The Day-Level Association Between Child Care Attendance and 24-Hour Movement Behaviors in Preschool-Aged Children.

BACKGROUND: Twenty-four hour movement behaviors (ie, physical activity [PA], screen time [ST], and sleep) are associated with children's health outcomes. Identifying day-level contextual factors, such as child care, that positively influence children's movement behaviors may help identify potential intervention targets, like improving access to child care programs. This study aimed to examine the between- and within-person effects of child care on preschoolers' 24-hour movement behaviors. METHODS: Children (N = 74, 4.7 [0.9] y, 48.9% girls, 63.3% White) wore an Axivity AX3 accelerometer on their nondominant wrist 24 hours per day for 14 days to measure PA and sleep. Parents completed surveys each night about their child's ST and child care attendance that day. Linear mixed effects models predicted day-level 24-hour movement behaviors from hours spent in child care. RESULTS: Children spent an average of 5.0 (2.9) hours per day in child care. For every additional hour of child care above their average, children had 0.3 hours (95% CI, -0.3 to -0.2) less ST that day. Between-person effects showed that compared with children who attended fewer overall hours of child care, children who attended more hours had less overall ST (B = -0.2 h; 95% CI, -0.4 to 0.0). Child care was not significantly associated with PA or sleep. CONCLUSIONS: Child care attendance was not associated with 24-hour PA or sleep; however, it was associated with less ST. More research utilizing objective measures of ST and more robust measures of daily schedules or structure is necessary to better understand how existing infrastructure may influence preschool-aged children's 24-hour movement behaviors. In addition, future research should consider how access to child care may influence child care attendance.

Comparison of raw accelerometry data from ActiGraph, Apple Watch, Garmin, and Fitbit using a mechanical shaker table.

The purpose of this study was to evaluate the reliability and validity of the raw accelerometry output from research-grade and consumer wearable devices compared to accelerations produced by a mechanical shaker table. Raw accelerometry data from a total of 40 devices (i.e., n = 10 ActiGraph wGT3X-BT, n = 10 Apple Watch Series 7, n = 10 Garmin Vivoactive 4S, and n = 10 Fitbit Sense) were compared to reference accelerations produced by an orbital shaker table at speeds ranging from 0.6 Hz (4.4 milligravity-mg) to 3.2 Hz (124.7mg). Two-way random effects absolute intraclass correlation coefficients (ICC) tested inter-device reliability. Pearson product moment, Lin's concordance correlation coefficient (CCC), absolute error, mean bias, and equivalence testing were calculated to assess the validity between the raw estimates from the devices and the reference metric. Estimates from Apple, ActiGraph, Garmin, and Fitbit were reliable, with ICCs = 0.99, 0.97, 0.88, and 0.88, respectively. Estimates from ActiGraph, Apple, and Fitbit devices exhibited excellent concordance with the reference CCCs = 0.88, 0.83, and 0.85, respectively, while estimates from Garmin exhibited moderate concordance CCC = 0.59 based on the mean aggregation method. ActiGraph, Apple, and Fitbit produced similar absolute errors = 16.9mg, 21.6mg, and 22.0mg, respectively, while Garmin produced higher absolute error = 32.5mg compared to the reference. ActiGraph produced the lowest mean bias 0.0mg (95%CI = -40.0, 41.0). Equivalence testing revealed raw accelerometry data from all devices were not statistically significantly within the equivalence bounds of the shaker speed. Findings from this study provide evidence that raw accelerometry data from Apple, Garmin, and Fitbit devices can be used to reliably estimate movement; however, no estimates were statistically significantly equivalent to the reference. Future studies could explore device-agnostic and harmonization methods for estimating physical activity using the raw accelerometry signals from the consumer wearables studied herein.

POSITION STATEMENT: Pass the RESTORE (Re-entry Support Through Opportunities for Resources and Essentials) Act.

