Introduction: Forced migrants experience trauma that adversely affects their health, leading to disproportionately high rates of sleep disturbance. Despite this burden, gaps remain in sleep research, clinical training, and the development of treatment protocols for this population. Likewise, limited research exists on the bidirectional relationship between sleep and other prevalent conditions in this population. This study assessed the relationship of sleep quality with anxiety, depression, post-traumatic stress disorder (PTSD), chronic pain, blood pressure, resting heart rate, and heart rate variability in a forced migrant population. It also reports on associations of sleep quality with trauma exposure and social participation. Materials and Methods: This was a cross-sectional study of 65 forced migrants who have at least mild chronic pain. Partial correlations were conducted with sleep quality and each outcome, controlling for age, body mass index (BMI), sex, length of time in the United States, and length of services at two trauma rehabilitation clinics. Results: Participants experienced high rates of poor sleep (92.3%). Sleep quality scores were significantly associated with PTSD, depression, anxiety, and chronic pain but not blood pressure, resting heart rate, or heart rate variability. Trauma exposure was significantly associated with poorer sleep quality, whereas social participation was associated with better sleep quality. Conclusion: Sleep quality was significantly associated with PTSD, anxiety, depression, and chronic pain in forced migrants and may represent an important clinical target in trauma rehabilitation. The contribution of this study is documenting these associations within a forced migrant population, where sleep remains understudied. Future work should develop and test sleep interventions adapted for the needs and context of forced migrants.

Abstract Introduction Emergency service personnel, such as paramedics, predominantly perform rotational shift work to provide the public with around-the-clock care in times of crisis. Consequently, a high prevalence of emergency service personnel experience shift work disorder (SWD), a circadian rhythm sleep disorder associated with the shift work schedule that comprises symptoms of insomnia and/or excessive sleepiness. Despite the high rates of SWD in paramedics, the risk factors that predispose new personnel to SWD are not well understood. The present study examined whether mental health symptoms in new paramedics prior to shift and emergency work were associated with SWD later in their career. Methods Mental health symptoms and sleep disorder risk were examined in recruit paramedics (n=105) at baseline, prior to any shift and emergency work, and then again after 12-months of shift work as a paramedic. Prior to baseline, participants had no previous employment in any emergency service or defence force and had not worked shift work in the last 3 months. At both timepoints, participants completed validated measures to assess depression (Patient Health Questionnaire-9) and anxiety symptoms (Generalised Anxiety Disorder-7) and screen for risk of SWD (SWD Screening Questionnaire). Multivariate logistic regression models examined whether depression and anxiety symptoms at baseline were associated with SWD risk at the 12-month follow-up, after adjustment for confounders using the backward elimination method. Results Eighteen percent of paramedics were high risk of SWD after 12-months of shift and emergency work. Increased depression symptoms before beginning shift and emergency work were associated with higher odds of SWD at the 12-month timepoint (Adjusted Odds Ratio 1.25, 95% Confidence Interval 1.01-1.56, p = 0.04). Anxiety symptoms at baseline were not associated with SWD at the 12-month follow-up (Adjusted Odds Ratio 1.07, 95% Confidence Interval 0.88-1.28, p = 0.44). Conclusion Our findings establish depression symptoms before shift and emergency work as an early risk factor for the later development of SWD in new paramedics. These results suggest the need to investigate the effectiveness of interventions that target depression early in paramedics’ careers to reduce the future risk of SWD in this demanding occupation. Support (if any) APP1138322, ASA Rob Pierce Grant in Aid

Objectives Shift work disorder (SWD) is common in paramedics and is associated with increased severity of depression and anxiety. Prior research shows pre-shift work depression symptoms are associated with increased risk of SWD after 6-months of work in paramedics. The current study aims to extend this area by investigating both depression and anxiety symptoms as risk factors for SWD after 12-months of work in new paramedics. Methods New paramedics completed an online survey measuring depression (Patient Health Questionnaire-9), anxiety (Generalized Anxiety Disorder Questionnaire-7), and SWD (SWD-screening Questionnaire) before (n=105) and after 12-months of rotating shift work (n=92). Results After 12-months of shift work, 18.5% of paramedics were at high risk for SWD. Pre-shift work depression (OR=1.25[1.01,1.56]) but not anxiety (OR=1.07[0.88,1.28]) predicted being high risk for SWD at 12-months. Conclusions Paramedic depression symptom severity before commencing shift work remains an important predictor of SWD risk after 12-months of work.

