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Introduction Sleep disorders in individuals with Attention Deficit Hyperactivity Disorder (ADHD) are more prevalent than in people without ADHD. Given that sleep disorders (e.g., insomnia and OSA) impact daytime function (e.g., mood, memory, motivation, attention, executive function [EF], etc.), it is reasonable to wonder if these domains interact. Thus, the aim of the present analysis was to evaluate subjects diagnosed with ADHD who were also symptomatic for insomnia or OSA on a self-report measure of executive function. The hypothesis for the analysis being: subjects with insomnia would show more severe executive function deficits as compared to subjects without symptoms of insomnia and/or subjects with OSA. Methods This analysis includes data from 149 subjects diagnosed with ADHD (38% female, Mage 32.8±13.2yrs). Sleep disorder and EF data was provided by the Penn ADHD Treatment and Research Program. Database assessments were gathered from intakes, which included the SDS-CL-25 (a comprehensive screener for sleep disorders) and the BDEFS-LF (a self-report measure of EF deficit). In order to type individuals as “symptom positive” for insomnia or OSA, subjects were required to score >3 for any item within each category. These groups were then compared for their scores on the BDEFS-LF (total score and for three factor scores: self-restraint score [BDEFS-SR], self-regulation of emotions score [BDEFS-SRM], and self-motivation score [BDEFS-SM]). Results Subjects with-and-without insomnia symptoms were not found to significantly differ on the BDEFS-T, or any of the three sub-scales. In contrast, subjects with-and-without OSA symptoms significantly differed on the BDEFS-T (p=0.0328), and on two of the three sub-scales (BDEFS-SR [p=0.0183] & BDEFS-SRM [p=0.0032]). Conclusion Contrary to our hypothesis, it was the symptom positive OSA group that showed the most deficits on executive function (as measured by the BDEFS-T). This suggests that, in people with ADHD, sleep fragmentation and/or hypoxia may be more associated with EF deficits than problems with sleep initiation or maintenance. This said, it is also possible that other measures of insomnia that better represent sleep insufficiency and/or total nocturnal wakefulness may be more associated with executive functioning deficits, alone or in combination with the sleep sequela of OSA. Support (if any)

Introduction It has been widely reported in the literature that insomnia, depression, and anxiety are reciprocally related, and that CBT-I not only improves insomnia but also symptoms of depression and anxiety. With respect to cancer, patients of-ten report high co-morbidity of insomnia, fatigue, depression, and anxiety, with fatigue occurring in almost all patients diagnosed with cancer (irrespective of diagnoses and staging) and extending well into survivorship. The underlying mechanisms of fatigue are not well understood and, as such, there could be many contributing factors (e.g., insomnia and mood disturbance). The present analysis is based on a pilot study evaluating whether sleep continuity and CRF is improved by CBT-I dose (4 & 8 [Low dose] vs 10 & 12 [High dose] sessions). The present analysis evaluates whether dose of CBT-I effects depression and anxiety in patients diagnosed with breast and prostate cancer. Methods This descriptive analysis (percent change from pre to post treatment) includes 12 adult subjects (83.3% female, Mage 58.4±7.5yrs.; [Low dose, n=6], [High dose, n=6]). CBT-I was provided by a master therapist via video conferencing (telehealth CBT-I). Subjects were asked to complete sleep diaries and weekly measures of fatigue (FACIT), insomnia severity (ISI), depression (PHQ-9), and anxiety (GAD-7). Results On the PHQ-9, subjects in the Low dose group exhibited a 57% improvement and subjects in the High dose group had a 52% improvement. On the GAD-7, this corresponded to a 26% improvement (High dose group) and 25% improvement. Conclusion As increasingly reported in the literature, CBT-I produced robust effects on depression as assessed by the PHQ-9. The effects on anxiety appear to be less robust. This may be the case because CBT-I’s effects on fatigue are likely to impact a variety of depressive symptoms, where this is less the case for anxiety. Analyses are ongoing, where the relative effects will be adjusted for insomnia-related items and rendered in terms of effect sizes. Support (if any) 5T32HL00795320;K24AG055602

Introduction Cancer-related fatigue (CRF) is highly prevalent during acute illness and survivorship, with almost 100% of cancer patients experiencing such symptomatology. While CRF commonly co-occurs with sleep disturbance during and/or after cancer treatment, CRF is (nevertheless) defined as occurring independent of sleep considerations. Last year it was reported (based on preliminary findings from a pilot study), that CBT-I affects both sleep continuity and fatigue, with high dose CBT-I producing up to a 72% reduction in pre-to-post measures of Fatigue. The present analysis is based on a completed pilot study where we evaluate the durability of the anti-fatigue and sleep continuity effects of CBT-I in patients diagnosed with breast and prostate cancer. Methods This descriptive analysis (percent change from post-treatment to three month follow-up) includes 11 adult subjects (91% female; Mage=57.8±7.7yrs). CBT-I was provided by a master CBT-I therapist via video conferencing (telehealth CBT-I). Subjects were asked to complete sleep diaries, and weekly measures of fatigue (FACIT), and insomnia severity (ISI) questionnaires. In order to evaluate durability, post-treatment scores were compared to three-month follow-up scores, where all subjects were typed for whether or not they retained > 90% of their clinical gains as assessed with the ISI and the FACIT. Results 82% of the subjects in our pilot study maintained their clinical gains with respect to fatigue and 64% maintained their gains with respect to insomnia. Conclusion This preliminary analyses suggest that clinical gains via CBT-I are remarkably robust for fatigue outcomes. The findings with respect to the ISI, while less robust, are within the range that is typical for insomnia RCTs (~70% of subjects maintain treatment responses at follow-ups). If these results are replicated, this may suggest that the anti-fatigue effects of CBT-I are more durable than the “insomnialytic” effects. Support (if any) 5T32HL00795320;K24AG055602

