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Study Objectives To compare overnight declarative memory consolidation and non-rapid eye movement (NREM) sleep electroencephalogram (EEG) oscillations in older adults with obstructive sleep apnea (OSA) to a control group and assess slow-wave activity (SWA) and sleep spindles as correlates of memory consolidation. Methods Forty-six older adults (24 without OSA and 22 with OSA) completed a word-pair associate's declarative memory task before and after polysomnography. Recall and recognition were expressed as a percentage of the morning relative to evening scores. Power spectral analysis was performed on EEG recorded at frontal (F3-M2, F4-M1) and central (C3-M2, C4-M1) sites. We calculated NREM absolute slow oscillation (0.25–1 Hz) and delta (0.5–4.5 Hz) EEG power, and slow (11–13 Hz) spindle density (number of events per minute of N2 sleep) and fast (13–16 Hz) spindle density. Results There were no significant differences in overnight recall and recognition between OSA (mean age 58.7 ± 7.1 years, apnea–hypopnea index (AHI) 41.9 ± 29.7 events/hour) and non-OSA (age 61.1 ± 10.3 years, AHI 6.6 ± 4.2 events/hour) groups. The OSA group had lower fast spindle density in the frontal region (p = 0.007). No between-group differences in SWA were observed. In the Control group, overnight recognition positively correlated with slow spindle density in frontal (rho = 0.555, p = 0.020) and central regions (rho = 0.490, p = 0.046). Overnight recall was not related to SWA or spindle measures in either group. Conclusions Older adults with OSA had deficits in fast sleep spindles but showed preserved overnight declarative memory consolidation. It is possible that compensatory mechanisms are being recruited by OSA patients to preserve declarative memory consolidation despite the presence of sleep spindle deficits.

Objective This pilot trial aimed to provide evidence for whether the integration of a wearable device with digital behavioral therapy for insomnia (dBTi) improves treatment outcomes and engagement. Participants and methods One hundred and twenty-eight participants with insomnia symptoms were randomized to a 3-week dBTi program (SleepFix®) with a wearable device enabling sleep data synchronization (dBTi+wearable group; n = 62) or dBTi alone (n = 66). Participants completed the Insomnia Severity Index (ISI) and modified Pittsburgh Sleep Quality Index (PSQI) parameters: wake-after-sleep-onset (WASO), sleep-onset-latency (SOL), and total sleep time (TST) at baseline and weeks 1, 2, 3, and primary endpoint of week 6 and follow-up at 12 weeks. Engagement was measured by the number of daily sleep diaries logged in the app. Results There was no difference in ISI change scores between the groups from pre- to post-treatment (Cohen's d= 0.7, p= .061). The dBTi+wearable group showed greater improvements in WASO (d= 0.8, p = .005) and TST (d= 0.3, p= .049) compared to the dBTi group. Significantly greater engagement (sleep diary entries) was observed in the dBTi+wearable group (mean = 22.4, SD = 10.0) compared to the dBTi group (mean = 14.1, SD = 14.2) (p = .010). Conclusions This pilot trial found that integration of wearable device with a digital insomnia therapy enhanced user engagement and led to improvements in sleep parameters compared to dBTi alone. These findings suggest that adjunctive wearable technologies may improve digital insomnia therapy effectiveness.

Sleep restriction therapy (SRT) is an effective stand-alone behavioural intervention for insomnia disorder. However, its daytime side effects, particularly sleepiness, may be troubling for patients and/or may be a necessary part of the patient's treatment journey. This pilot trial aims to explore the potential benefit of armodafinil, a wakefulness promoter. Patients were treated with SRT with open label adjunctive armodafinil (150 mg/day). Thirty-three patients from previous studies that have undergone exactly the same SRT intervention acted as controls. The primary outcome measure was the insomnia severity index (ISI), and secondary outcomes were the Epworth sleepiness scale, sleep restriction adherence scale (SRAS), and safety from baseline through to 12 weeks. We recruited 25 patients into the trial. Data for the primary end point (ISI at 12 weeks) was available for 20 of the participants. The baseline insomnia severity index was 20.2 (SD 3.3) and decreased to 9.1 (SE 1.1), with no change, to 10.2 and 11.2 at weeks 6 and 12 respectively (all p 0.05 compared with baseline). The insomnia severity index values for armodafinil patients were statistically inferior to historical controls at the primary time point of 12 weeks (11.2 vs. 6.7, p 0.01). Sleep restriction therapy plus armodafinil treatment was associated with frequent minor side effects but was generally safe and acceptable to patients. Sleep restriction therapy was associated with a robust clinical response in the insomnia severity index values for insomnia patients. Based upon historical control data, armodafinil does not appear to have beneficial adjunctive effects in addition to sleep restriction therapy alone.

BACKGROUND: Obstructive sleep apnea (OSA) is a highly prevalent sleep disorder that is associated with a range of adverse daytime sequelae, including significantly higher rates of clinical depression than is seen in the general community. Improvements in depressive symptoms occur after treatment of the primary sleep disorder, suggesting that comorbid depression might be an intrinsic feature of OSA. However, there are limited data on whether treatment for OSA in patients diagnosed with clinical depression improves mood symptoms meaningfully enough to lead to the remission of the psychiatric diagnosis. METHODS: N = 121 untreated OSA patients were randomized to either continuous positive airway pressure (CPAP) treatment or waitlist control, and depressive symptoms, sleepiness and clinical depression (using a structured clinical interview) were assessed at baseline and 4 months. Linear and logistic regression analyses were conducted, controlling for baseline scores, stratification factors and antidepressant use. RESULTS: Depressive symptoms (odds ratio [OR] = -4.19; 95% confidence interval [CI] = -7.25, -1.13; p = .008) and sleepiness (OR = -4.71; 95% CI = -6.26, -3.17; p

