Level of Sleepiness and Total Sleep Time Following Various Time in Bed Conditions

The discrepancy between natural sleep-wake rhythm and actual sleep times in shift workers can cause sleep loss and negative daytime consequences. Irregular shift schedules do not follow a fixed structure and change frequently, which makes them particularly harmful and makes affected individuals more susceptible to insomnia. The present study compares insomnia symptoms of non-shift workers, regular shift workers, and irregular shift workers and takes into account the moderating role of the Big Five personality traits and levels of perfectionism. Employees of an Austrian railway company completed an online survey assessing shift schedules, sleep quality and duration, daytime sleepiness, and personality traits. A total of 305 participants, of whom 111 were non-shift workers, 60 regular shift workers, and 134 irregular shift workers, made up the final sample. Irregular shift workers achieved significantly worse scores than one or both of the other groups in time in bed, total sleep time, sleep efficiency, sleep duration, sleep quality, sleep latency, and the number of awakenings. However, the values of the irregular shifts workers are still in the average range and do not indicate clinical insomnia. Participants working regular shifts reported the best sleep quality and longest sleep duration and showed the least nocturnal awakenings, possibly due to higher conscientiousness- and lower neuroticism scores in this group. Agreeableness increased the effect of work schedule on total sleep time while decreasing its effect on the amount of sleep medication taken. Perfectionism increased the effect of work schedule on time in bed and total sleep time. Generalization of results is limited due to the high percentage of males in the sample and using self-report measures only.

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0409 The Efficacy of Afternoon-Evening Sleep Following Night Shifts on Sleep and Alertness in Nurses with Rotating Shift Work Schedule: Real World Data

SLEEP ◽

10.1093/sleep/zsaa056.406 ◽

2020 ◽

Vol 43 (Supplement_1) ◽

pp. A156-A157

Author(s):

J Kim ◽

S Han ◽

S Kim ◽

J Duffy

Keyword(s):

Sleep Duration ◽

Shift Work ◽

Total Sleep Time ◽

Sleep Time ◽

Hospital Nurses ◽

Sleep Timing ◽

Time In Bed ◽

Shift Schedules ◽

Sleep Schedule ◽

Night Shifts

Abstract Introduction The aim of this study was to investigate the efficacy of changing sleep timing to afternoon-evening following nightshifts in hospital nurses with three rapid rotating shift schedules. Methods Hospital nurses with three rotating shift schedules were enrolled for a 1-month pre-intervention and a 1-month intervention study. During the Intervention, sleep timing following nightshifts was directed to afternoon-evening sleep for 8h time-in-bed (TIB) after 1 PM, and ad-lib sleep schedule for other shifts. Baseline and follow-up evaluation included sleep schedule, sleep duration, Epworth sleepiness scale (ESS), insomnia severity index (ISI) for each shift, Beck depression inventory (BDI), and Beck anxiety inventory (BAI). Sleep was assessed by sleep diary and actigraphy. Alertness during the night shift was evaluated using the Karolinska sleepiness scale (KSS) in the beginning and at the end of the shift by texts sent to their cell phones. The participants were asked to give feedback and a willingness to continue this intervention. Results A total of 26 subjects (30.7±8.5years, 25 female) finished the study among 29 nurses who participated in the study. The shift work was 6.5±8.0years. The mean morningness-eveningness scale was 42.1±8.0(31-62). TIB following nightshifts were 379.9±91.2 and 478.4±48.7 min for preintervention and intervention, respectively (p=0.001). Total sleep time (TST) was 328.0±91.0 vs. 361.0±70.4min, respectively following nightshifts (p=0.187, Cohen’s drm = 0.467). BDI, BAI, ESS, and ISI were significantly improved after the intervention. 60.7% and 49% of the participants reported improved alertness, and work efficiency during the nightshift. 17.9% and 42.9% of the participants reported increased sleep duration, and improved sleep quality after nightshift, respectively. Only eight participants were willing to continue the afternoon-evening sleep schedule following night shifts. KSS was not different between pre-intervention and intervention. Conclusion The afternoon-evening sleep schedule modestly increased total sleep time following nightshift. The overall mood, sleepiness and insomnia scale improved after the intervention although the alertness assessed by KSS failed to show the difference. The individual difference should be considered for applying afternoon-evening sleep for rapid rotating shift schedules. Support 2018 Research award grants from the Korean sleep research society and NRF-2019R1A2C1090643 funded by the Korean national research foundation

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Sleep and Circadian Rhythm Disturbance in Remitted Schizophrenia and Bipolar Disorder: A Systematic Review and Meta-analysis

Schizophrenia Bulletin ◽

10.1093/schbul/sbaa024 ◽

2020 ◽

Vol 46 (5) ◽

pp. 1126-1143 ◽

Cited By ~ 4

Author(s):

Nicholas Meyer ◽

Sophie M Faulkner ◽

Robert A McCutcheon ◽

Toby Pillinger ◽

Derk-Jan Dijk ◽

...

