scholarly journals 0127 Relationship Between Sleep Metrics with Free-Living Glucose Concentrations and Glycemic Variability in Non-Diabetic Adults

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A50-A50
Author(s):  
J R Sparks ◽  
E E Kishman ◽  
X Wang
Keyword(s):  
South Carolina ◽  
Glucose Metabolism ◽  
Sleep Onset ◽  
Glycemic Variability ◽  
Sleep Efficiency ◽  
Sleep Diary ◽  
Poor Sleep ◽  
Free Living ◽  
Experimental Conditions ◽  
Time In Bed

Abstract Introduction Insufficient sleep and poor sleep quality have been associated with impaired glucose metabolism at fasting and under experimental conditions. Continuous glucose monitoring (CGM) measures glucose concentrations over an extended, free-living period that can be used to assess glycemic health. Relationships between CGM-assessed glucose concentrations and glycemic variability, an emerging glycemic health marker, with sleep metrics have yet to be elucidated. The purpose of this study was to examine the relationships between sleep metrics with glucose concentrations and glycemic variability in non-diabetic adults. Methods Twenty-four non-diabetic adults (age=46.0±5.8 years; BMI=32.2±5.7 kg/m2) completed actigraphy, sleep diary, and CGM over 7 consecutive days. Time-in-bed (TIB), total sleep time (TST), wake duration after sleep onset, and sleep efficiency [(TST÷TIB)×100%] were determined using actigraphy assisted with sleep diary input. Nightly variability of each sleep metric was calculated as standard deviation (SD) across all nights. Glucose concentrations at waking in the morning, and 1, 2, and 3 hours prior to waking, and diurnal, nocturnal, and 24-hour means were determined. Intra-day glycemic variability, including mean amplitude of glycemic excursions and continuous overlapping of net glycemic action of 1, 2, and 4 hours, and inter-day glycemic variability, mean of daily differences, were calculated. Pearson product correlations between sleep metrics with glucose concentrations and glycemic variability were performed. Results Average TIB and TST were 462.6±61.7 minutes and 403.3±59.7 minutes, respectively. TIB negatively correlated with glucose concentrations at 2 and 3 hours prior to waking (r=-0.42, p=0.04 and r=-0.42, p=0.04, respectively). Nightly variability in sleep efficiency positively correlated with waking, and 1, 2, and 3 hours prior to waking glucose concentrations (0.44≤r≤0.48, p≤0.03 for all). No sleep metrics correlated with glycemic variability measures (p≥0.10 for all). Conclusion Findings suggest a longer amount of sleep opportunity and more consistent sleep efficiency relate to better glucose metabolism in non-diabetic adults. Support American Heart Association 14BGIA20380706 and University of South Carolina Support to Promote Advancement of Research and Creativity Grant #11530-17-43917.

Cancer related insomnia and wireless technology: A pilot study.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e21645-e21645
Author(s):  
Brenda O'Connor ◽  
Pauline Ui Dhuibhir ◽  
Declan Walsh
Keyword(s):  
High Reliability ◽  
Objective Assessment ◽  
Sleep Onset ◽  
Work Productivity ◽  
Sleep Diary ◽  
Poor Sleep ◽  
Time In Bed ◽  
Concurrent Use ◽  
Bedside Monitor ◽  
Delayed Sleep

