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Aim: To evaluate the impact transformational leadership (TFL) behaviors and What Matters to You conversations have on RNs finding meaning and joy in work (MJW) and turnover. Background: The nursing profession is plagued by burnout - a precursor to loss of MJW. Loss of MJW was exhibited as low

Aim: To evaluate the impact transformational leadership (TFL) behaviors and What Matters to You conversations have on RNs finding meaning and joy in work (MJW) and turnover. Background: The nursing profession is plagued by burnout - a precursor to loss of MJW. Loss of MJW was exhibited as low morale and increased turnover among acute care RNs at a small hospital in Southwest Arizona. Addressing loss of MJW aligns with caring for the caregiver, the fourth aim of the quadruple aim initiative. Methods: This was a quasi?experimental mixed methodology evidence-based project. The target populations were core RNs and leaders working in the intensive care unit, care unit, and emergency department. Intervention was multimodal – survey using Meaning and Joy in Work Questionnaire, TFL education, and steps one and two of the IHI four steps for leaders model. Results: Final sample was 18 RNs. Statistical analyses did not reveal significant impact; pre- and post-survey MJWQ scores remained above four. Themes from the What Matters to You conversations included making a difference, coworkers/connections, staffing, and negativity. Turnover trended positively in two of the three units. Conclusion: This project heightened awareness about MJW and illuminated the impact TFL behaviors can have on RNs finding MJW and turnover. The coronavirus pandemic and acute nursing shortage were significant limitations of the project. Implications: Healthcare organizations are encouraged to view MJW as a system asset, embed it in their cultures, invest in innovative solutions, and continually evaluate outcome measures of MJW.
Created2022-04-28
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Burnout has become an increasingly popular topic among registered nurses, but unfortunately burnout among psychiatric nursing is less understood than other nursing specialties such as the Intensive Care Unit, Emergency Room, or Oncology. Psychiatry is unique and psychiatric nurses, in particular, are often subjected to physical and verbal violence as

Burnout has become an increasingly popular topic among registered nurses, but unfortunately burnout among psychiatric nursing is less understood than other nursing specialties such as the Intensive Care Unit, Emergency Room, or Oncology. Psychiatry is unique and psychiatric nurses, in particular, are often subjected to physical and verbal violence as well as exposure to patient’s trauma. The aim of this project was to decrease burnout among psychiatric nurses in a private practice out-patient family psychiatric facility using Rossworm and Larabee’s change model (Appendix D). The MBI-HSS was completed by 1 participant (n=1) at pre-intervention and post-intervention. Between the pre/post MBI-HSS questionnaire the participant was asked to partake in a mindfulness-based intervention utilizing the smartphone application Headspace to complete a 10-session meditation course over one week. The results conclude the participant’s burnout decreased overall from pre-intervention to post-intervention. Internal Review Board (IRB) was granted in September 2021, and the project was completed in November 2021. The impact of the project was projected to have a more thorough statistical influence, but due to the participant size, there is minimal impact of system or polices in the psychiatric facility.
Created2022-04-30
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Description
Purpose & Background: Nurses regularly have encounters with traumatic and stressful events which can have deleterious effects on their physical and psychological well-being and lead to burnout. The Covid-19 pandemic has further exacerbated the stress on nurses. The purpose of this project is to evaluate if an evidence-based, guided mindfulness-based intervention

Purpose & Background: Nurses regularly have encounters with traumatic and stressful events which can have deleterious effects on their physical and psychological well-being and lead to burnout. The Covid-19 pandemic has further exacerbated the stress on nurses. The purpose of this project is to evaluate if an evidence-based, guided mindfulness-based intervention would reduce burnout levels among registered nurses (RNs) working in in-patient settings. Methods: Participants enrolled in nursing programs from a local university were recruited for the project with the following inclusion requirements: (1) RNs working in an in-patient setting, (2) aged 18 years old or older; (3) fluent in the English language. Participants completed a pre-survey and then enrolled in a free mindfulness application via their phone or computer. Participants listened to one ten-minute mindfulness session for a consecutive ten days and then completed a post-survey. Results: Data collected from the pre and post surveys included the use of the following valid and reliable instrument tools: Copenhagen Burnout Inventory, Brief Resiliency Coping Scale, and Short Form Health Survey. Data was analyzed using descriptive statistics and the Wilcoxon Signed Ranks Test. The analyzed data showed that there was statistical significance in decreased burnout levels, increased resiliency, and increased health perceptions of the participants. Conclusion: By finding ways to cope with the experience of burnout in nurses, nurses’ mental health wellness can improve in order for nurses to continue to be an integral part of the healthcare system.
Created2022-05-06
Description

Hybrid system models - those devised from two or more disparate sub-system models - provide a number of benefits in terms of conceptualization, development, and assessment of dynamical systems. The decomposition approach helps to formulate complex interactions that are otherwise difficult or impractical to express. However, hybrid model development and

Hybrid system models - those devised from two or more disparate sub-system models - provide a number of benefits in terms of conceptualization, development, and assessment of dynamical systems. The decomposition approach helps to formulate complex interactions that are otherwise difficult or impractical to express. However, hybrid model development and usage can introduce complexity that emerges from the composition itself.

To improve assurance of model correctness, sub-systems using disparate modeling formalisms must be integrated above and beyond just the data and control level; their composition must have model specification and simulation execution aspects as well. Poly-formalism composition is one approach to composing models in this manner.

This dissertation describes a poly-formalism composition between a Discrete EVent System specification (DEVS) model and a Cellular Automata (CA) model types. These model specifications have been chosen for their broad applicability in important and emerging domains. An agent-environment domain exemplifies the composition approach. The inherent spatial relations within a CA make it well-suited for environmental representations. Similarly, the component-based nature of agents fits well within the hierarchical component structure of DEVS.

This composition employs the use of a third model, called an interaction model, that includes methods for integrating the two model types at a formalism level, at a systems architecture level, and at a model execution level. A prototype framework using DEVS for the agent model and GRASS for the environment has been developed and is described. Furthermore, this dissertation explains how the concepts of this composition approach are being applied to a real-world research project.

This dissertation expands the tool set modelers in computer science and other disciplines have in order to build hybrid system models, and provides an interaction model for an on-going research project. The concepts and models presented in this dissertation demonstrate the feasibility of composition between discrete-event agents and discrete-time cellular automata. Furthermore, it provides concepts and models that may be applied directly, or used by a modeler to devise compositions for other research efforts.

ContributorsMayer, Gary R. (Author)
Created2009
Description

PowerPoint presentation to the Santa Fe Institute, October 2004.

ContributorsBarton, C. Michael (Author)
Created2004