Subjective–objective sleep discrepancy in patients with insomnia during and after cognitive behavioural therapy: An actigraphy study

Although patients with insomnia often show a discrepancy between self‐reported and objective sleep parameters, the role of and change in this phenomenon during treatment remain unclear. The present study aimed to assess the effect of cognitive behavioural therapy for insomnia on subjective and objective sleep discrepancy of total sleep time, sleep‐onset latency and wake after sleep onset. The total sleep time discrepancy was also assessed across the entire therapy. The second aim was to examine the treatment outcome of two insomnia groups differing in sleep perception. Thirty‐six adults with insomnia (mean age = 46.7 years, SD = 13.9; 22 females) were enrolled in the final analyses. Patients underwent a 6‐week group cognitive behavioural therapy for insomnia programme. Sleep diary and actigraphy measurements were obtained during the therapy. Patients who underestimated total sleep time (n = 16; underestimating group) were compared with patients who accurately perceived or overestimated total sleep time (n = 20; accurate/overestimating group). After cognitive behavioural therapy for insomnia, a significant decrease of total sleep time and sleep‐onset latency discrepancy was observed without a change in wake after sleep onset discrepancy in the total sample. Only the underestimating group reported decreased sleep‐onset latency discrepancy after the treatment, whereas total sleep time discrepancy significantly changed in both groups. The underestimating group showed a significant decrease of total sleep time discrepancy from Week 1 to Week 2 when the sleep restriction was implemented, whereas the accurate/overestimating group showed the first significant change at Week 4. In conclusion, both groups differing in sleep perception responded similarly to cognitive behavioural therapy for insomnia, although different In conclusion, both groups differing in sleep perception responded similarly to cognitive behavioural therapy for insomnia, although different therapeutic components could play important roles in each group. components could play important roles in each group.     

The subjective–objective mismatch in sleep perception among those with insomnia and sleep apnea

The diagnosis and management of insomnia relies primarily on clinical history. However, patient self‐report of sleep–wake times may not agree with objective measurements. We hypothesized that those with shallow or fragmented sleep would under‐report sleep quantity, and that this might account for some of the mismatch. We compared objective and subjective sleep–wake times for 277 patients who underwent diagnostic polysomnography. The group included those with insomnia symptoms (n = 92), obstructive sleep apnea (n = 66) or both (n = 119). Mismatch of wake duration was context dependent: all three groups overestimated sleep latency but underestimated wakefulness after sleep onset. The insomnia group underestimated total sleep time by a median of 81 min. However, contrary to our hypothesis, measures of fragmentation (N1, arousal index, sleep efficiency, etc.) did not correlate with the subjective sleep duration estimates. To unmask a potential relationship between sleep architecture and subjective duration, we tested three hypotheses: N1 is perceived as wake; sleep bouts under 10 min are perceived as wake; or N1 and N2 are perceived in a weighted fashion. None of these hypotheses exposed a match between subjective and objective sleep duration. We show only modest performance of a Naïve Bayes Classifier algorithm for predicting mismatch using clinical and polysomnographic variables. Subjective–objective mismatch is common in patients reporting insomnia symptoms. We conclude that mismatch was not attributable to commonly measured polysomnographic measures of fragmentation. Further insight is needed into the complex relationships between subjective perception of sleep and conventional, objective measurements.     

The wrist is not the brain: Estimation of sleep by clinical and consumer wearable actigraphy devices is impacted by multiple patient‐ and device‐specific factors

Clinical actigraphy devices provide adequate estimates of some sleep measures across large groups. In practice, providers are asked to apply clinical or consumer wearable data to individual patient assessments. Inter‐individual variability in device performance will impact such patient‐specific interpretation. We assessed two devices, clinical and consumer, to determine the magnitude and predictors of this individual‐level variability. One hundred and two patients (55 [53.9%] female; 56.4 [±16.3] years old) undergoing polysomnography wore Jawbone UP3 and/or Actiwatch2. Device total sleep time, sleep efficiency, wake after sleep onset and sleep latency were compared with polysomnography. Demographics, sleep architecture and clinical measures were compared to device performance. Actiwatch overestimated total sleep time by 27.2 min (95% confidence limits [CL], 138.3 min over to 84.0 under), overestimated sleep efficiency by 6.8% (95% CL, 34.1% over to 20.5% under), overestimated sleep onset latency by 2.6 min (95% CL, 63.3 over to 58.2 under) and underestimated wake after sleep onset by 50.7 min (95% CL, 162.5 under to 61.2 over). Jawbone overestimated total sleep time by 59.1 min (95% CL, 208.6 min over to 90.5 under) and overestimated sleep efficiency by 14.9% (95% CL, 52.6% over to 22.7% under). In multivariate models, age, sleep onset latency, wake after sleep onset, % N1 and apnea–hypopnea index explained only some of the variance in device performance. Gender also affected performance. Actiwatch and Jawbone mis‐estimate sleep measures with very wide confidence limits and accuracy varies with multiple patient‐level characteristics. Given these large individual inaccuracies, data from these devices must be applied only with extreme caution in clinical practice.     