Keyword(s):

Bipolar Disorder ◽

Circadian Rhythm ◽

Motor Activity ◽

Sleep Latency ◽

Total Sleep Time ◽

Sleep Time ◽

Mean Difference ◽

Effect Sizes ◽

Time In Bed ◽

Modifiable Factors

Abstract Background Sleep and circadian rhythm disturbances in schizophrenia are common, but incompletely characterized. We aimed to describe and compare the magnitude and heterogeneity of sleep-circadian alterations in remitted schizophrenia and compare them with those in interepisode bipolar disorder. Methods EMBASE, Medline, and PsycINFO were searched for case–control studies reporting actigraphic parameters in remitted schizophrenia or bipolar disorder. Standardized and absolute mean differences between patients and controls were quantified using Hedges’ g, and patient–control differences in variability were quantified using the mean-scaled coefficient of variation ratio (CVR). A wald-type test compared effect sizes between disorders. Results Thirty studies reporting on 967 patients and 803 controls were included. Compared with controls, both schizophrenia and bipolar groups had significantly longer total sleep time (mean difference [minutes] [95% confidence interval {CI}] = 99.9 [66.8, 133.1] and 31.1 [19.3, 42.9], respectively), time in bed (mean difference = 77.8 [13.7, 142.0] and 50.3 [20.3, 80.3]), but also greater sleep latency (16.5 [6.1, 27.0] and 2.6 [0.5, 4.6]) and reduced motor activity (standardized mean difference [95% CI] = −0.86 [−1.22, −0.51] and −0.75 [−1.20, −0.29]). Effect sizes were significantly greater in schizophrenia compared with the bipolar disorder group for total sleep time, sleep latency, and wake after sleep onset. CVR was significantly elevated in both diagnoses for total sleep time, time in bed, and relative amplitude. Conclusions In both disorders, longer overall sleep duration, but also disturbed initiation, continuity, and reduced motor activity were found. Common, modifiable factors may be associated with these sleep-circadian phenotypes and advocate for further development of transdiagnostic interventions that target them.

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Sleep and Physical Activity Patterns in Urban American Indian Children

American Journal of Health Behavior ◽

10.5993/ajhb.44.1.7 ◽

2020 ◽

Vol 44 (1) ◽

pp. 67-75

Author(s):

Vernon M. Grant ◽

Emily J. Tomayko ◽

Raymond D. Kingfisher

Keyword(s):

Physical Activity ◽

American Indian ◽

Screen Time ◽

Total Sleep Time ◽

Activity Patterns ◽

Sleep Time ◽

Indian Children ◽

Time In Bed ◽

Prevention Interventions ◽

Urban American Indian

Objectives: In this study, we examined patterns of obesity, physical activity (PA), sleep, and screen time in urban American Indian (AI) youth in the 6th-8th grade. Methods: A youth sample (N = 36) from 3 middle schools was recruited to participate in this observational sample of convenience. Youth completed a demographic and screen time survey, measurements of height and weight, and wore a wrist accelerometer continuously for 7 days to assess PA and sleep. Results: Approximately 42% of participants were overweight or obese. Average weekday screen time was 254.7±98.1 minutes. Compared to weekdays, weekend sedentary activity increased (weekday, 159.2±81.1 minutes vs weekend, 204.3±91.7 minutes; p = .03) and vigorous PA (weekday, 20.9±19.1 minutes vs weekend, 5.7±8.1 minutes; p = .0001) and moderate-to-vigorous PA (weekday, 192.65±62.3 minutes vs weekend, 141±71.7 minutes; p = .002) decreased. Compared to weekdays, weekend total sleep time (weekday, 512.8±48.6 minutes vs weekend, 555.3±84.3 minutes; p = .007) and time in bed (weekday, 487.3±49.6 minutes vs weekend, 528.6±71.2 minutes; p = .01) increased. Conclusions: Weekday to weekend shifts in PA and sleep must be considered when designing targeted obesity prevention interventions.

