scholarly journals Subjective Happiness Is Associated with Objectively Evaluated Sleep Efficiency and Heart Rate during Sleep: An Exploratory Study Using Non-Contact Sheet Sensors

2020 ◽  
Vol 12 (11) ◽  
pp. 4630
Author(s):  
Hisayoshi Okamura ◽  
Kengo Mihara ◽  
Akira Tsuda ◽  
Toshihiro Morisaki ◽  
Yoshiyuki Tanaka ◽  
...  
Keyword(s):  
Heart Rate ◽  
Sleep Onset ◽  
Sleep Efficiency ◽  
Sleep Onset Latency ◽  
Subjective Happiness ◽  
Onset Latency ◽  
Lower Heart Rate ◽  
Subjective Sleep ◽  
Subjective Happiness Scale ◽  
The Relationship

The objective of this study was to explore the relationship between subjective happiness and subjective and objective sleep. The participants were 24 healthy university students (11 males, 13 females; mean age 22.4 ± 2.1). Their subjective happiness was measured by the Japanese Subjective Happiness Scale (JSHS). Furthermore, their subjective and objective sleep evaluation was measured by Ogri-Shirakawa-Azumi sleep inventory MA version (OSA-MA) and a non-contact sheet sensor (SS). The results indicated that participants with higher subjective happiness had objectively shorter sleep onset latency, higher sleep efficiency, and lower heart rate during sleep. On the other hand, no such correlations were found between subjective sleep evaluation with OSA and subjective happiness. These results suggest that subjective happiness is related with the ability to more easily fall asleep and better sleep efficiency.

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.

Utility of Activity Monitors and Thermometry in Assessing Sleep Stages and Sleep Quality

2018 ◽  
Vol 1 (3) ◽  
pp. 108-121
Author(s):  
Natashia Swalve ◽  
Brianna Harfmann ◽  
John Mitrzyk ◽  
Alexander H. K. Montoye
Keyword(s):  
Sleep Quality ◽  
Skin Temperature ◽  
Sleep Stage ◽  
Sleep Onset ◽  
Sleep Efficiency ◽  
Sleep Stages ◽  
Sleep Onset Latency ◽  
Onset Latency ◽  
Activity Monitors ◽  
Research Grade

Activity monitors provide an inexpensive and convenient way to measure sleep, yet relatively few studies have been conducted to validate the use of these devices in examining measures of sleep quality or sleep stages and if other measures, such as thermometry, could inform their accuracy. The purpose of this study was to compare one research-grade and four consumer-grade activity monitors on measures of sleep quality (sleep efficiency, sleep onset latency, and wake after sleep onset) and sleep stages (awake, sleep, light, deep, REM) against an electroencephalography criterion. The use of a skin temperature device was also explored to ascertain whether skin temperature monitoring may provide additional data to increase the accuracy of sleep determination. Twenty adults stayed overnight in a sleep laboratory during which sleep was assessed using electroencephalography and compared to data concurrently collected by five activity monitors (research-grade: ActiGraph GT9X Link; consumer-grade: Fitbit Charge HR, Fitbit Flex, Jawbone UP4, Misfit Flash) and a skin temperature sensor (iButton). The majority of the consumer-grade devices overestimated total sleep time and sleep efficiency while underestimating sleep onset latency, wake after sleep onset, and number of awakenings during the night, with similar results being seen in the research-grade device. The Jawbone UP4 performed better than both the consumer- and research-grade devices, having high levels of agreement overall and in epoch-by-epoch sleep stage data. Changes in temperature were moderately correlated with sleep stages, suggesting that addition of skin temperature could increase the validity of activity monitors in sleep measurement.

scholarly journals Anxiety mediates the relationship between sleep onset latency and emotional eating in minority children

