Browsing by Author "Honaker, Sarah"
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Item 237 Sleep disturbances, online instruction, and learning during COVID-19: evidence from 4148 adolescents in the NESTED study(Oxford University Press, 2021-05) Saletin, Jared; Owens, Judith; Wahlstrom, Kyla; Honaker, Sarah; Wolfson, Amy; Seixas, Azizi; Wong, Patricia; Carskadon, Mary; Meltzer, Lisa; Pediatrics, School of MedicineIntroduction: COVID-19 fundamentally altered education in the United States. A variety of in-person, hybrid, and online instruction formats took hold in Fall 2020 as schools reopened. The Nationwide Education and School in TEens During COVID (NESTED) study assessed how these changes impacted sleep. Here we examined how instruction format was associated with sleep disruption and learning outcomes. Methods: Data from 4148 grade 6-12 students were included in the current analyses (61% non-male; 34% non-white; 13% middle-school). Each student’s instructional format was categorized as: (i) in-person; (ii) hybrid [≥1 day/week in-person]; (iii) online/synchronous (scheduled classes); (iv) online/asynchronous (unscheduled classes); (v) online-mixed; or (vi) no-school. Sleep disturbances (i.e., difficulty falling/staying asleep) were measured with validated PROMIS t-scores. A bootstrapped structural equation model examined how instructional format and sleep disturbances predict school/learning success (SLS), a latent variable loading onto 3 outcomes: (i) school engagement (ii) likert-rated school stress; and (iii) cognitive function (PROMIS t-scores). The model covaried for gender, race-ethnicity, and school-level Results: Our model fit well (RMSEA=.041). Examining total effects (direct + indirect), online and hybrid instruction were associated with lower SLS (b’s:-.06 to -.26; p’s<.01). The three online groups had the strongest effects (synchronous: b=-.15; 95%CI: [-.20, -.11]; asynchronous: b=-.17; [-.23, -.11]; mixed: b=-.14; [-.19, -.098]; p’s<.001). Sleep disturbance was also negatively associated with SLS (b=-.02; [-.02, -.02], p<.001). Monte-carlo simulations confirmed sleep disturbance mediated online instruction’s influence on SLS. The strongest effect was found for asynchronous instruction, with sleep disturbance mediating 24% of its effect (b = -.042; [-0.065, -.019]; p<.001). This sleep-mediated influence of asynchronous instruction propagated down to each SLS measure (p’s<.001), including a near 3-point difference on PROMIS cognitive scores (b = -2.86; [-3.73, -2.00]). Conclusion These analyses from the NESTED study indicate that sleep disruption may be one mechanism through which online instruction impacted learning during the pandemic. Sleep disturbances were unexpectedly influential for unscheduled instruction (i.e., asynchronous). Future analyses will examine specific sleep parameters (e.g., timing) and whether sleep’s influence differs in teens who self-report learning/behavior problems (e.g., ADHD). These nationwide data further underscore the importance of considering sleep as educators and policy makers determine school schedules.Item 238 Adolescent Sleep Variability, Social Jetlag, and Mental Health during COVID-19: Findings from a Large Nationwide Study(Oxford University Press, 2021-05) Wong, Patricia; Wolfson, Amy; Honaker, Sarah; Owens, Judith; Wahlstrom, Kyla; Saletin, Jared; Seixas, Azizi; Meltzer, Lisa; Carskadon, Mary; Pediatrics, School of MedicineIntroduction: Adolescents are vulnerable to short, insufficient sleep stemming from a combined preference for late bedtimes and early school start times, and also circadian disruptions from frequent shifts in sleep schedules (i.e., social jetlag). These sleep disruptions are associated with poor mental health. The COVID-19 pandemic has impacted education nationwide, including changes in instructional formats and school schedules. With data from the Nationwide Education and Sleep in TEens During COVID (NESTED) study, we examined whether sleep variability and social jetlag (SJL) during the pandemic associate with mental health. Methods: Analyses included online survey data from 4767 students (grades 6-12, 46% female, 36% non-White, 87% high school). For each weekday, participants identified if they attended school in person (IP), online-scheduled synchronous classes (O/S), online-no scheduled classes (asynchronous, O/A), or no school. Students reported bedtimes (BT) and wake times (WT) for each instructional format and for weekends/no school days. Sleep opportunity (SlpOpp) was calculated from BT and WT. Weekday night-to-night SlpOpp variability was calculated with mean square successive differences. SJL was calculated as the difference between the average sleep midpoint on free days (O/A, no school, weekends) versus scheduled days (IP, O/S). Participants also completed the PROMIS Pediatric Anxiety and Depressive Symptoms Short Form. Data were analyzed with hierarchical linear regressions controlling for