Short-term effects of wake- and bright light therapy on sleep in depressed youth

Chronotherapeutics are well established for the treatment of depression and associated sleeping problems in adults. However, effects are still understudied in adolescents. Two pilot studies highlighted the crucial role of sleep when it comes to the treatment of depression, by means of chronotherapeutics, in adolescents. The aim of the present study was to investigate the role of adjunctive wake therapy (WT) in addition to bright light therapy (BLT) with respect to sleep behaviors. In the present study, 62 depressed inpatients (aged 13–18 years; diagnosed with Beck Depression Inventory Revision) were randomly assigned to two groups: BLT only (BLT-group) and a combination of BLT and WT (COMB-group). After one night of WT adolescents in the COMB-group revealed longer sleep durations, time in bed, advanced sleep onset, less wakes during night and an improved sleep efficiency. However, one night of WT plus BLT had no additional effect on sleep parameters compared with BLT-group in the long run. Therefore, future studies should assess whether more nights of WT might lead to more sustainable effects.     

SLEEP PATTERNS IN HIGH SCHOOL AND UNIVERSITY STUDENTS: A LONGITUDINAL STUDY

We performed a longitudinal study to investigate whether changes in social zeitgebers and age alter sleep patterns in students during the transition from high school to university. Actimetry was performed on 24 high-school students (mean age?±?SD: 18.4?±?0.9 yrs; 12 females) for two weeks. Recordings were repeated in the same subjects 5 yrs later when they were university students. The sleep period duration and its center, the mid-sleep time, and total sleep time were estimated by actimetry. Actigraphic total sleep time was similar when in high school and at the university on school days (6.31?±?0.47 vs. 6.45?±?0.80?h, p?=?ns) and longer on leisure days by 1.10?±?1.10?h (p?<?0.0001 vs. school days) when in high school, but not at the university. Compared to the high school situation, the mid-sleep time was delayed when at the university on school days (03∶11?±?0.6 vs. 03∶55?±?0.7?h, p?<?0.0001), but not on leisure days. Individual mid-sleep times on school and leisure days when in high school were significantly correlated with the corresponding values 5 yrs later when at the university (r?=?0.58 and r?=?0.55, p?<?0.05, respectively). The large differences in total sleep time between school and leisure days when students attended high school and the delayed mid-sleep time on school days when students attended university are consistent with a circadian phase shift due to changes in class schedules, other zeitgebers, and lifestyle preferences. Age-related changes may also have occurred, although some individuality of the sleep pattern was maintained during the 5 yr study span. These findings have important implications for optimizing school and work schedules in students of different age and level of education. (Author correspondence: pneubloc@usz.uzh.ch)     

Validation of an innovative method,based on tilt sensing,for the assessment of activity and body position