Using quantitative EEG (qEEG) analysis, we investigated sleep EEG microstructure as correlates of neurobehavioural performance after 24 h of extended wakefulness in untreated OSA. Eight male OSA patients underwent overnight polysomnography (PSG) at baseline followed by 40 h awake with repeated performance testing (psychomotor vigilance task [PVT] and AusEd driving simulator). EEG slowing during REM and spindle density during NREM sleep were calculated using power spectral analysis and a spindle detection algorithm at frontal and central electrode sites. Correlations between sleep EEG microstructure measures and performance after 24-h awake were assessed. Greater EEG slowing during REM sleep was associated with slower PVT reaction times (rho = − 0.79, p = 0.02), more PVT lapses (rho = 0.87, p = 0.005) and more AusEd crashes (rho = 0.73, p = 0.04). Decreased spindle density in NREM sleep was also associated with slower PVT reaction times (rho = 0.89, p = 0.007). Traditional PSG measures of disease severity were not consistent correlates of neurobehavioural performance in OSA. Sleep EEG microstructure measures recorded during routine PSG are associated with impaired vigilance in OSA patients after sleep deprivation. Quantitative brain oscillatory (or EEG)–based measures of sleep may better reflect the deleterious effects of untreated OSA than traditional PSG metrics in at-risk individuals. Trial Registration ACTRN12606000066583

Insomnia disorder (ID) is a heterogeneous disorder with proposed subtypes based on objective sleep duration. We speculated that insomnia subtyping with additional power spectral analysis and measurement of response to acute sleep restriction may be informative in overall assessment of ID. To explore alternative classifications of ID subtypes, insomnia patients (n = 99) underwent two consecutive overnight sleep studies: (i) habitual sleep opportunity (polysomnography, PSG) and, (ii) two hours less sleep opportunity (electroencephalography, EEG), with the first night compared to healthy controls (n = 25). ID subtypes were derived from data-driven classification of PSG, EEG spectral power and interhemispheric EEG asymmetry index. Three insomnia subtypes with different sleep duration and NREM spectral power were identified. One subtype (n = 26) had shorter sleep duration and lower NREM delta power than healthy controls (short-sleep delta-deficient; SSDD), the second subtype (n = 51) had normal sleep duration but lower NREM delta power than healthy controls (normal-sleep delta-deficient; NSDD) and a third subtype showed (n = 22) no difference in sleep duration or delta power from healthy controls (normal neurophysiological sleep; NNS). Acute sleep restriction improved multiple objective sleep measures across all insomnia subtypes including increased delta power in SSDD and NSDD, and improvements in subjective sleep quality for SSDD (p = 0.03), with a trend observed for NSDD (p = 0.057). These exploratory results suggest evidence of novel neurophysiological insomnia subtypes that may inform sleep state misperception in ID and with further research, may provide pathways for personalised care.

Difficulties falling asleep or staying asleep (symptoms of insomnia) are common following paediatric traumatic brain injury (TBI). Yet, interventions to treat insomnia in this population have not yet been reported. This single-case series examined the feasibility and acceptability of cognitive behavioral treatment for insomnia (CBT-I) for adolescents (

Objective/background Patients with obstructive sleep apnea (OSA) experience daytime sleepiness, cognitive impairment and depressive symptoms. However, the measured prevalence of clinical depression in OSA using standardized clinical assessment is currently unclear. The aims of this study were to examine the prevalence of clinical depression and antidepressant use in untreated OSA patients, to examine predictors of depression, and to conduct an exploratory meta-analysis to determine the pooled prevalence of clinical depression in this population. Patients/methods In sum, 109 consecutive patients with diagnosed OSA (mean age (SD) = 52.6 (12.1) years; 43.1% female) who presented to the sleep laboratory completed a structured clinical interview for depression (SCID-IV), the Hospital Anxiety and Depression Scale, the Pittsburgh Sleep Quality Index (PSQI), the Functional Outcomes of Sleep Questionnaire (FOSQ), the Assessment of Quality of Life Questionnaire (AQoL) and the Epworth Sleepiness Scale (EES). An exploratory meta-analysis was also conducted to quantify the risk of clinical depression in untreated OSA. Results Twenty-five (22.7%) participants had clinical depression based on the SCID-IV, and 24.8% were using antidepressants. Those with clinical depression had significantly poorer sleep quality and impaired quality of life. In a regression model, quality of life impairment was most strongly associated with clinical depression. Results from the meta-analysis revealed a pooled prevalence of 23% of clinical depression in OSA patients across seven studies. Conclusion Clinical depression and antidepressant use is common in patients with OSA. Depression was associated with reduced quality of life and poorer subjective sleep, however it was not associated with polysomnographic measures or daytime sleepiness. Whether CPAP treatment can alleviate the burden of clinical depression needs to be determined in future studies.

Study ObjectivesUntreated obstructive sleep apnea (OSA) is associated with cognitive deficits and altered brain electrophysiology. We evaluated the effect of continuous positive airway pressure (CPAP) treatment on quantitative sleep electroencephalogram (EEG) measures and cognitive function.MethodsWe studied 167 patients with OSA (age 50 ± 13, AHI 35.0 ± 26.8) before and after 6 months of CPAP. Cognitive tests assessed working memory, sustained attention, visuospatial scanning, and executive function. All participants underwent overnight polysomnography at baseline and after CPAP. Power spectral analysis was performed on EEG data (C3-M2) in a sub-set of 90 participants. Relative delta EEG power and sigma power in NREM and EEG slowing in REM were calculated. Spindle densities (events/min) in N2 were also derived using automated spindle event detection. All outcomes were analysed as change from baseline.ResultsCognitive function across all cognitive domains improved after six months of CPAP. In our sub-set, increased relative delta power (p ConclusionsCognitive performance was improved and sleep EEG features were enhanced when assessing the effects of CPAP. These findings suggest the reversibility of cognitive deficits and altered brain electrophysiology observed in untreated OSA following six months of treatment.

