bluuebunny/crossref_metadata_2025_split huggingface dataset:
0336 Workday Rhythms and Bedtime Behaviors: The Role of Work Timing and Duration in Bedtime Procrastination
Authors: Carlson Steven , Williams Paula 
Published: April 2024

Abstract

Introduction
Bedtime procrastination, or bedtime delays in the absence of external obligations, is a common behavior that undermines multiple dimensions of sleep health. Most research investigating the factors which underly bedtime procrastination centers on cognitive processes (i.e., self-regulation, rumination, worry). However, individuals may also intentionally delay their bedtime to provide themselves with personal time to wind down at the end of a late work day. The current study sought to evaluate whether work timing, duration, and time spent winding down at the end of the day were associated with bedtime procrastination in a daily diary investigation of young adults’ sleep behaviors.

Methods
117 young adult participants (Mage = 25.2, SD = 8.3) completed 14-days of experience sampling assessment, including self-report measures of daily work schedules and morning ratings of prior-night bedtime procrastination and wind down time. Participants also completed the morningness-eveningness questionnaire as a measure of chronotype. Multilevel models were constructed to identify the contributions of work timing (start and end time), work duration, and end-of-day wind down duration in daily bedtime procrastination.

Results
Across days, average later work start time (B = 0.50, p = 0.017) and end time (B = 0.39, p = 0.043) were associated with higher average bedtime procrastination. However, there were no significant associations observed at the level of daily observations. Work duration and self-reported wind down duration at night were not associated with either average or daily bedtime procrastination. Secondary analyses revealed that, when chronotype was included in the model, the association between work timing and bedtime procrastination was reduced to non-significance.

Conclusion
Individuals who had later average work timing were more likely to habitually procrastinate their bedtime. However, the within-person association was not significant; daily changes in work schedule were not associated with same-day variation in bedtime procrastination, indicating that this may not be a mechanism for sleep delay behavior. Further, findings suggest that shared variance with evening chronotype may partially explain the observed association between work timing and bedtime procrastination. Future research should distinguish between preferences for doing activities in the evening and circadian timing in the development of bedtime procrastination.

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0337 Impact of Sleep Schedule Changes on the International Space Station
Authors: Jansen Rachel , Flynn-Evans Erin , Glaros Zachary 
Published: April 2024

Abstract

Introduction
Astronaut crews have historically averaged six hours of sleep per night. In recent years, ISS crew have had more stable schedules, with consistent bed and wake times. Despite these improvements, there remain uncontrollable operational events that require crewmembers to shift their sleep. It is unclear what impact these acute schedule changes have on sleep and performance outcomes. The aims of this analysis are to characterize approaches to sleep shifting and to determine the impact on sleep outcomes and crew alertness and performance.

Methods
Crewmembers (n = 20) on the ISS were provided with actiwatches that they wore before flight, inflight, and immediately upon return. They were scheduled for 8.5 hours of sleep per day, between 2130-0600, unless operational events took place during the sleep episode. We characterized the impact of two types of sleep shifts, including splitting the daily sleep opportunity in two (“split sleep”) and shifting the entire sleep opportunity later, following the operational event.

Results
Ten crewmembers had 15 episodes of split sleep while inflight. These periods surrounded seven separate operational events that interfered with their nominal sleep window. The first sleep opportunity typically occurred before the disrupting event, while the second took place the following morning. Sleep duration was shorter (M1=2.60(0.80) vs. M2=4.11(1.51)) and efficiency lower (M1=74.72(13.94) vs. M2=82.50(8.99)) during the first sleep opportunity. When aggregating the two periods, the sleep opportunity lasted 7.08(1.06) hours. Thirteen individuals had 28 phase delayed sleep episodes following 11 disruptive events. These single sleep episodes were 5.99(1.05) hours long, sleep efficiency averaged 84.31(7.71), and the sleep opportunity was 6.85(0.67) hours. On remaining nights, crewmembers averaged 6.63(0.49) hours of sleep with a sleep efficiency of 82.51(3.41) and sleep opportunity of 7.45(0.51).

