Faculty Bibliography

INTRODUCTION/UNASSIGNED:Young Black children experience poorer sleep health than children from other racial/ethnic groups. Tailored family-centered interventions are needed to improve sleep health among young Black children. Tailoring requires information about parent perceptions, practices and context. The purpose of this study was to (1) understand the contextual definition of sleep health for Black families; (2) bedtime routines and sleep practices among Black families; and (3) parent preferences that may inform intervention design. METHODS/UNASSIGNED:We engaged 30 Black parents of 3-8-year-old children with mild sleep problems (e.g., child takes >30 min to fall asleep at bedtime) in this study. Parents completed three ratings scales about sleep health practices and child bedtime behavior and a semi-structured interview. Statistical analysis included descriptive statistics and correlations. We used an implementation science rapid qualitative analysis approach to analyze qualitative data from the interviews. RESULTS/UNASSIGNED:The final sample identified as 52% African-American, 14% Jamaican, 10% Haitian, and 26% mixed multi-ethnic groups. Parent mean age was 41 years and child mean age were 5 years old. About 80% of responders were women. About one-third of the sample held a doctoral degree, and half the sample had a bachelor's or Master's degree. Parents answered 56% of sleep knowledge questions accurately (ranging from 32 to 100%) and reported an average of two sleep problems. Parents described healthy sleep as involving flexibility in sleep timing and bedtime routines. More than half of parents reported co-sleeping practices, with reasons ranging from a strategy to address night wakings, to a way to preserve bonding. Later child bedtime (after 9 pm) was associated with bedtime resistance, permissive parenting, and parent stress. Many parents reported that they had poor sleep quality and duration. DISCUSSION/UNASSIGNED:Findings elucidate a range of factors to consider in tailoring sleep health interventions for Black families of young children. These include the common practice of co-sleeping, parents' value for flexibility related to bedtime and bedtime routines, and parents' own challenges with getting enough and good quality sleep. Tailored family-centered interventions will benefit from considering these factors.

BACKGROUND:Best practices for engaging patients and the community in biomedical research evolved significantly in recent years. However, few focus on patient engagement in the design and implementation of a national study. OBJECTIVES/OBJECTIVE:To describe the initial engagement development and implementation; present findings from data collected during the first year; and discuss lessons learned. METHODS:Data were collected as part of continuous quality improvement efforts to assess and refine the engagement strategy. Fifty-two patient, caregiver, and community representatives were invited to complete a brief online survey about their experience participating in a national initiative. RESULTS:A framework for engagement was created and 35 representatives completed the survey (67% response rate). Representatives demonstrated awareness related to their roles and responsibilities. Seventy-six percent indicated that they felt comfortable expressing opinions and the decision-making process. CONCLUSIONS:The RECOVER initiative's approach promoted greater transparency and trust between researchers and the community, leading to more impactful engagement.

IMPORTANCE/UNASSIGNED:Millions of children worldwide are experiencing prolonged symptoms after SARS-CoV-2 infection, yet social risk factors for developing long COVID are largely unknown. As child health is influenced by the environment in which they live and interact, adverse social determinants of health (SDOH) may contribute to the development of pediatric long COVID. OBJECTIVE/UNASSIGNED:To identify whether adverse SDOH are associated with increased odds of long COVID in school-aged children and adolescents in the US. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:This cross-sectional analysis of a multicenter, longitudinal, meta-cohort study encompassed 52 sites (health care and community settings) across the US. School-aged children (6-11 years; n = 903) and adolescents (12-17 years; n = 3681) with SARS-CoV-2 infection history were included. Those with an unknown date of first infection, history of multisystem inflammatory syndrome in children, or symptom surveys with less than 50% of questions completed were excluded. Participants were recruited via health care systems, long COVID clinics, fliers, websites, social media campaigns, radio, health fairs, community-based organizations, community health workers, and existing research cohorts from March 2022 to August 2024, and surveys were completed by caregivers between March 2022 and August 2024. EXPOSURE/UNASSIGNED:Twenty-four individual social determinant of health factors were grouped into 5 Healthy People 2030 domains: economic stability, social and community context, caregiver education access and quality, neighborhood and built environment, and health care access and quality. Latent classes were created within each domain and used in regression models. MAIN OUTCOMES AND MEASURES/UNASSIGNED:Presence of long COVID using caregiver-reported, symptom-based, age-specific research indices. RESULTS/UNASSIGNED:The mean (SD) age among 4584 individuals included in this study was 14 (3) years, and 2330 (51%) of participants were male. The number of latent classes varied by domain; the reference group was the class with the least adversity. In unadjusted analyses, most classes in each domain were associated with higher odds of long COVID. After adjusting for many factors, including age group, sex, timing of infection, referral source, and other social determinant of health domains, economic instability characterized by difficulty covering expenses, poverty, receipt of government assistance, and food insecurity were associated with an increased risk of having long COVID (class 2 adjusted odds ratio [aOR], 1.57; 95% CI, 1.18-2.09; class 4 aOR, 2.39; 95% CI, 1.73-3.30); economic instability without food insecurity (class 3) was not (aOR, 0.93; 95% CI, 0.70-1.23). Poorer social and community context (eg, high levels of discrimination and low social support) was also associated with long COVID (aOR, 2.17; 95% CI, 1.77-2.66). Sensitivity analyses stratified by age group and adjusted for race and ethnicity did not alter or attenuate these results. CONCLUSIONS AND RELEVANCE/UNASSIGNED:In this study, economic instability that included food insecurity and poor social and community context were associated with greater odds of pediatric long COVID. Those with food security, despite experiencing other economic challenges, did not have greater odds of long COVID. Further study is needed to determine if addressing SDOH factors can decrease the rate of pediatric long COVID.