IntroductionInsomnia is a prevalent sleep disorder that causes substantial personal and societal harm. There is evidence that placebo interventions can reduce insomnia symptoms, but this research has involved deceptively administering the placebo under the guise of a real medication (conventional placebo, CP), which has obvious ethical constraints. Open-label placebo (OLP) treatment, in which a placebo is administered with full disclosure that there are no active ingredients, has been proposed as a method of using the placebo effect ethically, but the efficacy and acceptability of OLP for insomnia is currently unknown.Methods and analysisThis study uses a cohort multiple randomised controlled trial design to compare OLP, CP and no treatment for insomnia. Two-hundred and sixty-seven participants with self-reported insomnia symptoms (Insomnia Severity Index, ISI ≥10) will be recruited into an observational study and have their sleep monitored over a 2-week period. Participants will then be randomised to one of three groups: invite to OLP, invite to CP described deceptively as a new pharmacological agent, or no invite/observational control. Those in OLP and CP accepting the invite receive identical placebos for a 2-week treatment period while sleep is monitored in all participants. The primary outcome is ISI at the end of the treatment period. Secondary outcomes include treatment uptake and clinically significant response rates, objective and subjective sleep parameters, fatigue, mood, expectancy, treatment satisfaction and side effects. Predictors of uptake and responses to OLP and CP will be explored.Ethics and disseminationThe trial has been approved by The University of Sydney Human Research Ethics Committee. Written informed consent is obtained from every participant. OLP and CP participants accepting the invite undergo an additional consent process. Results will be disseminated via peer-reviewed conference proceedings and publications.Trial registration numberACTRN12620001080910.

Objectives Insomnia is diagnosed using clinical interview but actigraphy is often used as a consecutive multi-day measurement of activity-rest cycles to quantify sleep-wake periods. However, discrepancies between subjective complaints of insomnia and objective actigraphy measurement exist. The aims of the current study were to (i) predict subjective sleep quality using actigraphic data and, (ii) identify features of actigraphy that are associated with poor subjective sleep quality. Methods Actigraphy data were collected for 14-consecutive days with corresponding subjective sleep quality ratings from participants with Insomnia Disorder and healthy controls. We fitted multiple machine learning algorithms to determine the best performing method with the highest accuracy of predicting subjective quality rating using actigraphic data. Results We analysed a total of 1278 days of actigraphy and corresponding subjective sleep quality ratings from 86 insomnia disorder patients and 20 healthy controls. The k-neighbors classifier provided the best performance in predicting subjective sleep quality with an overall accuracy, sensitivity and specificity of 83%, 74% and 87% respectively, and an average AUC-ROC of 0.88. We also found that activity recorded in the early morning (04:00-08:00) and overnight periods (00:00-04:00) had the greatest influence on sleep quality scores, with poor sleep quality related to these periods.. Conclusions A machine learning model based on actigraphy time-series data successfully predicted self-reported sleep quality. This approach could facilitate clinician’s diagnostic capabilities and provide an objective marker of subjective sleep disturbance.

Continuous positive airway pressure (PAP) is still the most efficacious treatment for obstructive sleep apnea when used effectively. Since the availability of PAP 39 years ago there have been considerable technological advances, such as quieter, lighter and smaller machines with better humidification. However, adherence to treatment is still a major problem. This article reviews studies published on behavioral interventions aimed at improving the uptake and maintenance of PAP treatment (January 2016–February 2020). It discusses underlying factors in the poor uptake and discontinuation of treatment and the role of qualitative research to better understand the perspective of the patients.

Background Mobile health (mHealth) apps offer a scalable option for treating sleep disturbances at a population level. However, there is a lack of clarity about the development and evaluation of evidence-based mHealth apps. Objective The aim of this systematic review was to provide evidence for the design engineering and clinical implementation and evaluation of mHealth apps for sleep disturbance. Methods A systematic search of studies published from the inception of databases through February 2020 was conducted using 5 databases (MEDLINE, Embase, Cochrane Library, PsycINFO, and CINAHL). Results A total of 6015 papers were identified using the search strategy. After screening, 15 papers were identified that examined the design engineering and clinical implementation and evaluation of 8 different mHealth apps for sleep disturbance. Most of these apps delivered cognitive behavioral therapy for insomnia (CBT-I, n=4) or modified CBT-I (n=2). Half of the apps (n=4) identified adopting user-centered design or multidisciplinary teams in their design approach. Only 3 papers described user and data privacy. End-user acceptability and engagement were the most frequently assessed implementation metrics. Only 1 app had available evidence assessing all 4 implementation metrics (ie, acceptability, engagement, usability, and adherence). Most apps were prototype versions (n=5), with few matured apps. A total of 6 apps had supporting papers that provided a quantitative evaluation of clinical outcomes, but only 1 app had a supporting, adequately powered randomized controlled trial. Conclusions This is the first systematic review to synthesize and examine evidence for the design engineering and clinical implementation and evaluation of mHealth apps for sleep disturbance. The minimal number of apps with published evidence for design engineering and clinical implementation and evaluation contrasts starkly with the number of commercial sleep apps available. Moreover, there appears to be no standardization and consistency in the use of best practice design approaches and implementation assessments, along with very few rigorous efficacy evaluations. To facilitate the development of successful and evidence-based apps for sleep disturbance, we developed a high-level framework to guide researchers and app developers in the end-to-end process of app development and evaluation.