Under the Personal Responsibility and Work Opportunity Reconciliation Act (PRWORA), current federal policy mandates a lifetime ban for individuals with a past felony drug conviction from receiving Supplemental Nutrition Assistance Program (SNAP) and Temporary Assistance for Needy Families (TANF) benefits. Denying nutritional and financial assistance to individuals with a past felony conviction will widen existing structural health inequities, set back individuals' successful re-entry into society, and contribute to recidivism and poorer health outcomes. Therefore, the Society of Behavioral Medicine supports the RESTORE ACT (Re-Entry Support Through Opportunities for Resources and Essentials Act), which would repeal the lifetime ban on receiving SNAP and TANF benefits for individuals convicted of a drug felony.

Current US law bans people who have been convicted of felony drug crime from participating in nutritional and financial assistance programs (i.e. Supplemental Nutrition Assistance Program [SNAP] and Temporary Assistance for Needy Families [TANF]). By not allowing people who have been convicted of a drug felony to access these programs, this law risks worsening health outcomes and perpetuating existing health disparities. The Society of Behavioral Medicine supports the RESTORE Act (Re-Entry Support Through Opportunities for Resources and Essentials Act), which would end the federal ban and allow all income-eligible people to access SNAP and TANF benefits.

A comparison of perceived barriers to optimal child sleep among families with low and high income.

OBJECTIVE: Families with low-income experience suboptimal sleep compared to families with higher-income. Unique drivers likely contribute to these disparities, along with factors that universally impede sleep patterns, despite income level. To inform intervention tailoring, this mixed-methods study gathered parent's perceptions about child sleep challenges to identify similarities/differences in families with lower-income and higher-income. METHODS: Parents who experienced difficulties with their child (ages 2-4years) sleep were categorized as lower income (n = 15; $30,000 ± 17,845/year) or higher income (n = 15; $142,400 ± 61,373/year). Parents completed a survey and semistructured interview to explore barriers and facilitators for child sleep. Two coders independently evaluated transcripts for lower-income and higher-income groups using inductive analyses. Constant-comparison methods generated themes and characterized similarities/differences by income group. RESULTS: Groups were similar in themes related to diverse bedtime routines, nighttime struggles with child sleep, parent strategies to reduce night wakings, parent effort to provide a sleep-promoting environment, and presence of electronic rules. Groups differed in themes related to factors influencing routine setting (eg, lower income: external factors influencing routines; higher income: personal attributes for structure), parent appraisal of child sleep (eg, higher income: ambivalence; lower income: mostly negative appraisal), nap timing and duration (eg, lower income: longer naps), and strategy utilization and pursuit of resources (eg, higher income: more parents tried various strategies and accessed online/print resources). CONCLUSIONS: Parents experienced many similar barriers to child sleep, with a few distinct differences by income group. These findings can inform future intervention components for all families, as well as customized components to address the unique needs of families across income levels.

Prioritize "Food is Medicine" initiatives in the 2024 Farm Bill for human and planetary health.

The Society of Behavioral Medicine (SBM) supports increased funding for policies in the 2024 Farm Bill that align with a Food is Medicine (FIM) framework and address multiple dimensions of human and planetary health.

The Society of Behavioral Medicine (SBM) supports funding for policies in 2024 Farm Bill that align with a Food is Medicine (FIM) framework and address multiple dimensions of human and planetary health. Recommendations include increasing funding for produce prescription programs, establishing systems to align federal- and state-funded initiatives, and the allocation of funding for financial incentives when sustainable agricultural practices are utilized in government-funded local and regional farm-to-institution programs.

A Device Agnostic Approach to Predict Children's Activity from Consumer Wearable Accelerometer Data: A Proof-of-Concept Study.

