RESULTS:The rate of high depressive symptom burden at 1-year follow-up was 28.5%, and the overall death rate was 8.8% across the study follow-up period. In age-adjusted models, higher depressive symptom burden at 1 year was associated with increased mortality risk; however, this association was progressively attenuated after adjustment for functional status and preinjury mental health variables and was no longer statistically significant in fully adjusted models. Sensitivity analyses using multiple imputation yielded similar results. CONCLUSION:Findings suggest that depressive symptom burden at 1 year postinjury is not independently associated with 5-year mortality after accounting for functional status and preinjury mental health history. Depression may, nonetheless, function as a clinically meaningful marker of broader vulnerability. Further research is warranted to explore whether targeting depression and functional recovery influence long-term survival after TBI.
OBJECTIVES:We aimed to forecast headache in individuals with persisting postconcussion symptoms using foundation machine learning (ML) models and multimodal longitudinal data. METHODS:This was an ML analysis of data from the Digital Solutions for Concussion (DiSCo) study, a research project assessing the usability and feasibility of 2 mobile health apps for individuals with persisting postconcussion symptoms. The participants completed daily symptom registrations and daily biofeedback sessions measuring heart rate variability, peripheral skin temperature, and upper trapezius muscle tension. Two foundation ML models, TabPFN and longitudinal TabPFN, were recruited and evaluated to predict moderate-to-severe (at least 4 on the 11-point numeric rating scale) headache days occurring in the subsequent 24-hour window using prior physiological and symptom data. The top-performing model was further evaluated for forecasting days with fatigue, which was rated as the second to headache most bothersome symptom, within the subsequent 24-hour window. Models were trained and optimized on a train-set and evaluated on a hold-out test-set with the area under the receiver operating characteristics curve (AUC) and 95% confidence intervals (CIs). RESULTS:Twenty individuals were included in the forecasting models, with data collected over a planned 28-day registration period, yielding a total of 338 days. The most stable model, longitudinal TabPFN, achieved a test-set AUC of 0.69 (95% CI: 0.62-0.74). The conventional TabPFN model achieved an AUC of 0.68 (95% CI: 0.55-0.80). In the case of fatigue, the longitudinal TabPFN model achieved an AUC of 0.81 (95% CI: 0.75-0.86). Both physiological measurements and symptomology information seemed to be important predictors. CONCLUSIONS:Moderate-to-severe postconcussion headache days can be predicted with modest accuracy 24 hours before their occurrence from multimodal physiological and self-reported symptomatology data. Incorporating temporal dynamics using longitudinal foundation models may improve such forecasting.
OBJECTIVE:To define Military Occupational Blast Exposure (MOBE) as a standardized construct of cumulative occupational blast exposure spanning low-level blast and high-level blast, and propose reproducible MOBE risk classification groups based on military occupations when objective blast records or detailed lifetime interviews are unavailable. SETTING:Data were drawn from 2 Long-term Impact of Military-relevant Brain Injury Consortium-Chronic Effects of Neurotrauma Consortium (LIMBIC-CENC) studies: a retrospective cohort study and a multisite prospective longitudinal cohort. PARTICIPANTS:The Phenotype Study included 2 522 880 post-9/11 service members and Veterans. The Prospective Longitudinal Study (PLS) included 1666 service members and Veterans who had experienced combat. DESIGN:The Phenotype Study was used to operationalize MOBE risk classification and characterize demographic and military correlates. PLS data were used to evaluate whether MOBE risk classification aligned with blast exposure history and blast traumatic brain injury (TBI) history. MAIN MEASURES:MOBE risk classification was compared with the generalized blast exposure value (GBEV) and blast exposure category scores from the Blast Exposure Threshold Survey, as well as blast TBI history from clinical interview data. RESULTS:The Phenotype study classified 31.1% of military occupational codes into high-risk MOBE (MOBE+). In the PLS, MOBE+ individuals were more likely than MOBE- individuals to report blast TBI history (43.7% vs. 27.0%) and exceed the GBEV threshold of 200 000 (66.0% vs. 42.2%; both P < .001). MOBE+ individuals also reported higher mean blast exposure scores across all categories, with significant differences for small arms and large explosives. Occupational-level analyses showed meaningful heterogeneity in blast exposure profiles across high-risk occupations. CONCLUSIONS:MOBE risk classification differentiated meaningful patterns of blast exposure and blast-related injury in a well-characterized cohort. Findings support MOBE as a practical, scalable, standardized approach for estimating occupational blast exposure risk and improving comparability across studies when detailed individual exposure histories are unavailable.
