Search

Nicole Lovato,1 Michelle A Short,2 Gorica Micic,3 Rachel M Hiller,4 Michael Gradisar3 1Adelaide Institute for Sleep Health: A Flinders Centre of Research Excellence, Repatriation General Hospital, Flinders University, 2Centre for Sleep Research, University of South Australia, 3School of Psychology, Flinders University, Adelaide, SA, Australia; 4Department of Psychology, University of Bath, North East Somerset, UK Objective: The prospective, bidirectional relationship between sleep disturbance and depressed mood was assessed in a school-based sample of adolescents. Method: One hundred and thirty-eight Australian adolescents (mean age time 1 =15.69, standard deviation =0.92; 64% male) completed questionnaires to assess sleep parameters and depressed mood, on two occasions over 1 year. Results: Cross-sectional associations were observed between depressed mood and sleep duration, as well as wakefulness in bed. Prospective analyses revealed depressed mood predicted less total sleep time on school nights and a longer latency to sleep onset on weekends 1 year later. There was no prospective support for sleep predicting later depressed mood. Conclusion: Contrary to prediction, our results suggest in this case that depressed mood may act as a precursor to poor sleep rather than the converse. Keywords: adolescence, sleep disturbance, school-based, prospective, depressive symptoms

Michelle A Short,1,2 Michael Gradisar,1 Leon C Lack,1 Helen R Wright,1 Alex Chatburn21School of Psychology, Flinders University, 2Centre for Sleep Research, University of South Australia, Adelaide, South Australia, AustraliaBackground: In research and clinical contexts, parent reports are often used to gain information about the sleep patterns of their adolescents; however, the degree of concordance between parent reports and adolescent-derived measures is unclear. The present study compares parent estimates of adolescent sleep patterns with adolescent self-reports from surveys and sleep diaries, together with actigraphy.Methods: A total of 308 adolescents (59% male) aged 13–17 years completed a school sleep habits survey during class time at school, followed by a 7-day sleep diary and wrist actigraphy. Parents completed the Sleep, Medical, Education and Family History Survey.Results: Parents reported an idealized version of their adolescent's sleep, estimating significantly earlier bedtimes on both school nights and weekends, significantly later wake times on weekends, and significantly more sleep than either the adolescent self-reported survey, sleep diary, or actigraphic estimates.Conclusion: Parent reports indicate that the adolescent averages a near-optimal amount of sleep on school nights and a more than optimal amount of sleep on weekends. However, adolescent-derived averages indicate patterns of greater sleep restriction. These results illustrate the importance of using adolescent-derived estimates of sleep patterns in this age group and the importance of sleep education for both adolescents and their parents.Keywords: concordance, parent, sleep, sleep measurement, survey, actigraphy

Adolescent sleep quality and quantity is commonly linked to worse emotion regulation. One maladaptive emotion regulation strategy that is on the rise is non-suicidal self-injury (NSSI), which includes burning, hitting, or scratching one's own body tissue without suicidal intent. The aim of this study was to explore the frequency of NSSI among different longitudinal trajectories of insomnia symptoms and short sleep duration to identify at-risk adolescents. We used questionnaire data collected annually (3 time points over 2 years) from a sample of Swedish adolescents (N = 1,294; Mage = 13.2 [range: 12–15 years], SD = 0.4; 46.8% girls). Adolescents answered questions about their sleep duration, symptoms of insomnia, NSSI, depressive symptoms, and demographics. Adolescents who reported persistent or increasing sleep problems over time also reported more NSSI. A notable pattern was that adolescents whose insomnia symptoms were high and increasing reported the highest frequency of NSSI, also compared to adolescents who started at the same high level of insomnia symptoms but improved over time. Therefore, measuring NSSI may help identify a risk-group for persistent sleep problems and self-injury. Because sleep disturbances, especially insomnia, and NSSI go hand-in-hand for most adolescents, sleep interventions would benefit the treatment and prevention of self-injury. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has seen a rise in anxiety and depression among adolescents. This study aimed to investigate the longitudinal associations between sleep and mental health among a large sample of Australian adolescents and examine whether healthy sleep patterns were protective of mental health in the context of the COVID-19 pandemic. We used three waves of longitudinal control group data from the Health4Life cluster-randomized trial (N = 2781, baseline M age  = 12.6, SD =  0.51; 47% boys and 1.4% 'prefer not to say'). Latent class growth analyses across the 2 years period identified four trajectories of depressive symptoms: low-stable (64.3%), average-increasing (19.2%), high-decreasing (7.1%), moderate-increasing (9.4%), and three anxiety symptom trajectories: low-stable (74.8%), average-increasing (11.6%), high-decreasing (13.6%). We compared the trajectories on sociodemographic and sleep characteristics. Adolescents in low-risk trajectories were more likely to be boys and to report shorter sleep latency and wake after sleep onset, longer sleep duration, less sleepiness, and earlier chronotype. Where mental health improved or worsened, sleep patterns changed in the same direction. The subgroups analyses uncovered two important findings: (1) the majority of adolescents in the sample maintained good mental health and sleep habits (low-stable trajectories), (2) adolescents with worsening mental health also reported worsening sleep patterns and vice versa in the improving mental health trajectories. These distinct patterns of sleep and mental health would not be seen using mean-centred statistical approaches., (© 2024. The Author(s).)

