[Bayesian network prediction study on the impact of occupational health psychological factors on insomnia among thermal power generation workers].

Objective: To explore the risk factors of insomnia among employees in the thermal power generation industry and the network relationships between their interactions, and to provide scientific basis for personalized interventions for high-risk groups with insomnia. Methods: In November 2022, 860 employees of a typical thermal power generation enterprise were selected as the research subjects by cluster sampling. On-site occupational health field surveys and questionnaire surveys were used to collect basic information, occupational characteristics, anxiety, depression, stress, occupational stress, and insomnia. The interaction between insomnia and occupational health psychological factors was evaluated by using structural equation model analysis and Bayesian network construction. Results: The detection rates of anxiety, depression and stress were 34.0% (292/860), 32.1% (276/860) and 18.0% (155/860), respectively. The total score of occupational stress was (445.3±49.9) points, and 160 workers (18.6%) were suspected of insomnia, and 578 workers (67.2%) had insomnia. Structural equation model analysis showed that occupational stress had a significant effect on the occurrence of insomnia in thermal power generation workers (standardized load coefficient was 0.644), and occupational health psychology had a low effect on insomnia (standardized load coefficient was 0.065). However, the Bayesian network model further analysis found that anxiety and stress were the two parent nodes of insomnia, with direct causal relationships, the arc strength was-8.607 and -15.665, respectively. The model prediction results showed that the probability of insomnia occurring was predicted to be 0 in the cases of no stress and anxiety, low stress without anxiety, and no stress with low anxiety. When high stress with low anxiety and low stress with high anxiety occurred, the predicted probability of insomnia occurring were 0.38 and 0.47, respectively. When both high stress and high anxiety occurred simultaneously, the predicted probability of insomnia occurring was 0.51. Conclusion: Bayesian network risk assessment can intuitively reveal and predict the insomnia risk of thermal power generation workers and the network interaction relationship between the risks. Anxiety and stress are the direct causal risks of insomnia, and stress is the main risk of individual insomnia of thermal power generation workers. The occurrence of insomnia can be reduced based on scientific intervention of stress conditions.

[Effects of Personality and Psychological Acceptance on Medical Workers' Occupational Stress].

Objective: To assess psychological acceptance and occupational stress of medical staff, analyze the relationship among personality, psychological acceptance and occupational stress and discuss the direct or indirect effects of personality to occupational stress. Methods: Eysenck Personality Questionnaire (EPQ-RSC) , Acceptance and Action Questionnaire-II (AAQ-Ⅱ) and Revised Occupational Stress Inventory (OSI-R) were administered to 749 medical staff. Results: The level of occupational stress of medical staff was high, the score of PSY was 26.8±7.13 and the score of PHS was 24.3±6.50. Personality and psychological acceptance can predict occupational stress. Psychological acceptance was a protective factor of occupational stress. Medical staff with personality of introversion, neuroticism and psychoticism suffered higher occupational stress. Personality have both direct and indirect effects on occupational stress. Neuroticism have the strongest effect on occupational stress with effect size of 0.496 (psychological stress) and 0.431 (physical strain) . Conclusion: Medical staff have heavier occupational stress. There is a significant correlation between personality and occupational stress. Measures depending on personality should be taken to deal with this situation.

[Mediating effect of mental elasticity on occupational stress and depression in female nurses].

Objective: To investigate the interaction between mental elasticityand occupational stress and depressionin female nurses and the mediating effect of mental elasticity, as well as the functioning way of mental elasticity in occupational stress-depression. Methods: From August to October, 2015, cluster sampling was used to select 122 female nurses in a county-level medical institution as study subjects. The Connor-Davidson Resilience Scale (CD-RISC) , Occupational Stress Inventory-Revised Edition (OSI-R) , and Self-Rating Depression Scale (SDS) were used to collect the data on mental elasticity, occupational stress, and depression and analyze their correlation and mediating effect. Results: The 122 female nurses had a mean mental elasticity score of 62.4±15.1, which was significantly lower than the Chinese norm (65.4±13.9) (P<0.05) ; the mean depression score was 41.0±7.7, which was significantly higher than the Chinese norm (33.5±8.6) (P<0.01) , and the incidence rate of depression of 52.5%. Mental elasticity was negatively correlated with occupational stress and depression (r=-0.559 and -0.559, both P<0.01) . Occupational stress and the two subscales mental stress reaction and physical stress reaction were positively correlated with depression (r=0.774, 0.734, and 0.725, all P<0.01) . After adjustment for confounding factors, occupational stress had a positive predictive effect on depression (ß=0.744, P<0.01) , and mental elasticity had a negative predictive effect on depression (ß=-0.221, P<0.01) . The analysis of mediating effect showed a significant direct effect of occupational stress on depression and a significant mediating effect of mental elasticity (a=-0.527, b=-0.227, c=0.744, c'=0.627; all P<0.01) , and the mediating effect of mental elasticity accounted for 16.08% of the total effect. Conclusion: As a partial mediating variable, mental elasticity has an indirect effect on the relationship between occupational stress and depression and can alleviate the adverse effect of occupational stress and reduce the development of depression.