Sleep patterns and insomnia among adolescents: a population‐based study

The aim of the current study was to examine sleep patterns and rates of insomnia in a population‐based study of adolescents aged 16–19 years. Gender differences in sleep patterns and insomnia, as well as a comparison of insomnia rates according to DSM‐IV, DSM‐V and quantitative criteria for insomnia (Behav. Res. Ther., 41 , 2003, 427), were explored. We used a large population‐based study in Hordaland county in Norway, conducted in 2012. The sample included 10 220 adolescents aged 16–18 years (54% girls). Self‐reported sleep measurements included bedtime, rise time, time in bed, sleep duration, sleep efficiency, sleep onset latency, wake after sleep onset, rate and frequency and duration of difficulties initiating and maintaining sleep and rate and frequency of tiredness and sleepiness. The adolescents reported short sleep duration on weekdays (mean 6:25 hours), resulting in a sleep deficiency of about 2 h. A majority of the adolescents (65%) reported sleep onset latency exceeding 30 min. Girls reported longer sleep onset latency and a higher rate of insomnia than boys, while boys reported later bedtimes and a larger weekday–weekend discrepancy on several sleep parameters. Insomnia prevalence rates ranged from a total prevalence of 23.8 (DSM‐IV criteria), 18.5 (DSM‐V criteria) and 13.6% (quantitative criteria for insomnia). We conclude that short sleep duration, long sleep onset latency and insomnia were prevalent in adolescents. This warrants attention as a public health concern in this age group.     

Exploring the impact of experimental sleep restriction and sleep deprivation on subjectively perceived sleep parameters

We aimed to investigate the effect of increased sleep pressure and shortened sleep duration on subjective sleep perception in relation to electroencephalographic sleep measures. We analyzed the data from a study in which 14 healthy male volunteers had completed a baseline assessment with 8 hr time in bed, a sleep deprivation (40 hr of wakefulness) and a sleep restriction protocol with 5 hr time in bed during 7 nights. In this work, we assessed perception index, derived through dividing the subjectively perceived total sleep time, wake after sleep onset and sleep latency duration by the objectively measured one at each condition. We found that total sleep time was subjectively underestimated at baseline and shifted towards overestimation during sleep restriction and after deprivation. This change in accuracy of subjective estimates was not associated with any changes in sleep architecture or sleep depth. Wake after sleep onset was significantly underestimated only during sleep restriction. Sleep latency was always overestimated subjectively without any significant change in this misperception across conditions. When comparing accuracy of subjective and actimetry estimates, subjective estimates regarding total sleep time and wake after sleep onset deviated less from electroencephalography derived measures during sleep restriction and after deprivation. We conclude that self‐assessments and actimetry data of patients with chronic sleep restriction should be interpreted cautiously. The subjectively decreased perception of wake after sleep onset could lead to overestimated sleep efficiency in such individuals, whereas the underestimation of sleep time and overestimation of wake after sleep onset by actimetry could lead to further underestimated sleep duration.     

School start time and sleep in Canadian adolescents

Insufficient sleep is a serious problem in adolescents and school start time is thought to be a key contributor. This study provided the first comprehensive assessment of school start times across Canada and examined whether school start times were associated with sleep duration and tiredness among adolescents. We collected information on school start times from 362 schools that participated in the 2013/2014 Health Behaviour in School‐aged Children study. We calculated sleep duration from weekday bedtime and wake time reported by 29 635 students (aged 10–18 years). We classified weekday sleep as sufficient if it met national recommendations, and used data on self‐reported tiredness at school in the morning. Random‐effects regression models estimated the association of school start time with sleep duration, sleep sufficiency and tiredness. On average, schools started at 08:43 hours. Students slept an average of 8:36 h on weekdays and 69% met sleep duration recommendations, but 60% reported feeling tired in the morning. Every 10‐min delay in school start time corresponded with 3.2 [95% confidence interval (CI): 2.0, 4.5] additional minutes of sleep, a 1.6% (95% CI: 0.5, 2.8) greater probability of sufficient sleep and a 2.1% (95% CI: 1.0, 3.2) smaller probability of feeling tired at school in the morning. Students from schools that started later slept longer, were more likely to meet sleep recommendations and were less likely to report feeling tired in the morning. The study adds weight to the mounting evidence that delaying school start time benefits adolescent sleep.     