Since there is less movement during sleep than during wake, the recording of body movements by actigraphy has been used to indirectly evaluate the sleep–wake cycle. In general, most actigraphic devices are placed on the wrist and their measures are based on acceleration detection. Here, we propose an alternative way of measuring actigraphy at the level of the arm for joint evaluation of activity and body position. This method analyzes the tilt of three axes, scoring activity as the cumulative change of degrees per minute with respect to the previous sampling, and measuring arm tilt for the body position inference. In this study, subjects (N?=?13) went about their daily routine for 7 days, kept daily sleep logs, wore three ambulatory monitoring devices and collected sequential saliva samples during evenings for the measurement of dim light melatonin onset (DLMO). These devices measured motor activity (arm activity, AA) and body position (P) using the tilt sensing of the arm, with acceleration (wrist acceleration, WA) and skin temperature at wrist level (WT). Cosinor, Fourier and non-parametric rhythmic analyses were performed for the different variables, and the results were compared by the ANOVA test. Linear correlations were also performed between actimetry methods (AA and WA) and WT. The AA and WA suitability for circadian phase prediction and for evaluating the sleep–wake cycle was assessed by comparison with the DLMO and sleep logs, respectively. All correlations between rhythmic parameters obtained from AA and WA were highly significant. Only parameters related to activity levels, such as mesor, RA (relative amplitude), VL5 and VM10 (value for the 5 and 10 consecutive hours of minimum and maximum activity, respectively) showed significant differences between AA and WA records. However, when a correlation analysis was performed on the phase markers acrophase, mid-time for the 10 consecutive hours of highest (M10) and mid-time for the five consecutive hours of lowest activity (L5) with DLMO, all of them showed a significant correlation for AA (R?=?0.607, p?=?0.028; R?=?0.582, p?=?0.037; R?=?0.620, p?=?0.031, respectively), while for WA, only acrophase did (R?=?0.621, p?=?0.031). Regarding sleep detection, WA showed higher specificity than AA (0.95?±?0.01 versus 0.86?±?0.02), while the agreement rate and sensitivity were higher for AA (0.76?±?0.02 versus 0.66?±?0.02 and 0.71?±?0.03 versus 0.53?±?0.03, respectively). Cohen’s kappa coefficient also presented the highest values for AA (0.49?±?0.04) and AP (0.64?±?0.04), followed by WT (0.45?±?0.06) and WA (0.37?±?0.04). The findings demonstrate that this alternative actigraphy method (AA), based on tilt sensing of the arm, can be used to reliably evaluate the activity and sleep–wake rhythm, since it presents a higher agreement rate and sensitivity for detecting sleep, at the same time allows the detection of body position and improves circadian phase assessment compared to the classical actigraphic method based on wrist acceleration.     

Correlations between objective and subjective sleep and circadian markers in remitted patients with bipolar disorder

Bipolar disorder (BD) is a chronic psychiatric condition characterized by recurrences of depressive and (hypo)manic episodes. Patients in remission report a wide range of sleep and circadian disturbances that correlate with several outcomes measures such as functioning or physical health. The most appropriate way to measure these abnormalities in clinical practice requires further investigation since the external validity of self-reports, as compared to more physiological measures (such as polysomnography or actigraphy), has been questioned. Despite the fact that questionnaires are inexpensive, fast and easy to use, they need to be validated against objective measures. This study aims to validate three sleep and circadian questionnaires, namely the Pittsburgh Sleep Quality Index (PSQI), the Composite Scale of Morningness (CSM) and the Circadian Type Inventory (CTI) – against actigraphy in BD patients in remission. Twenty-six carefully assessed BD patients in remission completed the PSQI, the CTI and the CSM, and wore an actigraph (AW7, Camntech) for 21 consecutive days. Phase preference assessed by the CSM strongly correlated with actigraphic phase markers (M10 onset ρ?=??0.69 and L5 onset ρ?=??0.63). Sleep duration and sleep latency assessed by the PSQI and by actigraphy were also highly correlated (ρ?=??0.76; ρ?=?0.50). Moderate correlation coefficients were observed between questionnaires and actigraphy for markers that explored the stability of rhythms, sleep quality, sleep latency and sleep disturbances (|ρ|?>?0.40) although these were not significant after correcting for multiple testing. No correlation was observed between markers for the amplitude of rhythms. While the external validity of the CTI clearly requires further investigation, this study supported the external validity of the CSM and the PSQI for phase preference, sleep duration and latency. We conclude that the CSM and the PSQI could be useful in routine practice and research when actigraphy is not easily available.     

Efficient and Regular Patterns of Nighttime Sleep are Related to Increased Vulnerability to Microsleeps Following a Single Night of Sleep Restriction