Conclusion
Scheduling astronauts for off-nominal operations came with some costs. When crew split their sleep, they slept longer than the average, while a delay reduced sleep. Crew had shorter sleep opportunities when forced to sleep outside of the nominal window, leading to improved sleep efficiencies. Further study is needed to determine the best scheduling approaches to accommodate uncontrollable operational events.

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0338 Consolidated Work Schedule: The Impact on Firefighters’ Sleep and Health
Authors: Billings Joel 
Published: April 2024

Abstract

Introduction
Career fire departments in the US typically operate on a variety of 24-hour shift schedules, the most common being 24-hours-on and 48-hours-off (24/48). Recently, more departments have expressed interest in consolidated work schedules, specifically the 48-hours-on and 96-hours-off (48/96), to attract new recruitments, reduce commute frequencies, and improve firefighter morale. While some firefighters may be able to rest when not otherwise responding to emergencies and other tasks, it is uncertain how consolidated work schedules impact sleep and health. Therefore, the objective of this research is to assess sleep and health outcomes before and after firefighters transitioned to a consolidated work schedule.

Methods
A Southcentral US fire department (n=24) participated in this longitudinal study. Baseline assessment was conducted while firefighters operated on the 24/48 and post assessment was conducted six months after transitioning to the 48/96. Total sleep time (TST) was assessed for 18-days each round using wrist actigraphy and the Emergency Services Sleep Diary. At the beginning of each round, participants completed a questionnaire that included the Insomnia Severity Index (ISI), Beck Depression Inventory II (BDI-II), Beck Anxiety Invitatory (BAI), and Multidimensional Assessment of Fatigue (MAF).

Results
The results of paired t-tests indicated statistically significance difference means for ISI scores [t(23) = 2.83,p&lt; 0.01] and BDI-II scores [t(23) = 4.49,p&lt; 0.001], suggesting insomnia and depression scores improved during the 48/96. Mean ISI scores before and after shift schedule transition are 7.4(4.2) and 5.5(3.5), respectively. The mean BDI-II scores before and after are 5.3(4.8) and 3.3(4.4). No statistically significant differences were found in TST, BAI, and MAF scores.

Conclusion
Firefighters reported an improvement in insomnia and depression six months after transitioning to the 48/96 consolidated work schedule. Since sleep, anxiety, and fatigue were not statistically different, the results suggest that the 48/96 may provide firefighters an opportunity to develop a more consistent sleep pattern due to fewer early awakenings to commute to work. However, further research is needed to continue assessing these relationships along with exploring how differences in workload (e.g., emergency calls) may influence these outcomes.

Support (if any)
The development of the research reported herein was supported by FEMA Fire Prevention & Safety Grant, EMW-2022-FP-00464.
0343 Sleep Knowledge, Information, and Values Test: A New Measure to Examine College Students
Authors: Reynolds Alexandria , Scullin Michael , Oliver Michael , Walther Sam , Hughes Joshua , Holladay Cathryn 
Published: April 2024

Abstract

Introduction
College students are notorious for inconsistent sleep schedules and poor sleep hygiene, which can influence mental health and academic success. Many intervention programs seek to improve college student sleep quality by educating them on the importance of sleep and healthy sleep behaviors; however, it remains an open question whether poor sleep behaviors are due to a lack of knowledge about sleep. To inform this issue, we developed a test of sleep knowledge and compared outcomes to standard scales of sleep duration and quality.

Methods
Participants (N=130, 21 male) included full-time undergraduate students (mean age=19.65, SD=1.54 years) who completed a series of online questionnaires examining sleep quality and duration (Pittsburgh Sleep Quality Index, PSQI), sleep hygiene (Sleep Hygiene Index, SHI), and a new measure of sleep knowledge (Sleep Knowledge, Information, and Values Test, SKIV). The SKIV is a self-reported questionnaire that includes questions about weekday and weekend sleep duration, sleep quality, confidence and source of sleep health knowledge, perceived importance of sleep education in different populations, and basic sleep hygiene and sleep health questions.