OBJECTIVE:University performing artists are an under-represented population in concussion literature. The purposes of this study were to identify (1) areas of improvement regarding concussion education and management and (2) barriers with potential solutions to improve concussion care among university performing arts departments. SETTING:Electronic survey. PARTICIPANTS:The panel (n = 21, mean age = 41.9 ± 11.6 years; 71.4% female) included university-affiliated clinicians (n = 5), sport-related concussion researchers (n = 5), performing arts faculty/staff (n = 7), and students/alumni (n = 4) with self-reported concussion history. DESIGN:Modified Delphi technique. METHODS:During round 1, panelists responded to 4 open-ended response questions regarding concussion education topics in the performing arts, challenges returning to performance, barriers to accessing care, and strategies to support postconcussion management. Constant comparative analysis was used among the research team to generate statements for subsequent rounds of voting. In round 2, panelists anonymously rated the statements using a 9-point scale (1 = strongly disagree, 9 = strongly agree). During round 3, panelists could either uphold or modify their score after reviewing the group's averages. MAIN MEASURES:Consensus was achieved if the statements earned average group scores ≥7 after round 3. RESULTS:After the Delphi process, panelists agreed on 20 topics (60.6%) to be included in future concussion education materials, 21 statements (65.6%) regarding the challenges in returning to performance after concussion, 13 barriers (48.2%) performing arts students experience when seeking care on campus, and 23 strategies (63.9%) to improve postconcussion support. CONCLUSION:These recommendations may support institutional policy development to address the unique gaps in concussion preparation and management among university performing arts departments.
OBJECTIVE:To conduct a systematic review and meta-analysis of studies examining the proportion of first responders (law enforcement and corrections officers, firefighters, and emergency medical services personnel) with traumatic brain injury (TBI). METHODS:This review is reported in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and was a priori registered in PROSPERO. Eligible observational and interventional studies reporting the proportion of first responders with TBI (lifetime history; job/career-related; job/training-related; event-related) were identified and data were abstracted by 2 independent reviewers (with disagreements resolved by a third reviewer) from systematic searches in 5 databases (PubMed, Embase, Scopus, CINAHL [Cumulative Index to Nursing and Allied Health Literature], and Web of Science). Random-effects meta-analyses were performed when population-based denominators were available with between-study heterogeneity evaluated using I2. Risk of bias was assessed using an adapted Newcastle-Ottawa Scale. RESULTS:Twenty-three studies met inclusion criteria, with 5 contributing data to meta-analyses. Studies were heterogeneous in the method of TBI ascertainment, with some defining TBI from self-reported validated or unvalidated survey responses and others using medical or job-related administrative data to define TBI. Furthermore, definitions and language regarding the injury were heterogeneous between studies, with some studies referring to TBI (with or without loss of consciousness) and others referring to concussion or head injury/trauma. Among law enforcement and corrections officers, the pooled prevalence of lifetime TBI was 58.8% (95% confidence interval [CI]: 48.0%-69.6%; I2 = 91.5%), and the proportion with job/career-related TBI was 17.2% (95% CI: 5.8%-28.6%; I2 = 97.2%). Firefighters were found to have high self-reported lifetime TBI prevalence (62%-77%), although data were limited. Emergency medical service data were sparse and largely restricted to administrative or event-related reports. CONCLUSION:Traumatic brain injury is common among first responders, but studies are heterogeneous. Standardized TBI definition, surveillance, routine screening, and longitudinal occupational health monitoring are needed to address cumulative injury risk and inform prevention and policy.
