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Patient health literacy is vital to clinical trial engagement. Knowledge and beliefs about clinical trials may contribute to patient literacy of clinical trials, influencing engagement, enrollment and retention. We developed and assessed a survey that measures clinical trial health knowledge and beliefs, known as the Clinical trial HEalth Knowledge and belief Scale (CHEKS). The 31 survey items in CHEKS represent knowledge and beliefs about clinical trial research (n = 409) in 2017. We examined item-scale correlations for the 31 items, eliminated items with item-scale correlations less than 0.30, and then estimated internal consistency reliability for the remaining 25 items. We used the comparative fit index (CFI) and the root mean squared error of approximation (RMSEA) to evaluate model fit. The average age of the sample was 34 (SD = 15.7) and 48% female. We identified 6 of the 31 items that had item-scale correlations (corrected for overlap) lower than 0.30. Coefficient alpha for the remaining 25 items was 0.93 A one-factor categorical confirmatory factor analytic model with 16 correlated errors was not statistically significant (chi-square = 10011.994, df = 300, p < 0.001) but fit the data well (CFI = 0.95 and RMSEA = 0.07). CHEKS can assess clinical trial knowledge and beliefs.

Patient health literacy is vital to clinical trial engagement. Knowledge and beliefs about clinical trials may contribute to patient literacy of clinical trials, influencing engagement, enrollment and retention. We developed and assessed a survey that measures clinical trial health knowledge and beliefs, known as the Clinical trial HEalth Knowledge and belief Scale (CHEKS). The 31 survey items in CHEKS represent knowledge and beliefs about clinical trial research (n = 409) in 2017. We examined item-scale correlations for the 31 items, eliminated items with item-scale correlations less than 0.30, and then estimated internal consistency reliability for the remaining 25 items. We used the comparative fit index (CFI) and the root mean squared error of approximation (RMSEA) to evaluate model fit. The average age of the sample was 34 (SD = 15.7) and 48% female. We identified 6 of the 31 items that had item-scale correlations (corrected for overlap) lower than 0.30. Coefficient alpha for the remaining 25 items was 0.93 A one-factor categorical confirmatory factor analytic model with 16 correlated errors was not statistically significant (chi-square = 10011.994, df = 300, p < 0.001) but fit the data well (CFI = 0.95 and RMSEA = 0.07). CHEKS can assess clinical trial knowledge and beliefs.

Azizi A Seixas,1,2 Arlener D Turner,2 Omonigho Michael Bubu,1,2 Girardin Jean-Louis,1,2 Mony J de Leon,3 Ricardo S Osorio,2 Lidia Glodzik3 1New York University Grossman School of Medicine, Department of Population Health, New York, NY, 10016, USA; 2New York University Grossman School of Medicine, Department of Psychiatry, New York, NY, 10016, USA; 3Weill Cornell Medicine, Department of Radiology, New York, NY, 10021, USACorrespondence: Azizi A SeixasDepartments of Population Health and Psychiatry, New York University Grossman School of Medicine, 180 Madison Avenue, Office # 715, New York, NY, 10016, USATel +1 646-501-3430Fax +1 212-263-4595Email Azizi.Seixas@nyulangone.orgObjective: Compared to European Americans, research indicates that African Americans have higher white matter hyperintensity (WMH) load; however, the clinical and biological bases underlying this higher burden are poorly understood. We hypothesize that obesity may explain differences in WMH between African and European Americans.Methods: Participants enrolled in longitudinal brain aging studies (n=292; 61% Female; 92% European American; mean age=69.6± 7.7) completed evaluations including medical exams, neuroimaging, and sociodemographic surveys. Overweight/obese status defined as body mass index ≥ 30 kg/m2, and WMH load, captured by FLAIR images, as sum of deep and periventricular volumes, scored using the Fazekas scale (0– 6), WMH≥ 4 considered high.Results: Logistic regression analyses, adjusted for age, sex, hypertension, and smoking history, indicated that age and interaction between race and obesity were significant predictors of WMH, demonstrating that obesity significantly moderated the relationship between race and WMH. Age independently increased the odds of high WMH by 16% (OR=1.16, 95% CI=1.09– 1.23, p< 0.001). Stratified analysis indicates that older European Americans had increased WMH (OR=1.17, 95% CI=1.09– 1.23, p< 0.001), while obese African Americans had increased

Sleep medicine is well positioned to benefit from advances that use big data to create artificially intelligent computer programs. One obvious initial application in the sleep disorders center is the assisted (or enhanced) scoring of sleep and associated events during polysomnography (PSG). This position statement outlines the potential opportunities and limitations of integrating artificial intelligence (AI) into the practice of sleep medicine. Additionally, although the most apparent and immediate application of AI in our field is the assisted scoring of PSG, we propose potential clinical use cases that transcend the sleep laboratory and are expected to deepen our understanding of sleep disorders, improve patient-centered sleep care, augment day-to-day clinical operations, and increase our knowledge of the role of sleep in health at a population level.