INTRODUCTION: This study examined the potential of a device agnostic approach for predicting physical activity from consumer wearable accelerometry compared with a research-grade accelerometry. METHODS: Seventy-five 5- to 12-year-olds (58% male, 63% White) participated in a 60-min protocol. Children wore wrist-placed consumer wearables (Apple Watch Series 7 and Garmin Vivoactive 4) and a research-grade device (ActiGraph GT9X) concurrently with an indirect calorimeter (COSMED K5). Activity intensities (i.e., inactive, light, moderate-to-vigorous physical activity) were estimated via indirect calorimetry (criterion), and the Hildebrand thresholds were applied to the raw accelerometer data from the consumer wearables and research-grade device. Epoch-by-epoch (e.g., weighted sensitivity, specificity) and discrepancy (e.g., mean bias, absolute error) analyses evaluated agreement between accelerometry-derived and criterion estimates. Equivalence testing evaluated the equivalence of estimates produced by the consumer wearables and ActiGraph. RESULTS: Estimates produced by the raw accelerometry data from ActiGraph, Apple, and Garmin produced similar criterion agreement with weighted sensitivity = 68.2% (95% confidence interval (CI), 67.1%-69.3%), 73.0% (95% CI, 71.8%-74.3%), and 66.6% (95% CI, 65.7%-67.5%), respectively, and weighted specificity = 84.4% (95% CI, 83.6%-85.2%), 82.0% (95% CI, 80.6%-83.4%), and 75.3% (95% CI, 74.7%-75.9%), respectively. Apple Watch produced the lowest mean bias (inactive, -4.0 ± 4.5; light activity, 2.1 ± 4.0) and absolute error (inactive, 4.9 ± 3.4; light activity, 3.6 ± 2.7) for inactive and light physical activity minutes. For moderate-to-vigorous physical activity, ActiGraph produced the lowest mean bias (1.0 ± 2.9) and absolute error (2.8 ± 2.4). No ActiGraph and consumer wearable device estimates were statistically significantly equivalent. CONCLUSIONS: Raw accelerometry estimated inactive and light activity from wrist-placed consumer wearables performed similarly to, if not better than, a research-grade device, when compared with indirect calorimetry. This proof-of-concept study highlights the potential of device-agnostic methods for quantifying physical activity intensity via consumer wearables.

Nutritional needs, resources, and barriers among unhoused adults cared for by a street medicine organization in Chicago, Illinois: a cross-sectional study.

BACKGROUND: Those experiencing houselessness rely on obtaining food from community organizers and donations. Simultaneously, the houseless face disproportionally high rates of medical conditions that may be affected by diet including diabetes, hypertension, and hyperlipidemia. There is limited literature on the resources and barriers of the houseless community regarding optimal nutrition from an actionable perspective. Further, less data is available on how street medicine organizations may best impact the nutrition of the unhoused they serve. Elucidating this information will inform how organizational efforts may best support the nutrition of the houseless community. METHODS: In partnership with the medical student-run organization, Chicago Street Medicine, at Northwestern University Feinberg School of Medicine, twenty adults experiencing houselessness in Chicago, Illinois participated in the cross-sectional study. A 10-item survey was verbally administered to characterize the participants' daily food intake, food sources, barriers, resources, and nutritional preferences and needs. All data was directly transcribed into REDCap. Descriptive statistics were generated. RESULTS: Individuals consumed a median of 2 snacks and meals per day (IQR: 1-3). No participant consumed adequate servings of every food group, with only one participant meeting the dietary intake requirements for one food group. Participants most often received their food from donations (n = 15), purchasing themselves (n = 11), food pantries (n = 4), and shelters (n = 3). Eleven of nineteen participants endorsed dental concerns as a major barrier to consuming certain foods. Twelve participants had access to a can opener and twelve could heat their meals on a stove or microwave. Seven had access to kitchen facilities where they may prepare a meal. Approximately half of participants had been counseled by a physician to maintain a particular diet, with most related to reducing sugar intake. CONCLUSION: Most houseless participants were unable to acquire a balanced diet and often relied on organizational efforts to eat. Organizations should consider the chronic health conditions, dentition needs, and physical resources and barriers to optimal nutrition when obtaining food to distribute to the unhoused.

Are parent-reported sleep logs essential? A comparison of three approaches to guide open source accelerometry-based nocturnal sleep processing in children.