Sleep-deprived people, or those performing extended monotonous tasks, can exhibit brief episodes in which they suspend performance and appear to fall asleep momentarily—behavioral microsleeps (“microsleeps”). In this study, microsleeps were identified using eye video and tracking response during a 20-min continuous tracking task undertaken by 16 healthy volunteers (mean age 24.9?yrs; 8 females, 8 males) in the early afternoon following a normally rested night and a night of restricted sleep (time-in-bed restricted to 4?h). Sessions were 1 wk apart and counterbalanced. Wrist actigraphy, self-reported sleepiness, and sleep quality were also recorded. We hypothesized that high microsleep rates when normally rested or after a night of sleep restriction would be related to poor sleep quality, sleep disturbance, circadian type, irregular sleep patterns, low daily sleep duration, or poor sleep efficiency. We also hypothesized that prior performance on a 10-min psychomotor vigilance task (PVT) (mean reaction time or number of PVT lapses) would be related to the number of microsleeps during the tracking task and that PVT performance could, therefore, be used as a fitness-for-duty indicator. The number of microsleeps during the tracking task increased following sleep restriction (mean 11.4 versus 27.9; p?=?0.03). There were no correlations between the number of microsleeps in the normally rested session and any of the actigraphically measured or self-reported sleep measures. However, the number of microsleeps following sleep restriction was correlated with sleep efficiency (r?=?0.73, p?=?0.001), sleep onset latency (r?=??0.57, p?=?0.02), and sleep onset time-of-day standard deviation (r?=??0.54, p?=?0.03) over 11 normally rested nights. There was no correlation between PVT performance and the subsequent number of microsleeps during the tracking task in either session. Attributes usually associated with beneficial nighttime sleep patterns—going to sleep at a similar time each night, falling asleep quickly, and infrequent arousals—were related to greater vulnerability to microsleeps following sleep restriction. There were intercorrelations between all the sleep measures associated with microsleep rate following sleep restriction, indicating that the measures form a pattern of behaviors and are not independently related to microsleep rate. Perhaps some people maintain a regular sleep pattern because they experience sleepiness the following day when their pattern is disrupted. Conversely, people with more variation in their sleep pattern may do so because this does not substantially increase sleepiness the following day. We conclude that people with consistent sleep patterns and efficient sleep may be more prone to microsleeps than other people when their usual regular pattern is disrupted by sleep restriction.     

Comparison of Two Different Actigraphs with Polysomnography in Healthy Young Subjects

The present study aimed to compare two commercially available actigraphs, with a concurrent polysomnographic (PSG) recording. Twelve healthy volunteers (six women; age range 19–28 yrs) simultaneously wore the Basic Mini‐Motionlogger® and Actiwatch® for seven overnight polysomnographic recordings. Comparisons of the following sleep measures were focused on: sleep onset latency (SOL), total sleep time, wake after sleep onset, and sleep efficiency. Both devices underestimated SOL in comparison to PSG, but they had similar performance compared to PSG for the other sleep measures. A limit of the study is that the results can be only generalized to healthy young subjects.     

Performance comparison of different interpretative algorithms utilized to derive sleep parameters from wrist actigraphy data

ABSTRACT

We compared performance of four popular interpretative algorithms (IAs), i.e., Cole–Kripke, Rescored Cole–Kripke, Sadeh, and UCSD, utilized to derive sleep parameters from wrist actigraphy data. We conducted in-home sleep study of 40 healthy adults (17 female/23 male; age 26.7 ± 12.1 years), assessing sleep variables both by Motionlogger® Micro Watch Actigraphy (MMWA) and Zmachine® Insight+ electroencephalography (EEG). Data of MMWA were separately scored per 30 sec epochs by each of the four popular IAs, and data of the Zmachine were also scored per 30 sec epochs by its proprietary IA. In reference to the EEG Zmachine method, all four of the MMWA algorithms showed high (~94 to 98%) sensitivity and moderate (~42 to 54%) specificity in detecting Sleep epochs. All of them significantly underestimated Sleep Onset Latency (SOL: ~9 to 20 min), and all of them, except the Sadeh IA, significantly underestimated Wake After Sleep Onset (WASO: ~22 to 25 min) and overestimated Total Sleep Time (TST: ~32 to 45 min) and Sleep Efficiency (SE: ~7 to 9%). The Sadeh IA showed significantly smaller bias than the other three IAs in deriving WASO, TST, and SE. Overall, application of ‘Rescoring Rules’ improved performance of the Cole–Kripke IA. The Sadeh and Rescored Cole–Kripke IAs exhibited highest agreement with the EEG Zmachine method (Cohen’s Kappa: ~51%), while the UCSD IA exhibited lowest agreement (Cohen’s kappa: ~47%). However, minimum detectable change across all sleep parameters was smallest with use of the UCSD IA and, except for SOL, largest with use of the Sadeh algorithm. Findings of this study indicate the Sadeh IA is most appropriate for deriving sleep parameters of healthy adults, while the UCSD IA is most appropriate for evaluating change in sleep parameters over time or in response to medical intervention.     