Actigraphy‐assessed sleep during school and vacation periods: a naturalistic study of restricted and extended sleep opportunities in adolescents

School‐related sleep restriction in adolescents has been identified by studies comparing weekday and weekend sleep. This study compared weekday and vacation sleep to assess restricted and extended sleep opportunities. One‐hundred and forty‐six adolescents (47.3% male) aged 16.2 ± 1.0 years (M ± SD) from the general community wore an actigraph continuously for 4 weeks: the last week of a school term (Time‐E), the following 2‐week vacation, and the first week of the next term. Self‐reported sleep was assessed for each of the three time intervals, and chronotype was assessed using the Morningness–Eveningness Questionnaire at Time‐E. Daily actigraphy bedtime, rise‐time, time‐in‐bed, total sleep time, sleep onset latency, sleep efficiency, and % wake after sleep onset were analysed using latent growth curve modelling. The removal of school‐related sleep restriction was associated with an abrupt delay in sleep timing and increase in sleep duration. Subsequently, bedtime and rise‐time showed further linear delays throughout the vacation, while changes in time‐in‐bed were non‐significant. Sleep onset latency increased linearly, peaking in the middle of the second vacation week. Across the first vacation week, total sleep time and sleep efficiency linearly decreased, while % wake after sleep onset increased. These changes stabilized during the second vacation week. Older age and eveningness were associated with later bedtime and rise‐time, whilst females had longer time‐in‐bed, total sleep time and sleep onset latency. Compared with school days, sleep during the vacation was characterized by later timing, longer duration, lower quality and greater variability. Recovery from school‐related sleep restriction appeared to be completed within the 2 weeks of naturalistic extended sleep.     

Chronic stress undermines the compensatory sleep efficiency increase in response to sleep restriction in adolescents

To investigate the effects of real‐life stress on the sleep of adolescents, we performed a repeated‐measures study on actigraphic sleep estimates and subjective measures during one regular school week, two stressful examination weeks and a week's holiday. Twenty‐four adolescents aged 17.63 ± 0.10 years (mean ± standard error of the mean) wore actigraphs and completed diaries on subjective stress, fatigue, sleep quality, number of examinations and consumption of caffeine and alcohol for 4 weeks during their final year of secondary school. The resulting almost 500 assessments were analysed using mixed‐effect models to estimate the effects of mere school attendance and additional examination stress on sleep estimates and subjective ratings. Total sleep time decreased from 7:38 h ± 12 min during holidays to 6:40 h ± 12 min during a regular school week. This 13% decrease elicited a partial compensation, as indicated by a 3% increase in sleep efficiency and a 6% decrease in the duration of nocturnal awakenings. During examination weeks total sleep time decreased to 6:23 h ± 8 min, but it was now accompanied by a decrease in sleep efficiency and subjective sleep quality and an increase in wake bout duration. In conclusion, school examination stress affects the sleep of adolescents. The compensatory mechanism of more consolidated sleep, as elicited by the sleep restriction associated with mere school attendance, collapsed during 2 weeks of sustained examination stress.     