Introduction Insomnia identity is defined as the “conviction that one has insomnia” or self-identifies as an “insomniac.” The present study sought to evaluate whether insomnia chronicity and past insomnia treatment predicts whether someone identifies as an “insomniac” in a large sample of adult participants with sleep complaints. Methods This study utilized a cross-sectional group design in an archival/community dataset that was collected in the Philadelphia area. The data were drawn from 2,950 adults between 18 and 90 years of age who specifically reported problems with total sleep time (TST). All participants answered questions regarding age of problem onset, insomnia treatment history, and insomnia identity (“Do you think of yourself as an ‘insomniac’?”). Results Of the 2,863 participants included in this analysis (Mage=53.5±10.7; 76.6% female; 91.2% White), 45.1% identified as an “insomniac.” Binary logistic regression was used to examine whether TST problem chronicity (Myears=12.3±10.0) and treatment history (36.6%) were associated with the likelihood of identifying as an “insomniac.” Outliers were removed and assumptions were met. The model was statistically significant X2=(2, N=2,863)=172.4, p< 0.001, suggesting that it could distinguish between those who did and did not identify as an “insomniac.” The model correctly classified 60.9% of cases. TST problem chronicity (OR=1.04, 95% CI [1.027, 1.043]) and treatment history (OR=0.51, 95% CI [0.435, 0.596]) significantly contributed to the model. Conclusion Participants were 4% more likely to identify as an “insomniac” with each year of TST problem chronicity and were 49% less likely to identify as an “insomniac” if they engaged in prior insomnia treatment. Findings align with a recent study that also found that individuals with insomnia identity reported longer insomnia chronicity and that individuals with and without insomnia identity seek insomnia treatment. Future analyses should consider additional variables including insomnia frequency (days per week), severity (e.g., total nocturnal wakefulness [TWT]), daytime symptomatology, perceived sleep need, and demographic factors including age, sex, and race. Support (if any) K24AG055602

Introduction Insomnia affects 10 to 20 percent of Americans annually. Unfortunately, evidence-based training on the diagnosis and management of insomnia during U.S. undergraduate medical education is limited. This educational gap may promote use of off-label medications or supplements (e.g., melatonin) and contribute to the “medicalization of sleeplessness”. By contrast, cognitive behavioral therapy for insomnia (CBT-I) is the first-line recommendation of the American Academy of Sleep Medicine and the American College of Physicians, and CBT-I is increasingly available in a digital format that can even be prescribed by primary care providers. Most physicians are not trained in how CBT-I works, however, and thus are ill-equipped to prescribe or refer this service. Therefore, this pilot study evaluated a brief educational intervention to improve medical student knowledge about insomnia. Methods The first author (AST) developed a 20-minute in-person lecture on insomnia which was delivered to 122 undergraduate medical students during their third-year medical curriculum. Topics included epidemiology, Spielman’s 3-P model of pathophysiology, and the treatment recommendations from the AASM with an emphasis on CBT-I. A total of 43 students (36%) provided informed consent and provided pre- and post-presentation ratings (0–100-point scale) of 1) their comfort in discussing insomnia with their patients, 2) the importance of insomnia for human health, 3) their familiarity with the pathophysiology of insomnia, and 4) their familiarity with treatments for insomnia. Participants were additionally asked to categorize a list of treatments as evidence-based or not. Results Following the presentation, students reported increased comfort in discussing insomnia with their patients, knowledge of the pathophysiology of insomnia, and knowledge of evidence-based treatments. In selecting treatments, more students chose CBT-I as an evidence-based treatment, while fewer students identified sleep hygiene, PAP therapy, diphenhydramine, hydroxyzine, melatonin, quetiapine, and trazodone. Conclusion A brief lecture on insomnia improved medical students’ knowledge of the disease process and evidence-based treatments for insomnia. Forthcoming analyses will determine whether students utilized this knowledge during subsequent clerkships. Future work will examine whether alternative formats (e.g., flipped-class, case-based instruction, interactive modules) are more effective for conveying this information. Support (if any)

Introduction Previous studies have shown that stressful life events are the primary trigger in the development of insomnia. One etiological model of insomnia suggests that sleep reactivity, or the vulnerability to stress-related sleep disturbance, may be an important moderator of this association. That is, some individuals have a predisposition to experience insomnia following acute stressors (i.e., sleep reactivity). The goal of the present study was to provide a proof of concept and, specifically, additional empirical evidence that the link between stressful life events and the onset of acute insomnia is moderated by sleep reactivity. Methods 1,225 adults with a history of good sleep (Mage = 53.2 years, 68% female, 83% white) were recruited nationwide for an online study on sleep health. Participants completed surveys to assess sleep reactivity (baseline), sleep patterns (daily sleep diaries), and stressful life events (weekly survey). This high-density data (daily/weekly measures) allowed for a close examination of whether sleep reactivity predicts acute insomnia and how the association between stressful life events and sleep disturbance varies as a function of sleep reactivity. Due to the high variability of stressful life events and sleep over time, frequent data points were needed to test this etiological model of insomnia. Sleep diary data were used to identify sleep initiation/maintenance difficulties, including whether they met criteria for acute insomnia at any point during the one-year interval. Results Participants with high sleep reactivity, compared to low sleep reactivity, were at 76% increased odds of developing acute insomnia during the one-year interval. In general, greater weekly stressful life events were associated with greater insomnia during the subsequent week. Additionally, those participants with high sleep reactivity demonstrated a stronger relationship between weekly stressful life events and insomnia, such that they reported the greatest levels of insomnia following weeks where they experienced a greater number of stressful life events. Conclusion These results further support the sleep reactivity model of insomnia, and specifically, provide evidence that sleep reactivity predicts the incidence of acute insomnia in a sample of participants with no history of insomnia. Support (if any) Perlis: R01AG041783, K24AG055602; Vargas: K23HL141581, R25HL10544

Introduction Co-morbid sleep continuity disturbance (SCD) and insufficient sleep duration (ISD) disproportionately affect the sleep health of Black Americans (BA). Simultaneously, treating SCD and ISD may improve health and reduce disparities experienced by this community. Although standard cognitive behavioral therapy for insomnia (CBT-I) ranges from six to eight sessions and directly addresses SCD, standard CBT-I does not appreciably increase total sleep time (TST) and therefore does not adequately address ISD during treatment. This report presents the overall study outcomes of CBT-I (without respect to dose of CBT-I) in BA. Methods Twelve BA adults (83% female, Mage 46.0±13.9yrs) were recruited from the Philadelphia area. CBT-I was provided by one of four master CBT-I therapists via telehealth for up to 16 sessions. Two follow-up assessments were conducted at 3 and 6 months. Participants completed daily measures of sleep continuity (sleep diaries) and weekly measures of insomnia severity (ISI). Results Overall, 75% of participants exhibited a treatment response corresponding to a reduction of 58% (effect size [ES]=-2.3) on the ISI. With respect to sleep continuity (measured in minutes), there was a 61% (ES=-1.4) reduction in sleep latency (30.1 to 11.8), 76% (ES=-1.7) reduction in wake-after-sleep onset (32.4 to 7.8), 81% (ES=-1.2) reduction in early morning awakenings (32.2 to 6.3), 7% (ES=0.3) increase in TST (381.3 to 408.0), a 9% (ES=-0.6) reduction in time in bed (476.0 to 433.7), and an overall 16% (ES=2.9) improvement in sleep efficiency. Conclusion Results from this pilot study indicate that standard CBT-I produces robust effects in BA with insomnia. Analyses are ongoing and will examine group interactions and treatment durability at follow-up. Support (if any) K24AG055602