Sleep disparities exist among Hispanics/Latinos, although little work has characterized individuals at the United States (US)–Mexico border, particularly as it relates to acculturation. This study examined the association of Anglo and Mexican acculturation to various facets of sleep health among those of Mexican descent at the US–Mexico border. Data were collected from N = 100 adults of Mexican descent in the city of Nogales, Arizona (AZ). Surveys were presented in English or Spanish. Acculturation was assessed with the Acculturation Scale for Mexican-Americans (ARSMA-II). Insomnia was assessed with the Insomnia Severity Index (ISI), sleepiness was assessed with the Epworth Sleepiness Scale (ESS), sleep apnea risk was assessed with the Multivariable Apnea Prediction (MAP) index, weekday and weekend sleep duration and efficiency were assessed with the Sleep Timing Questionnaire, sleep quality was assessed with the Pittsburgh Sleep Quality Index (PSQI), and sleep duration and sleep medication use were assessed with PSQI items. No associations were found between Mexican acculturation and any sleep outcomes in adjusted analyses. Anglo acculturation was associated with less weekend sleep duration and efficiency, worse insomnia severity and sleep quality, and more sleep apnea risk and sleep medication use. These results support the idea that sleep disparities may depend on the degree of acculturation, which should be considered in risk screening and interventions.

Sleep disparities exist among Hispanics/Latinos, although little work has characterized individuals at the United States (US)–Mexico border, particularly as it relates to acculturation. This study examined the association of Anglo and Mexican acculturation to various facets of sleep health among those of Mexican descent at the US–Mexico border. Data were collected from N = 100 adults of Mexican descent in the city of Nogales, Arizona (AZ). Surveys were presented in English or Spanish. Acculturation was assessed with the Acculturation Scale for Mexican-Americans (ARSMA-II). Insomnia was assessed with the Insomnia Severity Index (ISI), sleepiness was assessed with the Epworth Sleepiness Scale (ESS), sleep apnea risk was assessed with the Multivariable Apnea Prediction (MAP) index, weekday and weekend sleep duration and efficiency were assessed with the Sleep Timing Questionnaire, sleep quality was assessed with the Pittsburgh Sleep Quality Index (PSQI), and sleep duration and sleep medication use were assessed with PSQI items. No associations were found between Mexican acculturation and any sleep outcomes in adjusted analyses. Anglo acculturation was associated with less weekend sleep duration and efficiency, worse insomnia severity and sleep quality, and more sleep apnea risk and sleep medication use. These results support the idea that sleep disparities may depend on the degree of acculturation, which should be considered in risk screening and interventions.

Girardin Jean-Louis,1 Arlener D Turner,1 Peng Jin,2 Mengling Liu,2 Carla Boutin-Foster,3 Samy I McFarlane,3 Azizi Seixas1 1Departments of Population Health, Psychiatry, and Biostatistics, New York University Langone Health, New York, NY, USA; 2Department of Biostatistics, New York University Langone Health, New York, NY, USA; 3Departments of Medicine and Endocrinology, SUNY Downstate Medical Center, New York, NY, USACorrespondence: Girardin Jean-LouisNYU Grossman School of Medicine, 180 Madison Avenue, 7th Floor, New York, NY 10016, USATel +1 646.501.3431Email Girardin.Jean-Louis@nyulangone.orgAbstract: Mounting evidence shows a disproportionate COVID-19 burden among Blacks. Early findings indicate pre-existing metabolic burden (eg, obesity, hypertension and diabetes) as key drivers of COVID-19 severity. Since Blacks exhibit higher prevalence of metabolic burden, we examined the influence of metabolic syndrome on disparate COVID-19 burden. We analyzed data from a NIH-funded study to characterize metabolic burden among Blacks in New York (Metabolic Syndrome Outcome Study). Patients (n=1035) were recruited from outpatient clinics, where clinical and self-report data were obtained. The vast majority of the sample was overweight/obese (90%); diagnosed with hypertension (93%); dyslipidemia (72%); diabetes (61%); and nearly half of them were at risk for sleep apnea (48%). Older Blacks (age≥ 65 years) were characterized by higher levels of metabolic burden and co-morbidities (eg, heart disease, cancer). In multivariate-adjusted regression analyses, age was a significant (p≤ .001) independent predictor of hypertension (OR=1.06; 95% CI: 1.04– 1.09), diabetes (OR=1.03; 95% CI: 1.02– 1.04), and dyslipidemia (OR=0.98; 95% CI: 0.97– 0.99), but not obesity. Our study demonstrates an overwhelmingly high prevalence of the metabolic risk factors related to COVID-19 among Blacks in New York, highlighting disparate metabolic burden among Bla

