bluuebunny/crossref_metadata_2025_split huggingface dataset:
0203 Time-In-Bed Classroom Challenges: Incentivizing Undergraduate Students to Improve Sleep During Final Exams Week
Authors: Cruz Andri , Nickel Allison , Barley Blake , Diaz Laurel , Scullin Michael 
Published: May 2023

Abstract

Introduction
Late bedtimes and all-nighters are ingrained into student culture, especially during final exam week. We previously found that extra credit incentives “to sleep 8 hours” encouraged longer sleep durations in small-sized classes. The current work investigated whether a modified approach—extending one’s time-in-bed—was scalable to larger-sized classes and dependent on the size of the incentive.

Methods
Across two studies, 129 undergraduate students completed baseline actigraphy and sleep diary monitoring early in Fall 2021 or Fall 2022. At the end of the semester, students could opt to take a time-in-bed challenge to earn large-sized (8 points; Study 1) or medium-sized (5 points; Study 2) extra credit on their final exam if they maintained an average time-in-bed of nine hours (or average total sleep time of eight hours). A smaller-sized extra credit (2 points) could be earned if the overall benchmarks were not met but one still improved on their baseline sleep duration by 20 minutes or sleep efficiency by 3%. Participants provided informed consent and the class instructor was kept blinded until after exams were graded.

Results
Most students attempted the time-in-bed sleep challenge (Study 1: 86.79%; Study 2: 92.11%). In Study 1, large-sized extra credit encouraged a 66 minute/night improvement in actigraphy-defined total sleep time from early-semester baseline (6.72 ± 1.18 hours) to final exams week (7.82 ± 0.89 hours; p&lt;.001). In Study 2, a medium-sized extra credit opportunity improved actigraphy-defined total sleep time by 46 minutes/night from baseline (6.69 ± 0.80 hours) to finals week (7.46 ± 1.12 hours; p&lt;.001). The interaction with incentive size was non-significant (p&gt;.05). Sleep efficiency was similar across timepoints in Study 1 (83.6 ± 5.35 to 82.8 ± 5.18, p&gt;.10) and Study 2 (82.9 ± 6.1 to 82.9 ± 6.47, p&gt;.10). Students did not have to sacrifice total sleep time to perform well on their final exams (rs&lt;.10); interestingly, students with higher sleep efficiencies performed better on their final exams (r=.28, p&lt;.05).

Conclusion
The all-nighter culture of final exam week can be overcome by creating incentives for students to prioritize nighttime sleep.

Support (if any)
National Science Foundation (1920730 and 1943323).
0205 Catechol-O-methyltransferase Genotype, but not Dopamine Receptor D2 Genotype, Modulates Slow Wave Sleep
Authors: Muck Rachael , Van Dongen Hans , Satterfield Brieann 
Published: May 2023

Abstract

Introduction
Slow wave sleep (SWS), a putative marker of sleep homeostasis, robustly increases following total sleep deprivation (TSD). The neurotransmitter dopamine is substantively involved in sleep-wake regulation. Single nucleotide polymorphisms (SNP) in the dopaminergic genes of dopamine receptor D2 (DRD2) and catechol-O-methyltransferase (COMT) have been found to alter dopamine availability primarily in the striatum and prefrontal cortex (PFC), respectively. Here, we investigate if these SNPs are associated with changes in SWS at baseline and following TSD.

Methods
N=105 healthy adults (ages 26.5±5.0; 55 females) completed one of three 4-day/3-night in-laboratory studies with 10h baseline sleep opportunity (22:00–08:00), 38h TSD period, and 10h recovery sleep opportunity. Sleep periods were recorded polysomnographically and visually scored according to AASM criteria. DNA isolated from whole blood was assayed for DRD2 (C957T, rs6277) and COMT (Val158Met, rs4680) genotypes using real-time PCR. For each genotype, SWS duration was analyzed using mixed-effects ANOVA with fixed effects for genotype, night (baseline vs. recovery), and their interaction, controlling for study, and a random effect over subjects on the intercept.

Results
DRD2 genotypes (25 C/C, 52 C/T, 28 T/T) and COMT genotypes (23 Val/Val, 58 Val/Met, 24 Met/Met) were in Hardy-Weinberg Equilibrium. As expected, SWS was substantially increased during recovery sleep compared to baseline. There was no main effect of DRD2 (F[2,102]=2.78, p=0.07), nor interaction of DRD2 by night (F[2,102]=1.45, p=0.24). However, there was a significant main effect of COMT on SWS duration (F[2,102]=3.20, p=0.04), without interaction of COMT by night (F[2,102]=1.43, p=0.24). Compared to Met allele carriers, Val homozygotes displayed reduced SWS duration during both baseline and recovery sleep.