We examined the comparability of children's nocturnal sleep estimates using accelerometry data, processed with and without a sleep log. In a secondary analysis, we evaluated factors associated with disagreement between processing approaches. Children (n = 722, age 5-12 years) wore a wrist-based accelerometer for 14 days during Autumn 2020, Spring 2021, and/or Summer 2021. Outcomes included sleep period, duration, wake after sleep onset (WASO), and timing (onset, midpoint, waketime). Parents completed surveys including children's nightly bed/wake time. Data were processed with parent-reported bed/wake time (sleep log), the Heuristic algorithm looking at Distribution of Change in Z-Angle (HDCZA) algorithm (no log), and an 8 p.m.-8 a.m. window (generic log) using the R-package 'GGIR' (version 2.6-4). Mean/absolute bias and limits of agreement were calculated and visualised with Bland-Altman plots. Associations between child, home, and survey characteristics and disagreement were examined with tobit regression. Just over half of nights demonstrated no difference in sleep period between sleep log and no log approaches. Among all nights, the sleep log approach produced longer sleep periods (9.3 min; absolute mean bias [AMB] = 28.0 min), shorter duration (1.4 min; AMB = 14.0 min), greater WASO (11.0 min; AMB = 15.4 min), and earlier onset (13.4 min; AMB = 17.4 min), midpoint (8.8 min; AMB = 15.3 min), and waketime (3.9 min; AMB = 14.8 min) than no log. Factors associated with discrepancies included smartphone ownership, bedroom screens, nontraditional parent work schedule, and completion on weekend/summer nights (range = 0.4-10.2 min). The generic log resulted in greater AMB among sleep outcomes. Small mean differences were observed between nights with and without a sleep log. Discrepancies existed on weekends, in summer, and for children with smartphones and screens in the bedroom.

Use of guidelines, checklists, frameworks, and recommendations in behavioral intervention preliminary studies and associations with reporting comprehensiveness: a scoping bibliometric review.

BACKGROUND: Guidelines, checklists, frameworks, and recommendations (GCFRs) related to preliminary studies serve as essential resources to assist behavioral intervention researchers in reporting findings from preliminary studies, but their impact on preliminary study reporting comprehensiveness is unknown. The purpose of this study was to conduct a scoping bibliometric review of recently published preliminary behavioral-focused intervention studies to (1) examine the prevalence of GCFR usage and (2) determine the associations between GCFR usage and reporting feasibility-related characteristics. METHODS: A systematic search was conducted for preliminary studies of behavioral-focused interventions published between 2018 and 2020. Studies were limited to the top 25 journals publishing behavioral-focused interventions, text mined to identify usage of GCFRs, and categorized as either not citing GCFRs or citing ≥ 2 GCFRs (Citers). A random sample of non-Citers was text mined to identify studies which cited other preliminary studies that cited GCFRs (Indirect Citers) and those that did not (Never Citers). The presence/absence of feasibility-related characteristics was compared between Citers, Indirect Citers, and Never Citers via univariate logistic regression. RESULTS: Studies (n = 4143) were identified, and 1316 were text mined to identify GCFR usage (n = 167 Citers). A random sample of 200 studies not citing a GCFR were selected and categorized into Indirect Citers (n = 71) and Never Citers (n = 129). Compared to Never Citers, Citers had higher odds of reporting retention, acceptability, adverse events, compliance, cost, data collection feasibility, and treatment fidelity (ORrange = 2.62-14.15, p < 0.005). Citers also had higher odds of mentioning feasibility in purpose statements, providing progression criteria, framing feasibility as the primary outcome, and mentioning feasibility in conclusions (ORrange = 6.31-17.04, p < 0.005) and lower odds of mentioning efficacy in purpose statements, testing for efficacy, mentioning efficacy in conclusions, and suggesting future testing (ORrange = 0.13-0.54, p < 0.05). Indirect Citers had higher odds of reporting acceptability and treatment fidelity (ORrange = 2.12-2.39, p < 0.05) but lower odds of testing for efficacy (OR = 0.36, p < 0.05) compared to Never Citers. CONCLUSION: The citation of GCFRs is associated with greater reporting of feasibility-related characteristics in preliminary studies of behavioral-focused interventions. Researchers are encouraged to use and cite literature that provides guidance on design, implementation, analysis, and reporting to improve the comprehensiveness of reporting for preliminary studies.

Evaluation of a device-agnostic approach to predict sleep from raw accelerometry data collected by Apple Watch Series 7, Garmin Vivoactive 4, and ActiGraph GT9X Link in children with sleep disruptions.

