scholarly journals 0954 Sleep of Gifted Children Using Actigraphy

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A362-A363
Author(s):  
L Bastien ◽  
R Théoret ◽  
R Godbout
Keyword(s):  
Normative Data ◽  
Intellectual Development ◽  
Total Sleep Time ◽  
Sleep Onset ◽  
Sleep Time ◽  
Gifted Children ◽  
Typically Developing ◽  
Relational Development ◽  
Wake Time ◽  
Definition Of

Abstract Introduction Intellectual giftedness is characterized by an intellectual development superior to peers (QI > 120) while emotional and relational development corresponds to the age norms. Anecdotal reports from parents suggest that they sleep poorly compared to typically developing (TD) peers. We measured sleep of gifted children using actigraphy. Methods Thirteen gifted children (10 boys, mean age = 10.58, SD = 2.11) were studied. Giftedness was identified using Renzulli’s three-factor definition of giftedness conceptualise in terms of above-average ability and high levels of task commitment (refined or focused form of motivation), and creativity. Sleep was measured with actigraphy for two weeks and compared to normative data from TD children using T-tests. Results Compared to normative data from TD children, gifted children had a significantly shorter sleep latency (p < 0.001), longer sleep periods (p = 0.001), shorter total sleep time and more wake time after sleep onset (p = 0.03). These differences were present both on week nights and weekend nights except that total sleep time was shorter in gifted children only during weekends (p < 0.001). Conclusion These data suggest that gifted children sleep poorly, and more so upon weekends. Whether this correlates with daytime functioning remains to be determined. Support N/A

scholarly journals Study of correlation between perceived sleep disturbances in depressed patients with objective changes in sleep architecture using polysomnography before and after antidepressant therapy

2020 ◽  
Vol 8 (7) ◽  
pp. 2551
Author(s):  
Ganesh Ingole ◽  
Harpreet S. Dhillon ◽  
Bhupendra Yadav
Keyword(s):  
Sleep Disturbances ◽  
Total Sleep Time ◽  
Antidepressant Treatment ◽  
Sleep Onset ◽  
Sleep Time ◽  
Sleep Efficiency ◽  
Sleep Architecture ◽  
Wake Time ◽  
Depressed Patients ◽  
Before And After

Background: A prospective cohort study to correlate perceived sleep disturbances in depressed patients with objective changes in sleep architecture using polysomnography (PSG) before and after antidepressant therapy.Methods: Patients were recruited into the study after applying strict inclusion and exclusion criterion to rule out other comorbidities which could influence sleep. A diagnosis of Depressive episode was made based on ICD-10 DCR. Psychometry, in the form of Beck Depressive inventory (BDI) and HAMD (Hamilton depression rating scale) insomnia subscale was applied on Day 1 of admission. Patients were subjected to sleep study on Day 03 of admission with Polysomnography. Patients were started on antidepressant treatment post Polysomnography. An adequate trial of antidepressants for 08 weeks was administered and BDI score ≤09 was taken as remission. Polysomnography was repeated post remission. Statistical analysis was performed using Kruskal Wallis test and Pearson correlation coefficient.Results: The results showed positive (improvement) polysomnographic findings in terms of total sleep time, sleep efficiency, wake after sleep onset, percentage wake time and these findings were statistically significant. HAM-D Insomnia subscale was found to correlate with total sleep time, sleep efficiency, wake after sleep onset, total wake time and N2 Stage percentage.Conclusions: Antidepressant treatment effectively improves sleep architecture in Depressive disorder and HAM-D Insomnia subscale correlates with objective findings of total sleep time, sleep efficiency, wake after sleep onset, total wake time and duration of N2 stage of NREM.

scholarly journals Sleep Parameters in Short Daily versus Conventional Dialysis: An Actigraphic Study

2017 ◽  
Vol 2017 ◽  
pp. 1-6
Author(s):  
Ludimila D’Avila e Silva Allemand ◽  
Otávio Toledo Nóbrega ◽  
Juliane Pena Lauar ◽  
Joel Paulo Russomano Veiga ◽  
Einstein Francisco Camargos
Keyword(s):  
Total Sleep Time ◽  
Linear Regression Analysis ◽  
Sleep Onset ◽  
Objective Measure ◽  
Sleep Time ◽  
Cross Sectional ◽  
Convenience Sample ◽  
Wake Time ◽  
Daily Dialysis ◽  
Sleep Parameters