Bedtime,shuteye time and electronic media: sleep displacement is a two‐step process

This study argues that going to bed may not be synonymous with going to sleep, and that this fragmentation of bedtime results in a two‐step sleep displacement. We separated bedtime (i.e. going to bed) from shuteye time (i.e. attempting to go to sleep once in bed) and assessed the prevalence of electronic media use in both time slots. A convenience sample of 338 adults (aged 18–25 years, 67.6% women) participated in an online survey. Results indicated a gap of 39 min between bedtime and shuteye time, referred to as ‘shuteye latency’. Respondents with a shuteye latency of, respectively, ≤30 min, ≤1 or >1 h, were 3.3, 6.1 and 9.3 times more likely to be rated as poor sleepers compared to those who went to sleep immediately after going to bed. Before bedtime, volume of electronic media use (17 h 55 min per week) was higher than non‐media activities (14 h per week), whereas the opposite was true after bedtime (media = 3 h 41 min, non‐media = 7 h 46 min). Shuteye latency was related exclusively to prebedtime media use. Findings confirmed the proposed fragmentation of bedtime. Sleep displacement should therefore be redefined as a two‐step process, as respondents not only engage in the delay of bedtime, but also in the delay of shuteye time once in bed. Theoretical, methodological and practical implications are discussed.     

An approach to understanding sleep and depressed mood in adolescents: person‐centred sleep classification

Depressive mood in youth has been associated with distinct sleep dimensions, such as timing, duration and quality. To identify discrete sleep phenotypes, we applied person‐centred analysis (latent class mixture models) based on self‐reported sleep patterns and quality, and examined associations between phenotypes and mood in high‐school seniors. Students (n = 1451; mean age = 18.4 ± 0.3 years; 648 M) completed a survey near the end of high‐school. Indicators used for classification included school night bed‐ and rise‐times, differences between non‐school night and school night bed‐ and rise‐times, sleep‐onset latency, number of awakenings, naps, and sleep quality and disturbance. Mood was measured using the total score on the Center for Epidemiologic Studies‐Depression Scale. One‐way anova tested differences between phenotype for mood. Fit indexes were split between 3‐, 4‐ and 5‐phenotype solutions. For all solutions, between phenotype differences were shown for all indicators: bedtime showed the largest difference; thus, classes were labelled from earliest to latest bedtime as ‘A’ (n = 751), ‘B’ (n = 428) and ‘C’ (n = 272) in the 3‐class solution. Class B showed the lowest sleep disturbances and remained stable, whereas classes C and A each split in the 4‐ and 5‐class solutions, respectively. Associations with mood were consistent, albeit small, with class B showing the lowest scores. Person‐centred analysis identified sleep phenotypes that differed in mood, such that those with the fewest depressive symptoms had moderate sleep timing, shorter sleep‐onset latencies and fewer arousals. Sleep characteristics in these groups may add to our understanding of how sleep and depressed mood associate in teens.     

Preventing sleep deficit in adolescents: Long‐term effects of a quasi‐experimental school‐based intervention study