Model-free (MF) and model-based (MB) learning strategies are complementary decision-making processes used in evaluating choices with potential rewards. Disorders involving compulsive behaviours (e.g., substance use, gambling) are suggested to emerge from an overreliance on MF learning, though the reasons for this bias remain unclear. Sleep disruptions, common in these disorders, could be a contributing factor, however no study has examined the impact of sleep and/or sleep loss on an individual's engagement of each strategy. Thus, this study examined the influence of sleep on MF/MB learning in healthy adults. Participants (n = 67, Mage = 26.21yrs, SD = 5.82yrs, females = 65.67%) completed a two-stage reinforcement learning paradigm following a week of either sleep restriction (5-hr time in bed/night) or well-rested sleep (9-hr/night). Using mixed-effect logistic regressions and comprehensive computational modelling, we found no differences in MF and MB learning based on sleep condition (all p = > 0.05). However, regressions showed less REM sleep was associated with increased use of MB learning, whilst greater levels of REM sleep were associated with increased use of MF learning. Computational modelling supported this, revealing negative associations between the MB parameter estimate and REM sleep percentage (τ = -0.22, p = 0.02). This suggests the amount of REM sleep prior to learning may potentially play a role in determining which strategy will dominate. In particular, individuals with less REM sleep may be less willing or able to assess the relative costs and benefits of each strategy. Future research should explore this relationship further.

Study objectives: The comorbidity of insomnia and obstructive sleep apnea (COMISA) is common and associated with adverse clinical consequences. While insomnia is often underdiagnosed among individuals with OSA, the identification of insomnia among these individuals may lead to improved medical care. Our objective was to assess the performance of two simplified tools (insomnia severity index-2 (ISI-2) and ISI-3) to identify insomnia among individuals with OSA. We hypothesized that the ISI-2 and ISI-3 perform well to diagnose insomnia among individuals with OSA. Methods: Four different cohorts of individuals with sleep disorders were studied. Cohorts 1,2 and 3 included individuals with OSA. Cohort 4 included individuals with insomnia only. The performance of ISI-2 and ISI-3 was compared to ISI-7-based diagnosis of insomnia using receiving operating characteristic curve analysis. Results: Cohorts 1, 2, 3 and 4 included 490, 124, 39 and 118 individuals, respectively. Individuals from cohorts 1, 2 and 3 were middle-aged, obese and had severe OSA on average. Individuals from cohort 2 were predominantly male while from cohorts 3 and 4 were predominantly female. Individuals from cohort 4 were slightly younger, and eutrophic on average. Cohorts 3 and 4 had higher insomnia severity (ISI-7) than cohorts 1 and 2. Using cohort 1, the best cut-offs for ISI-2 and ISI-3 were >= 6 and >= 8, respectively. Area under the curve (AUC) for ISI-2 was .900, .951 and .893 among cohorts 1, 2 and 4, respectively. AUC for ISI-3 was .924, .961 and .936 among cohorts 1, 2 and 4, respectively. Conclusion: ISI-2 and ISI-3 are accurate screening tools for insomnia among individuals with sleep disorders. Easy recognition of insomnia among individuals with COMISA may improve clinical outcomes.

Sleep and physical activity (PA) are pillars of health. However, the temporal dynamics between these two behaviors remain poorly understood. This research aims to examine the independent and interactive between- and within-person associations of sleep duration and sleep onset timing on next-day PA duration in two large, longitudinal samples of adults under free-living conditions. In the primary study, participants (N = 19,963; 5,995,080 person-nights) wore a validated biometric device (WHOOP) for 1 y (01/09/2021 to 31/08/2022). Objective sleep and PA metrics were derived from the wrist-worn device. Generalized additive mixed models assessed between- and within-person associations between sleep and PA variables, adjusted for age, sex, Body Mass Index, weekday/weekend, seasonal effects, biometric feedback, and autocorrelated errors. Between participants, longer sleep duration and later sleep onset timing were associated with decreased moderate-to-vigorous PA (MVPA) and overall PA duration (ps < 0.001). Within participants, sleeping shorter-than-usual and falling asleep earlier-than-usual were associated with increased next-day MVPA and overall PA, whereas sleeping longer-than-usual, or falling asleep later-than-usual, showed the opposite relationship (ps < 0.001). Next-day MVPA duration was highest following earlier-than-usual sleep onset timing combined with one's typical sleep duration. Results were consistent but smaller in magnitude in the external validation study (N = 5,898; 635,477 person-nights) using Fitbit data from the All of Us Research Program. Individuals may sacrifice time in one health behavior for time in the other. Interventions promoting exercise and holistic public health messaging should consider the temporal dynamics between sleep and next-day PA outcomes.