Introduction The hyperarousal model suggests that insomnia is characterized by increased cortical, cognitive, and physiological arousal. However, the relationship between these domains of arousal remains insufficiently studied. The aim of the current observational study was to investigate pre-sleep cognitive arousal, cortical arousal during the night, and the relationship between these domains. Methods 109 patients with insomnia disorder (ID) and 109 age-and gender matched healthy controls (GSC) were investigated on two sleep laboratory nights. As a measure of cortical arousal, EEG spectral power was analyzed during NREM and REM sleep. In addition, participants completed the Pre-Sleep Arousal Scale (PSAS), which consists of a subscale for cognitive arousal (PSAS-CA) and another subscale for self-reported somatic arousal (PSAS-SA). The relationship between the subscale scores and EEG spectral power was calculated by multivariate and univariate analyses of variance. Results The total sample consisted of 218 participants. ID patients had a mean age of 44.7 years (± 10.6 years) and GSC had a mean age of 44.4 years (± 12.6 years). Both groups consisted of 78 women and 31 men.During NREM and REM sleep, patients with ID showed significantly increased spectral power in the EEG gamma band (NREM: p < .001; REM: p = .002). In addition, patients with ID showed significantly increased scores on the PSAS-SA (ID: M = 12.4, SD = 4.4; GSC: M = 10.7, SD = 3.3; t(216) = 3.34, p = .001, d = 0.45) and the PSAS-CA (ID: M = 18.3, SD = 7.2; GSC: M = 10.6, SD = 2.9; t(216) = 10.33, p < .001, d = 1.40). The PSAS-CA score was significantly associated with increased NREM (p = .001) and REM gamma power (p = .004), whereas PSAS-SA was associated with significant decreases in NREM (p < .001) and REM gamma power (p = .001). Conclusion In line with our hypothesis, patients with ID showed increased cortical and cognitive arousal. Moreover, there was a relationship between pre-sleep cognitive arousal and high-frequency EEG activity during the night. This might suggest that the latter is caused (at least in part) by pre-sleep worry and rumination. Support (if any)

Introduction The Spielman 3P and Perlis 4P models represent illness severity over the course of insomnia disorder. The 3P model suggests that illness severity is worst when subjects experience acute illness (as compared to the subchronic and chronic phases of the disorder). The 4P model suggests that illness severity crescendos with chronicity. The present analysis uses an archival data set to assess illness severity with new onset illness (i.e.,from Good Sleep [GS] to Acute Insomnia [AI] and from AI to Chronic Insomnia [CI]). Illness severity is quantified in terms of Total Wake Time (TWT). Number of affected days/week is a tabulation of nights/week with clinical insomnia symptoms. Methods Subjects were recruited as GSs(N=911), followed up to 1-year with digital sleep diaries, and were classified as GS, AI, or CI based on standardized criteria. Data for CI subjects were anchored to the 1st of 14 days with insomnia so that day-to-day TWT, SL, WASO, and EMA were represented for ~100 days prior-to-and-following AI onset. A similar graphic (+/-Acute onset) was constructed for number of days per week with insomnia. GS data were matched to CI subjects dates (i.e., the data were temporally tethered). Segmented linear mixed regression models were applied to examine the change in slopes in the AI-to-CI period compared to GS and AI period. Results 883 subjects remained as GSs (Mage=53.1±10.8years;35.1%female;83.0%white), while 28 indi-viduals transitioned to AI and then CI (Mage=53.6±12.6years;39.3%female;89.3%white). Average TWT rose over the course of the first 2 weeks from the AI onset(b=1.6,SE=0.52minutes,p=0.002) and then was stable for 3 months(b=-0.004,SE=0.03,p=0.91). This worsening of sleep continuity was almost entirely related to increased WASO. Average number of affected days was found to be stable from AI to CI (b=0.002,SE=0.002,p=0.20). That is, while there was week-to-week variability in the number of days affected, no linear trend was evident. Conclusion These data suggest that, in our sample of CIs with primarily middle insomnia, the average severity and number of affected days was worst with the onset of AI (worst is first) and stable thereafter. Whether this temporal trend applies equally to new onset Initial and Late insomnia remains to be determined. Analyses ongoing. Support (if any) R01AG041783

Introduction It has been suggested that sleep continuity disturbance and/or short sleep duration is associated with increased impulsivity across clinical populations (i.e., The Mind After Midnight Theory). Consistent with this theory are the findings showing that sleep disturbance is associated with increased binge eating (BE; a subjective sense of loss of control over one’s eating) both cross-sectionally and longitudinally. To date, no study has examined whether impulsivity mediates the association between sleep disturbance and BE. Further, the extant literature has relied on retrospective self-report assessment of impulsivity which is subject to recall and social desirability biases. The aim of the present study was to examine whether performance on a behavioral measure of impulsivity (Go/No-Go task) mediated the association between sleep quality (SQ), sleep efficiency (SE%), and daytime dysfunction (DD), as measured by the PSQI, and BE frequency. Methods The parent study was a sample of 63 individuals (85.9% female; X̅age=40.6 years) seeking treatment for BE. Of note, individuals with extremely low levels of impulsivity were excluded from the parent study. Mediation models using the lavaan package in R (version 4.1.3) examined the effect of sleep disturbance on impulsivity and whether DD mediated this association.". The current analyses included the full available sample and all models co-varied for depressive symptoms. Results A negative direct effect of DD on impulsivity was observed (B=-55.43, S.E.=22.06, p=.01) and impulsivity did not significantly mediate the association between SQ (B=0.20, S.E.=0.59, p=0.73), SE (B=-0.02, S.E.= 0.14, p=0.92), or DD (B= 0.160, S.E.=1.14, p=0.51) and BE frequency. Conclusion While impulsivity did not mediate the association between sleep disturbance and BE in our sample, the current study may have been under-powered to detect even large effects due to its moderate sample size and low levels of insomnia symptoms. Future studies should evaluate these associations in large samples, using prospective measures of sleep continuity and do so in samples with clinical levels of insomnia. Further, such studies should take into account time of day considerations. Support (if any)