GOAL AND AIMS: Evaluate the performance of a sleep scoring algorithm applied to raw accelerometry data collected from research-grade and consumer wearable actigraphy devices against polysomnography. FOCUS METHOD/TECHNOLOGY: Automatic sleep/wake classification using the Sadeh algorithm applied to raw accelerometry data from ActiGraph GT9X Link, Apple Watch Series 7, and Garmin Vivoactive 4. REFERENCE METHOD/TECHNOLOGY: Standard manual PSG sleep scoring. SAMPLE: Fifty children with disrupted sleep (M = 8.5 years, range = 5-12 years, 42% Black, 64% male). DESIGN: Participants underwent to single night lab polysomnography while wearing ActiGraph, Apple, and Garmin devices. CORE ANALYTICS: Discrepancy and epoch-by-epoch analyses for sleep/wake classification (devices vs. polysomnography). ADDITIONAL ANALYTICS AND EXPLORATORY ANALYSES: Equivalence testing for sleep/wake classification (research-grade actigraphy vs. commercial devices). CORE OUTCOMES: Compared to polysomnography, accuracy, sensitivity, and specificity were 85.5, 87.4, and 76.8, respectively, for Actigraph; 83.7, 85.2, and 75.8, respectively, for Garmin; and 84.6, 86.2, and 77.2, respectively, for Apple. The magnitude and trend of bias for total sleep time, sleep efficiency, sleep onset latency, and wake after sleep were similar between the research and consumer wearable devices. IMPORTANT ADDITIONAL OUTCOMES: Equivalence testing indicated that total sleep time and sleep efficiency estimates from the research and consumer wearable devices were statistically significantly equivalent. CORE CONCLUSION: This study demonstrates that raw acceleration data from consumer wearable devices has the potential to be harnessed to predict sleep in children. While further work is needed, this strategy could overcome current limitations related to proprietary algorithms for predicting sleep in consumer wearable devices.

Free Healthy School Meals for All as a Means to Advance Child Health Equity.

This Viewpoint discusses how providing free, healthy meals to all schoolchildren can advance health equity.

Student-driven disability advocacy and education within the health professions: pilot survey results from a single-day virtual conference.

BACKGROUND: Health professional programs can promote equitable healthcare delivery but few programs include disability in these efforts. Limited opportunities exist for health professional students to engage with disability education within the classroom or beyond. The Disability Advocacy Coalition in Medicine (DAC Med) is a national interprofessional student-led organization which hosted a virtual conference for health professional students in October 2021. We describe the impact of this single-day virtual conference on learning and the current state of disability education across health professional programs. METHODS: This cross-sectional study utilized a 17-item post-conference survey. A 5-point Likert scale-based survey was distributed to conference registrants. Survey parameters included background in disability advocacy, curricular exposure to disability, and impact of the conference. RESULTS: Twenty-four conference attendees completed the survey. Participants were enrolled in audiology, genetic counseling, medical, medical scientist, nursing, prosthetics and orthotics, public health, and 'other' health programs. Most participants (58.3%) reported not having a strong background in disability advocacy before the conference, with 26.1% indicating they learned about ableism in their program's curriculum. Almost all students (91.6%) attended the conference to learn how to be a better advocate for patients and peers with disabilities, and 95.8% reported that the conference provided this knowledge. Eighty-eight percent of participants agreed that they acquired additional resources to better care for patients with disabilities. CONCLUSIONS: Few health professional students learn about disability in their curriculum. Single-day virtual, interactive conferences are effective in providing advocacy resources and empowering students to employ them.

Understanding Accelerated Summer Body Mass Index Gain by Tracking Changes in Children's Height, Weight, and Body Mass Index Throughout the Year.