Sleep disturbance is a common symptom encountered by cannabis-dependent individuals abstaining from cannabis use. In the present study, we investigated the effect of daily aerobic cycling exercise versus control stretching on sleep quality during inpatient cannabis withdrawal in treatment-seeking dependent cannabis users. The protocol incorporated three consecutive phases: a 4-Day (4-Night) (at-home) 'Baseline' phase, a 6-Day (5-Night) 'Treatment' phase (within a 7-Day inpatient hospital stay) and a 3-Day (4-Night) (at-home) 'Post-Treatment' phase. Participants performed 35 min of monitored activity per day during the Treatment phase. The intervention group (n = 19) cycled at ~60% aerobic capacity (VO2max ), while the control group (n = 12) performed a stretching routine. Objective sleep quality was measured nightly throughout the study using wrist actigraphy ratings of subjective sleep quality were also recorded during the Treatment phase. There were no group differences in sleep measures during the Baseline phase (all p > .05). Objective sleep onset latency increased from the Baseline to the Treatment phase in the control (stretching) group (p = .042). In contrast, the Cycling group exhibited improvements in sleep duration (p = .008) and sleep efficiency (p = .023) during the Treatment phase compared to the Baseline phase. Cycling also increased sleep duration (p = .005), decreased average wake bout (p = .040) and tended to increase sleep efficiency (p = .051) compared to stretching during the Treatment phase. Subjective sleep quality ratings did not differ between groups (p > .10). These preliminary findings suggest that moderate-intensity aerobic exercise may attenuate the sleep disturbances associated with cannabis withdrawal.

We examined whether a polymorphism of the PERIOD3 gene (PER3; rs57875989) modulated the sleep promoting effects of melatonin in Delayed Sleep-Wake Phase Disorder (DSWPD). One hundred and four individuals (53 males; 29.4±10.0 years) with DSWPD and a delayed dim light melatonin onset (DLMO) collected buccal swabs for genotyping (PER34/4 n=43; PER3 5 allele [heterozygous and homozygous] n=60). Participants were randomised to placebo or 0.5mg melatonin taken 1 hour before desired bedtime (or ~ 1.45 h before DLMO), with sleep attempted at desired bedtime (4 weeks; 5-7 nights/week). We assessed sleep (diary and actigraphy), Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI), Patient-Reported Outcomes Measurement Information System (PROMIS: Sleep Disturbance, Sleep-Related Impairment), Sheehan Disability Scale (SDS), and Patient- and Clinician-Global Improvement (PGI-C, CGI-C). Melatonin treatment response on actigraphic sleep onset time did not differ between genotypes. For PER34/4 carriers, self-reported sleep onset time was advanced by a larger amount and sleep onset latency (SOL) was shorter in melatonin-treated patients compared to those receiving placebo (P=0.008), while actigraphic sleep efficiency in the first third of the sleep episode (SE T1) did not differ. For PER3 5 carriers, actigraphic SOL and SE T1 showed a larger improvement with melatonin (P

Study Objectives Poor sleep is commonly problematic during pregnancy and postpartum and is associated with depression. This trial investigated the efficacy of prenatal brief, group sleep psychoeducation in improving postpartum maternal sleep, and depression. Methods A total of 215 healthy expectant first-time mothers were cluster randomized (1:1) to receive either a 2 × 1.5 h psychoeducation intervention and a set of booklets, or a set of booklets only. Participants completed questionnaires during pregnancy (pre-intervention), and 6 weeks and 4 months postpartum. A post hoc subset of questionnaires was collected at 10 months postpartum. The primary hypothesis was the intervention group would have improved postpartum sleep quality, and reduced levels of insomnia symptoms, fatigue, and daytime sleepiness compared to the control group. Secondary outcomes included depression, anxiety, and stress. Results Linear mixed model analyses failed to confirm a group by time interaction on primary or secondary outcomes across all time points. There was no effect of the intervention on outcomes at 6 weeks, or 10 months postpartum. A significant time by group interaction was found at 4 months, favoring the intervention for sleep quality (p = 0.03) and insomnia symptoms (p = 0.03), but not fatigue or daytime sleepiness. Conclusions Prenatal sleep psychoeducation did not produce a sustained effect on maternal sleep throughout the postpartum period. There was little evidence of benefits on depressive symptoms. Clinical Trial Registration ACTRN12611000859987

Introduction Insomnia is a highly prevalent and costly condition that is associated with increased health risks and healthcare utilisation. Anecdotally, cannabis use is frequently reported by consumers to promote sleep. However, there is limited research on the effects of cannabis on sleep and daytime function in people with insomnia disorder using objective measures. This proof-of-concept study will evaluate the effects of a single dose of an oral cannabis-based medicine on sleep and daytime function in participants with chronic insomnia disorder. Methods and analysis A randomised, crossover, placebo-controlled, single-dose study design will be used to test the safety and efficacy of an oral oil solution (‘ETC120’) containing 10 mg Δ9-tetrahydrocannabinol (THC) and 200 mg cannabidiol (CBD) in 20 participants diagnosed with chronic insomnia disorder. Participants aged 35–60 years will be recruited over an 18-month period commencing August 2019. Each participant will receive both the active drug and matched placebo, in a counterbalanced order, during two overnight study assessment visits, with at least a 1-week washout period between each visit. The primary outcomes are total sleep time and wake after sleep onset assessed via polysomnography. In addition, 256-channel high-density electroencephalography and source modelling using structural brain MRI will be used to comprehensively examine brain activation during sleep and wake periods on ETC120 versus placebo. Next-day cognitive function, alertness and simulated driving performance will also be investigated. Ethics and dissemination Ethics approval was received from Bellberry Human Research Ethics Committee (2018-04-284). The findings will be disseminated in a peer-reviewed open-access journal and at academic conferences. Trial registration number ANZCTRN12619000714189.