Results
Average sleep duration (PSQI) was 7.00 hours per night (SD=1.36) and sleep quality was poor (PSQI M=6.86, SD=3.33). Participants scored an average 13.47 out of 20 points (SD=3.59) on multiple choice and multi-answer questions about general sleep knowledge (SKIV). SKIV sleep knowledge test scores and SKIV ratings of importance of sleep education were positively correlated with SHI scores (M=21.53, SD=7.56; r=.309, p&lt;.001 and r=.267, p=.002), but not PSQI global sleep quality (r=-.025, p=.783; r=.005, p=.954) or PSQI sleep duration (r=.065, p=.463; r=.071, p=.423). SHI scores were significantly correlated with PSQI sleep quality (r=.467, p&lt;.001).

Conclusion
College students with greater sleep knowledge reported engaging in better sleep hygiene practices, but still showed short duration or poor quality sleep. Therefore, future interventions should go beyond sleep education to changing environmental features (e.g., noise and light in dormitories) and institutional practices (early class start times, midnight homework deadlines) that hinder sleep health in students.

Support (if any)
None.
0344 Convergent and Divergent Validity of a Sleep Health Literacy Measure
Authors: Feldman Emily , Slavish Danica 
Published: April 2024

Abstract

Introduction
The Sleep Health Literacy (SHL) scale, grounded in the integrated model of health literacy, consists of two subscales: “Sleep Health Communication” and “Sleep Health Knowledge.” This study aims to explore the validity of the SHL scale by examining its relationships with scales measuring health literacy, sleep, and non-related constructs. Further, this study sought to conduct confirmatory factor analysis to evaluate the reliability of the SHL measure.

Methods
253 students were recruited from the undergraduate SONA psychology pool (M age = 20.3, 53% white, 75% women). Participants completed the Dysfunctional Beliefs about Sleep Scale, Sleep Practices and Attitudes Questionnaire (SPAQ), Sleep Beliefs Scale (SBS), Sleep Hygiene Index (SHI), Insomnia Severity Index (ISI), All Aspects of Health Literacy Scale (AAHL), Alcohol Use Disorder Identification Test (AUDIT), and General Anxiety Disorder 7 Item (GAD-7) Scale as well as the Sleep Health Literacy (SHL) Scale.

Results
The SHL part 1 was significantly associated with part 2 scores (r = .25, p &lt; .00), the sleep hygiene index (r = .21, p &lt; .002), sleep beliefs scale total correct (r = .28, p &lt; .00), AAHL total score (r = -.27, p &lt; .00), AAHL communicative subscale (r = -.39, p &lt; .00), functional (r = .15, p = .04) and AAHL critical subscale (r = -.25, p &lt; .00). Scores on part 2 of the SHL were correlated with items correct on the SBS (r = .53, p &lt; .00) and AAHL functional subscale (r = .15, p = .04). Confirmatory factor analysis (CFA) was performed on two factors and showed a model with reasonable fit (χ² = 144.986, df = 43, p &lt; 0.001, RMSEA = 0.103, CFI = 0.833, GFI = 0.891, AGFI = 0.832).

Conclusion
This study examined the Sleep Health Literacy (SHL) Scale, a tool designed to assess an individual’s ability to communicate and comprehend sleep-related concepts. The scale demonstrated significant associations with related constructs, including sleep hygiene, sleep beliefs, and health literacy. These findings contribute to the SHL scale’s potential for assessing sleep health literacy and offer useful insights into areas of refinement.

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0345 The Moderating Effect of Screen Time on the Relationship Between Physical Activity and Sleep in Young Athletes
Authors: turpin chloé , Caron Jean-François , Pétrin Rachel , Forest Geneviève 
Published: April 2024

Abstract

Introduction
Studies have emphasized the significance of sleep in performance and well-being of young athletes. Physical activity has been shown to improve various aspects of sleep in adolescents, including sleep quality. Yet, excessive screen time has been found to have a negative impact on sleep among adolescents, possibly dampening the beneficial effects of physical activity. Hence, our research aimed to investigate the moderating effect of screen time on the relationship between physical activity and sleep quality in young athletes.

