scholarly journals O020 What helped you and what prevented you from getting good sleep? Contribution of daily facilitators and barriers to adolescent sleep

2021 ◽  
Vol 2 (Supplement_1) ◽  
pp. A9-A10
Author(s):  
S Maskevich ◽  
L Shen ◽  
J Wiley ◽  
S Drummond ◽  
B Bei
Keyword(s):  
Everyday Life ◽  
Sleep Onset ◽  
Sleep Time ◽  
Sleep Onset Latency ◽  
Onset Latency ◽  
Previous Night ◽  
Quality Sleep ◽  
Sleep Environment ◽  
Facilitators And Barriers ◽  
Good Sleep

Abstract Introduction This intense longitudinal study examined factors that facilitate and hinder sufficient and good quality sleep in adolescents’ everyday life. Methods 205 (54.2% female, 64.4% non-white) Year 10–12 adolescents (Mage = 16.9 ± 0.9) completed daily morning surveys and wore actigraphy over 2 school-weeks and 2 subsequent vacation-weeks. Morning surveys assessed self-reported sleep and the usage of 8 facilitators and 6 barriers of sleep from the previous night. Linear mixed-effects models examined contribution of facilitators/barriers to actigraphy and self-reported total sleep time (TST) and sleep onset latency (SOL), controlled for age, sex, race, place of birth, and study day. Schooldays/non-schooldays was included as a moderator. Results Seven facilitators and two barriers were endorsed by high proportions (>30%) of adolescents as frequently (≥50% days) helping/preventing them from achieving good sleep. Facilitators predicting longer TST and shorter SOL, were: “follow body cues”, “manage thoughts and emotions”, “create good sleep environment”, “avoid activities interfering with sleep” and “plan bedtime and go to bed as planned” (only TST on schooldays). Barriers predicting shorter TST and longer SOL, were: “pre-bedtime thoughts and emotions”, “unconducive sleep environment”, “activities interfering with sleep”, “inconsistent routines” and “other household members’ activities”. Overall, facilitators or barriers explained an additional 1–5% (p-values < .001) of variance beyond the covariates. Discussion Adolescents perceive a range of factors as facilitating and as preventing sufficient and good quality sleep in everyday life. These factors are predictive of their sleep duration and onset latency, and need further research to understand their functions and clinical implications.

577 Daily facilitators and barriers to adolescent sleep: Contribution to actual sleep over 28-days of school and vacation

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A227-A228
Author(s):  
Svetlana Maskevich ◽  
Lin Shen ◽  
Joshua Wiley ◽  
Sean Drummond ◽  
Bei Bei
Keyword(s):  
Sleep Onset ◽  
Sleep Time ◽  
Daily Basis ◽  
Sleep Onset Latency ◽  
Onset Latency ◽  
Previous Night ◽  
Frequent Use ◽  
Quality Sleep ◽  
Sleep Environment ◽  
Facilitators And Barriers

Abstract Introduction Little is known about what adolescents perceive as helping (facilitators) or preventing (barriers) them from getting sufficient and good quality sleep, and how these factors contribute to their actual sleep. Methods 205 (54.2% female, 64.4% non-white) Year 10–12 adolescents (Mage = 16.9 ± 0.9) completed daily morning surveys, and their sleep was measured via actigraphy over 2 school-weeks and 2 subsequent vacation-weeks. Morning surveys assessed self-reported sleep and the usage of 8 facilitators and 6 barriers of sleep from the previous night. Linear mixed-effects models were used to examine contributions of facilitators/barriers to actigraphy and self-reported total sleep time (TST) and sleep onset latency (SOL), controlling for age, sex, race, place of birth, and study day, separately for school and non-school days. Results On average, adolescents reported using 3.7 facilitators and encountering 1.5 barriers daily. Compared to school, non-school days were characterised by more frequent use of facilitators and more barriers encountered. Overall, facilitators or barriers explained an additional 1–7% (p-values < .01) of variance beyond the covariates. Similar facilitators and barriers contributed to actigraphy and self-reported TST and SOL, however, self-reported sleep variables were more affected. Notable facilitators that predicted longer TST and shorter SOL were: “follow body cues”, “avoid activities interfering with sleep”, “create good sleep environment”, “plan bedtime and go to bed as planned” (only TST on school days), and “manage thoughts and emotions” (only SOL). Notable barriers that predicted shorter TST and longer SOL were: “pre-bedtime thoughts and emotions”, “inconsistent routines”, “unconducive sleep environment”, “activities interfering with sleep” (only non-school) and “other household members’ activities” (only SOL). Conclusion This intense longitudinal study showed that on a daily basis, adolescents perceive a range of factors as facilitating and preventing sufficient and good quality sleep. These factors are predictive of their actual sleep duration and onset latency and need further research to understand their functions and clinical implications. Support (if any):

scholarly journals 1253 Multiple sleep onset REM episodes in middle age woman with excessive daytime sleepiness – Is this automatically assumed narcolepsy?