e21645 Background: Cancer related insomnia (CRI) includes difficulty with sleep onset, maintenance or non-restorative sleep. CRI is common with prevalence up to 95%. Consequences include cognitive dysfunction, fatigue, increased hospitalisation and lost work productivity. Early detection may help. CRI remains under-investigated as objective assessment has needed specialised laboratories. Mobile technology may provide a solution. This study aimed to determine the feasibility and acceptability of a wireless bedside monitor (SleepMinder [ResMed Sensor Technologies Ltd, Dublin]) to evaluate CRI. Methods: A prospective observational study recruited 10 consecutive hospice inpatients (IP) and 20 consecutive community participants (CP) with cancer. Participants used a wireless non-contact bedside sleep monitor for 3 consecutive nights. Three insomnia features were examined (sleep onset, maintenance, early awakening). Computerised algorithm-generated metrics were compared to visual inspection of the monitor sleep/activity report. Acceptability questionnaires were completed by patient, nurse and family. Results: The device successfully recorded sleep patterns in all 30 participants. No technical difficulties were experienced. IP: Mean age was 63 +/- 9 years. 7/10 had one or more insomnia features with delayed sleep onset most common. The monitor over-estimated Sleep Latency (77% nights), Duration (77% nights) and Final Awakening (63% nights). CP: Mean age was 64 +/- 10 years. 15/20 had one or more insomnia features with poor sleep maintenance most common. The monitor overestimated Sleep Duration (62% nights) and Final Awakening (45% nights). Lower levels were noted in CP as they spent less time in bed. Patients, nurses and family members reported high (100%) device acceptability. Conclusions: A wireless bedside monitor effectively measured sleep in seriously ill cancer patients in both inpatient and outpatient settings without the use of a sleep laboratory High reliability and acceptability supports routine clinical use Sensitivity of wakefulness detection was reduced as the device incorrectly identified sleep during awake but motionless periods Concurrent use of sleep diary and a monitor is recommended for comprehensive assessment

scholarly journals 1020 Sleep and Glycemic Control in Adults With Long-Standing Type 1 Diabetes and Hypoglycemia Unawareness

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A387-A388
Author(s):  
S K Malone ◽  
A J Peleckis ◽  
A I Pack ◽  
N Perez ◽  
G Yu ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Glycemic Control ◽  
Sleep Onset ◽  
Glucose Monitoring ◽  
Glycemic Variability ◽  
Sleep Efficiency ◽  
Hypoglycemia Unawareness ◽  
Time In Bed ◽  
Hba1c Levels

Abstract Introduction Nocturnal hypoglycemia is life threatening for individuals with type 1 diabetes (T1D) due to loss of hypoglycemia symptom recognition (hypoglycemia unawareness) and impaired glucose counterregulation. These individuals also show disturbed sleep, which may result from glycemic dysregulation. Whether use of a hybrid closed loop (HCL) insulin delivery system with integrated continuous glucose monitoring (CGM) designed for improving glycemic control, relates to better sleep across time in this population remains unknown. Methods Six adults (median age=58y,T1D duration=41y) participated in an 18-month ongoing clinical trial assessing the effectiveness of an HCL system. Sleep and glycemic control were measured concurrently using wrist actigraphs and CGM at baseline (1 week) and months 3 and 6 (3 weeks) following HCL initiation. BMI and hemoglobin A1c (HbA1c) were collected at all timepoints. Spearman’s correlations modeled associations between sleep, BMI, and glycemic control at each time point. Repeated ANOVAs modeled sleep and glycemic control changes from baseline to 3 months and to 6 months. Results Sleep and glycemic control indices showed significant associations at baseline and 3 months. More time-in-bed and later sleep offset related to higher HbA1c levels at baseline. Later sleep onset, midpoint and offset, and greater sleep efficiency associated with greater %time with hyperglycemia (glucose >180 mg/dL) or hypoglycemia (glucose <70 mg/dL) at baseline and 3 months. Longer sleep duration and greater sleep efficiency related to greater %time with hyperglycemia at 3 months. At 3 months, more wake after sleep onset associated with lower HbA1c levels and longer nocturnal awakenings and more sleep fragmentation associated with less glycemic variability. While both sleep and glycemic control improved from baseline to 3 and 6 months, these were not statistically significant. Conclusion Various dimensions of actigraphic sleep related to concurrently estimated glycemic indices indicative of poorer glycemic control and HbA1c across time in adults with long-standing T1D and hypoglycemia unawareness. Support This work was supported by NIH R01DK117488 (NG), R01DK091331 (MRR), and K99NR017416 (SKM).

