bluuebunny/crossref_metadata_2025_split huggingface dataset:
0139 Testing the Mood Regulatory Hypothesis of Dreaming
Authors: Baber Garrett , Jun Daiil , Girard Jeffrey , Gratton Matthew , Hamilton Nancy 
Published: April 2024

Abstract

Introduction
Dreaming has been theorized to facilitate fear extinction learning in a manner akin to desensitization therapy. A testable hypothesis from this theory is that the experience of fear in dreams leads to lower subsequent daytime negative affect. This study employed a novel natural language processing tool and multilevel modeling to test whether fear in dreams led to reductions in negative affective the next day.

Methods
Data from 553 participants (4986 observations) were analyzed from a larger online daily survey study of sleep and mental health from Boston College. Participants completed multiple days of dream reports and measures of daytime negative affect and sleep efficiency. Dream fear was estimated using a novel deep learning natural language processing model trained on fear-annotated tweets, applied to participants' dream report text. We fitted a Bayesian zero-inflated negative binomial multilevel model to estimate within- and between-person effects of dream fear on next-day negative affect while controlling for sleep efficiency, dream report word count, the difference between time of survey completion and time awake, total number of dreams per subject, and neuroticism.

Results
The analysis revealed that days with higher dream fear within individuals were associated with higher next-day negative affect, controlling for other variables. Specifically, for each standardized increase in dream fear, a 14% increase in next-day negative affect was predicted, surpassing the effect of poor sleep efficiency (6% increase). Moreover, individuals consistently reporting higher average dream fear tended to exhibit higher average negative affect (12%).

Conclusion
Contrary to the proposed hypothesis that dream fear regulates daytime mood, we found that fearful dreams may lead to lower next-day mood. Nights higher in dream fear were associated with increased next-day negative affect for that person, independent of sleep efficiency and neuroticism. Notably, dream fear appeared to contribute more than twice as much as poor sleep efficiency to heightened negative affect. Leveraging advanced natural language processing and multilevel modeling, this research increases our understanding of the ways dream experiences affect waking life by showing that fearful dreams may be an important day-to-day predictor of mood. Future work should explore dynamic relationships between dream emotions and mood.

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0141 Nighttime Napping Dampens Daily Peak of Sleepiness in Simulated Night Shift Schedules with Restricted Daytime Sleep
Authors: Muck Rachael , Jones Christopher , Basner Mathias , Dinges David , Van Dongen Hans 
Published: April 2024

Abstract

Introduction
Night shift workers experience increased sleepiness during the night due to increasing homeostatic sleep drive and reduced circadian wake drive, and because their daytime sleep is typically restricted. Nighttime napping is a countermeasure to sleepiness, but the effectiveness of different amounts of nighttime nap sleep in night shift schedules with restricted daytime sleep has not been systematically investigated.

Methods
N=79 healthy adults (ages 28.5±6.8y; 53 males) participated in a laboratory study with 8 days of simulated night shift. Subjects were randomized to one of 18 daily sleep regimens involving restricted daytime sleep (4.2h, 5.2h, 6.2h, or 8.2h TIB centered at 14:00) combined with a nighttime nap (0h, 0.4h, 0.8h, 1.2h, 1.6h, 2.0h, or 2.4h TIB centered at 02:00). Every day at 20:10, 22:10, 00:10, 04:10, 06:10, 08:10 (all post sleep inertia), subjective sleepiness and vigilant attention were assessed with the Karolinska Sleepiness Scale (KSS) and Psychomotor Vigilance Test (PVT), respectively. For each subject, circadian change was determined as the difference between the daily peak and trough of KSS scores and PVT lapses (RT&gt;500ms). Daily peak sleepiness and circadian change were analyzed using mixed-effects regression with fixed effects for nighttime nap TIB (categorical), night shift day, and their interaction; covariates for daytime sleep TIB (categorical) by itself and in interaction with day; and a random effect over subjects on the intercept.

