bluuebunny/crossref_metadata_2025 huggingface dataset:
0954 Associations Between Sleep Duration and Timing and Postpartum Anxiety Symptoms
Authors: Cox Rebecca , Aylward Brandon , Macarelli Isabella , Okun Michele
Published: April 2024

Introduction

Postpartum anxiety is understudied and underdiagnosed in postpartum women, despite being more common than postpartum depression. Given associations between postpartum anxiety and adverse maternal and infant outcomes, it is crucial to identify patterns and predictors of postpartum anxiety. We examined the associations between sleep duration and timing and postpartum anxiety over 6 months following delivery.

Methods

Pregnant women (n=147; 30-39 weeks) with a history of depression completed the Pittsburgh Sleep Quality Index (PSQI), Edinburgh Postnatal Depression Scale, and Generalized Anxiety Disorder Scale-7 monthly following delivery for 6 months. Sleep duration and timing were extracted from the PSQI. Sleep timing was calculated as the midpoint between sleep onset and offset. In a multilevel model, sleep duration and timing were person-mean centered at level 1 (month level) and grand-mean centered at level 2 (participant level). Level 1 included main effects of time, sleep duration and timing, and interactions between time and person-mean centered sleep duration and timing and time and grand-mean centered sleep duration and timing. Level 2 included main effects of sleep duration and timing. Depression symptoms were included as a covariate at both levels.

Results

The intraclass correlation for anxiety symptoms was .46, supporting the use of a multilevel model. Anxiety symptoms increased over time (p<.001). Months with shorter sleep duration were associated with higher concurrent anxiety symptoms (p<.001). The effect of sleep duration on anxiety symptoms varied over time, such that those with shorter sleep duration reported higher anxiety symptoms than those with longer sleep duration in early postpartum months, whereas anxiety symptoms increased during later postpartum months regardless of sleep duration. Sleep timing was not significantly associated with anxiety symptoms (p>.05).

Conclusion

Postpartum anxiety increased over time, suggesting such symptoms are not transient features of the immediate postpartum period and highlighting the need to identify predictors. Shorter sleep duration may signal risk for elevated postpartum anxiety on a monthly timescale, particularly during early postpartum months. Treatments aimed at promoting sleep to improve postpartum anxiety may be most effective if targeted at early postpartum months. Future research should replicate these findings with objective sleep measures.

Support (if any)

Happiest Baby, Inc.; NIH T32 HL149646
0955 Correlation Between CPAP Use and Symptoms of Depression, Anxiety, and Sleepiness in Patients with OSA
Authors: Singh Amitoj , Bradshaw Samuel , Niraula Rijesh , Meghpara Sanket , Keenan Lynn , Yan Yueki , DelRosso Lourdes
Published: April 2024

Introduction

Obstructive Sleep Apnea (OSA) is a prevalent sleep disorder associated with poor health outcomes, including sleepiness, anxiety, and depression. This study aimed to further explore this relationship by looking at outcomes after treatment of OSA with continuous positive airway pressure (CPAP) therapy, using the Patient Health Questionnaire (PHQ-9), Generalized Anxiety Disorder 7 (GAD-7), and Epworth Sleepiness Scale (ESS) questionnaires respectively.

Methods

An observational longitudinal study in which the PHQ-9, GAD7, and ESS questionnaires were administered to adult patients diagnosed with OSA during the initial consultation and after three months of CPAP use. All patients had a diagnosis of OSA by a sleep study. Data collected included demographics, PSG data, and questionnaire results. Patients without follow-up or incomplete data were not included.

Results

One hundred patients were initially recruited. Thirty-five patients have completed data after three months. The mean±SD age was 50.9±15.4, BMI 36.5±8.9, 54% male and 46% female. Women were older 61.1±14 than men 46.5±14.9, p< 0.001. The percent of CPAP adherence was 68.7±36.7, and hours used per day were 5.5±1.8. The PHQ-9 initially was 10.4±5.6 decreased to 5.32±5.3 p< 0.001. GAD-7 initially 6.4±6.2 decreased to 4.29±4.8 p< 0.001, ESS initially 11.1±5.5 decreased to 5.8±4.3 p< 0.001. Neither age, BMI, or AHI correlated with compliance or hours used. The strongest negative correlation was between post-treatment GAD-7 and compliance (r= -0.45), followed by a mild negative correlation between PHQ-9 and compliance (r = -0.345). A mild positive correlation existed between the initial ESS and the AHI (r = 0.288). There were no statistical differences in questionnaire results between men and women.

Conclusion

The study demonstrates that daytime symptoms of sleepiness, depression, and anxiety improved in a cohort of patients with OSA and CPAP. The post-CPAP GAD-7 was moderately and negatively correlated with CPAP compliance percent use, while PHQ-9 was mildly negatively correlated. Initial ESS was mildly correlated with AHI, and although it improved, it was not correlated with compliance.

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0958 Prior Night Self-report and Behaviorally-assessed Sleep Duration Is Associated with the Pupillary Unrest Index
Authors: Taylor Maddison , Wescott Delainey , Klevens Alison , Franzen Peter , Roecklein Kathryn
Published: April 2024

Introduction

Excessive daytime sleepiness is experienced by approximately 5-10% of adults and 20-30% of older adults (Young et al., 2004). However, assessment of sleepiness has posed challenges, specifically lack of agreement between different assessments. While the construct of sleepiness hinges on insufficiently sleep, different assessments of sleepiness may conflate fatigue, mood, or anhedonia. This study tested whether physiological (Pupillary unrest) and subjectively assessed sleepiness were associated with prior night sleep duration. Results may allow subjective reports of sleepiness to be clarified with the potential to intervene more effectively.