Objective: Evaluate changes in subjective-objective sleep discrepancies among participants with insomnia and a history of moderate-to-severe traumatic brain injury (TBI) following computerized cognitive behavioral therapy for insomnia (cCBT-I). Setting: An outpatient setting at a Department of Veterans Affairs medical center. Participants: United States veterans between the ages of 18 and 60 years with current insomnia and a history of moderate-to-severe TBI ( N = 36). Design: A secondary analysis of intervention-arm data from a randomized controlled trial. Participants completed an online cCBT-I program called SleepEZ. The program was primarily self-guided, with adjunctive assistance provided by a study clinician. Main Measures: Subjective sleep outcomes were measured using the Consensus Sleep Diary, which were collected nightly throughout the entire intervention. Objective sleep outcomes were measured using wrist-based actigraphy, which were collected during the initial and final weeks of the program. Subjective-objective sleep discrepancies were calculated for total sleep time (TST), sleep onset latency (SOL), waking after sleep onset (WASO), early morning awakening (EMA), and sleep efficiency. Measure agreement was estimated with Bland-Altman plots. Changes in subjective-objective sleep discrepancies were estimated through multilevel modeling. Results: Poor agreement was observed for all 4 sleep outcomes. At baseline, participants overreported SOL and EMA on sleep diaries. However, WASO was greatly underreported, resulting in higher TST values calculated using sleep diaries compared with actigraphy. Following cCBT-I, overreporting of SOL decreased and sleep efficiency discrepancies grew larger, driven by improvements in subjective, but not objective, sleep measures. Conclusion: The concurrent use of subjective and objective measures is recommended to fully capture sleep health when treating insomnia after moderate-to-severe TBI. Further research is needed to elucidate mechanisms contributing to subjective-objective sleep discrepancies—potentially including specific aspects of cognitive impairment, striatal hyperactivity, or sleep pressure homeostasis—which may inform novel targets for post-TBI insomnia treatments among those with more severe injuries.
OBJECTIVE:Evaluate the relationship between risk of occupational low-level blast (LLB) exposure and health outcomes (ie, substance use disorder, long-term opioid receipt, headaches, and back pain). We integrated 2 established military occupation-based LLB exposure risk classification strategies (Belding and colleagues and Carr and colleagues) to use military service occupation as a proxy for LLB exposure risk. SETTING:Records were drawn from the Substance Use and Psychological Injury Combat Study and included Military Health System inpatient and outpatient care data, pharmacy fill records, and military history characteristics. PARTICIPANTS:Enlisted Army soldiers returning from an Afghanistan/Iraq deployment during fiscal years 2008-2014 (n = 477 746). DESIGN:Longitudinal and observational with exposure and outcome periods before and after the date of return from the first deployment ending in the study period, respectively. Belding and Carr classification strategies were integrated to create a 5-level LLB exposure risk framework (ie, High-Belding & Carr, High-Belding Only, Medium-Belding Only, Mixed, Low-Belding Only). MAIN MEASURES:Outcomes were long-term opioid receipt and diagnoses of substance use disorder, headache (including migraine), and back pain; covariates included demographic and military history characteristics, exposure-period traumatic brain injury diagnosis, exposure-period mental health and self-harm/suicidal behavior, and exposure-period observation of outcomes measures. RESULTS:Approximately 6.0% were classified as high exposure by the High-Belding & Carr classification, and 27.2% were classified as High-Belding Only. Comparing the High-Belding Only and High-Belding & Carr groups, respectively, with the Low-Belding Only group, survival models revealed elevated hazard ratios for long-term opioid receipt (1.29, P < .001; 1.33, P < .001) and substance use diagnoses (1.19, P < .001; 1.27, P < .001), somewhat elevated hazard ratios for headache (1.12, P < .001; 1.08, P < .001), and slightly lowered hazard ratios (0.98, P < .001; 0.98, P < .01) for back pain. CONCLUSION:Study results add to the existing research underscoring the urgency for advancing knowledge about LLB exposure and potential military health impacts and provide direction for future research.