Results
Nap duration influenced KSS daily peak (F[6,543]=2.25, P=0.037) and circadian change (F[6,543]=3.18, P=0.005), with 0h TIB (no nap) yielding the highest peak and circadian change (P&lt; 0.05), 0.8h TIB the lowest (P&lt; 0.05), and no significant differences comparing the other nap durations. Nap duration did not significantly affect PVT daily peak impairment (P=0.36) or circadian change (P=0.16).

Conclusion
Nighttime napping of any duration (0.4h–2.4h TIB) centered at 02:00 has the potential to mitigate peak subjective sleepiness during night shift schedules with restricted daytime sleep. This napping effect does not appear to extend to impairment in objectively measured vigilant attention. More research is needed to understand the extent to which performance and safety benefit from nighttime napping under conditions of sustained daytime sleep restriction during night shift schedules.

Support (if any)
NASA NCC 9-58-159 with NSBRI
0143 Effects of Optimal-timed Automatic Awakening from a Short Daytime Nap on Cognitive Performance and Fatigue
Authors: Abe Takashi , Suzuki Yoko , Suzuki Chihiro , Ohigashi Tomohiro , Maruo Kazushi , Watanabe Yumi , Endo Junki , Watanabe Takahiro 
Published: April 2024

Abstract

Introduction
Daytime naps, although known to improve performance, can impair performance if overextended, as slow-wave sleep causes sleep inertia. Hayashi et al. (2014) showed that a nap duration of 9 min after N2 onset maximized performance. However, awakening 9 min after N2 is challenging, other than in sleep laboratories, because it requires manual polysomnography (PSG) scoring. We developed a system that automatically awakens 9 min after N2 by an automatic sleep stage estimator using a blood flow meter and investigated whether this improved performance, sleepiness, and fatigue compared to no napping and also its effectiveness as compared to manual awakening.

Methods
Eighty-one healthy adults (33.6±12.8 years [mean ± standard deviation], 47 women) were randomly assigned to three groups of 27 participants each: automatic awakening, manual awakening, and rest. The digit symbol substitution test (DSST) was used to evaluate cognitive speed and visual detection task (VDT) to evaluate attention. The Karolinska Sleepiness Scale and the visual analog scale were used for the sleepiness and fatigue evaluation; the tasks were performed thrice after attaching the PSG and used as a baseline. The automatic and manual awakening groups napped wearing the blood-flow-meter device. The latter group was awakened 9 min after the N2 onset. The participants in the rest group remained awake for 22 minutes. After the nap or rest, the task was performed again for six sessions consisting of three times tasks. Groups were compared for the changes detected from the baseline in each session.

Results
The automatic awakening group woke up 19.6 ± 6.0 (mean ± standard deviation) [min-max 7.9–27.1] min from N2. Subjective sleepiness and fatigue in the automatic awakening group decreased compared to the rest group in all sessions and were comparable to those in the manual awakening group; the number of correct answers on the DSST increased in the sixth session for manual awakening compared to rest. VDT did not differ between groups.

Conclusion
Napping with the automatic awakening device improved sleepiness and fatigue comparable to manual awakening.

Support (if any)
This work was funded by Kyocera Corporation.
0144 The Impact of Controlled Rest on Neurobehavioral Outcomes at Top-Of-Descent
Authors: Hilditch Cassie , Arsintescu Lucia , Pradhan Sean , Gregory Kevin , Flynn-Evans Erin 
Published: April 2024

Abstract

Introduction
Long and irregular working hours can lead to fatigue in aviation operations. In some regions, a short nap taken on the flight deck (known as controlled rest) can be used as a countermeasure to unexpected in-flight sleepiness. We aimed to investigate the impact of taking controlled rest on neurobehavioral measures at top-of-descent.

Methods
Data from 120 long-haul (&gt; 6 h flight duration), unaugmented flights were analyzed (n = 31 pilots). Pilots wore actigraphs and completed sleep logs before and during trips. At pre-flight and top-of-descent, pilots completed a 5-minute psychomotor vigilance task (PVT) and Karolinska Sleepiness Scale (KSS). A series of mixed-effects models were conducted to assess the impact of controlled rest on outcome measures at top-of-descent. Sleep duration in the prior 48 hours, timing of the flight, and pre-flight scores for each measure were included as covariates.

