Delwyn J. Bartlett

Sleep health New South Wales: chronic sleep restriction and daytime sleepiness

Aims: The aim of this study was to provide the first population‐based descriptions of typical sleep duration and the prevalence of chronic sleep restriction and chronic sleepiness in community‐dwelling Australian adults.

Adolescent Sleep Patterns and Night-Time Technology Use: Results of the Australian Broadcasting Corporation's Big Sleep Survey

Introduction Electronic devices in the bedroom are broadly linked with poor sleep in adolescents. This study investigated whether there is a dose-response relationship between use of electronic devices (computers, cellphones, televisions and radios) in bed prior to sleep and adolescent sleep patterns. Methods Adolescents aged 11–17 yrs (n = 1,184; 67.6% female) completed an Australia-wide internet survey that examined sleep patterns, sleepiness, sleep disorders, the presence of electronic devices in the bedroom and frequency of use in bed at night. Results Over 70% of adolescents reported 2 or more electronic devices in their bedroom at night. Use of devices in bed a few nights per week or more was 46.8% cellphone, 38.5% computer, 23.2% TV, and 15.8% radio. Device use had dose-dependent associations with later sleep onset on weekdays (highest-dose computer adjOR  = 3.75: 99% CI  = 2.17–6.46; cellphone 2.29: 1.22–4.30) and weekends (computer 3.68: 2.14–6.32; cellphone 3.24: 1.70–6.19; TV 2.32: 1.30–4.14), and later waking on weekdays (computer 2.08: 1.25–3.44; TV 2.31: 1.33–4.02) and weekends (computer 1.99: 1.21–3.26; cellphone 2.33: 1.33–4.08; TV 2.04: 1.18–3.55). Only ‘almost every night’ computer use (: 2.43: 1.45–4.08) was associated with short weekday sleep duration, and only ‘almost every night’ cellphone use (2.23: 1.26–3.94) was associated with wake lag (waking later on weekends). Conclusions Use of computers, cell-phones and televisions at higher doses was associated with delayed sleep/wake schedules and wake lag, potentially impairing health and educational outcomes.

The utility of the AusEd driving simulator in the clinical assessment of driver fatigue

Several driving simulators have been developed which range in complexity from PC based driving tasks to advanced “real world” simulators. The AusEd® driving simulator is a PC based task, which was designed to be conducive to and test for driver fatigue. This paper describes the AusEd driving simulator in detail, including the technical requirements, hardware, screen and file outputs, and analysis software. Some aspects of the test are standardized, while others can be modified to suit the experimental situation. The AusEd driving simulator is sensitive to performance decrement from driver fatigue in the laboratory setting, potentially making it useful as a laboratory or office based test for driver fatigue risk management. However, more research is still needed to correlate laboratory based simulator performance with real world driving performance and outcomes.

The Bidirectional Relationship Between Pain Intensity and Sleep Disturbance/Quality in Patients with Low Back Pain

Objectives:This study investigated the bidirectional relationship between the intensity of low back pain (LBP) and sleep disturbance. Further, the study aimed to determine whether any relationship is dependent on pain duration, symptoms of depression and anxiety, and the method of sleep assessment (subjective vs. objective). Materials and Methods:Eighty patients with LBP completed a sleep diary. A subgroup of 50 patients additionally wore an electronic device (Armband) to measure sleep for 7 consecutive days. Pain intensity was assessed twice daily using a sleep diary. Depression and anxiety symptoms were assessed at baseline using the Depression Anxiety Stress Scale questionnaire. Generalized estimating equations (GEE) with an exchangeable correlation structure were used to examine the relationship between day-time pain intensity and sleep. Results:The GEE analysis showed that a night of poor sleep quality, difficulty falling sleep (assessed by the sleep diary), waking after sleep onset, and low sleep efficiency (assessed by the sleep diary and Armband) were followed by a day with higher pain intensity. Further, a day with higher pain intensity was associated with a decrease in the subsequent night’s sleep quality, an increase in sleep latency (assessed by the sleep diary), waking after sleep onset (assessed by both measures), and low sleep efficiency (assessed by the Armband). Discussion:The findings demonstrate that there is a bidirectional relationship between sleep and pain intensity in patients with LBP. The relationship is independent of pain duration and baseline symptoms of depression and anxiety and somewhat dependent on the method of sleep measurement (sleep diary or Armband). Future research is needed to determine whether targeting sleep improvement in patients with LBP contributes to pain reduction.