Previous studies have observed worse sleep quality in patients undergoing conventional dialysis as compared to daily dialysis. Our aim was to compare the sleep parameters of patients undergoing daily or conventional dialysis using an objective measure (actigraphy). This cross-sectional study was performed in three dialysis centers, including a convenience sample (nonprobability sampling) of 73 patients (36 patients on daily hemodialysis and 37 patients on conventional hemodialysis). The following parameters were evaluated: nocturnal total sleep time (NTST), expressed in minutes; wake time after sleep onset (WASO), expressed in minutes; number of nighttime awakenings; daytime total sleep time (DTST), expressed in minutes; number of daytime naps; and nighttime percentage of sleep (% sleep). The Mini-Mental State Examination and the Beck Depression Inventory were also administered. The mean age was 53.4  ±  17.0 years. After adjustment of confounding factors using multiple linear regression analysis, no difference in actigraphy parameters was detected between the groups: NTST (p=0.468), WASO (p=0.88), % sleep (p=0.754), awakenings (p=0.648), naps (p=0.414), and DTST (p=0.805). Different from previous studies employing qualitative analysis, the present assessment did not observe an influence of hemodialysis modality on objective sleep parameters in chronic renal patients.

scholarly journals P129 A substantial percentage of patients with Chronic Insomnia do not appreciably increase Total Sleep Time after Cognitive Behavioural Therapy for Insomnia

2021 ◽  
Vol 2 (Supplement_1) ◽  
pp. A63-A63
Author(s):  
H Scott ◽  
J Cheung ◽  
A Muench ◽  
H Ivers ◽  
M Grandner ◽  
...  
Keyword(s):  
Total Sleep Time ◽  
Sleep Onset ◽  
Severity Index ◽  
Randomised Clinical Trial ◽  
Sleep Time ◽  
Early Morning ◽  
Behavioural Therapy ◽  
Sleep Diary ◽  
Wake Time ◽  
Sleep Continuity

Abstract Introduction Total sleep time (TST) does not exceed baseline for the majority of patients after CBT-I. However by follow-up, TST increases by almost 1 hour on average. The current study investigated the extent to which this TST improvement is common and assessed for baseline predictors of increased TST after CBT-I. Methods This study is an archival analysis of data from a randomised clinical trial comparing acute CBT-I to acute CBT-I plus maintenance therapy (N = 80). The percent of patients that exceeded baseline TST by ≥30 minutes was assessed at post treatment and 3, 6, 12, and 24 months following treatment. Linear mixed models were conducted to assess the effect of patient demographics (age, sex, ethnicity, marital status), and baseline Sleep Diary-reported sleep continuity and Insomnia Severity Index (ISI) scores on changes in TST. Results 17% of patients achieved an appreciable increase in TST by treatment end, and this proportion only increased to 58% over time. Sleep Diary-reported sleep latency, wake after sleep onset, early morning awakenings, total wake time, TST, and sleep efficiency at baseline were associated with greater increases in TST after CBT-I (interaction ps < .03). Demographics and ISI scores were not significant predictors (interaction ps > .07). Conclusion A substantial proportion of patients do not appreciably increase TST after CBT-I, but patients with more severe sleep continuity disturbances at baseline exhibited the largest improvements. Whether all patients could increase their TST even further after CBT-I is a topic for further investigation.

scholarly journals The feasibility and reliability of actigraphy to monitor sleep in intensive care patients: an observational study

Critical Care ◽  
2021 ◽  
Vol 25 (1) ◽  
Author(s):  
L. J. Delaney ◽  
E. Litton ◽  
K. L. Melehan ◽  
H.-C. C. Huang ◽  
V. Lopez ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Observational Study ◽  
Total Sleep Time ◽  
Sleep Time ◽  
Moderate Level ◽  
Sleep Monitoring ◽  
Clinical Trial Registration ◽  
Wake Time ◽  
Intensive Care Patients

