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Wearable sleep-tracking technology is of growing use in the sleep and circadian fields, including for applications across other disciplines, inclusive of a variety of disease states. Patients increasingly present sleep data derived from their wearable devices to their providers and the ever-increasing availability of commercial devices and new-generation research/clinical tools has led to the wide adoption of wearables in research, which has become even more relevant given the discontinuation of the Philips Respironics Actiwatch. Standards for evaluating the performance of wearable sleep-tracking devices have been introduced and the available evidence suggests that consumer-grade devices exceed the performance of traditional actigraphy in assessing sleep as defined by polysomnogram. However, clear limitations exist, for example, the misclassification of wakefulness during the sleep period, problems with sleep tracking outside of the main sleep bout or nighttime period, artifacts, and unclear translation of performance to individuals with certain characteristics or comorbidities. This is of particular relevance when person-specific factors (like skin color or obesity) negatively impact sensor performance with the potential downstream impact of augmenting already existing healthcare disparities. However, wearable sleep-tracking technology holds great promise for our field, given features distinct from traditional actigraphy such as measurement of autonomic parameters, estimation of circadian features, and the potential to integrate other self-reported, objective, and passively recorded health indicators. Scientists face numerous decision points and barriers when incorporating traditional actigraphy, consumer-grade multi-sensor devices, or contemporary research/clinical-grade sleep trackers into their research. Considerations include wearable device capabilities and performance, target population and goals of the study, wearable device outputs and availability of raw and aggregate data, and data extraction, processing, and analysis. Given the difficulties in the implementation and utilization of wearable sleep-tracking technology in real-world research and clinical settings, the following State of the Science review requested by the Sleep Research Society aims to address the following questions. What data can wearable sleep-tracking devices provide? How accurate are these data? What should be taken into account when incorporating wearable sleep-tracking devices into research? These outstanding questions and surrounding considerations motivated this work, outlining practical recommendations for using wearable technology in sleep and circadian research., (© The Author(s) 2023. Published by Oxford University Press on behalf of Sleep Research Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Purpose: To examine associations between objectively measured sleep duration and sleep timing with odds of completion of an in vitro fertilization (IVF) cycle., Methods: This prospective cohort study enrolled 48 women undergoing IVF at a large tertiary medical center between 2015 and 2017. Sleep was assessed by wrist-worn actigraphy, 1-2 weeks prior to initiation of the IVF cycle. Reproductive and IVF cycle data and demographic and health information were obtained from medical charts. Sleep duration, midpoint, and bedtime were examined in relation to IVF cycle completion using logistic regression models, adjusted for age and anti-Müllerian hormone levels. A sub-analysis excluded women who worked non-day shifts to control for circadian misalignment., Results: The median age of all participants was 33 years, with 29% of women >35 years. Ten women had an IVF cycle cancelation prior to embryo transfer. These women had shorter sleep duration, more nocturnal awakenings, lower sleep efficiency, and later sleep timing relative to those who completed their cycle. Longer sleep duration was associated with lower odds of uncompleted IVF cycle (OR = 0.88; 95%CI 0.78, 1.00, per 20-min increment of increased sleep duration). Women with later sleep midpoint and later bedtime had higher odds of uncompleted cycle relative to those with earlier midpoint and earlier bedtime; OR = 1.24; 95%CI 1.09, 1.40 and OR = 1.33; 95%CI 1.17, 1.53 respectively, for 20-min increments. These results were independent of age, anti-Müllerian hormone levels, or sleep duration, and remained significant after exclusion of shift-working women., Conclusions: Shorter sleep duration and later sleep timing increase the odds of uncompleted cycles prior to embryo transfer., (© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Millions of wearable-device users record their heart rate (HR) and activity. We introduce a statistical method to extract and track six key physiological parameters from these data, including an underlying circadian rhythm in HR (CRHR), the direct effects of activity, and the effects of meals, posture, and stress through hormones like cortisol. We test our method on over 130,000 days of real-world data from medical interns on rotating shifts, showing that CRHR dynamics are distinct from those of sleep-wake or physical activity patterns and vary greatly among individuals. Our method also estimates a personalized phase-response curve of CRHR to activity for each individual, representing a passive and personalized determination of how human circadian timekeeping continually changes due to real-world stimuli. We implement our method in the "Social Rhythms" iPhone and Android app, which anonymously collects data from wearable-device users and provides analysis based on our method.