IntroductionInsomnia is a highly prevalent and costly condition that is associated with increased health risks and healthcare utilisation. Anecdotally, cannabis use is frequently reported by consumers to promote sleep. However, there is limited research on the effects of cannabis on sleep and daytime function in people with insomnia disorder using objective measures. This proof-of-concept study will evaluate the effects of a single dose of an oral cannabis-based medicine on sleep and daytime function in participants with chronic insomnia disorder.Methods and analysisA randomised, crossover, placebo-controlled, single-dose study design will be used to test the safety and efficacy of an oral oil solution (‘ETC120’) containing 10 mg Δ9-tetrahydrocannabinol (THC) and 200 mg cannabidiol (CBD) in 20 participants diagnosed with chronic insomnia disorder. Participants aged 35–60 years will be recruited over an 18-month period commencing August 2019. Each participant will receive both the active drug and matched placebo, in a counterbalanced order, during two overnight study assessment visits, with at least a 1-week washout period between each visit. The primary outcomes are total sleep time and wake after sleep onset assessed via polysomnography. In addition, 256-channel high-density electroencephalography and source modelling using structural brain MRI will be used to comprehensively examine brain activation during sleep and wake periods on ETC120 versus placebo. Next-day cognitive function, alertness and simulated driving performance will also be investigated.Ethics and disseminationEthics approval was received from Bellberry Human Research Ethics Committee (2018-04-284). The findings will be disseminated in a peer-reviewed open-access journal and at academic conferences.Trial registration numberANZCTRN12619000714189.

Insomnia is a major public health concern. Sleep restriction therapy (SRT) is an effective behavioral treatment but its delivery is impeded by a shortage of trained clinicians. We developed a mobile app delivering SRT to individuals with insomnia. This feasibility study employed a mixed-methods design to examine the engagement, acceptability, and potential efficacy of the mobile app. Fifteen participants diagnosed with insomnia disorder used the mobile app synchronized with a wearable device for 3 weeks. Those who persisted with the study (n = 12) found the mobile app to be highly acceptable and engaging, logging on average 19 nightly sleep diary entries across the 21 day period. Significant improvements were observed for sleep measures (insomnia severity and sleep efficiency) and daytime symptoms (fatigue and sleepiness). The results suggest that a mobile app delivering SRT to individuals with insomnia is engaging, acceptable, and potentially efficacious. Further, a full-scale effectiveness study is warranted.

Background Depression is common in patients with obstructive sleep apnea (OSA). Whether treating OSA with continuous positive airway pressure (CPAP) improves depressive symptoms remains inconclusive. We examined the impact of CPAP on depressive symptoms in OSA patients compared to sham CPAP. Methods A sub-analysis of two previous randomized sham-controlled trials was conducted. 126 male OSA patients (age = 51 ± 11 years; BMI = 32.0 ± 5.1 kg/m2; apnea hypopnea index = 42.4 ± 22.6 events/hour) were randomised either to therapeutic CPAP (n = 65) or sham CPAP (n = 61). Depressive symptoms were measured using the Depression, Anxiety and Stress Scale (DASS). The main outcome was the change in the DASS depression score (DASSD) after three months between the therapeutic and sham CPAP arms. Results The change in DASSD at three months did not differ between therapeutic and sham CPAP (mean difference: 0.5, 95% CI -3.6 to 4.6, p = 0.80). There was no significant between-group differences within the sub-groups of adherent users (device usage≥4hrs/day), or those with baseline depression (DASSD>9). In a secondary analysis of patients with baseline depression, adherent therapeutic CPAP use was associated with a greater reduction in DASSD scores compared to non-adherers (−10.0, 95% CI -18.3 to −1.8, p = 0.019). Conclusions: Overall, three months of CPAP did not significantly improve depression scores in OSA patients. Adherent use of therapeutic CPAP in patients with baseline depressive symptoms was associated with a reduction in symptom score. Future trials involving OSA patients with higher depressive symptoms will enable us to understand the complex interaction between OSA and depression.

Methods for predicting circadian phase have been developed for healthy individuals. It is unknown whether these methods generalize to clinical populations, such as delayed sleep–wake phase disorder (DSWPD), where circadian timing is associated with functional outcomes. This study evaluated two methods for predicting dim light melatonin onset (DLMO) in 154 DSWPD patients using ~ 7 days of sleep–wake and light data: a dynamic model and a statistical model. The dynamic model has been validated in healthy individuals under both laboratory and field conditions. The statistical model was developed for this dataset and used a multiple linear regression of light exposure during phase delay/advance portions of the phase response curve, as well as sleep timing and demographic variables. Both models performed comparably well in predicting DLMO. The dynamic model predicted DLMO with root mean square error of 68 min, with predictions accurate to within ± 1 h in 58% of participants and ± 2 h in 95%. The statistical model predicted DLMO with root mean square error of 57 min, with predictions accurate to within ± 1 h in 75% of participants and ± 2 h in 96%. We conclude that circadian phase prediction from light data is a viable technique for improving screening, diagnosis, and treatment of DSWPD.

Objective/Background: Sleep-wake disturbance is associated with poor cognitive functioning and several other adverse outcomes that increase dementia risk in older adults. Targeting sleep-wake distu...