Seasonal Effect on Infants' Sleep Regulation: A Preliminary Study in a Mediterranean Climate

Infants' sleep-wake rhythms are influenced by multiple factors, including developmental and contextual aspects, as well as circadian cycles. Empirical studies that address the seasonal impact on infants' sleep are scarce. The present study examined aspects of sleep schedule and quality, comparing summer and winter months in a Mediterranean climate. This report is based on a convenience sample of 34 healthy 7-mo-olds, an age in which sleep is well consolidated and regulated compared with the first few months of life. Sleep was measured with actigraphy, in the home context. It was found that compared with winter, in the summer months, sleep onset occurred at a later hour, and more motor activity during sleep was detected. Although the overall sleep quality, as defined by sleep efficiency score, was similar in the two seasons, in the summer, more active sleep was observed. The authors discuss the finding in terms of circadian rhythms, developmental characteristics, as well as possible environmental factors and family routines, and call for more studies, in different climates and geographical zones, and in different developmental periods. (Author correspondence: cohen.dini@gmail.com or anats@edu.haifa.ac.il)     

Validating functional data analysis measures from 24-h actigraphy data

The timing of sleep and wakefulness are under the influence of the circadian pacemaker in the suprachiasmatic nucleus, and the set-point for the circadian pacemaker is revealed by the time of onset of the secretion of melatonin under dim light conditions (DLMO). Measuring DLMO is time intensive and requires biochemical assays; hence it would be desirable to develop simpler alternatives to DLMO measurement that would otherwise provide similar information about health and illness. Continuous, multi-day measurement of actigraphy can be processed to reveal underlying features such as the time of greatest activity (acrophase), or the time of least activity (bathyphase). In this paper, we explore the calculation of the acrophase and bathyphase using a statistical approach called functional data analysis (FDA), and validated the FDA-calculated bathyphase by correlating it with morningness–eveningness self-reports from 47 depressed adults.     

Actigraphic Monitoring of the Activity-Rest Behavior of Preterm and Full-Term Infants at 20 Months of Age

Differences in the activity-rest behavior of preterm and full-term infants provide an important contribution to the analysis of the ontogeny of circadian rhythms. In this study, we recorded the activity-rest behavior of 17 preterm and 8 full-term infants at the approximate age of 20 months over an average of 10 days by means of actigraphic monitoring (Actiwatch®, Cambridge Neurotechnology Ltd.). At the same time, the parents of the infants kept a daily diary. The activity-rest rhythm, the nighttime sleep duration, the daytime rest duration, as well as the sleep quality of the infants were analyzed. Preterm and full-term infants at the age of 20 months show a circadian rhythm with a period length between 23 h 32 min (23:32 h) and 24 h 23 min (24:23 h). It can be concluded that the preterm and full-term infants all reached a vital developmental step by showing the dominant circadian rhythm in the spectrum. The daytime rest duration of preterm infants is significantly shorter than that of full-term infants. The sleep quality of preterm infants is significantly lower than that of full-term infants, which means that the preterm infants have a larger percentage of less restful nighttime sleep. In other studies preterm infants show an over-proportional frequency of attention deficit hyperactivity disorder (ADHD). For this reason, future analyses should reveal whether or not actigraphic monitoring is a suitable means for an early identification of activity-rest behavior in children who may develop ADHD.