Sleep of Wheelchair Rugby Athletes: Training, Rest and Competition

2020 ◽  
Author(s):  
Victor Sanz-Milone ◽  
Fernanda V. Narciso ◽  
Andressa da Silva ◽  
Milton Misuta ◽  
Marco Túlio de Mello ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Sleep Onset ◽  
Sleep Efficiency ◽  
Sleep Diary ◽  
Poor Sleep ◽  
Subjective Sleep Quality ◽  
Wheelchair Rugby ◽  
Rest Periods ◽  
Rugby Players

AbstractThe aim of this study was to evaluate the sleep-wake cycle of wheelchair rugby athletes during the pre-season compared to in-season. Wheelchair Rugby athletes wore an actigraph monitor during two respective 10-day periods: 1) pre-season and 2) in-season, each of which comprised three training days, three rest days, and four competition days, respectively. In addition, the players completed questionnaires regarding sleepiness, subjective quality of sleep, and chronotype, as well as the use of the sleep diary along with the actigraph measurements (20 days). The wheelchair rugby athletes had poor subjective sleep quality in both stages observed by sleep efficiency below 85% (ES 0.31) and high score in the Pittsburgh questionnaire (effect size-ES 0.55), the actigraphy results presented an increase of sleep latency (ES 0.47), and wake after sleep onset (ES 0.42). When comparing the athlete’s routine, the competition days, demonstrated a reduction in the total time of sleep and the sleep efficiency, in addition to an increase in wakefulness after sleep onset when compared with the training and rest periods. As a result, the wheelchair rugby players did not describe a pattern of sleep-wake cycle during different training phases, as well as poor sleep quality.

scholarly journals 0519 Mindfulness Based Therapy for Insomnia Improves Objective Markers of Sleep in the Elderly: Preliminary Data from the Mindfulness Sleep Therapy (MIST) Study

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A198-A199
Author(s):  
K F Wong ◽  
F Perini ◽  
S L Henderson ◽  
J Teng ◽  
Z Hassirim ◽  
...  
Keyword(s):  
Preliminary Data ◽  
Repeated Measures ◽  
Mixed Model ◽  
Controlled Trial ◽  
Sleep Onset ◽  
Sleep Diary ◽  
Control Group ◽  
Poor Sleep ◽  
Sleep Onset Latency ◽  
Time In Bed

Abstract Introduction Mindfulness-based treatment for insomnia (MBTI) is a viable intervention for improving poor sleep. We report preliminary data from an ongoing pre-registered, randomized controlled trial which investigates the effect of MBTI on elderly adults. Methods Participants above 50 years old with PSQI ≥ 5 were recruited and randomised into either MBTI or an active control group (Sleep hygiene education and exercise program, SHEEP) in sequential cohorts with about 20 participants per cohort (10 per group). Before and after the intervention, 1 night of portable polysomnography (PSG) and 1 week of actigraphy (ACT) and sleep diary (DIARY) data were collected. We report the ACT and DIARY results of the first 3 cohorts (n = 46, male = 23, mean age = 62.3, std = 6.3) and PSG data of the first 2 cohorts (n = 29, male = 12, mean age = 62.5, std = 5.7). Time in bed (TIB), total sleep time (TST), sleep onset latency (SOL), wake after sleep onset (WASO), and sleep efficiency (SE) were analysed with mixed-model repeated-measures ANOVA. Results We observed increases in TIBDIARY (F1,44 = 5.151, p < .05) and SEDIARY (F1,44 = 22.633, p < .0001), and significant reductions in SOLDIARY (F1,44 = 7.031, p < .05) and WASODIARY (F1,39 = 7.411, p < .05). In the actigraphy data, we found a significant interaction in SOLACT (F1,39 = 4.273, p < .05) with an increase in SHEEP SOLACT (t18= 2.36, p < .05). Significant reductions were also observed in WASOACT (F1,44 = 16.459, p < .0001) Finally, we observed a reduction in SOLPSG (F1,26 = 5.037, p <. 05). All other tests were non-significant. Conclusion Preliminary results suggest that both interventions lead to improvements in sleep with more pronounced effects in subjective sleep reports. Objective sleep data suggest that improvements in sleep is a result of improved sleep quality and not simply extending sleep opportunity. These preliminary data shows that MBTI may be a promising intervention for elderly individuals with sleep difficulties. Support This study was supported by an award from the 7th grant call of the Singapore Millennium Foundation Research Grant Programme

Mindfulness and Behaviour Therapy for Insomnia: An Assessment of Treatment Effect in a Sleep Disorders Clinic Population with Insomnia