average SlpOpp, gender, and school-level (middle vs high school). Results: Mean reported symptoms of anxiety (60.0 ±9.1; 14%≧70) and depression (63.4 ±10.2; 22%≧70) fell in the at-risk range. Shorter average SlpOpp (mean=8.3±1.2hrs) was correlated with higher anxiety (r=-.10) and depression (r=-.11; p’s<.001) T-scores. Greater SlpOpp variability was associated with higher anxiety (B=.71 [95%CI=.41-1.01, p<.001) and depression (B=.67 [.33-1.00], p<.001) T-scores. Greater SJL (mean=1.8±1.2hrs; 94% showed a delay in midpoint) was associated with higher anxiety (B=.36 [.12-.60], p<.001) and depression (B=.77 [.50-1.03], p<.001) T-scores. Conclusion: In the context of system-wide education changes during COVID-19, students on average reported at-risk levels of anxiety and depression symptoms which were associated with greater variability in sleep opportunity across school days and greater social jetlag. Our findings suggest educators and policymakers should consider these sleep-mental health associations when developing instructional formats and school schedules during and post-pandemic.Item 675 COVID-19 Instruction Style (In-Person, Virtual, Hybrid), School Start Times, and Sleep in a Large Nationwide Sample of Adolescents(Oxford University Press, 2021-05) Meltzer, Lisa; Wahlstrom, Kyla; Owens, Judith; Wolfson, Amy; Honaker, Sarah; Saletin, Jared; Seixas, Azizi; Wong, Patricia; Carskadon, Mary; Pediatrics, School of MedicineIntroduction: The COVID-19 pandemic significantly disrupted how and when adolescents attended school. This analysis used data from the Nationwide Education and Sleep in TEens During COVID (NESTED) study to examine the association of instructional format (in-person, virtual, hybrid), school start times, and sleep in a large diverse sample of adolescents from across the U.S. Methods: In October/November 2020, 5346 nationally representative students (grades 6–12, 49.8% female, 30.6% non-White) completed online surveys. For each weekday, participants identified if they attended school in person (IP), online-scheduled synchronous classes (O/S), online-no scheduled classes (asynchronous, O/A), or no school. Students reported school start times for IP or O/S days, and bedtimes (BT) and wake times (WT) for each applicable school type and weekends/no school days (WE). Sleep opportunity (SlpOpp, total sleep time proxy) was calculated from BT and WT. Night-to-night sleep variability was calculated with mean square successive differences. Results: Significant differences for teens’ sleep across instructional formats were found for all three sleep variables. With scheduled instructional formats (IP and O/S), students reported earlier BT (IP=10:54pm, O/S=11:24pm, O/A=11:36pm, WE=12:30am), earlier WT (IP=6:18am, O/S=7:36am, O/A=8:48am, WE=9:36am), and shorter SlpOpp (IP=7.4h, O/S=8.2h, O/A=9.2h, WE=9.2h). Small differences in BT, but large differences in WT were found, based on school start times, with significantly later wake times associated with later start times. Students also reported later WT on O/S days vs. IP days, even with the same start times. Overall, more students reported obtaining sufficient SlpOpp (>8h) for O/S vs. IP format (IP=40.0%, O/S=58.8%); when school started at/after 8:30am, sufficient SlpOpp was even more common (IP=52.7%, O/S=72.7%). Greater night-to-night variability was found for WT and SlpOpp for students with hybrid schedules with >1 day IP and >1 day online vs virtual schedules (O/S and O/A only), with no differences in BT variability reported between groups. Conclusion: This large study of diverse adolescents from across the U.S. found scheduled school start times were associated with early wake times and shorter sleep opportunity, with greatest variability for hybrid instruction. Study results may be useful for educators and policy makers who are considering what education will look like post-pandemic.Item A National Survey of U.S. Adolescent Sleep Duration, Timing, and Social Jetlag During the COVID-19 Pandemic(Taylor & Francis, 2023) Wesley, Katherine L.; Cooper, Emily H.; Brinton, John T.; Meier, Maxene; Honaker, Sarah; Simon, Stacey L.; Pediatrics, School of MedicineObjectives: To assess changes in duration, timing, and social jetlag in adolescent sleep during the COVID-19 pandemic and evaluate the impact of mood, physical activity, and social interactions on sleep. Study design: An online survey queried adolescents' sleep before (through retrospective report) and during the initial phase of COVID-19 in May 2020. Adolescents (N = 3,494), 13-19 years old, in the United States (U.S.) answered questions about their current and retrospective (prior to COVID-19) sleep, chronotype, mood, and physical and social activities. Linear regression models were fit for time in bed, reported bed and wake times, and social jetlag during COVID-19, accounting for pre-COVID-19 values. Results: Total reported time in bed (a proxy for sleep duration) increased on