Conclusion
The DRD2 T allele is associated with decreased dopamine D2 receptors and decreased dopaminergic signaling in the striatum relative to the C allele. The COMT Val allele is associated with increased enzymatic activity and decreased dopaminergic signaling in the PFC relative to the Met allele. Our results indicate that compared to striatal dopamine, PFC dopamine may be a more prominent mediator of SWS regulation, with less PFC dopamine corresponding to less SWS. This needs to be confirmed in a larger sample.

Support (if any)
CDMRP W81XWH1610319; USAMRDC W81XWH1810100; ONR N000141310302; NIH R21CA16769; ARO W911NF2210223.
0207 Acute Total Sleep Deprivation Adversely Impacts Cardiovascular Measures across Long-Duration Intervals
Authors: Goel Namni , Rosendahl-Garcia Kathleen , Pasetes Lauren 
Published: May 2023

Abstract

Introduction
For the first time, we comprehensively investigated the effects of repeated exposures to baseline (BL), total sleep deprivation (TSD), and recovery (REC) phases at 2, 4, and 8 months on cardiovascular (CV) measures.

Methods
We conducted a five-day experiment twice (at months 2 and 4) in a 4-month study (N=6 healthy adults; 3 females), and a similar five-day experiment three times (at months 2, 4, and 8) in an 8-month study (N=5 healthy adults; 2 females). During these repeated experiments, CV measures were collected via echocardiography or blood pressure monitor [systolic and diastolic blood pressure (SBP and DBP)] at three assessment time points: 1) after two baseline 8h time in bed (TIB) nights (BL); 2) after a night of total sleep deprivation (TSD); and 3) after two recovery nights of 8-10h TIB (REC). CV measures were also collected once pre and post study. Seated stroke volume (SV), cardiac index (CI), left ventricular ejection time (LVET), SBP and DBP, systemic vascular resistance index (SVRI), and mean arterial pressure (MAP) were collected. Data did not significantly differ between the two studies and therefore were pooled together for analysis (N=11). Repeated measures ANOVA and post-hoc comparisons corrected for multiple testing examined CV measures across all time points.

Results
SV, CI, SVRI, LVET, and SBP, but not DBP or MAP, showed significant changes across time. SV increased with TSD compared to pre-study, BL, and post-study at month 2. CI increased with TSD compared to pre-study, BL, REC, and post-study at month 2. SVRI decreased with TSD compared to pre-study, BL, and REC at month 2 and LVET and SBP increased with TSD compared to BL at month 2. In the 8-month sample subset, SBP increased with TSD compared to BL at month 8.

Conclusion
TSD increased SV, CI, LVET, and SBP, and decreased SVRI, compared to BL at month 2. Notably, TSD also increased SBP compared to BL at month 8, indicating a sustained adverse effect after long-duration repeated exposure to TSD. Overall, SV, CI, SVRI, LVET, and SBP are reliable biomarkers for assessing the harmful long-term cardiovascular effects of TSD.

Support (if any)
NASA grants NNX14AN49G and 80NSSC20K0243 (NG)
0209 Cardiovascular Measures Display Robust Phenotypic Stability to Total Sleep Deprivation Across Long-Duration Intervals
Authors: Pasetes Lauren , Rosendahl-Garcia Kathleen , Goel Namni 
Published: May 2023

Abstract

Introduction
For the first time, we determined whether individual differences in cardiovascular (CV) measures are observed in response to total sleep deprivation as well as the stability of such responses across 4-month and 8-month long-duration studies.

Methods
We conducted a five-day experiment twice (at months 2 and 4) in a 4-month study (N=6 healthy adults; 3 females), and a similar five-day experiment three times (at months 2, 4, and 8) in an 8-month study (N=5 healthy adults; 2 females). During these repeated experiments, CV measures were collected via echocardiography or blood pressure monitor [systolic blood pressure (SBP)] at three assessment time points: 1) after two baseline 8h time in bed (TIB) nights (BL); 2) after a night of total sleep deprivation (TSD); and 3) after two recovery nights of 8-10h TIB (REC). Seated SBP, stroke volume (SV), heart rate (HR), cardiac index (CI), left ventricular ejection time (LVET), and systemic vascular resistance index (SVRI) were collected. Data did not significantly differ between the two studies and therefore were pooled together for analysis (N=11). Intraclass correlation coefficients (ICCs) assessed the stability of CV measures during TSD. Spearman’s rho assessed the relative rank of individuals’ averaged TSD-TSD responses across CV measures.

