Faculty Bibliography

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.

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.

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.

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.

BACKGROUND:Inclusion of patients, caregivers, and community members in scientific research should be essential for patient-centered care. Patients’ lived experiences can propose new areas of focus that may not have previously been considered, ensure that potentially sensitive topics are addressed thoughtfully, contribute to the interpretation of findings, and identify future directions of research. Further, their inclusion in the drafting of manuscripts can ensure that research findings are translatable to real-world practice. To achieve this goal, the Researching COVID to Enhance Recovery (RECOVER) consortium developed a Representative Authorship system for development of scientific manuscripts that report RECOVER data. This paper describes a Quality Improvement (QI) project that was conducted to identify system strengths and improvement opportunities. METHODS:An online QI survey was distributed to RECOVER’s Representative Authors about a year into the implementation of the Representative Authorship System. The survey focused on several key aspects, including the clarity regarding the authorship process, training opportunities, the matching process, communication within writing groups, and the perceived impact of the representative engagement on the quality and applicability of research. The survey also explored participants’ satisfaction with compensation, support, and involvement in the system, as well as areas for improvement. RESULTS:The survey was sent to 49 representative authors with 17 respondents (35%). Most respondents reported positive experiences, highlighting the effective matching to manuscripts based on their expertise and the perceived positive impact of their involvement on research outcomes. Additionally, participants felt that including diverse voices enhanced the relevance of research for clinical practice. Several areas for improvement were identified, including communication challenges within writing groups, the utility of manuscript orientation calls, and the fairness of compensation. Respondents also indicated a need for more training opportunities and logistical support. CONCLUSIONS:RECOVER’s Representative Authorship system is effective in fostering collaboration and improving the inclusivity of scientific research. The survey findings indicate that there are logistical changes around communication, training, and compensation that could enhance the experience for all collaborators. Based on these findings, we plan to implement changes to improve awareness, understanding, and collaboration. Additional work is needed to solicit feedback from investigators and administrative staff to obtain a more holistic understanding of the system. SUPPLEMENTARY INFORMATION:The online version contains supplementary material available at 10.1186/s12913-025-12914-3.

Previous studies have demonstrated that text message reminders can improve pediatric vaccination rates, including low income & diverse settings such as those served by federally qualified health centers. In this study, we aimed to improve compliance with routine childhood immunizations via a text message intervention in a network of urban, federally qualified health centers at a large academic medical center. We targeted parents or guardians of children aged 0-2 years who were overdue or due within 14 days for at least one routine childhood immunization without a scheduled appointment. In Round 1, two versions of a text were compared to a control (no text). In subsequent Rounds, a new text was compared to a control (no text). In each round the content, wording, and frequency of texts changed. Subjects were randomized to receive a text (treatment group(s)) or to not receive a text (control group) in each round between 2020 and 2022. The primary outcome was whether overdue vaccines had been given by 12 week follow up. The secondary outcome was appointment scheduling within the 72 hours after text messages were sent. In Round 1 (n=1203) no significant differences were found between groups in overdue vaccine administration per group or per patient at follow up, or in appointment scheduling. In Round 2 (n=251) there was no significant difference in vaccine administration per group or per patient. However, significantly more patients in the intervention group scheduled an appointment (9.1% vs. 1.7%, p=0.01). In Round 3 (n=1034), vaccine administration was significantly higher in the intervention group compared to the control overall (7.0% vs. 5.5%, 0.016) and per subject (p=0.02). Significantly more patients in the intervention group scheduled an appointment compared to the control (3.3% vs. 1.2%, p=0.02). We found that text messaging can be an effective intervention to promote health service utilization such as pediatric vaccination rates, which although improved in this study, remain low.

BACKGROUND/UNASSIGNED:Children from racial and ethnic minority groups are at greater risk for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, but it is unclear whether they have increased risk for post-acute sequelae of SARS-CoV-2 (PASC). Our objectives were to assess whether the risk of respiratory and neurologic PASC differs by race/ethnicity and social drivers of health. METHODS/UNASSIGNED:We conducted a retrospective cohort study of individuals <21 years seeking care at 24 health systems across the U.S, using electronic health record (EHR) data. Our cohort included those with a positive SARS-CoV-2 molecular, serology or antigen test, or with a COVID-19, multisystem inflammatory disease in children, or PASC diagnosis from February 29, 2020 to August 1, 2022. We identified children/youth with at least 2 codes associated with respiratory and neurologic PASC. We measured associations between sociodemographic and clinical characteristics and respiratory and neurologic PASC using odds ratios and 95% confidence intervals estimated from multivariable logistic regression models adjusted for other sociodemographic characteristics, social vulnerability index or area deprivation index, time period of cohort entry, presence and complexity of chronic respiratory (respectively, neurologic) condition and healthcare utilization. FINDINGS/UNASSIGNED:Among 771,725 children in the cohort, 203,365 (26.3%) had SARS-CoV-2 infection. Among children with documented infection, 3217 children had respiratory PASC and 2009 children/youth had neurologic PASC. In logistic regression models, children <5 years (Odds Ratio [OR] 1.78, 95% CI 1.62-1.97), and of Hispanic White descent (OR 1.19, 95% CI 1.05-1.35) had higher odds of having respiratory PASC. Children/youth living in regions with higher area deprivation indices (OR 1.25, 95% CI 1.10-1.420 for 60-79th percentile) and with chronic complex respiratory conditions (OR 3.28, 95% CI 2.91-3.70) also had higher odds of respiratory PASC. In contrast, older (OR 1.57, 95% CI 1.40-1.77 for those aged 12-17 years), non-Hispanic White individuals and those with chronic pre-existing neurologic conditions (OR 2.04, 95% CI 1.78-2.35) were more likely to have a neurologic PASC diagnosis. INTERPRETATION/UNASSIGNED:Racial and ethnic differences in healthcare utilization for neurologic and respiratory PASC may reflect social drivers of health and inequities in access to care. FUNDING/UNASSIGNED:National Institutes of Health.