Methods

Participants included 95 never depressed control (M age=38, SD=12) and individuals diagnosed with seasonal depression (M age=39, SD=12). We administrated the pupil sleepiness test, while the EYE-TRAC (R) 6000 tracked pupil diameter at 60Hz. The PUI was quantified as the cumulative change in pupil diameter (mm) over 1 minute. The average PUI over the full 11-minute protocol was calculated. Self-reported sleep duration was calculated as the difference between bedtime and waketime the night prior to the PUI. Self-report sleepiness was assessed via the Epworth Sleepiness Scale the week of the PUI assessment. A subset of participants had actigraphically-assessed sleep (n=47). We used multi-level models to account for repeated measures in winter and summer and included PUI testing time, diagnostic group, season, age, and gender as covariates. PUI was log transformed to account for skewness.

Results

The PUI was inversely associated with both self-report (b=-0.03, p=0.01) and actigraphy sleep duration (b=-0.00, p=0.02). Conversely, subjective sleepiness was not associated with either self-report sleep duration (b=-0.00, p=0.16) or actigraphy calculated sleep duration (b=-0.02, p=0.31).

Conclusion

The current findings suggest the PUI is correlated with sleep duration the prior night, but subjective reports of sleepiness is not. This indicates that sleep duration may be a mechanism contributing to excessive physiological daytime sleepiness. Individuals reporting greater sleepiness may be actually experiencing fatigue, anhedonia, or depressed mood; overlapping but distinct constructs with unique etiological considerations. Future work should work to examine how different sleep parameters may be differentially related to sleepiness and fatigue constructs, and to determine if using the PUI to match intervention strategies is clinically advantageous.

Support (if any)

NIH
0960 Unraveling Sleep EEG-ECG Interactions in Major Depression: Preliminary Results of a Coherence Analysis
Authors: Azad Mohammad Hasan , Robillard Rebecca , Higginson Caitlin , Lina Jean-Marc , Forouzanfar Mohamad
Published: April 2024

Introduction

In addition to common sleep disturbances, major depression involves intricate interactions between the cardiovascular and central nervous systems, underscoring the multidimensional nature of its pathophysiology. This study investigates how brain and heart activity interact across sleep states and brain topography in the context of depression.

Methods

Simultaneous sleep electrocardiograms (ECG) and electroencephalograms (EEG: F3, C3, and O1) were extracted from the polysomnograms of 50 individuals diagnosed with major depression and 50 controls. Following artifact removal, a coherence metric based on cross-power spectral density between the ECG and EEG was developed to characterize brain-heart connections in the 0.015-4 Hz delta and 4-8 Hz theta bands. Statistical analysis including bootstrapping, t-tests, analysis of variance, and multiple comparison tests were utilized to identify significant differences in brain-heart coherence between the depressed and healthy groups.

Results

Preliminary results show that, in NREM sleep within the theta band, individuals with depression showed significantly higher mean of ECG-EEG coherence values (MCV) compared to healthy controls across all EEG channels. MCVs for the depression and control group respectively were: 0.576±0.014 vs. 0.563±0.014 in F3, 0.545 ± 0.006 vs. 0.540±0.008 in C3, and 0.574±0.014 vs. 0.563±0.012 in O1 (p< 0.0001). No significant group difference was observed during REM sleep. Furthermore, irrespective of depression status, the MCV in O1 was significantly higher in NREM compared to REM sleep for the full spectrum between the delta and theta bands (p< 0.00001). In contrast, MCV in F3 and C3 did not significantly differ between NREM and REM sleep. In the delta band, regardless of depression status, the MCV was significantly lower in C3 compared to F3 and O1 during NREM sleep, but during REM sleep MCV was significantly higher in C3 than in O1 (p< 0.0001).

Conclusion

The higher brain-heart coherence linked to theta activity during NREM sleep we observed in people with depression may suggest stronger interactions between autonomic and cortical arousal. This could be one of the factors worsening sleep during depression. Beyond generating new insights about pathophysiological mechanisms underlying the high comorbidity between sleep, cardiovascular, and mental disorders, this may inform further work to identify multi-systemic biomarkers of depression.

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0962 Reciprocal Interactions Between Sleep and Mental Health: A Structural Equation Analysis in a Digital Cohort
Authors: Julien Coelho , Pécune Florian , D'Incau Emmanuel , Sagaspe Patricia , Levavasseur Yannick , De Sevin Etienne , Micoulaud-Franchi Jean-Arthur , Philip Pierre
Published: April 2024

Introduction

New digital tools constitute an opportunity in understanding the interactions between sleep health and mental health. Structural equation analysis applied to these e-cohort allows to study the bidirectional associations between these dimensions. Thus, we aimed to study the reciprocal interactions between behaviors (duration, temporality, regularity) and sleep health (insomnia and somnolence) and mental health (anxiety and depression).

Methods

Digital cohort of 3000 participants invited to complete weekly self-questionnaires over 17 days on their sleep health (Epworth and ISI), their mental health (PHQ-9 and PHQ-2) as well as sleep diaries which made it possible to calculate their sleep behaviors (duration, median, and regularity index). The interaction analysis used a longitudinal structure equation model.

Results

The average age of the participants was 51 years (68% women). The average sleep duration was 7h24, the median sleep time was 3h30 in the morning, the regularity index was 84/100. Among them, 57% reported insomnia (ISI≥15), 41% reported drowsiness (ESS≥11), 19% reported anxiety (PHQ-2≥3) and 18% reported depression (PHQ-9≥15). Sleep behaviors were associated with sleep health and mental health cross-sectionally. Longitudinal structural equation modeling shows bidirectional associations between sleep health behaviors and mental health.

