bluuebunny/crossref_metadata_2025_split huggingface dataset:
0134 Associations between psychological resilience and slow wave sleep in healthy adults
Authors: Chen Chris Xie , Wang Ran , Cheung Forrest Tin Wai , Chan Ngan Yin , Chan Joey , Li Cheng , Hou Wai Kai , Yau Sonata Suk-Yu , Liu Fiona Yan , Lee Tatia Mei-Chun , Li Shirley Xin , Wing Yun Kwok 
Published: May 2023

Abstract

Introduction
Psychological resilience can be viewed as a personality trait, an ability to bounce back, or a positive outcome after life adversities. Although there have been increasing reports of the importance of sleep and circadian factors in contributing to an individual’s resilience, current studies were devoid of objective measurements and in-depth analysis. Whether psychological resilience is related to the slow wave sleep that facilitates recovery processes is of particular interest.

Methods
This study focused on the association between resilience and sleep in healthy young individuals free of physical and mental disorders. 160 young adults (61.7% female, mean age: 29.55±4.94) were included. Psychological resilience was defined as both a trait and a positive health outcome despite adversities. The trait resilience was measured by the Connor-Davidson Resilience Scale (CDRS-10), at which scores exceeding the 50th percentile of CDRS-10 were categorized as a “High resilient trait”. The outcome resilience was measured by the residual score of the linear regression model with psychological health level as the dependent variable and accumulative adversities as the independent variable. Those with a positive residual value were categorized as “Resilient outcome”. The accumulative adversities included childhood adversities (e.g., emotional and physical neglect, sexual abuse) and lifetime stressors (e.g., accident, death of families or close friends). Sleep architecture was assessed by polysomnography, and sleep microstructure was computed by spectrum power analysis and slow wave sleep autodetection.

Results
Resilient participants had more slow wave sleep (SWS; N3%: 15.69% vs 12.89%, p = 0.021) and higher delta power in N3 (Absolute: 750.36 uV2 vs 617.55 uV2, p = 0.059) than those non-resilient participants. Linear regression models showed that increased SWS was associated with higher resilient trait (SWS density: B=0.25, p=0.006; Absolute power of N3 delta: B=0.003, p=0.004) and resilient outcome (N3%: B=0.02, p=0.058; SWS density: B: 0.03, p=0.073; Delta power in N3: B=0.0004, p=0.020).

Conclusion
Psychological resilience was related to greater slow wave sleep. The findings suggested a critical role of sleep quality in maintaining psychological resilience. Longitudinal studies are need to examine the underlying mechanism of the link between resilience and slow wave sleep.

Support (if any)
The Collaborative Research Fund of Hong Kong, China (C7069-19GF).
0136 Decreased Sleep Efficiency May Link Adverse Childhood Experiences with Increased Visceral Adiposity
Authors: Schwager Laura , Hart Thomas , Zucker Anna , Flores Mark , Diesel Sara , Moon Chooza , Thomas Emily , Jenkins Nathaniel 
Published: May 2023

Abstract

Introduction
Poor sleep has been shown to negatively impact cardiometabolic health. Adverse Childhood Experiences (ACEs), potentially traumatic events occurring within the first 18 years of life, have been linked to both poor sleep and cardiometabolic disease in adulthood. Evidence is needed to understand whether poor sleep plays a mechanistic role in the link between ACE exposure and cardiometabolic risk. The purpose of this study was to examine associations of ACE exposure with self-reported sleep efficiency (SE%) and waist circumference (WC).

Methods
In 25 young adults (21F/4M; mean±SD, age=25±5 y), we assessed ACE exposure using the 10-item ACE Questionnaire and SE% as the reported average sleep duration relative to time-in-bed from the Pittsburgh Sleep Quality Index. We measured WC, a known cardiometabolic risk factor, as a surrogate of visceral adiposity. We used multiple linear regression analyses to examine associations between ACE exposure, SE%, and WC adjusted for sex. We then utilized ANCOVA analyses to examine the possible mechanistic effect of SE% on the relationship between ACE exposure and WC. For these analyses, participants with 0-1 ACEs were categorized as low-ACE exposure (ACE-low) and participants with 2+ ACEs were categorized as moderate-to-high ACE exposure (ACE-mh).