Recovery sleep and performance following sleep deprivation with dextroamphetamine

Twelve subjects were studied to determine the after-effects of using three 10-mg doses of dextroamphetamine to sustain alertness during sleep deprivation. Sleep architecture during recovery sleep was evaluated by comparing post-deprivation sleep beginning 15 h after the last dextroamphetamine dose to post-deprivation sleep after placebo. Performance and mood recovery were assessed by comparing volunteers who received dextroamphetamine first (during sleep deprivation) to those who received placebo first. Stages 1 and 2 sleep, movement time, REM latency, and sleep latency increased on the night after sleep deprivation with dextroamphetamine vs. placebo. Stage 4 was unaffected. Comparisons to baseline revealed more stage 1 during baseline than during either post-deprivation sleep period and more stage 2 during baseline than during sleep following placebo. Stage 4 sleep was lower during baseline than it was after either dose, and REM sleep was lower during baseline and after dextroamphetamine than after placebo. Sleep onset was slowest on the baseline night. Next-day performance and mood were not different as a function of whether subjects received dextroamphetamine or placebo during deprivation. These data suggest dextroamphetamine alters post-deprivation sleep architecture when used to sustain alertness during acute sleep loss, but next-day performance and subjective mood ratings are not substantially affected. A recovery sleep period of only 8 h appears to be adequate to regain baseline performance levels after short-term sleep deprivation.     

Validity,potential clinical utility,and comparison of consumer and research‐grade activity trackers in Insomnia Disorder I: In‐lab validation against polysomnography

Consumer activity trackers claiming to measure sleep/wake patterns are ubiquitous within clinical and consumer settings. However, validation of these devices in sleep disorder populations are lacking. We examined 1 night of sleep in 42 individuals with insomnia (mean = 49.14 ± 17.54 years) using polysomnography, a wrist actigraph (Actiwatch Spectrum Pro: AWS) and a consumer activity tracker (Fitbit Alta HR: FBA). Epoch‐by‐epoch analysis and Bland?Altman methods evaluated each device against polysomnography for sleep/wake detection, total sleep time, sleep efficiency, wake after sleep onset and sleep latency. FBA sleep stage classification of light sleep (N1 + N2), deep sleep (N3) and rapid eye movement was also compared with polysomnography. Compared with polysomnography, both activity trackers displayed high accuracy (81.12% versus 82.80%, AWS and FBA respectively; ns) and sensitivity (sleep detection; 96.66% versus 96.04%, respectively; ns) but low specificity (wake detection; 39.09% versus 44.76%, respectively; p = .037). Both trackers overestimated total sleep time and sleep efficiency, and underestimated sleep latency and wake after sleep onset. FBA demonstrated sleep stage sensitivity and specificity, respectively, of 79.39% and 58.77% (light), 49.04% and 95.54% (deep), 65.97% and 91.53% (rapid eye movement). Both devices were more accurate in detecting sleep than wake, with equivalent sensitivity, but statistically different specificity. FBA provided equivalent estimates as AWS for all traditional actigraphy sleep parameters. FBA also showed high specificity when identifying N3, and rapid eye movement, though sensitivity was modest. Thus, it underestimates these sleep stages and overestimates light sleep, demonstrating more shallow sleep than actually obtained. Whether FBA could serve as a low‐cost substitute for actigraphy in insomnia requires further investigation.     

Morningness/eveningness and the need for sleep

The purpose of this study was to determine, in a large sample of adults of all ages (17-80 years), the effect of morningness/eveningness on sleep/wake schedules, sleep needs, sleep hygiene and subjective daytime somnolence. A total of 617 subjects (219 subjects per chronotype group) matched for age, sex and employment status, completed an abridged morningness/eveningness questionnaire, a questionnaire on sleep habits and the quality of sleep, and the Epworth Sleepiness Scale. Eveningness was associated with a greater need for sleep, less time in bed during the week compared to ideal sleep needs, more time in bed at the weekend, a later bedtime and waking-up time especially at the weekend, more irregular sleep/wake habits and greater caffeine consumption. These subjects built up a sleep debt during the week and extended their duration of sleep at the weekend. They did not, however, rate themselves more sleepy than other types, despite the fact that our results showed a clear link between subjectively evaluated daytime somnolence and sleep debt. Why they were less affected by sleep deprivation is not clear. This raises the question of individual susceptibility to the modification of sleep parameters.     