Conclusion

The demonstration of these reciprocal interactions confirms the importance of the joint assessment and management of sleep and mental health behaviors and health in digital interventions aimed at modifying them. New interventional studies are awaited to confirm these results in the general population but also in subgroups of individuals at risk.

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0966 Mood in OSA Patients with Different Chronotypes with and Without Chronic Pain
Authors: Weber Amberlee , Weingarten Jeremy , Dubrovsky Boris , Cunningham John
Published: April 2024

Introduction

Mood has been related to chronotype, OSA and pain, although no studies have examined these three variables simultaneously. This study analyzes depression symptoms in relationship to self-reported sleep timing, PSG-determined AHI and the presence of chronic pain conditions (CPC) in patients referred for OSA evaluation.

Methods

From patients tested between 08/2017 and 04/2021, 360 (210 women) were selected based on self-reported sleep time criteria, no shift work, no significant cardiac, pulmonary, neurological, endocrine or psychiatric history except depression/anxiety; 78 had CPC (e.g., fibromyalgia, arthritis, sciatica, musculoskeletal pain and similar). Self-reported sleep times defined typical chronotype (TC, asleep 10pm-12am, wake-up 6-9am), early and late chronotypes (EC, LC, earlier or later than TC); those not clearly meeting these criteria or reporting < 6hr or >10hr of usual sleep were excluded. The Center for Epidemiologic Studies Depression Scale-Revised (CESDR) was an outcome; explanatory variables were AHI, chronotypes (EC, TC, LC), CPC; covariates were age, sex, BMI.

Results

EC (n=115), TC (n=163) and LC (n=82) were unrelated to CPC (chi-square=1.1, p=0.58). Older age (M=48.5±15.7) was predictive of lower CESDR (F=17.5, p< 0.001). AHI (M=14.6±21.0) was unrelated to CESDR (F=1.6, p=0.21) and did not interact with CPC or chronotypes. CPC presence predicted higher CESDR (F=8.1, p=0.004). Chronotypes predicted CESDR (F=7.8, p< 0.001) without significant interaction with CPC. LC/CPC-absent group had higher CESDR (M=20.7±18.9) relative to EC/CPC-absent (M=11.5±11.3, p< 0.001) and TC/CPC-absent (M=10.1±10.6, p< 0.001, Bonferroni post-hoc). Among CPC-present patients, CESDR did not significantly differ between EC (M=17.5±14.5), TC (M=16.3±10.3) and LC (M=22.9±17.3).

Conclusion

In this sample, there was no relationship between OSA and depression symptoms. In patients without CPC, late self-reported sleep time was associated with higher depression symptoms, relative to early and typical sleep times. However, in patients with CPC, CESDR scores did not reach significant difference between chronotypes, apparently due to the overall elevation of depression symptoms in these patients.

Support (if any)

none
0968 Perceived Stress and Worry Mediate the Link Between Sleep Quality and Immune Function
Authors: Lueke Niloufar , Assar Arash , Desai Vedant , Diaz Kayla , Jung Aena , LeBlanc Izabella , Lueke Adam
Published: April 2024

Introduction

Given that college students have an increased risk for spreading infection (White et al., 2003), it is important to examine factors that influence the immune functioning of this population. The present work examined the effect of sleep quality on the immune function of college students. Sleep problems are highly prevalent among college students (Kloss et al., 1011). Poor sleep quality has been shown to be related to reduced immune function (Irwin, 2015), and among college students, it has been linked to a multitude of negative outcomes, including heightened perceived stress (Veeramachaneni et al., 2019). Not only does poor sleep predict stress levels (Wu et al., 2015), but worry is a common cognitive reaction to stress (Borkovec et al., 1998). Worry has also been associated with reduced immune function (Brosschot et al., 2006). Based on this evidence, the present work proposed a serial mediation model, in which sleep quality (X) was modeled to increase perceived stress (M1), which in turn, increases worry (M2), thereby resulting in a decreased in immune function (Y).

Methods

Participants were 391 undergraduate students (68.3% female; Mage = 19.19, SDage = ±2.03) who completed scales related to sleep quality, perceived stress, worry, and immune function.

Results

A serial mediation model tested whether perceived stress (M1) and worry (M2) sequentially mediated the relation between poor sleep quality (X) and immune functioning (Y). A 95% bias-corrected confidence interval based on 5,000 bootstrap samples indicated that the indirect effect of perceived stress alone (i.e., X→M1→Y) was non-significant (indirect effect = .05, SE = .03, 95% CI [-.00, .11]). Likewise, the indirect effect through worry alone (i.e., X→M2→Y) was also non-significant (indirect effect = .01, SE = .01, 95% CI [-.01, .11]). Lastly, and as hypothesized, poor sleep quality was an indirect significant predictor of immune functioning through perceived stress and worry, in a sequential manner (i.e., X→M1→ M2→Y; indirect effect = .04, SE = .02, 95% CI [.01, .07]).

Conclusion

Findings demonstrate the importance of college students’ sleep in relation to both their mental health and subsequent immune functioning, rendering sleep as an important target for preventative intervention.