Background: Insomnia and eveningness are common and often comorbid conditions in youths. While cognitive behavioural therapy for insomnia (CBT-I) has been suggested as a promising intervention, it remains unclear whether it is sufficient to also address circadian issues in youths. In addition, despite that light has been shown to be effective in phase-shifting one's circadian rhythm, there has been limited data on the effects of bright light therapy and its combination with CBT-I on sleep and circadian outcomes in youths. The current protocol outlines a randomised controlled trial that examines the efficacy of CBT-I and CBT-I plus bright light therapy (BLT) in reducing insomnia severity, improving mood symptoms and daytime functioning (e.g. sleepiness, fatigue, cognitive function), and improving subjective and objective sleep and circadian measures compared to a waitlist control group., Methods: We will carry out a randomised controlled trial (RCT) with 150 youths aged 12-24 who meet the criteria of insomnia and eveningness. Participants will be randomised into one of three groups: CBT-I with bright light therapy, CBT-I with placebo light, and waitlist control. Six sessions of CBT-I will be delivered in a group format, while participants will be currently asked to use a portable light device for 30 min daily immediately after awakening throughout the intervention period for bright light therapy. The CBT-I with light therapy group will receive bright constant green light (506 lx) while the CBT-I with placebo light group will receive the modified light device with the LEDs emitting less than 10 lx. All participants will be assessed at baseline and post-treatment, while the two active treatment groups will be additionally followed up at 1 month and 6 months post-intervention. The primary outcome will be insomnia severity, as measured by the Insomnia Severity Index. Secondary outcomes include self-reported mood, circadian, daytime functioning, and quality of life measures, as well as sleep parameters derived from actigraphy and sleep diary and neurocognitive assessments. Objective measures of the circadian phase using dim-light melatonin onset assessment and sleep parameters using polysomnography will also be included as the secondary outcomes., Discussion: This study will be the first RCT to directly compare the effects of CBT-I and BLT in youths with insomnia and eveningness. Findings from the study will provide evidence to inform the clinical management of insomnia problems and eveningness in youths., Trial Registration: ClinicalTrials.gov NCT04256915. Registered on 5 February 2020., (© 2024. The Author(s).)

Study Objectives: The aim of this study was to; (1) explore whether adolescents use technology as distraction from negative thoughts before sleep, (2) assess whether adolescents who perceive having a sleep problem use technology as distraction more compared to adolescents without sleep complaints, and (3) collect qualitative information about which devices and apps adolescents use as a distraction., Methods: This study used a mixed-methods cross-sectional design, where 684 adolescents ( M = 15.1, SD = 1.2, 46% female) answered both quantitative and qualitative questions about their sleep (perceived sleep problem, sleep onset time (SOT), and sleep onset latency [SOL]) and technology use as distraction from negative thoughts., Results: The majority of adolescents answered "yes" or "sometimes" using technology as a distraction from negative thoughts (23.6% and 38.4%). Adolescents who answered "yes" to using technology as distraction were more likely to report having a sleep problem, longer SOL, and later SOT, compared to adolescents who answered "no". The most popular device to distract was the phone, because of its availability, and the most common apps used for distraction included YouTube, Snapchat, and music apps., Conclusions: This study shows that many adolescents use technology to distract themselves from negative thoughts, which may help them manage the sleep-onset process. Thus, distraction may be one mechanism explaining how sleep affects technology use, rather than vice versa., (© The Author(s) 2022. Published by Oxford University Press on behalf of Sleep Research Society.)