Comparison of subjective and objective assessments of sleep in healthy older subjects without sleep complaints

Older adults have reduced sleep quality compared with younger adults when sleeping at habitual times and greater sleep disruption when their sleep is at adverse times. The purpose of this analysis was to investigate how subjective measures of sleep relate to objectively recorded sleep in older subjects scheduled to sleep at all times of day. We analyzed data from 24 healthy older (55–74 years) subjects who took part in a 32-day inpatient study where polysomnography was recorded each night and subjective sleep was assessed after each scheduled wake time. The study included baseline nights and a forced desynchrony (FD) protocol when the subjects lived on a 20-h rest activity schedule. Our postsleep questionnaire both included quantitative and qualitative questions about the prior sleep. Under baseline and FD conditions, objective and subjective sleep latency were correlated, subjective sleep duration was related to slow-wave sleep and wake after sleep onset, subjective sleep quality was related to stage 1 and 2 sleep, and sleepiness and refreshment at wake time were related to duration of premature awakening. During FD, most measures of objective and subjective sleep varied with circadian phase and many additional correlations between objective and subjective sleep were present. Our findings show that when sleeping at habitual times, these healthy older subjects did not perceive their generally poor sleep quality, but under FD conditions where sleep quality changed from day-to-day their subjective sleep ratings were more associated with their objective sleep.     

The ability to self‐monitor cognitive performance during 60 h total sleep deprivation and following 2 nights recovery sleep

We aimed to investigate whether self‐monitoring of performance is altered during 60 h of total sleep deprivation, following 2 nights of recovery sleep, and by task difficulty and/or subjective sleepiness. Forty adults (22 females, aged 19–39 years) underwent a 5‐day protocol, with a well‐rested day, 66 h total sleep deprivation (last test session at 60 h), and 2 nights of 8 h recovery sleep. An arithmetic task (MATH) with three difficulty levels assessed working memory. The Psychomotor Vigilance Task assessed sustained attention. Arithmetic accuracy and Psychomotor Vigilance Task median reaction time measured objective performance. Subjective performance was measured with self‐reported accuracy and speed. Objective–subjective differences assessed self‐monitoring ability. The performance on both tasks declined during total sleep deprivation and improved following recovery. During total sleep deprivation, participants accurately self‐monitored performance on the Psychomotor Vigilance Task; however, they overestimated cognitive deficits on MATH, self‐reporting performance as worse than actually observed. Following recovery, participants overestimated the extent of performance improvement on the Psychomotor Vigilance Task. Task difficulty influenced self‐monitoring ability, with greater overestimation of performance deficits during total sleep deprivation as difficulty increased. Subjective sleepiness predicted subjective performance ratings at several time points, only for the Psychomotor Vigilance Task. The ability to self‐monitor performance was impaired during total sleep deprivation for working memory and after recovery sleep for the Psychomotor Vigilance Task, but was otherwise accurate. The development of self‐monitoring strategies, assessing both subjective perceptions of performance and subjective sleepiness, within operational contexts may help reduce the consequences of sleep‐related impairments.     

Lengthening of the photoperiod influences sleep characteristics before and during total sleep deprivation in rat

The photoperiod has been evidenced to influence sleep regulation in the rat. Nevertheless, lengthening of the photoperiod beyond 30 days seems to have little effect on the 24‐hr baseline level of sleep and the response to total sleep deprivation. We studied the effects of 12:12 (habitual) and 16:8 (long) light–dark photoperiods on sleep, locomotor activity and body core temperature, before and after 24 hr of total sleep deprivation. Eight rats were submitted for 14 days to light–dark 12:12 (lights on: 08:00 hours–20:00 hours) followed by total sleep deprivation, and then for 14 days to light–dark 16:8 (light extended to 24:00 hours) followed by total sleep deprivation. Rats were simultaneously recorded for electroencephalogram, locomotor activity and body core temperature for 24 hr before and after total sleep deprivation. At baseline before total sleep deprivation, total sleep time and non‐rapid eye movement sleep per 24 hr and during extended light hours (20:00 hours–24:00 hours) were higher (13% for total sleep time) after light–dark exposure compared with habitual photoperiod, while percentage delta power in non‐rapid eye movements and rapid eye movements were unchanged. Locomotor activity and body core temperature were lower, particularly during extended light hours (20:00 hours–24:00 hours). Following total sleep deprivation, total sleep time and non‐rapid eye movements were significantly lower after long photoperiod between 20:00 hours and 24:00 hours, and between 10:00 hours and 12:00 hours, and unchanged per 24 hr. The percentage delta power in non‐rapid eye movements was lower between 08:00 hours and 11:00 hours. Total sleep deprivation decreased locomotor activity and body core temperature after habitual photoperiod exposure only. Fourteen days under long photoperiod (light–dark 16:8) increased non‐rapid eye movements sleep, and decreased sleep rebound related to total sleep deprivation (lower non‐rapid eye movements duration and delta power). This may create a model of sleep extension for the rat that has been found to favour anabolism in the brain and the periphery.     