Detecting insomnia in patients with low back pain: accuracy of four self-report sleep measures

BackgroundAlthough insomnia is common in patients with low back pain (LBP), it is unknown whether commonly used self-report sleep measures are sufficiently accurate to screen for insomnia in the LBP population. This study investigated the discriminatory properties of the Pittsburgh Sleep Quality Index (Pittsburgh questionnaire), Insomnia Severity Index (Insomnia index), Epworth Sleepiness Scale (Epworth scale) and the sleep item of the Roland and Morris Disability Questionnaire (Roland item) to detect insomnia in patients with LBP by comparing their accuracy to detect insomnia to a sleep diary. The study also aimed to determine the clinical optimal cut-off scores of the questionnaires to detect insomnia in the LBP population.MethodsSeventy nine patients with LBP completed the four self-reported questionnaires and a sleep diary for 7 consecutive nights. The accuracy of the questionnaires was evaluated using Receiver Operator Characteristic (ROC) curves with the Area Under the Curve (AUC) used to examine each test’s accuracy to discriminate participants with insomnia from those without insomnia.ResultsThe Pittsburgh questionnaire and Insomnia index had moderate accuracy to detect insomnia (AUC = 0.79, 95% CI = 0.68 to 0.87 and AUC = 0.78, 95% CI = 0.67 to 0.86 respectively), whereas the Epworth scale and the Roland item were not found to be accurate discriminators (AUC = 0.53, 95% CI = 0. 41 to 0.64 and AUC = 0.64, 95% CI = 0.53 to 0.75 respectively). The cut-off score of > 6 for the Pittsburgh questionnaire and the cut-off point of > 14 for the Insomnia index provided optimal sensitivity and specificity for the detection of insomnia.ConclusionsThe Pittsburgh questionnaire and Insomnia index had similar ability to screen for insomnia in patients with low back pain.

Integrating psychology and medicine in CPAP adherence – New concepts?

To date, continuous positive airway pressure (CPAP) is the most effective intervention in the treatment of obstructive sleep apnoea, but adherence to this treatment is often less than optimal. A variety of factors and interventions that influence and improve CPAP use have been examined. There is increasing recognition of the multifaceted nature of CPAP adherence: the patients psychological profile and social environment have been recognised, in addition to the more extensively researched patients treatment and physiological profile. Understanding how these multiple factors impact on CPAP use in an integrative fashion might provide us with a useful holistic model of CPAP adherence. This concept of integration--a biopsychosocial (BPS) approach to health and illness--has previously been described to understand care provision for various chronic health disorders. This paper proposes an adherence framework, whereby variables integrally affect CPAP use. The BPS model has been considered for nearly 35 years; the presence of poor CPAP adherence was acknowledged in the early 1990s--it is timely to incorporate this approach into our care pathway of CPAP users.

Increasing Adherence to Obstructive Sleep Apnea Treatment with a Group Social Cognitive Therapy Treatment Intervention: A Randomized Trial

OBJECTIVE To examine whether a social cognitive therapy (SCT) intervention increases continuous positive airway pressure (CPAP) use compared to equivalent social interaction (SI) time. PARTICIPANTS Individuals with obstructive sleep apnea (OSA) referred for CPAP therapy. INTERVENTION Participants received a 30-min group education session regarding OSA and CPAP. Groups of three to four participants were then randomly assigned to an SCT session or social interaction. MEASUREMENTS CPAP usage was assessed at 7 nights, then 1, 3, and 6 months. The two primary outcomes were adherence, usage ≥ 4 h per night at 6 months, and uptake of CPAP. Questionnaires were given pretreatment and posttreatment. RESULTS Two hundred six individuals were randomized to SI (n = 97) or SCT (n = 109). CPAP uptake was not different between groups (82% in SI, 88% in SCT groups, P = 0.35). There were no differences between groups in adherence: 63-66% at 1 week, and at 6 months 55-47% (P = 0.36). Higher pretreatment apnea-hypopnea index, higher baseline self-efficacy, and use of CPAP (≥ 4 h) at 1 week were independent predictors of CPAP adherence at 6 months. CPAP adherence increased by a factor of 1.8 (odds ratio = 1.8, 95% confidence interval 1.1-3.0) for every one-unit increase in self-efficacy. There was no difference between groups postintervention in self-efficacy scores, sleepiness, mood, or sleep quality. CONCLUSIONS In this randomized trial, a single SCT application did not increase adherence when compared with SI time. Although self-efficacy scores prior to CPAP predicted adherence, self-efficacy was not increased by the interventions. Increasing intensity and understanding of SCT interventions may be needed to improve CPAP adherence. CLINICAL TRIALS REGISTRATION Australian New Zealand Clinical Trials Registry, ACTRN12607000424404.