Travel across time zones disrupts circadian rhythms causing increased daytime sleepiness, impaired alertness and sleep disturbance. However, the effect of repeated consecutive transmeridian travel on sleep-wake cycles and circadian dynamics is unknown. The aim of this study was to investigate changes in alertness, sleep-wake schedule and sleepiness and predict circadian and sleep dynamics of an individual undergoing demanding transmeridian travel. A 47-year-old healthy male flew 16 international flights over 12 consecutive days. He maintained a sleep-wake schedule based on Sydney, Australia time (GMT + 10 h). The participant completed a sleep diary and wore an Actiwatch before, during and after the flights. Subjective alertness, fatigue and sleepiness were rated 4 hourly (08:00-00:00), if awake during the flights. A validated physiologically based mathematical model of arousal dynamics was used to further explore the dynamics and compare sleep time predictions with observational data and to estimate circadian phase changes. The participant completed 191 h and 159 736 km of flying and traversed a total of 144 time-zones. Total sleep time during the flights decreased (357.5 min actigraphy; 292.4 min diary) compared to baseline (430.8 min actigraphy; 472.1 min diary), predominately due to restricted sleep opportunities. The daily range of alertness, sleepiness and fatigue increased compared to baseline, with heightened fatigue towards the end of the flight schedule. The arousal dynamics model predicted sleep/wake states during and post travel with 88% and 95% agreement with sleep diary data. The circadian phase predicted a delay of only 34 min over the 16 transmeridian flights. Despite repeated changes in transmeridian travel direction and flight duration, the participant was able to maintain a stable sleep schedule aligned with the Sydney night. Modelling revealed only minor circadian misalignment during the flying period. This was likely due to the transitory time spent in the overseas airports that did not allow for resynchronisation to the new time zone. The robustness of the arousal model in the real-world was demonstrated for the first time using unique transmeridian travel.

Research in sleep medicine over the last decades has involved a broad variety of sleep disorders in both men and women. Gender differences have been identified in sleep physiology as well as in the three most common sleep disorders: obstructive sleep apnoea (OSA), insomnia and restless legs syndrome (RLS). However, research on gender differences in sleep medicine appears limited. This clinical review aims to give an updated overview of gender differences, in relation to prevalence, clinical presentation, treatment and quality of life in OSA, insomnia and RLS. Future research directions in the adult population will also be discussed.

Objective This pilot trial aimed to test the effectiveness of integration of a wearable device with digital brief behavioural therapy for insomnia (dBBTi) on insomnia symptom severity, sleep metrics and therapy engagement. Participants and Methods One hundred and twenty-eight participants with insomnia symptoms were randomised to a 3-week dBBTi program with a wearable device enabling sleep data synchronization (dBBTi+wearable group; n = 62) or dBBTi alone (n = 66). We assessed the Insomnia Severity Index (ISI) and modified Pittsburgh Sleep Quality Index (PSQI; wake-after-sleep-onset (WASO), sleep-onset-latency (SOL), and total sleep time (TST)) at baseline and weeks 1, 2, 3, 6 and 12. Engagement was measured by the number of daily sleep diaries. Results There was no significant difference in ISI scores between the groups (d = 0.7, p = 0.061). The dBBTi+wearable group showed greater improvements in WASO (d = 0.8, p = 0.005) and TST (d = 0.3, p = 0.049) compared to the dBBTi group after 6 weeks. There was significantly greater engagement in the dBBTi+wearable group compared to the dBTi group (d =0.7, p = 0.010). Conclusions This pilot trial found that wearable device integration with a digital insomnia therapy led to improvements in WASO and TST and enhanced user engagement. We suggest that incorporation of adjunctive wearable technologies may improve digital insomnia therapy.

Introduction Digital health interventions (DHI) have the potential to address the unmet sleep health needs of patients in primary care. The current study explored primary care health providers’ attitudes and beliefs towards DHIs for sleep health and the implementation into practice. Methods A mixed-methods study was conducted in a convenience sample of primary care service providers (GPs, nurses, pharmacists). An online survey captured participants’ scope of practice and attitudes towards DHIs. Associations between practice factors and attributes of DHIs were explored. A subset of participants was interviewed to explore perceived barriers/facilitators for implementing DHIs into primary care, which was thematically analysed using the Framework Approach. Results 71 surveys were returned (GPs = 26, nurses = 21, pharmacists = 24) and 37 interviews were conducted (GPs = 13, nurses = 12, pharmacists = 12). Self-reported familiarity with DHIs was highest for GPs followed by pharmacists and nurses. Three major themes were identified: 1) Technology in Current Practice 2) Education Gaps and Training Needs and 3) Envisioning a Model of Care. Participants reported the “vague” definition of DHIs and mostly spoke in terms of personal experience and/or the health informatics systems used in practice. Despite recognising knowledge gaps, participants were confident in becoming upskilled and welcomed the idea of expanding digitalisation into sleep health. However, implementation success would depend on a supportive practice culture, patient uptake, and revising reimbursement structures. Conclusion With appropriate training and support, service providers highlighted the potential for embedding DHIs into primary care to optimise sleep health.

Introduction A previous high-density EEG investigation in OSA showed regional sleep EEG deficits particularly slow wave activity (SWA) in the parietal region. It is unclear whether CPAP treatment can reverse local sleep EEG abnormalities, and whether any recovery is related to improved cognitive function. Methods Fifteen males with moderate-severe OSA (age 50.4±6.5yrs, AHI 51.7±23.5/h) underwent polysomnography with 256-channel high-density EEG at baseline and following 3 months of CPAP. Tasks assessing cognitive performance and sleep-dependent memory were administered. Topographical spectral power maps were calculated for standard frequency ranges for sleep stages. Differences in normalized power between baseline and treatment were determined by statistical nonparametric mapping. Results In 11 CPAP compliant patients (data loss: intolerant of CPAP[n=3]/high-density EEG [n=1]), total sleep time did not change after CPAP but N1 (baseline vs. treatment: 66.9 vs. 39.5 mins, p=0.008) and N2 (195.0 vs. 150.6 mins, p=0.002) sleep was lower and N3 (89.8 vs. 128.7 mins, p=0.003) was higher. Topographic high-density EEG analysis revealed a regional increase in SWA (1–4.5Hz) during N3 sleep in a cluster of 22 electrodes overlying the parietal cortex (paired t-test, t(10)=-3.9, p=0.0029). The change in N3 SWA in the parietal cluster after CPAP was correlated with improved overnight procedural memory on the motor sequence task (rho=0.79, p=0.03) and better executive functioning (Stroop accuracy, rho=0.73, p=0.01). Conclusion CPAP treatment reduces localised deficits in sleep EEG, and specific regional recovery relates to short-term improvements in memory and executive function. These data also highlight the potential for long-term therapeutic effects on cognitive outcomes.