weekdays by an average of 1.3 ± 1.8 hours (p < .001) during COVID-19, compared to retrospective report of time in bed prior to COVID-19. During COVID-19, 81.3% of adolescents reported spending 8 hours or more in bed on weekdays compared to only 53.5% prior to COVID-19. On weekdays, bedtimes were delayed on average by 2.5 hours and wake times by 3.8 hours during COVID-19 compared to prior to COVID-19. On weekends, bedtimes were delayed on average by 1.6 hours and waketimes by 1.5 hours (all p's < 0.001). Social jetlag of >2 hours decreased to 6.3% during COVID-19 compared to 52.1% prior to COVID-19. Anxiety and depression symptoms and a decline in physical activity during COVID-19 were associated with delayed bed and wake times during COVID-19. Conclusions: During COVID-19, adolescents reported spending more time in bed, with most adolescents reporting 8 hours of sleep opportunity and more consistent sleep schedules. As schools return to in-person learning, additional research should examine how sleep schedules may change due to school start times and what lessons can be learned from changes that occurred during COVID-19 that promote favorable adolescent sleep.Item Sibling sleep-What can it tell us about parental sleep reports in the context of autism?(American Psychological Association, 2016-06) Schwichtenberg, A. J.; Hensle, Tara; Honaker, Sarah; Miller, Meghan; Ozonoff, Sally; Anders, Thomas; Pediatrics, School of MedicineSleep problems are common in families raising children with Autism Spectrum Disorder (ASD). Clinicians often depend on parent reports of child sleep but minimal research exists to address the accuracy or biases in these reports. To isolate parent-report accuracy (from differences in sleep behaviors), the sleep of younger siblings were assessed within a two-group design. The present study compared parent diary reports of infant sibling sleep to videosomnography and actigraphy. In the high-risk group, families had at least one child with ASD and a younger sibling (n = 33). The low-risk comparison group had no family history of ASD (n = 42). We confirmed comparable sleep behaviors between the groups and used paired t tests, two-one-sided-tests (TOST), and Bland-Altman plots to assess parent report accuracy. The parameters of sleep onset, nighttime sleep duration, awakenings, morning rise time, and daytime sleep duration were evaluated. Diary and videosomnography estimates were comparable for nighttime sleep duration, morning rise time, and awakenings for both groups. Diary and actigraph estimates were less comparable for both groups. Daytime sleep duration estimates had the largest discrepancy with both groups reporting (on average) 40 additional minutes of sleep when compared to actigraphy estimates. In the present study, families raising children with ASD were just as accurate as other families when reporting infant sleep behaviors. Our findings have direct clinical implications and support the use of parent nighttime sleep reports.Item Unexplained Practice Variation in Primary Care Providers' Concern for Pediatric Obstructive Sleep Apnea(APA, 2018) Honaker, Sarah; Dugan, Tamara; Daftary, Ameet; Davis, Stephanie; Saha, Chandan; Baye, Fitsum; Freeman, Emily; Downs, Stephen; Pediatrics, School of MedicineObjective To examine primary care provider (PCP) screening practice for obstructive sleep apnea (OSA) and predictive factors for screening habits. A secondary objective was to describe the polysomnography (PSG) completion proportion and outcome. We hypothesized that both provider and child health factors would predict PCP suspicion of OSA. Methods A computer decision support system that automated screening for snoring was implemented in five urban primary care clinics in Indianapolis, Indiana. We studied 1086 snoring children between 1 and 11 years seen by 26 PCPs. We used logistic regression to examine the association between PCP suspicion of OSA and child demographics, child health characteristics, provider characteristics, and clinic site. Results PCPs suspected OSA in 20% of snoring children. Factors predicting PCP concern for OSA included clinic site (p < .01; OR=0.13), Spanish language (p < .01; OR=0.53), provider training (p=.01; OR=10.19), number of training years (p=.01; OR=4.26) and child age (p<.01), with the youngest children least likely to elicit PCP concern for OSA (OR=0.20). No patient health factors (e.g., obesity) were significantly predictive. Proportions of OSA suspicion were variable between clinic sites (range 6% to 28%) and between specific providers (range 0% to 63%). Of children referred for PSG (n=100), 61% completed the study. Of these, 67% had OSA. Conclusions Results suggest unexplained small area practice variation in PCP concern for OSA amongst snoring children. It is likely that many children at-risk for OSA remain unidentified. An important next step is to evaluate interventions to support PCPs in evidence-based OSA identification.