Adolescents are at risk of sleep deficit, which has serious consequences for their daytime functioning. However, school‐based interventions to improve sleep have shown limited success. This might be due to the content of the programmes (e.g., not targeting central factors such as daytime stress and technology use) or because changes have not been captured due to a lack of long‐term follow‐ups. Hence, the aim of this study was to evaluate the long‐term effects of a school‐based sleep education curriculum including time‐management training. The study used a quasi‐experimental design. Participants were 3,622 adolescents (mean age 13.7, 48% girls); 286 were in the intervention group and 3,336 were followed as a natural control group. Data were collected before the intervention and at a 1‐year follow‐up. We divided participants into three groups according to baseline sleep duration (calculated from self‐reported bed‐ and wake times, minus sleep onset latency): insufficient (<7 hr), borderline (7–8 hr) and adequate (>8 hr). Adolescents in the intervention group were ~2 times less likely to report insufficient sleep at follow‐up as compared to controls. Sleep knowledge improved significantly in the intervention group but there were no changes in emotional sleep hygiene (e.g., bedtime worry) and perceived stress. Surprisingly, technology use increased and behavioural sleep hygiene worsened in the intervention group. Although the mechanisms of change need further investigation, the results of this study point to potential long‐term benefits of school‐based sleep programmes.     

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.     

Brief school‐based interventions to assist adolescents’ sleep‐onset latency: Comparing mindfulness and constructive worry versus controls

Difficulties falling asleep are common among adolescents, especially during times of stress. Adolescents may thus benefit from brief techniques (15 min) that decrease pre‐sleep cognitive‐emotional arousal and sleep‐onset latency. The present study used a 3 (intervention: mindfulness bodyscan mp3, constructive worry, control) by 3 (time: baseline, week 1, week 2) mixed‐model design on a school‐based sample of adolescents (N = 232; M_age = 15.9 ± 0.8 years, range = 14–18 years; 19% male), and a sub‐sample of adolescents with prolonged sleep‐onset latency (i.e. ≥30 min; N = 119; M_age = 16.9 ± 0.9 years; 21% male). It was expected that the 15‐min pre‐recorded breath‐based mindfulness bodyscan, and constructive worry, would decrease sleep‐onset latency and pre‐sleep arousal similarly over time, relative to the control condition. A significant interaction was observed among adolescents with prolonged sleep‐onset latency, who completed ≥3 days for at least 1 week (p = .001), where mindfulness decreased sleep‐onset latency relative to constructive worry and the control. Neither technique changed pre‐sleep worry or cognitive‐emotional arousal, or associated daytime functioning (both the whole sample and sub‐sample). A pre‐recorded mp3 breath‐based mindfulness bodyscan technique is a promising means by which adolescents with prolonged sleep‐onset latency can decrease sleep‐onset latency. This simple tool has potential for scalable dissemination by stakeholders (e.g. teachers), unqualified to treat adolescent sleep difficulties. Future studies are needed to determine whether benefits may extend to academic performance and mental health, if performed for a longer time period with increased compliance.     

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.     

Sleep and academic performance in later adolescence: results from a large population‐based study

The aim of the current study was to assess the association between sleep duration and sleep patterns and academic performance in 16–19 year‐old adolescents using registry‐based academic grades. A large population‐based study from Norway conducted in 2012, the youth@hordaland‐survey, surveyed 7798 adolescents aged 16–19 years (53.5% girls). The survey was linked with objective outcome data on school performance. Self‐reported sleep measures provided information on sleep duration, sleep efficiency, sleep deficit and bedtime differences between weekday and weekend. School performance [grade point average (GPA)] was obtained from official administrative registries. Most sleep parameters were associated with increased risk for poor school performance. After adjusting for sociodemographic information, short sleep duration and sleep deficit were the sleep measures with the highest odds of poor GPA (lowest quartile). Weekday bedtime was associated significantly with GPA, with adolescents going to bed between 22:00 and 23:00 hours having the best GPA. Also, delayed sleep schedule during weekends was associated with poor academic performance. The associations were somewhat reduced after additional adjustment for non‐attendance at school, but remained significant in the fully adjusted models. In conclusion, the demonstrated relationship between sleep problems and poor academic performance suggests that careful assessment of sleep is warranted when adolescents are underperforming at school. Future studies are needed on the association between impaired sleep in adolescence and later functioning in adulthood.     