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0969 Predicting Differences Between Objective and Subjective Sleep Parameters with Mental Health Questionnaires
Authors: Marsolek Mason , Emert Sarah , Dietch Jessica , Tucker Emme , Taylor Daniel
Published: April 2024

Introduction

Differences between objectively and subjectively measured sleep can vary widely between participants and these differences may depend on individual characteristics, including mental health. The severity of mental health symptoms may be beneficial in assessing the magnitude of discrepancies between participants’ objective and subjective data. This secondary data analysis examined the predictivity of validated measures of post-traumatic stress symptoms, anxiety symptoms, and depressive symptoms on differences between sleep electroencephalogram (EEG) and actigraphy with sleep diary data.

Methods

Adults in the community (N=80; Mage=32.65 years, 63% female, 88.8% White) completed the Post-Traumatic Stress Disorder Checklist, State-Trait Anxiety Inventory, Quick Inventory of Depressive Symptomatology, and seven days of sleep assessment via sleep diaries, actigraphy, and EEG. The mean absolute value of differences between the sleep diary, actigraphy, and EEG data was calculated for total sleep time, time in bed (TIB), sleep efficiency, sleep onset latency (SOL), wakefulness after sleep onset, terminal wakefulness, and number of awakenings. Stepwise linear regression was used to examine whether the anxiety, post-traumatic stress, and depressive symptom scores were significant predictors of the objective-subjective differences between these sleep parameters.

Results

Depressive symptoms significantly predicted differences between EEG and sleep diary data for SOL, F(1,72)=9.958, p=.002, R2=0.121. Anxiety symptoms significantly predicted differences between actigraphy and sleep diary data for SOL, F(1,69)=6.335, p=.014, R2=0.084. Anxiety and post-traumatic stress symptoms significantly predicted differences between actigraphy and sleep diary data for TIB, F(2,70)=10.355, p<.001, R2=.228, βQIDS=0.62, βPCL=-.42.

Conclusion

Anxiety, post-traumatic stress, and depressive symptoms significantly predicted EEG and actigraphy objective-subjective differences for SOL and TIB. To better assess whether these variations are due to measurement type or if there are individual characteristics responsible for the discrepancies (i.e., sleep state misperception, symptom of mental health), a larger sample with more longitudinal data is needed. Additionally, future studies may focus on clinical samples. For instance, SOL and TIB variations may be indicative of mental health concerns (i.e., hyperarousal, anxiety, depression).

Support (if any)

National Institutes of Health/National Institute of Allergy and Infectious Disease (R01AI128359-01), the Foundation for Rehabilitation Psychology, and the General Sleep Corporation.
0970 Real-world Use of Solriamfetol for Excessive Daytime Sleepiness in Patients Reporting Anxiety or Depression
Authors: Kallweit Ulf , Benes Heike , Burghaus Lothar , Eglit Graham , Abeynayake Iresha , Floam Samantha , Parks Gregory , Winter Yaroslav
Published: April 2024

Introduction

Psychiatric comorbidities are common in patients with excessive daytime sleepiness (EDS) from narcolepsy or obstructive sleep apnea (OSA). Real-world efficacy and safety data of wake promoting agents in these populations is limited. Solriamfetol (Sunosi®), a dopamine/norepinephrine reuptake inhibitor that activates TAAR1 and 5HT1A receptors, is approved to treat EDS associated with narcolepsy or OSA. Solriamfetol clinical trials excluded and the prescribing information caution against use in patients with severe psychiatric comorbidities, so limited data exists for this population. Here we describe real world use of solriamfetol in German patients with narcolepsy or OSA who self-reported depression/anxiety (yes/no response) at baseline.

Methods

We performed a retrospective chart review (SURWEY) using data from German physicians who prescribed solriamfetol to patients with EDS associated with narcolepsy or OSA and at a stable dose for ≥6 weeks. Comorbidities, including anxiety/depression, were documented with background information at baseline.

Results

Of the 154 patients, n=48 (31.2%) reported anxiety and/or depression (OSA, n=23/83 [27.7%], narcolepsy, n=25/71 [35.2%]). Most patients (≥85%) reported no additional psychiatric, neurological, or sleep disorder. Regardless of primary etiology, baseline mean±SD Epworth Sleepiness Scale (ESS) scores were generally similar in patients with (OSA, 16.0±2.8; narcolepsy, 17.9±3.6) and without (OSA, 16.0±3.3; narcolepsy, 17.5±2.9) anxiety/depression. Overall, mean±SD decreases in ESS scores were 4.6±3.2 and 5.2±3.6 with and without anxiety/depression, respectively; and similar in OSA (5.2±3.1 vs 5.5±3.9), narcolepsy (3.9±3.2 vs 4.9±3.3). Ninety percent of patients achieved ≥2-point reduction in ESS scores from baseline and patients (≥89%) and physicians (≥91%) reported improvement in EDS with solriamfetol, which were both similar across primary etiologies and anxiety/depression presence. Anxiety/depression data was not collected at follow-up. Common adverse events were headache, insomnia, and decreased appetite, which generally occurred at similar rates regardless of reported anxiety/depression.

Conclusion

These real-world data describe solriamfetol treatment outcomes in narcolepsy or OSA patients who did and did not self-report anxiety/depression. Regardless of anxiety/depression, ESS scores improved, and most patients and physicians reported improved EDS. Our findings are consistent with clinical trial results and suggest that solriamfetol is effective in managing EDS symptoms in this population regardless of common psychiatric comorbidities.