OBJECTIVE:Prior research has established several risk factors for poor neurobehavioral outcomes after traumatic brain injury (TBI) in Iraq/Afghanistan-era-Veterans. However, no studies have examined the impact of environmental exposures on neurobehavioral symptoms in this population. The purpose of this study was to examine the relationship between environmental exposures and neurobehavioral symptoms in post-9/11 Veterans with a probable history of TBI. SETTING:Veterans Affairs (VA) Million Veteran Program (MVP). PARTICIPANTS:Participants included MVP-enrolled Veterans who completed the Veterans Health Administration's (VHA's) TBI Screening and Evaluation Program. Eligible participants were those who screened positive for TBI on the VHA Clinical Reminder Screen (N = 3370). DESIGN:Retrospective, cross-sectional design using secondary data analysis. MAIN MEASURES:Primary outcomes were 6 indices derived from the Neurobehavioral Symptom Inventory (NSI): total score (overall symptom severity), positive symptom total (symptom breadth), and 4 system clusters (vestibular, somatic/sensory, cognitive, and affective). Environmental exposures were self-reported by MVP surveys and included an exposure burden score and 7 individual exposure types: chemical or biological warfare agents; solvents/fuels; petroleum/combustion products; lead; other metals; pesticides; and open-air burn pits. RESULTS:The most frequently reported environmental exposures included petroleum combustion products (90.38%), burn pits (87.58%), and solvents/fuels (84.25%). Adjusted linear regression analyses, controlling for age, sex, race/ethnicity, and posttraumatic stress disorder status, showed significant positive associations between exposure burden and most neurobehavioral symptom outcomes (β = 0.13-1.08, all Ps < .001). In addition, there were several significant associations observed between each individual exposure variable and NSI outcomes, with the most consistent effects observed for other metals (β = 0.37-3.14, all Ps = <.001) and solvents/fuels (β = 0.88-2.95, all Ps = <.001). CONCLUSIONS:In post-9/11 Veterans with a probable history of TBI, environmental exposure burden and specific exposure types (particularly other metals and solvents/fuels) were associated with greater neurobehavioral symptom severity and breadth, suggesting environmental exposures as an additional, important contributor to chronic symptoms.
INTRODUCTION:Hospitalized adults with traumatic brain injury (TBI) often experience acute confusional states. However, conceptual clarity remains limited because of overlapping terminology, which hinders assessment. OBJECTIVES:This study aimed to map the terminology and assessment of acute confusional states in hospitalized TBI adults and examine their alignment with established definitions. METHODS:We conducted a scoping review (2013-2025) in 4 databases (MEDLINE, PsycInfo, CINAHL, and Google Scholar) following the Arksey and O'Malley framework. Peer-reviewed studies and clinical guidelines addressing acute confusional states in hospitalized TBI adults were included. Data extraction focused on terminology, assessment practices, and correspondence with definitions. RESULTS:Thirty-four studies were included. The most frequently reported terms were post-traumatic amnesia (PTA; n = 18), agitation (n = 11), delirium (n = 5), and post-traumatic confusional state (PTCS; n = 2). PTA was described as a transient state, reflecting daily assessment using unimodal cognitive screening tools rather than a broader recovery phase. It was characterized by amnesia and disorientation after sedation, aligning with international cognitive rehabilitation guidelines (INCOG 2.0), although additional features were reported. Agitation, also described as a state, involved fluctuating motor restlessness, impulsivity, aggression, and intense emotions, often without significant cognitive impairment, partially aligning with Cohen-Mansfield definition. Delirium was conceptualized as a syndrome encompassing disturbances across cognitive, attentional, behavioral, psycho-affective, and perceptual domains, and was assessed using multicomponent instruments, consistent with Diagnostic & Statistical Manual of Mental Disorders (DSM-5). PTCS was described as a transitional period during early recovery of consciousness, assessed using a multidimensional observational tool, and characterized by attentional and executive disturbances, such as disorientation, slowed processing, attention deficits, as well as fluctuating emotional and behavioral responses, consistent with the case definition. CONCLUSION:Although overlapping features exist, PTA, agitation, delirium, and PTCS differ in underlying constructs and temporal framing. Refining definitions to better integrate behavioral and psycho-affective features and clarify transitional phases may improve conceptual and diagnostic clarity in acute TBI.
OBJECTIVE:To investigate the influence of resilience on quality of life (QoL) in patients with mild traumatic brain injury (mTBI), and to evaluate the mediating roles of sleep quality and depression in the relationship. Setting: Emergency and neurosurgical outpatient departments in regional medical center in northern Taiwan. PARTICIPANTS:A total of 310 adults patients diagnosed with mTBI were recruited between 3 and 12 months postinjury. DESIGN:A cross-sectional observational study using self-report measures and serial-mediation analysis. MAIN MEASURES:Participants completed the Resilience Scale for Adults, Pittsburgh Sleep Quality Index, Beck Depression Inventory-II, and the WHO Quality of Life-BREF. Data were analyzed using PROCESS Model 6 with 5000 bootstrap resamples. RESULTS:Resilience was associated with improved QoL, both directly and indirectly through sleep quality and depression. In particular, resilience predicted higher sleep quality and fewer depressive symptoms. Poor sleep quality was associated with greater depressive symptoms, which in turn predicted lower QoL. All direct and indirect pathways in the serial mediation model were significant (P < 0.001), and the model explained 54% of the variance in QoL. CONCLUSION:Our findings suggest that resilience influences QoL through sleep quality and depression. Enhancing resilience and sleep quality may reduce depressive symptoms and improve overall well-being in patients recovering from mTBI.