Circadian clocks control the timing of many physiological events in the 24-h day. When individuals undergo an abrupt external shift (e.g., change in work schedule or travel across multiple time zones), circadian clocks become misaligned with the new time and may take several days to adjust. Chronic circadian misalignment, e.g., as a result of shift work, has been shown to lead to several physical and mental health problems. Despite the serious health implications of circadian misalignment, relatively little is known about how genetic variation affects an individual's ability to entrain to abrupt external changes. Accordingly, we used the one-hour advance from the onset of daylight saving time (DST) as a natural experiment to comprehensively study how individual heterogeneity affects the shift of sleep/wake cycles in response to an abrupt external time change. We found that individuals genetically predisposed to a morning tendency adjusted to the advance in a few days, while genetically predisposed evening-inclined individuals had not shifted. Observing differential effects by genetic disposition after a one-hour advance underscores the importance of heterogeneity in adaptation to external schedule shifts. These genetic differences may affect how individuals adjust to jet lag or shift work as well., (© 2021. The Author(s).)

Study Objectives: By March 2020, COVID-19 forced much of the world to stay at home to reduce the spread of the disease. Whereas some health care workers transitioned to working from home, many continued to report to work in person as essential employees. We sought to explore changes in sleep, health, work, and mood in health care workers during the stay-at-home orders., Methods: We developed a cross-sectional online survey administered to health care workers. The survey assessed changes in sleep, work, screen time, media exposure, diet, exercise, substance use, and mood. The survey data were collected between March 28, 2020, and April 29, 2020., Results: A total of 834 of 936 individuals completed the entire survey. Respondents were from 41 US states. Mood after the stay-at-home orders worsened, and screen time and substance use increased. Total sleep time shortened in those continuing to work in person (P < .001), whereas it was unchanged in those working from home (P = .73). Those working from home went to bed later, woke up later, and worked fewer hours. Reduced total sleep time and increased screen time before bed were associated with worse mood and screen time. Longer sleep time was associated with better mood., Conclusions: Health care workers' mood worsened regardless of whether work was in person or remote, although total sleep time was shorter for those working in person. Those working from home may have shifted their sleep time to be more in line with their endogenous circadian phase. Peer or other support services may be indicated to address sleep, mood, and health behaviors among health care workers during these unprecedented times., (© 2021 American Academy of Sleep Medicine.)

Objective: To demonstrate that commercial activity monitoring devices (CAMDs) are practical for monitoring resident sleep while on call. Studies that have directly monitored resident sleep are limited, likely owing to both cost and difficulty in study interpretation. The advent of wearable CAMDs that estimate sleep presents the opportunity to more readily evaluate resident sleep in physically active settings and "home call," a coverage arrangement familiar to urology programs., Methods: Twelve urology residents were outfitted with Fitbit Flex devices during "home call" for a total of 57 (out of 64, or 89%) call or post-call night pairs. Residents were surveyed with the Stanford Sleepiness Scale (SSS), a single-question alertness survey. Time in bed (TIB) was "time to bed" to "rise for day." Fitbit accelerometers register activity as follows: (1) not moving; (2) minimal movement or restless; or (3) above threshold for accelerometer to register steps. Total sleep time (TST) was the number of minutes in level 1 activity during TIB. Sleep efficiency (SE) was defined as TST divided by TIB., Results: While on call, 10 responding (of 12 available, 83%) residents on average reported TIB as 347 minutes, TST as 165 minutes, and had an SE of 47%. Interestingly, SSS responses did not correlate with sleep parameters. Post-call sleep demonstrated increases in TIB, SE, and TST (+23%, +15%, and +44%, respectively) while sleepiness was reduced by 22%., Conclusion: We demonstrate that urologic residents can consistently wear CAMDs while on home call. SSS did not correlate with Fitbit-estimated sleep duration. Further study with such devices may enhance sleep deprivation recognition to improve resident sleep., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Objective: Sleep disturbances are thought to be frequent in women undergoing IVF despite minimal research of this hypothesis. Our goal was to longitudinally assess sleep duration and disturbances in women undergoing IVF and assess impact of habitual sleep duration on oocytes retrieved, an important outcome in IVF., Methods: Actigraphy and questionnaire batteries containing sleep and psychometric instruments were performed prior to and throughout 24 IVF cycles., Results: TST <7 h was present in 46%, 57%, 69%, and 42% of baseline, stimulation, post-oocyte retrieval, and post-embryo transfer recordings. ESS >10 was noted in 24%, 33%, and 36% of cycles during baseline, stimulation, and post-embryo transfer. PSQI >5 was noted in 57%, 43%, and 29% of cycles during baseline, stimulation, and post-embryo transfer. TST (F = 2.95, p = 0.04) and ESS (F = 4.36, p = 0.02) were the only sleep metrics in which a significant main effect of time was found by mixed models analysis. The final linear regression model chosen by stepwise selection to best explain the variability in oocytes retrieved included anti-mullerian hormone, day three follicle stimulating hormone, and baseline TST and explained 40% of the variance in oocytes retrieved (adjusted R 2  = 0.40, p = 0.03). Although not statistically significant, a trend towards a linear association between baseline TST and oocytes retrieved was seen with an increase of oocytes retrieved by 1.5 for every hour increase in TST (p = 0.09)., Conclusions: This is the first study to describe, with subjective and objective measures, sleep disturbances present throughout the IVF cycle. Importantly, a trend towards a linear relationship between TST and oocytes retrieved was found in this pilot study. Sleep may be a modifiable target to improve outcomes in women undergoing IVF and further investigations are needed., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Sleep medicine is well positioned to benefit from advances that use big data to create artificially intelligent computer programs. One obvious initial application in the sleep disorders center is the assisted (or enhanced) scoring of sleep and associated events during polysomnography (PSG). This position statement outlines the potential opportunities and limitations of integrating artificial intelligence (AI) into the practice of sleep medicine. Additionally, although the most apparent and immediate application of AI in our field is the assisted scoring of PSG, we propose potential clinical use cases that transcend the sleep laboratory and are expected to deepen our understanding of sleep disorders, improve patient-centered sleep care, augment day-to-day clinical operations, and increase our knowledge of the role of sleep in health at a population level.