Support (if any)

Axsome Therapeutics, Jazz Pharmaceuticals, Pharmanovia
0973 Romantic Partnership Mitigates the Influence of Anxiety and Mood on Sleep Disturbance in Full-Service Sex Workers
Authors: Tiani Alaina , Ramos Stephen , Du Bois Steff
Published: April 2024

Introduction

In the United States, an estimated 1-2 million full-service sex workers (FSSW) face notable physical and mental health challenges, including increased depression, anxiety, and sleep difficulties as compared to the general population (Ramos et al., 2022). The "partnership-health associations" concept suggests that romantic relationships may protect mental and physical well-being (Du Bois et al., 2021). Notably, a recent study found no significant health outcome differences between partnered and non-partnered FSSW at the univariate level (Du Bois et al., 2023). This secondary analysis aims to explore whether partnership buffers the link between mood, anxiety, and sleep disturbance among FSSW.

Methods

83 FSSW completed the Patient Reported Outcomes Measure Information System-29 (PROMIS-29) online from November 2019-February 2020. Four moderation analyses, utilizing PROCESS, examined anxiety and depression as predictor variables and global sleep disturbance score as an outcome, with partnership status (partnered versus non-partnered) as the moderating variable.

Results

The sample was primarily white (81.9%), non-Hispanic (77.1%), and cisgender female (66.3%), with a mean age of 28.01 (±4.25) years. The overall model for partnership status as a moderator of the association between anxiety and sleep disturbance was significant (F(3, 79)=17.65,p<.001,R2=.40). The interaction effect showed a significant link between increased anxiety and sleep disturbance for both non-partnered FSSW (b=0.88,SE=0.13,t(79)=6.74, p<.001) and partnered FSSW (b=0.35,SE=0.14,t(79)=2.48,p<.05), with a more pronounced association for non-partnered FSSW. Similarly, the overall model for the association between depression and sleep disturbance was significant (F(3, 79)=12.50,p<.001,R2=.32). The interaction effect indicated a significant link between increased depression and sleep disturbance for both non-partnered FSSW (b=0.75,SE=0.13,t(79)=5.61,p<.001) and partnered FSSW (b=0.34,SE=0.15,t(79)=2.18,p<.05), with a more pronounced association for non-partnered individuals.

Conclusion

Analyzing mental-physical health associations at a multivariable level provides a nuanced understanding that partnership may protect against unfavorable mood, anxiety, and sleep health associations in FSSW. Future studies should include a larger sample size and explore specific underlying mechanisms by which romantic partnership relates to a protective effect of low mood and high anxiety on sleep, both in FSSW and other groups who experience health inequities.

Support (if any)

American Psychological Foundation, The Drs. Rosalee G. and Raymond A. Weiss Research and Program Innovation Grant
0975 Mediators of the Insomnia-Suicidality Association
Authors: Simmons Zach , Jones Jolynn , Davis Elijah , Sherriff-Clayton Dustin , Jube Eric , Wright Andrew , Cruickshank Jared , Cheney Eric , Mills Andrew , Crawford Olivia , Kay Daniel
Published: April 2024

Introduction

Insomnia severity is a significant risk factor for heightened suicidality, including ideation, attempts, and death by suicide. As a modifiable risk factor, insomnia is a potential target for suicide prevention; however, the models explaining the association between insomnia and suicidality remain unclear. Our model posits that insomnia hinders sleep’s regional recuperative brain functions, contributing to daytime impairments, including emotional dysregulations. Another model links insomnia to suicidality through additional factors including perceived burdensomeness and thwarted belongingness. Each of these potential factors are associated with both insomnia and suicidality. This study aimed to investigate potential psychological mechanisms in the insomnia-suicidality association, using validated measures in a nationally representative sample.

Methods

Through a Qualtrics survey, participants (N=428) completed the Difficulties in Emotion Regulation Scale to assess emotional dysregulation, Interpersonal Needs Questionnaire to measure perceived burdensomeness and thwarted belongingness, Frequency of Suicidal Ideation Inventory to assess suicidality severity, Insomnia Severity Index, and PROMIS–Depression, and -Anxiety short forms. We used regression analyses to investigate the association between insomnia, suicidality severity, and demographic variables. Structural equation modeling was used to determine whether emotional dysregulation, perceived burdensomeness, or thwarted belongingness mediated the insomnia-suicidality severity association, even when accounting for depression.

Results

Insomnia severity was related to greater suicidality (p< 0.001, CI=0.19–0.31). This association was mediated by depression severity (p=0.836, CI=-0.06–0.08). Emotion dysregulation and perceived burdensomeness partially mediated the insomnia-suicidality severity association (β=0.06, p=0.001; β=0.18, p< 0.001), and when accounting for depression severity, fully mediated the insomnia-suicidality severity association (β=0.04, p=0.045; β=0.24, p< 0.001). Thwarted belongingness did not mediate the association before (β=0.02, p=0.142) or after accounting for depression (β=0.01, p=0.412).

Conclusion

This study replicates considerable evidence that insomnia is an important marker and risk factor for suicidality. The mechanisms through which insomnia may confer risk for suicidality include depression, emotion dysregulation, and perceived burdensomeness. Insomnia may be an ideal upstream target for reducing suicidality and its risk factors including depression, emotion dysregulation, and perceived burdensomeness.

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0978 A Spectrum of Altered Non-rapid Eye Movement Sleep in Schizophrenia
Authors: Kozhemiako Nataliia , Jiang Chenguang , Sun Yifan , Guo Zhenglin , Mylonas Dimitrios , Murphy Michael , Zhu Wei , Zhou Zhenhe· , Huang Hailiang , Manoach Dara S ,   GRINS Consortium, Wang Jun , Hall Mei-Hua· , Pan Jen· , Purcell Shaun M ·
Published: April 2024

Introduction

Multiple facets of sleep neurophysiology, including electroencephalography (EEG) metrics such as non-rapid eye movement (NREM) spindles and slow oscillations (SO), are altered in individuals with schizophrenia (SCZ). However, beyond group-level analyses which treat all patients as a unitary set, the extent to which NREM deficits vary among patients is unclear, as are their relationships to other sources of heterogeneity including clinical factors, illness duration and ageing, cognitive profiles and medication regimens.