Background: Drivers of summer body mass index (BMI) gain in children remain unclear. The Circadian and Circannual Rhythm Model (CCRM) posits summer BMI gain is biologically driven, while the Structured Days Hypothesis (SDH) proposes it is driven by reduced structure. Objectives: Identify the mechanisms driving children's seasonal BMI gain through the CCRM and SDH. Methods: Children's (N = 147, mean age = 8.2 years) height and weight were measured monthly during the school year, and once in summer (July-August). BMI z-score (zBMI) was calculated using CDC growth charts. Behaviors were measured once per season. Mixed methods regression estimated monthly percent change in children's height (%HΔ), weight (%WΔ), and monthly zBMI for school year vs. summer vacation, seasonally, and during school months with no breaks vs. school months with a break ≥1 week. Results: School year vs. summer vacation analyses showed accelerations in children's %WΔ (Δ = 0.9, Standard Error (SE) = 0.1 vs. Δ = 1.4, SE = 0.1) and zBMI (Δ = -0.01, SE = 0.01 vs. Δ = 0.04, SE = 0.3) during summer vacation, but %HΔ remained relatively constant during summer vacation compared with school (Δ = 0.3, SE = 0.0 vs. Δ = 0.4, SE = 0.1). Seasonal analyses showed summer had the greatest %WΔ (Δ = 1.8, SE = 0.4) and zBMI change (Δ = 0.05, SE = 0.03) while %HΔ was relatively constant across seasons. Compared with school months without a break, months with a break showed higher %WΔ (Δ = 0.7, SE = 0.1 vs. Δ = 1.6, SE = 0.2) and zBMI change (Δ = -0.03, SE = 0.01 vs. Δ = 0.04, SE = 0.01), but %HΔ was constant (Δ = 0.4, SE = 0.0 vs. Δ = 0.3, SE = 0.1). Fluctuations in sleep timing and screen time may explain these changes. Conclusions: Evidence for both the CCRM and SDH was identified but the SDH may more fully explain BMI gain. Interventions targeting consistent sleep and reduced screen time during breaks from school may be warranted no matter the season.

Implementing cone-beam computed tomography-guided online adaptive radiotherapy in cervical cancer.

Background and purpose: Adaptive radiotherapy (ART) in locally advanced cervical cancer (LACC) has shown promising outcomes. This study investigated the feasibility of cone-beam computed tomography (CBCT)-guided online ART (oART) for the treatment of LACC. Material and methods: The quality of the automated radiotherapy treatment plans and artificial intelligence (AI)-driven contour delineation for LACC on a novel CBCT-guided oART system were assessed. Dosimetric analysis of 200 simulated oART sessions were compared with standard treatment. Feasibility of oART was assessed from the delivery of 132 oART fractions for the first five clinical LACC patients. The simulated and live oART sessions compared a fixed planning target volume (PTV) margin of 1.5 cm around the uterus-cervix clinical target volume (CTV) with an internal target volume-based approach. Workflow timing measurements were recorded. Results: The automatically-generated 12-field intensity-modulated radiotherapy plans were comparable to manually generated plans. The AI-driven organ-at-risk (OAR) contouring was acceptable requiring, on average, 12.3 min to edit, with the bowel performing least well and rated as unacceptable in 16 % of cases. The treated patients demonstrated a mean PTV D98% (+/-SD) of 96.7 (+/- 0.2)% for the adapted plans and 94.9 (+/- 3.7)% for the non-adapted scheduled plans (p<10-5). The D2cc (+/-SD) for the bowel, bladder and rectum were reduced by 0.07 (+/- 0.03)Gy, 0.04 (+/-0.05)Gy and 0.04 (+/-0.03)Gy per fraction respectively with the adapted plan (p <10-5). In the live.setting, the mean oART session (+/-SD) from CBCT acquisition to beam-on was 29 +/- 5 (range 21-44) minutes. Conclusion: CBCT-guided oART was shown to be feasible with dosimetric benefits for patients with LACC. Further work to analyse potential reductions in PTV margins is ongoing.

2002-2017 anthropogenic emissions data for air quality modeling over the United States.

