Factors Affecting Infection Control Performance of School Health Nurses During the COVID-19 Pandemic in South Korea

Yim, Mi-Ra; Kim, Boyoung

doi:10.2147/jmdh.s356939

Cited by 3 publications

(2 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Xinru Wan et al [ 49 ] used the control efficiency to reflect the transmission of SARS-CoV-2 under different temperatures and humidities. A Korean study explored the attitudes and work stress of school nurses to improve the efficiency of school infection control [ 50 ]. Resource optimization played an enormous role in the effect of epidemic control, especially when resources were limited.…”

Section: Discussionmentioning

confidence: 99%

Optimal resource allocation model for COVID-19: a systematic review and meta-analysis

Wang,

Zhang,

et al. 2024

BMC Infect Dis

View full text Add to dashboard Cite

Background A lack of health resources is a common problem after the outbreak of infectious diseases, and resource optimization is an important means to solve the lack of prevention and control capacity caused by resource constraints. This study systematically evaluated the similarities and differences in the application of coronavirus disease (COVID-19) resource allocation models and analyzed the effects of different optimal resource allocations on epidemic control. Methods A systematic literature search was conducted of CNKI, WanFang, VIP, CBD, PubMed, Web of Science, Scopus and Embase for articles published from January 1, 2019, through November 23, 2023. Two reviewers independently evaluated the quality of the included studies, extracted and cross-checked the data. Moreover, publication bias and sensitivity analysis were evaluated. Results A total of 22 articles were included for systematic review; in the application of optimal allocation models, 59.09% of the studies used propagation dynamics models to simulate the allocation of various resources, and some scholars also used mathematical optimization functions (36.36%) and machine learning algorithms (31.82%) to solve the problem of resource allocation; the results of the systematic review show that differential equation modeling was more considered when testing resources optimization, the optimization function or machine learning algorithm were mostly used to optimize the bed resources; the meta-analysis results showed that the epidemic trend was obviously effectively controlled through the optimal allocation of resources, and the average control efficiency was 0.38(95%CI 0.25–0.51); Subgroup analysis revealed that the average control efficiency from high to low was health specialists 0.48(95%CI 0.37–0.59), vaccines 0.47(95%CI 0.11–0.82), testing 0.38(95%CI 0.19–0.57), personal protective equipment (PPE) 0.38(95%CI 0.06–0.70), beds 0.34(95%CI 0.14–0.53), medicines and equipment for treatment 0.32(95%CI 0.12–0.51); Funnel plots and Egger’s test showed no publication bias, and sensitivity analysis suggested robust results. Conclusion When the data are insufficient and the simulation time is short, the researchers mostly use the constructor for research; When the data are relatively sufficient and the simulation time is long, researchers choose differential equations or machine learning algorithms for research. In addition, our study showed that control efficiency is an important indicator to evaluate the effectiveness of epidemic prevention and control. Through the optimization of medical staff and vaccine allocation, greater prevention and control effects can be achieved.

show abstract

Section: Discussionmentioning

confidence: 99%

Optimal resource allocation model for COVID-19: a systematic review and meta-analysis

Wang,

Zhang,

et al. 2024

BMC Infect Dis

View full text Add to dashboard Cite

show abstract

“…Additionally, during the COVID 19 pandemic, contact tracing is a cross-departmental, human resource-intensive task in which the first round of case investigations for students and school staff is completed within 10 h by school nurses to halt the spread of the disease ( Lin et al, 2020 ). School nurses may experience extra job stress under the heavy workload of conducting infectious disease control tasks in schools within the urgent time frame ( Yim & Kim, 2022 ). Such perceived stressors experienced daily by school nurses can impact their mental health and well-being ( Hale et al, 2022 ; Lee et al, 2021 ).…”

mentioning

confidence: 99%

Burnout and Mental Health and Well-Being of School Nurses After the First Wave of the COVID-19 Pandemic: A National Cross-Sectional Survey

Chen

Liao

Lin

et al. 2023

The Journal of School Nursing

View full text Add to dashboard Cite

The aim of this study was to examine the associations between job stressors, COVID-19-related concerns, burnout, and mental health and well-being among school nurses, and whether any of these associations are mediated by burnout. Based on stratified proportional sampling, data collection was conducted by an online questionnaire distributed to 600 school nurses in Taiwan. A total of 256 participants aged between 27 and 62 years (mean = 47.08; standard deviation = 7.28) returned questionnaires. Results showed that burnout was the main mediating variable that fully mediated the relationship between COVID-19-related concerns and mental health and well-being. The effects of job stressors on mental health and well-being included direct negative effects (β = −.29) and indirect negative effects (β = −.67) through mediating factors. School health managers should be more aware of burnout and mental health and well-being among school nurses under the impact of COVID-19.

show abstract

Job Stress and Burnout Among School Health Teachers During the COVID-19 Pandemic: The Mediating Effect of Resilience and the Moderating Effect of School Organizational Culture

Jung,

Jang,

Sun

2024

Healthcare

View full text Add to dashboard Cite

Objectives: This study aims to examine the mediating effect of resilience and the moderating effect of school organizational culture on the relationship between job stress and burnout among school health teachers during COVID-19. Methods: The participants of the study were 223 school health teachers. The data collected included the Korean version of the Connor-Davidson Resilience Scale (K-CD-RISC), Job Stress Scale, Maslach Burnout Inventory (MBI), and School Organizational Culture Scale. Data analysis was performed using SPSS/WIN 25.0 software. Results: There was a significant positive correlation between job stress and burnout among school health teachers. Conversely, both resilience and school organizational culture were negatively correlated with burnout. The mediating effect of resilience on the relationship between job stress and burnout was significant. However, the moderating effect of school organizational culture was not significant. Conclusions: To prevent burnout in school health teachers, it is necessary to develop policy alternatives aimed at reducing job stress and to implement psychological and emotional support measures to improve resilience.

show abstract

Factors Affecting Infection Control Performance of School Health Nurses During the COVID-19 Pandemic in South Korea

Cited by 3 publications

References 22 publications

Optimal resource allocation model for COVID-19: a systematic review and meta-analysis

Optimal resource allocation model for COVID-19: a systematic review and meta-analysis

Burnout and Mental Health and Well-Being of School Nurses After the First Wave of the COVID-19 Pandemic: A National Cross-Sectional Survey

Job Stress and Burnout Among School Health Teachers During the COVID-19 Pandemic: The Mediating Effect of Resilience and the Moderating Effect of School Organizational Culture

Contact Info

Product

Resources

About