2010 ◽  
Vol 11 (4) ◽  
pp. 297-300 ◽  
Author(s):  
Selena T. Nguyen-Rodriguez ◽  
Arianna D. McClain ◽  
Donna Spruijt-Metz
Keyword(s):  
Emotional Eating ◽  
Sleep Onset ◽  
Sleep Onset Latency ◽  
Onset Latency ◽  
Minority Children ◽  
The Relationship

scholarly journals 0916 The Use of Immersive Virtual Reality and Slow Breathing to Enhance Relaxation and Sleep in Adolescents

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A348-A348
Author(s):  
D Yüksel ◽  
A Goldstone ◽  
D Prouty ◽  
M Forouzanfar ◽  
S Claudatos ◽  
...  
Keyword(s):  
Heart Rate ◽  
Virtual Reality ◽  
Sleep Disturbances ◽  
Sleep Onset ◽  
Apparent Difference ◽  
Sleep Onset Latency ◽  
Onset Latency ◽  
Post Intervention ◽  
Falling Asleep ◽  
Slow Breathing

Abstract Introduction Sleep disturbances frequently emerge during adolescence amongst profound, normative, sleep maturation and biopsychosocial changes. Factors like stress, worry or rumination may make falling asleep and maintaining sleep more difficult. Here, we evaluate the efficacy of a novel intervention based on virtual reality (VR) and slow breathing to promote bedtime relaxation and facilitate sleep in high-school adolescents. Methods Twenty-nine 16-18 year-old adolescents with (N=9, 6 girls) and without (N=20, 11 girls) sleep difficulties underwent two counterbalanced in-lab relaxation and baseline polysomnography (PSG) nights. For the relaxation condition, immediately preceding bedtime, participants were engaged in slow diaphragmatic breathing (to promote physiological downregulation) whilst passively experiencing a relaxation immersive VR environment, designed to promote cognitive relaxation/distraction (20min). On the baseline night, participants engaged in quiet activities (e.g., reading a book) before bedtime (20min). Results The VR intervention resulted in a significant immediate increase in perceived relaxation and reduced worry (p&lt;0.05). Also, heart rate dropped (~5bpm) in the pre-to-post intervention (p&lt;0.05), while no significant change in heart rate was evident before and after the time spent in quiet activities on the baseline night. PSG-defined sleep onset latency was shorter (~6min reduction) and sleep efficiency was greater (~3% increase) on the VR relaxation night compared to the baseline night (p&lt;0.05). In addition, baseline sleep onset latency was related to the magnitude of the baseline-to-relaxation reduction in sleep onset latency in participants (R2=0.70; p&lt;0.01). There was no apparent difference in responses to the VR intervention between adolescents with or without insomnia. Conclusion Our data highlight the potential for combining cognitive relaxation/distraction strategies, using immersive VR technology and physiological downregulation, to promote bedtime relaxation and improve overall sleep quality in adolescents. Further research is needed to evaluate the feasibility and effectiveness of such interventions over time. Support National Heart, Lung and Blood Institute (NHLBI) R01HL139652 (to MdZ)

105 Sleep Behaviors Are Differentially Associated with Eating Behavior Characteristics Based on Sex

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A43-A43
Author(s):  
Rocio Barragan ◽  
Faris Zuraikat ◽  
Victoria Tam ◽  
Samantha Scaccia ◽  
Justin Cochran ◽  
...  
Keyword(s):  
Eating Behavior ◽  
Sleep Onset ◽  
Sleep Efficiency ◽  
Sleep Fragmentation ◽  
Poor Sleep ◽  
Sleep Onset Latency ◽  
Onset Latency ◽  
Obesity Risk ◽  
Fragmentation Index ◽  
Behavior Characteristics