Results
Due to missing data, complete data from 76 flights (n = 28 participants) were available in the models examining the PVT metrics, and data from 83 flights (n = 29 participants) were available in the analyses of the KSS. Pilots who took controlled rest had faster response speeds at top-of-descent (p = .03, η2p = 0.07; estimated marginal mean [EMM] = 4.19, standard error [SE] = 0.07, 95% CI [4.08, 4.29]) than those who did not take controlled rest (EMM = 4.00, SE = 0.05, 95% CI [3.86, 4.14]). There were no differences by controlled rest status for KSS scores and PVT lapses (p values &gt; .05, η2p values ≤ 0.01).

Conclusion
Our results suggest that taking controlled rest may improve vigilant attention at critical phases of flight and, thus, may be a useful fatigue management tool during unaugmented flights. Further research is necessary to determine the impact of factors on the decision to take controlled rest (e.g., airline culture, personal preference) and how the controlled rest policy is applied in practice.

Support (if any)
NASA Airspace Operations and Safety Program, System-Wide Safety Project.
0146 Supine Sleep Position and Angina Episodes: The Sleep Heart Health Study
Authors: Logan Jeongok , Byon Ha Do , Davis Eric , Kwon Younghoon 
Published: April 2024

Abstract

Introduction
Poor sleep features are associated with an increased risk of cardiovascular disease (CVD). While habitual sleep postures may influence cardiovascular function, previous studies have mainly focused on the benefits of left-side sleeping during pregnancy and different sleep positions in relation to musculoskeletal symptoms. It remains largely unknown how the supine position is associated with cardiovascular risk in general populations. The purpose of this study was to examine the association of supine position with angina episodes, the most common symptom of ischemic heart disease.

Methods
This study used data form the Sleep Heart Health Study (SHHS). Sleep position was operationalized as a percentage of total sleep duration in the supine position, measured by unattended home polysomnography (PSG) during SHHS visit 1. Angina was defined as the number of episodes from baseline PSG to SHHS visit 2. Multiple regression analysis was conducted with covariates including age, race, gender, body mass index, smoking status, systolic blood pressure, history of diabetes, total sleep duration, sleep efficiency, apnea hypopnea index, hypertension medication, diabetes medication (oral or insulin), lipid medication, cholesterol, triglyceride, HDL, and psychological stress, obtained during the SHHS visit 1.

Results
The study included a total of 4458 participants (2363 females, 53%) with mean age of 64.33 years old and a mean systolic BP of 125 mmHg. The mean of supine position was 33.64% and the mean number of angina episodes was 0.54. The supine position was an independent predictor of the number of angina episodes (p=&lt;.001). A one standard deviation increase in the supine position resulted in 0.076 standard deviations increase in the number of angina episodes (β=.076), while age and body mass index resulted in .077 and .098 increase in the outcome (β = .077, p=&lt;.001; β = .098, p=.&lt;.001).

Conclusion
Sleeping in the supine position was significantly associated with the number of angina episodes. However, the current study lacks specific information regarding the percentage of sleep duration in non-supine positions (either left/right side or prone position). Identifying sleep positions optimal for facilitating cardiovascular function may make a meaningful contribution to CVD prevention.

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0148 Interconnected Dynamics of Sleep Duration, Social Media Engagement, and Neural Reward Responses in Adolescents
Authors: Kiss Orsolya , Zhang Linhao , Müller-Oehring Eva , Bland-Boyd Brittany , Harkness Anya , Kerr Erin , Durley Ingrid , Arra Nicole , Camacho Leticia , Tager Lucas , Fan Ruby , Perez-Amparan Evelyn , Gombert Marie , Nagata Jason , Baker Fiona 
Published: April 2024

Abstract

Introduction
In today’s digital landscape, social media features prominently in adolescents’ social interactions and information consumption, influencing their development, potentially altering brain processes. Research shows a bidirectional relationship between social media use and both sleep health and brain activities, especially in executive control and reward processing. These neural developments are pivotal in adolescent behavioral and psychological growth, with sleep being crucial yet underexplored in the context of reward, social (media) behaviors.