The effect of caffeine abstinence on sleep among habitual caffeine users with poor sleep

Caffeine is the most widely used psychoactive substance in the world and is known to disrupt healthy sleep. However, very few studies have directly tested the effect of caffeine abstinence on sleep, and these have yielded inconsistent findings. The purpose of the present study was to examine changes in sleep following caffeine abstinence and examine the extent to which characteristics of habitual caffeine use moderated this change. Participants included 66 healthy, young adults with habitual caffeine use and poor sleep. During the 2‐week baseline, sleep was assessed using wrist actigraphy and daily caffeine use was assessed with bedtime diaries. Eligible participants then completed 1 week of caffeine abstinence, during which sleep was measured with wrist actigraphy. Multilevel models found no significant differences between either mean levels or growth trajectories of total sleep time or sleep efficiency between baseline and caffeine abstinence. Mean levels of sleep onset latency also did not differ between baseline and caffeine abstinence. A small but significant quadratic effect was observed, such that sleep onset latency decreased during the first few days of caffeine abstinence, then increased to levels above baseline. Characteristics of caffeine use did not moderate changes in sleep between baseline and caffeine abstinence. These data suggest that abstaining from caffeine may not result in long‐term sleep improvement for habitual caffeine users, which contradicts the common sleep health recommendation. The present findings encourage more rigorous investigation of the effectiveness of caffeine restriction on sleep.     

An experimental study of adolescent sleep restriction during a simulated school week: changes in phase,sleep staging,performance and sleepiness

This laboratory study investigated the impact of restricted sleep during a simulated school week on circadian phase, sleep stages and daytime functioning. Changes were examined across and within days and during a simulated weekend recovery. Participants were 12 healthy secondary school students (six male) aged 15–17 years [mean = 16.1 years, standard deviation (SD) = 0.9]. After 2 nights with 10 h (21:30–07:30 hours), time in bed was restricted to 5 h for 5 nights (02:30–07:30 hours), then returned to 10 h time in bed for 2 nights (21:30–07:30 hours). Saliva was collected in dim light on the first and last sleep restriction nights to measure melatonin onset phase. Sleep was recorded polysomnographically, and the Psychomotor Vigilance Task (PVT) and Karolinska Sleepiness Scale were undertaken 3‐hourly while awake. Average phase delay measured by melatonin was 3 h (SD = 50 min). Compared to baseline, sleep during the restriction period contained a smaller percentage of Stages 1 and 2 and rapid eye movement (REM) and a greater percentage of Stage 4. PVT lapses increased significantly during sleep restriction and did not return to baseline levels during recovery. Subjective sleepiness showed a similar pattern during restriction, but returned to baseline levels during recovery. Results suggest that sustained attention in adolescents is affected negatively by sleep restriction, particularly in the early morning, and that a weekend of recovery sleep is insufficient to restore performance. The discrepancy between sleepiness ratings and performance may indicate a lack of perception of this residual impairment.     

Trait‐like characteristics of sleep EEG power spectra in adolescents across sleep opportunity manipulations

The electroencephalographic power spectra of non‐rapid eye movement sleep in adults demonstrate trait‐like consistency within participants across multiple nights, even when prior sleep deprivation is present. Here, we examined the extent to which this finding applies to adolescents who are habitually sleep restricted on school‐days and sleep longer on weekends. We evaluated 78 adolescents across three sleep restriction groups who underwent different permutations of adequate sleep (9 hr time‐in‐bed), sleep restriction (5 hr time‐in‐bed), afternoon naps (1 hr afternoon) and recovery sleep (9 hr time‐in‐bed) that simulate behaviour on school‐days and weekends. The control group comprised a further 22 adolescents who had 9 hr of sleep opportunity each night. Intra‐class correlation coefficients showed moderate to almost perfect within‐subject stability in electroencephalographic power spectra across multiple nights in both sleep restriction and control groups, even when changes to sleep macrostructure were observed. While nocturnal intra‐class correlation metrics were lower in the low‐frequency and spindle frequency bins in the sleep restriction compared with the control group, hierarchical clustering measures could still identify multi‐night electroencephalographic spectra as originating from the same individual. The trait‐like characteristics of electroencephalographic spectra from an adolescent remain identifiable despite the disruptive effects of multi‐night sleep restriction to sleep architecture.     