Methods

Using newly collected high-density sleep EEG data on 103 individuals with SCZ and 68 controls, we first sought to replicate our previously reported (Kozhemiako et. al, eLife, 2022) group-level mean differences between patients and controls (original N=130). Then in the combined sample (N=301 including 175 patients), we characterized patient-to-patient variability in NREM neurophysiology. Sleep EEG preprocessing was conducted using an open-source package called Luna (http://zzz.bwh.harvard.edu/luna/).

Results

We replicated all group-level mean differences and confirmed the high accuracy of our predictive model (Area Under the ROC Curve, AUC = 0.93 for diagnosis). Compared to controls, patients showed significantly increased between-individual variability across many (26%) sleep metrics, with patterns only partially recapitulating those for group-level mean differences. Although multiple clinical and cognitive factors were associated with NREM metrics including spindle density, collectively they did not account for much of the general increase in patient-to-patient variability. Medication regime was a greater (albeit still partial) generator of variability, although original group mean differences persisted after controlling for medications. Some sleep metrics including fast spindle density showed exaggerated and accelerated age-related effects in SCZ, and patients exhibited older predicted biological ages based on an independent model of ageing and the sleep EEG.

Conclusion

We demonstrated robust and replicable alterations in sleep neurophysiology in individuals with SCZ and highlighted distinct patterns of effects contrasting between-group means versus within-group variances. That increased NREM heterogeneity was not explained by traditional clinical or cognitive patient assessments suggests the sleep EEG provides novel, nonredundant information to support the goals of personalized medicine. Collectively, our results point to a spectrum of NREM sleep deficits among SCZ

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0979 Associations Among Young Adults’ Sleep Quality and Sleepiness, Risk-taking Behaviors, and E-cigarette Attitudes
Authors: Stevens Elise , Lee Donghee , Stevens Hannah , Patterson Freda , Klerman Elizabeth , Rigotti Nancy , Robbins Rebecca
Published: April 2024

Introduction

Young adulthood is both a time of initiation and progression to habitual tobacco use and when risk-taking behaviors (e.g., sensation seeking and impulsivity) peak. Poor sleep quality and greater daytime sleepiness may influence greater risk-taking, which may, in turn, increase susceptibility to use tobacco products. We explored associations among young adults’ sleep quality and sleepiness, risk-taking, and susceptibility and motivation to use electronic cigarettes (e-cigarettes), the most popular tobacco product among this age group.

Methods

In an online survey, young adults recruited from social media who did not use e-cigarettes in the past 30 days (N=75) completed questions about their sleep quality (Pittsburgh Sleep Quality Index [PSQI], higher scores = greater sleep problems) and sleepiness (Epworth Sleepiness Scale [ESS], higher scores = greater daytime sleepiness), risk-taking (sensation seeking and impulsivity), susceptibility to use e-cigarettes, and motivations to avoid e-cigarettes in the future. Using a series of PROCESS mediation models, we examined the association between sleep (quality and sleepiness) and susceptibility and motivation to use e-cigarettes when mediated by risk-taking.

Results

Participants identified as predominantly female (77%), non-Hispanic White (60%), and were on average 23 years old (range: 18 to 26 years). Higher PSQI scores were significantly associated with greater sensation seeking (p = 0.02). Greater sensation seeking was associated with greater susceptibility to use e-cigarettes (p = 0.03). The indirect effects were significant (95% CI [0.002, 0.064]) while the direct effect between PSQI and susceptibility was not. Similarly, higher ESS scores were significantly associated with greater impulsivity (p = 0.01). Greater impulsivity was significantly associated with lower motivations to avoid e-cigarettes (p = 0.01). The indirect effects were significant (95% CI [-0.100, -0.004]) while the direct effect between ESS and motivation was not. No other associations were significant.

Conclusion

We provide preliminary evidence on how worse sleep is indirectly associated with increased susceptibility/motivation to use e-cigarettes through risk-taking. This complex association between sleep health and e-cigarette susceptibility should be further examined.

Support (if any)

This work was supported by the National Institute on Drug Abuse at the National Institutes of Health (NIH, Grant # R00DA046563 Supplement).
0981 Gender Has Inversed Roles in a Model Linking Lifetime Substance Use and Sleep
Authors: Silva Vinicius , Berro Laís , Galduróz José , Tufik Sergio , Andersen Monica
Published: April 2024

Introduction

The knowledge about the relationship between sleep and substance use constantly undergoes change. Many questions still remain, including how substance use initiation correlates to sleep parameters. In order to expand this body of knowledge, this study aimed at evaluating how lifetime substance use predicts changes in objective and subjective sleep parameters.

Methods

Volunteers from the EPISONO 2007, a large-scale epidemiological study assessing sleep in a representative sample from the city of São Paulo, Brazil, filled in questionnaires evaluating their general health, and underwent a full-night polysomnographic exam. For this analysis the first question of the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST), asking if the individual ever used any of the listed substances, was considered. Age and scores in the Beck Depression and Anxiety Indexes were included as covariates. Gender was also added as an independent variable.