Abstract Introduction Poor sleep health is a key determinant of obesity risk, largely explained by overconsumption of energy. Eating behavior characteristics are predictive of energy intake and weight change and may link sleep with risk factors for obesity. However, the relationships between sleep and dimensions of eating behavior, and potential individual differences in these relations, are not well characterized. Elucidating these relations may aid in the development of targeted strategies to mitigate obesity risk. Therefore, we aimed to 1) evaluate whether associations of sleep were related with eating behavior characteristics, 2) explore if these associations differed by sex. Methods This was a cross-sectional analysis of 179 adults aged 20–73 y (68.7% women; 64.8% with BMI≥25 kg/m2; 27.4% minority). Sleep was assessed over 2 wk using wrist actigraphy; eating behavior characteristics (dietary restraint, disinhibition and hunger) were measured with the Three-Factor Eating Questionnaire. Linear regression models were used to evaluate associations of sleep with eating behavior characteristics, adjusting for confounding variables. In separate models, sex was added as an interaction term and analyses were stratified when interactions were significant (p&lt;0.10). Results Variable (sleep midpoint standard deviation &gt;60 min) vs. stable sleep timing was associated with greater tendency towards hunger (β=0.84 ± 0.39, p=0.03). When evaluated on the continuous scale, lower sleep efficiency (β=-0.13 ± 0.05; p=0.01), longer wake after sleep onset (β=0.03 ± 0.01; p=0.01) and higher sleep fragmentation index (β=0.074 ± 0.036; p=0.041) were associated with higher dietary restraint. Sex influenced associations of sleep efficiency, sleep onset latency, and sleep fragmentation index with hunger. In men, but not women, lower sleep efficiency (β=-0.15 ± 0.05; p&lt;0.01), longer sleep onset latency (β=0.17 ± 0.07; p=0.02) and higher sleep fragmentation index (β=0.11 ± 0.04; p&lt;0.01) were associated with greater hunger. Conclusion Objective measures of sleep were associated with eating behaviors previously linked with obesity and its risk factors. Moreover, we provide evidence of sex-specific associations between poor sleep and tendency towards hunger. Our results suggest that, particularly in men, differences in eating behavior traits may underlie susceptibility to overeating in response to poor sleep. Support (if any) Supported by NIH grants R01HL128226 and R01HL142648 and AHA grant 16SFRN27950012 (PI: St-Onge).

scholarly journals P113 An Exploration of Factors that Affect Perceived Onset Latency during the MSLT Test

2021 ◽  
Vol 2 (Supplement_1) ◽  
pp. A58-A58
Author(s):  
M Puglia ◽  
A Turton ◽  
J Stonehouse ◽  
A Rossely ◽  
A Grbic ◽  
...  
Keyword(s):  
Room Temperature ◽  
Sleep Onset ◽  
Scale Space ◽  
Sleep Onset Latency ◽  
Onset Latency ◽  
Written Comments ◽  
Patient’S Experience ◽  
The Relationship ◽  
Test Outcomes ◽  
Perception Of Sleep

Abstract It is assumed that during the MSLT test, the sleep laboratory environment will be appropriately resourced to facilitate sleep. However, anecdotal evidence suggests that a variety of factors may actually hinder sleep onset, although this possibility has not been formally investigated in the literature. Thirty-four MSLT participants, who attended the sleep unit between 2018 and 2019, completed a questionnaire that was designed to test perception of sleep onset latency by asking them how easy/difficult it was for them to fall asleep on 17 items that came from four categories. The four categories were the 1. sleep unit environment, e.g. noise/ room temperature; 2. the MSLT procedure, e.g. wires/fixed nap times; 3. the MSLT staff e.g. manner/ clarity of explanations and 4. pain/distress unrelated to the test. All items were rated on a five-point Likert scale. Space was provided for written comments for each category. Overall, the relationship with staff had the greatest impact on perceived sleep onset latency. Forty-one percent of participants reported that the provision of a thorough explanation of the day’s procedure helped them fall asleep in naps. Thirty-five percent reported that their own pain and discomfort affected their ability to sleep. Light and noise had little impact. This research indicates that the staff-patient relationship plays a significant role in patient’s experience of the MSLT and may potentially affect test outcomes.

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.

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