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.     

Objectively measured night‐to‐night sleep variations are associated with body composition in very elderly women

This cross‐sectional study examined the association between objectively measured sleep patterns and body composition in very elderly community‐dwelling women. Participants included 191 community‐dwelling adults aged ≥ 80 years (mean age: 83.4 ± 2.6 years; age range: 80–92 years). Sleep and physical activity were monitored via accelerometer (ActiGraph GT3X+) during at least five consecutive 24‐h periods. Night‐to‐night sleep pattern variability across all nights of recording was assessed using standard deviations (SDs). Body composition was assessed using dual‐energy X‐ray absorptiometry. Simple and multivariable linear regression analyses were performed. The mean number of nights with usable actigraphy data was 7.3 ± 1.3. On average, participants went to bed at 22:57 hours (SD: 1.11 h) and rose from bed at 6:27 hours (SD: 1.01 h). Night‐to‐night bedtime, sleep duration and sleep timing mid‐point variations correlated slightly with the percentage body fat and percentage lean mass (P < 0.05). Multiple linear regression analysis revealed significant associations of night‐to‐night bedtime variations and inconsistent sleep–wake patterns with all body composition indices after adjusting for potential confounding factors, including mean nightly sleep duration, self‐reported nap duration and daily physical activity. After further adjusting for night‐to‐night wake time, sleep timing mid‐point and sleep duration variations, greater bedtime variability remained associated significantly with all body composition indices except lean/fat mass ratio. Inconsistent sleep–wake patterns were associated independently with an increased fat mass and decreased lean mass among very elderly women. These findings suggest that in most elderly individuals, sleep patterns might be an important modifiable factor associated with obesity and sarcopenia development.     

Interaction of chronic sleep restriction and circadian system in humans

Nocturnal sleep restriction and compensation with daytime naps is common in today’s society. In a between‐participants design, we examined the effects of chronic (10 nights) sleep restriction on 24 h plasma melatonin profiles in humans. Following a baseline period with 8.2 h time in bed (TIB) for sleep, participants were randomized to a control (8.2 h TIB) or sleep‐restriction condition (4.2 h TIB), with and without diurnal naps. Sleep restriction was achieved via delaying bedtime and advancing wake time by 2 h each relative to the baseline sleep period. Participants were maintained in a controlled, time isolated laboratory environment throughout the protocol, with light levels below 40 lx at all times. Twenty‐four hour plasma melatonin profiles were assessed at baseline and at the end of the sleep‐restriction period, with subjects maintained in a constant posture protocol. Compared with the baseline assessment and the 8.2 h TIB control group, a significant phase delay in melatonin onset (1.2 ± 0.9 h) occurred in all sleep‐restriction (4.2 h TIB) groups (P < 0.05). There was no evidence of a phase advance or shortening of the period of melatonin secretion associated with the advanced waking time. These results suggest that nocturnal light and dark exposure may be more potent in effecting circadian phase shifts than exposure to morning light, at least in conditions of controlled, dim lighting in the laboratory.     

Estimating dim light melatonin onset (DLMO) phase in adolescents using summer or school-year sleep/wake schedules