Abstract Background Sleep amongst intensive care patients is reduced and highly fragmented which may adversely impact on recovery. The current challenge for Intensive Care clinicians is identifying feasible and accurate assessments of sleep that can be widely implemented. The objective of this study was to investigate the feasibility and reliability of a minimally invasive sleep monitoring technique compared to the gold standard, polysomnography, for sleep monitoring. Methods Prospective observational study employing a within subject design in adult patients admitted to an Intensive Care Unit. Sleep monitoring was undertaken amongst minimally sedated patients via concurrent polysomnography and actigraphy monitoring over a 24-h duration to assess agreement between the two methods; total sleep time and wake time. Results We recruited 80 patients who were mechanically ventilated (24%) and non-ventilated (76%) within the intensive care unit. Sleep was found to be highly fragmented, composed of numerous sleep bouts and characterized by abnormal sleep architecture. Actigraphy was found to have a moderate level of overall agreement in identifying sleep and wake states with polysomnography (69.4%; K = 0.386, p < 0.05) in an epoch by epoch analysis, with a moderate level of sensitivity (65.5%) and specificity (76.1%). Monitoring accuracy via actigraphy was improved amongst non-ventilated patients (specificity 83.7%; sensitivity 56.7%). Actigraphy was found to have a moderate correlation with polysomnography reported total sleep time (r = 0.359, p < 0.05) and wakefulness (r = 0.371, p < 0.05). Bland–Altman plots indicated that sleep was underestimated by actigraphy, with wakeful states overestimated. Conclusions Actigraphy was easy and safe to use, provided moderate level of agreement with polysomnography in distinguishing between sleep and wakeful states, and may be a reasonable alternative to measure sleep in intensive care patients. Clinical Trial Registration number ACTRN12615000945527 (Registered 9/9/2015).

scholarly journals P062 Sleep parameter validation of a home-based ballistocardiograph sleep tracker

2021 ◽  
Vol 2 (Supplement_1) ◽  
pp. A41-A42
Author(s):  
M Kholghi ◽  
I Szollosi ◽  
M Hollamby ◽  
D Bradford ◽  
Q Zhang
Keyword(s):  
Total Sleep Time ◽  
Sleep Onset ◽  
Sleep Time ◽  
Daily Routine ◽  
Sleep Onset Latency ◽  
Onset Latency ◽  
Sleep Monitoring ◽  
Significant Discrepancy ◽  
Home Based ◽  
Wake Detection

Abstract Introduction Consumer home sleep trackers are gaining popularity for objective sleep monitoring. Amongst them, non-wearable devices have little disruption in daily routine and need little maintenance. However, the validity of their sleep outcomes needs further investigation. In this study, the accuracy of the sleep outcomes of EMFIT Quantified Sleep (QS), an unobtrusive and non-wearable ballistocardiograph sleep tracker, was evaluated by comparing it with polysomnography (PSG). Methods 62 sleep lab patients underwent a single clinical PSG and their sleep measures were simultaneously collected through PSG and EMFIT QS. Total Sleep Time (TST), Wake After Sleep Onset (WASO), Sleep Onset Latency (SOL) and average Heart Rate (HR) were compared using paired t-tests and agreement analysed using Bland-Altman plots. Results EMFIT QS data loss occurred in 47% of participants. In the remaining 33 participants (15 females, with mean age of 53.7±16.5), EMFIT QS overestimated TST by 177.5±119.4 minutes (p&lt;0.001) and underestimated WASO by 44.74±68.81 minutes (p&lt;0.001). It accurately measured average resting HR and was able to distinguish SOL with some accuracy. However, the agreement between EMFIT QS and PSG on sleep-wake detection was very low (kappa=0.13, p&lt;0.001). Discussion A consensus between PSG and EMFIT QS was found in SOL and average HR. There was a significant discrepancy and lack of consensus between the two devices in other sleep outcomes. These findings indicate that while EMFIT QS is not a credible alternative to PSG for sleep monitoring in clinical and research settings, consumers may find some benefit from longitudinal monitoring of SOL and HR.

Relations Between Sleep and Temperament in Preschool Children With ADHD

2018 ◽  
Vol 24 (4) ◽  
pp. 535-544 ◽  
Author(s):  
Maria Grazia Melegari ◽  
Stefania Sette ◽  
Elena Vittori ◽  
Luca Mallia ◽  
Alessandra Devoto ◽  
...  
Keyword(s):  
Sleep Onset ◽  
Sleep Time ◽  
Child Temperament ◽  
Novelty Seeking ◽  
Typically Developing ◽  
Temperament And Character Inventory ◽  
Children With Adhd ◽  
Wrist Actigraphy ◽  
Adhd Children ◽  
Character Inventory

Objective: The objective of this study was to assess the links between temperament and sleep in a group of preschoolers with ADHD. Method: Twenty-five ADHD ( M = 5.37 years, SD = 1.09) and 22 typically developing (TD; M = 5.10, SD = 1.18) preschoolers participated in the study. Sleep was assessed with the Sleep Disturbance Scale and wrist actigraphy. The Preschool Temperament and Character Inventory (PsTCI) was used to evaluate the child temperament. Results: ADHD children showed a temperamental profile characterized by higher novelty seeking, lower persistence, self-directness, and cooperativeness and marginally lower harm avoidance (HA) compared with controls. HA was associated negatively to wakefulness after sleep onset and sleep fragmentation and positively with sleep efficiency and sleep time. Reward dependence was negatively associated with wake episode length. Conclusion: Sleep and temperament are correlated in preschoolers with ADHD and temperament might represent an intermediate endophenotype underlying the relation between ADHD and sleep disorders.