AIMS:This multicenter retrospective cohort study aimed to develop 3 predictive models to estimate consciousness status 3 months after admission. These models were designed to serve as complementary prognostic tools for patients diagnosed with unresponsive wakefulness syndrome (UWS) using the Coma Recovery Scale-Revised (CRS-R). METHODS:We retrospectively collected data from 154 patients with UWS across 2 clinical centers, encompassing demographic, clinical, and laboratory biomarkers. Variable selection was performed using adaptive least absolute shrinkage and selection operator (LASSO) and ridge regression. The final predictive models were constructed using binary logistic regression, while additional machine-learning algorithms (Random Forest, SVM, and XGBoost) were applied for comparative evaluations of predictive performance. RESULTS:Of the patients studied, 88 (57%) regained responsiveness within 3 months, while 66 (43%) remained in UWS. Model UWS-base, incorporating clinical factors such as traumatic brain injury (TBI), hypoxic encephalopathy, hydrocephalus, and diffuse injury, demonstrated utility for outpatient preliminary screening. Model UWS-plus achieved superior accuracy (AUC = 0.84) by integrating key biomarkers, including fT3, albumin score, lymphocyte count, and alkaline phosphatase. Model UWS-lite, retaining only lymphocyte count alongside clinical variables, maintained robustness in resource-limited settings (AUC = 0.83). Notably, these biomarkers emerged as factors potentially associated with recovery, generating hypotheses for future interventional studies. CONCLUSION:We propose a biomarker-integrated model that complements the prognosis of UWS. Our findings also encourage a more holistic approach to clinical practice, wherein hydrocephalus management and systemic biomarkers may be considered alongside traditional scales to inform prognosis and guide therapeutic decisions.
OBJECTIVE:To evaluate validity, reliability, and targeting of the Norwegian 7-item Fatigue Severity Scale (FSS-7) in adults with moderate-to-severe traumatic brain injury (TBI). SETTING:Inpatient and outpatient acute care and postacute rehabilitation facilities. PARTICIPANTS:Ninety-four patients with intracranial injury, 20% women, with a mean age of 45.8 years (SD = 13.6), provided 185 complete FSS-7 responses at 6 months (n = 94) and 12 months (n = 91) post-TBI. DESIGN:Secondary analysis of data from a longitudinal observational study using the Rasch model and graphical log-linear Rasch models (GLLRM). MAIN MEASURES:The FSS-7 is a self-report fatigue measure derived from the original FSS by omitting items 1 and 2. Differential item functioning (DIF) was examined for sex, age, education, and sleep disturbances (Epworth sleepiness scale and insomnia severity index). RESULTS:The FSS-7 did not fit the Rasch model due to poor fit of item 4 and local dependence between items 5 and 6. A 6-item version (FSS-6), excluding item 4, provided good fit to a GLLRM accounting for the local dependence between items 5 and 6. No DIF or item parameter drift over time was detected. The FSS-6 demonstrated excellent reliability (r = 0.936), while targeting was less than optimal, as on average, only 57% of the maximum obtainable test information was reached. CONCLUSIONS:The FSS-6, excluding item 4, provides a valid measure of fatigue with excellent reliability for adults at 6 and 12 months post-TBI. The total raw score is invariant across sex, age, educational level, and sleep disturbances with no item parameter drift from 6 to 12 months postinjury. The FSS-6 may be useful for screening and monitoring fatigue in TBI rehabilitation and research, although a reassessment of targeting is recommended for future research on a larger and broader sample of patients.