Results
Following adjustment for sex, ACE score predicted SE% (β=-0.53, p=0.009) and WC (β=0.52, p=0.01), and SE% predicted WC (β=-0.44, p=0.03). Similarly, ANCOVA analyses indicated that ACE-mh was associated with greater WC than ACE-low, adjusted for sex (adjusted means ± 95% CI, 0.86 ± 0.07 m vs. 0.78±0.06 m; p=0.049). However, the effect of ACE group on WC was no longer significant following inclusion of SE% as a covariate (0.84 ± 0.07 m vs. 0.80 ± 0.07 m; p=0.29).

Conclusion
Both ACEs and sleep efficiency are associated with visceral adiposity. Further, SE% may serve as a mechanistic biobehavioral link between ACE exposure and increased visceral adiposity in young adults. These preliminary findings warrant further investigation with implications for sleep interventions as a possible preventative approach to reduce cardiometabolic risk in individuals exposed to ACEs.

Support (if any)
Research reported in this publication was partly supported by the NCATS of the NIH (UL1TR002537) and by the Injury Prevention Research Center through the CDC (R49 CE003095).
0137 The effect of the 2020 US Presidential election on sleep and its relationship to public mood and alcohol consumption
Authors: Cunningham Tony , Fields Eric , Denis Dan , Bottary Ryan , Stickgold Robert , Kensinger Elizabeth 
Published: May 2023

Abstract

Introduction
Major events, such as the Super Bowl, World Cup, elections, and disasters can influence the general public's affective state in both positive and negative directions. More recently, evidence has indicated that other affect-related processes, such as sleep, may be similarly influenced, but the relationship between changes in sleep and emotion metrics in the wake of these significant events remains unknown. Here, we investigated the extent that a major sociopolitical event – the 2020 US presidential election – impacted sleep, measures of public mood and emotional well-being, and alcohol consumption. We also explored the relationship between changes in sleep, affect, and alcohol consumption during the peak period of election stress.

Methods
A non-representative, convenience sample of US-residing (n = 437) and non-US-residing (n = 106) participants were recruited online for participation as part of the Boston College COVID-19 Sleep and Well-Being Study (https://osf.io/gpxwa/). For the present analysis, participants were responded to daily surveys via email assessing their affect, sleep, and alcohol consumption during a baseline period (October 1-13, 2020) and in the days surrounding the 2020 US Election (October 30-November 12, 2020).

Results
Changes following the election were investigated separately for US and non-US participants. Election Day evoked a significant reduction in sleep duration and efficiency, coupled with heightened stress, negative affect, and increased alcohol use. While the impact was greater for US participants in a number of domains, non-US residents also reported sleep loss and increased stress on Election night compared to baseline. Across participants, changes in emotional well-being and alcohol consumption on Election Day correlated with changes in sleep metrics on Election Night.

Conclusion
These results suggest that major sociopolitical events can have global impacts on sleep that interact with significant fluctuations in public mood and well-being. Further, while the largest impact is on the local population, these results suggest that globalization may extend the effects beyond borders. These findings provide an ecologically-relevant example of the relationship between daytime mood and subsequent sleep and highlight the potential impact of future sociopolitical events on public well-being.

Support (if any)
Project was supported by Boston College and a Small Research Grant from the Sleep Research Society Foundation
0140 Nightmares are Associated with Increased Suicidality in Young Adulthood: A Population-based Cohort Study
Authors: Atha Raegan , Paquet Caitlin , Calhoun Susan , He Fan , Vgontzas Alexandros , Liao Jason , Bixler Edward , Liao Duanping , Fernandez-Mendoza Julio 
Published: May 2023

Abstract

Introduction
Childhood nightmares have a second increase in incidence in young adulthood, which has been attributed to trauma and psychopathology. As suicide rates are high in young adults and have been associated with nightmares, more research is needed regarding this relationship in this age range. This study aimed to examine the association of nightmares, independent of sleep disturbances, insufficient sleep or trauma-history, with suicidality in young adulthood.

Methods
The Penn State Child Cohort is a random, population-based sample of 700 children (5-12 years at baseline) studied in the sleep laboratory who returned for follow-up visits during adolescence and young adulthood. For the current study, 258 young adults (25.1±2.7 years old, 53.9% female, 24.8% racial/ethnic minority) completed their follow-up visit 15.9±2.0 years later. Nightmares were ascertained by self-report. The presence of suicidality was ascertained from responses on items querying suicidal ideation and/or attempts via clinically-relevant sources (i.e., MINI structured interview, Child Behavior Checklist Adult Self-Report, and Depression Anxiety and Stress Scale). General linear and logistic regression models adjusted for important covariates.

