BackgroundNumerous studies have shown that healthcare professionals are exposed to psychological distress. However, since most of these studies assessed psychological distress using self-reporting questionnaires, the magnitude of the problem is largely unknown. We evaluated the risks of mood disorders, anxiety disorders, sleep disorders, and any psychiatric disorders in workers in healthcare industry using Korea National Health Insurance (NHI) claims data from 2014, which are based on actual diagnoses instead of self-evaluation.MethodsWe used Korea 2014 NHI claims data and classified employees as workers in the healthcare industry, based on companies in the NHI database that were registered with hospitals, clinics, public healthcare, and other medical services. To estimate the standardized prevalence of the selected mental health disorders, we calculated the prevalence of diseases in each age group and sex using the age distribution of the Korea population. To compare the risk of selected mental disorders among workers in the healthcare industry with those in other industries, we considered age, sex, and income quartile characteristics and conducted propensity scored matching.ResultsIn the matching study, workers in healthcare industry had higher odds ratios for mood disorders (1.13, 95% CI: 1.11–1.15), anxiety disorders (1.15, 95% CI: 1.13–1.17), sleep disorders (2.21, 95% CI: 2.18–2.24), and any psychiatric disorders (1.44, 95% CI: 1.43–1.46) than the reference group did. Among workers in healthcare industry, females had higher prevalence of psychiatric disorders than males, but the odds ratios for psychiatric disorders, compared to the reference group, were higher in male workers in healthcare industry than in females.ConclusionsThe prevalence of mood disorders, anxiety disorders, sleep disorders, and all psychiatric disorders for workers in the healthcare industry was higher than that of other Korean workers. The strikingly high prevalence of sleep disorders could be related to the frequent night-shifts in these professions. The high prevalence of mental health problems among workers in healthcare industry is alarming and requires prompt action to protect the health of the “protectors.”

BackgroundWith the development of technology, extensive use of computers in the workplace is prevalent and increases efficiency. However, computer users are facing new harmful working conditions with high workloads and longer hours. This study aimed to investigate the association between computer use at work and self-reported depressive and anxiety disorder (DAD) in a nationally representative sample of South Korean workers.MethodsThis cross-sectional study was based on the third Korean Working Conditions Survey (2011), and 48,850 workers were analyzed. Information about computer use and DAD was obtained from a self-administered questionnaire. We investigated the relation between computer use at work and DAD using logistic regression.ResultsThe 12-month prevalence of DAD in computer-using workers was 1.46 %. After adjustment for socio-demographic factors, the odds ratio for DAD was higher in workers using computers more than 75 % of their workday (OR 1.69, 95 % CI 1.30−2.20) than in workers using computers less than 50 % of their shift. After stratifying by working hours, computer use for over 75 % of the work time was significantly associated with increased odds of DAD in 20–39, 41–50, 51–60, and over 60 working hours per week. After stratifying by occupation, education, and job status, computer use for more than 75 % of the work time was related with higher odds of DAD in sales and service workers, those with high school and college education, and those who were self-employed and employers.ConclusionsA high proportion of computer use at work may be associated with depressive and anxiety disorder. This finding suggests the necessity of a work guideline to help the workers suffering from high computer use at work.Electronic supplementary materialThe online version of this article (doi:10.1186/s40557-016-0146-8) contains supplementary material, which is available to authorized users.

Long working hours are significantly related to risk of coronary heart disease.

Doping and alloying are fundamental strategies to improve the thermoelectric performance of bare materials. However, identifying outstanding elements and compositions for the development of high-performance thermoelectric materials is challenging. In this study, we present a data-driven approach to improve the thermoelectric performance of SnSe compounds with various doping. Based on the newly generated experimental and computational dataset, we built highly accurate predictive models of thermoelectric properties of doped SnSe compounds. A well-designed feature vector consisting of the chemical properties of a single atom and the electronic structures of a solid plays a key role in achieving accurate predictions for unknown doping elements. Using the machine learning predictive models and calculated map of the solubility limit for each dopant, we rapidly screened high-dimensional material spaces of doped SnSe and evaluated their thermoelectric properties. This data-driven search provided overall strategies to optimize and improve the thermoelectric properties of doped SnSe compounds. In particular, we identified five dopant candidate elements (Ge, Pb, Y, Cd, and As) that provided a high ZT exceeding 2.0 and proposed a design principle for improving the ZT by Sn vacancies depending on the doping elements. Based on the search, we proposed yttrium as a new high-ZT dopant for SnSe with experimental confirmations. Our research is expected to lead to novel high-ZT thermoelectric material candidates and provide cutting-edge research strategies for materials design and extraction of design principles through data-driven research.