Methods
This study investigated the reciprocal links between social media use, self-reported sleep duration, and brain activation in 6,516 adolescents (ages 10-14 years, 46.2% female) from the Adolescent Brain Cognitive Development (ABCD) Study®. Sleep duration was assessed from the Munich Chronotype questionnaire, and recreational social media use through the Youth Screen Time Survey. Brain activities were analyzed from fMRI scans during the Monetary Incentive Delay (MID) task, targeting regions associated with reward processing. The study used three different sets of models, switching predictors and outcomes each time, to examine the reciprocal relationships between sleep duration, brain activation, and social media use, and their interactions. Age, COVID-19 pandemic timing (before/during), and socio-demographic characteristics were included in the models.

Results
Shorter sleep duration correlated with greater social media usage (p&lt;.001). Notably, interactions between sleep duration and brain activation in the cingulate gyrus (p=.021), inferior frontal gyrus (p=.009), and precuneus (p=.008) predicted social media use. In predicting brain activity, interactions between sleep duration and social media use emerged as significant for the inferior (p=.008) and middle frontal gyrus(p=.003). For sleep duration predictions, interactions were important between social media use and brain activation spanning seven areas, including the cingulate gyrus (p=.039), hippocampus (p=.005), insula (p=.015), inferior frontal gyrus (p=.001), middle frontal gyrus (p=.003), precuneus (p=.038) and the superior frontal gyrus (p=.028).

Conclusion
These results highlight distinct relationships between sleep, social media, and activity across frontolimbic brain regions, key for executive control and reward processing. Such insights deepen our understanding of how individual's unique neural sensitivities to digital technology use and sleep necessity interact in adolescents. Future longitudinal studies based on these findings could pave the way for developing more nuanced, individualized interventions.

Support (if any)
NIH: U01DA041022 and R01MH128959.
0149 Perception of Prior Sleep-Wake State upon Abrupt Exogenous Awakenings
Authors: Hilditch Cassie , Costedoat Gregory , Bathurst Nicholas , Shattuck Nita , Flynn-Evans Erin 
Published: April 2024

Abstract

Introduction
The period immediately following an awakening is characterized by sleepiness, poor cognitive performance, and disorientation known as sleep inertia. In an exploratory analysis, we investigated the accuracy of perceived sleep-wake state after being abruptly awoken.

Methods
Thirty-six participants (18 female; 26.6 years ± 6.1) slept in their own homes and were called on a pre-set cell phone three times: twice during their habitual sleep period (approximately 45 min and 135 min after habitual bedtime) and once at their habitual waketime the next morning (n = 108 awakenings). Sleep stage prior to waking was measured by polysomnography. Researchers observed participants remotely via an infrared camera. Participants were asked whether they thought they had been ‘asleep’, ‘awake’, or ‘unsure’ immediately prior to receiving the phone call.

Results
Polysomnography determined that participants were asleep prior to the call for 88.0% (n = 99) of the awakenings (Wake: 8.3%, N1: 10.2%, N2: 27.8%, N3: 38.9%, REM: 11.1%, Undefined: 3.7%). Participants were asleep for all instances in which the self-perceived state prior to awakening was ‘asleep’. When state was self-perceived as ‘awake’ or ‘unsure’, participants were awake 25% of the time and in N3 sleep 19% of the time (sensitivity: 71.6%; specificity: 100%). One-fifth (n = 7) of the cohort were unable to correctly identify being asleep on multiple awakenings.

Conclusion
Participants correctly identified themselves as being asleep with moderately low sensitivity, but high specificity. Interestingly, even participants in deep sleep stages (N3) sometimes perceived themselves to be awake before the call. A portion of participants were consistently poor at identifying being asleep. These misperceptions of sleep-wake state upon awakening may contribute to the disorientation experienced during the sleep inertia period and may be influenced by individual differences. Although the uneven distribution of sleep-wake states in this sample limits us to descriptive statistics, our exploratory analysis suggests that a systematic assessment of perception during the sleep-wake transition and its subsequent effect on alertness, cognitive performance, and decision making is warranted.