Chronic insomnia is a prevalent sleep disorder where <1% of patients receive the recommended first-line treatment; Cognitive Behavioural Therapy for Insomnia. Digital technologies and self-managed therapies are scalable solutions to address this critical gap in patient care, but it is presently difficult to know which therapies are best. This study will test the comparative efficacy and cost-benefits of Intensive Sleep Retraining administered by the THIM sleep tracker, Sleep Healthy Using the Internet (SHUTi) treatment program, and their combination (THIM then SHUTi) versus a waitlist control group. This study is a 4 (treatment: +/- THIM and +/- SHUTi) × 3 (time: pretreatment, posttreatment, and 2-month follow-up) randomized controlled trial. Participants who meet the diagnostic criteria for Chronic Insomnia Disorder will be randomized to one of four groups. Sleep and daytime functioning symptoms will be assessed via self-report daily and weekly questionnaires, and objective sleep trackers during treatment and for 2 weeks at pre-treatment, post-treatment, and 2-month follow-up. The primary outcome is total wake time, with a reduction of ≥30 minutes considered a clinically meaningful difference. For the primary analysis, the interaction between the treatment group and time on total wake time will be analyzed using repeated measures analyses of variance (ANOVA). This project was approved by the Southern Adelaide Clinical Human Research Ethics Committee (2021/HRE00414) and registered in the Australian and New Zealand Clinical Trials Registry (ACTRN12622000778785). As the first study to investigate the comparative efficacy of two different technology-enabled treatments for insomnia, this study will help inform clinicians and public health policy regarding the use cases for public and private health-funded technology-enabled options for insomnia.

Objectives The primary aims of the current study were to 1) investigate whether cognitive factors are associated with an increased risk of shift work disorder (SWD), and 2) whether symptoms of insomnia and/or excessive sleepiness mediate this association. Additionally, a third exploratory aim of the study was to examine whether these mediators of insomnia and excessive sleepiness vary in the relationship between cognitive factors and two phenotypes of SWD (i.e., SWD with high insomnia and low excessive sleepiness (SWD-I), and SWD with high excessive sleepiness with or without high insomnia (SWD-E)). Methods Shift workers (n = 126), predominantly working a schedule involving night shifts, completed a survey comprising measures of SWD risk, insomnia, excessive sleepiness, and cognitive factors, including pre-sleep cognitive and somatic arousal, dysfunctional beliefs about sleep, and sleep reactivity. Results Logistic regressions found cognitive factors were not associated with SWD risk. Mediation analysis showed insomnia symptoms mediated the impact of pre-sleep somatic arousal, dysfunctional beliefs about sleep, and sleep reactivity on high SWD risk. Of those at high risk of SWD (37 %), 43 % and 34 % had the SWD-I and SWD-E phenotype, respectively. Insomnia symptoms mediated the relationship between all cognitive factors and SWD-I, but not SWD-E. Conclusions Although cognitive factors were not directly associated with SWD risk, insomnia severity, but not excessive sleepiness, was a significant cross-sectional mediator in the relationship between cognitive factors and risk of SWD. When exploring SWD phenotypes, cognitive factors were associated with a risk of having SWD when participants did not have excessive sleepiness (i.e., SWD-I). To expand on our findings, future research should investigate insomnia's role as a mediator in individuals diagnosed with SWD and to investigate the SWD phenotypes with larger samples.