Azizi A Seixas,1,2,* Debbie P Chung,1,* Shannique L Richards,1 Shreya Madhavaram,1 Preeti Raghavan,1,3 Juan Gago,1,4 George Casimir,1,5 Girardin Jean-Louis1,2 1Department of Population Health, Center for Healthful Behavior Change, NYU Langone Health, NY, New York, USA; 2Department of Psychiatry, Center for Healthful Behavior Change, NYU Langone Health, NY, New York, USA; 3Department of Rehabilitation Medicine, NYU Langone Health, NY, New York, USA; 4Cervical Cancer Prevention Program, National Cancer Institute of Argentina, Buenos Aires, Argentina; 5Department of Psychiatry, SUNY Downstate Medical Center, Brooklyn, NY, USA *These authors contributed equally to this work Objective: Stroke survivors generally have problems completing instrumental activities of daily living (IADL; eg, preparing meals, chores, taking a bath, and managing finances). However, it is unclear how stroke survivors might stave off IADL issues. Studies indicating that sleep has restorative neurological effects provide potential mechanisms to address issues with IADL. The aim of this study was to ascertain the association between sleep duration (short or long sleep duration) and IADL among stroke survivors and those without a stroke history.Methods: Data of 486,619 participants were analyzed from the 2000 to 2015 National Health Interview Survey (NHIS), a nationally representative sample. Measures of self-reported stroke, sociodemographic variables, sleep duration, and IADL problems were collected. Binary logistic regression was utilized to analyze the relationship of short (≤6 hours) and long (≥9 hours) sleep duration with limitations to IADL.Results: Of the sample, 3% reported a physician-diagnosed stroke event. The mean age was 45.73 years; 52.7% were female; 77.4% were White; 14.2% were Black; 41.3% were married, 62.7% were employed; 31.1% reported that annual family income was less than $35,000; 87% reported good-to-excellent health; and 29.7% reported short sleep (≤6 h

Azizi A Seixas,1 Joao V Nunes,2 Collins O Airhihenbuwa,3 Natasha J Williams,1 Seithikurippu Ratnas Pandi-Perumal,1 Caryl C James,4 Girardin Jean-Louis11Center for Healthful Behavior Change, Department of Population Health, Division of Population Health, New York University School of Medicine, 2Sophie Davis School of Biomedical Education, City College of New York, New York, NY, USA; 3Department of Biobehavioral Health, The Pennsylvania State University, State College, PA, USA; 4Department of Sociology, Psychology and Social Work, The University of the West Indies, Mona, JamaicaObjective: The objective of the study was to examine the independent association of emotional distress with unhealthy sleep duration (defined as <7 or >8 hours).Methods: Data from the 2009 National Health Interview Survey (NHIS), a cross-sectional household survey, were analyzed to investigate the associations of emotional distress with unhealthy sleep durations, adjusting for sociodemographic factors, health risks, and chronic diseases through hierarchical multiple logistic regression analysis.Participants: A total of 27,731 participants (age range 18–85 years) from the NHIS 2009 dataset were interviewed.Measures: Unhealthy sleep duration is defined as sleep duration <7 or >8 hours, whereas healthy sleep is defined as sleep duration lasting for 7–8 hours. Emotional distress is based on the Kessler 6 Non-Specific Distress Battery, which assesses the frequency of feeling sad, nervous, restless, hopeless, worthless, and burdened, over a 30-day period.Results: Of the sample, 51.7% were female; 83.1% were white and 16.9% were black. Eleven percent experienced emotional distress and 37.6% reported unhealthy sleep. Adjusted logistic regression analysis revealed that individuals with emotional distress had 55% greater odds of reporting unhealthy sleep (odds ratio [OR] =1.55, 95% confidence interval [CI] =1.42, 1.68, P<0.001).Conclusion: Emotional

This study examined the relationship between chronic cumulative community strain (CCCS), such as exposure to violence and poverty, and delinquency, in a sample of 74 African American adolescent boys. In addition, the moderational effects of positive coping, family cohesion, authoritarian parenting styles, prosocial involvement and male identity on the relationship between CCCS and delinquency were examined. Results demonstrate the significant main effect associations between exposure to violence and delinquency and SES and delinquency provide support for chronic cumulative community strain being associated with delinquency. In addition, negative coping and family conflict were related to delinquency, but the relationship was not significant after controlling for their relationship to exposure to violence. The current study also showed that a reference group nondependent (RGND) male identity moderated the positive relationship between violence victimization and delinquent behavior. In addition, the study showed that the no reference group identity had a buffering effect in which African American boys who have low levels of this identity status and have experienced being a victim of violence are less likely to be involved in delinquent behavior. Positive coping, family cohesion, authoritarian parenting styles, and prosocial involvement did not significantly moderate the relationship between CCCS and delinquency.

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