Validation of Fitbit Charge 4 for assessing sleep in Chinese patients with chronic insomnia: A comparison against polysomnography and actigraphy

Causal dynamics of sleep, circadian rhythm, and mood symptoms in patients with major depression and bipolar disorder: insights from longitudinal wearable device data

BACKGROUND

Sleep and circadian rhythm disruptions are common in patients with mood disorders. The intricate relationship between these disruptions and mood has been investigated, but their causal dynamics remain unknown.

METHODS

We analysed data from 139 patients (76 female, mean age = 23.5 ± 3.64 years) with mood disorders who participated in a prospective observational study in South Korea. The patients wore wearable devices to monitor sleep and engaged in smartphone-delivered ecological momentary assessment of mood symptoms. Using a mathematical model, we estimated their daily circadian phase based on sleep data. Subsequently, we obtained daily time series for sleep/circadian phase estimates and mood symptoms spanning >40,000 days. We analysed the causal relationship between the time series using transfer entropy, a non-linear causal inference method.

FINDINGS

The transfer entropy analysis suggested causality from circadian phase disturbance to mood symptoms in both patients with MDD (n = 45) and BD type I (n = 35), as 66.7% and 85.7% of the patients with a large dataset (>600 days) showed causality, but not in patients with BD type II (n = 59). Surprisingly, no causal relationship was suggested between sleep phase disturbances and mood symptoms.

INTERPRETATION

Our findings suggest that in patients with mood disorders, circadian phase disturbances directly precede mood symptoms. This underscores the potential of targeting circadian rhythms in digital medicine, such as sleep or light exposure interventions, to restore circadian phase and thereby manage mood disorders effectively.

FUNDING

Institute for Basic Science, the Human Frontiers Science Program Organization, the National Research Foundation of Korea, and the Ministry of Health & Welfare of South Korea.

LSD increases sleep duration the night after microdosing

Microdosing psychedelic drugs at a level below the threshold to induce hallucinations is an increasingly common lifestyle practice. However, the effects of microdosing on sleep have not been previously reported. Here, we report results from a Phase 1 randomized controlled trial in which 80 healthy adult male volunteers received a 6-week course of either LSD (10 µg) or placebo with doses self-administered every third day. Participants used a commercially available sleep/activity tracker for the duration of the trial. Data from 3231 nights of sleep showed that on the night after microdosing, participants in the LSD group slept an extra 24.3 min per night (95% Confidence Interval 10.3-38.3 min) compared to placebo-with no reductions of sleep observed on the dosing day itself. There were no changes in the proportion of time spent in various sleep stages or in participant physical activity. These results show a clear modification of the physiological sleep requirements in healthy male volunteers who microdose LSD. The clear, clinically significant changes in objective measurements of sleep observed are difficult to explain as a placebo effect. Trial registration: Australian New Zealand Clinical Trials Registry: A randomized, double-blind, placebo-controlled trial of repeated microdoses of lysergic acid diethylamide (LSD) in healthy volunteers; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=381476 ; ACTRN12621000436875.

Accuracy of Fitbit Charge 4, Garmin Vivosmart 4, and WHOOP Versus Polysomnography: Systematic Review

Background

Despite being the gold-standard method for objectively assessing sleep, polysomnography (PSG) faces several limitations as it is expensive, time-consuming, and labor-intensive; requires various equipment and technical expertise; and is impractical for long-term or in-home use. Consumer wrist-worn wearables are able to monitor sleep parameters and thus could be used as an alternative for PSG. Consequently, wearables gained immense popularity over the past few years, but their accuracy has been a major concern.

Objective

A systematic review of the literature was conducted to appraise the performance of 3 recent-generation wearable devices (Fitbit Charge 4, Garmin Vivosmart 4, and WHOOP) in determining sleep parameters and sleep stages.