Cognitive behavioral therapy for insomnia (CBT-I) improves obstructive sleep apnea (OSA) severity in comorbid insomnia and sleep apnea, though the mechanisms underlying this change are unstudied. CBT-I, which promotes sleep continuity and reduces hyperarousal, may improve OSA by raising the respiratory arousal threshold. We aimed to investigate the effect of CBT-I on OSA severity and its impact on the arousal threshold and other endotype traits. In this single-arm trial, 25 patients with comorbid insomnia and sleep apnea (13 females and 12 males, mean age [standard deviation] = 53.7 [8.7] years) completed a 7-week individual CBT-I program. Patients met diagnostic criteria for insomnia and demonstrated an apnea-hypopnea index (AHI) ≥ 10 events/h (mean AHI [standard deviation] = 35.2 [16.4] events/h). Overnight polysomnography before and after CBT-I measured OSA severity, sleep architecture, and the 4 OSA endotypes (ie, collapsibility, muscle compensation, loop gain, and arousal threshold). There was a 7.7 ± 10.2 events/h reduction in the AHI from baseline to posttreatment (P = .001) but no change in any of the OSA endotype traits studied (all P > .05). Secondary analyses showed a relationship whereby increases in stage N3 sleep were associated with decreases in AHI (r2 = .19, P = .03). Significant improvements were also found in insomnia severity and sleep diary–based sleep efficiency, sleep onset latency, and wake after sleep onset at posttreatment (all P < .001). CBT-I is beneficial in improving insomnia symptoms and we provide further support CBT-I improves OSA severity. Despite no change in the OSA endotype traits, the improvement in the AHI may be associated with increased amounts of stage N3 sleep. These results underscore the importance of managing insomnia in comorbid insomnia and sleep apnea. Registry: Australian New Zealand Clinical Trial Registry; Name: Project COMISA (Comorbid Insomnia and obstructive Sleep Apnea): A study investigating the effect of cognitive behavioral therapy for insomnia (CBT-I) on obstructive sleep apnea severity and cognitive functioning in patients experiencing COMISA; URL: http://www.anzctr.org.au/ ; Identifier: ACTRN12622000226707. Brooker EJ, Landry SA, Genta PR, Abdelmessih GT, Edwards BA, Drummond SPA. Cognitive behavioral therapy for insomnia is associated with reduced sleep apnea severity but not its endotype traits in those with comorbid insomnia and sleep apnea. J Clin Sleep Med. 2025;21(6):1041–1051.

Paramedics make up an integral part of modern healthcare systems, however, there remains a paucity of research on the occupational demands of their role. The majority of paramedics in Australia work on a rotating shift schedule. Despite the documented impact of shift work on sleep loss, and resultant performance and physiological impairments, few studies have examined the implications of shift work in paramedic populations. This study explores the impact of shift work, and the resultant circadian rhythm disruption, on paramedic decision making, work performance and underlying physiology. The study aims to recruit 22 Australian paramedics with an entry to practice scope. In pairs, participants complete a two 12-hour day shift, two 12-hour night shift simulated work rotation. All sleep opportunities during the rotation occur in the Monash Sleep and Circadian Medicine Laboratory and are monitored with polysomnography. Simulated paramedic shifts take place in the Monash Paramedic Simulation Centre, where participants engage in high-fidelity immersive paramedic scenarios throughout the shift. Paramedic scenarios are recorded for asynchronous evaluation by subject matter experts. In addition to paramedic scenarios, participants complete two cognitive and decision-making batteries during each shift. Biological markers are also collected throughout the rotation to assess changes in paramedics' stress responses (i.e., alpha-amylase, cortisol, heart rate variability, cytokines), as well as circadian phase (i.e., 6-sulfatoxymelatonin). The novel simulated work environment study design contributes significantly to the paramedic body of literature through advancing our understanding of the impacts of shift work on paramedics. This study provides valuable insights into the nature of paramedic work and generates future research directions that will allow for further examination and understanding of the occupational demands of the paramedic profession.