Methods
211 young elite athletes (M=14.9±1.6 years old; 60.4% females) completed online questionnaires, including the Pittsburgh Sleep Quality Index (PSQI) and a homemade sports and lifestyle habits questionnaire. A moderation analysis was conducted using PROCESS 4.2 to examine the moderating effect of screen time (the average number of hours per day spent on screens) on the relationship between physical activity (the average number of training hours per week) and sleep quality (subscale #1 of the PSQI). Age, BMI, and sex were added as covariates, since they were correlated with the physical activity and sleep quality variables.

Results
The moderation model was significant (F(6,203)=8.14, p&lt;.001) and accounted for 16.2% of the variance. Results indicate a significant main effect of screen time on sleep quality (b=.294, p=.004) and a significant interaction of screen time and physical activity on sleep quality (b=.005, p=.021). Physical activity was associated with sleep quality when screen time was at one SD below the mean (b=-.025, p&lt;.018) but not at the mean (b=-.006, p&lt;.433) nor above the mean (b=.014, p&lt;.236). The simple plot analysis revealed that when young athletes had low screen time, more physical activity was related to better sleep quality, while lower training hours were associated with poorer sleep quality. However, in athletes with high and average screen time, their level of physical activity was not related to their sleep quality.

Conclusion
This study highlights the possible mitigating effect of screen time on the potential beneficial association between physical activity and sleep in young athletes. This underscores the importance of promoting healthy lifestyle habits and appropriate sleep hygiene among athletes, who are also a population at greater risk of sleep disturbances.

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0347 Sleep Behaviour and Shift Work Tolerance in New Paramedics Beginning Shift Work
Authors: Harris Rachael , Drummond Sean P A , Meadley Ben , Rajaratnam Shantha M W , Williams Brett , Smith Karen , Bowles Kelly-Ann , Nguyen Elle , Dobbie Megan L , Wolkow Alexander P 
Published: April 2024

Abstract

Introduction
In experienced shift workers, researchers have evaluated levels of shift work tolerance (SWT) and sleep behaviours. SWT refers to not experiencing negative consequences associated with shift work, whereas sleep behaviours, describe strategies workers may use to cope with shift work. Neither sleep behaviours nor SWT have been longitudinally investigated in new emergency personnel. The current study aimed to track changes in sleep behaviour during the first 12-months of shift work, and secondly to explore whether changes in sleep behaviour were associated with SWT after 12-months of work.

Methods
One-hundred and five recruit paramedics were investigated at baseline (before shift work), and after 6- and 12-months of shift work. Paramedics’ sleep and mental health were evaluated at each timepoint via questionnaires. Participants also completed a 14-day shift work (via work diaries) and sleep (via sleep diaries and actigraphy) monitoring period at each timepoint. Sleep opportunity (SO), regularity, and behaviours in relation to nightshift were investigated. SWT at 12-months was categorised based on symptoms of depression, anxiety, insomnia, and sleep quality and efficiency on rest days.

Results
Linear mixed models found SO increased on day shifts and rest days, and sleep regularity declined from baseline to 6- and 12-months of shift work. There were no changes in SO on rest days, day shifts, or nightshifts between 6- and 12-months of shift work. Latent profile analyses identified levels of SWT as high (n=52), medium (n=27), and low (n=9) after 12-months of shift work. These profiles were primarily distinguished by levels of insomnia, depression, and anxiety. Increasingly irregular sleep between 6- and 12-months of shift work, and prioritising major sleep episodes (i.e., ≥3hrs) rather than naps at 6-months predicted classification as high SWT.

Conclusion
Our findings suggest after 12-months of shift work, different levels of SWT exist in paramedics, distinguished by their severity of insomnia, depression, and anxiety symptoms. Though sleep behaviours across the whole cohort did not change between 6- and 12-months, those whose sleep became less regular were more likely to have high SWT. Likewise, prioritising major sleep episodes at 6-months was associated with better SWT after 12-months of shift work.