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Predicting Symptoms of Depression and Anxiety Using Smartphone and Wearable Data

Frontiers in Psychiatry ◽

10.3389/fpsyt.2021.625247 ◽

2021 ◽

Vol 12 ◽

Author(s):

Isaac Moshe ◽

Yannik Terhorst ◽

Kennedy Opoku Asare ◽

Lasse Bosse Sander ◽

Denzil Ferreira ◽

...

Keyword(s):

Multilevel Models ◽

Total Sleep Time ◽

Sleep Onset ◽

Sleep Time ◽

Wearable Devices ◽

Screening Methods ◽

Sleep Onset Latency ◽

Depression And Anxiety ◽

Symptoms Of Depression ◽

Time In Bed

Background: Depression and anxiety are leading causes of disability worldwide but often remain undetected and untreated. Smartphone and wearable devices may offer a unique source of data to detect moment by moment changes in risk factors associated with mental disorders that overcome many of the limitations of traditional screening methods.Objective: The current study aimed to explore the extent to which data from smartphone and wearable devices could predict symptoms of depression and anxiety.Methods: A total of N = 60 adults (ages 24–68) who owned an Apple iPhone and Oura Ring were recruited online over a 2-week period. At the beginning of the study, participants installed the Delphi data acquisition app on their smartphone. The app continuously monitored participants' location (using GPS) and smartphone usage behavior (total usage time and frequency of use). The Oura Ring provided measures related to activity (step count and metabolic equivalent for task), sleep (total sleep time, sleep onset latency, wake after sleep onset and time in bed) and heart rate variability (HRV). In addition, participants were prompted to report their daily mood (valence and arousal). Participants completed self-reported assessments of depression, anxiety and stress (DASS-21) at baseline, midpoint and the end of the study.Results: Multilevel models demonstrated a significant negative association between the variability of locations visited and symptoms of depression (beta = −0.21, p = 0.037) and significant positive associations between total sleep time and depression (beta = 0.24, p = 0.023), time in bed and depression (beta = 0.26, p = 0.020), wake after sleep onset and anxiety (beta = 0.23, p = 0.035) and HRV and anxiety (beta = 0.26, p = 0.035). A combined model of smartphone and wearable features and self-reported mood provided the strongest prediction of depression.Conclusion: The current findings demonstrate that wearable devices may provide valuable sources of data in predicting symptoms of depression and anxiety, most notably data related to common measures of sleep.

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262 Comparing Two Methods for Scoring Wrist Actigraphy to Polysomnography for Estimating Total Sleep Time in Healthy Men

SLEEP ◽

10.1093/sleep/zsab072.261 ◽

2021 ◽

Vol 44 (Supplement_2) ◽

pp. A105-A105

Author(s):

Emma Tussey ◽

Corey Rynders ◽

Christine Swanson

Keyword(s):

Decision Tree ◽

Total Sleep Time ◽

Reference Method ◽

Sleep Time ◽

Sleep Diary ◽

Scoring Methods ◽

Scoring Method ◽

Time In Bed ◽

Wrist Actigraphy ◽

Rest Intervals

Abstract Introduction This analysis assessed whether manually setting rest (i.e., time in bed) intervals prior to using a proprietary software package (Actiware, version 6.09) to analyze wrist actigraphy data improved estimates of total sleep time (TST) compared to polysomnography (PSG). Methods The Phillips Actiwatch 2 and PSG (reference method) were used to calculate TST on two separate nights in twelve men (age=28.3 ± 5.7). Participants had an 8-hour sleep opportunity on night one and a 5-hour sleep opportunity and on night two. Estimates of TST from actigraphy data were calculated using two scoring methods. For scoring method 1, we allowed the software to automatically choose rest intervals and then applied a proprietary algorithm to calculate TST. For scoring method 2, we manually entered rest intervals using a published decision tree that incorporates activity, light, event marker, and sleep diary data. After the rest intervals were set in method 2, the proprietary algorithm was applied to calculate TST. Mean bias and limits of agreement (LOA) from Bland-Altman plots compared TST derived from both actigraphy scoring methods to PSG estimates. Results On night 1 (n=8) TST measured by PSG was 398.4 ± 40.6 minutes, compared to 395.5 ± 70.9 minutes using actigraphy scoring method 1 and 396 ± 44.5 minutes using scoring method 2. Mean bias was similar when comparing both scoring methods to PSG, but the LOA were wider in method 1 compared to method 2 (method 1 vs. PSG: -2.9 [-110.4, 104.7]; method 2 vs. PSG: -2.4 [-66.5, 61.7]; minutes). On night 2 (n=12) TST determined by PSG was 283.3 ± 11.2 minutes, compared to 302.1 ± 84.4 minutes using actigraphy scoring method 1 and 273.1 ± 14.5 minutes using scoring method 2. Again, LOA for TST estimated by actigraphy scoring method 1 were wider compared to scoring method number 2 (method 1 vs. PSG: 18.8 [-136.9, 174.6]; method 2 vs. PSG: -10.2 [-35.1, 14.8]). Conclusion These data demonstrate that applying a decision tree to manually set time in bed intervals prior to running analyses in the software results in better agreement when estimating TST from wrist actigraphy compared to PSG. Support (if any) UL1RR025780, K23AR070275.