Objectives Fibromyalgia is characterized by chronic widespread pain, mood, and sleep disturbance. Pharmacological treatments have modest efficacy and are associated with negative side effects, and alternative approaches are needed. Morning bright light treatment may assist in the management of fibromyalgia as it can reduce depressive symptoms, improve sleep, and advance circadian timing. Methods Sixty people with fibromyalgia (58 women, mean age 41.8 ± 13.3 years) were enrolled in a study comparing 4 weeks of a 1-hour daily morning bright light treatment (active treatment) to a morning dim light treatment (comparison treatment). Both light treatments included behavioral procedures to stabilize sleep timing. The morning bright light treatment was expected to produce larger improvements in pain and function than the dim light treatment and larger improvements in potential mediators (mood, sleep, and circadian timing). Results Both the bright and dim light treatment groups achieved significant but similar levels of improvement in pain intensity, pain interference, physical function, depressive symptoms, and sleep disturbance. Overall, the sample on average displayed a clinically meaningful improvement in the Fibromyalgia Impact Questionnaire-Revised score (mean reduction of 11.2 points), comparable to that reported following physical exercise treatments. Minimal side effects were observed. Conclusions Findings indicate that the effects of a morning bright light treatment did not exceed those of a comparison dim light treatment; yet the changes on average in both conditions revealed clinically meaningful improvements. Future research is warranted to identify what elements of this trial may have contributed to the observed effects. [ABSTRACT FROM AUTHOR]

• A seven-domain framework was used to evaluate the sleep health of people with MS. • Objective sleep domains: duration, continuity, timing, regularity, rhythmicity. • Subjective sleep domains: daytime sleepiness and perception of sleep quality. • Seventy-six percent of the sample had extreme values for ≥2 sleep domains. Although sleep disturbances are common among people with Multiple Sclerosis (PwMS), understanding of their impact has been stymied by limitations in approaches to sleep measurement within this population. The aim of this study was to comprehensively phenotype sleep patterns in PwMS through application of an emerging seven-domain framework that includes sleep duration, continuity, timing, quality, rhythmicity, regularity, and sleepiness. Sleep domains were estimated from wrist-worn accelerometry, Epworth Sleepiness Scale and Pittsburgh Sleep Quality Index responses. Extreme sleep values within each domain were constructed using previously published guidelines. A composite score of extreme values was calculated for each participant. Associations between sleep domains and severity of MS symptoms were explored (pain, fatigue, depressive symptoms, and cognitive dysfunction). Among n = 49 participants, median total sleep time was 456.3 min. Median time spent awake after sleep onset was 37 min. Sleepiness, abnormal sleep timing, and poor sleep quality affected 33%, 35%, and 45% of participants, respectively. Seventy-six percent had ≥2 sleep domains in extreme ranges. PwMS had longer sleep duration and decreased sleep regularity compared to a non-MS historical cohort of older men. Greater daytime sleepiness, poorer sleep quality, and higher composite sleep health score were associated with more depressive symptoms, and lower sleep rhythmicity was associated with higher fatigue. Associations were observed between measures of cognitive function and sleep fragmentation, duration, quality, rhythmicity, and composite score. Application of a seven-domain sleep health framework that captures the dynamic and multifaceted aspects of sleep is feasible in PwMS, and offers potential for an improved understanding of the scope and impact of sleep disturbances in PwMS. [ABSTRACT FROM AUTHOR]