Mental health symptoms among dependent contractors in Korea: a cross-sectional study based on the Fifth Korean Working Condition Survey.

Background: Recently, there has been a call to improve the holistic welfare of dependent contractors (DCs). Thus, our study examined the relationship between DCs and mental health symptoms and how this relationship was modified by age, sex, and income status of workers.

Methods: A total of 27,980 workers from the Fifth Korean Working Conditions Survey are included in our study.

Irregular Work Hours and the Risk of Sleep Disturbance Among Korean Service Workers Required to Suppress Emotion.

Although a necessity in a modern society, irregular work schedule can lead to sleep problems. We investigated the effect of work schedule irregularity on sleep disturbance of 17,846 Korean service workers using the fifth Korean Working Conditions Survey. The odds ratio (OR) and 95% confidence interval (CI) for sleep disturbance occurrence were calculated through a multiple logistic regression model.

Work Schedule Irregularity and the Risk of Work-Related Injury among Korean Manual Workers.

Work schedules comprise various variables and generate health and safety outcomes, including work-related injury, which causes socioeconomic problems, such as productivity loss and damage to worker health. We investigated the association between work schedule irregularity and the incidence of work-related injury among South Korean manual workers using data from the 5th Korean Working Conditions Survey. In total, 18,330 manual workers were included.

The role of customer service manual on workplace emotional burden in nationwide cross sectional study.

Background: We aim to discuss the overall effect of customer service manual (CSM) on service industry workers using Korean Working Condition Survey.

Methods: Out of 50,007 total survey participants, 11,946 customer service workers were included in the current study (5613 men, 6333 women). Answers to survey questions were used to define the use of CSM, emotional burden, emotional dissonance, engaging angry customers and other covariates.

Deep Learning Algorithms with Demographic Information Help to Detect Tuberculosis in Chest Radiographs in Annual Workers' Health Examination Data.

We aimed to use deep learning to detect tuberculosis in chest radiographs in annual workers' health examination data and compare the performances of convolutional neural networks (CNNs) based on images only (I-CNN) and CNNs including demographic variables (D-CNN). The I-CNN and D-CNN models were trained on 1000 chest X-ray images, both positive and negative, for tuberculosis. Feature extraction was conducted using VGG19, InceptionV3, ResNet50, DenseNet121, and InceptionResNetV2.

Income Changes Due to Disability Ratings and Participation in Economic Activities Caused by Industrial Accidents: A Population-Based Study of Data from the Fourth Panel Study of Workers' Compensation Insurance (PSWCI).

Industrial accidents cost a huge amount of money, but they also have negative consequences in many respects. We analyzed the data of the first to fourth panel study of workers' compensation insurance (PSWCI). Repeated measures ANOVA was used to compare the annual income before and after the industrial accident, and a general linear model was used to identify changes in income due to disability ratings and participation in economic activities.

Abdominal fat suspension device for maintaining normal cardiorespiratory function in patients undergoing conscious sedation during surgery: a feasibility study.

Obese patients undergoing conscious-sedation surgery have increased perioperative morbidity because their excess abdominal tissue limits diaphragmatic excursion. We describe a simple device that might help attenuate this risk. We created a noninvasive suction device for abdominal suspension.