Background:Insufficient sleep and circadian timing are both linked with obesity, primarily via unhealthy food choice, yet the cognitive mechanisms underpinning such relationships remain unclear. Methods:Across two studies, we implemented an ecologically valid within-subjects at-home protocol. Study 1 (n = 118) involved a within-subjects examination of how sleep restriction (SR) versus well-rested (WR) sleep levels affect choices in a food-based approach-avoidance task (AAT) and go-no/go (GNG) task, a food liking task, a food-choice task, a psychomotor vigilance task (PVT), and a monetary choice task. Study 2 (n = 119) involved examining choices in the same set of tasks administered once in the afternoon (4pm) and once during the night (4am), which leveraged circadian influences on sleepiness and cognitive function. Results:During the night, participants indicated steeper discounting rates relative to the afternoon. Furthermore, such rates predicted higher liking of high-calorie food choices regardless of time of day and when sleep restricted. Approach bias for low-calorie food interacted with the night condition in predicting both low- and high-calorie food choices. Conclusion:Both delay discounting and approach bias may be important cognitive mechanisms predicting food liking and choice under sleep restricted and altered circadian timing conditions. Further research should replicate such results using real rewards.

Story retelling is an important form of communication, cultural practice, and message transmission. Insufficient sleep is known to affect relevant cognitive skill areas necessary for story retelling or transmission fidelity. We conducted a preregistered randomized cross-over study on n = 155 young adults with exogenously assigned nightly sleep levels experienced in their at-home environments. A serial story reproduction task was administered online, and chains of up to three retells of a given story involved varied numbers of sleep restricted (SR) versus well-rested (WR) retellers. While story content decayed with each retell, group-level analysis showed that additional SR retellers in a chain was associated with greater decay, which mostly resulted from the introduction of an initial SR reteller at the first retell. Supporting the group-level effect, individual-level analysis confirmed that the number of details and the story’s key event were significantly less preserved during a participant’s SR treatment week. Exploratory analysis showed an attenuation of this effect in those reporting a higher level of affective response (interest or surprise) in the story. This suggests that emotional engagement can combat the deleterious effects of SR on successful story retelling, and perhaps on other types of content recollection.

Public health guidelines recommend exercise as a key lifestyle intervention for promoting and maintaining healthy sleep function and reducing disease risk. However, strenuous evening exercise may disrupt sleep due to heightened sympathetic arousal. This study examines the association between strenuous evening exercise and objective sleep, using data from 14,689 physically active individuals who wore a biometric device during a one-year study interval (4,084,354 person-nights). Here we show later exercise timing and higher exercise strain are associated with delayed sleep onset, shorter sleep duration, lower sleep quality, higher nocturnal resting heart rate, and lower nocturnal heart rate variability. Regardless of strain, exercise bouts ending ≥4 hours before sleep onset are not associated with changes in sleep. Our results suggest evening exercise-particularly involving high exercise strain-may disrupt subsequent sleep and nocturnal autonomic function. Individuals aiming to improve sleep health may benefit from concluding exercise at least 4 hours before sleep onset or electing lighter strain exercises within this window.

The impact of sleep loss on decision-making is well-documented, yet current quantitative methods often obscure the cognitive mechanisms underlying these impairments. This review examines evidence from key studies on how sleep deprivation affects decision-making domains, including risk propensity, effort and delay discounting, Bayesian reasoning, and cognitive flexibility. We critique the prevalent reliance on global behavioural metrics, highlighting three key limitations: 1) sleep-driven cognitive effects may be masked despite non-significant behavioural outcomes, 2) alternative cognitive strategies are often overlooked, and 3) these metrics fail to incorporate advances in cognitive neuroscience. To address these issues, we advocate for integrating computational cognitive models with existing quantitative methods. These models provide precise estimates of latent cognitive processes often missed by conventional analyses. As an exemplar, we reanalyse previously published data, revealing sleep-related deficits in value sensitivity and increased decision noise. These insights highlight the utility of computational cognitive models in supplementing traditional methods to uncover how sleep loss affects specific cognitive processes essential for decision-making. Beyond improving mechanistic insights, computational cognitive models may enhance the accuracy and interpretability of sleep research and inform the development of targeted interventions to mitigate decision-making impairments caused by sleep loss.

