The differential impact of COVID-19 on mental health: Implications of ethnicity, sexual orientation, and disability status in the United States.

The COVID-19 pandemic's effects on mental health interact with preexisting health risks and disparities to impact varying populations differently. This study explored the relationship between demographic variables (e.g., ethnicity, sexual orientation, and disability status), distress and mental health (e.g., depression, anxiety, somatic complaints, and pandemic distress), and vulnerability factors for COVID-19 (e.g., personal health vulnerabilities, community members' health vulnerabilities, and environmental exposure risks at work or home). An online cross-sectional study was conducted from 18 June to 17 July 2020, reflecting the impact of early phase COVID-19 pandemic and related shelter-in-place measures in the United States. Participants were adults residing in the United States (N = 594), with substantial subsamples (N ≥ 70) of American Indian, Asian American, African-American, and Hispanic and/or Latinx participants, as well as people with disabilities and sexual minorities. Outcomes measured were depression, hopelessness, somatic complaints, anxiety-related disorders, locus of control (LOC), and a novel measure of pandemic-related distress. Data were analyzed using analyses of covariance (ANCOVA), chi-square test, and correlation coefficients. Generally, younger individuals, and those with less financial power-across all identities-suffered more distress. When controlling for age, lower financial power was associated with higher scores on the Center for Epidemiologic Studies Depression Scale-Revised (CESD-R; r = -0.21, p = < 0.001), Beck Hopelessness Scale (BHS; r = -0.17, p < 0.001), Patient Health Questionnaire-15 (PHQ-15; r = -0.09, p = 0.01), Screen for Child Anxiety Related Emotional Disorders for Adults Panic Disorder (SCARED-A PD; r = -0.14, p < 0.001), SCARED-A generalized anxiety disorder (GAD; r = -0.13, p = 0.002), SCARED-A obsessive-compulsive disorder (OCD; r = -0.08, p = 0.04), and the COVID-19 Pandemic Distress restriction/disconnection scale (C19PDS; r = -0.10, p = 0.009). In addition, disparities were found, in general, for marginalized identities by gender, sexual orientation, and disability status. Importantly, each ethnicity subsample showed a unique pattern of relationships between COVID-19 risk variables and mental health symptoms. The results support the hypothesis that any pandemic may amplify preexisting social and financial disparities. Overall, interventions at the clinical, governmental, or health equity level should take into consideration the needs of vulnerable groups.

Assessment of Follow-up Care After Emergency Department Presentation for Mild Traumatic Brain Injury and Concussion: Results From the TRACK-TBI Study.

Importance: Mild traumatic brain injury (mTBI) affects millions of Americans each year. Lack of consistent clinical practice raises concern that many patients with mTBI may not receive adequate follow-up care. Objective: To characterize the provision of follow-up care to patients with mTBI during the first 3 months after injury. Design, Setting, and Participants: This cohort study used data on patients with mTBI enrolled in the Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) study between February 26, 2014, and August 25, 2016. We examined site-specific variations in follow-up care, the types of clinicians seen by patients receiving follow-up care, and patient and injury characteristics associated with a higher likelihood of receiving follow-up care. The TRACK-TBI study is a prospective, multicenter, longitudinal observational study of patients with TBI presenting to the emergency department of 1 of 11 level I US trauma centers. Study data included patients with head trauma who underwent a computed tomography (CT) scan within 24 hours of injury, had a Glasgow Coma Scale score of 13 to 15, were aged 17 years or older, and completed follow-up care surveys at 2 weeks and 3 months after injury (N = 831). Main Outcomes and Measures: Follow-up care was defined as hospitals providing TBI educational material at discharge, hospitals calling patients to follow up, and patients seeing a physician or other medical practitioner within 3 months after the injury. Unfavorable outcomes were assessed with the Rivermead Post Concussion Symptoms Questionnaire. Results: Of 831 patients (289 [35%] female; 483 [58%] non-Hispanic white; mean [SD] age, 40.3 [16.9] years), less than half self-reported receiving TBI educational material at discharge (353 patients [42%]) or seeing a physician or other health care practitioner within 3 months after injury (367 patients [44%]). Follow-up care varied by study site; adjusting for patient characteristics, the provision of educational material varied from 19% to 72% across sites. Of 236 patients with a positive finding on a CT scan, 92 (39%) had not seen a medical practitioner 3 months after the injury. Adjusting for injury severity and demographics, patient admission to the hospital ward or intensive care unit, patient income, and insurance status were not associated with the probability of seeing a medical practitioner. Among the patients with 3 or more moderate to severe postconcussive symptoms, only 145 of 279 (52%) reported having seen a medical practitioner by 3 months. Conclusions and Relevance: There are gaps in follow-up care for patients with mTBI after hospital discharge, even those with a positive finding on CT or who continue to experience postconcussive symptoms.

Long-term disability and survival in traumatic brain injury: results from the National Institute on Disability and Rehabilitation Research Model Systems.

OBJECTIVES: To document long-term survival in 1-year survivors of traumatic brain injury (TBI); to compare the use of the Disability Rating Scale (DRS) and FIM as factors in the estimation of survival probabilities; and to investigate the effect of time since injury and secular trends in mortality. DESIGN: Cohort study of 1-year survivors of TBI followed up to 20 years postinjury. Statistical methods include standardized mortality ratio, Kaplan-Meier survival curve, proportional hazards regression, and person-year logistic regression. SETTING: Postdischarge from rehabilitation units. PARTICIPANTS: Population-based sample of persons (N=7228) who were admitted to a TBI Model Systems facility and survived at least 1 year postinjury. These persons contributed 32,505 person-years, with 537 deaths, over the 1989 to 2011 study period. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURE: Survival. RESULTS: Survival was poorer than that of the general population (standardized mortality ratio=2.1; 95% confidence interval, 1.9-2.3). Age, sex, and functional disability were significant risk factors for mortality (P<.001). FIM- and DRS-based proportional hazards survival models had comparable predictive performance (C index: .80 vs .80; Akaike information criterion: 11,005 vs 11,015). Time since injury and current calendar year were not significant predictors of long-term survival (both P>.05). CONCLUSIONS: Long-term survival prognosis in TBI depends on age, sex, and disability. FIM and DRS are useful prognostic measures with comparable statistical performance. Age- and disability-specific mortality rates in TBI have not declined over the last 20 years. A survival prognosis calculator is available online (http://www.LifeExpectancy.org/tbims.shtml).

Economic factors and longevity in spinal cord injury: a reappraisal.

OBJECTIVE: To review and reassess the findings of Krause and colleagues on the effect of economic and other risk factors on life expectancy after spinal cord injury, using an expanded and updated database. DESIGN: Pooled person-year analysis. SETTING: Model Spinal Cord Injury Systems hospitals. PARTICIPANTS: A total of 7331 persons injured since 1973 who were enrolled in the National Spinal Cord Injury Database and received an evaluation between November 1995 and December 2005. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Mortality, determined by routine follow-up supplemented by information from the Social Security Death Index. Logistic regression models based on the predictor variables were developed to estimate the chance of dying in a given year. RESULTS: As in the Krause study, life expectancies of persons with the greatest handicap in economic self-sufficiency were substantially shorter than average. However, the positive effect of favorable economics was much less than previously reported, largely because having health insurance coverage through workers' compensation was no longer a powerful (or statistically significant) predictor of survival. CONCLUSIONS: The beneficial effect of favorable economics appears to be much less than previously reported. Further, the interpretation of the effects of modifiable factors (such as economics and social integration) is complicated by questions of cause and effect.