2020 ◽  
pp. 1-15
Author(s):  
Allie Peters ◽  
John Reece ◽  
Hailey Meaklim ◽  
Moira Junge ◽  
David Cunnington ◽  
...  
Keyword(s):  
Sleep Disorders ◽  
Treatment Effect ◽  
Sleep Onset ◽  
Sleep Efficiency ◽  
Health Concern ◽  
Sleep Diary ◽  
Sleep Onset Latency ◽  
Subjective Sleep ◽  
Sleep Parameters

Abstract Insomnia is a common major health concern, which causes significant distress and disruption in a person's life. The objective of this paper was to evaluate a 6-week version of Mindfulness-Based Therapy for Insomnia (MBTI) in a sample of people attending a sleep disorders clinic with insomnia, including those with comorbidities. Thirty participants who met the DSM-IV-TR diagnosis of insomnia participated in a 6-week group intervention. Outcome measures were a daily sleep diary and actigraphy during pre-treatment and follow-up, along with subjective sleep outcomes collected at baseline, end-of-treatment, and 3-month follow-up. Trend analyses showed that MBTI was associated with a large decrease in insomnia severity (p < .001), with indications of maintenance of treatment effect. There were significant improvements in objective sleep parameters, including sleep onset latency (p = .005), sleep efficiency (p = .033), and wake after sleep onset (p = .018). Significant improvements in subjective sleep parameters were also observed for sleep efficiency (p = .005) and wake after sleep onset (p < .001). Overall, this study indicated that MBTI can be successfully delivered in a sleep disorders clinic environment, with evidence of treatment effect for both objective and subjective measures of sleep.

324 Naturalistic Characterization of Sleep in Chronic Insomnia Using a Non-Contact Sleep Measurement Device

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A130-A130
Author(s):  
Devon Hansen ◽  
Mary Peterson ◽  
Roy Raymann ◽  
Hans Van Dongen ◽  
Nathaniel Watson
Keyword(s):  
Sleep Onset ◽  
Contact Device ◽  
Chronic Insomnia ◽  
Poor Sleep ◽  
Measurement Device ◽  
Home Setting ◽  
Time In Bed ◽  
Sleep Measurement ◽  
Measurement Devices

Abstract Introduction Individuals with insomnia report poor sleep quality and non-restorative sleep, and often exhibit irregular sleep patterns over days and weeks. First night effects and logistical challenges make it difficult to measure these sleep characteristics in the laboratory. Also, sensitivity to sleep disruption from obtrusive measurement devices confounds sleep measurements in people with insomnia in their naturalistic setting. Non-contact sleep measurement devices have the potential to address these issues and enable ecologically valid, longitudinal characterization of sleep in individuals with insomnia. Here we use a non-contact device – the SleepScore Max (SleepScore Labs) – to assess the sleep of individuals with chronic insomnia, compared to healthy sleeper controls, in their home setting. Methods As part of a larger study, 13 individuals with chronic insomnia (ages 25-60y, 7 males) and 8 healthy sleeper controls (ages 21-46y, 6 females) participated in an at-home sleep monitoring study. Enrollment criteria included an age range of 18-65y and, for the insomnia group, ICSD-3 criteria for chronic insomnia with no other clinically relevant illness. Participants used the non-contact sleep measurement device to record their sleep periods each night for 8 weeks. Sleep measurements were analyzed for group differences in both means (characterizing sleep overall) and within-subject standard deviations (characterizing sleep variability across nights), using mixed-effects regression controlling for systematic between-subject differences. Results Based on the non-contact sleep measurements, individuals with chronic insomnia exhibited greater variability in bedtime, time in bed, total sleep time, sleep latency, total wake time across time in bed, wakefulness after sleep onset, sleep interruptions, and estimated light sleep, compared to healthy sleeper controls (all F&gt;5.7, P&lt;0.05). No significant differences were found for group averages and for variability in estimated deep and REM sleep. Conclusion In this group of individuals with chronic insomnia, a non-contact device used to characterize sleep naturalistically captured enhanced variability across nights in multiple aspects of sleep stereotypical of sleep disturbances in chronic insomnia, differentiating the sample statistically significantly from healthy sleeper controls. Support (if any) NIH grant KL2TR002317; research devices provided by SleepScore Labs.

scholarly journals A study on sleep apnea in patients with abnormal sewda type of depression

