Purpose: The aim of this study was to investigate and identify work environment, job embeddedness, and burnout among general hospital nurses in Korea. Methods: The participants were 563 clinical nurses working in 13 general hospitals across the country. Data were analyzed using SPSS and Microsoft Excel programs. Results: Mean scores were 2.62 for nurses' work environment, 2.97 for job embeddedness, and 3.61 for burnout. Nurses' work environment showed a positive correlation with job embeddedness (r=.70, p<.001), but a negative correlation with burnout (r=-.49, p<.001). Subcategories of nurses' work environment that predicted job embeddedness included satisfaction and happiness, hospital support for the work environment, patient care environment, satisfaction with work schedule, manager leadership, supportive environment for nurses' work, and computer problems. Subcategories of nurses' work environment that predicted burnout included satisfaction and happiness, violence within ward, hospital support for work environment, and patient care environment. Conclusion: Findings from this study indicate the need to evaluate and improve the work environment for nurses to increase job embeddedness and control burnout. Future studies should explore ways in which turnover intention can be decreased by changing nurses' work environment.
연구의 필요성서비스산업은Purpose: The purpose of this study was to propose and test a predictive model that could explain and predict nursing productivity. Methods: A survey using a structured questionnaire was conducted with 360 nurses in Korea. The data were analyzed using SPSS Windows 18.0 and AMOS 19.0 program. Results: Based on the constructed model, burnout and organizational commitment were found to have direct effects on nurses' turnover intention and nursing productivity. While nursing work environment was found to have indirect effects on nurses' turnover intention and nursing productivity. Conclusion: This structural equational model is a comprehensive theoretical model that explains the related factors and their relationship with nursing productivity. Comprehensive organizational interventions to improve nursing productivity should focus on improving the nursing work environment. Findings from this study can be used to design appropriate strategies to decrease nurse turnover in Korea. Further studies are needed to prospectively verify these causal relationships with larger samples.
T cell receptor (TCR) repertoires are critical for antiviral immunity. Determining the TCR repertoires composition, diversity, and dynamics and how they change during viral infection can inform the molecular specificity of viral infection such as SARS-CoV-2. To determine signatures associated with COVID-19 disease severity, here we performed a large-scale analysis of over 4.7 billion sequences across 2,130 TCR repertoires from COVID-19 patients and healthy donors. TCR repertoire analyses from these data identified and characterized convergent COVID-19 associated CDR3 gene usages, specificity groups, and sequence patterns. T cell clonal expansion was found to be associated with upregulation of T cell effector function, TCR signaling, NF-kB signaling, and Interferon-gamma signaling pathways. Machine learning approaches accurately predicted disease severity for patients based on TCR sequence features, with certain high-power models reaching near-perfect AUROC scores across various predictor permutations. These analyses provided an integrative, systems immunology view of T cell adaptive immune responses to COVID-19.
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