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0348 The Mediating Role of Sleep Duration in the Link Between Night Shift Work and Inflammation in Nurses
Authors: Bates Amanda , Husein Danya , Feldman Emily , Slavish Danica , Taylor Daniel , Kelly Kimberly , Ruggero Camilo , Dietch Jessica , Messman Brett , Kohut Marian 
Published: April 2024

Abstract

Introduction
Identifying risk factors and mechanisms involved in heightened inflammation is critical for developing targeted interventions. Night shift work is a well-established factor contributing to disrupted and insufficient sleep, which is linked to heightened inflammation. This study aimed to assess the impact of night shift frequency and sleep duration on inflammatory biomarkers in a sample of nurses.

Methods
As part of a larger longitudinal study, 392 nurses (mean age = 39.54 years, 92% female; 23% night shift-working) completed daily sleep diaries and wore an actigraphy watch for 7 days. On day 7, nurses had blood drawn to measure inflammatory markers, including C-reactive protein (CRP), interleukin-6 (IL-6), tumor necrosis factor alpha (TNF-α), and interleukin-1 beta (IL-1β). Mediation analyses were conducted to examine the mediating role of sleep duration on the links between night shifts worked in the past 7 days and inflammatory markers on day 7.

Results
Sleep duration did not mediate the effect of night shift work on inflammatory biomarkers. However, there were several significant direct effects. More night shifts worked was associated with lower actigraphy-measured sleep duration (b = -0.16, p &lt; 0.001) and greater IL-6 (b = 0.03, p = 0.002). Similarly, more night shifts worked (b = 0.03, p = 0.003) and lower self-reported sleep time (b = -0.19, p &lt; 0.001) were independently linked to greater IL-6. Fewer night shifts worked (b = -0.05, p = 0.02) and lower self-reported sleep duration (b = -0.19, p &lt; 0.001) were associated with higher IL-1β.

Conclusion
Given the critical role that nurses play in the healthcare system, it is important to understand the potentially modifiable factors impacting their health and well-being. This study demonstrated that short sleep duration may explain how night shift work impacts physiological dysregulation in nurses, including elevated systemic inflammation. Promoting adequate sleep opportunity in shift workers may be a way to improve their long-term health outcomes, although additional future experimental work on this topic is needed.

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NIAID 1R01AI128359 (PIs: Taylor & Kelly)
0349 Differences in Sleep on Working and off Days in Shift Working Nurses
Authors: Nagy Samantha , Hackworth Katelyn , Lopez Nicole , Taylor Daniel 
Published: April 2024

Abstract

Introduction
Sleep deficiencies are common in nurses, with up to 89% of nurses working some form of shiftwork (i.e., working before 6am and/or after 9pm). It is estimated that approximately 34% of nurses report insomnia disorder and 14% report shift work sleep disorder. Nurses face unique physical, psychological, and occupational demands that disrupt their sleep quality and duration and may conflict with their natural circadian rhythm.

Methods
Nurses (N = 26, 88% female, 80% white, mean age = 36.16 years, SD = 8.56) were asked to wear an Actiwatch to measure objective sleep parameters, a daily adhesive sweat collection patch, provide two blood samples (at Day 1 and Day 7), and report daily subjective sleep parameters (total sleep time, sleep onset latency, wake after sleep onset, and sleep efficiency) via the Consensus Sleep Diary for 7 days. The sample was further divided into day shift (n = 14) and night shift (n = 12) nurses. Data collection and cleaning are ongoing and preliminary results of complete sleep diary data are presented.

Results
Results of the independent sample t tests suggest that total sleep time was significantly different on days on shift versus off shift (t(86) = 2.94, p = .002) for day shift nurses but not for night shift nurses (t(76) = .48, p = .317). There was no difference in total sleep time between day and night shift workers. Additional exploratory analyses will be completed by the conference, comparing additional parameters (e.g., timing) in individual sleep periods (i.e., 1st work day, 2nd work day; 1st off day, 2nd off day) both within (night & day shift), as well as between (night vs day shift) groups on the final sample (N=40; 20 day and 20 night shift).

Conclusion
The results may indicate that day shift nurses have more variable sleep than night shift nurses. Further analyses will help fill gaps in our understanding of the deficient (i.e., inadequate, interrupted, mistimed) sleep in nurses (i.e., within and between day and night working), as well as inform potential interventions (i.e., CBTI for shift workers) to improve the sleep of critical nursing staff.

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