Objectives To compare overnight declarative memory consolidation and NREM sleep EEG oscillations in older adults with OSA to an age-matched control group, and to assess the quantitative sleep EEG features as correlates of memory consolidation. Methods 46 participants (24 without OSA and 22 patients with OSA) were recruited. Participants completed a word-paired associates declarative memory task before and after an 8-hour sleep opportunity with full polysomnography. Power spectral analysis was performed on all-night EEG recorded at frontal and central electrode sites. We calculated slow wave activity (slow oscillations absolute power 0.25–1 Hz; and delta EEG power (0.5–4.5 Hz) in NREM sleep. Slow spindle density (11–13 Hz, events p/min) and fast spindle density (13–16 Hz, events p/min) in stage N2 was derived using an automated spindle detection algorithm. Results Patients with OSA showed no significant differences in overnight memory recall and recognition compared to individuals without OSA. The OSA group showed reduced slow spindle density at the central region and fast spindle density at the frontal region relative to controls. No differences were observed in SWA. Within group correlations showed slow and fast spindle density were correlated to percent recognition in the control group. Conclusion Older adults with OSA had deficits in slow and fast sleep spindles compared to controls. OSA patients showed preserved sleep-dependent declarative memory consolidation despite sleep fragmentation and intermittent hypoxemia. Sleep spindles were positively correlated with overnight memory consolidation in controls but not OSA patients. Targeted interventions to boost spindles may enhance memory consolidation in older adults.

Background and aims Cannabis withdrawal is thought to be a major contributor to relapse to cannabis use and is now included in the DSM-5. Aerobic exercise relieves withdrawal symptoms from tobacco and other drugs, but has yet to be tested in cannabis users. Methods A prospective, single blind, parallel-group RCT comparing daily aerobic exercise to a control stretching intervention. Setting A seven-day inpatient hospital admission, with follow-up at 28 days’ post-discharge. Participants The study population will be 80 cannabis dependent adults seeking assistance with cannabis withdrawal. Intervention and comparator Participants in the Intervention group will undergo 35 min of aerobic exercise daily, at 60% of their VO2 Max, on an exercise bicycle. The Control group will participate in a structured non-aerobic daily stretching routine for 35 min daily. Both groups receive treatment as usual in the withdrawal management unit of the hospital. Measurements The primary outcome measure is the severity of cannabis withdrawal symptoms assessed daily using the Cannabis Withdrawal Scale and the Marijuana Cravings Questionnaire – pre and post exercise, across the week. Mechanisms by which exercise may affect cannabis withdrawal will be assessed by analysis of endogenous cannabinoids, and plasma and urine cannabinoid levels. Discussion This is the first RCT of aerobic exercise for cannabis dependence that has a valid control group to aid in interpretation of findings. Should the intervention prove effective, it would give empirical support to an inexpensive and accessible treatment approach for drug withdrawal management.

To evaluate changes in rates of family physician (FP) management of insomnia in Australia from 2000-2015.The Bettering the Evaluation And Care of Health (BEACH) program is a nationally representative cross-sectional survey of 1,000 newly randomly sampled family physicians' activity in Australia per year, who each record details of 100 consecutive patient encounters. This provided records of approximately 100,000 encounters each year. We identified all encounters with patients older than 15 years where insomnia or difficulty sleeping was managed and assessed trends in these encounters from 2000-2015.There was no change in the management rate of insomnia from 2000-2007 (1.54 per 100 encounters [95% confidence interval [CI]: 1.49-1.58]). This rate was lower from 2008-2015 (1.31 per 100 encounters [95% CI: 1.27-1.35]). There was no change in FP management: pharmacotherapy was used in approximately 90% of encounters; nonpharmacological advice was given at approximately 20%; and onward referral at approximately 1% of encounters. Prescription of temazepam changed from 54.6 [95% CI: 51.4-57.9] per 100 insomnia problems in 2000-2001 to 43.6 [95% CI: 40.1-47.0] in 2014-2015, whereas zolpidem increased steadily from introduction in 2000 to 14.6 [95% CI: 12.2-17.1] per 100 insomnia problems in 2006-2007, and then decreased to 7.3 [95% CI: 5.4-9.2] by 2014-2015.Insomnia management frequency decreased after 2007 in conjunction with ecologically associated Australian media reporting of adverse effects linked to zolpidem use. Australian FPs remain reliant on pharmacotherapy for the management of insomnia.

Using quantitative EEG (qEEG) analysis, we investigated sleep EEG microstructure as correlates of neurobehavioural performance after 24 h of extended wakefulness in untreated OSA.Eight male OSA patients underwent overnight polysomnography (PSG) at baseline followed by 40 h awake with repeated performance testing (psychomotor vigilance task [PVT] and AusEd driving simulator). EEG slowing during REM and spindle density during NREM sleep were calculated using power spectral analysis and a spindle detection algorithm at frontal and central electrode sites. Correlations between sleep EEG microstructure measures and performance after 24-h awake were assessed.Greater EEG slowing during REM sleep was associated with slower PVT reaction times (rho = - 0.79, p = 0.02), more PVT lapses (rho = 0.87, p = 0.005) and more AusEd crashes (rho = 0.73, p = 0.04). Decreased spindle density in NREM sleep was also associated with slower PVT reaction times (rho = 0.89, p = 0.007). Traditional PSG measures of disease severity were not consistent correlates of neurobehavioural performance in OSA.Sleep EEG microstructure measures recorded during routine PSG are associated with impaired vigilance in OSA patients after sleep deprivation.Quantitative brain oscillatory (or EEG)-based measures of sleep may better reflect the deleterious effects of untreated OSA than traditional PSG metrics in at-risk individuals. Trial Registration ACTRN12606000066583.

