The purpose of this study was to investigate the status of occupational burnout and its influence on the psychological health of factory workers and miners, in order to provide theoretical basis and reference for alleviating occupational burnout and promoting psychological health. The cross-sectional study investigated 6130 factory workers and miners with online questionnaire; the Chinese Maslach Burnout Inventory (CMBI) and Symptom Check List-90 (SCL-90) were used. In total, 6120 valid questionnaires were collected; effectiveness was 99.8%. The percentage of the factory workers and miners suffering from occupational burnout was 85.98% and psychological health problems was 38.27%. A statistically significant difference was observed in relation to the prevalence of occupational burnout among factory workers and miners of different sex, education level, labor contracts, work schedule, monthly incomes, weight, hypertension, age, working years, working hours per day, working hours per week, coal dust, silica dust, asbestos dust, benzene, lead, and noise. The detection rate of psychological health was higher for males than females. The detection rate of psychological health was higher for working days per week less than 5 days than more than 5 days. The detection rate of psychological health with high school education, senior professional title, night shift, divorced, monthly income less than 3000 yuan, weight more than 75 kg, age more than 45 years, and working years between 25 and 30 years was higher than that of the other groups. The results showed that sex, education level, professional title, work schedule, monthly income, hypertension, age, working years, asbestos dust, benzene, and occupational burnout affected psychological health among factory workers and miners. Factory workers and miners had high levels of occupational burnout, and occupational burnout was a risk factor that can lead to psychological health.
Background The coronavirus disease 2019 (COVID-19) has increased the physical and psychological stress of medical workers. This study was designed to investigate the prevalence and risk factors of job burnout and its impact on work ability among Biosafety Laboratory (BSL) staffs during the COVID-19 epidemic in Xinjiang. Methods A total of 7911 qualified BSL staffs in Xinjiang were investigated by electronic questionnaires. The Maslach Burnout Inventory-General Survey (MBI-GS) was used for job burnout survey. Work Ability Index (WAI) was used for work ability survey. The prevalence and risk factors of job burnout in BSL staffs were analyzed through chi square test, t-test and one-way ANOVA. And then, the influence of demographic and job-related variables, i.e., confounding factors, were eliminated to the greatest extent by the propensity score analysis (PSA) method, to investigate the impact of job burnout on work ability in BSL staffs. Results A total of 67.6% BSL staffs experienced job burnout. There were significant differences in the detection rate of job burnout among demographic and job-related variables, including gender, age, ethnicity, education, working years, professional title, marital status, number of night shift per month and overall sleep condition (all P < 0.05). The detection rate of job burnout in female was higher than that in male. The detection rates of job burnout in 45–50 years old, Han ethnicity, education of postgraduate or above, 11–20 years of working, intermediate professional title, married, staff with many night shifts per month and poor overall sleep condition were higher than that of other groups. The average burnout scores of the Emotional Exhaustion (EE), Cynicism (CY), Reduced Personal Accomplishment (PA) scale were 10.00 ± 5.99, 4.64 ± 4.59 and 15.25 ± 8.16, respectively. Multiple logistic regression analysis showed that the three dimensions of job burnout, i.e., EE, CY, PE, were negatively correlated with work ability and significantly affected the work ability of BSL staffs (all P < 0.001). Conclusions Our results suggest that the prevalence of job burnout is extremely common among BSL staffs. In addition, the work ability decreases with the increase of job burnout and the improvement of job burnout can enhance work ability among BSL staffs.
This study is to evaluate the effects of different occupational hazards on job stress and mental health of factory workers and miners. A total of 6120 workers from factories and mining enterprises in seven districts and one district of Urumqi were determined using the stratified cluster random sampling method. The Effort-Reward Imbalance (ERI) questionnaire and the Symptom Checklist-90 (SCL-90) were used to evaluate the effects of occupational hazard factors on job stress and mental health of workers. The propensity score analysis was used to control the confounding factors. The occupational hazards affecting job stress of workers were asbestos dust (OR=1.3, 95% CI: 1.09-1.55), benzene (OR=1.25, 95% CI: 1.10-1.41), and noise (OR=1.39, 95% CI: 1.22-1.59). The occupational hazards affecting the mental health of workers were coal dust (OR=1.19, 95% CI: 1.02-1.38), asbestos dust (OR=1.58, 95% CI: 1.32-1.92), benzene (OR=1.28, 95% CI: 1.13-1.47), and noise (OR=1.23, 95% CI: 1.07-1.42). Different occupational hazards have certain influence on job stress and mental health of factory workers and miners. The enhancements in occupational hazard and risk assessment, occupational health examination, and occupational protection should be taken to relieve job stress and enhance the mental health of factory workers and miners.
Background Hypertension has been declared as a global public health crisis by the World Health Organization, because of its high prevalence. It affects the health of one billion people worldwide and is directly responsible for the deaths of more than 10 million people per year. The purpose of our research was to explore the influence of occupational stress and psychological health on hypertension of miners who work in a noisy environment and provide decision reference for relevant departments to keep miners’ health. Methods A case-control study was carried out in this research. The study subjects were divided into case groups and control groups based on whether they had hypertension or not. Effort-Reward Imbalance questionnaire and Self-Reporting Inventory questionnaire were used to investigate the psychological health status and occupational stress of the target population. General information was balanced between case and control groups through propensity score matching method. After propensity score matching, a multifactorial analysis was used to explore the impact of occupational stress and psychological health on hypertension. Results According to the result of the multivariate analysis, psychological health was hazard to hypertension (t = 5.080, P<0.001) and occupational stress was not a direct risk factor for hypertension (t = 1.760, P = 0.080). The model was statistically significant (χ2 = 20.4, P<0.01). Conclusions For miners working in the noisy environment, psychological status was a direct risk factor to hypertension, while occupational stress was an indirect factor.
Occupational disease is a huge problem in China, and many workers are under risk. Accurate forecasting of occupational disease incidence can provide critical information for prevention and control. Therefore, in this study, five hybrid algorithm combing models were assessed on their effectiveness and applicability to predict the incidence of occupational diseases in China. The five hybrid algorithm combing models are the combination of five grey models (EGM, ODGM, EDGM, DGM, and Verhulst) and five state-of-art machine learning models (KNN, SVM, RF, GBM, and ANN). The quality of the models were assessed based on the accuracy of model prediction as well as minimizing mean absolute percentage error (MAPE) and root-mean-squared error (RMSE). Our results showed that the GM-ANN model provided the most precise prediction among all the models with lowest mean absolute percentage error (MAPE) of 3.49% and root-mean-squared error (RMSE) of 1076.60. Therefore, the GM-ANN model can be used for precise prediction of occupational diseases in China, which may provide valuable information for the prevention and control of occupational diseases in the future.
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