Conectar
by Jiaxu Chen, Lin Zhao, Jinghui Liu, Gaolei Wang, Zhan Guo
To quantitatively analyze the coupling relationships between railway safety risk factors, identify key factors contributing to railway accidents, and develop scientific strategies for accident prevention, this study introduces a complex network-based N-K model to investigate the coupling relationships of railway safety risk factors. First, we identified 18 railway safety risk factors by analyzing case data from railway accidents. The occurrence probabilities and coupling values of these risk factors were then calculated using the N-K model. Subsequently, based on the constructed railway safety risk complex network, reachability and centrality analyses were performed to determine the key factors of railway safety risk. Results indicate that the occurrence of railway accidents is directly proportional to the risk coupling value; the greater the number of coupling factors, the higher the risk value. The coupling of personnel factors and equipment factors is particularly prone to leading to railway accidents. Conversely, effective management of the coupling between personnel and equipment factors can significantly reduce the likelihood of accidents. Inadequate maintenance and unsafe human behavior were identified as critical factors contributing to railway accidents and should be prioritized in prevention efforts.This study aimed to develop a structural model to elucidate the contributions of social support, health literacy and psychological resilience to self-management behaviours in liver transplant recipients after surgery.
Cross-sectional study.
This study included 215 Chinese patients who returned to the outpatient department after liver transplantation between June 2023 and March 2024. Data were collected via a general demographic questionnaire, a self-management questionnaire for liver transplant recipients, a chronic disease resource questionnaire, the Connor–Davidson resilience scale and the health literacy scale for chronic patients. Correlation analysis and structural equation modelling were utilised to analyse the relationships among social support, health literacy, psychological resilience and self-management ability.
The final model showed good fit (χ 2/df = 1.690, GFI = 0.919, IFI = 0.951, TLI = 0.938, CFI = 0.950 and RMSEA = 0.057). The direct effect coefficient of social support on self-management ability is 0.293. The indirect effect value of health literacy on the relationship between social support and self-management ability was 0.312, whereas the indirect effect value of psychological resilience in this context was 0.096. Furthermore, the chain-mediating effect involving both health literacy and psychological resilience between social support and self-management ability was 0.109.
The revised model, grounded in social cognitive theory, demonstrated a strong fit for predicting self-management behaviours among liver transplant recipients. Furthermore, social support, health literacy and psychological resilience exerted both direct and indirect influences on the self-management behaviours of these recipients.
Strengthening the Reporting of Observational Studies in Epidemiology (STROBE).
In public or patient involvement in this study.
FreshRSS 