INTRODUCTION/BACKGROUND:We examined the landscape of early childhood sleep health interventions that utilized digital tools designed for parents to improve sleep health outcomes during early childhood, (ages 3-8). METHODS:We performed a scoping review of peer-reviewed articles published from inception to April 2025 from the following databases: PubMed, Embase, Web of Science, MEDLINE, Cochrane Library, Engineering Village, Global Health, citation searching, and others. Two medical science librarians conducted the extensive literature search, with strategies detailed at [osf.io/74hba]. This study was guided by the implementation science outcomes framework. RESULTS:Twenty-one articles met the final inclusion criteria. Included studies reported clinical sleep, behavioral and/or implementation science outcomes. Implementation science outcomes primarily focused on acceptability, appropriateness and feasibility of pediatric digital sleep and family-based tools. Mobile apps were most prominently used, followed by websites and telehealth. Websites contributed to improved child sleep duration, sleep onset, sleep efficiency, daytime sleepiness and reduced night wakings. Mobile apps reported the aforementioned child sleep outcomes, as well as improvements in parent mental health and daytime functioning. CONCLUSIONS:Digital sleep health tools have the potential to ameliorate sleep problems in young children. Digital interventions may improve sleep and wellbeing in the family unit.

Wearables yield a wide array of sleep-related measures that are relevant to Long COVID. We leveraged wearables-derived sleep measures (WDSM) to identify differences between individuals with Long COVID (LC) versus individuals with possible or no LC in the RECOVER adult cohort. We found significant associations between LC and reduced heart rate variability measured during sleep and increased nightly variability in sleep duration after adjusting for confounders. Moreover, LC was independently associated with lower sleep efficiency, greater variability of nighttime sleep timing, higher resting heart rate, lower respiratory rate during rapid eye movement (REM) sleep, prolonged REM sleep onset latency, worse global physical and mental health. Cluster analysis identified distinct multidimensional patterns of WDSM that are associated with LC and quality of life. Together, the strong association between WDSM, or WDSM clusters, with LC provides a potential biomarker for future validation efforts to detect LC and monitor treatment effectiveness.

INTRODUCTION/UNASSIGNED:The growing availability of AI tools is transforming health and science communication by streamlining content creation and promotion. This study investigates the impact of AI-assisted research summaries on user engagement with the NIH-funded RECOVER program's website and evaluates the efficiency and readability of the content. METHODS/UNASSIGNED:We analyzed Google Analytics 4 data from two distinct periods: one with entirely human-generated content and a second with AI-assisted content. We measured changes in page views, active users, and average engagement time, and assessed the review time and readability of the AI-enhanced summaries. RESULTS/UNASSIGNED:There was no significant change in page views or active users between the two periods. However, average engagement time increased by 4.37 seconds (P = .0461), suggesting AI-assisted content may be more compelling. Human review of AI-drafts averaged 19.88 changes, and readability improved, with the mean Flesch-Kincaid grade level decreasing from 12.28 to 11.56. CONCLUSION/UNASSIGNED:This study demonstrates that AI can be a valuable tool for accelerating the creation of accessible and engaging content. Our findings highlight a crucial balance: while AI can save effort and reduce cost in public engagement efforts, human oversight remains essential to ensure the accuracy, clarity, and accessibility of vital health communications.

BACKGROUND/UNASSIGNED:Social determinants of health (SDoH) contribute to disparities in SARS-CoV-2 infection, but their associations with long COVID are unknown. OBJECTIVE/UNASSIGNED:To determine associations between SDoH at the time of SARS-CoV-2 infection and risk for long COVID. DESIGN/UNASSIGNED:Prospective observational cohort study. SETTING/UNASSIGNED:33 states plus Washington, DC, and Puerto Rico. PARTICIPANTS/UNASSIGNED:Adults (aged ≥18 years) enrolled in RECOVER-Adult (Researching COVID to Enhance Recovery) between October 2021 and November 2023 who were within 30 days of SARS-CoV-2 infection; completed baseline SDoH, comorbidity, and pregnancy questionnaires; and were followed prospectively. MEASUREMENTS/UNASSIGNED:Social risk factors from SDoH baseline questionnaires, ZIP code poverty and household crowding measures, and a weighted score of 11 or higher on the Long COVID Research Index 6 months after infection. RESULTS/UNASSIGNED:Among 3787 participants, 418 (11%) developed long COVID. After adjustment for demographic characteristics, pregnancy, disability, comorbidities, SARS-CoV-2 severity, and vaccinations, financial hardship (adjusted marginal risk ratio [ARR], 2.36 [95% CI, 1.97 to 2.91]), food insecurity (ARR, 2.36 [CI, 1.83 to 2.98]), less than a college education (ARR, 1.60 [CI, 1.30 to 1.97]), experiences of medical discrimination (ARR, 2.37 [CI, 1.94 to 2.83]), skipped medical care due to cost (ARR, 2.87 [CI, 2.22 to 3.70]), and lack of social support (ARR, 1.79 [CI, 1.50 to 2.17]) were associated with increased risk for long COVID. Living in ZIP codes with the highest (vs. lowest) household crowding was also associated with greater risk (ARR, 1.36 [CI, 1.05 to 1.71]). LIMITATION/UNASSIGNED:Selection bias may influence observed associations and generalizability. CONCLUSION/UNASSIGNED:Participants with social risk factors at the time of SARS-CoV-2 infection had greater risk for subsequent long COVID than those without. Future studies should determine whether social risk factor interventions mitigate long-term effects of SARS-CoV-2 infection. PRIMARY FUNDING SOURCE/UNASSIGNED:National Institutes of Health.