The United States Environmental Protection Agency (US EPA) has developed a set of annual North American emissions data for multiple air pollutants across 18 broad source categories for 2002 through 2017. The sixteen new annual emissions inventories were developed using consistent input data and methods across all years. When a consistent method or tool was not available for a source category, emissions were estimated by scaling data from the EPA's 2017 National Emissions Inventory with scaling factors based on activity data and/or emissions control information. The emissions datasets are designed to support regional air quality modeling for a wide variety of human health and ecological applications. The data were developed to support simulations of the EPA's Community Multiscale Air Quality model but can also be used by other regional scale air quality models. The emissions data are one component of EPA's Air Quality Time Series Project which also includes air quality modeling inputs (meteorology, initial conditions, boundary conditions) and outputs (e.g., ozone, PM2.5 and constituent species, wet and dry deposition) for the Conterminous US at a 12 km horizontal grid spacing.

Statewide Examination of Access to Cancer Surgery During the COVID-19 Pandemic.

INTRODUCTION: The COVID-19 pandemic caused interruptions in the delivery of medical care across a wide range of conditions including cancer. Trends in surgical treatment for cancer during the pandemic have not been well described. We sought to characterize associations between the pandemic and access to surgical treatment for breast, colorectal, and lung cancer in Illinois. METHODS: We performed a retrospective cohort study evaluating inpatient admissions at Illinois hospitals providing surgical care for lung cancer (n = 1913 cases, n = 64 hospitals), breast cancer (n = 910 cases, n = 108 hospitals), and colorectal cancer (n = 5339 cases, n = 144 hospitals). Using discharge data from the Illinois Health and Hospital Association's Comparative Health Care and Hospital Data Reporting Services database, average monthly surgical case volumes were compared from 2019 to 2020. We also compared rates of cancer surgery for each cancer type, by patient characteristics, and hospital type across the three time periods using Pearson chi-squared and ANOVA testing as appropriate. Three discrete time periods were considered: prepandemic (7-12/2019), primary pandemic (4-6/2020), and pandemic recovery (7-12/2020). Hospital characteristics evaluated included hospital type (academic, community, safety net), COVID-19 burden, and baseline cancer surgery volume. RESULTS: There were 2096 fewer operations performed for breast, colorectal, and lung cancer in 2020 than 2019 in Illinois, with the greatest reductions in cancer surgery volume occurring at the onset of the pandemic in April (colorectal, -48.3%; lung, -13.1%) and May (breast, -45.2%) of 2020. During the pandemic, breast (-14.6%) and colorectal (-13.8%) cancer surgery experienced reductions in volume whereas lung cancer operations were more common (+26.4%) compared to 2019. There were no significant differences noted in gender, race, ethnicity, or insurance status among patients receiving oncologic surgery during the primary pandemic or pandemic recovery periods. Academic hospitals, hospitals with larger numbers of COVID-19 admissions, and those with greater baseline cancer surgery volumes were associated with the greatest reduction in cancer surgery during the primary pandemic period (all cancer types, P < 0.01). During the recovery period, hospitals with greater baseline breast and lung cancer surgery volumes remained at reduced surgery volumes compared to their counterparts (P < 0.01). CONCLUSIONS: The COVID-19 pandemic was associated with significant reductions in breast and colorectal cancer operations in Illinois, while lung cancer operations remained relatively consistent. Overall, there was a net reduction in cancer surgery that was not made up during the recovery period. Academic hospitals, those caring for more COVID-19 patients, and those with greater baseline surgery volumes were most vulnerable to reduced surgery rates during peaks of the pandemic and to delays in addressing the backlog of cases.

Barriers to Optimal Child Sleep among Families with Low Income: A Mixed-Methods Study to Inform Intervention Development.

This study gathered formative data on barriers to optimal child sleep to inform the development of a sleep intervention for parents of preschool-aged children in low-income households. Parents (n = 15, age: 34 ± 8 years, household income: $30,000 ± 17,845/year) reporting difficulties with their child's sleep participated in this study. Mixed methods included an online survey and semi-structured phone interview. Items assessed barriers/facilitators to optimal child sleep and intervention preferences. Interview transcripts were coded using inductive analyses and constant-comparison methods to generate themes. Derived themes were then mapped onto the Theoretical Domains Framework to contextualize barriers and inform future intervention strategies. Themes that emerged included: stimulating bedtime activities, child behavior challenges, variability in children's structure, parent work responsibilities, sleep-hindering environment, and parent's emotional capacity. Parent's intervention preferences included virtual delivery (preferred by 60% of parents) to reduce barriers and provide flexibility. Mixed preferences were observed for the group (47%) vs. individual (53%) intervention sessions. Parents felt motivated to try new intervention strategies given current frustrations, the potential for tangible results, and knowing others were in a similar situation. Future work will map perceived barriers to behavior change strategies using the Behavior Change Wheel framework to develop a parenting sleep intervention.