OBJECTIVE:Episodic memory is one of the cognitive domains most affected after a traumatic brain injury (TBI), and memory decline is a hallmark of both normal aging and Alzheimer disease (AD). Although TBI is reported to accelerate age-related cognitive decline and brain atrophy, it is unclear how this trajectory is shaped by frequent co-occurring factors such as post-traumatic stress disorder (PTSD) and psychotropic medication use. This study tested whether age-related decline in delayed verbal memory is more pronounced among adults with a history of TBI than those without TBI. Analyses also explored PTSD status and use of selective serotonin reuptake inhibitors or serotonin-norepinephrine reuptake inhibitors (SSRIs/SNRIs) as independent moderators of verbal memory performance. SETTING:VA Medical Center and surrounding community. PARTICIPANTS:Sixty-two Veterans and civilians, ages 30-65, were enrolled. Participants who performed below established cutoffs on performance validity testing were excluded. Analyses (n = 56) included 28 adults with a history of TBI (82% mild, 18% moderate) and 28 demographically matched controls without TBI. MAIN MEASURES:Delayed recall on a standardized verbal memory task was the primary outcome measure. Analyses tested for main effects of TBI status, age, and their interaction, as well as interactions with the moderator variables (PTSD status and SSRI/SNRI use). DESIGN:Observational, cross-sectional design. RESULTS:Participants with a TBI history did not significantly differ from those without TBI in verbal memory performance. There was a trend toward poorer memory performance with age among participants with a TBI history not taking SSRIs/SNRIs, while participants with PTSD and TBI taking SSRIs/SNRIs demonstrated better performance with age. CONCLUSION:The findings underscore the importance of considering psychiatric comorbidities and medication use when examining cognition and aging effects in individuals with TBI. Larger, longitudinal studies are warranted to clarify how traumatic stress and psychotropic medications may mediate cognitive aging trajectories after TBI.
OBJECTIVE:This study examined 1) longitudinal trajectories of depression and suicidal ideation (SI) trajectories over the first 10 years after traumatic brain injury (TBI) in a sample of Asian American and Pacific Islander (AAPI) individuals; 2) demographic and injury-related predictors of these trajectories; and 3) time-varying depression symptoms as predictors of SI. SETTING:Participants who completed inpatient rehabilitation at a TBI Model Systems (TBIMS) center. PARTICIPANTS:Three hundred seven AAPI participants with moderate-to-severe TBI. DESIGN:Multisite, longitudinal observational cohort study. MAIN MEASURES:Patient Health Questionnaire (PHQ-9) completed at least once for any follow-up time point (ie, 1, 2, 5, or 10 years after TBI), demographic variables, functional characteristics, and injury characteristics. Depression was assessed using PHQ-8 total score, and SI was assessed from the PHQ-9 item 9 score. RESULTS:Rates of clinically significant depression symptoms ranged from 10.1% to 20.6% over 10 years across the 4 time points. Depression symptom trajectories remained flat over time. Higher education was associated with lower overall depression trajectories, whereas a prior history of mental health treatment and violent cause of injury were associated with higher depression trajectories. SI trajectories also remained stable, with higher overall levels observed among participants who were unmarried at injury, were employed at injury, and had a lifetime history of suicide attempts. Higher depression symptoms-both within individuals over time and between individuals-were associated with higher SI. CONCLUSION:The findings reinforce the importance of detection, long-term monitoring, and targeted support through culturally responsive mental health services for AAPI individuals with TBI.
OBJECTIVE:Cyberscams represent a significant global crime. As a result of injury-related cognitive and social difficulties, individuals with acquired brain injury (ABI) may experience greater difficulty recognizing cyberscams, learning cybersafety, and seeking appropriate help. This study aimed to objectively examine the association between cognitive function and cyberscam risk in people with and without ABI. We hypothesized that poorer cognitive functioning would be associated with poorer cybersafety and higher frequency of scam experiences. PARTICIPANTS:Participants were recruited from a larger longitudinal traumatic brain injury outcome study through research databases, social media, and word-of-mouth. Participants with and without ABI were eligible if they were aged ≥18 years, living within Australia or New Zealand, and fluent in English. The final sample comprised 85 participants with and 94 without ABI. DESIGN:Cross-sectional design. MEASURES:Participants completed an online survey including demographic and cyberscam questions and The CyberAbility Scale, followed by a phone-administered cognitive assessment battery (Brief Test of Adult Cognition by Telephone [BTACT]). RESULTS:Group differences in standardized BTACT scores were examined using 2-sample t-tests and Wilcoxon rank sum tests, and Spearman correlations were run between BTACT and CyberAbility Scale scores. Mediation analysis evaluated the role of cognition in the relationship between ABI and cybersafety. Those reporting prior scam experience showed significantly poorer executive function and overall cognition in both groups. Worse self-rated cybersafety on The CyberAbility Scale was significantly associated with poorer overall cognition. The association between ABI and cybersafety was primarily mediated through cognition. CONCLUSIONS:Findings highlight the association of cognitive impairment, particularly executive dysfunction, with increased cyberscam vulnerability. People with ABI, who commonly experience such cognitive impairments, represent a high-risk group, underscoring the need for tailored cybersafety resources that accommodate for cognitive impairment.