Results
Subjects reporting nightmares (n=109) had a significantly higher rate of suicidality (29%) than those absent of nightmares (14%; p=0.002), after adjusting for sex, age, sleep disturbances, sleep duration and trauma history. This rate was even higher (46%) in those reporting moderate-to-severe nightmares (n=24; p&lt; 0.01). The odds of suicidality associated with nightmares were 2.3-fold (95%CI=1.1-4.7), after adjusting for sex, age, sleep disturbances, sleep duration and trauma history (p=0.023); a risk that increased to 6.1-fold (95%CI=2.0-18.6) in those reporting moderate-to-severe nightmares (p=0.001).

Conclusion
These findings further strengthen previous research that has established nightmares’ significant relationship to increased suicidality, even when controlling for other important risk factors such as sleep disturbances and trauma history. Furthermore, as these results come from a random, population-based sample, it also demonstrates the generalizability of the association between nightmares and suicide. As the search for effective prevention strategies for suicide continues, it will be important to assess for the presence and severity of nightmares in those who express suicidal ideation, especially given the treatable nature of nightmares.

Support (if any)
National Institutes of Health (R01HL136587, R01MH118308, UL1TR000127)
0141 Short-Term Stability of Sleep Parameters in Comorbid Nightmares and Chronic Insomnia Disorder
Authors: Paquet Caitlin , Lenker Kristina , Calhoun Susan , Vgontzas Alexandros , Bixler Edward , Fernandez-Mendoza Julio 
Published: May 2023

Abstract

Introduction
Nightmares are highly comorbid with insomnia and have been associated, yet not consistently, with distinct polysomnographic (PSG) disturbances, such as reduced total sleep time (TST), sleep efficiency and slow wave sleep as well as increased nocturnal awakenings and wake after sleep onset (WASO) or abnormal REM sleep. However, most prior studies have relied on a single night of PSG and the degree of stability of sleep parameters or overall differences between individuals with nightmares comorbid with insomnia disorder (NCI), individuals with chronic insomnia disorder (CID) and otherwise good sleeping controls (GSC), remain unknown. Therefore, the aim of this study was to determine if there were significant differences amongst these aforementioned groups in the way their sleep changes across time while being studied in the lab.

Methods
A total of 142 GSC, 126 CID and 24 NCI participants underwent 8-hour PSG recordings for 4 consecutive nights. Outcomes included sleep continuity, architecture, and REM-related parameters across nights 1 through 4. Intraclass correlation coefficients (ICC) with mixed-effect variances and repeated-measure analysis of variance (ANOVA) were used to determine short-term stability as well as between-subjects and time-by-group interaction effects, respectively.

Results
ICC were similar across groups on all outcomes (ICCs&gt;0.6) except that the NCI group did not display stability for WASO, stage 1 sleep, REM latency or REM interval. There were no significant time-by-group interaction effects on PSG parameters (ps&gt;0.05). There were significant between-group effects for SOL, number of awakenings, WASO, TST, REM latency, and number of REM episodes (all ps&lt; 0.05), where the NCI group showed significantly longer SOL (58.10±11.08), shorter TST (6.64 hours±1.02), and less REM episodes (3.81±0.76).

Conclusion
This study suggests greater night-to-night variability and overall disturbance in nighttime sleep continuity and REM sleep in individuals with NCI. These disturbances may be attributed to the occurrence of nightmares, causing wakefulness out of REM sleep, as well as a greater level of hyperarousal as evidenced by the greater SOL and reduced TST, relative to the other groups. These data also suggest the utility of objective sleep measures in nightmare research and clinical practice alike.

Support (if any)
National Institutes of Health (UL1TR000127)
0144 A Mixed Methods Exploration of Stigma, Discrimination, and Sleep among Individuals on Medication for Opioid Use Disorder
Authors: Nwanaji-Enwerem Uzoji , Sadler Lois , Jeon Sangchoon , Barry Declan , Yaggi H , Redeker Nancy 
Published: May 2023

Abstract

Introduction
Many individuals who suffer from opioid use disorder (OUD) experience symptoms of insomnia. OUD-related stigma and discrimination are major concerns and represent complex, chronic stressors that lead to negative health and social outcomes. However, how OUD-related stigma and discrimination are associated with insomnia among those on Medication for OUD (MOUD) is not known. The purpose of this study is to examine the associations among OUD-related stigma, intersectional discrimination, and insomnia among patients on MOUD.

