Assessment of Stress and Well-Being of Japanese Employees Using Wearable Devices for Sleep Monitoring Combined With Ecological Momentary Assessment: Pilot Observational Study.

BACKGROUND: Poor sleep quality can elevate stress levels and diminish overall well-being. Japanese individuals often experience sleep deprivation, and workers have high levels of stress. Nevertheless, research examining the connection between objective sleep assessments and stress levels, as well as overall well-being, among Japanese workers is lacking. OBJECTIVE: This study aims to investigate the correlation between physiological data, including sleep duration and heart rate variability (HRV), objectively measured through wearable devices, and 3 states (sleepiness, mood, and energy) assessed through ecological momentary assessment (EMA) and use of rating scales for stress and well-being. METHODS: A total of 40 office workers (female, 20/40, 50%; mean age 40.4 years, SD 11.8 years) participated in the study. Participants were asked to wear a wearable wristband device for 8 consecutive weeks. EMA regarding sleepiness, mood, and energy levels was conducted via email messages sent by participants 4 times daily, with each session spaced 3 hours apart. This assessment occurred on 8 designated days within the 8-week timeframe. Participants' stress levels and perception of well-being were assessed using respective self-rating questionnaires. Subsequently, participants were categorized into quartiles based on their stress and well-being scores, and the sleep patterns and HRV indices recorded by the Fitbit Inspire 2 were compared among these groups. The Mann-Whitney U test was used to assess differences between the quartiles, with adjustments made for multiple comparisons using the Bonferroni correction. Furthermore, EMA results and the sleep and HRV indices were subjected to multilevel analysis for a comprehensive evaluation. RESULTS: The EMA achieved a total response rate of 87.3%, while the Fitbit Inspire 2 wear rate reached 88.0%. When participants were grouped based on quartiles of well-being and stress-related scores, significant differences emerged. Specifically, individuals in the lowest stress quartile or highest subjective satisfaction quartile retired to bed earlier (P<.001 and P=.01, respectively), whereas those in the highest stress quartile exhibited greater variation in the midpoint of sleep (P<.001). A multilevel analysis unveiled notable relationships: intraindividual variability analysis indicated that higher energy levels were associated with lower deviation of heart rate during sleep on the preceding day (ß=-.12, P<.001), and decreased sleepiness was observed on days following longer sleep durations (ß=-.10, P<.001). Furthermore, interindividual variability analysis revealed that individuals with earlier midpoints of sleep tended to exhibit higher energy levels (ß=-.26, P=.04). CONCLUSIONS: Increased sleep variabilities, characterized by unstable bedtime or midpoint of sleep, were correlated with elevated stress levels and diminished well-being. Conversely, improved sleep indices (eg, lower heart rate during sleep and earlier average bedtime) were associated with heightened daytime energy levels. Further research with a larger sample size using these methodologies, particularly focusing on specific phenomena such as social jet lag, has the potential to yield valuable insights. TRIAL REGISTRATION: UMIN-CTR UMIN000046858; https://center6.umin.ac.jp/cgi-open-bin/ctr/ctr_view.cgi?recptno=R000053392.

Associations between glycemic variability, sleep quality, and daily steps in subjects without diabetes using wearable devices.

Background: Since there are limited studies on the associations between glycemic variability (GV) and sleep quality or physical activity in subjects without diabetes, we evaluated the associations between GV, as assessed by continuous glucose monitoring (CGM), and both sleep quality and daily steps using wearable devices in healthy individuals. Methods: Forty participants without diabetes were monitored by both an intermittently scanned CGM and a smartwatch-type activity tracker for 2 weeks. The standard deviation (SD) and coefficient of variation (CV) of glucose were evaluated as indices of GV. The activity tracker was used to calculate each participant's average step count per day. We also calculated sleep duration, sleep efficiency, and sleep latency based on data from the activity tracker. Spearman's correlation coefficient was used to assess the association between GV and sleep indices or daily steps. For each participant, periods were divided into quartiles according to step counts throughout the day. We compared mean parameter differences between the periods of lowest quartile and highest quartile (lower 25% and upper 25%). Results: SD glucose was significantly positively correlated with sleep latency (R = 0.23, P < 0.05). There were no significant correlations among other indices in GV and sleep quality (P > 0.05). SD glucose and CV glucose levels in the upper 25% period of daily steps were lower than those in the lower 25% period in each participant (both, P < 0.01). Conclusion: In subjects without diabetes, GV evaluated by intermittently scanned CGM was positively associated with the time to fall asleep. Furthermore, GV in the days of larger daily steps was decreased compared to the days of smaller daily steps in each participant.

Assessment of glycemic variability and lifestyle behaviors in healthy nondiabetic individuals according to the categories of body mass index.