STUDY OBJECTIVES: This analysis examined associations between the salivary dim light melatonin onset (DLMO) phase and self-selected sleep/ wake schedules in groups of children and adolescents during summer vacation and during the school year to determine the degree to which sleep/wake patterns can estimate salivary DLMO phase. DESIGN AND SETTING: Participants slept at home on self-selected schedules for 5 consecutive nights and reported their bedtime and wake-up time via daily telephone messages. Salivary melatonin was sampled in the laboratory on one evening every 30 minutes in dim light (< 50 lux) to determine DLMO phase. Within group bivariate regressions between sleep pattern measures (bedtime, wake-up time, and midsleep time) and DLMO phase were computed. PARTICIPANTS: One group, ages 9 to 17 years (mean age = 12.5, SD = 2.3 years, 74 males, 75 females) contributed 149 DLMO phase and sleep/wake pattern measures while on a school year schedule ("school group"). A separate group, ages 9 to 16 years (mean age = 13.1, SD = 1.3 years, 30 males, 29 females) contributed 59 DLMO phase and sleep/wake pattern measures while on a summer schedule ("summer group"). RESULTS: Bedtime, midsleep time, and wake-up time were positively correlated with DLMO phase in both groups. Although all correlation coefficients for the summer group were statistically greater compared to the school group, the regression equations predicted DLMO phase within +/- 1 hour of the measured DLMO phase in approximately 80% for both groups. CONCLUSIONS: DLMO phase can be estimated using self-selected sleep/wake patterns during the school year or summer vacation in healthy children and adolescents.     

Ecological momentary assessment of daytime symptoms during sleep restriction therapy for insomnia

This study profiles changes in self‐reported daytime functioning during sleep restriction therapy (SRT) for insomnia. Ecological momentary assessment (EMA) captured point‐in‐time symptomatology to map the time–course of symptoms. We hypothesized a deterioration (week 1) followed by improvements at week 3 of therapy relative to baseline. Nine patients with psychophysiological insomnia completed the Daytime Insomnia Symptom Scale (DISS) at rise‐time, 12:00 hours, 18:00 hours and bedtime for 1 week before and 3 weeks during SRT. Four validated factors from the DISS were analyzed (alert cognition, positive mood, negative mood and sleepiness/fatigue) across 28 days yielding 17 170 data points. Factors evaluated week (baseline versus weeks 1 and 3) and time of day symptomatology. Insomnia Severity Index scores decreased significantly pre‐to‐post treatment (mean 18 versus 7). Reflecting acute effects of SRT, significant differences were found for all factors, except negative mood, between baseline and week 1 of SRT, suggesting adverse effects. By week 3, sleepiness/fatigue and negative mood decreased significantly compared to baseline, and positive mood showed a trend towards improvement (P = 0.06). Sleepiness/fatigue displayed a significant week × time of day interaction, explained by a reduction in sleepiness/fatigue at every daytime assessment point (except bedtime, which remained high). A significant interaction for alert cognition was associated with reduction in alertness at bedtime by week 3 and an increase in alertness at rise‐time, suggesting that SRT not only improves sleep, but moderates alertness and sleepiness in therapeutic ways. Initial SRT is associated with an increase in sleepiness/fatigue and a decrease in alert cognition.     

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.     

Are qualitative and quantitative sleep problems associated with delinquency when controlling for psychopathic features and parental supervision?

The aim of this study was to explore the relationship between sleep, including both qualitative and quantitative aspects, and delinquent behaviour while controlling for psychopathic features of adolescents and parental supervision at bedtime. We analysed data from a nationally representative sample of 4855 Finnish adolescents (mean age 15.3 years, 51% females). Sleep problems, hours of sleep and delinquency were evaluated via self‐report. Psychopathic features were measured with the Antisocial Process Screening Device – Self‐Report. In negative binomial regressions, gender and sleep‐related variables acted as predictors for both property and violent crime after controlling for psychopathic features and parental supervision at bedtime. The results suggest that both sleep problems (at least three times per week, at least for a year) and an insufficient amount of sleep (less than 7 h) are associated with property crime and violent behaviour, and the relationship is not explained by gender, degree of parental supervision at bedtime or co‐occurring psychopathic features. These results suggest that sleep difficulties and insufficient amount of sleep are associated with delinquent behaviour in adolescents. The significance of addressing sleep‐related problems, both qualitative and quantitative, among adolescents is thus highlighted. Implications for a prevention technique of delinquent behaviour are discussed.