Poverty, Literacy, and Social Transformation: An Interdisciplinary Exploration of the Digital Divide

Harnessing scholarship focused on literacy and poverty, in this article we aim to complicate the common understanding of the digital divide. First, we argue that the dominant literature on the digital divide misses broader connections between technological exclusion and broader forms of economic and social exclusion. Accordingly, and following recent qualitative research on the digital divide, we believe future scholarship must examine the complicated relationships between poverty, inequality, and the digital divide and we look to poverty scholarship to understand the complicated and shifting nature of poverty. Finally, we make the case that scholars and practitioners focused on digital literacy programs should pay attention to historical and critical scholarship on education and its role in mediating poverty and fostering social mobility, as it serves digital divide and broadband adoption scholars to understand the ways education processes can either reproduce or set the stage to alter entrenched social realities

Sleep Hygiene and Sleep Quality in Italian and American Adolescents

This study investigated cross-cultural differences in adolescent sleep hygiene and sleep quality. Participants were 1348 students (655 males; 693 females) aged 12-17 years from public school systems in Rome, Italy (n = 776) and Southern Mississippi (n = 572). Participants completed the Adolescent Sleep-Wake Scale and the Adolescent Sleep Hygiene Scale. Reported sleep hygiene and sleep quality were significantly better for Italian than American adolescents. A moderate linear relationship was observed between sleep hygiene and sleep quality in both samples (Italians: R =.40; Americans: R =.46). Separate hierarchical multiple regression analyses showed that sleep hygiene accounted for significant variance in sleep quality, even after controlling for demographic and health variables (Italians: R-2 =.38; Americans: R-2 =.44). The results of this study suggest that there are cultural differences in sleep quality and sleep hygiene practices, and that sleep hygiene practices are importantly related to adolescent sleep quality

Sleep Hygiene and Sleep Quality in Italian and American Adolescents

This study investigated cross-cultural differences in adolescent sleep hygiene and sleep quality. Participants were 1348 students (655 males; 693 females) aged 12-17 years from public school systems in Rome, Italy (n = 776) and Southern Mississippi (n = 572). Participants completed the Adolescent Sleep-Wake Scale and the Adolescent Sleep Hygiene Scale. Reported sleep hygiene and sleep quality were significantly better for Italian than American adolescents. A moderate linear relationship was observed between sleep hygiene and sleep quality in both samples (Italians: R =.40; Americans: R =.46). Separate hierarchical multiple regression analyses showed that sleep hygiene accounted for significant variance in sleep quality, even after controlling for demographic and health variables (Italians: R-2 =.38; Americans: R-2 =.44). The results of this study suggest that there are cultural differences in sleep quality and sleep hygiene practices, and that sleep hygiene practices are importantly related to adolescent sleep quality

Sleep Hygiene and Sleep Quality in Italian and American Adolescents

This study investigated cross-cultural differences in adolescent sleep hygiene and sleep quality. Participants were 1348 students (655 males; 693 females) aged 12-17 years from public school systems in Rome, Italy (n = 776) and Southern Mississippi (n = 572). Participants completed the Adolescent Sleep-Wake Scale and the Adolescent Sleep Hygiene Scale. Reported sleep hygiene and sleep quality were significantly better for Italian than American adolescents. A moderate linear relationship was observed between sleep hygiene and sleep quality in both samples (Italians: R =.40; Americans: R =.46). Separate hierarchical multiple regression analyses showed that sleep hygiene accounted for significant variance in sleep quality, even after controlling for demographic and health variables (Italians: R-2 =.38; Americans: R-2 =.44). The results of this study suggest that there are cultural differences in sleep quality and sleep hygiene practices, and that sleep hygiene practices are importantly related to adolescent sleep quality

Accounting for heterogeneous invasion rates reveals management impacts on the spatial expansion of an invasive species