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Elusive hypersomnolence in seasonal affective disorder: actigraphic and self-reported sleep in and out of depressive episodes

Psychological Medicine ◽

10.1017/s003329172100283x ◽

2021 ◽

pp. 1-10

Author(s):

Delainey L. Wescott ◽

Peter L. Franzen ◽

Brant P. Hasler ◽

Megan A. Miller ◽

Adriane M. Soehner ◽

...

Keyword(s):

Affective Disorder ◽

Seasonal Affective Disorder ◽

Total Sleep Time ◽

Sleep Time ◽

Self Report ◽

Clinical Interviews ◽

Sleep Diaries ◽

Time In Bed ◽

Research Findings ◽

Depressive Episodes

Abstract Background Hypersomnolence has been considered a prominent feature of seasonal affective disorder (SAD) despite mixed research findings. In the largest multi-season study conducted to date, we aimed to clarify the nature and extent of hypersomnolence in SAD using multiple measurements during winter depressive episodes and summer remission. Methods Sleep measurements assessed in individuals with SAD and nonseasonal, never-depressed controls included actigraphy, daily sleep diaries, retrospective self-report questionnaires, and self-reported hypersomnia assessed via clinical interviews. To characterize hypersomnolence in SAD we (1) compared sleep between diagnostic groups and seasons, (2) examined correlates of self-reported hypersomnia in SAD, and (3) assessed agreement between commonly used measurement modalities. Results In winter compared to summer, individuals with SAD (n = 64) reported sleeping 72 min longer based on clinical interviews (p < 0.001) and 23 min longer based on actigraphy (p = 0.011). Controls (n = 80) did not differ across seasons. There were no seasonal or group differences on total sleep time when assessed by sleep diaries or retrospective self-reports (p's > 0.05). Endorsement of winter hypersomnia in SAD participants was predicted by greater fatigue, total sleep time, time in bed, naps, and later sleep midpoints (p's < 0.05). Conclusion Despite a winter increase in total sleep time and year-round elevated daytime sleepiness, the average total sleep time (7 h) suggest hypersomnolence is a poor characterization of SAD. Importantly, self-reported hypersomnia captures multiple sleep disruptions, not solely lengthened sleep duration. We recommend using a multimodal assessment of hypersomnolence in mood disorders prior to sleep intervention.

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Sleep Quality in Family Caregivers and Matched Non-Caregiving Controls: The REGARDS Study

Innovation in Aging ◽

10.1093/geroni/igab046.2982 ◽

2021 ◽

Vol 5 (Supplement_1) ◽

pp. 818-818

Author(s):

Marcela Blinka ◽

Adam Spira ◽

Orla Sheehan ◽

Tansu Cidav ◽

J David Rhodes ◽

...

Keyword(s):

Sleep Quality ◽

Family Caregivers ◽

Total Sleep Time ◽

Sleep Onset ◽

Sleep Time ◽

Care Recipient ◽

Sleep Onset Latency ◽

Onset Latency ◽

Time In Bed ◽

Regards Study

Abstract The high levels of stress experienced by family caregivers may affect their physical and psychological health, including their sleep quality. However, there are few population-based studies comparing sleep between family caregivers and carefully-matched controls. We evaluated differences in sleep and identified predictors of poorer sleep among the caregivers, in a comparison of 251 incident caregivers and carefully matched non-caregiving controls, recruited from the national REasons for Geographic and Racial Differences in Stroke (REGARDS) Study. Incident caregivers and controls were matched on up to seven demographic and health factors (age, sex, race, education level, marital status, self-rated health, and self-reported serious cardiovascular disease history). Sleep characteristics were self-reported and included total sleep time, sleep onset latency, wake after sleep onset, time in bed, and sleep efficiency. Family caregivers reported significantly longer sleep onset latency, before and after adjusting for potential confounders, compared to non-caregiving controls (ps < 0.05). Depressive symptoms in caregivers predicted longer sleep onset latency, greater wake after sleep onset, and lower sleep efficiency. Longer total sleep time in caregivers was predicted by employment status, living with the care recipient, and number of caregiver hours. Employed caregivers and caregivers who did not live with the care recipient had shorter total sleep time and spent less time in bed than non-employed caregivers. Additional research is needed to evaluate whether sleep disturbances contributes to health problems among caregivers.