Results

From the total 1,042 participants, 876(388 men and 488 women) were included. Volunteers reported use of cannabis(n=181), cocaine(n=79), inhalants(n=69), amphetamines(n=54), sedatives(n=31), alcohol(n=802) and tobacco(n=538). Lifetime use of cannabis, cocaine and sedatives directly correlated to alterations in sleep latency, REM sleep onset latency, sleep efficiency and scores in the Epworth Sleepiness Scale. Gender significantly interacted with substance use, with women who consumed cocaine and cannabis and men who never did presenting increased total sleep time when compared to their counterpart groups (men who ever consumed these substances and women who never did).

Conclusion

We found not only an effect of the lifetime consumption of popular drugs, such as cocaine and cannabis, but also identified an important role for gender, which seems to have inversed roles in males and females. These results provide an intriguing lead to unravelling a network in which gender, sleep and substance use are present, and advances in this area will be a major step in the investigation of the importance of sleep in the psychopharmacology scenario.

Support (if any)

Our studies are supported by grants from the Associacão Fundo de Incentivo à Pesquisa (AFIP) and Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP – grant #2020/13467-8 to MLA). MLA is a Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) fellowship recipient.
0984 Sleep, Anxiety, Depression, and Demand for Wearables in Adults with Autism Spectrum Disorder versus Controls
Authors: Reed Derek , Devine Jaime , Choynowski Jake , Hursh Steven
Published: April 2024

Introduction

Sleep difficulties are common in Autism Spectrum Disorder (ASD) populations. While much literature exists on sleep difficulties in ASD children, there is relatively scant research on adults. ASD is frequently co-morbid with symptoms of anxiety or depression, which are independently related to sleep problems. Personalized feedback from wearables may appeal to ASD adults looking to improve their sleep. This study examined sleep quality and severity of anxiety/depression in ASD adults with comorbid anxiety/depression and matched controls and establish demand for information about sleep from wearables in each group.

Methods

Participants were recruited through Prolific; 100 ASD adults with anxiety/depression and 100 matched controls with anxiety/depression completed the survey. Participants completed the Pittsburgh Sleep Quality Index (PSQI), General Anxiety Scale (GAD-7), Center for Epidemiologic Studies Depression Scale (CESD-10), and a task to establish demand for wearables that provide sleep or blood oxygenation information. Student’s t-tests and Cohen’s d examined between-group differences. Pearson's chi-squared test (χ²) examined differences between expected and observed frequencies of GAD-7 categories and poor sleepers (PSQI ≥ 5) between groups.

Results

Participants in the ASD group had higher anxiety (t=3.42, d=0.47, p=0.001) and depression (t=3.23, d=.45, p=0.001) than controls. Bad sleepers had higher anxiety (t=5.20, d=0.99, p< 0.001) and depression (t=5.17, d=0.98, p< 0.001) than good sleepers. Individuals in the autistic group had higher frequencies of moderate or severe anxiety than expected (χ²=12.90, p=0.05); control participants had lower frequencies of poor sleepers than expected (χ²=3.19, p=0.07). Both groups demonstrated more robust demand for sleep data than blood oxygenation data. ASD participants had more robust demand than matched controls for any wearable data.

Conclusion

ASD participants may have a higher burden of mental health and sleep issues relative to controls. The effect sizes suggest that self-report sleep quality was more strongly related to self-report depression and anxiety than autism diagnosis status. The demand task offers a novel framework to examine interest in potential sleep solutions in adult populations with co-morbid mental health diagnoses. ASD participants may have a greater interest in data from wearables; next steps will explore whether feedback from wearables can improve sleep in an adult ASD population.

Support (if any)

NA
0985 Comparison of Various Sleep Measurement Devices in Psychiatric Patients
Authors: Kawai Keita , Iwamoto Kunihiro , Miyata Seiko , Okada Ippei , Fujishiro Hiroshige , Ando Motoo , Noda Akiko , Ozaki Norio , Ikeda Masashi
Published: April 2024

Introduction

Sleep disturbances are key symptoms in psychiatric disorders. Despite the development of various methods to assess sleep patterns and their quality, the concordance between these methods in those with psychiatric disorders is unclear. In particular, it is not well understood how comorbid symptoms of depression and obstructive sleep apnea (OSA), which are common in psychiatric disorders, relate to the concordance of sleep measurements.

Methods

In this study, 62 individuals with psychiatric disorders from Nagoya University Hospital were included as participants. Their sleep was monitored using several

methods

polysomnography (PSG), a portable EEG device called Zmachine, Fitbit, and sleep logs. The morning after the sleep measurement with these objective sleep devices for a single night, participants estimated their sleep duration subjectively. To evaluate sleep parameters, Intraclass Correlation Coefficients (ICCs) were used. This research was carried out following the approval of the Ethics Review Committees at Nagoya University Hospital, and written consent was acquired from all participants.

Results

PSG and Zmachine demonstrated moderate concordance in Total Sleep Time (TST: ICC=0.46), Wake After Sleep Onset (WASO: ICC=0.39), and Sleep Efficiency (SE: ICC=0.40). However, there was a lack of agreement between PSG and Zmachine parameters with Fitbit, and between Fitbit and sleep logs. Sleep logs showed minimal correlation with PSG and Zmachine for TST and WASO, and a slight agreement for SE with Zmachine. When participants with severe OSA were excluded, ICCs for TST, WASO, and SE between PSG and sleep logs improved marginally (TST: ICC=0.27; WASO: ICC=0.38; SE: ICC=0.22). Excluding participants with severe depression, the TST ICC for PSG and sleep logs were slightly elevated (TST: ICC=0.24). However, even when participants with severe depression and OSA were excluded, ICCs between Fitbit and other sleep measurement methods did not elevate.