Results
TSD ICCs across months 2 and 4 were substantial to almost perfect for all CV measures (0.755-0.962). In the 8-month sample subset, TSD ICCs were moderate to almost perfect across 2, 4, and 8 months for all CV measures (0.643-0.944). Individuals also exhibited significant consistency of responses within CV measures: SV was positively correlated with LVET (ρ=0.791, P=0.004), HR was negatively correlated with LVET (ρ=-0.627, P=0.039) and CI was negatively correlated with SVRI (ρ=-0.936, P&lt; 0.001).

Conclusion
Vulnerability to repeated TSD exposures showed trait-like stability in CV measures across months 2, 4, and 8, with significant consistency of responses within CV measures. For the first time, we demonstrate robust phenotypic stability of cardiovascular measures during total sleep deprivation across 2-month, 4-month and 8-month time points in long-duration studies. Our results herald the use of biomarkers and countermeasures for prediction and mitigation of this critical vulnerability.

Support (if any)
NASA grants NNX14AN49G and 80NSSC20K0243 (NG)
0212 Insufficient Sleep and Behavioral Health in the Military: A 5-Nation Perspective
Authors: Alger Sara , Bennett Clare , Bennett Neanne , Huebner Matthew , Lee Jennifer , Edge Heather McCuiag , Simms Amos , Adler Amy 
Published: May 2023

Abstract

Introduction
Insufficient sleep (&lt; 7 hours per night) degrades both health and performance and constitutes a risk to military mission success. Accordingly, militaries across the globe are increasingly focusing on sleep management, including the role that leaders play in fostering and promoting a healthy sleep culture. In the present study, we assessed survey data from the militaries of five nations on: 1) sleep behavior, 2) the relationship between sleep behavior and mental health, and 3) the role leaders play in improving service member sleep. The goal was to determine the extent to which insufficient sleep, its link to behavioral health, and the role of leaders were relevant in militaries across allied English-speaking nations.

Methods
Data from five nations: Australia, Canada, New Zealand, the United Kingdom, and the United States were assessed. Each nation administered a survey to a military sample, including questions on sleep problems (e.g., Insomnia Severity Index) and mental health. In addition, some countries assessed how first-line leaders addressed sleep in their units using items from the sleep leadership scale. Each data collection differed in terms of scope, setting, and objective.

Results
Insufficient sleep (&lt; 7 hours per night) was reported by 34.9%, 67.2% and 95.4% of survey respondents from the New Zealand Defence Force, Canadian Armed Forces, and the US Army, respectively. Those reporting shorter mean sleep durations also reported fewer sleep difficulties, likely reflecting higher sleep pressure from chronic sleep loss. Across all five nations, sleep problems (e.g., difficulty falling asleep) were positively correlated with behavioral health symptoms (e.g., depression and anxiety symptoms). Importantly, leader engagement in promoting healthy sleep was positively correlated with sleep duration and negatively correlated with sleep problems and behavioral health symptoms.

Conclusion
Insufficient sleep is pervasive in the militaries of the nations included in the present study – a finding that has serious implications for the behavioral health and resilience of service members, and more broadly for the overall effectiveness of these military forces. Across nations, militaries should attend to these risks and examine ways that first-line leaders can promote healthy sleep in their service members.

Support (if any)
Department of Defense Military Operational Medicine Research Program
0213 Sleep and well-being of culinary specialists on United States Navy ships
Authors: Shattuck Nita , Matsangas Panagiotis 
Published: May 2023

Abstract

Introduction
In the US Navy, “galley workers” are those sailors involved in cooking and preparing meals and maintaining the overall cleanliness and hygiene of the galley spaces and messdecks. These sailors begin their workday in the ship’s kitchen in the early morning, working until late in the evening, typically sleeping at night. The purpose of the current study was to assess the fatigue levels, work/rest patterns, health-related behaviors, and well-being of galley workers on US Navy ships while underway.

Methods
In this longitudinal field assessment, 80 fit-for-duty US Navy galley workers performed their normal duties on 11 surface ships. Participants wore actigraphs, and completed activity logs and questionnaires to include four standardized tools (Pittsburgh Sleep Quality Index – PSQI; Epworth Sleepiness Scale – ESS; Insomnia Severity Index – ISI; Profile of Mood States – POMS).