A new EEG biomarker of neurobehavioural impairment and sleepiness in sleep apnea patients and controls during extended wakefulness.

OBJECTIVE To explore the use of detrended fluctuation analysis (DFA) scaling exponent of the awake electroencephalogram (EEG) as a new alternative biomarker of neurobehavioural impairment and sleepiness in obstructive sleep apnea (OSA). METHODS Eight patients with moderate-severe OSA and nine non-OSA controls underwent a 40-h extended wakefulness challenge with resting awake EEG, neurobehavioural performance (driving simulator and psychomotor vigilance task) and subjective sleepiness recorded every 2-h. The DFA scaling exponent and power spectra of the EEG were calculated at each time point and their correlation with sleepiness and performance were quantified. RESULTS DFA scaling exponent and power spectra biomarkers significantly correlated with simultaneously tested performance and self-rated sleepiness across the testing period in OSA patients and controls. Baseline (8am) DFA scaling exponent but not power spectra were markers of impaired simulated driving after 24-h extended wakefulness in OSA (r=0.738, p=0.037). OSA patients had a higher scaling exponent and delta power during wakefulness than controls. CONCLUSIONS The DFA scaling exponent of the awake EEG performed as well as conventional power spectra as a marker of impaired performance and sleepiness resulting from sleep loss. SIGNIFICANCE DFA may potentially identify patients at risk of neurobehavioural impairment and assess treatment effectiveness.

BRAIN FUNCTION IN OBSTRUCTIVE SLEEP APNEA: RESULTS FROM THE BRAIN RESOURCE INTERNATIONAL DATABASE

Obstructive sleep apnea (OSA) is expected to impair vigilance and executive functioning, owing to the sensitivity of the prefrontal cortex to the effects of sleep fragmentation and intermittent hypoxia. Studies examining the pattern of cognitive dysfunction show variable results, with the heterogeneity in part due to small sample sizes in current studies and little consistency of the tests used. We examined a group of fifty subjects from the Brain Resource International Database (BRID), predicted to have OSA on the basis of the Multivariable Apnea Prediction Index, and compared them with 200 matched controls. On electrophysiological tests, the OSA group showed reduced eyes closed alpha power, increased auditory oddball N100 and P200 amplitude, but reduced N200 and P300 amplitude. The latency to P300 was not significantly different between groups, but latencies to N200 and P200 were prolonged in the OSA group. Performance testing of the executive function found that verbal interference and the switching of attention were impaired in the OSA group. We have demonstrated that a diagnostic algorithm based on apnea symptoms and demographic factors can be used to select a group with likely OSA manifesting deficits in information processing and executive function.

The effect of continuous positive airway pressure usage on sleepiness in obstructive sleep apnoea: real effects or expectation of benefit?

Rationale Placebo responses are complex psychobiological phenomena and often involve patient expectation of benefit. With continuous positive airway pressure (CPAP) treatment of obstructive sleep apnoea, greater hours of CPAP use are associated with reduced sleepiness. However, these open-label studies have not controlled for patient expectation of benefit derived from their knowledge of hours of device use. Objectives To investigate the relative effectiveness of the use of real or placebo CPAP on daytime sleepiness. Methods Patient-level meta-analysis combining data on sleepiness measured by the Epworth Sleepiness Scale from three randomised placebo-controlled crossover trials. Mixed model analysis of variance was used to quantify the effects of real versus placebo device treatment, usage, their interaction and regression to the mean. Measurements and main results Duration of real and placebo CPAP use was correlated within patients (r=0.53, p<0.001). High use of real CPAP reduced sleepiness more than high use of placebo (difference 3.0 points; 95% CI 1.7 to 4.3, p<0.001) and more than low use of real CPAP (difference 3.3; 95% CI 1.9 to 4.7, p<0.0001). High use of placebo was superior to low use of placebo (difference 1.5; 95% CI 0.1 to 2.8, p=0.03). Twenty-nine per cent of the effect of high usage of CPAP (4.2 points; 95% CI 3.3 to 5.1) was explained by the expectation of benefit effect associated with high use of placebo (1.2 points ; 95% CI 0.2 to 2.3). Conclusions A clinically significant proportion of the effectiveness of high CPAP use in reducing sleepiness is probably caused by patient expectation of benefit.