Conclusion

Our results indicated that Fitbit has a discrepancy when comparing data from PSG and sleep logs in individuals with psychiatric disorders. Although the growing adoption of Fitbit for sleep measurement, it is essential to acknowledge its weakness in the assessment of individuals with psychiatric disorders.

Support (if any)
0986 Inter-Individual Differences in Sleep Architecture of Patients Receiving Methadone for Opioid Use Disorder
Authors: Gardiner Poppy , Finlay Myles , Erwin Julie , Hansen Devon , Quock Raymond , Wilson Marian , Layton Matthew , Van Dongen Hans
Published: April 2024

Introduction

Methadone treatment for opioid use disorder (OUD) reduces drug cravings and promotes abstinence, but sleep disturbances can negatively impact OUD recovery outcomes. Irregular sleep architecture and respiratory disturbance in outpatients administered methadone as medication for OUD (MOUD) are common, but inter-individual differences may be substantial. We investigated the magnitude and stability of inter-individual differences in sleep architecture and respiratory measures in outpatients in their first 90 days of MOUD treatment.

Methods

N=6 adults (42.5±10.4y, four females) enrolled in local MOUD programs participated in this research study. The daily methadone dose varied between participants (75.8±23.2mg, range 50-120mg). All participants reported past use of multiple substances; four reported current mental health disorders; and four reported chronic pain. As part of the study, participants underwent two consecutive nights of cardiorespiratory PSG, with lights off at 21:49 on average (range 21:17-22:16) on both nights. Sleep stages and apnea-hypopnea index (AHI) were analyzed for systematic inter-individual differences using variance components analysis. The stability of inter-individual differences was quantified with the intraclass correlation coefficient (ICC, ranging from 0 to 1 for negligible to complete stability).

Results

On night one, mean±SD was 441.9±21.1min for total sleep time (TST), 9.0±5.2min for sleep latency (SL), 35.3±22.4min for wakefulness after sleep onset (WASO), 28.8±26.6min for N1, 220.8±58.6min for N2, 114.0±77.2min for N3, and 78.3±65.6min for REM. AHI scores were 16.4±9.1, indicating moderate sleep apnea on average. Compared to similarly aged healthy adults, N1 was low, and TST, WASO, N2, REM, and AHI were high. Stability was significant and substantial for N1, N2, REM, and AHI (ICC≥0.68, F≥5.19, P< 0.05).

Conclusion

Despite small sample size, we found substantial, stable inter-individual differences in N1, N2, REM, and AHI, whereas TST, SL, WASO, and N3 did not reach statistical significance. Varying methadone doses, prior substance use, physical and mental health, chronic pain, and (epi)genetic predisposition may partially account for these inter-individual differences. Our PSG data were collected in-laboratory, not naturalistically; results should be interpreted accordingly. Given the substantial, stable inter-individual differences in sleep architecture, a personalized approach to sleep management may be crucial to help improve OUD recovery outcomes.

Support (if any)

WSU ORAP and HSCL
0988 Evaluation of Sleep Disorders in College Student Athletes
Authors: Emert Sarah , Kim Kelly , Huskey Alisa , Taylor Daniel
Published: April 2024

Introduction

College student athletes experience unique factors in addition to those of being a traditional college student that may exacerbate sleep difficulties and/or mental health difficulties which may in turn negatively affect sleep (e.g., competition pressures, training, travel demands). Previous research has found that mental health problems are common in this population, however, less attention has been given to the evaluation of sleep disorders. This study provides an evaluation of sleep disorder questionnaires and comparison with a structured clinical sleep disorders interview (SCISD-R).

Methods

College student athletes (N = 114) from two Universities completed self-report questionnaires and participated in a clinical interview. Average total scores were calculated for the Epworth Sleepiness Scale (ESS), Nightmare Disorders Index (NDI), Reduced Composite Scale of Morningness (rCSM), Sleep Condition Indicator (CSI), Shiftwork Disorder Index (SWDI), STOP-Bang Questionnaire, PROMIS Sleep Disturbance B (SD) and Sleep Related Impairment (SRI), and International RLS Rating Scale (IRLS-RS). Diagnostic criteria were calculated for the SCISD-R, NDI, SCI, and SWDI. Endorsement of Insomnia Identity (“I am an Insomniac”) was obtained.

Results

Averages and standard deviations are as follows: ESS = 6.75±3.16; NDI = 2.83±3.38; rCSM = 20.42±2.92; SCI = 24.87±5.92; SWDI = 3.11±2.03; STOP-Bang = 1.28±1.06; PROMIS SD = 18.05±6.35; PROMIS SRI = 17.37±6.46; IRLS-RS = 2.70±4.62. Diagnostic criteria for assessments and clinical interview with shared symptoms are as follows: Nightmare disorder: 4 participants met criteria on the NDI and 3 met criteria on the SCISD-R. Insomnia disorder: 1 participant met criteria on the SCI and 10 met criteria on the SCISD-R. Circadian disorder - Shiftwork type: 11 participants met criteria for on the SWDI and 1 met criteria on the SCISD-R. Additionally on the SCISD-R, 5 participants met for hypersomnolence, 5 met for possible obstructive sleep apnea, and 1 met for possible narcolepsy. 6 participants endorsed an insomnia identity.

Conclusion

College student athletes endorse symptoms across a variety of sleep disorders. Differences in the number of participants who met criteria based on assessment measures versus the structured clinical interview indicate that alternate cutoff scores may be warranted for this population.

Support (if any)

Pacific-12 Conference Student-Athlete Health and Well-Being Initiative Grant