Results
Galley workers had a median age of 25 (IQR=11.8) years and most of them were male (68, 85.0%). Most galley workers reported drinking caffeinated beverages (60, 80.0%), with nicotine or tobacco products used by 22 (29.3%) participants. In terms of working out, 46 (61.3%) reported having an exercise routine. The typical schedule of the galley workers included sleeping at night with work hours extending from around 6:00 AM till 8:00 PM. Specifically, they slept on average 6.57±0.85 hours/day (~29% slept &lt; 6 hours/day) and worked 12.8±2.43 hours/day (25% worked &gt;14.5 hours/day). Approximately 84% were classified as poor sleepers, ~57% had excessive daytime sleepiness, and ~38% had elevated insomnia symptoms. Compared to adult norms for the POMS total and subscales scores, the mood of galley workers was worse in terms of total mood disturbance (84.1%), tension-anxiety (71.4%), anger-hostility (79.4%), vigor-activity (77.8%), fatigue (68.3%), and confusion-bewilderment (73.0%).

Conclusion
Galley workers on USN ships are chronically sleep-deprived and work long hours. To ameliorate the detrimental effects of these issues on sailor well-being, leaders should consider adopting strategies to improve sailor well-being. For example, appropriately timed short naps during the day, use of caffeine, and exposure to bright light may be viable methods to incorporate into the daily schedule of galley workers to alleviate the effects of their arduous work schedules.

Support (if any)
0216 The relationship between work and sleep in the naval operational environment
Authors: Matsangas Panagiotis , Shattuck Nita 
Published: May 2023

Abstract

Introduction
Several studies conducted by the Naval Postgraduate School Crew Endurance Team have shown that a sailor’s life at sea is characterized by limited opportunities to sleep and long work hours. In this environment, which is saturated with work duties, time is a rare commodity. This study assesses how work hours affect sleep duration. The information presented herein is a subset of the measures taken from multiple field assessments on sailors aboard nine different USN ships.

Methods
Longitudinal (average = 11 days; range = 7 to 18 days), prospective, naturalistic observations were made of sailors (N=675; 18-59 years of age, 79.3% males, 85.3% enlisted) while performing their normal underway duties on nine US Navy surface ships. Activity logs were used to assess work hours, messing (meals), and personal time. Sleep was objectively assessed by actigraphs.

Results
The average sailor’s workday was 11.6 hours (s.d.=2.48). Sailors slept on average 6.53 hours/day (s.d.=0.97), a median 1.34 hours/day (IQR=0.88) were spent messing/eating and a median 3.25 hours/day (IQR=2.50) were reported for personal time. Work hours were associated with daily sleep duration (F(1,602)=105, p &lt; 0.001; R2=0.148), personal time (F(1,673)=1539, p &lt; 0.001; R2=0.696), and messing time (F(1,673)=32.0, p&lt; 0.001; R2=0.044). Within the range of our data, every extra hour of work was associated with an average of ~9 minutes less sleep, ~41 minutes less personal time, and ~3 minutes less time at meals. The association between work hours and sleep duration was evident (all p&lt; 0.001) even after adjusting for confounding factors, i.e., watchstanding status (watchstander, non-watchstander), type of watch schedule (fixed, rotating), rank group (officer, enlisted), and detailed rank group (E1-E3, E4-E6, E7-E9, O1-O3, O4-O6).

Conclusion
The naval operational environment is dominated by long work hours that, in turn, lead to sleep deprivation. The competing relation between work and sleep, however, is ameliorated by the existence of personal time (i.e., spare time in which sailors do not work). More research should be focused on spare time and its importance for sailor wellbeing while underway.

Support (if any)
0217 Trait-Like Stability of Cardiovascular Measures Across Long-Duration Intervals after Baseline and Recovery Sleep Phases
Authors: Pasetes Lauren , Rosendahl-Garcia Kathleen , Goel Namni 
Published: May 2023

Abstract

Introduction
We determined for the first time whether individual differences in cardiovascular (CV) measures are observed after repeated baseline and recovery sleep (prior to and after exposure to total sleep deprivation) as well as the stability of such responses across 4-month and 8-month long-duration studies.