Introduction Insomnia symptoms, which include sleep disturbances and daytime dysfunction, are associated with poor physical and mental health. Physical activity has been associated with good sleep while sedentary behavior has been associated with poor sleep. This study investigated whether physical activity and sedentary behavior are associated with insomnia symptoms both generally (i.e., between-persons, mean-level) and dynamically (i.e., within-persons, person-centered). Methods Participants (N=775) included adults (Mage=47.3 years,54.6% female) who completed an online longitudinal study investigating sleep and health across the lifespan at three time points (approximately 17-weeks apart). Participants reported: (a) their duration of moderate-to-vigorous physical activity per week (in minutes), (b) the percentage of their day spent sedentary, and (c) their insomnia symptoms via the Insomnia Severity Index which was scored according to traditional standards (i.e., total score) as well as proposed two factor scores: (1) Sleep Disturbance (items 1,2,3) and (2) Daytime Dysfunction (items 4,5,6,7). Multilevel modeling was used to examine the associations among physical activity, sedentary behavior, and insomnia symptoms at both between- and within-persons levels. Results No significant associations were observed among total ISI score or the factor scores, and minutes spent in moderate-to-vigorous physical activity (all p’s>.05). Sedentary behavior, however, was significantly associated with total ISI score at both the between-person and within-person levels (β=.02, t=2.71, p=.007; β=0.03, t=2.62, p=.009, respectively). For the Sleep Disturbance factor, between-person sedentary behavior was not a significant predictor while within-person sedentary behavior was associated with higher sleep disturbance scores (β=0.01, t=1.16, p=.245; β=.01, t=2.06, p=.039, respectively). For the Daytime Dysfunction factor, both between-persons and within-person levels of sedentary behavior were associated with increased daytime dysfunction (β=.02, t=3.30, p=.001; β=.01, t=2.53, p=.012). Conclusion Sedentary behavior appears to be a more robust predictor of insomnia symptoms than physical activity. Further, the association between sedentary behavior and insomnia symptoms was observed to be dynamic in that when an individual reported being more sedentary than customary, they also reported more insomnia symptoms. Future analyses should consider demographic variables and comorbid conditions to identify subgroups in which these associations are most pronounced. Support (if any) National Institute on Aging of the National Institutes of Health under Award Number K23AG049955 (PI: Dzierzewski).

Introduction Insomnia is associated with risk for suicidal thoughts and behaviors. It is unclear if insomnia drives risk equivalently across all individuals, or whether there are subgroups of high-risk individuals for whom insomnia is more relevant. This exploratory archival analysis examined the relationship between insomnia and current suicidal ideation among subgroups of individuals with lifetime suicidal ideation. Methods Data were acquired from the Military Suicide Research Consortium on 2,617 individuals without missingness on measures of suicidal thoughts and behaviors, anxiety, insomnia, thwarted belongingness, traumatic brain injury, risky alcohol use, and symptoms of post-traumatic stress. Medoid (k-means) clustering algorithms identified subgroups. Robust Poisson models tested interactions between insomnia and cluster identity in association with current suicidal ideation. Models were unadjusted, adjusted for demographic factors, and adjusted for clinical characteristics. Results Clustering identified two subgroups: Cluster 1 (N=1,141) and Cluster 2 (N=1,494). Cluster 1 had fewer individuals with current suicidal ideation (29.2% vs. 66.6%) and in general had less severe symptoms of anxiety, PTSD, insomnia, traumatic brain injury, and suicidal thoughts and behaviors. Across clusters, insomnia severity was associated with risk for current suicidal ideation (PRR: 1.09 [1.03-1.14]). Although individuals in Cluster 1 were less likely to have current suicidal ideation (PRR 0.51 [0.44-0.58]), greater severity of insomnia was associated with greater risk (PRR: 1.11 [1.04-1.18]). By contrast, individuals in Cluster 2 had a greater risk of current suicidal ideation (PRR: 1.68 [1.51-1.88]) and greater severity of insomnia was associated with a diminished risk of current ideation (PRR 0.92 [0.88-0.97]). Conclusion In this exploratory study, individuals with less severe psychopathology were more likely to report current suicidal ideation with worsening insomnia, while those with severe psychopathology were less likely to report suicidal ideation with worsening insomnia. Insomnia may disproportionately increase suicide risk among lower risk individuals. Support (if any) This work was in part supported by the Military Suicide Research Consortium (MSRC), an effort supported by the Office of the Assistant Secretary of Defense for Health Affairs under Award No. (W81XWH-16-2-0003). Opinions, interpretations, conclusions, and recommendations are those of the author and are not endorsed by the MSRC or the Department of Defense.

