Background Virtual reality exposure therapy (VRET) is currently being used to treat social anxiety disorder (SAD); however, VRET's magnitude of efficacy, duration of efficacy, and impact on treatment discontinuation are still unclear. Methods We conducted a meta-analysis of studies that investigated the efficacy of VRET for SAD. The search strategy and analysis method are registered at PROSPERO (#CRD42019121097). Inclusion criteria were: (1) studies that targeted patients with SAD or related phobias; (2) studies where VRET was conducted for at least three sessions; (3) studies that included at least 10 participants. The primary outcome was social anxiety evaluation score change. Hedges' g and its 95% confidence intervals were calculated using random-effect models. The secondary outcome was the risk ratio for treatment discontinuation. Results Twenty-two studies (n = 703) met the inclusion criteria and were analyzed. The efficacy of VRET for SAD was significant and continued over a long-term follow-up period: Hedges' g for effect size at post-intervention, −0.86 (−1.04 to −0.68); three months post-intervention, −1.03 (−1.35 to −0.72); 6 months post-intervention, −1.14 (−1.39 to −0.89); and 12 months post-intervention, −0.74 (−1.05 to −0.43). When compared to in vivo exposure, the efficacy of VRET was similar at post-intervention but became inferior at later follow-up points. Participant dropout rates showed no significant difference compared to in vivo exposure. Conclusion VRET is an acceptable treatment for SAD patients that has significant, long-lasting efficacy, although it is possible that during long-term follow-up, VRET efficacy lessens as compared to in vivo exposure.

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.

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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 (&gt;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

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.

Introduction: Mental disorders are a leading cause of disability worldwide and, among mental disorders, major depressive disorder was highly ranked in years lived with disability. 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 or connected to the computer (pulse wave data extracted from the facial video images), a microphone built into or connected to 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 (New Occupational Stress Questionnaire, Perceived Stress Scale, Satisfaction With Life Scale, Japanese version of Positive and Negative Affect Schedule, Japanese Flourishing Scale, Subjective Well-being / Ideal Happiness, and Japanese version of Patient Health Questionnaire-9). 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. 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

This study aimed to investigate how people’s subjective health changed after the coronavirus disease 2019 (COVID-19) pandemic. This survey was conducted in May 2021 as a nationwide online self-reported survey in Japan. The respondents indicated how their sleep, physical condition, and mental state altered after the pandemic. Furthermore, they answered questionnaires about their intention to get vaccinated, the means of gathering information, etc. A logistic regression analysis was performed. Of the 2,573 responses, there was a decline of approximately 13.6%, 14.0%, and 23.8% in subjective sleep, physical condition, and mental health after the pandemic, respectively. The logistic regression analysis demonstrated that regarding sleep, the affected group was younger, got vaccinated against influenza annually, had lower income, experienced poor sleep quality in the past month, and had worse physical and psychiatric symptoms than before the pandemic. Concerning the physical condition, the affected group lived alone, witnessed deficient sleep quality in the past month, and had deteriorated mental health status than before the COVID-19 pandemic. In terms of mental status, the affected group was younger, females, had access to more sources of information, and experienced worse sleep and physical conditions than the unchanged or improved group (p < 0.05). Each group indicated an association with the background factors, confirming that the subjective sleep, physical condition, and mental state affected each other. From a preventive perspective, the results of this study suggested that factors such as youth, gender, sleep quality, pregnancy, reduced income, and greater access to information, may be necessary for physical and mental support. The above-mentioned factors should be considered in light of community life and approached accordingly.

BACKGROUND Poor sleep quality and daytime sleepiness can hinder work efficiency and adversely affect well-being. Sleep quality can be objectively assessed by wearable devices, and daytime sleepiness and mental state can be timely ascertained from by ecological momentary assessment (EMA); however, few studies have been conducted using a combination of all of these tools. OBJECTIVE The aim of this study was to explore the association between physiological data, such as sleep time and heart rate variability (HRV), measured objectively by wearable devices, and sleepiness, mood, and vitality status measured by EMA and use of rating scales for stress/well-being. METHODS A total of 40 office workers (mean age, 40.4 years; SD, 11.8 years) participated in the study. Their stress levels and perception of well-being (hereinafter, stress/well-being) were assessed at the beginning of the study. Then, they were asked to wear a wearable wristband device (Fitbit Inspire 2 from Fitbit Inc.) during the day for 8 consecutive weeks. EMA on sleepiness, mood, and vitality was conducted through email messages sent by the subjects four times a day, each three hours apart, on eight designated days during the 8-week period. After the device-wearing period of 8 weeks, the stress/well-being of the workers were assessed again. Subjects were divided into quartiles based on the assessed scores, and the sleep indices measured by the Fitbit were compared between the groups with values in the lowest quartile and highest quartile. RESULTS The total response rate for the EMA was 87.3%, and the total Fitbit wear rate was 88.0%. Groups with higher subjective stress went to bed significantly later than the group with lower subjective stress (p=0.0001). The group with higher scores on well-being showed statistically smaller weekly standard deviations of the midpoint of sleep as compared with the group with lower scores on well-being (P-values: <0.0001). CONCLUSIONS This study, which utilized both wearable devices and EMA, was well-received by the participants. Some relationships were found between objective sleep indicators and the stress/well-being of the subjects. Future research utilizing these methods focused on specific targets, for example, social jet lag, could provide further useful insights. CLINICALTRIAL UMIN-CTR UMIN000046858 https://center6.umin.ac.jp/cgi-open-bin/ctr/ctr_view.cgi?recptno=R000053392