Faculty Bibliography

PURPOSE OF REVIEW/OBJECTIVE:In this current review, we describe the benefits of community-based and "precision and personalized population health" (P3H) approaches to assessing and addressing sleep health problems and sleep-related cardiovascular diseases (CVD) among vulnerable populations such as racial/ethnic minorities, the elderly, and the socioeconomically disadvantaged. RECENT FINDINGS/RESULTS:Very few sleep health programs utilize a community-based or P3H approach, which may account for low estimates of sleep health problems, related CVD outcomes, and inadequate healthcare infrastructure to address sleep-related health outcomes at the community and population level. We describe community-based and P3H approaches and programs as solutions to accurately capture estimates of sleep health and reduce burden of sleep health problems and corollary CVD outcomes at the level of the community and population. Specifically, we describe seven critical steps needed to successfully implement a community-based and P3H approach to address sleep health problems. Community-based and P3H approaches are effective strategies to assessing and addressing sleep health problems and related health conditions.

BACKGROUND:Participation in clinical trials among people of color remains low, compared with white subjects. This protocol describes the development of "Advancing People of Color in Clinical Trials Now!" (ACT Now!), a culturally tailored website designed to influence clinical trial decision making among people of color. OBJECTIVE:This cluster randomized study aims to test the efficacy of a culturally tailored website to increase literacy, self-efficacy, and willingness to enroll in clinical trials among people of color. METHODS:ACT Now! is a randomized trial including 2 groups: (1) intervention group (n=50) with access to the culturally tailored website and (2) control group (n=50) exposed to a standard clinical recruitment website. Clinical trial literacy and willingness to enroll in a clinical trial will be measured before and after exposure to the website corresponding to their assigned group (intervention or control). Surveys will be conducted at baseline and during the 1-month postintervention and 3-month follow-up. Website architecture and wireframing will be informed by the literature and experts in the field. Statistical analysis will be conducted using a two-tailed t test, with 80% power, at .05 alpha level, to increase clinical trial literacy, self-efficacy, and willingness to enroll in clinical trials 3 months post intervention. RESULTS:We will design a culturally tailored website that will provide leverage for community stakeholders to influence clinical trial literacy, self-efficacy, and willingness to enroll in clinical trials among racial and ethnic groups. ACT Now! applies a community-based participatory research approach through the use of a community steering committee (CSC). The CSC provides input during the research study conception, development, implementation, and enrollment. CSC relationships help foster trust among communities of color. ACT Now! has the potential to fill a gap in clinical trial enrollment among people of color through an accessible web-based website. This study was funded in July 2017 and obtained institutional review board approval in spring 2017. As of December 2019, we had enrolled 100 participants. Data analyses are expected to be completed by June 2020, and expected results are to be published in fall 2020. CONCLUSIONS:ACT Now! has the potential to fill an important gap in clinical trial enrollment among people of color through an accessible web-based website. TRIAL REGISTRATION/BACKGROUND:ClinicalTrials.gov NCT03243071; https://clinicaltrials.gov/ct2/show/NCT00102401. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)/UNASSIGNED:DERR1-10.2196/17589.

Patient nonadherence to healthy lifestyle behaviors and medical treatments (like medication adherence) accounts for a significant portion of chronic disease burden. Despite the plethora of behavioral interventions to overcome key modifiable/nonmodifiable barriers and enable facilitators to adherence, short- and long-term adherence to healthy lifestyle behaviors and medical treatments is still poor. To optimize adherence, we aimed to provide a novel mobile health solution steeped in precision and personalized population health and a pantheoretical approach that increases the likelihood of adherence. We have described the stages of a pantheoretical approach utilizing tailoring, clustering/profiling, personalizing, and optimizing interventions/strategies to obtain adherence and highlight the minimal engineering needed to build such a solution.

BACKGROUND:This study examined the relationships between resilience and sleep disturbance in a diverse sample of older women with a history of hypertension and whether this relationship is moderated by individuals' race/ethnicity. METHODS:Sample includes 700 females from a community-based study in Brooklyn, New York with a mean age of 60.7 years (SD=6.52). Of the participants, 28.1% were born in the U.S.; 71% were African-descent, 17.4% were European and 11.6% were Hispanics descents. Data were gathered on demographics and sleep disturbance using the Comprehensive Assessment and Referral Evaluation (CARE) and the Stress Index Scale (SIS). Resilience Factors were assessed with both the Index of Self-Regulation of Emotion (ISE) and religious health beliefs. Chi-Square, Anova, Student t-tests, and multilinear regression analysis were conducted to explore associations between resilience factors and sleep disturbance. Associations between resilience factors and sleep disturbance were examined using stratified multilinear regression analysis in three models by race/ethnicity. Regression models was conducted examining the interaction between resilience factors and stress RESULTS: Resilience factor, ISE emerged as the strongest independent predictor of sleep disturbance [B(SE) = -0.368(0.008); p < .001] for African descents. ISE was not a significant predictor of sleep disturbance among Hispanic participants [B(SE) = -0.218(0.022);p = .052], however interaction effect analysis revealed that stress level moderates significantly the relationship between ISE, and their sleep disturbance [B(SE) = 0.243(0.001);p = .036]. CONCLUSIONS:Results of our study suggest that resilience factors might be a more important protective factor for sleep disturbance among diverse older females.

Previous epidemiologic studies have examined the relationship between sleep disturbances with prostate cancer (PCa) risk and/or survival. However, less has been published about the impact of sleep disturbance on quality of life for PCa survivors and their caregivers. Although PCa presents numerous potential barriers to sleep (e.g. hot flashes, nocturia), current survivorship guidelines do not address sleep. In addition to its impact on quality of life, sleep disturbances also mediate the impact of cancer status on missed days from work and healthcare expenditures.

BACKGROUND:Population estimates of sleep duration and quality are inconsistent because they rely primarily on self-reported data. Passive and ubiquitous digital tracking and wearable devices may provide more accurate estimates of sleep duration and quality. OBJECTIVE:This study aimed to identify trends in sleep duration and quality in New York City based on 2 million nights of data from users of a popular mobile sleep app. METHODS:We examined sleep duration and quality using 2,161,067 nights of data captured from 2015 to 2018 by Sleep Cycle, a popular sleep-tracking app. In this analysis, we explored differences in sleep parameters based on demographic factors, including age and sex. We used graphical matrix representations of data (heat maps) and geospatial analyses to compare sleep duration (in hours) and sleep quality (based on time in bed, deep sleep time, sleep consistency, and number of times fully awake), considering potential effects of day of the week and seasonality. RESULTS:Women represented 46.43% (1,003,421/2,161,067) of the sample, and men represented 53.57% (1,157,646/2,161,067) of individuals in the sample. The average age of the sample was 31.0 years (SD 10.6). The mean sleep duration of the total sample was 7.11 hours (SD 1.4). Women slept longer on average (mean 7.27 hours, SD 1.4) than men (mean 7 hours, SD 1.3; P<.001). Trend analysis indicated longer sleep duration and higher sleep quality among older individuals than among younger (P<.001). On average, sleep duration was longer on the weekend nights (mean 7.19 hours, SD 1.5) than on weeknights (mean 7.09 hours, SD 1.3; P<.001). CONCLUSIONS:Our study of data from a commercially available sleep tracker showed that women experienced longer sleep duration and higher sleep quality in nearly every age group than men, and a low proportion of young adults obtained the recommended sleep duration. Future research may compare sleep measures obtained via wearable sleep trackers with validated research-grade measures of sleep.