Introduction The Sleep Disorders Symptom Checklist (SDSCL-25) is a brief assessment of patient-reported symptoms that suggest risk for a wide range of sleep disorders. To ensure the validity of study subject responses, the SDSCL-25 was translated into Spanish by a bilingual research study team. It was then administered to study subjects in their preferred language. Methods Data were collected from a sample of N=100 individuals of Mexican Descent in Nogales, Arizona, US-Mexico border. The SDSCL-25 is a screening tool that assesses the presence of a wide range of symptoms for sleep disorders. To translate the measure into Spanish, the following procedure was followed: (1) a bilingual study team member performed an initial translation; (2) a bilingual community member edited the translation; (3) a certified medical translator edited the revision; (4) a focus group of N=5 bilingual community members made contextual edits; (5) a back-translation was performed; (6) an additional bilingual focus group examined the final version for compatibility; and (7) the medical translator certified the accuracy of the final version. T-tests examined differences between those who completed the measure in Spanish vs English. Results Of the N=100 survey respondents, N=42 completed the SDSCL-25 in Spanish. Those who took the measure in Spanish showed no differences in frequency of reports of delayed sleep phase (p=0.28), snoring (p=0.85), morning dry mouth (p=0.87), choking/gasping (p=0.09), uncomfortable sensations in legs (p=0.25), urge to move legs (p=0.09), cataplexy (p=0.09), sleep paralysis (p=0.12), sleepwalking (p=0.08), or bruxism (p=0.13). Respondents in Spanish reported lower frequency of insufficient sleep (p=0.01), variability in bedtime (p=0.02), difficulty falling asleep (p=0.002), difficulty staying asleep (p=0.01), early morning awakenings (p=0.02), daytime tiredness/fatigue (p=0.006), phase advance (p=0.0003), daytime sleepiness (p=0.03), loud snoring (0.002), breathing pauses (p=0.049), frequent awakenings (p=0.0007), hypnogogic/pompic hallucinations (p=0.003), nightmares (p=0.047), panic awakenings (p=0.01), and overall sleep disturbance (p=0.043). Conclusion The present study describes a Spanish translation of the SDSCL-25. For those that took the Spanish version, there were lower reported frequencies of insufficient sleep, variability in bedtime, insomnia symptoms, daytime sleepiness and tiredness/fatigue, phase advance, sleep apnea symptoms, frequent awakenings, hypnogogic/pompic hallucinations, nightmares, panic awakenings, and overall sleep disturbance. Support (If Any)

Introduction The risk for suicide is greatest at night after adjusting for population wakefulness, possibly due to sleep- and circadian-dependent changes in neurophysiology to promote sleep. Those who die by suicide at night, however, may differ by demographic and/or clinical characteristics from those who die by suicide during the day. Methods An archival analysis of the National Violent Death Reporting System for 2003-2017 identified 77,784 suicide deaths with time of fatal injury. Cases were divided into daytime (5AM to 10:59PM) or nighttime (11PM to 4:59AM) and characterized by age, sex, race, ethnicity, marital status, military service, education, prior diagnosis of an anxiety disorder, bipolar disorder, depression, history of suicidal ideation, PTSD, and schizophrenia, as well as the presence of an opiate or cannabis, and blood alcohol level (BAL) on autopsy. Bidirectional stepwise regression and robust Poisson models characterized significant predictors of nocturnal suicide using incident risk ratios (IRR). Results Nocturnal and daytime suicides differed on all sociodemographic variables. Nocturnal suicides were more prevalent among those with bipolar disorder, PTSD, an elevated BAL, and those who tested positive for cannabis. Stepwise models identified a significant age by BAL interaction. Using adults 35-64 with BAL=0mg/dl as the reference, adults 35-64 with a BAL0mg/dl did not differ from those aged 35-64 with BAL=0mg/dl. The risk of nocturnal suicide was also 17% greater among those with a prior history of suicidal ideation, and 13% less likely among those with documented depression. Conclusion Nocturnal suicide is more prevalent among intoxicated younger adults and those with previous suicidal ideation. However, suicide victims with depression were less likely to die at night. Further research is needed to target suicide prevention efforts at appropriately times for those with mood, substance, and alcohol use disorders. Support (If Any)

Introduction Previous studies have shown that prescription sleep medications are associated with suicide ideation. In this study we seek to identify the risk of off-label or illicit use of sedatives/hypnotics to predict suicidal ideation. Methods Data were from the Sleep and Healthy Activity, Diet, Environment, and Socialization (SHADES) Study, including N=1,003 working-age adults. For the present study, the data on off-label or illicit stimulants and sedatives were examined. Suicide ideation was assessed by whether participant reported any ideation in the past 2 weeks (PHQ, Item #9). Covariates included age, sex, education, race/ethnicity, and smoking. Additional models included adjustment for insomnia severity (ISI), daytime sleepiness (ESS), sleep duration (NHANES), psychiatric health (PHQ4), and general stress (PSS). Results In adjusted models examining sedatives/hypnotic use, higher likelihood of suicidal ideation was associated with any use (OR=1.77, 95%CI[1.26,2.47]), recent use (OR=2.71, 95%CI[1.77,4.15]), desire to use (OR=2.14, 95%CI[2.74,6.26]),problematic use (OR=7.39, 95%CI[3.32,16.47]), role limitations (OR=7.94, 95%CI[3.39,18.59]), others expressing concern (OR=4.38, 95%CI([2.29,8.41]), and inability to control use (OR=7.15, 95%CI[3.60,14.20]). Similarly, models examining stimulant use showed that higher likelihood of suicide ideation was associated with history of use (OR=1.81, 95%CI[2.01,3.93]), recent use (OR=4.44, 95%CI[2.63,7.49]), desire to use (4.82, 95%CI[2.78,8.34]), problematic use (OR=17.04, 95%CI[5.67,51.24]), role limitations (OR=9.07, 95%CI[3.47,23.68]), others expressing concern (OR=17.26, 95%CI([7.48,39.84]), and inability to control use (OR=6.44, 95%CI[3.26,12.71]). When sleep and mental health variables were added to the model, results were attenuated but remained significant at the p Conclusion Illicit use of substances that both promote sleep or arousal are associated with suicidal ideation, over and above contributions of sleep disturbance and mood/stress. It is possible that these behaviors represent self-medication attempts or an adverse effect of these drugs. Further research on these problematic associations is recommended. Support (If Any)