Study Objectives: During adolescence, an interplay between biological and environmental factors leads to constrained sleep duration and timing. The high prevalence of sleep deprivation during this developmental period is a public health concern, given the value of restorative sleep for mental, emotional, and physical health. One of the primary contributing factors is the normative delay of the circadian rhythm. Therefore, the present study aimed to evaluate the effect of a gradually advanced morning exercise schedule (30 min shift each day) completed for 45 min on 5 consecutive mornings, on the circadian phase and daytime functioning of adolescents with a late chronotype, compared with a sedentary control group., Methods: A total of 18 physically inactive male adolescents aged 15-18 years spent 6 nights at the sleep laboratory. The morning procedure included either 45 min walking on a treadmill or sedentary activities in dim light. Saliva dim light melatonin onset, evening sleepiness, and daytime functioning were assessed during the first and last night of laboratory attendance., Results: The morning exercise group had a significantly advanced (earlier) circadian phase (27.5 min ± 32.0), while sedentary activity resulted in a phase delay (-34.3 min ± 53.2). Morning exercise also led to higher evening sleepiness in the earlier hours of the night, but not at bedtime. Mood measures improved slightly in both study conditions., Conclusions: These findings highlight the phase-advancing effect of low-intensity morning exercise among this population. Future studies are needed to test the transference of these laboratory findings to adolescents' real life., (© The Author(s) 2022. Published by Oxford University Press on behalf of Sleep Research Society.)

Study Objectives: The day-to-next day predictions between physical activity (PA) and sleep are not well known, although they are crucial for advancing public health by delivering valid sleep and physical activity recommendations. We used Big Data to examine cross-lagged time-series of sleep and PA over 14 days and nights., Methods: Bi-directional cross-lagged autoregressive pathways over 153,154 days and nights from 12,638 Polar watch users aged 18-60 years (M = 40.1 SD = 10.1; 44.5% female) were analyzed with cross-lagged panel data modeling (RI-CPL). We tested the effects of moderate-to-vigorous physical activity (MVPA) vs. high intensity PA (vigorous, VPA) on sleep duration and quality, and vice versa., Results: Within-subject results showed that more minutes spent in VPA the previous day was associated with shorter sleep duration the next night, whereas no effect was observed for MVPA. Longer sleep duration the previous night was associated with less MVPA but more VPA the next day. Neither MVPA nor VPA were associated with subsequent night's sleep quality, but better quality of sleep predicted more MVPA and VPA the next day., Conclusions: Sleep duration and PA are bi-directionally linked, but only for vigorous physical activity. More time spent in VPA shortens sleep the next night, yet longer sleep duration increases VPA the next day. The results imply that a 24-h framing for the interrelations of sleep and physical activity is not sufficient - the dynamics can even extend beyond, and are activated specifically for the links between sleep duration and vigorous activity. The results challenge the view that sleep quality can be improved by increasing the amount of PA. Yet, better sleep quality can result in more PA the next day., (© 2022. The Author(s).)

Study Objectives: We examined how adolescents' sleep patterns (i.e. insomnia symptoms and sleep duration) change from early- to mid-adolescence and whether adolescents follow different trajectories. Furthermore, we also examined the characteristics of adolescents within different trajectories, with a specific focus on the role of school-related stress., Methods: We used three longitudinal waves of questionnaire data collected annually from a sample of Swedish adolescents ( n = 1294; M age = 13.2 [range: 12-15 years], SD = .42; 46.8% girls). Using established measures, the students reported on their sleep duration, insomnia symptoms, and perceived school-stress (including stress of school performance, peer and teacher relations, attendance, and school-leisure conflict). We used latent class growth analysis (LCGA) to identify adolescents' sleep trajectories, and the BCH method to describe the characteristics of the adolescents in each trajectory., Results: We found four trajectories for adolescents' insomnia symptoms; (1) low insomnia (69%), (2) low-increasing (17%, 'emerging risk-group'), (3) high-decreasing (9%), (4) high-increasing (5%; 'risk-group'). For sleep duration, we found two trajectories; (1) ~8 h sufficient-decreasing (85%), (2) ~7 h insufficient- decreasing (15%; 'risk-group'). Adolescents in risk-trajectories were more likely to be girls and consistently reported higher levels of school stress, particularly regarding school performance and attending school., Conclusions: School stress was prominent among adolescents suffering from persistent sleep problems, especially insomnia, and deserves further attention., (© The Author(s) 2022. Published by Oxford University Press on behalf of Sleep Research Society.)