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A477-A477
Author(s):  
Kamal Patel ◽  
Bianca J Lang
Keyword(s):  
Daytime Sleepiness ◽  
Sleep Latency ◽  
Sleep Onset ◽  
Sleep Time ◽  
Multiple Sleep Latency Test ◽  
Sleep Onset Latency ◽  
Onset Latency ◽  
Obstructive Sleep ◽  
Falling Asleep ◽  
Multiple Sleep Latency

Abstract Introduction Presence of sleep onset REM episodes often raises concerns of narcolepsy. However other conditions have shown to have presence of sleep on REM episodes which include but not limited to obstructive sleep apnea, sleep wake schedule disturbance, alcoholism, neurodegenerative disorders, depression and anxiety Report of Case Here we present a case of 30 year old female with history of asthma, patent foraman ovale, migraine headache, and anxiety who presented with daytime sleepiness, falling asleep while at work, occasional scheduled naps, non-restorative sleep, sleep paralysis, and hypnopompic hallucination. Pertinent physical exam included; mallampati score of 4/4, retrognathia, high arched hard palate, crowded posterior oropharynx. She had a score of 16 on Epworth sleepiness scale. Patient previously had multiple sleep latency test at outside facility which revealed 4/5 SOREM, with mean sleep onset latency of 11.5 minutes. She however was diagnosed with narcolepsy and tried on modafinil which she failed to tolerate. She was tried on sertraline as well which was discontinued due to lack of benefit. She had repeat multiple sleep latency test work up which revealed 2/5 SOREM, with mean sleep onset latency was 13.1 minutes. Her overnight polysomnogram prior to repeat MSLT showed SOREM with sleep onset latency of 10 minutes. Actigraphy showed consistent sleep pattern overall with sufficient sleep time but was taking hydroxyzine and herbal medication. Patient did not meet criteria for hypersomnolence disorder and sleep disordered breathing. Conclusion There is possibility her medication may have played pivotal role with her daytime symptoms. We also emphasize SOREMs can be present in other disorders such as anxiety in this case and not solely in narcolepsy

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<0.001) and underestimated WASO by 44.74±68.81 minutes (p<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<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.

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 1144 Actigraphy-defined Sleep And Neurocognitive Decline In Middle-age Hispanic/Latino Adults

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A435-A436
Author(s):  
C Agudelo ◽  
W Tarraf ◽  
B Wu ◽  
D M Wallace ◽  
S R Patel ◽  
...  
Keyword(s):  
Sleep Duration ◽  
Verbal Memory ◽  
Middle Age ◽  
Verbal Learning ◽  
Sleep Onset ◽  
Sleep Time ◽  
Sleep Onset Latency ◽  
Onset Latency ◽  
Latino Adults ◽  
Neurocognitive Decline

Abstract Introduction Few studies have evaluated objective sleep measures and longitudinal neurocognitive decline, particularly in middle-age or Hispanic/Latino adults. We evaluated prospective associations between actigraphy-defined sleep and 7-year neurocognitive change among Hispanic/Latino adults. We hypothesized that sleep duration would be associated with neurocognitive decline. Methods We analyzed data from 1,036 adults 45-64 years of age from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), a multi-center prospective cohort study of diverse community-dwelling Hispanic/Latino adults. At Visit 1 (2008-2011), participants underwent neurocognitive assessments, 7-days of actigraphy, home sleep testing, and sleep questionnaires (including the Insomnia Severity Index). Seven years later, participants repeated neurocognitive assessments. The neurocognitive battery included the Six-Item Screener, Brief Spanish-English Verbal Learning Test, phonemic word fluency test, and Digit Symbol Subtest. Survey linear regression was used to evaluate prospective associations between actigraphy-defined or self-reported sleep variables and neurocognitive change. Final models adjusted for objectively-defined variables (age, body-mass index, Field Center, and time between neurocognitive assessments), and self-reported variables (sex, education, Hispanic/Latino background, alcohol consumption, physical activity, heart failure, cerebrovascular events, depression and anxiety symptoms, and antidepressant use). Results At Visit 1, the sample was 55% female and mean age was 54.9±2.2 years. The mean sleep duration was 402.6±27.6 minutes, mean sleep-onset latency was 11.3±9.7 minutes, mean number of days with naps of ≥ 15 minutes duration was 1.1±0.7, and mean sleep-time per nap was 51±14.1 minutes. Increased sleep-onset latency was associated with 7-year declines in global neurocognitive function (β=-0.0026, p&lt;0.01), verbal learning (β=-0.0028, p&lt;0.001) and verbal memory (β=-0.036, p&lt;0.05). Increased sleep-time per nap predicted better verbal memory (β=0.0038, p&lt;0.05). In contrast, sleep duration, sleep fragmentation, and self-reported sleep measures were not associated with neurocognitive change. Conclusion Among middle-age adults, sleep-onset latency and nap duration were associated with neurocognitive change. These findings may serve as targets for intervention of neurocognitive decline. Support This work is supported by the National Institute on Aging: R01AG048642, RF1AG054548, R01AG061022, R21AG056952, and R21HL140437 (AR).

