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SafeVRwards: Designing a complementary virtual reality module to the Safewards framework intended to relax and manage conflict in mental health wards. | LitMetric

AI Article Synopsis

  • A study looks at using virtual reality (VR) therapy to help manage conflict in mental health hospitals, based on a system called Safewards that has 10 strategies like 'Calm Down Methods'.
  • The research gathers feedback from nurses at a hospital to see how well VR can add to the existing techniques to keep everyone safe and calm.
  • Early results suggest that VR could be a useful tool in mental health care, with plans to make it even better based on the staff's ideas and experiences.

Article Abstract

Background: Aggression and negative activation in mental health inpatient units pose significant challenges for both patients and staff with severe physical and psychological ramifications. The Safewards model is an evidence-based conflict-containment framework including 10 strategies, such as 'Calm Down Methods'. As virtual reality (VR) scenarios have successfully enhanced anxiolytic and deactivating effects of therapeutic interventions, they are increasingly considered a means to enhance current models, like Safewards.

Objectives: The present participatory design investigates the feasibility and user experience of integrating VR therapy as an add-on strategy to the Safewards model, gathering preliminary data and qualitative feedback from bedside staff in an adult inpatient mental health unit.

Methods: An exploratory within-subjects design combining qualitative observations, self-report questionnaires and semistructured interviews is employed with four nurse champions from the mental health unit at Michael Garron Hospital (Toronto, Canada).

Results: A chronological overview of the design process, adaptations and description of the user experience is reported.

Conclusion: 'SafeVRwards' introduces VR as a promising conflic-containment strategy complementary to the Safewards model, which can be optimised for deployment through user-oriented refinements and enhanced customisation capacity driven by clinical staff input.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11163655PMC
http://dx.doi.org/10.1136/bmjoq-2024-002769DOI Listing

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