There is limited evidence surrounding the relationship between parent-set technology rules and adolescent sleep. This study had two aims: 1) to investigate the relationship between presence of and compliance to parent-set technology rules and adolescent sleep outcomes and daytime sleepiness; 2) to investigate if compliance, non-compliance, or the absence of rules could moderate the relationship between Fear of Missing Out (FoMO) and Bedtime Procrastination (BtP) on sleep outcomes and daytime sleepiness. A total of 711 adolescents aged 12-18 years old (46% Female, M age  = 15.1, SD  = 1.2) were recruited through secondary schools in South Australia. Participants completed a survey containing self-report measures about their sleep, daytime sleepiness, FoMO, BtP, the presence/absence of technology rules in their house, and their compliance to these rules. The study design was cross sectional. Results indicated that the presence of a parent-set technology rule was associated with earlier bedtimes regardless of compliance. Earlier lights out times and increased sleep duration were observed in adolescents who always complied to their rules compared to those who did not comply or did not have parent-set technology rules. BtP and FoMO were associated with later bedtimes, later lights out times, longer sleep onset latency, shorter sleep duration, and more daytime sleepiness. However, parent-set rules did not moderate the links between BtP/FoMO and adolescent sleep. Whilst longitudinal investigations are warranted to examine the directionality of these relationships, the present study suggests that parent-set technology rules may play an important role in protecting adolescent sleep., (© 2022 The Authors.)

This study evaluated a brief sleep intervention designed to improve the sleep, mood, and cognitive performance of professional electronic sports (esports) athletes from three major esports regions (i.e., Asia, North America, and Oceania). Fifty-six esports athletes from South Korea (N = 34), the United States (N = 7), and Australia (N = 15) completed the study. Participants completed an initial 2-week pre-intervention phase to establish a baseline, followed by a 2-week intervention phase that involved a group sleep education class, 1:1 session with a trained clinical psychologist, and daily biofeedback. A wrist activity monitor and daily sleep diary were used to monitor sleep during both phases, while at pre- and post-intervention, participants completed a battery of sleep and mood questionnaires and underwent cognitive performance testing. Sleep knowledge increased from pre- to post-intervention (d = 0.83 [95% CI −1.21, −0.43], p =< 0.001), while there were modest improvements in sleep diary estimates (i.e., sleep onset latency (Mdiff = −2.9 min, p = 0.02), sleep onset time (Mdiff = −12 min, p = 0.03), and sleep efficiency (Mdiff = 1.1%, p = 0.004)) and wrist activity monitor estimates (i.e., sleep onset time (Mdiff = −18 min, p = 0.01)). Insomnia severity scores decreased significantly (d = 0.47 [95% CI 0.08, 0.84], p = 0.001), while sleepiness scores increased but not meaningfully (d = 0.23 [95% CI −0.61, 0.14], p = 0.025). However, there was no significant change in mood (i.e., depression and anxiety) or cognitive performance scores (i.e., mean reaction time or lapses). Sleep interventions for esports athletes require further investigation. Future research should examine whether a stepped-care model, whereby increasing therapeutic input is provided as needed, can optimize sleep, mood, and cognitive performance outcomes.

