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    A skills acquisition study on ECMOjo: a screen-based simulator for extracorporeal membrane oxygenation

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    Date
    2020
    Author
    Alsalemi, Abdullah
    Tanaka, Len
    Ogino, Mark
    Disi, Mohammed Al
    Alhomsi, Yahya
    Bensaali, Faycal
    Amira, Abbes
    Alinier, Guillaume
    ...show more authors ...show less authors
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    Abstract
    Background: Extracorporeal membrane oxygenation relies heavily on didactic teaching, emphasizing on essential cognitive skills, but overlooking core behavioral skills such as leadership and communication. Therefore, simulation-based training has been adopted to instill clinical knowledge through immersive experiences. Despite simulation-based training's effectiveness, training opportunities are lessened due to high costs. This is where screen-based simulators come into the scene as affordable and realistic alternatives. Aim: This article evaluates the educational efficacy of ECMOjo, an open-source screen-based extracorporeal membrane oxygenation simulator that aims to replace extracorporeal membrane oxygenation didactic instruction in an interactive and cost-effective manner. Method: A prospective cohort skills acquisition study was carried out. A total of 44 participants were pre-assessed, divided into two groups, where the first group received traditional didactic teaching, and the second used ECMOjo. Participants were then evaluated through a wet lab assessment and two questionnaires. Results: The obtained results indicate that the two assessed groups show no statistically significant differences in knowledge and efficacy. Hence, ECMOjo is considered an alternative to didactic teaching as per the learning outcomes. Conclusion: The present findings show no significant dissimilarities between ECMOjo and didactic classroom-based teaching. Both methods are very comparable in terms of the learner's reported self-efficacy and complementary to mannequin-based simulations. The Author(s) 2019.
    DOI/handle
    http://dx.doi.org/10.1177/0267659119859120
    http://hdl.handle.net/10576/37829
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    • Computer Science & Engineering [‎2428‎ items ]
    • Electrical Engineering [‎2822‎ items ]

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