Sleep disturbance and quality of life in Rheumatoid Arthritis: a prospective mobile health study (Preprint)

2021 ◽  
Author(s):  
John McBeth ◽  
William G Dixon ◽  
Susan Mary Moore ◽  
Bruce Hellman ◽  
Ben James ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Rheumatoid Arthritis ◽  
Sleep Disturbance ◽  
Mobile Health ◽  
Sleep Disturbances ◽  
Total Sleep Time ◽  
Sleep Onset ◽  
Sleep Time ◽  
Domain Scores

BACKGROUND Sleep disturbance and poor health related quality of life (HRQoL) are common in people with rheumatoid arthritis (RA). Sleep disturbances, such as less total sleep time, more waking periods after sleep onset, and higher levels of non-restorative sleep, may be a driver of HRQoL. However, understanding if these sleep disturbances reduce HRQoL has, to date, been challenging due to the need to collect complex time-varying data in high resolution. Such data collection has now been made possible by the widespread availability and use of mobile health (mHealth) technologies. OBJECTIVE In a mobile health (mHealth) study we tested whether sleep disturbance (both absolute values and variability) caused poor HRQoL. METHODS The Quality of life, sleep and rheumatoid arthritis (QUASAR) study was a prospective mHealth study of adults with RA. Participants completed a baseline questionnaire, and for 30 days wore a triaxial accelerometer to objectively assess sleep, and provided daily reports via a smartphone app of sleep (Consensus Sleep Diary (CSD)), pain, fatigue, mood, and other symptoms. Participants completed the World Health Organization Quality of Life-Brief (WHOQoL-BREF) questionnaire every 10 days. Multi-level modelling tested the relationship between sleep variables and WHOQoL-BREF domains (physical, psychological, environment and social). RESULTS Of 268 recruited participants, 254 were included in this analysis. Across all WHOQoL-BREF domains, participant’s scores were lower than the population average. CSD sleep parameters predicted WHOQoL-BREF domain scores. For example, for each hour increase in the total time asleep physical domain scores increased by 1.11 points (β = 1.11 (0.07, 2.15)) and social domain scores increased by 1.65 points. These associations were not explained by sociodemographic and lifestyle factors, disease activity, medication use, levels of anxiety, sleep quality, or clinical sleep disorders. They were, however, attenuated and no longer significant when pain, fatigue and mood were included in the model. Increased variability in the total time asleep, was associated with poorer physical and psychological domain scores independently of all covariates. There were no patterns of association between actigraphy measured sleep and WHOQoL-BREF. CONCLUSIONS Optimising total sleep time, increasing sleep efficiency, decreasing sleep onset latency, and reducing the variability in total sleep time could improve HRQoL in people with RA.

scholarly journals 1059 Sleep Parameters In People With Type 2 Diabetes With And Without Insomnia Symptoms

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A402-A403
Author(s):  
M Alshehri ◽  
A Alkathiry ◽  
A Alenazi ◽  
S Alothman ◽  
J Rucker ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Total Sleep Time ◽  
Sleep Onset ◽  
Sleep Time ◽  
Circular Data ◽  
Objective Measures ◽  
Subjective Measures ◽  
Sleep Parameters ◽  
Insomnia Symptoms

Abstract Introduction There is an increasing awareness of the high prevalence of insomnia symptoms in people with type 2 diabetes (T2D). Past studies have demonstrated the importance of measuring sleep parameters in both averages and variabilities using subjective and objective methods. Thus, we aimed to compare the averages and variability of sleep parameters in people with T2D with and without insomnia symptoms. Methods Actigraph measurements and sleep diaries were used in 59 participants to assess sleep parameters, including sleep efficiency (SE), sleep latency, total sleep time, and wake after sleep onset over seven nights. Validated instruments were used to assess the symptoms of depression, anxiety, and pain. Circular data were used to describe the distribution of bed distribution with SE as a magnitude for both groups. Mann Whitney U test was utilized to compare averages and variability of sleep parameters between the two groups. Multivariable general linear model to control for demographic and clinical variables. For the secondary aim, multiple linear regression tests were utilized to assess the association between averages and variability values for both groups. Results SE was found to be lower in average and higher in variability for participants with T2D and insomnia symptoms, than those with T2D only subjectively and objectively. SE variability was also the only sleep parameter higher in people with T2D and insomnia symptoms, with psychological symptoms potentially playing a role in this difference. We observed that people in T2D+Insomnia tend to go to bed earlier compared to the T2D only group based on objective measures, but no difference was observed between groups in subjective measures. The only significant relationship in both objective and subjective measures was between the averages and variability of SE. Conclusion Our findings suggest a discrepancy between subjective and objective measures in only average of total sleep time, as well as agreement in measures of variability in sleep parameters. Also, the relationship between averages and variabilities suggested the importance of improving SE to minimize its variability. Further research is warranted to investigate the complex relationship between sleep parameters and psychological factors in people with T2D and insomnia symptoms. Support None