2020 ◽  
pp. 1-8
Author(s):  
Aman Gul ◽  
Nassirhadjy Memtily ◽  
Pirdun Mijit ◽  
Palidan Wushuer ◽  
Ainiwaer Talifu ◽  
...  
Keyword(s):  
Rem Sleep ◽  
Sleep Onset ◽  
Sleep Time ◽  
Sleep Efficiency ◽  
Control Group ◽  
Poor Sleep ◽  
Sleep Structure ◽  
Maintenance Rate ◽  
Sleep Maintenance ◽  
Insomnia Symptoms

Objective: To preliminarily investigate the clinical features and PSG in abnormal sewda-type depressive insomnia. Methods: A total of 127 abnormal sewda-type depressive insomnia patients were evaluated with overnight PSG, and 32 normal participants were compared. Results: Patients with abnormal sewda-type depressive insomnia were compared with the control group; the sleep symptoms showed a long incubation period of sleep, low sleep maintenance rate, low sleep efficiency and poor sleep quality as well as daytime dysfunction. At process and continuity of sleep: Total sleep time, sleep efficiency, sleep maintenance rate in abnormal sewda-type depressive insomnia group were shorter than the control group. Wake after sleep onset, and sleep latency were longer than the control group. At sleep structure: N1 ratio and N2 ratio in depressive insomnia group were longer than the control group, N3 ratio and REM sleep ratio shorter than the control group. At REM index: REM latency, REM cycles, and REM sleep time were shorter than the control group. Conclusion: Insomnia symptoms in abnormal sewda-type depression comorbid insomnia patients were similar to the ordinary insomnia patients. The PSG characteristics had significant changes in sleep process, sleep structure and REM indicators. The severity of the abnormal sewda-type depression was closely related to REM indicators. Change of REM sleep characteristics may be the specificity, and these could be taken as reference in diagnosis and identification of abnormal sewda-type depressive insomnia.

Nocturnal Sleep–Wake Parameters of Adolescents at Home Following Cancer Chemotherapy

2011 ◽  
Vol 14 (3) ◽  
pp. 236-241 ◽  
Author(s):  
Amy J. Walker ◽  
Kyle P. Johnson ◽  
Christine Miaskowski ◽  
Vivian Gedaly-Duff
Keyword(s):  
Sleep Duration ◽  
Cancer Chemotherapy ◽  
Sleep Onset ◽  
Sleep Diary ◽  
Nocturnal Sleep ◽  
Wake Time ◽  
Targeted Interventions ◽  
Time In Bed ◽  
Wrist Actigraphy ◽  
At Home

Purpose: The purpose of this descriptive, longitudinal study was to describe objective nocturnal sleep–wake parameters of adolescents at home after receiving chemotherapy in the hospital or outpatient clinic and explore differences in sleep variables by age, gender, and corticosteroid use. Methods: We collected 7 days of wrist actigraphy and sleep diary data from 48 adolescents (10–19 years) who were receiving cancer chemotherapy for a primary or secondary cancer or a relapse. The actigraphic sleep variables included rest interval (i.e., time in bed), sleep onset, sleep offset, sleep duration, total sleep time (TST), wake after sleep onset (WASO), and %WASO. Results: Of the 48 adolescents, 38 had at least five nights of scored actigraphy and were included in analyses. Older (13–18 years) adolescents went to bed later and had fewer minutes of TST than younger adolescents (10–12 years). Exploratory analyses revealed no differences between adolescents who were taking oral corticosteroids (i.e., prednisone, dexamethasone) and those who were not or between males and females. Conclusion: These adolescents had sleep durations that met or exceeded the recommended sleep duration for their age groups but experienced significant WASO. Further research is needed to estimate sleep needs of adolescents during chemotherapy and determine factors that contribute to nocturnal wake-time so that targeted interventions can be designed to improve sleep quality.

scholarly journals 1134 Light Exposure At Daytime On Sleep Quality In Stroke Patient During Rehabilitation

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A432-A432
Author(s):  
W Liao ◽  
S Lin ◽  
N Meng ◽  
H Tin ◽  
S Tsai ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Stroke Patient ◽  
Light Exposure ◽  
Sleep Onset ◽  
Bright Light ◽  
Sleep Efficiency ◽  
Poor Sleep ◽  
Cross Sectional ◽  
Melatonin Concentration ◽  
Improve Sleep Quality

