XR2ESILIENCE

Project: Research

Project participants

Description

The health care system is in crisis and although the importance of nurses' mental health is widely recognized, achieving this goal is highly challenging. Promoting resilience in times of crisis appears to be a promising goal for public mental health. Innovative digital technologies to enhance resilience might contribute to a solution. Extended reality (XR) applications are highly immersive, interactive, and attractive to use. The proposed project aims to leverage the potential of XR to promote esilience in nursing staff. As resilience has a multitude of facets a prospective cohort study together with new analysis of existing large datasets will inform about those resilience factors that are the most promising target for interventions in nurses. Likewise, barriers and facilitators of acceptance of resilience training in general and XR-supported interventions in particular will be extensively considered and researched within this project. As acceptance through participation is a key success factor, a XR-supported training to foster resilience will be developed in close cooperation with nurses and other stakeholders. The proposed XR2ESILIENCE solution consists of a flexible selection of XR modules that can be customised to meet individual nurse needs. The efficacy of XR2ESILIENCE on stress coping and resilience will be investigated in a randomised controlled trial including a health economic evaluation. In addition, the project will go beyond the individual perspective and consider
organisational and structural challenges. The cohort study will enable to identify working environments where nurses can grow and enfold their resilience. Based on the results, will develop a set of recommendations and checklists for employers and policymakers that support them in making nursing facilities resilience friendly places. XR2ESILIENCE outlines a strategy for building resilience and the role of XR in resilience training.
StatusActive
Period01.08.2431.07.28

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Publications

  1. Identification of conductive fiber parameters with transcutaneous electrical nerve stimulation signal using RLS algorithm
  2. Artificial intelligence
  3. Early Detection of Faillure in Conveyor Chain Systems by Wireless Sensor Node
  4. Design, Modeling and Control of an Over-actuated Hexacopter Tilt-Rotor
  5. A framework for business model development in technology-driven start-ups
  6. Introducing split orders and optimizing operational policies in robotic mobile fulfillment systems
  7. Comparison of Bio-Inspired Algorithms in a Case Study for Optimizing Capacitor Bank Allocation in Electrical Power Distribution
  8. Managing complexity in automative production
  9. Designing and evaluating blended learning bridging courses in mathematics
  10. What Makes for a Good Theory? How to Evaluate a Theory Using the Strength Model of Self-Control as an Example
  11. Do connectives improve the level of understandability in mathematical reality-based tasks?
  12. Executive function and Language Learning
  13. An error management perspective on audit quality
  14. TARGET SETTING FOR OPERATIONAL PERFORMANCE IMPROVEMENTS - STUDY CASE -
  15. Measuring cognitive load with subjective rating scales during problem solving
  16. The temporal pattern of creativity and implementation in teams
  17. Conceptions of problem solving mathematics teaching
  18. A reference architecture for the integration of EMIS and ERP-Systems
  19. The erosion of relational values resulting from landscape simplification
  20. Parametric finite element model and mechanical characterisation of electrospun materials for biomedical applications
  21. What´s in a net? or: The end of the average
  22. Governing Objects from a Distance
  23. Obstacle Coordinates Transformation from TVS Body-Frame to AGV Navigation-Frame
  24. Noninteracting optimal and adaptive torque control using an online parameter estimation with help of polynomials in EKF for a PMSM
  25. Convolutional Neural Networks
  26. Development of a scoring parameter to characterize data quality of centroids in high-resolution mass spectra