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.

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

2019 ◽  
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, <i>P</i>=.008). A significant inverse association was also found between sleep onset latency and Δvitality (regression coefficient: –0.026, <i>P</i>=.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.

Actigraphy prior to MSLT: nighttime total sleep time predicts sleep onset latency

2021 ◽  
Author(s):  
Monica R. Kelly ◽  
Michelle R. Zeidler ◽  
Sharon DeCruz ◽  
Caitlin L. Oldenkamp ◽  
Karen R. Josephson ◽  
...  
Keyword(s):  
Total Sleep Time ◽  
Sleep Onset ◽  
Sleep Time ◽  
Sleep Onset Latency ◽  
Onset Latency

scholarly journals Home-Based Sleep Sensor Measurements in an Older Australian Population: Before and during a Pandemic

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 5993
Author(s):  
Mahnoosh Kholghi ◽  
Claire M. Ellender ◽  
Qing Zhang ◽  
Yang Gao ◽  
Liesel Higgins ◽  
...  
Keyword(s):  
Older Adults ◽  
Time Course ◽  
Total Sleep Time ◽  
Sleep Onset ◽  
Sleep Time ◽  
Community Dwelling ◽  
Sleep Efficiency ◽  
Sleep Onset Latency ◽  
Onset Latency ◽  
Short Sleep Duration

Older adults are susceptible to poor night-time sleep, characterized by short sleep duration and high sleep disruptions (i.e., more frequent and longer awakenings). This study aimed to longitudinally and objectively assess the changes in sleep patterns of older Australians during the 2020 pandemic lockdown. A non-invasive mattress-based device, known as the EMFIT QS, was used to continuously monitor sleep in 31 older adults with an average age of 84 years old before (November 2019–February 2020) and during (March–May 2020) the COVID-19, a disease caused by a form of coronavirus, lockdown. Total sleep time, sleep onset latency, wake after sleep onset, sleep efficiency, time to bed, and time out of bed were measured across these two periods. Overall, there was no significant change in total sleep time; however, women had a significant increase in total sleep time (36 min), with a more than 30-min earlier bedtime. There was also no increase in wake after sleep onset and sleep onset latency. Sleep efficiency remained stable across the pandemic time course between 84–85%. While this sample size is small, these data provide reassurance that objective sleep measurement did not deteriorate through the pandemic in older community-dwelling Australians.

scholarly journals Correlations between subjective and objective features of nocturnal sleep and excessive diurnal sleepiness in patients with narcolepsy

2009 ◽  
Vol 67 (4) ◽  
pp. 995-1000 ◽  
Author(s):  
Ulises Jiménez-Correa ◽  
Reyes Haro ◽  
Rosa Obdulia González ◽  
Javier Velázquez-Moctezuma
Keyword(s):  
Clinical Symptoms ◽  
Sleep Onset ◽  
Sleep Time ◽  
Control Group ◽  
Sleep Onset Latency ◽  
Sleep Paralysis ◽  
Onset Latency ◽  
Nocturnal Sleep ◽  
Subjective Sleep Quality ◽  
Multiple Sleep Latency

OBJECTIVE: To determine the correlations between excessive daytime sleepiness (EDS), assessed by the Epworth sleepiness scale (ESS), and the multiple sleep latency test (MSLT) and nocturnal sleep architecture features, clinical symptoms of narcolepsy (CSN) and subjective sleep quality (SSQ) in patients with narcolepsy. METHOD: Twenty three untreated patients were studied and compared with a matched control group. Diagnosis of narcolepsy was carried out employing a clinical interview, a polysomnographic (PSG) record, and an MSLT. RESULTS: Subjective number of awakenings was the SSQ indicator that best correlated with EDS (ESS and MSLT). Regarding clinical features, diurnal tiredness and sleep paralysis correlated with ESS values. Increase in ESS was related with decrease in total sleep time, SWS, and sleep onset latency. On the other hand, increase in MSLT was related with decrease in SWS. CONCLUSION: These data suggest that EDS in patients with narcolepsy could be impaired by disturbed nocturnal sleep.

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