Login / Signup

Learning and Treatment of Anaphylaxis by Laypeople: A Simulation Study Using Pupilar Technology.

Felipe Fernandez-MendezNieves Maria Saez-GallegoRoberto Barcala-FurelosCristian Abelairas-GomezAlexis Padron-CaboAlexandra Pérez-FerreirósCarlos Garcia-MaganJose Moure-GonzalezOnofre Contreras-JordanAntonio Rodriguez-Nuñez
Published in: BioMed research international (2017)
An anaphylactic shock is a time-critical emergency situation. The decision-making during emergencies is an important responsibility but difficult to study. Eye-tracking technology allows us to identify visual patterns involved in the decision-making. The aim of this pilot study was to evaluate two training models for the recognition and treatment of anaphylaxis by laypeople, based on expert assessment and eye-tracking technology. A cross-sectional quasi-experimental simulation study was made to evaluate the identification and treatment of anaphylaxis. 50 subjects were randomly assigned to four groups: three groups watching different training videos with content supervised by sanitary personnel and one control group who received face-to-face training during paediatric practice. To evaluate the learning, a simulation scenario represented by an anaphylaxis' victim was designed. A device capturing eye movement as well as expert valuation was used to evaluate the performance. The subjects that underwent paediatric face-to-face training achieved better and faster recognition of the anaphylaxis. They also used the adrenaline injector with better precision and less mistakes, and they needed a smaller number of visual fixations to recognise the anaphylaxis and to make the decision to inject epinephrine. Analysing the different video formats, mixed results were obtained. Therefore, they should be tested to evaluate their usability before implementation.
Keyphrases
  • decision making
  • virtual reality
  • emergency department
  • healthcare
  • primary care
  • intensive care unit
  • machine learning
  • combination therapy
  • quality improvement
  • electronic health record