BACKGROUND: There are limited data about the association between body mass index (BMI), glycemic variability (GV), and life-related factors in healthy nondiabetic adults. METHODS: This cross-sectional study was carried out within our ethics committee-approved study called "Exploring the impact of nutrition advice on blood sugar and psychological status using continuous glucose monitoring (CGM) and wearable devices". Prediabetes was defined by the HbA1c level of 5.7-6.4% and /or fasting glucose level of 100-125 mg/dL. Glucose levels and daily steps were measured for 40 participants using Free Style Libre and Fitbit Inspire 2 under normal conditions for 14 days. Dietary intakes and eating behaviors were assessed using a brief-type self-administered dietary history questionnaire and a modified questionnaire from the Obesity Guidelines. RESULTS: All indices of GV were higher in the prediabetes group than in the healthy group, but a significant difference was observed only in mean amplitude of glycemic excursions (MAGE). In the multivariate analysis, only the presence of prediabetes showed a significant association with the risk of higher than median MAGE (Odds, 6.786; 95% CI, 1.596-28.858; P = 0.010). Additionally, the underweight (BMI < 18.5) group had significantly higher value in standard deviation (23.7 ± 3.5 vs 19.8 ± 3.7 mg/dL, P = 0.038) and coefficient variability (22.6 ± 4.6 vs 18.4 ± 3.2%, P = 0.015), compared to the normal group. This GV can be partially attributed to irregularity of eating habits. On the contrary, the overweight (BMI ≥ 25) group had the longest time above the 140 or 180 mg/dL range, which may be due to eating style and taking fewer steps (6394 ± 2337 vs 9749 ± 2408 steps, P = 0.013). CONCLUSIONS: Concurrent CGM with diet and activity monitoring could reduce postprandial hyperglycemia through assessment of diet and daily activity, especially in non- normal weight individuals.

Association of work environment with stress and depression among Japanese workers.

BACKGROUND: There is a lack of studies that investigated the effect of a wide range of work environmental factors on stress and depression in Japan. OBJECTIVES: To examine the association of work environment factors with stress and depression among workers in Japan. METHODS: We conducted questionnaire surveys of workers that mainly engage in desk work in Japan. Stress was assessed through the Perceived Stress Scale (PSS), depression through the Patient Health Questionnaire-9 (PHQ-9), and work environment through physical and psychological workplace environment questionnaires. Workers were divided into low and high stress groups based on PSS score (median split), and divided into non-depressed and depressed groups based on their PHQ-9 score (< 5, and ≥5); these groups were then compared with their working environment. In addition, a multiple regression analysis was performed. RESULTS: Responses were obtained from 210 subjects. Multiple regression analysis showed that "Ability to work at one's own pace" and "Ability to apply personal viewpoint to work," etc., had effect on stress, while "Workplace harassment" and "Support from colleagues," etc., had effect on depression. CONCLUSIONS: The results suggest that stress and depression in Japanese workers are related to factors such as job demands, control of work, workplace harassment, and psychological safety.

Subjective well-being and month-long LF/HF ratio among deskworkers.

The importance of workers' well-being has been recognized in recent years. The assessment of well-being has been subjective, and few studies have sought potential biomarkers of well-being to date. This study examined the relationship between well-being and the LF/HF ratio, an index of heart rate variability that reflects sympathetic and parasympathetic nerve activity. Pulse waves were measured using photoplethysmography through a web camera attached to the computer used by each participant. The participants were asked to measure their pulse waves while working for 4 weeks, and well-being was assessed using self-reported measures such as the Satisfaction With Life Scale (SWLS), the Positive and Negative Affect Schedule (PANAS), and the Flourishing Scale (FS). Each of the well-being scores were split into two groups according to the median value, and the LF/HF ratio during work, as well as the number of times an LF/HF ratio threshold was either exceeded or subceeded, were compared between the high and low SWLS, positive emotion, negative emotion, and FS groups. Furthermore, to examine the effects of the LF/HF ratio and demographic characteristics on well-being, a multiple regression analysis was conducted. Data were obtained from 169 participants. The results showed that the low FS group had a higher mean LF/HF ratio during work than the high FS group. No significant differences were seen between the high and low SWLS groups, the high and low positive emotion groups, or the high and low negative emotion groups. The multiple regression analysis showed that the mean LF/HF ratio during work affected the FS and SWLS scores, and the number of times the mean LF/HF ratio exceeded +3 SD had an effect on the positive emotion. No effect of the LF/HF ratio on negative emotions was shown. The LF/HF ratio might be applicable as an objective measure of well-being.

Unobtrusive Sensing Technology for Quantifying Stress and Well-Being Using Pulse, Speech, Body Motion, and Electrodermal Data in a Workplace Setting: Study Concept and Design.

Introduction: Mental disorders are a leading cause of disability worldwide. Depression has a significant impact in the field of occupational health because it is particularly prevalent during working age. On the other hand, there are a growing number of studies on the relationship between "well-being" and employee productivity. To promote healthy and productive workplaces, this study aims to develop a technique to quantify stress and well-being in a way that does not disturb the workplace. Methods and analysis: This is a single-arm prospective observational study. The target population is adult (>20 years old) workers at companies that often engage in desk work; specifically, a person who sits in front of a computer for at least half their work hours. The following data will be collected: (a) participants' background characteristics; (b) participants' biological data during the 4-week observation period using sensing devices such as a camera built into the computer (pulse wave data extracted from the facial video images), a microphone built into their work computer (voice data), and a wristband-type wearable device (electrodermal activity data, body motion data, and body temperature); (c) stress, well-being, and depression rating scale assessment data. The analysis workflow is as follows: (1) primary analysis, comprised of using software to digitalize participants' vital information; (2) secondary analysis, comprised of examining the relationship between the quantified vital data from (1), stress, well-being, and depression; (3) tertiary analysis, comprised of generating machine learning algorithms to estimate stress, well-being, and degree of depression in relation to each set of vital data as well as multimodal vital data. Discussion: This study will evaluate digital phenotype regarding stress and well-being of white-collar workers over a 4-week period using persistently obtainable biomarkers such as heart rate, acoustic characteristics, body motion, and electrodermal activity. Eventually, this study will lead to the development of a machine learning algorithm to determine people's optimal levels of stress and well-being. Ethics and dissemination: Collected data and study results will be disseminated widely through conference presentations, journal publications, and/or mass media. The summarized results of our overall analysis will be supplied to participants. Registration: UMIN000036814.