Effective treatment of obstructive sleep apnoea (OSA) is primarily determined by adherence to the selected intervention. The most common treatment pathways are mechanical devices such as continuous positive airway pressure (CPAP) or a mandibular advancement device, often combined with weight loss therapy. Weight reduction is usually an adjunct therapy but may be used as a secondary treatment in mild-to-moderate OSA when mechanical treatments cannot be tolerated. To enhance the uptake and adherence to treatment, clinicians may assess patient's personality profiles and psychological readiness. There is a paucity of evidence related to these aspects of patient care and this article outlines the current research in relation to patient presentation, treatment uptake and barriers, and methods to enhance treatment adherence.This article disseminates personality traits observed in patients with OSA and identifies vulnerable groups who may require additional support to increase treatment adherence. It summarises the current evidence for treatment barriers in patients with OSA. Low self-efficacy in relation to CPAP and weight loss adherence will be explored as well as the potential to predict treatment responders and enhance therapeutic uptake and adherence. Extending personality traits into research and clinical practice could potentially result in more successful CPAP therapy and weight loss treatment outcomes.

Background Mobile health (mHealth) apps demonstrate promise for improving sleep at scale. End-user engagement is a prerequisite for sustained use and effectiveness. Objective We assessed the needs and preferences of those with poor sleep and insomnia to inform the development of an engaging sleep app. Methods We triangulated results from qualitative (focus groups and app reviews) and quantitative (online survey) approaches. A total of 2 focus groups were conducted (N=9). An online survey tested themes identified from the focus groups against a larger population (N=167). In addition, we analyzed 434 user reviews of 6 mobile apps available on app stores. Results Common focus group themes included the need to account for diverse sleep phenotypes with an adaptive and tailored program, key app features (alarms and sleep diaries), the complex yet condescending nature of existing resources, providing rationale for information requested, and cost as a motivator. Most survey participants (156/167, 93%) would try an evidence-based sleep app. The most important app features reported were sleep diaries (148/167, 88%), sharing sleep data with a doctor (116/167, 70%), and lifestyle tracking (107/167, 64%). App reviews highlighted the alarm as the most salient app feature (43/122, 35%) and data synchronization with a wearable device (WD) as the most commonly mentioned functionality (40/135, 30%). Conclusions This co-design process involving end users through 3 methods consistently highlighted sleep tracking (through a diary and WD), alarms, and personalization as vital for engagement, although their implementation was commonly criticized in review. Engagement is negatively affected by poorly designed features, bugs, and didactic information which must be addressed. Other needs depend upon the type of user, for example, those with severe insomnia.

Chronic insomnia is associated with subjective daytime cognitive dysfunction, but objective corroborative data are often lacking. In this study, we use Perceptual Load Theory to objectively assess distractibility in participants with insomnia ( N = 23) compared with age- and sex-matched controls ( N = 23). Following overnight supervised sleep observation, all participants completed a selective attention task which varied in the level of perceptual load and distractor congruency. The insomnia group was found to be more distracted than controls, whereas their selective attention mechanism appeared to be intact, with reduced distractor processing under high load for both groups. Insomnia symptom severity was positively correlated with participant distractibility. These findings suggest that there are insomnia-related daytime cognitive impairments that are likely to arise from compromised cognitive control rather than an ineffective selective attention mechanism. This task may be clinically useful in assessing daytime impairments, and potentially treatment response, in those with insomnia.

Background and aims The prevalence of chronic benzodiazepine use in primary care settings remains high despite clear evidence of adverse health outcomes resulting from long‐term use and the availability of effective alternative behavioural therapies. Eliciting factors influencing past or current usage experience of benzodiazepine users and their future behavioural intention regarding discontinuation or alternative behavioural therapy adoption could be useful in developing informed strategies facilitating successful benzodiazepine withdrawal in long‐term users. The aim of this study was to identify patient factors influencing their current long‐term benzodiazepine use, past withdrawal attempt, and future intention to trial safer alternative behavioural therapies. Additionally, the study also aimed to explore patients' preference for information sources on behavioural therapies. Methods Point of purchase surveys were conducted with patients obtaining benzodiazepines from selected pharmacies across New South Wales (NSW), Australia. Survey items included the Beliefs about Medicines Questionnaire (BMQ‐specific), questions about patient's sociodemographic characteristics, as well as their views about long‐term benzodiazepine use and behavioural therapies. Results Seventy‐five patients were recruited from 12 pharmacies across New South Wales (NSW). The surveys were conducted from November 2016 to July 2017. The mean (±SD) age of the participants was 54.3 (±16.7) with a range of 23 to 86 years, and 67% of the participants had been using the benzodiazepine for at least 1 year. Lower‐education levels, stronger beliefs about the necessity of use, and lower concerns about ongoing benzodiazepine use were significantly associated with prolonged use. Sixty‐four percent of the participants were not interested in behavioural therapies, and there was a significant relationship between the participants' future preference for behavioural therapies and their concerns about the potential adverse effects of benzodiazepines. A majority of the participants rated general practitioners (GPs) as their first choice and pharmacists as the second choice for discussing behavioural therapies. Conclusions Specific individual sociodemographic characteristics of benzodiazepine users and their medication‐related beliefs influence their current benzodiazepine usage and future intention to trial behavioural therapies as an alternative to their benzodiazepines. Based on the reported preferences of benzodiazepine users in this study, developing and evaluating GP‐pharmacist collaborative services to improve the uptake of behavioural therapies as an alternative to benzodiazepines can be recommended.