Background: A myriad of modifiable cognitive and behavioural factors influence adolescent sleep. Using an intense longitudinal design, we investigated adolescents’ perceptions of factors facilitating (i.e., facilitators) and hindering (i.e., barriers) sufficient and good quality sleep in their everyday life.Methods: 205 (54.2% female, 64.4% non-white) Year 10-12 adolescents (Mage = 16.9 ± 0.9) completed daily morning surveys and wore actigraphs over 2 school-weeks and 2 subsequent vacation-weeks (5162 total observations). Daily morning surveys assessed self-reported sleep and use of 8 facilitators and 6 barriers of sleep from the previous night. Linear mixed-effects models examined the contribution of facilitators/barriers to actigraphy and self-reported total sleep time (TST) and sleep onset latency (SOL), controlled for age, sex, race, place of birth, and study day. School/non-school day status was included as a moderator.Results: Seven facilitators and two barriers were endorsed by >30% of adolescents as frequently (≥50% nights) helping/preventing them from achieving good sleep. Overall, facilitators or barriers explained 1-5% (p-values <.001) of unique variance above and beyond the covariates. Facilitators, predicting longer TST and shorter SOL, were following body cues, managing thoughts and emotions, creating good sleep environment, avoiding activities interfering with sleep, and bedtime planning (only TST on school nights). Barriers, predicting shorter TST and longer SOL, were pre-bed thoughts and emotions, unconducive sleep environment, activities interfering with sleep, inconsistent routines, and other household members’ activities. Conclusions: Adolescents use a range of sleep facilitating behaviours and a number of factors prevent sufficient and good quality sleep in their everyday life. These factors are predictive of their sleep duration and onset latency and require further research to understand their functions and clinical implications.

The current study aimed to identify how manipulated sleep restriction affects dietary choices and physical activity (PA). Young adults were administered one week of well-rested sleep levels (WR: 8-9 h/night) and sleep-restriction (SR: 5-6 h/night) in their (naturalistic) at-home setting, using a randomized cross-over design. Participants made consequential bids for snacks/beverages following SR and WR in an auction task. Other primary outcome measures included daily self-reported dietary intake and actigraphy-measured PA. Multivariate regression analyses examined main and moderator impacts of SR on primary outcome measures. In total, 118 treatment participants completed the study (M = 20 years old, n = 65 females). SR predicted increased self-reported daily caloric intake and importance of taste (over healthiness) in auction bids, but only in participants with higher baseline cognitive or behavioral control characteristics (p < .05). Furthermore, SR predicted reduced average hourly PA (p < .01), increased sedentary behaviors (p < .01), and more prolonged bouts of sitting (p < .01) for all participants. While prior literature suggests dietary choices may mediate the link between SR and obesity, we did not find altered dietary choices. Rather, our results suggest decreased PA may also contribute to the link between SR and obesity.

Background Capturing sleep data historically required complex, expensive, and labour-intensive equipment, with the gold standard being overnight polysomnography (PSG). Newer portable devices, such as the Dreem 3 headband, provide a novel opportunity to collect field-based data and have demonstrated accuracy in healthy sleepers compared to PSG. However, this device's performance has not been assessed in Insomnia Disorder, despite sleep-tracking technologies traditionally performing poorly in disordered sleepers. This study aimed to evaluate the performance of Dreem 3 against PSG on key sleep outcomes. Methods Thirty-one adults (Mage = 45.9 years, 16 males) with Insomnia Disorder participated in an overnight sleep study wearing Dreem 3 and PSG simultaneously. Sensitivity and specificity were calculated using an epoch-by-epoch analysis. Bland-Altman plots further assessed performance related to sleep stages and continuity variables: total sleep time (TST), sleep efficiency (SE), sleep latency (SL), and wake after sleep onset (WASO). Results Dreem 3 showed the highest sensitivity for REM sleep (89.88 %) and the lowest sensitivity for N1 (29.79 %). N3 sensitivity was also notably low (65.65 %). Specificity was >90 % for all stages, except N2 (83.39 %). Dreem accurately summarised SL and WASO but significantly overestimated TST and SE. Conclusion The Dreem 3 headband can accurately evaluate and report most sleep staging and continuity variables in individuals with Insomnia Disorder. Users should be mindful of the strengths and limitations of the device when deciding whether the Dreem 3 is suitable for their needs. If applied and interpreted correctly, this device could facilitate large-scale, longitudinal sleep studies and assessment of sleep in Insomnia Disorder.