Introduction Nocturnal wakefulness may be dangerous for vulnerable populations: the incident risk for suicide is highest at night after adjusting for population wakefulness, and nocturnal wakefulness is associated with suicidal ideation. These observations support the hypothesis that sleep- and circadian-dependent changes in mood, reward processing, and executive function increase the risk for disinhibited behavior at night (during periods of nocturnal wakefulness). The present study evaluated this hypothesis by using the timing of emergency department encounters for suicidal ideation. Methods An archival analysis of data from two emergency departments (EDs) in Tucson, Arizona from 2018 and 2019 yielded 51,370 encounters for any reason across 29,359 individuals with usable data, and the time of initial contact was extracted for each case. Of these, 571 individuals (1.94%) sought care for 763 (1.49%) instances of suicidal ideation (determined by ICD-10 code R45.861). Encounters were characterized by date/time, age, sex, race/ethnicity, blood alcohol level (if tested), homelessness, and prior diagnosis of a psychotic disorder, bipolar disorder, or depressive disorder. Suicidal ideation encounters were analyzed as raw counts and as a proportion of all encounters by clock hour and time-of-day categories (night: 12AM-5:59AM; morning: 6AM-11:59AM; afternoon:12PM-5:59PM; evening: 6PM-11:59PM) using robust Poisson models. Results Although most ED encounters occurred between 6PM and midnight (mean: 9:42PM), the greatest number of suicidal ideation encounters occurred between 12AM and 3AM (mean: 12:18AM). After adjusting for the per-hour proportion of ED visits, the incident risk for a suicidal ideation encounter increased between 8AM and 11AM, peaked at 10AM (IRR: 1.95 [1.10-3.44]) and was lowest at 4PM (IRR: 0.54 [0.32-0.91]). Compared to the evening, the incident risk of suicidal ideation was 64% greater in the morning (IRR: 1.64 [1.31-2.06]), 25% greater at night (IRR: 1.25 [1.00-1.56]), but not different for afternoon encounters. Conclusion After adjusting for overall encounter rates, ED encounters for suicidal ideation are more likely to occur in the morning. Although the morning peak in incident risk is later than the reported nocturnal risk for incident suicide, this may reflect a delay between when an individual develops suicidal ideation and when they seek or receive treatment. Support (If Any)

Introduction According to the 3P model of insomnia, the variable that mediates the transition from acute to chronic insomnia is “sleep extension” (the behavioral tendency to expand sleep opportunity to compensate for sleep loss). Recently, this proposition was prospectively evaluated by assessing how Time-in-Bed (TIB) varied, week-by-week, relative to the incidence of acute insomnia in four groups, those that: maintained good sleep (GS,n=911), recovered good sleep (AI-REC,n=244); had persistent poor sleep (AI-PPS,n=65); and developed chronic insomnia (AI-CI,n=23)). Significant differences for pre-to-post acute insomnia TIB were not detected for the insomnia groups (as compared to one another or as compared to GSs). The observed trends suggested that the increases in TIB observed were minor (< 15 min overall, at 2 weeks, and at 12 weeks post AI). In the present analysis, a more granular evaluation was undertaken to assess whether sleep extension occurs on the nights following poor sleep bouts. Methods The same data set and subject groups were modeled for TIB occurring on the night following a poor night’s sleep (≥ 30 min for SL or WASO or EMA) for the post-acute insomnia interval (by weekday and weekend). Linear mixed effects model was used to account for up to 1 year of repeated nights per subject. Results During the weekdays, the groups did not differ with respect to TIB following a poor nights’ sleep. On average, the four groups (including good sleepers) did not vary TIB by more than 5 minutes. During the weekends, all four groups tended to restrict TIB. In this instance, AI-CI subjects restricted TIB the least (AI-CI -17.2[5.11]; (GS -25.7[SE 1.58]; AI-PPS -27.6[6.1]; AI-REC -32.3[1.9]. Conclusion As with the prior analysis, the transition to CI does not appear to be triggered by sleep extension. In the present analysis there is some evidence to support the notion that AI-CI subjects restrict TIB less. This counterintuitive finding needs to be further evaluated taking into account sleep timing. That is, time-to-bed and time-out-of-bed may vary (show the attempt to extend sleep opportunity) while TIB does not change appreciably (owing to limitations in sleep ability [plasticity]). Support (If Any) Support: R01AG041783;K24AG055602;R01AT003332

Introduction There is a nocturnal peak in incident suicide risk after adjusting for population wakefulness (Perlis et al., 2016; Tubbs et al., 2020). This peak in risk is hypothesized to result from a series of negative changes in mood, reward processing, and executive function that occur at night and increase the propensity for dysregulated and violent behaviors. Although the unadjusted incidence of dying by homicide is elevated at night, no existing studies of time-of-day and death by violent crime have adjusted for population wakefulness. Methods Data from 48,486 homicide victims with a known time of fatal injury were collected from the National Violent Death Reporting System (NVDRS) for 2003-2017, tabulated by clock hour, age, sex, race, and ethnicity, and combined with population wakefulness data from the American Time Use Survey (ATUS) for the same years. Homicide counts were additionally characterized by the proportion of cases with blood alcohol level (BAL) of 0, Results Homicide counts were lowest in the morning (6AM-7AM) and highest at night (10PM-11PM). After adjusting for population wakefulness, the incident risk for death by homicide was elevated between 10PM and 5AM compared to the 24-hour average, with the highest risk between 2AM (IRR: 8.25 [6.62-10.3]) and 3AM (IRR: 7.22 [6.04-8.64]). Moreover, the adjusted risk of dying by homicide was significantly greater at night for those with a BAL≥80mg/dl, such that the risk at 2AM was 13.8-fold greater than the 24-hour average (IRR: 13.8 [10.6-18.1]). Conclusion The risk of homicide death is higher at night after adjusting for population wakefulness and especially among those with alcohol intoxication. Although homicide victims do not choose when to die (unlike suicide victims), neurophysiological changes at night may promote risky behaviors or put victims in more dangerous circumstances than they would be otherwise. Future research should examine sociodemographic, clinical, and circadian risk factors for death by homicide, as well as examine time-of-day patterns in other violent crimes. Support (If Any)

Introduction Most prior research into relationships between sleep and health and daytime functioning have focused on average sleep duration or efficiency and ignored individual differences in sleep need. This study tested if sleep need is more strongly correlated with self-rated health and daytime function than sleep duration. Methods Data were drawn from the 2019 Sleep Health Foundation online survey of adult Australians (N=2,044, aged 18-90 years). Hierarchical multiple regressions assessed variance explained (R2 and R2 change) by demographics (Model 1: age, sex, BMI), self-reported sleep duration (Model 2: Model 1 + weighted variable of typical weekday/weekend sleep duration), and individual sleep need (Model 3: Model 2+ rating on a 5-point scale to ‘how often you get enough sleep to feel your best the next day’) on daytime function items for fatigue, concentration, motivation, and overall self-rated health (visual-analog scale from 0-100). Results Sleep need explained an additional 17.5–18.7% of the variance in fatigue, concentration, motivation, and health rating (all p < 0.001 for R2 change) in Model 3. In contrast, Model 2 showed that sleep duration alone only explained an additional 2.0–4.1% variance in these outcomes after accounting for demographic variables. Findings were similar when stratified by sex. Sleep need also explained greater variance for older adults than for younger and middle-aged adults, especially on health rating (Model 3: R2 change = 0.11 for ages 18-24y, 0.14 for 45-54y, 0.27 for 75y+). Conclusion Sleep need appears to explain considerably more variance in daytime function and self-rated health than sleep duration. The effect of sleep need on other daytime consequences, and in clinical populations, needs further exploration. Validated assessments of sleep need are also needed to elucidate its importance for understanding the effect of sleep on health and functioning. Support (If Any) The 2019 Sleep Health Foundation online survey was supported by the not-for-profit Sleep Health Foundation using an unrestricted grant from Merck Sharp & Dohme (Australia) which did not inform nor restrict study design, methodology, or presentation.