Endothelial function and sleep: associations of flow‐mediated dilation with perceived sleep quality and rapid eye movement (REM) sleep

Endothelial function typically precedes clinical manifestations of cardiovascular disease and provides a potential mechanism for the associations observed between cardiovascular disease and sleep quality. This study examined how subjective and objective indicators of sleep quality relate to endothelial function, as measured by brachial artery flow‐mediated dilation (FMD). In a clinical research centre, 100 non‐shift working adults (mean age: 36 years) completed FMD testing and the Pittsburgh Sleep Quality Index, along with a polysomnography assessment to obtain the following measures: slow wave sleep, percentage rapid eye movement (REM) sleep, REM sleep latency, total arousal index, total sleep time, wake after sleep onset, sleep efficiency and apnea–hypopnea index. Bivariate correlations and follow‐up multiple regressions examined how FMD related to subjective (i.e. Pittsburgh Sleep Quality Index scores) and objective (i.e. polysomnography‐derived) indicators of sleep quality. After FMD showed bivariate correlations with Pittsburgh Sleep Quality Index scores, percentage REM sleep and REM latency, further examination with separate regression models indicated that these associations remained significant after adjustments for sex, age, race, hypertension, body mass index, apnea–hypopnea index, smoking and income (Ps < 0.05). Specifically, as FMD decreased, scores on the Pittsburgh Sleep Quality Index increased (indicating decreased subjective sleep quality) and percentage REM sleep decreased, while REM sleep latency increased (Ps < 0.05). Poorer subjective sleep quality and adverse changes in REM sleep were associated with diminished vasodilation, which could link sleep disturbances to cardiovascular disease.     

Self‐reported sleep quantity,quality and sleep hygiene in elite athletes

Sleep is essential for recovery and performance in elite athletes. While actigraphy‐based studies revealed suboptimal sleep in athletes, information on their subjective experience of sleep is scarce. Relatively unexplored is also the extent to which athletes’ sleep is adversely affected by environmental conditions and daytime behaviours, that is sleep hygiene. This study aimed to provide insight in sleep quantity, quality and its putative association with sleep hygiene. Participants were 98 elite (youth) athletes competing at the highest (inter‐)national level. Sleep quantity, quality and sleep hygiene were assessed once covering a 1‐month period by using established (sub)clinical questionnaires, and repeatedly during 7 consecutive days. Sleep quality was generally healthy, although 41% of all athletes could be classified as ‘poor sleeper’, and 12% were identified as having a sleep disorder. Daily self‐monitoring revealed sleep durations of 8:11 ± 0:45 h, but elevated wake after sleep onset of 13 ± 19 min. Sleep quality, feeling refreshed, and morning vigor were moderate at best. Regarding sleep hygiene, general measures revealed irregular sleep–wake patterns, psychological strain and activating pre‐sleep behaviours. At the daily level, blue‐light exposure and late‐evening consumption of heavy meals were frequently reported. General sleep hygiene revealed significant associations with sleep quality (0.45 < r > 0.50; P < 0.001). Results indicate that there is ample room for optimization, specifically in onset latency and in wake after sleep onset. Subtle improvements in sleep seem possible, and optimizing sleep hygiene, such as regular sleep–wake patterns and reducing psychological strain, may facilitate this sleep upgrading process.     

Comparison of sleep parameters from actigraphy and polysomnography in older women: the SOF study

STUDY OBJECTIVES: Total sleep time (TST), sleep efficiency (SE), and wake after sleep onset (WASO) as assessed by actigraphy gathered in 3 different modes were compared to polysomnography (PSG) measurements. Each mode was compared to PSG to determine which was more accurate. Associations of the difference in TST measurement with demographics and sleep characteristics were examined. DESIGN: Observational study. SETTING: Community-based. PARTICIPANTS: Sixty-eight women (mean age 81.9 years) from the latest visit of the Study of Osteoporotic Fractures who were concurrently measured with PSG and actigraphy. INTERVENTIONS: N/A. MEASUREMENTS AND RESULTS: In-home 12-channel PSG was gathered along with actigraphy data in 3 modes: proportional integration mode (PIM), time above threshold (TAT) and zero crossings mode (ZCM). The PIM mode corresponded better to PSG, with a mean overestimation of TST of 17.9 min. For the PIM mode, the estimation of TST and SE by PSG and actigraphy significantly differed (P < 0.01), while the estimation of WASO was similar (P = 0.27). The intraclass correlation between the 2 procedures was moderate to high (PIM mode: TST 0.76; SE 0.61; WASO 0.58). On average, the PIM mode underestimated TST by 68 min for those who slept < or = 5 hr, overestimated TST by 31 min for those with SE < 70%, and underestimated TST by 24 min for self-reported poor sleepers (P < 0.05). CONCLUSIONS: Sleep parameters from actigraphy corresponded reasonably well to PSG in this population, with the PIM mode of actigraphy correlating highest. Those with poor sleep quality had the largest measurement error between the 2 procedures.     

