OVERCOMING OBSTACLES TO RECRUITMENT AND COMMUNITY ENGAGEMENT DURING COVID-19 AND DEVELOPMENT OF A DIGITAL COMMUNITY OUTREACH PROGRAM

Introduction: COVID-19 disrupted traditional research infrastructures and processes most notably in-person community recruitment, especially in underrepresented populations like racial ethnic minorities. To find creative and effective strategies, our group implemented and tested the efficacy of a culturally tailored community outreach plan (COP) developed during the US COVID-19 pandemic. Methods: In February 2021, we developed an 11 step culturallytailored community outreach program to support the implementation of three NIH funded community-based sleep studies. The following steps include: (1) description of the situation statement, 2) definition of goals, 3) engagement of audience/stakeholders, 4) tailoring message, 5) defining incentives, 6) choice of outreach methods, 7) identification of spokesperson, 8) choice of tools to assess progress, 9) identification of media outlets, 10) creation of study timeline, and 11) implementation of the plan. The studies leveraged several recruitment channels: 1) community settings (Place of worship, “community recruiter”, health fairs, word of mouth, & healthcare providers/doctors' clinics), 2) online platforms (Facebook, Twitter, LinkedIn and Research Match), and 3) preexisting datasets in NYC. Results: All three studies successfully met recruitment goals. ESSENTIAL [n= 224, 69% females, mean age= 36], MOSAIC [n=109, 61% females;mean age= 64] and Latinx/Hispanics: DORMIR[n=260, 61.3% of female;32.4]. Among the three NYC cohorts, the most common recruitment channels were: preexisting datasets (74%), community settings (19%), & online platform (7%) for ESSENTIAL;preexisting datasets (85%) & community settings (15%) for MOSAIC, and (71.7%) online platform for DORMIR. However, the Miami cohorts came mostly from community settings 90% for Essential and 97% for MOSAIC. Conclusion: Overall, the TSCS community outreach plan seems to be an effective tool to engage minoritized populations in greater NY and Miami. Our current field experience indicates that recruitment channels must be adapted to age, and community resources. Limited access to technology, particularly among older Blacks seem to be a major barrier for field staff to successfully engage the disenfranchised communities.

COVID-19 IS ASSOCIATED WITH SHORTER SLEEP DURATION AMONG AMERICAN ADULTS

Introduction: The COVID-19 pandemic has deteriorated sleep health in the United States (U.S.) and worldwide. Most studies that have examined the association between COVID-19 and sleep outcomes have used a non-probability sampling with potential sampling bias and limited generalizability. We examined the association between diagnosed COVID-19 and sleep health in a large representative sample of civilian adults aged ≥18 years in the U.S. Methods: This study was based on data from the 2020 National Health Interview Survey (NHIS) of adults (n=17,636). Sleep health was captured by self-reported sleep quantity [(very short (≤ 4 hours), short (5-6 hours), healthy (7-8 hours), or long (≥9 hours)] and sleep complaints (trouble falling and staying asleep;with responses ranging from never to every day) in the past 30 days. To account for correlated residuals among the endogenous sleep outcomes, generalized structural equation modeling (GSEM) was conducted with COVID-19 diagnosis as the predictor of interest. Other covariates (age, sex, race/ethnicity, education, employment, poverty level, marital status, birthplace, health insurance, region of residence, metropolitan areas, number of children and adults in the household, obesity, and sleep medication) were included in the models. NHIS complex probability sampling design was accounted for in descriptive and GSEM analyses. Results: About 4.2% of adults had a positive COVID-19 diagnosis. Among them, 3.1% had very short sleep, 24.2% had short sleep, 59.9% had healthy sleep, and 12.8% had long sleep;37.0% had trouble falling some days, 10.9% most days, and 6.5% every day;and 33.7% had trouble staying asleep some days, 13.9% most days, and 6.6% every day. Findings from GSEM revealed that a history of COVID-19 almost doubled the odds of having short sleep (OR: 1.9;95% CI: 1.1-3.4;p=0.032). No significant associations were found between COVID-19 and the other sleep outcomes. Conclusion: Individuals with a COVID-19 diagnosis were more likely to report very short sleep, although they did not exhibit a greater likelihood of reporting more sleep complaints. Further research using longitudinal national data and examining environmental factors are needed to determine causality.

DOES COPING STRATEGY PROTECT SLEEP QUALITY DURING COVID-19? AN EXAMINATION OF RACIAL, ETHNIC, CULTURAL DIFFERENCES

Introduction: Little has been done to examine within/between group predictors and mediators of race/ethnic differences in sleep health outcomes, due to COVID-19 exposure. We evaluated the effect of COVID-19 exposure on sleep quality in a multiracial/ethnic sample of New York residents. Methods: We conducted a cross-sectional study among adults exposed to COVID-19 across New York State from September to November of 2020. Comparisons of participant characteristics e.g., mean scores by race/ethnicity status were made using one-way ANOVA for continuous variables, and chi-square tests for categorical variables. Associations between social determinants of health (employment, location), Trauma Coping Self-Efficacy (CES-T), and sleep quality (Pittsburgh Sleep Quality Index-PSQI) were examined using multilinear regression analysis stratified by race/ethnicity. Results: Of the 541 participants, 373 (68.9%) were female;mean age was 40.9 years (SD=15), 198 (36.6%) identified as Whites, 111 (20.5%) as Black, 97 (17.9%) as Hispanics, and 135(25%) identified as either Asians, Native-Americans, Pacific-Islanders. Sex was the strongest predictor [β = 1.335;p < .05] of sleep quality, but only among Whites. Trauma Coping Self-Efficacy was negatively associated with sleep quality among Asian, Native-American, or Pacific- Islander participants [β = -.114;p < .05 ];Black [β = -.099;p < .05] and White participants [β = -0.79;p < .05] but not among Latinos/ as [β = -.058;p = 0.71]. Conclusion: Coping Self-Efficacy moderated the effect of COVID-19 on sleep quality among some, but not all, racial/ethnic groups. While CSE-T scores during the first wave of COVID-19 acted as a protective factor for sleep quality among Asians, Native-Americans, and Pacific- Islanders, White and Black participants, this was not the case for Latinos/as/Hispanics residing in New York. Clinical interventions that are tailored for racial/ethnic, community and cultural needs may help to mitigate sleep problems associated with COVID-19 exposure.