Methods
This concurrent mixed methods study is a sub-study (N = 120) of the NIH funded Collaboration Linking Opioid Use Disorder and Sleep (CLOUDS) study. Insomnia was measured with the Insomnia Severity Index. OUD-related stigma was assessed with the Brief Opioid Stigma Scale, and intersectional discrimination was assessed with the Intersectional Discrimination Index. Quantitative data were analyzed via Spearman correlations. A sub-sample of 25 participants participated in semi-structured interviews. Qualitative questions explored individuals’ perceptions and experiences of stigma and discrimination and their influence on sleep. Qualitative data were analyzed with thematic analysis.

Results
Hypotheses were partially supported. Spearman correlations revealed a small positive correlation (r = .17, p = .04) between intersectional discrimination and insomnia severity. Correlations between OUD-related stigma and insomnia severity were not statistically significant. Patterns of negative thinking and rumination were described by participants who felt their stigmatizing and discriminatory experiences affected their sleep.

Conclusion
Findings add to the growing literature linking discrimination to sleep deficiency in highly stigmatized populations. With larger diverse samples, future researchers should (1) utilize longitudinal designs to explore underlying pathways by which discrimination and stigma affect sleep and (2) identify intervention approaches that target multiple levels [individual, interpersonal, community, and structural] to decrease the impacts of discrimination and stigma on self-perception and sleep outcomes for those battling OUD.

Support (if any)
0146 Associations Between Mood and Sleep Architecture in Sedentary Office Workers
Authors: Vogan Olivia , Cheruka Caitlin , Egeler Mara , Kubala Andrew , Sanders Rachel , Paley Joshua , Patel Sanjay , Hall Martica , Perera Subashan , Gibbs Bethany , Kline Christopher 
Published: May 2023

Abstract

Introduction
Sleep, and rapid eye movement (REM) sleep in particular, has been suggested to play an important role in mood regulation. Currently, most of this research has come from laboratory settings under constrained conditions; less is known about one’s sleep in their own home. The purpose of this study was to further examine the associations between home-based polysomnography (PSG) sleep parameters and mood disturbance.

Methods
This cross-sectional study used baseline data from 120 inactive adults with desk-based jobs (52.5% female, 43.8±10.7 y) who were enrolled in an ongoing clinical trial. Mood was assessed using the Profile of Mood States (POMS); its 7 subscales (tension, anger, fatigue, depression, esteem-affect, vigor, confusion) were summed (with a constant of 100) to generate a Total Mood Disturbance (TMD) score with a higher score indicating greater TMD. Sleep stages were assessed after a full workday using one night of at-home PSG. Multiple linear regression models examined associations between sleep stages and mood adjusting for age, gender, and whether the assessment occurred pre- or post-COVID-19 emergence.

Results
The mean TMD score was 98.6±18.3. On average, participants slept for 397.4±60.0 minutes with a sleep efficiency of 84.6±9.1%. The mean percentage of time spent in REM sleep was 22.5±6.6%; the mean percentage of time spent in non-rapid eye movement (NREM) sleep, stage 1 (N1), stage 2 (N2), and stage 3 (N3) sleep were 7.8±5.0%, 53.7±10.1%, and 16.0±9.1%, respectively. A greater percentage of REM sleep was associated with lower TMD (β=-0.22, p=0.01). A greater percentage of N1 sleep was also associated with lower TMD (β=-0.23, p=0.01). However, neither percent of N2 nor N3 sleep were associated with TMD (p=0.10 and p=0.12, respectively).

Conclusion
Overall, the findings of this study support current literature that suggests REM sleep plays a significant role in mood regulation. They also suggest, aside from N1 sleep, NREM sleep may not impact mood disturbance. In the future, the effects of sleep architecture on mood disturbance could further be explored through randomized controlled trials.

Support (if any)
This study was funded by National Institutes of Health (NIH) grants R01HL134809 and R01HL147610.
0147 Does Sleep Regularity Link Child Maltreatment to Depressive Symptoms among Incoming First-Year College Students?
Authors: Rojo-Wissar Darlynn , Parade Stephanie , Barker David , Van Reen Eliza , Sharkey Katherine , Carskadon Mary 
Published: May 2023

Abstract

Introduction
Sleep patterns may partially account for associations between early life adversity and poor health outcomes; however, few studies have empirically tested this hypothesis. We examined whether an index of sleep regularity mediated associations between child maltreatment (CM) and depression symptoms among emerging adults undergoing the major life transition of starting college.