Subjective–objective sleep discrepancy among older adults: associations with insomnia diagnosis and insomnia treatment

Discrepancy between subjective and objective measures of sleep is associated with insomnia and increasing age. Cognitive behavioural therapy for insomnia improves sleep quality and decreases subjective–objective sleep discrepancy. This study describes differences between older adults with insomnia and controls in sleep discrepancy, and tests the hypothesis that reduced sleep discrepancy following cognitive behavioural therapy for insomnia correlates with the magnitude of symptom improvement reported by older adults with insomnia. Participants were 63 adults >60 years of age with insomnia, and 51 controls. At baseline, participants completed sleep diaries for 7 days while wearing wrist actigraphs. After receiving cognitive behavioural therapy for insomnia, insomnia patients repeated this sleep assessment. Sleep discrepancy variables were calculated by subtracting actigraphic sleep onset latency and wake after sleep onset from respective self‐reported estimates, pre‐ and post‐treatment. Mean level and night‐to‐night variability in sleep discrepancy were investigated. Baseline sleep discrepancies were compared between groups. Pre–post‐treatment changes in Insomnia Severity Index score and sleep discrepancy variables were investigated within older adults with insomnia. Sleep discrepancy was significantly greater and more variable across nights in older adults with insomnia than controls, P ≤ 0.001 for all. Treatment with cognitive behavioural therapy for insomnia was associated with significant reduction in the Insomnia Severity Index score that correlated with changes in mean level and night‐to‐night variability in wake after sleep onset discrepancy, P < 0.001 for all. Study of sleep discrepancy patterns may guide more targeted treatments for late‐life insomnia.     

The relation between polysomnography and subjective sleep and its dependence on age – poor sleep may become good sleep

Women complain more about sleep than men, but polysomnography (PSG) seems to suggest worse sleep in men. This raises the question of how women (or men) perceive objective (PSG) sleep. The present study sought to investigate the relation between morning subjective sleep quality and PSG variables in older and younger women. A representative sample of 251 women was analysed in age groups above and below 51.5 years (median). PSG was recorded at home during one night. Perceived poor sleep was related to short total sleep time (TST), long wake within total sleep time (WTSP), low sleep efficiency and a high number of awakenings. The older women showed lower TST and sleep efficiency and higher WTSP for a rating of good sleep than did the younger women. For these PSG variables the values for good sleep in the older group were similar to the values for poor sleep in the young group. It was concluded that women perceive different levels of sleep duration, sleep efficiency and wake after sleep onset relatively well, but that older women adjust their objective criteria for good sleep downwards. It was also concluded that age is an important factor in the relation between subjective and objective sleep.     

Comparison between subjective and actigraphic measurement of sleep and sleep rhythms

Sleep is often assessed in circadian rhythm studies and long-term monitoring is required to detect any changes in sleep over time. The present study aims to investigate the ability of the two most commonly employed methods, actigraphy and sleep logs, to identify circadian sleep/wake disorders and measure changes in sleep patterns over time. In addition, the study assesses whether sleep measured by both methods shows the same relationship with an established circadian phase marker, urinary 6-sulphatoxymelatonin. A total of 49 registered blind subjects with different types of circadian rhythms were studied daily for at least four weeks. Grouped analysis of all study days for all subjects was performed for all sleep parameters (1062-1150 days data per sleep parameter). Good correlations were observed when comparing the measurement of sleep timing and duration (sleep onset, sleep offset, night sleep duration, day-time nap duration). However, the methods were poorly correlated in their assessment of transitions between sleep and wake states (sleep latency, number and duration of night awakenings, number of day-time naps). There were also large and inconsistent differences in the measurement of the absolute sleep parameters. Overall, actigraphs recorded a shorter sleep latency, advanced onset time, increased number and duration of night awakenings, delayed offset, increased night sleep duration and increased number and duration of naps compared with the subjective sleep logs. Despite this, there was good agreement between the methods for measuring changes in sleep patterns over time. In particular, the methods agreed when assessing changes in sleep in relation to a circadian phase marker (the 6-sulphatoxymelatonin (aMT6s) rhythm) in both entrained (n = 30) and free-running (n = 4) subjects.     