Success of large-scale control programs for established invasive species is challenging to evaluate because of spatial variability in expansion rates, management techniques, and the strength of management intensity. For a well-established invasive species in the spreading phase of invasion, a useful metric of impact is the magnitude by which control slows the rate of spatial spread. The prevention of spatial spreading likely results in substantial benefits in terms of ecosystem or economic damage that is prevented by an expanding invasive species. To understand how local management actions could impact the spatial spread of an established invasive species, we analyzed distribution and management data for feral swine across contiguous United States using occupancy analysis. We quantified changes in the rate of spatial expansion of feral swine and its relationship to local management actions. We found that after 4 yr of enhanced control, invasion probability decreased by 8% on average relative to pre-program rates. This decrease was as high as 15% on average in states with low-density populations of feral swine. The amount of decrease in invasion rate was attributed to removal intensity in neighboring counties and depended on the extent of neighboring counties with feral swine (spatial heterogeneity in local invasion pressure). Although we did not find a significant overall increase in the probability of elimination, increased elimination probability tended to occur in regions with low invasion pressure. Accounting for spatial heterogeneity in invasion pressure was important for quantifying management impacts (i.e., the relationship between management intensity and spatial spreading processes) because management impacts changed depending on the strength of invasion pressure from neighboring counties. Predicting reduction in spatial spread of an invasive species is an important first step in valuation of overall damage reduction for invasive species control programs by providing estimates of where a species may be, and thus which natural and agricultural resources would be affected, if the control program had not been operating. For minimizing losses from spatial expansion of an invasive species, our framework can be used for adaptive resource prioritization to areas where spatial expansion and underlying damage potential are concurrently highest

Accounting for heterogeneous invasion rates reveals management impacts on the spatial expansion of an invasive species

Success of large-scale control programs for established invasive species is challenging to evaluate because of spatial variability in expansion rates, management techniques, and the strength of management intensity. For a well-established invasive species in the spreading phase of invasion, a useful metric of impact is the magnitude by which control slows the rate of spatial spread. The prevention of spatial spreading likely results in substantial benefits in terms of ecosystem or economic damage that is prevented by an expanding invasive species. To understand how local management actions could impact the spatial spread of an established invasive species, we analyzed distribution and management data for feral swine across contiguous United States using occupancy analysis. We quantified changes in the rate of spatial expansion of feral swine and its relationship to local management actions. We found that after 4 yr of enhanced control, invasion probability decreased by 8% on average relative to pre-program rates. This decrease was as high as 15% on average in states with low-density populations of feral swine. The amount of decrease in invasion rate was attributed to removal intensity in neighboring counties and depended on the extent of neighboring counties with feral swine (spatial heterogeneity in local invasion pressure). Although we did not find a significant overall increase in the probability of elimination, increased elimination probability tended to occur in regions with low invasion pressure. Accounting for spatial heterogeneity in invasion pressure was important for quantifying management impacts (i.e., the relationship between management intensity and spatial spreading processes) because management impacts changed depending on the strength of invasion pressure from neighboring counties. Predicting reduction in spatial spread of an invasive species is an important first step in valuation of overall damage reduction for invasive species control programs by providing estimates of where a species may be, and thus which natural and agricultural resources would be affected, if the control program had not been operating. For minimizing losses from spatial expansion of an invasive species, our framework can be used for adaptive resource prioritization to areas where spatial expansion and underlying damage potential are concurrently highest

675 COVID-19 Instruction Style (In-Person, Virtual, Hybrid), School Start Times, and Sleep in a Large Nationwide Sample of Adolescents

This article is made available for unrestricted research re-use and secondary analysis in any form or be any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.Introduction: 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

238 Adolescent Sleep Variability, Social Jetlag, and Mental Health during COVID-19: Findings from a Large Nationwide Study

This article is made available for unrestricted research re-use and secondary analysis in any form or be any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.Introduction: 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

237 Sleep disturbances, online instruction, and learning during COVID-19: evidence from 4148 adolescents in the NESTED study

This article is made available for unrestricted research re-use and secondary analysis in any form or be any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.Introduction: 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