Abstract Introduction Lights maintain the day and night rhythm to set patients’ “wake-up cycle” and to stabilize their physiological functions, which may be expected to improve sleep. This study was aimed to investigate the relations between sleep quality and daytime light exposure in stroke patient during rehabilitation. Methods A cross-sectional study design was adopted and 120 stroke patients were recruited from rehabilitation wards of two medical centers and 116 patients completed this study. Research instruments including the Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale, Sleep Log, and Somnowatch (Germany) for actigaphy sleep and light were used to collect data and urinary melatonin concentration were measured. Results 47.4% of the patients had poor sleep quality (PSQI&gt;5), 74.1% had actigraphic sleep efficiency less than 85%, and 90.5% waked more than 30 minutes after sleep onset. The average exposure time at lower level light (≤149 lux) were 288.8 minutes, accounting for 48% of the day (8:00-18:00). Compared to lower light exposure group (less than 319.5 min at &gt;150 lux), those who exposed to higher level light (more than 319.5 min at &gt;150 lux) had increased 52.1 minutes in actigraphic total sleep time (TST, t=-2.134, p=0.035), increased 8% in actigraphic sleep efficiency (SE, t=-2.053, p=0.042), and decreased 41.1 minutes in actigraphic wake-after-sleep-onset (WASO, t=2.209, p=0.029). Urinary melatonin concentration increased 52.7 pg/ml, but not statistically significant (t=-1.277, p=0.205). Result of multiple regression analysis showed that after controlling for age, gender, post-stroke complications, and environmental interference, time of bright light exposure significantly affected subjective sleep satisfaction (p=0.014), TST (p=0.04), SE (p=0.041), and WASO (p=0.026). Conclusion Increasing time of bright illumination (≥150 lux) during daytime may improve sleep quality. Results of this study provide empirical references for non-drug intervention to improve sleep quality in patients with stroke. Support This study was supported by the Ministry of Science and Technology, MOST 105-2628-B-040 -005 -MY2.

Night Games and Sleep: Physiological, Neuroendocrine, and Psychometric Mechanisms

2018 ◽  
Vol 13 (7) ◽  
pp. 867-873 ◽  
Author(s):  
Laura E. Juliff ◽  
Jeremiah J. Peiffer ◽  
Shona L. Halson
Keyword(s):  
Core Temperature ◽  
Sleep Onset ◽  
Sleep Efficiency ◽  
Poor Sleep ◽  
Sleep Onset Latency ◽  
Sleep Difficulty ◽  
Sleep Complaints ◽  
Temperature State ◽  
Psychometric Measures ◽  
Cortisol Responses

Context: Night games are a regular occurrence for team-sport athletes, yet sleep complaints following night competitions are common. The mechanisms responsible for reported sleep difficulty in athletes are not understood. Methods: An observational crossover design investigating a night netball game and a time-matched rest day in 12 netball athletes was conducted to ascertain differences in physiological (core temperature), psychometric (state and trait), and neuroendocrine (adrenaline, noradrenaline, and cortisol) responses. Results: Following the night game, athletes experienced reduced sleep durations, lower sleep efficiency, early awakenings, and poorer subjective sleep ratings compared with the rest day. No differences were found between core temperature, state psychometric measures, and cortisol at bedtime. Adrenaline and noradrenaline concentrations were elevated compared with the time-matched rest day prior to (26.92 [15.88] vs 12.90 [5.71] and 232.6 [148.1] vs 97.83 [36.43] nmol/L, respectively) and following the night game (18.67 [13.26] vs 11.92 [4.56] and 234.1 [137.2] vs 88.58 [54.08] nmol/L, respectively); however, the concentrations did not correlate to the sleep variables (duration, efficiency, and sleep-onset latency). A correlation (rs = −.611) between sleep efficiency and hyperarousal (trait psychometric measure) was found. Conclusions: Athletes experienced poor sleep following a night game. Furthermore, results suggest that athletes who have a tendency toward a high trait arousal may be more susceptible to sleep complaints following a night game. These data expand knowledge and refute frequently hypothesized explanations for poor sleep following night competition. The results may also help support staff and coaches target strategies for individual athletes at a higher risk of sleep complaints.

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