Introduction Cancer-related fatigue (CRF) is highly prevalent during acute illness and survivorship, with almost 100% of cancer patients experiencing some level of CRF. While CRF commonly co-occurs with sleep disturbance during and/or after cancer treatment, CRF is defined as occurring independent of sleep considerations. The present analysis is based on an ongoing pilot study where CBT-I dose (4 & 8 [Low] vs 10 & 12 [High] sessions) is being assessed for whether improved sleep continuity and/or increased TST can improve CRF in subjects diagnosed with breast and prostate cancer. Methods This interim analyses includes seven adult subjects (6 females, mean age=57.1 yrs.; n=3 [Low dose], n=4 [High dose]). CBT-I was provided by a master CBT-I therapist via video conferencing (telehealth CBT-I). Subjects were asked to complete sleep diaries, and weekly measures of fatigue (FACIT) and insomnia severity (ISI) questionnaires. Results Subjects in the low dose group exhibited a 9% improvement and subjects in the high dose group had a 21% improvement on the FACIT. This corresponded to a 28% improvement on the ISI (low group) and a 68% improvement on the ISI (high group). With respect to TWT, subjects in the low dose group decreased their wake time by 36% and those in the high dose group decreased their wake time by 43%. Finally, TST decreased by 7% in the low dose group but increased by 12% in the high dose group. Conclusion Preliminary results indicate that a higher CBT-I dose may significantly decrease fatigue, stabilize sleep schedules, and improve sleep continuity in patients with CRF, where the high dose group showed more than double the improvement on the FACIT and ISI (as compared to the low dose group). Not surprisingly, TWT was roughly comparable between the groups while TST was more substantially impacted by high dose CBT-I. This study is ongoing. Support (If Any) Support: 5T32HL00795320;K24AG055602

Introduction Hypnotics continue to be preferentially used in practice for the treatment of chronic insomnia, yet the comparative safety and efficacy of medication options are unclear. While several position statements and network meta-analyses have provided some guidance, none have provided a quantitative assessment of risk-benefit. In the present analysis, each therapeutic class commonly used for chronic insomnia is quantitatively ranked with respect to safety, efficacy, and risk-benefit. Methods Safety data for FDA-approved hypnotics were extracted from the package insert adverse event tables and standardized to form a placebo-adjusted adverse event rate per 1000 (AEr). Efficacy data were extracted from randomized controlled trials identified in professional society position statements and published systematic reviews. The efficacy metric was computed from placebo adjusted pre-post change scores for self-reported sleep continuity (i.e., sleep latency [SL], wake after sleep onset [WASO], and total sleep time [TST]) and represented as a summed composite effect size score (SWT). Risk-benefit (R/B) was represented as a ratio between AEr and SWT. Comparative safety, efficacy, and risk-benefit metrics were calculated for five therapeutic classes: Benzodiazepines (BZs), non-benzodiazepine benzodiazepine receptor agonists (BZRAs), dual orexin receptor antagonists (DORAs), melatonin receptor agonists (MELAs), and sedating antidepressants (SADs). Results With respect to safety, MELAs had the lowest adverse event rate (AEr=43.1) and BZRAs had the highest rate (AEr=255.0). With respect to efficacy, BZs were the most efficacious (SWT=1.94, Mean ES=0.59) and MELAs were least efficacious (SWT=0.11, Mean ES=0.02). Overall, with respect to risk-benefit, SADs had the most favorable profile (R/B=69.5), while MELAs had the least favorable profile (R/B=395.7). Conclusion The optimal selection of hypnotics requires consideration of both risk and benefit. Findings suggest that SADs can be considered the first-line pharmacotherapeutic option due to the superior risk-benefit profile. If treatment responses are inadequate or if SADs are contraindicated, risk-benefit rankings may serve as a decision tree as part of a medical algorithm protocol to guide treatment selection for patients with chronic insomnia. Support (If Any) Sleep Research Society Mentor-Mentee Award (Cheung); K24AG055602 & R01AG054521 (Perlis)

Introduction College students are at high risk for developing insomnia and co-morbid psychological distress. The aim of this research was to assess whether the lack of endogenous mindfulness was a risk factor for insomnia. Methods In order to address this issue, an archival analysis was conducted with a data set from MUN where the relationship between chronotype, mental health, sleep quality, and social support was assessed (n=3,160; 2,266 women; X̅age=22 years). The proband subsample of interest were subjects that completed the HADS, MEQ, the ISI, and the Mindful Attention Awareness Scale (MAAS). The MAAS is a 15 item self-report measure, where each item is scored on a six-point Likert scale. Scores range from 15-90, higher scores are indicative of greater mindfulness. In order to evaluate the relevance of mindfulness, the overall sample was split into two groups (endogenous mindfulness [average score of ≥4.2]): n=647; X̅age=22.4 years; nonendogenous mindfulness [average score of ≥4.2]: n=1,505; X̅age=22.04 years). Results Subjects (n=2,152) were between the ages of 18-35 (X̅=22+/- 3.72) and included primarily Caucasian individuals (86.6 %) and individuals who identified as female (71.7%). The means and ranges for the ISI, MAAS, and HADS were as follows: 9.0 + 5.6 (0-28), 3.7+.98 (1-6), and 5.3 + 3.9 (0-21), respectively. A correlation of -0.27 (p Conclusion There was a relationship found, in both groups, between mindfulness and the ISI, where the scores on the ISI were lower when mindfulness was high. This suggests that there is a moderate linear relationship between mindfulness and insomnia. This association needs to be further evaluated in samples that have a broader range of ISI scores and with analyses that more carefully parse the moderating influence of depression. Analyses are ongoing. Support (If Any) Support: K24AG055602