Risk factors associated with 31-day unplanned hospital readmission in newborns: a systematic review.

The purpose of this study is to synthesize evidence on risk factors associated with newborn 31-day unplanned hospital readmissions (UHRs). A systematic review was conducted searching CINAHL, EMBASE (Ovid), and MEDLINE from January 1st 2000 to 30th June 2021. Studies examining unplanned readmissions of newborns within 31 days of discharge following the initial hospitalization at the time of their birth were included. Characteristics of the included studies examined variables and statistically significant risk factors were extracted from the inclusion studies. Extracted risk factors could not be pooled statistically due to the heterogeneity of the included studies. Data were synthesized using content analysis and presented in narrative and tabular form. Twenty-eight studies met the eligibility criteria, and 17 significant risk factors were extracted from the included studies. The most frequently cited risk factors associated with newborn readmissions were gestational age, postnatal length of stay, neonatal comorbidity, and feeding methods. The most frequently cited maternal-related risk factors which contributed to newborn readmissions were parity, race/ethnicity, and complications in pregnancy and/or perinatal period. CONCLUSION: This systematic review identified a complex and diverse range of risk factors associated with 31-day UHR in newborn. Six of the 17 extracted risk factors were consistently cited by studies. Four factors were maternal (primiparous, mother being Asian, vaginal delivery, maternal complications), and two factors were neonatal (male infant and neonatal comorbidities). Implementation of evidence-based clinical practice guidelines for inpatient care and individualized hospital-to-home transition plans, including transition checklists and discharge readiness assessments, are recommended to reduce newborn UHRs. WHAT IS KNOWN: • Attempts have been made to identify risk factors associated with newborn UHRs; however, the results are inconsistent. WHAT IS NEW: • Six consistently cited risk factors related to newborn 31-day UHRs. Four maternal factors (primiparous, mother being Asian, vaginal delivery, maternal complications) and 2 neonatal factors (male infant and neonatal comorbidities). • The importance of discharge readiness assessment, including newborn clinical fitness for discharge and parental readiness for discharge. Future research is warranted to establish standardised maternal and newborn-related variables which healthcare providers can utilize to identify newborns at greater risk of UHRs and enable comparison of research findings.

Development of the UNC Perceived Message Effectiveness Scale for Youth.

PURPOSE: Tobacco prevention media campaigns are an important tool to address youth tobacco use. We developed a theory-based perceived message effectiveness (PME) Scale to use when vetting messages for campaigns. METHODS: Participants were a national sample of N=623 US adolescents (ages 13-17 years) recruited from a national probability-based panel. In an online experiment, we randomised adolescents to view tobacco prevention ads. All participants viewed an ad on smoking or vaping from the US Food and Drug Administration's The Real Cost campaign and a control video, in a random order. After ad exposure, we assessed PME using nine candidate items and constructs for convergent and criterion validity analyses. We used confirmatory factor analysis and examined information curves to select the scale items. RESULTS: A brief PME scale with three items (α=0.95) worked equally well for demographically diverse adolescents with different patterns of tobacco use. The Real Cost ads generated higher PME scores than the control videos for both vaping and smoking (convergent validity; p<0.05). Higher PME scores were associated with greater attention, fear, cognitive elaboration and anticipated social interactions (convergent validity; r=0.31-0.66), as well as more negative attitudes toward and lower susceptibility to vaping and smoking (criterion validity; r=-0.14 to -0.37). A single-item PME measure performed similarly to the three-item version. CONCLUSIONS: The University of North Carolina PME Scale for Youth is a reliable and valid measure of the potential effectiveness of vaping and smoking prevention ads. Employing PME scales during message development and selection may help youth tobacco prevention campaigns deploy more effective ads.