Methods

Per the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement, a comprehensive search was conducted using the PubMed, Web of Science, Google Scholar, Scopus, and Embase databases. Eligible publications were those that (1) involved the validity of sleep data of any marketed model of the candidate wearables and (2) used PSG or an ambulatory electroencephalogram monitor as a reference sleep monitoring device. Exclusion criteria were as follows: (1) incorporated a sleep diary or survey method as a reference, (2) review paper, (3) children as participants, and (4) duplicate publication of the same data and findings.

Results

The search yielded 504 candidate articles. After eliminating duplicates and applying the eligibility criteria, 8 articles were included. WHOOP showed the least disagreement relative to PSG and Sleep Profiler for total sleep time (-1.4 min), light sleep (-9.6 min), and deep sleep (-9.3 min) but showed the largest disagreement for rapid eye movement (REM) sleep (21.0 min). Fitbit Charge 4 and Garmin Vivosmart 4 both showed moderate accuracy in assessing sleep stages and total sleep time compared to PSG. Fitbit Charge 4 showed the least disagreement for REM sleep (4.0 min) relative to PSG. Additionally, Fitbit Charge 4 showed higher sensitivities to deep sleep (75%) and REM sleep (86.5%) compared to Garmin Vivosmart 4 and WHOOP.

Conclusions

The findings of this systematic literature review indicate that the devices with higher relative agreement and sensitivities to multistate sleep (ie, Fitbit Charge 4 and WHOOP) seem appropriate for deriving suitable estimates of sleep parameters. However, analyses regarding the multistate categorization of sleep indicate that all devices can benefit from further improvement in the assessment of specific sleep stages. Although providers are continuously developing new versions and variants of wearables, the scientific research on these wearables remains considerably limited. This scarcity in literature not only reduces our ability to draw definitive conclusions but also highlights the need for more targeted research in this domain. Additionally, future research endeavors should strive for standardized protocols including larger sample sizes to enhance the comparability and power of the results across studies.

Evaluating reliability in wearable devices for sleep staging

Sleep is crucial for physical and mental health, but traditional sleep quality assessment methods have limitations. This scoping review analyzes 35 articles from the past decade, evaluating 62 wearable setups with varying sensors, algorithms, and features. Our analysis indicates a trend towards combining accelerometer and photoplethysmography (PPG) data for out-of-lab sleep staging. Devices using only accelerometer data are effective for sleep/wake detection but fall short in identifying multiple sleep stages, unlike those incorporating PPG signals. To enhance the reliability of sleep staging wearables, we propose five recommendations: (1) Algorithm validation with equity, diversity, and inclusion considerations, (2) Comparative performance analysis of commercial algorithms across multiple sleep stages, (3) Exploration of feature impacts on algorithm accuracy, (4) Consistent reporting of performance metrics for objective reliability assessment, and (5) Encouragement of open-source classifier and data availability. Implementing these recommendations can improve the accuracy and reliability of sleep staging algorithms in wearables, solidifying their value in research and clinical settings.

Association between sleep health and rates of self-reported medical errors in intern physicians: an ancillary analysis of the Intern Health Study

STUDY OBJECTIVES

Reduced sleep duration and work hour variability contribute to medical error and physician burnout. This study assesses the relationships between physician performance, burnout, and the dimensions of sleep beyond hours slept.

METHODS

This was an ancillary analysis of 3 years of data from an international prospective cohort study: the Intern Health Study. Actigraphy data from 3,654 intern physicians capturing sleep timing, regularity, efficiency, and duration were used individually and combined as a composite sleep health index to measure the association of multidimensional sleep patterns on self-reported medical errors and burnout.

RESULTS

From 2017-2019, interns' work hours decreased by 4 hours per week and total sleep time also decreased (6.7 to 5.99 hours), and sleep efficiency, timing, and regularity all worsened (all P < .05). In the 21.2% of participants who committed an error, there was no difference in sleep duration, timing, or regularity. Lower sleep efficiency was associated with higher odds of committing an error (P = .003) and higher burnout scores (P < .001). Although overall sleep quality was poor in the entire cohort, interns in the lowest quintile of sleep duration, regularity, and efficiency had higher burnout scores than those in the best quintile.