Methods
We conducted a five-day experiment twice (at months 2 and 4) in a 4-month study (N=6 healthy adults; 3 females), and a similar five-day experiment three times (at months 2, 4, and 8) in an 8-month study (N=5 healthy adults; 2 females). During these repeated experiments, CV measures were collected via echocardiography at three assessment time points: 1) after two baseline 8h time in bed (TIB) nights (BL); 2) after a night of total sleep deprivation (TSD); and 3) after two recovery nights of 8-10h TIB (REC). Seated stroke volume (SV), heart rate (HR), cardiac index (CI), left ventricular ejection time (LVET), and systemic vascular resistance index (SVRI) were collected. Data did not significantly differ between the two studies and therefore were pooled together for analysis (N=11). Intraclass correlation coefficients (ICCs) assessed the stability of CV measures after BL and REC. Spearman’s rho assessed the relative rank of individuals’ averaged BL and REC responses across CV measures.

Results
BL ICCs (0.821-0.944) and REC ICCs (0.806-0.869) comparing months 2 and 4 for all CV measures were almost perfect. The ICCs comparing BL vs. REC measures at month 2 (0.816-0.969) and at month 4 (0.816-0.927) for all CV measures were similarly almost perfect. In the 8-month sample subset, BL ICCs (0.693-939) and REC ICCs (0.770-960) comparing months 2, 4 and 8 for all CV measures were substantial to almost perfect. The ICCs comparing BL vs. REC measures at month 8 for all CV measures were fair to almost perfect (0.314-0.960). Individuals also exhibited significant consistency of responses within CV measures across 2 months and 4 months during BL and REC.

Conclusion
This is the first demonstration of remarkable robust phenotypic stability of a number of cardiovascular measures across repeated baseline and recovery sleep and across various CV measures in long-duration studies.

Support (if any)
NASA grants NNX14AN49G and 80NSSC20K0243 (NG)
0218 Changes in sleep architecture and topography of sleep EEG slow wave activity following acute wake extension in early adolescence
Authors: Mason Gina , Dionisos Victoria , Christiansen Taylor , Dickstein Daniel , Carskadon Mary , Saletin Jared 
Published: May 2023

Abstract

Introduction
A progression of peak sleep EEG slow wave activity (SWA; EEG power 0.5-4Hz) from posterior to anterior expression reflects brain development. Further, increased EEG SWA after extended wakefulness is a marker of sleep pressure. However, it is unclear whether recovery sleep SWA in later youth is expressed in a similar scalp topography as typical sleep. Using experimental wake-extension, we investigated homeostatic changes in sleep architecture and SWA topography in early adolescence.

Methods
Twenty-two young adolescents (M±SD: 12.03±1.14y, 12F) participated in two consecutive laboratory stays after at least a week of at-home actigraphy-monitored stabilization (9.5h in bed). A baseline night (BSL; 9.5h 21:00-06:30) was followed by wake-extension (WE) to 02:30 and a 4h recovery sleep opportunity (RS; 02:30-06:30), each monitored by polysomnography including a 25-channel EEG array. The current analyses examined R&K sleep architecture at BSL and RS. SWA in RS was compared to the first 4h of BSL in two ways: (1) absolute NREM power (µV2); (2) an index (TI) of the topographical distribution of midline SWA (FPz-AFz-Fz-FCz-Cz-CPz-Pz-POz-Oz) providing a score of 1 to 9 indicating frontal to occipital peak distribution.

Results
WE significantly altered RS sleep architecture, including an increase in slow-wave sleep (%TST) versus BSL (M±SD BSL: 26.76±5.69%, RS: 51.65±7.83%, t(21)=-17.09, p&lt;.001, d=-3.65). SWA was also significantly greater in RS (channel-averaged SWA BSL: 11883.50±5142.17 µV2, RS: 18955.82±7451.20 µV2, t(21)=-8.67, p&lt;.001) with 22/25 individual electrodes meeting Bonferroni-corrected significance (ps&lt;.001). Finally, we observed a small frontal shift (t(21)=2.39, p=.027, d=.51) of maximal SWA in RS (TI: 4.46±2.58; i.e., FCz/Cz) compared to BSL (5.32±2.78, i.e., Cz/CPz).

Conclusion
These data indicate robust sleep homeostasis in young adolescents after wake extension, expressed as increased SWA across the scalp. The findings also add to existing literature by indicating that SWA topography may also be sensitive to homeostatic challenge. Specifically, a baseline centroparietal locus of maximal SWA typical to this age became more frontocentral in recovery sleep. This anterior shift may reflect a homeostatic need over developmentally sensitive prefrontal cortex. Next steps will assess how individual responses may reflect a child’s neurodevelopment (e.g., inattention symptoms) or manifested behavior after wake extension and recovery sleep.

Support (if any)
K01MH109854, P20GM139743, R01HD103655