Background: Adolescents with a late chronotype are at greater risk for mood disorders, risk-taking behaviors, school absenteeism, and lower academic achievement. As there are multiple causes for late chronotype, the field lacks studies on the relationship between mood, circadian phase, and phase angle of entrainment in late chronotype adolescents. Three objectives guide this explorative study: (1) to describe sleep, circadian phase, and phase angle of entrainment in late chronotype adolescents, (2) to explore how different levels of lateness are associated with sleep quality, sleep propensity, and mood, and (3) to investigate the influence of circadian phase on bedtime choice and sleep duration., Methods: Baseline data from 19 male adolescents (M = 16.4 ± 1.0 yrs), who were part of a larger intervention trial, were analyzed. Chronotype was measured with the Munich Chronotype Questionnaire, circadian timing via dim light melatonin onset (DLMO), and sleep habits with a 7-day sleep log. Further questionnaires assessed daytime sleepiness, sleep quality, and mood. Evening sleepiness and sustained attention were used as a proxy for evening sleep propensity., Results: On school nights, sleep duration averaged 7.78 h (±1.65), and 9.00 h (±1.42) on weekend nights. Mean DLMO was observed at 23.13 h (± 1.65), with a weekend phase angle of entrainment of 2.48 h. Regression fittings revealed a tendency for shorter phase angles with delayed DLMOs. Further analysis with chronotype subgroups revealed that this was only true for light and moderate late types, whereas extreme late types showed wide phase angles. Even though daytime sleepiness and sleep duration did not differ between subgroups, mood and sleep quality declined as lateness increased. Extreme late chronotypes experienced higher evening sleepiness, while slight late chronotypes showed higher evening attention. Chronotype but not DLMO predicted bedtime on school- and particularly weekend-nights., Conclusions: Our findings suggest that with increasing lateness, the likelihood of experiencing poor sleep quality and mood disorders increases. As DLMO did not predict bedtime, our data indicate that the factors contributing to a late chronotype are versatile and complex, particularly for extreme late types. Further studies involving a larger and gender-balanced sample are needed to confirm findings., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Lang, Richardson, Micic and Gradisar.)

Professional and colloquial sleep hygiene guidelines advise against evening physical activity, despite meta-analyses of laboratory studies concluding that evening exercise does not impair sleep. This study is the first to investigate the association between objectively measured evening physical activity and sleep within a real-world big-data sample. A total of 153,154 nights from 12,638 individuals aged 18-60 years ( M = 40.1 SD = 10.1; 44.5% female) were analyzed. Nighttime sleep and minutes of physical activity were assessed using Polar wearable devices for 14 consecutive days. Thirty minutes or more of moderate-to-near maximal physical activity during the 3 h before sleep onset were recorded in 12.4% of evenings, and were more frequent on weekdays than weekends (13.3 vs. 10.2% respectively, p < 0.001). Linear mixed modeling revealed that sleep efficiency was not significantly associated with evening physical activity, and that sleep duration was 3.4 min longer on average on nights following evenings in which participants engaged in 30 min or more of moderate-intense physical activity. Effects were found for sleep timing metrics, as evening physical activity was linked with earlier sleep onset and offset times (-13.7 and -9.3 min, respectively). Overall, these effects were greater- but still very small- on weekdays compared to weekends. The present study provides further evidence for the lack of meaningful links between sleep duration or quality and physical activity in the hours preceding sleep. Taken together with recent meta-analytic findings, these findings suggest that changes in public health recommendations are warranted regarding evening physical activity and its relation to sleep., Competing Interests: TK, LL, and KM were employees of Polar at the time of data collection and analysis. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Kahn, Korhonen, Leinonen, Martinmaki, Kuula, Pesonen and Gradisar.)

Esports is becoming increasingly professionalized, yet research on performance management is remarkably lacking. The present study aimed to investigate the sleep and mood of professional esports athletes. Participants were 17 professional esports athletes from South Korea ( N = 8), Australia ( N = 4), and the United States ( N = 5) who played first person shooter games (mean age 20 ± 3.5 years, 100% male). All participants wore a wrist-activity monitor for 7-14 days and completed subjective sleep and mood questionnaires. Participants had a median total sleep time of 6.8 h and a sleep efficiency of 86.4% per night. All participants had significantly delayed sleep patterns (median sleep onset 3:43 a.m. and wake time 11:24 a.m.). Participants had a median sleep onset latency of 20.4 min and prolonged wake after sleep onset of 47.9 min. Korean players had significantly higher depression scores compared to the other groups ( p < 0.01) and trained longer per day than the Australian or United States teams (13.4 vs. 4.8 vs. 6.1 h, respectively). Depression scores were strongly correlated with number of awakenings, wake after sleep onset, and daily training time ( p < 0.05). As the first pilot sleep study in the esports field, this study indicates that esports athletes show delayed sleep patterns and have prolonged wake after sleep onset. These sleep patterns may be associated with mood (depression) and training time. Sleep interventions designed specifically for esports athletes appear warranted.