CONCLUSIONS

Sleep efficiency, not duration, was associated with increased self-reported medical errors and burnout in intern physicians. Overall sleep quality and duration worsened despite fewer hours worked. Future studies on physician burnout should measure all aspects of sleep health.

CITATION

Hassinger AB, Velez C, Wang J, Mador MJ, Wilding GE, Mishra A. Association between sleep health and rates of self-reported medical errors in intern physicians: an ancillary analysis of the Intern Health Study. J Clin Sleep Med. 2024;20(2):221-227.

Acute social jetlag augments morning blood pressure surge: a randomized crossover trial

Although social jetlag (SJL) is generally considered a chronic condition, even acute SJL may have unfavorable effects on the cardiovascular system. We focused on the acute effects of SJL on morning blood pressure (BP) surge. This randomized crossover trial recruited 20 healthy men. In the SJL trial, participants delayed their bedtime by three hours on Friday and Saturday nights. Participants in the control (CON) trial implemented the same sleep-wake timing as on weekdays. Pre- and post-intervention measurements were performed to evaluate resting cardiovascular variables on Friday and Monday mornings, respectively. The ambulatory BP was automatically measured during the sleep and awake periods for 2 h after the participant woke up at night before pre- and post-intervention measurements. SJL (average mid-sleep time on weekends - average mid-sleep time on weekdays) occurred only in the SJL trial (SJL: 181 ± 24 min vs. CON: 8 ± 47 min). Carotid-femoral pulse wave velocity (cfPWV) and morning BP surge on Monday in the SJL trial were significantly higher than those on Friday in the SJL trial (cfPWV: P = 0.001, morning BP surge: P < 0.001), and those on Monday in the CON trial (cfPWV: P = 0.007; morning BP surge: P < 0.001). Furthermore, a significant positive correlation was found between ΔcfPWV and Δmorning BP surge (R = 0.587, P = 0.004). These results suggest that even acute SJL augments morning BP surge. This phenomenon may correspond to increased central arterial stiffness.State the details of Clinical Trials: Name: Effect of acute social jetlag on risk factors of lifestyle-related diseases. URL: https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000053204 . Unique identifier: UMIN000046639. Registration date: 17/01/2022.

Consumer Wearable Sleep Trackers: Are They Ready for Clinical Use?

As the importance of good sleep continues to gain public recognition, the market for sleep-monitoring devices continues to grow. Modern technology has shifted from simple sleep tracking to a more granular sleep health assessment. We examine the available functionalities of consumer wearable sleep trackers (CWSTs) and how they perform in healthy individuals and disease states. Additionally, the continuum of sleep technology from consumer-grade to medical-grade is detailed. As this trend invariably grows, we urge professional societies to develop guidelines encompassing the practical clinical use of CWSTs and how best to incorporate them into patient care plans.

Sleep and Perceived Stress: An Exploratory Mediation Analysis of the Role of Self-Control and Resilience among University Students

BACKGROUND

High levels of stress are frequent in university education, and a lack of sleep has been reported to make students more vulnerable to stress. The mechanisms through which sleep harms students have not been sufficiently clarified; therefore, this study aimed to explore the mediating role of self-control and resilience in the relationship between sleep quality and duration and perceived stress.

METHODS

Of 32 first-year college students, 21 (78%) were women, with a mean age of 18.47 (±0.84). They responded to a self-administered survey that included questions on stress, resilience, and sleep quality and recorded their daily sleep duration using a wristband for six days.

RESULTS

Perceived stress was significantly correlated with resilience (r = -0.63), self-control (r = -0.46), sleep duration (r = -0.35), and lower sleep quality (r = 0.57). Path analysis revealed that self-control and resilience were partially mediated by sleep quality (R2 = 0.62; p < 0.01) and completely mediated by sleep duration (R2 = 0.46; p < 0.01). In both models, self-control had a direct effect on resilience and had a good-fit index.

CONCLUSION

Being resilient seems to play a mediating role in the relationship between sleep and perceived stress; this ability can be favored by self-control, which is directly influenced by sleep.