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Temporal and bidirectional associations between physical activity and sleep in primary school-aged children

Applied Physiology Nutrition and Metabolism ◽

10.1139/apnm-2016-0424 ◽

2017 ◽

Vol 42 (3) ◽

pp. 238-242 ◽

Cited By ~ 15

Author(s):

Grace E. Vincent ◽

Lisa M. Barnett ◽

David R. Lubans ◽

Jo Salmon ◽

Anna Timperio ◽

...

Keyword(s):

Physical Activity ◽

Energy Expenditure ◽

Total Sleep Time ◽

Sleep Time ◽

School Aged Children ◽

Time In Bed ◽

Bidirectional Associations ◽

Objectively Measured ◽

Objectively Measured Physical Activity ◽

Activity Energy

The directionality of the relationship between children’s physical activity and sleep is unclear. This study examined the temporal and bidirectional associations between objectively measured physical activity, energy expenditure, and sleep in primary school-aged children. A subgroup of children (n = 65, aged 8–11 years) from the Fitness, Activity and Skills Testing Study conducted in Melbourne, Australia, had their sleep and physical activity assessed using the SenseWear Pro Armband for 8 consecutive days. Outcome measures included time spent in light-intensity physical activiy (LPA), moderate- to vigorous-intensity physical activity (MVPA), activity energy expenditure (AEE), time in bed, total sleep time, and sleep efficiency. Multilevel analyses were conducted using generalized linear latent mixed models to determine whether physical activity on 1 day was associated with sleep outcomes that night, and whether sleep during 1 night was associated with physical activity the following day. No significant associations were observed between time in bed, total sleep time, and sleep efficiency with LPA, MVPA, and AEE in either direction. This study found no temporal or bidirectional associations between objectively measured physical activity, AEE, and sleep. Future research is needed to understand other sleep dimensions that may impact on or be influenced by physical activity to provide potential intervention targets to improve these outcomes.

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Impact of Recent Job Loss on Sleep, Energy Consumption and Diet

Southwest Journal of Pulmonary and Critical Care ◽

10.13175/swjpcc045-21 ◽

2021 ◽

Vol 23 (5) ◽

pp. 129-137

Author(s):

Salma Batool-Anwar ◽

◽

Candace Mayer ◽

Patricia Haynes ◽

Yilin Liu ◽

...

Keyword(s):

Energy Consumption ◽

Sleep Quality ◽

Diet Quality ◽

Job Loss ◽

Total Sleep Time ◽

Activity Patterns ◽

College Education ◽

Sleep Time ◽

Sleep Diary ◽

Time In Bed

To examine how sleep quality and sleep duration affect caloric intake among those experiencing involuntary job loss. Methods Adequate sleep and self-reported dietary recall data from the Assessing Daily Activity Patterns through Occupational Transitions (ADAPT) study was analyzed. Primary sleep indices used were total sleep time, time spent in bed after final awakening, and sleep quality as measured by the Daily Sleep Diary (DSD). Mean Energy consumption (MEC) was the primary nutritional index. Secondary indices included diet quality using the Health Eating Index 2015 (HEI), and self-reported intake of protein, carbohydrates and fats. Results The study participants were comprised mainly of women (61%) and non-Hispanic white. The participants had at least 2 years of college education and mean body mass index of 30.2±8.08 (kg/m 2 (). The average time in bed was 541.8 (9 hrs) ±77.55 minutes and total sleep time was 461.1 (7.7 hrs) ±56.49 minutes. Mean sleep efficiency was 91±6%, self-reported sleep quality was 2.40±0.57 (0-4 scale, 4 = very good), and minutes earlier than planned morning awakening were 14.36±24.15. Mean HEI score was 47.41±10.92. Although the MEC was below national average for both men and women, male sex was associated with higher MEC. In a fully adjusted model sleep quality was positively associated with MEC. Conclusion Daily overall assessments of sleep quality among recently unemployed persons were positively associated with mean energy consumption. Additionally, the diet quality of unemployed persons was found to unhealthier than the average American and consistent with the relationship between poor socioeconomic status and lower diet quality.

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