Internet Gaming Disorder (IGD) is positioned in the appendix of the DSM-5 as a condition requiring further study. The IGD criteria refer to withdrawal symptoms, including irritability, anxiety, or sadness, that follow cessation of Internet gaming (APA, 2013). The aim of this study was to prospectively examine the nature of Internet gaming withdrawal symptoms, if they occur, under gaming abstinence conditions. This study employed a repeated-measures protocol to examine the cognitive-affective reactions of participants undertaking an 84-h Internet gaming abstinence period. The sample included individuals who met the IGD criteria as well as those who regularly played Internet games but did not meet the IGD criteria. Outcome variables included affect (positive and negative), psychological distress (depression, anxiety, stress), and Internet gaming withdrawal symptoms (craving/urge, thoughts about gaming, inability to resist gaming). A total of 24 participants ( M age  = 24.6 years, SD  = 5.8) were recruited from online gaming communities, and completed a series of online surveys before, during, and after abstaining from Massively Multiplayer Online (MMO) games. Both the IGD group and the non-IGD group experienced an abstinence-induced decline in withdrawal symptomatology, negative affect, and psychological distress. The IGD group experienced its largest decline in withdrawal symptomatology within the first 24 h of abstinence. These preliminary data suggest that gaming withdrawal symptoms may follow, at least initially, negative linear and quadratic trends. Further prospective work in larger samples involving longer periods of abstinence is required to verify and expand upon these observations.

The paper investigates the impact of text and background color combinations on the legibility of text presented on LCDs. The legibility of 56 elementary color combinations was tested by 308 participants. The first task required the participants to identify 21 uppercase alphabetic characters selected and presented in conformance with a Snellen chart in various color combinations. For each color combination, the number of correctly identified characters was recorded as a visual performance measure. In the second task, participants subjectively rated the legibility of color combinations on a ten-point Likert scale. The results show that neither the Le Courier legibility table nor the CRT legibility table is appropriate for LCDs. A new legibility table is proposed for LCDs where the highest ranked are contrastive color combinations with positive polarity whereas for CRT displays, the highest ranked are contrastive color combinations with negative polarity. The findings of this study can be used to determine the best possible color combinations when developing content displayed on LCDs., (Copyright © 2014 Elsevier Ltd and The Ergonomics Society. All rights reserved.)

Study Objectives: To describe the technology use and sleep quality of Americans, and the unique association between technology use and sleep disturbances., Methods: Interviews were conducted via random digit dialing (N = 750) or the Internet (N = 758). 1,508 Americans (13-64 years old, 50% males) matched to 2009 U.S. Census data provided complete interviews. The sample was further divided into adolescents (13-18 years, N = 171), young adults (19-29 years, N = 293), middle-aged adults (30-45 years, N = 469), and older adults (46-64 years, N = 565) to contrast different generations' technology use. Participants answered a 47-item semi-structured survey, including questions about their sleep habits, and the presence and use of technology in the hour before bed in the past 2 weeks., Results: Nine of 10 Americans reported using a technological device in the hour before bed (e.g., TVs the most popular; 60%). However, those under 30 years of age were more likely to use cell phones (72% of adolescents, 67% of young adults) than those over 30 years (36% of middle-aged, and 16% of older adults). Young adults' sleep patterns were significantly later than other age groups on both weekdays and weekend nights. Unlike passive technological devices (e.g., TV, mp3 music players), the more interactive technological devices (i.e., computers/laptops, cell phones, video game consoles) used in the hour before bed, the more likely difficulties falling asleep (β = 9.4, p < 0.0001) and unrefreshing sleep (β = 6.4, p < 0.04) were reported., Conclusions: Technology use near bedtime is extremely prevalent in the United States. Among a range of technologies, interactive technological devices are most strongly associated with sleep complaints.