Introduction Temporal patterns for suicide over a 24-hour period have shown mixed results among prior studies. However, analyses of 24-hour temporal patterns for wakeful actions including suicidal behavior, should adjust for expected sleep requirements that inherently skew such activities to conventional wakeful times. This study analysed the time-of-day for suicide cases from the Australian population for the year 2017, adjusting for expected sleep patterns. Identification of time-of-day trends using this methodology may reveal risk factors for suicide and potentially modifiable contributors. Methods The Australian Coronal database was accessed and data for suicide deaths were extracted for the most recent completed year, 2017. Time of suicidal action is frequently unable to be pinpointed and for this analysis an estimation was performed from time last seen alive and time found subsequently using data extracted from police and coronial reports. Time of suicide was allocated to one of four 6-hourly time bins across 24 hours from the mid position of time last seen alive and time found subsequently. Cases were excluded if allocation to a time bin was not able to be confidently determined if time last seen and time found crossed both boundaries for a given time bin. Prevalence of suicide for each time bin was adjusted for the likelihood of being awake for each bin according to sleep-wake norms published in 2020 from a large Australian community survey of 1966 subjects. Observed prevalence of suicide were compared to expected values predicted from likelihood of being awake across each time bin calculated as a standardised incidence ratio (SIR). Results For year 2017 there were 2208 suicides for which 1407 were able to be allocated into one of four 6-hourly time bins. Reasons for exclusion were cases for which allocaton into a time bin was not able to be performed. When adjusted for the likelihood of being awake based from population norms, cases were significantly more likely to enact suicide between the hours of 2301-0500 than predicted (SIR 3.93, P< 0.001). Furthermore, there was a lower-than expected rate of suicide for the time bins, 1101-1700 (SIR 0.86, P=0.002). When subcategories of suicide cases were analsysed, suicide death in asssociation with alcohol consumption demonstrated the strongest for relatoinship to the 2301-0500 time bin (SIR 6.03, P< 0.001). Conclusion Higher than expected rates of suicide overnight associated proposes that nocturnal wakefulness may represent a modifiable risk factor for triggering suicide events. Nocturnal wakefulness may be linked to increased rates of loneliness and depair as well as greater tendency toward impusive actions and behaviors. Impusivity may be compounded by alcohol consumption Our findings offer a potential mechanism for which individuals with insomnia have increased suicidal thoughts and behaviors. Support (If Any) Untied grant provided by Rhinomed LTD

Introduction While it is not surprising that COVID is associated with increased fatigue, there is emerging data that COVID-19 symptoms extend well beyond the acute illness period. This phenomenon, known as “Long COVID”, may include fatigue (persistent fatigue post viral infection). The present analysis was undertaken to evaluate fatigue in subjects with and without COVID-19 virus at two time points separated by ~ one year’s time. Methods The parent study was a large online study of subjects during the COVID lockdown which was designed to evaluate the effects of social distancing on mood and sleep (n=4052; 3,184 women; X̅age= 46.0 years). The proband subsample of interest was the subjects that reported having COVID as compared to matched controls (whole sample n=242; 195 women [80.6% female]; 206 identified primarily as white [85.1%]; X̅age=42.0 years). Subjects who reported testing positive for COVID-19 provided additional information on COVID-19 symptoms (e.g., severity and duration per symptom). The PROMIS Fatigue scale was administered at time one (T1: April-June 2020) and one year later (T2: January-March 2021). Control subjects were matched based on age, sex, and race to reduce potential confounding or effect modification by these variables. Results The mean PROMIS Fatigue scores for the COVID-19 group and Control groups at baseline (T1) were X̅=52.9 + 8.2 (n=121) and X̅=50.7 + 10.4, (n=121), p Conclusion As expected, there were significant differences in patient reported fatigue between the COVID-19 and the control group. The between group differences were modest. Significant and large scale group differences were not evident for T2 (during follow-up). This suggests that COVID is associated with increased fatigue but we did not detect “Long COVID” effects. This may be due to methodologic considerations. In order to observe “Long COVID” the data will need to be anchored to illness onset and offset. Support (If Any) Support: 5T32HL00795320;K24AG055602

Introduction The present study sought to evaluate whether insomnia severity (i.e., sleep continuity disturbance) is worse in those who endorse insomnia identity (i.e., identify as an “insomniac”) vs. those who endorse “having insomnia.” Methods This study utilized a cross-sectional group design in an archival/community dataset that was collected in the Philadelphia area. This dataset (n=3,483) was comprised of adults between 18 and 90 years of age (X̅age=53.6±11.0; female [76.4%]; White [91.4%]). All subjects in this analysis endorsed sleep problems. Subjects answered questions regarding demographics, sleep continuity (in minutes), and insomnia identity (“Do you think of yourself as someone that has insomnia” and “do you think of yourself as an ‘insomniac’"?). For both questions, individuals were categorized by their answers: strongly agree, agree, undecided, disagree, strongly disagree. MANOVAs and two-way ANOVAs were conducted to assess group differences (α=.01). Results Most individuals endorsed “having insomnia” (n=2,301 [66.1%; strongly agree and agree]) but did NOT endorse being an ‘insomniac’ (n=1,981 [56.9%; undecided, disagree, and strongly disagree]). For all measures, except TST, the two groups did not differ with respect to insomnia severity (i.e., SL[55.4±48.5;60.5±52.1], WASO[45.1±51.7;47.6±55.3], EMA[71.8±51.6;72.9±52.4], and TST [328±75.5;319.6±76.4, p=.009]). The magnitude of the differences between these groups ranged from 1-10 minutes. Conclusion It was found that individuals are more likely to endorse ‘having insomnia’ than they are to endorse being an ‘insomniac.’ Despite the implicit differences in “having” something vs. “being” something, the groups did not differ appreciably with respect to sleep continuity. Thus, the tendency to have insomnia identity may not be related to insomnia severity considerations. It is possible, if not likely, that such differences may be related to frequency or chronicity of insomnia. Barring, or in addition to these things, insomnia identity may be related to the mismatch between sleep ability and need and/or related to other non-specific factors. Future directions include refining the group definitions to include forms of insomnia identity that occur with relatively normal sleep continuity (i.e., normal severity and/or frequency and/or chronicity). It will also be important to evaluate whether the various forms of insomnia identity vary with age, sex, or disease comorbidity. Support (If Any) K24AG055602