Veteran perspectives of epilepsy care: Impact of Veteran satisfaction, knowledge, and proactivity.

OBJECTIVE: Veterans are at elevated risk of epilepsy due to higher rates of traumatic brain injury (TBI). However, little work has examined the extent to which quality of care is associated with key outcomes for Veterans with epilepsy (VWE). This study aimed to examine the impact of quality of care on three outcomes: patients' knowledge of epilepsy self-care, proactive epilepsy self-management, and satisfaction with care. METHOD: We conducted a cross-sectional study of Post-9/11 Veterans with validated active epilepsy who received VA care (n = 441). Veterans were surveyed on care processes using American Academy of Neurology epilepsy quality measures, and a patient-generated measure related to the use of emergency care. Outcome measures included epilepsy self-care knowledge, proactive epilepsy self-management, and satisfaction with epilepsy care. Covariates included sociodemographic and health status variables and a measure of patient-provider communication. An ordinary least-squares (OLS) regression model was used to determine if the quality of care was associated with the outcomes adjusting for multiple comparisons. RESULTS: Self-reported measures of quality of care were broadly associated with satisfaction with care and epilepsy knowledge. OLS modeling indicated that healthcare provider guidance on when to seek emergency care was significantly associated with higher Veteran satisfaction with care (p < 0.01). Veterans who were asked about seizure frequency at every visit by their provider also reported higher satisfaction with care (p < 0.01) and increased epilepsy knowledge (p < 0.01). Veteran-provider communication was positively associated with epilepsy knowledge and proactive epilepsy self-management. Veterans with epilepsy with drug resistance epilepsy were significantly less satisfied with their care and reported lower proactivity compared to epilepsy controlled with medications. Further analysis indicated Black VWEs reported lower scores on epilepsy self-care knowledge compared to Whites (p < 0.001). CONCLUSIONS: This study found that quality measures were associated with satisfaction and epilepsy knowledge but not associated with proactive self-management in multivariable models. The finding that better communication between providers and Veterans suggests that in addition to technical quality, interpersonal quality is important for patient outcomes. The secondary analysis identified racial disparities in epilepsy knowledge. This work offers opportunities to improve the quality of epilepsy care through the practice of patient-centered care models that reflect Veteran priorities and perceptions.

COVID-19 pandemic experiences among people with epilepsy: Effect on symptoms of co-occurring health conditions and fear of seizure.

OBJECTIVE: The Coronavirus disease 2019 (COVID-19) pandemic profoundly affected people worldwide, but little is known about how it impacted people with epilepsy (PWE). We examined the associations between COVID-19 stressors and health outcomes including increases in other health symptoms and fear of seizure among PWE. METHODS: This cross-sectional study used data from an online survey that asked about demographic characteristics, health conditions, and potential life stressors during COVID-19. Data were collected from October 30 to December 8, 2020. COVID-19 stressors were anger, anxiety, stress, healthcare access, fear of seeking healthcare, social isolation, sense of control over their lives, and alcohol consumption. A binary variable was created for each of these measures to indicate whether PWEs experienced a negative change versus a neutral or positive change. We used multivariable logistic regression to assess the associations of COVID-19 stressors with primary outcomes: exacerbated co-occurring health conditions and increasing fear of seizure during the pandemic. RESULTS: Of the 260 PWE included in the study, 165 (63.5%) were women; the average age was 38.7 years. During the survey administration period, 79 (30.3%) of the respondents reported exacerbated co-occurring health conditions, and 94 (36.2%) reported an increased fear of seizures. Regression results indicated that the fear of seeking healthcare during COVID-19 was associated with both exacerbated co-occurring health conditions (aOR 1.12; 95%CI 1.01-1.26) and increasing fear of seizure (aOR 2.31; 95%CI 1.14-4.68). Social isolation was associated with exacerbated co-occurring health conditions during COVID-19 (aOR 1.14; 95%CI 1.01-1.29). Reduced access to physical healthcare was associated with increasing fear of seizure (aOR 2.58; 95%CI 1.15-5.78). CONCLUSION: A considerable number of PWE experienced more symptoms of existing health conditions and fear of seizure during the initial year of the pandemic (2020). Fear of seeking healthcare services was associated with both negative outcomes. Assuring access to health care and reducing social isolation could potentially reduce negative outcomes for PWE. It is necessary to provide adequate support for PWE to reduce risks as COVID-19 continues to be a health concern.

Bridging Big Data: Procedures for Combining Non-equivalent Cognitive Measures from the ENIGMA Consortium.

Investigators in neuroscience have turned to Big Data to address replication and reliability issues by increasing sample sizes, statistical power, and representativeness of data. These efforts unveil new questions about integrating data arising from distinct sources and instruments. We focus on the most frequently assessed cognitive domain - memory testing - and demonstrate a process for reliable data harmonization across three common measures. We aggregated global raw data from 53 studies totaling N = 10,505 individuals. A mega-analysis was conducted using empirical bayes harmonization to remove site effects, followed by linear models adjusting for common covariates. A continuous item response theory (IRT) model estimated each individual's latent verbal learning ability while accounting for item difficulties. Harmonization significantly reduced inter-site variance while preserving covariate effects, and our conversion tool is freely available online. This demonstrates that large-scale data sharing and harmonization initiatives can address reproducibility and integration challenges across the behavioral sciences.