A Comparative Study of Sleep and Mood Between Young Elite Athletes and Age-Matched Controls

2017 ◽  
Vol 14 (6) ◽  
pp. 465-473 ◽  
Author(s):  
Anette Harris ◽  
Hilde Gundersen ◽  
Pia Mørk Andreassen ◽  
Eirunn Thun ◽  
Bjørn Bjorvatn ◽  
...  
Keyword(s):  
Physical Activity ◽  
Total Sleep Time ◽  
Elite Athletes ◽  
Sleep Onset ◽  
Sleep Time ◽  
Sleep Diary ◽  
Sleep Onset Latency ◽  
Onset Latency ◽  
Social Jetlag ◽  
Weekly Training

Background:Sleep and mood have seldom been compared between elite athletes and nonelite athletes, although potential differences suggest that physical activity may affect these parameters. This study aims to explore whether adolescent elite athletes differ from controls in terms of sleep, positive affect (PA) and negative affect (NA).Methods:Forty-eight elite athletes and 26 controls participating in organized and nonorganized sport completed a questionnaire, and a 7-day sleep diary.Results:On school days, the athletes and the controls who participated in organized and nonorganized sport differed in bedtime (22:46, 23:14, 23:42, P < .01), sleep onset (23:03, 23:27, 00:12, P < .01), and total sleep time (7:52, 8:00, 6:50, P < 01). During weekend, the athletes, the controls who participated in organized and nonorganized sport differed in bedtime (23:30, 00:04, 00:49, P < .01), sleep onset (23.42, 00:18, 01:13, P < .01), rise time (9:15, 9:47, 10:55, P < .01), sleep efficiency (95.0%, 94.2%, 90.0%, P < 05), and sleep onset latency (11.8, 18.0, 28.0 minutes, P < .01). Furthermore, the athletes reported less social jetlag (0:53) and higher score for PA (34.3) compared with the controls who participated in nonorganized sport (jetlag: 1:25, P < .05, PA: 29.8, P < .05).Conclusions:An almost dose-response association was found between weekly training hours, sleep, social jetlag and mood in adolescents.

scholarly journals Association Between Electroencephalogram-Derived Sleep Measures and the Change of Emotional Status Analyzed Using Voice Patterns: Observational Pilot Study

10.2196/16880 ◽  
2020 ◽  
Vol 4 (6) ◽  
pp. e16880
Author(s):  
Hirotaka Miyashita ◽  
Mitsuteru Nakamura ◽  
Akiko Kishi Svensson ◽  
Masahiro Nakamura ◽  
Shinichi Tokuno ◽  
...  
Keyword(s):  
Pilot Study ◽  
Regression Coefficient ◽  
Total Sleep Time ◽  
Sleep Onset ◽  
Sleep Time ◽  
Sleep Onset Latency ◽  
Inverse Association ◽  
Onset Latency ◽  
Emotional Status ◽  
Nighttime Sleep

Background Measuring emotional status objectively is challenging, but voice pattern analysis has been reported to be useful in the study of emotion. Objective The purpose of this pilot study was to investigate the association between specific sleep measures and the change of emotional status based on voice patterns measured before and after nighttime sleep. Methods A total of 20 volunteers were recruited. Their objective sleep measures were obtained using a portable single-channel electroencephalogram system, and their emotional status was assessed using MIMOSYS, a smartphone app analyzing voice patterns. The study analyzed 73 sleep episodes from 18 participants for the association between the change of emotional status following nighttime sleep (Δvitality) and specific sleep measures. Results A significant association was identified between total sleep time and Δvitality (regression coefficient: 0.036, P=.008). A significant inverse association was also found between sleep onset latency and Δvitality (regression coefficient: –0.026, P=.001). There was no significant association between Δvitality and sleep efficiency or number of awakenings. Conclusions Total sleep time and sleep onset latency are significantly associated with Δvitality, which indicates a change of emotional status following nighttime sleep. This is the first study to report the association between the emotional status assessed using voice pattern and specific sleep measures.

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