Objectives: To examine the efficacy of self-report and parental report of adolescent sleep problems and compare these findings to the incidence of adolescents who fulfill clinical criteria for a sleep problem. Sleep and daytime functioning factors that predict adolescents' self-identification of a sleep problem will also be examined., Method: 308 adolescents (aged 13-17 years) from eight socioeconomically diverse South Australian high schools participated in this study. Participants completed a survey battery during class time, followed by a 7-day Sleep Diary and the Flinders Fatigue Scale completed on the final day of the study. Parents completed a Sleep, Medical, Education and Family History Survey., Results: The percentage of adolescents fulfilling one or more of the criteria for a sleep problem was inordinately high at 66%. Adolescent self-reporting a sleep problem was significantly lower than the adolescents who had one or more of the clinical criteria for a sleep problem (23.1% vs. 66.6%; χ(2) = 17.46, p<.001). Parental report of their adolescent having a sleep problem was significantly lower than adolescent self-report (14.3% vs. 21.1%, p<.001). Adolescents who reported unrefreshing sleep were 4.81 times more likely to report a sleep problem. For every hour that bedtime was delayed, the odds of self-reporting a sleep problem increased by 1.91 times, while each additional 10 minutes taken to fall asleep increased the odds 1.40 times., Conclusion: While many adolescents were found to have sleep patterns indicative of a sleep problem, only a third of this number self-identify having a sleep problem, while only a sixth of this number are indicated by parental report. This study highlights important features to target in future sleep education and intervention strategies for both adolescents and parents.

Study Objectives: To establish the extent to which the developmental changes in sleep timing experienced by Australian adolescents meet the International Classification of Sleep Disorders (ICSD-2) diagnostic criteria for delayed sleep phase disorder (DSPD), and whether adolescents with DSPD engage in poorer lifestyle choices, and are more impaired compared to good sleeping adolescents., Methods: Three-hundred seventy-four Australian adolescents (mean age 15.6 years, SD 1.0) participants completed a 7-day sleep diary, wore wrist actigraphy, and completed a battery of questionnaires to assess DSPD criteria., Results: The ICSD-2 criteria for DSPD were met by 1.1% (N = 4) of the adolescents sampled. The majority of adolescents (51.9%, N = 194) met one criterion, 14% (N = 52) of the adolescents met 2 criteria, while 33.2% (N = 124) did not fulfill any DSPD criteria. Despite having significantly delayed sleep timing, adolescents who met all criteria for DSPD reported similar lifestyle habits and daytime functioning. However, there were trends for greater alcohol and caffeine consumption, less sport participation, yet more time spent on extracurricular activities (i.e., learning to play a musical instruments for adolescents with DSPD., Conclusions: Despite the majority of adolescents reporting DSPD symptoms, only a small minority met full diagnostic criteria. Adolescents with DSPD reported similar lifestyle habits and daytime functioning to those with some or no symptoms. Future investigations of non-school-attending DSPD adolescents are needed to confirm the trends for lifestyle behaviors found in the present study.

Study Objectives: Many studies of adolescent insomnia use experience of insomnia-like symptoms to categorize "caseness." This is likely to lead to inflated prevalence and may have important ramifications for the research using individual symptoms to operationalize insomnia. The aim of the present study was to contrast the occurrence of insomnia symptoms with cases of insomnia diagnosed using criteria from the fourth edition of the Diagnostic and Statistical Manual for Mental Disorders (DSM-IV) and the second edition of the International Classification of Sleep Disorders (ICSD-II) in a sample of Australian adolescents., Methods: Data were collected from 384 representative Australian adolescents aged 13-18 years old (59% male). During school hours, adolescents completed a comprehensive questionnaire battery targeting insomnia criteria and then completed a sleep diary for 7 days., Results: Insomnia symptoms were frequently reported by adolescents (e.g., 34.6% for frequent sleep-related daytime consequences). The proportion of adolescents meeting the diagnositc criteria for insomnia was much smaller: 10.9% of adolescents were classified as having General Insomnia using ICSD-II criteria, and 7.8% were classified as having Primary Insomnia according to DSM-IV criteria. ICSD-II Psychophysiological Insomnia was observed in 3.4% of adolescents. Insomnia diagnoses did not vary according to age, gender, school grade, or socioeconomic status. Using the ICSD-II criteria for General Insomnia resulted in a significantly higher number of insomnia diagnoses than did DSM-IV criteria for Primary Insomnia (p < 0.001) and ICSD-II Psychophysiological Insomnia (p < 0.001)., Conclusions: These results reveal that approximately 3 adolescents in the average classroom of 30 are likely to meet the diagnostic criteria for insomnia, while many more will have insomnia symptoms. There were significant differences in prevalence rates, depending on how insomnia was operationalized.