Occupational and socioeconomic differences in actigraphically measured sleep

Occupational conditions, together with socioeconomic status, may modulate sleep. This study examined the association of occupational conditions and socioeconomic status with actigraphic measures of sleep in workers. Fifty‐five employees (40 ± 12 years) wore a wrist actigraph during sleep for seven consecutive nights. Sleep variables addressed included total sleep time, sleep efficiency, mean activity during sleep, sleep‐onset latency, and wake after sleep onset. We also measured household income, occupational class, work schedule, weekly work hours, job demand, job control, worksite social support, effort–reward imbalance, organizational justice, and workplace social capital. Multiple linear regression models were used to determine the association of occupational indicators, socioeconomic status, as well as age and gender with each sleep variable. Higher workplace social capital was associated consistently with longer total sleep time (P < 0.001), higher sleep efficiency (P < 0.05) and lower mean activity during sleep (P < 0.07). Low occupational class (P < 0.01), higher job demand (P < 0.05) and lower job control (P < 0.05) were associated with longer total sleep time. No associations were significant for sleep‐onset latency or wake after sleep onset. These preliminary results suggest that enhanced workplace social capital is closely associated with better quality and quantity of sleep.     

The effects of rapid eye movement sleep deprivation during late pregnancy on newborns' sleep

Sleep deprivation during pregnancy is an emerging concern, as it can adversely affect the development of the offspring brain. This study was conducted to evaluate the effects of deprivation of rapid eye movement (REM) sleep during the third term of pregnancy on the sleep–wake profiles of neonates in the Wistar rat model. Sleep–wake patterns were assessed through electrophysiological measures and behavioural observations during postnatal days 1–21 on pups born to REM sleep‐deprived dams and control rats. Pups of REM sleep‐deprived dams had active sleep that was not only markedly higher in percentage during all the days studied, but also had reduced latency during later postnatal days 15–21. Quiet sleep and wake periods were lower. These factors, along with less frequent but longer sleep–wake cycles, indicated maturational delay in the sleep–wake neural networks. The disruption of time‐bound growth of sleep–wake neural networks was substantiated further by the decreased slope of survival plots in the sleep bouts. Examination of altered sleep–wake patterns during early development may provide crucial information concerning deranged neural development in the offspring. This is the first report, to our knowledge, to show that maternal sleep deprivation during pregnancy can delay and impair the development of sleep–wake profile in the offspring.     

Alpha‐wave frequency characteristics in health and insomnia during sleep

Appearances of alpha waves in the sleep electrencephalogram indicate physiological, brief states of awakening that lie in between wakefulness and sleep. These microstates may also cause the loss in sleep quality experienced by individuals suffering from insomnia. To distinguish such pathological awakenings from physiological ones, differences in alpha‐wave characteristics between transient awakening and wakefulness observed before the onset of sleep were studied. In polysomnographic datasets of sleep‐healthy participants (n = 18) and patients with insomnia (n = 10), alpha waves were extracted from the relaxed, wake state before sleep onset, wake after sleep‐onset periods and arousals of sleep. In these, alpha frequency and variability were determined as the median and standard deviation of inverse peak‐to‐peak intervals. Before sleep onset, patients with insomnia showed a decreased alpha variability compared with healthy participants (P < 0.05). After sleep onset, both groups showed patterns of decreased alpha frequency that was lower for wake after sleep‐onset periods of shorter duration. For patients with insomnia, alpha variability increased for short wake after sleep‐onset periods. Major differences between the two groups were encountered during arousal. In particular, the alpha frequency in patients with insomnia rebounded to wake levels, while the frequency in healthy participants remained at the reduced level of short wake after sleep‐onset periods. Reductions in alpha frequency during wake after sleep‐onset periods may be related to the microstate between sleep and wakefulness that was described for such brief awakenings. Reduced alpha variability before sleep may indicate a dysfunction of the alpha generation mechanism in insomnia. Alpha characteristics may also prove valuable in the study of other sleep and attention disorders.