OBJECTIVE:To compare head motion capacity during a prescribed in-laboratory task with head motion performance in free-living daily life in individuals with mild traumatic brain injury (mTBI) and healthy controls. A secondary objective was to assess whether in-laboratory peak head motion metrics were associated with near maximal (95th percentile) free-living movements. SETTING:Research laboratory and participants' daily environments over 7 days of continuous monitoring. PARTICIPANTS:Twenty-three adults participated: 10 individuals with subacute, symptomatic mTBI (5F; age 30.3 (7.7) years; 35.2 (20.1) days postinjury) and 13 healthy controls (7F; age 31.9 (9.6) years). Participants were free of neurological, musculoskeletal, or balance-affecting conditions. DESIGN:Observational study combining a laboratory gait task with horizontal head turns and a 7-day free-living monitoring period using wearable inertial sensors on the head and lumbar spine. MAIN OUTCOME MEASURES:In-laboratory head turn amplitude and peak angular velocity (capacity); daily-life amplitude and angular velocity distributions (mean, median, 95th percentile), intra- and interday variability (performance); and associations with free-living measures. RESULTS:Individuals with mTBI demonstrated slower in-laboratory head turns than controls (223.53 (62.32) deg/s versus 302.01 (55.88) deg/s; P = 0.006), with no difference in amplitude. Daily-life amplitude and velocity did not differ between the groups. However, mTBI participants showed consistently smaller intra- and interday variability (P < 0.05), indicating more constrained daily movement patterns. Associations between in-laboratory peaks and free-living 95th percentile values were weak (r = -0.22 for amplitude; r = 0.10 for angular velocity). CONCLUSION:Although mTBI participants show reduced head motion capacity in laboratory tasks, their average daily-life kinematics are comparable to healthy adults. Reduced variability suggests constrained free-living movement strategies. These findings highlight the dissociation between capacity and performance and support integrating both laboratory assessments and continuous monitoring as complementary measures to fully characterize motor behavior following mTBI.
OBJECTIVE:To determine if remote military mild traumatic brain injury (mTBI) is uniquely associated with deficits in global metacognition, independent of psychopathology. SETTING:Translational Research Center for TBI and Stress Disorders, VA Boston Healthcare System. PARTICIPANTS:A total of 567 community-dwelling post-9/11 veterans (mean age = 34): 182 veterans with no mTBI, 134 with at least one nonmilitary mTBI, and 251 with at least one military mTBI. Exclusion criteria were severe neurologic, psychiatric, or cognitive impairment; moderate/severe TBI; or effort-measure failure. DESIGN:Cross-sectional examining predictors of global metacognition of cognitive abilities. MAIN MEASURES:Global metacognitive bias, calculated as self-reported cognition (WHODAS-II Understanding/Communicating) minus objective cognitive performance (attention, memory, executive composite). Secondary measures included self-reported and objective cognition and global metacognitive sensitivity (correlation between self-reported and objective cognition). RESULTS:Self-reported cognition scores for veterans with remote military mTBI were significantly lower than their objective cognition scores, resulting in significantly more negative metacognitive bias (M = -0.27, SD = 1.05) than those with a nonmilitary mTBI (M = 0.24, SD = 0.84) or no mTBI (M = 0.33, SD = 0.99). Notably, this effect remained significant after accounting for post-traumatic stress disorder (PTSD), depression, and anxiety/stress. It was not explained by blast exposure, peritraumatic context, or time since last mTBI, although it was modestly related to lifetime mTBI count. CONCLUSION:Military mTBI is associated with more negative metacognitive bias independent of psychiatric conditions. Such bias may impede recovery and treatment effectiveness, suggesting that metacognitive interventions could be a valuable component of mild TBI care.