Study Objectives: Video-game use before bedtime has been linked with poor sleep outcomes for adolescents; however, experimental evidence to support this link is sparse. The present study investigated the capacity of presleep video-game playing to extend sleep latency and reduce subjective feelings of sleepiness in adolescents. The arousing psychophysiologic mechanisms involved and the impact of presleep video-game playing on sleep architecture were also explored., Method: Thirteen male adolescent "evening types" (mean age = 16.6 years, SD = 1.1) participated in a counterbalanced, within-subjects design with experimental (active video gaming) and control (passive DVD watching) conditions. The experiment was conducted in the Flinders University Sleep Research Laboratory., Results: Relative to the control condition, presleep video-game playing increased sleep-onset latency (Z= 2.45, p= .01) and reduced subjective sleepiness (Z = 2.36, p = .02)-but only slightly. Video gaming was related to changes in cognitive alertness (as measured by a power: p < 0.01) but not physiologic arousal (as measured by heart rate: p > 0.05). Contrary to previous findings, sleep architecture was unaffected (both rapid eye movement and slow wave sleep: p > 0.05)., Conclusions: Results suggest the direct effect of presleep video-game playing on adolescent sleep may be more modest than previously thought, suggesting that surveys linking stimulating presleep activities to poor sleep need substantiating with empirical evidence.

Study Objectives: To evaluate the psychometric properties and clinical significance of a new scale for measuring daytime fatigue associated with insomnia: The Flinders Fatigue Scale (FFS)., Methods: The 7-item FFS was used in two separate studies. Study 1 was an on-line validation study involving 1093 volunteers (mean [SD] age = 38.6 [14.7] y, 626 poor sleepers, 467 good sleepers) in a cross-sectional design; Study 2 investigated the clinical sensitivity of the FFS on 113 insomnia patients (mean [SD] age = 48.3 [15.0] y) in response to a 5-week cognitive-behavior therapy for insomnia (CBT-I) program., Results: The FFS had an internal consistency of 0.91; it comprised a single factor, accounting for 67% of the total variance. Poor sleepers in Study 1 scored significantly higher than good sleepers on the FFS (p < 0.0001). In Study 2, significant reductions in FFS scores were found in response to CBT-I (p < 0.0001). These reductions in fatigue correlated with improvements on subjective sleep parameters (all p < 0.0001). The FFS showed good discriminant validity with the Epworth Sleepiness Scale., Conclusions: The Flinders Fatigue Scale is a brief, clinically sensitive measure with strong psychometric properties.

For good sleepers, distal skin temperatures (e.g., hands and feet) have been shown to increase when sleep is attempted. This process is said to reflect the body's action to lose heat from the core via the periphery. However, little is known regarding whether the same process occurs for insomniacs. It would be expected that insomniacs would have restricted heat loss due to anxiety when attempting sleep. The present study compared the finger skin temperature changes when sleep was attempted for 11 chronic primary insomniacs [mean age = 40.0 years (SD 13.3)] and 8 good sleepers [mean age = 38.6 years (SD 13.2)] in a 26-h constant routine protocol with the inclusion of multiple-sleep latency tests. Contrary to predictions, insomniacs demonstrated increases in finger skin temperature when attempting sleep that were significantly greater than those in good sleepers (P = 0.001), even though there was no significant differences in baseline finger temperature (P = 0.25). These significant increases occurred despite insomniacs reporting significantly greater sleep anticipatory anxiety (P < 0.0008). Interestingly, the core body temperature mesor of insomniacs (37.0 +/- 0.2 degrees C) was significantly higher than good sleepers (36.8 +/- 0.2 degrees C; P = 0.03). Whether insomniacs could have impaired heat loss that is masked by elevated heat production is discussed.