Promoting a Mock Disaster Simulation with Leadership from a Nurse Residency Program

Opsahl, Angela; Morris, Toni; Judge, Deborah; Werskey, Karen; Edwards, Billie; Robinson, Danielle

doi:10.1016/j.teln.2019.01.004

Cited by 12 publications

(2 citation statements)

References 12 publications

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“…Literature [16] used a multiple regression model to conduct regression analysis on landslide mass and described the horizontal motion law of landslide mass from a statistical point of view. In the study of power grid vulnerability, aiming at the instability of the power system, literature [17] constructs the probability model of transmission line failure. Literature [18] proposes a method to test the cable stiffness.…”

Section: Introductionmentioning

confidence: 99%

Reliability Analysis of Multisensor Fusion Technology in Disaster Nursing Application

Luo

Zhou

et al. 2022

Journal of Sensors

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The harm and impact of various natural disasters are becoming more and more obvious. Due to the high suddenness of natural disasters and the low efficiency of information sharing, our stress system will still not be able to respond to disasters in time. Therefore, facing the current complex natural environment and the diversity of disasters, we urgently need a practical and comprehensive online collaborative natural disaster protection system. Therefore, this paper proposes a disaster protection application system based on a multisensor information fusion algorithm. Firstly, the software platform of the natural disaster protection system based on multisensor is constructed; the hardware platform of multisensor disaster acquisition is designed. An information fusion algorithm based on Kalman joint filter is proposed. The main problems of joint filter are (1) improving the filtering accuracy, (2) improving the fault-tolerant performance of the filter, and (3) optimizing the fusion algorithm and reducing the amount of calculation and data communication, so as to facilitate real-time implementation of the algorithm. Combined with DS evidence theory, BP neural network, and support vector mechanism, a comprehensive diagnosis model is established. The model uses the preliminary diagnosis results of the BP neural network and support vector machine to carry out the BPA of DS evidence theory, which avoids the blindness caused by human operation. The simulation results show that the comprehensive diagnosis model can significantly improve the prediction accuracy of disasters, solve the uncertainty and fuzziness of diagnosis results of a single diagnosis model, and provide a new method for disaster protection. The results of the BP neural network in the disaster nursing system are fused at the decision level, the results show that the distribution probability corresponding to the fusion disaster category is greater than the threshold value of 0.8, and the diagnosis result can be given immediately. The diagnosis result is completely consistent with the actual disaster category.

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Section: Introductionmentioning

confidence: 99%

Reliability Analysis of Multisensor Fusion Technology in Disaster Nursing Application

Luo

Zhou

et al. 2022

Journal of Sensors

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“…Simulation has been identified as an effective strategy to teach disaster response to nursing students. Specifically, it has been shown to enhance comprehension of disaster response, triage skills, and increase student confidence in client care and teamwork abilities 9–11 …”

Section: Introductionmentioning

confidence: 99%

Nursing student's attitudes toward teams in an undergraduate interprofessional mass casualty simulation

et al. 2021

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Background Interprofessional education (IPE) aims to prepare future nurses for collaboration with healthcare professionals. Army style lane training may be an effective pedagogical technique for delivering emergency care and mass casualty training while incorporating IPE. Purpose. This study sought to determine attitudes toward IPE and teamwork in pre‐licensure, undergraduate nursing students following a lane training simulation. Method Pre‐ and postsimulation surveys containing sociodemographic, reflection, and KidSIM Attitude Toward Teamwork in Training Undergoing Designed Educational Simulation (KidSIM) items (Sigalet et al., 2012) were conducted. Results The KidSIM tool was deemed reliable (α = .98). Paired sample t tests resulted in significant increases for the KiDSIM and its subscales, with the exception of communication. However, communication, along with situation assessment and teamwork were reported to be most enhanced by students. Conclusion Results support using the Army lane training model in an IPE environment for teaching emergency care, triage, and mass casualty procedures.

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Leveraging the community of inquiry framework to support web-based simulations in disaster studies

Cooper

Forino

Kanjanabootra

et al. 2020

The Internet and Higher Education

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Promoting a Mock Disaster Simulation with Leadership from a Nurse Residency Program

Cited by 12 publications

References 12 publications

Reliability Analysis of Multisensor Fusion Technology in Disaster Nursing Application

Reliability Analysis of Multisensor Fusion Technology in Disaster Nursing Application

Nursing student's attitudes toward teams in an undergraduate interprofessional mass casualty simulation

Leveraging the community of inquiry framework to support web-based simulations in disaster studies

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