Support (if any)
Naval Postgraduate School, via the Naval Medical Research Center's Naval Advanced Medical Development Department (MIPR N3239820WXHN007). NASA Airspace Operations and Safety Program, System-Wide Safety.
0154 Effects of Fatigue on Operational Performance in Navy Expeditionary Robotics Operators: A Descriptive Study
Authors: Dunn Timothy , Schrom Brandon 
Published: April 2024

Abstract

Introduction
Expeditionary robotics operators have a unique mission set within the Navy. These operators utilize small vessels and various robotics systems to achieve missions in austere settings. Those missions often require that operators perform their job under varying environmental conditions that have the potential to induce high levels of fatigue.

Methods
Four platoons (1, n = 10; 2, n = 9; 3, n = 9; 4, n = 11) that were enrolled in a training unit underwent a 5-day field exercise designed to simulate the operational settings of being deployed. Participants were issued a Fatigue Science ReadiBand to collect actigraphy that calculated metrics such as sleep quantity, quality, efficiency, and an alertness score. Operational data (errors) were provided to the research team via the training unit instructor staff. Participants completed the Need for Cognition Scale pre-exercise and the Intrinsic Motivation Inventory (IMI) post-exercise.

Results
Three platoons (1, 3, and 4) completed the entire exercise while platoon 2’s exercise was cut short 1 day early due to making too many critical errors. The total number of operational errors were as follows: platoon 1 committed 9 errors; platoon 2, 5 errors; platoon 3, 10 errors; and platoon 4, 2 errors. Platoons 1 and 4 showed a similar downward trend in alertness throughout the exercise, while platoons 2 and 3 had similar but more stable alertness profiles during the exercise. Sleep quality and sleep efficiency were lower in platoons 1 and 4 compared with platoons 2 and 3. Data from the IMI indicated that platoons 1 and 4 demonstrated that they felt more pressure during the exercise than platoons 2 and 3.

Conclusion
Platoon fatigue was not related to operational performance in a straightforward manner. Platoons 1 and 4 were the most operationally competent platoons per instructor feedback, though they experienced lower levels of alertness, worse sleep, and committed more or a similar number of errors relative to the other platoons. It is possible that platoons 1 and 4 were able to compensate in ways that allowed them to overcome heightened fatigue. This highlights the in-depth analyses required when assessing operational fatigue and performance during field operations.

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0155 The Influence of Subjective Sleepiness on Solider Fatigue During a 72-Hour Live-Fire Mission Simulation
Authors: Jones Rachell , Eldringhoff Hannah , Carlsson Kajsa , Overman Grace , Chaudhury Sidhartha , Bode Victoria , Elkin-Frankston Seth , Elmore Wade , Bovard Pooja , Brown Stephanie , Burke Tina 
Published: April 2024

Abstract

Introduction
The military works under 24/7 operations which can lead to sleep loss and Soldier fatigue. Both sleep loss and fatigue impact functionality and success of the Soldier and ultimately, the entire unit. The functional impact of sleepiness and fatigue can be present differently. Therefore, clarifying the relationship between subjective sleepiness and fatigue is important for military readiness and provides leadership with critical information to ensure mission success.

Methods
Fifty-one healthy, young male participants were recruited from a sample of active-duty Soldiers. The study lasted 5 days with a 72-hour live-fire mission simulation from days 2 to 4. On each of these days, Soldiers completed daily morning surveys, including measures of sleepiness using the Epworth Sleepiness Scale (an 8-question measure to identify clinical sleepiness) as well as subjective fatigue through the Visual Analog Scale.

Results
A repeated measures ANOVA showed a significant main effect for subject sleepiness and fatigue among mission days (p &lt; 0.05). Linear regression indicated sleepiness scores were significantly predictive of fatigue each mission day.

Conclusion
On mission day 3 during the 72-hour live fire mission, soldiers were significantly more sleepy and more fatigued compared to other mission days. Additionally, for each mission day, subjective sleepiness was predictive of soldier fatigue. Understanding this relationship and its predictive nature can help military leadership plan accordingly for mission and training events to maximize success in operational contexts.

Support (if any)
Department of Defense Military Operational Medicine Research Program (MOMRP); DEVCOM SC