Methods
First-year college students (N=731; 41% male; 48% Non-Hispanic White, 21% Non-Hispanic Asian, 15% Hispanic all races, 5% Non-Hispanic Black, and 11% Non-Hispanic other races) completed daily sleep diaries (DSDs) for 9 weeks and completed the Childhood Trauma Questionnaire (CTQ) and Center for Epidemiologic Studies Depression Scale (CES-D) following DSD completion. DSD data were used to compute participants’ Sleep Regularity Index (SRI). We used a nonparametric SEM bootstrap approach to examine whether sleep regularity mediated associations between childhood trauma and depressive symptoms, controlling for sex, race/ethnicity, and US vs. international status. Separate models were run for CTQ total score and five CTQ subscale scores: emotional, physical, and sexual abuse, and physical and emotional neglect.

Results
The prevalence of moderate to severe CM was 20.7%, and 40% reported clinically significant depressive symptoms at the end of the assessment period. Significant indirect effects of CTQ total score (estimate=0.02, 95% CI=0.003, 0.036); emotional abuse (0.06 [0.004, 0.107]); physical abuse (0.08 [0.003, 0.164]); sexual abuse (0.06 [0.014, 0.114]); emotional neglect (0.04 [0.002, 0.075]) on greater depression symptoms through lower sleep regularity were observed; and we saw no significant indirect effect of physical neglect (0.04 [-0.015, 0.089]). The percentage of the total effect of CM (i.e., CTQ total score and subscale scores) on greater depressive symptoms accounted for by lower sleep regularity were CTQ total score: 6%; physical abuse: 24%; sexual abuse: 19%; emotional abuse: 7%; and emotional neglect: 5%.

Conclusion
Variable sleep patterns account, in part, for associations between CM and depressive symptoms among first-year college students, with the largest effects observed for physical and sexual abuse. Sleep regularity should be included as a target in student health interventions on college campuses and may help buffer against poor mental health outcomes for students with CM.

Support (if any)
P20GM139743, MH079179, T32HD101392, P20GM139767.
0148 Early Diagnosis of Post-Traumatic Stress Disorder in Nurses based on Physical Behavior and Sleep Actigraphy using Machine Learning
Authors: Garg Ria , Slavish Danica , Taylor Daniel , Ruggero Camilo , Messman Brett , Kelly Kimberly , Dietch Jessica 
Published: May 2023

Abstract

Introduction
Disturbances in sleep/wake patterns and circadian rhythms are common in post-traumatic stress disorder (PTSD). Nurses are one population particularly susceptible to both sleep/circadian disruption and PTSD, given they frequently engage in shift work and experience high occupational stress. However, the specific types of sleep and circadian disruptions in PTSD have not been identified in nurses using validated measures of sleep, limiting potential intervention efforts.

Methods
To address this gap, we developed a machine learning algorithm for calculating risk of PTSD in nurses based on sleep, light, and physical activity patterns derived from actigraphy, in conjunction with inflammatory biomarkers. Participants were 392 nurses (mean age = 39.54, 92% female, 78% White) recruited from two Dallas-area hospitals for a larger longitudinal study on sleep and vaccine response. At baseline, nurses reported on demographics and PTSD symptoms using the PTSD Checklist for DSM-5 (PCL-5). Nurses were categorized as having probable PTSD if they reported scores &gt;31 on the PCL-5. Nurses wore actigraphy devices for two weeks to track sleep/wake, activity counts, and light exposure. In the middle of the two-week period, nurses also had a blood draw to determine inflammatory markers interleukin-6 (IL-6), C-reactive protein (CRP), tumor necrosis factor-alpha (TNF-α), IL-1 beta (IL-1β), and interferon gamma-induced protein 10 (IP-10).

Results
4.7% of nurses met criteria for probable PTSD. Using the actigraphy and inflammatory biomarker data, a Recurrent Neural Network (RNN) was developed to detect PTSD risk. Furthermore the Ridge Classifier was tested using activity counts, light exposure, and sleep/wake data to obtain an accuracy score of 0.97 and an F1 score (ranging between 0 and 1) of 0.96, indicating that the model was able to balance and maximize precision and determine PTSD risk successfully.

Conclusion
Using a novel machine learning algorithm, we show that actigraphy data can be used to accurately and non-invasively detect PTSD risk among nurses. Although additional validation is needed, results tentatively highlight the utility of harnessing real-time data to inform just-in-time adaptive interventions for PTSD among nurses. Given the essential role nurses play in the healthcare system, finding ways to support their well-being is of critical public health importance.

Support (if any)
NIH/NIAID R01AI128359